Annotation of imach/src/imach.c, revision 1.364
1.364 ! brouard 1: /* $Id: imach.c,v 1.363 2024/06/28 09:31:55 brouard Exp $
1.126 brouard 2: $State: Exp $
1.360 brouard 3: $Log: imach.c,v $
1.364 ! brouard 4: Revision 1.363 2024/06/28 09:31:55 brouard
! 5: Summary: Adding log lines too
! 6:
1.363 brouard 7: Revision 1.362 2024/06/28 08:00:31 brouard
8: Summary: 0.99s6
9:
10: * imach.c (Module): s6 errors with age*age (harmless).
11:
1.362 brouard 12: Revision 1.361 2024/05/12 20:29:32 brouard
13: Summary: Version 0.99s5
14:
15: * src/imach.c Version 0.99s5 In fact, the covariance of total life
16: expectancy e.. with a partial life expectancy e.j is high,
17: therefore the complete matrix of variance covariance has to be
18: included in the formula of the standard error of the proportion of
19: total life expectancy spent in a specific state:
20: var(X/Y)=mu_x^2/mu_y^2*(sigma_x^2/mu_x^2 -2
21: sigma_xy/mu_x/mu_y+sigma^2/mu_y^2). Also an error with mle=-3
22: made the program core dump. It is fixed in this version.
23:
1.361 brouard 24: Revision 1.360 2024/04/30 10:59:22 brouard
25: Summary: Version 0.99s4 and estimation of std of e.j/e..
26:
1.360 brouard 27: Revision 1.359 2024/04/24 21:21:17 brouard
28: Summary: First IMaCh version using Brent Praxis software based on Buckhardt and Gegenfürtner C codes
29:
1.359 brouard 30: Revision 1.6 2024/04/24 21:10:29 brouard
31: Summary: First IMaCh version using Brent Praxis software based on Buckhardt and Gegenfürtner C codes
1.358 brouard 32:
1.359 brouard 33: Revision 1.5 2023/10/09 09:10:01 brouard
34: Summary: trying to reconsider
1.357 brouard 35:
1.359 brouard 36: Revision 1.4 2023/06/22 12:50:51 brouard
37: Summary: stil on going
1.357 brouard 38:
1.359 brouard 39: Revision 1.3 2023/06/22 11:28:07 brouard
40: *** empty log message ***
1.356 brouard 41:
1.359 brouard 42: Revision 1.2 2023/06/22 11:22:40 brouard
43: Summary: with svd but not working yet
1.355 brouard 44:
1.354 brouard 45: Revision 1.353 2023/05/08 18:48:22 brouard
46: *** empty log message ***
47:
1.353 brouard 48: Revision 1.352 2023/04/29 10:46:21 brouard
49: *** empty log message ***
50:
1.352 brouard 51: Revision 1.351 2023/04/29 10:43:47 brouard
52: Summary: 099r45
53:
1.351 brouard 54: Revision 1.350 2023/04/24 11:38:06 brouard
55: *** empty log message ***
56:
1.350 brouard 57: Revision 1.349 2023/01/31 09:19:37 brouard
58: Summary: Improvements in models with age*Vn*Vm
59:
1.348 brouard 60: Revision 1.347 2022/09/18 14:36:44 brouard
61: Summary: version 0.99r42
62:
1.347 brouard 63: Revision 1.346 2022/09/16 13:52:36 brouard
64: * src/imach.c (Module): 0.99r41 Was an error when product of timevarying and fixed. Using FixedV[of name] now. Thank you Feinuo
65:
1.346 brouard 66: Revision 1.345 2022/09/16 13:40:11 brouard
67: Summary: Version 0.99r41
68:
69: * imach.c (Module): 0.99r41 Was an error when product of timevarying and fixed. Using FixedV[of name] now. Thank you Feinuo
70:
1.345 brouard 71: Revision 1.344 2022/09/14 19:33:30 brouard
72: Summary: version 0.99r40
73:
74: * imach.c (Module): Fixing names of variables in T_ (thanks to Feinuo)
75:
1.344 brouard 76: Revision 1.343 2022/09/14 14:22:16 brouard
77: Summary: version 0.99r39
78:
79: * imach.c (Module): Version 0.99r39 with colored dummy covariates
80: (fixed or time varying), using new last columns of
81: ILK_parameter.txt file.
82:
1.343 brouard 83: Revision 1.342 2022/09/11 19:54:09 brouard
84: Summary: 0.99r38
85:
86: * imach.c (Module): Adding timevarying products of any kinds,
87: should work before shifting cotvar from ncovcol+nqv columns in
88: order to have a correspondance between the column of cotvar and
89: the id of column.
90: (Module): Some cleaning and adding covariates in ILK.txt
91:
1.342 brouard 92: Revision 1.341 2022/09/11 07:58:42 brouard
93: Summary: Version 0.99r38
94:
95: After adding change in cotvar.
96:
1.341 brouard 97: Revision 1.340 2022/09/11 07:53:11 brouard
98: Summary: Version imach 0.99r37
99:
100: * imach.c (Module): Adding timevarying products of any kinds,
101: should work before shifting cotvar from ncovcol+nqv columns in
102: order to have a correspondance between the column of cotvar and
103: the id of column.
104:
1.340 brouard 105: Revision 1.339 2022/09/09 17:55:22 brouard
106: Summary: version 0.99r37
107:
108: * imach.c (Module): Many improvements for fixing products of fixed
109: timevarying as well as fixed * fixed, and test with quantitative
110: covariate.
111:
1.339 brouard 112: Revision 1.338 2022/09/04 17:40:33 brouard
113: Summary: 0.99r36
114:
115: * imach.c (Module): Now the easy runs i.e. without result or
116: model=1+age only did not work. The defautl combination should be 1
117: and not 0 because everything hasn't been tranformed yet.
118:
1.338 brouard 119: Revision 1.337 2022/09/02 14:26:02 brouard
120: Summary: version 0.99r35
121:
122: * src/imach.c: Version 0.99r35 because it outputs same results with
123: 1+age+V1+V1*age for females and 1+age for females only
124: (education=1 noweight)
125:
1.337 brouard 126: Revision 1.336 2022/08/31 09:52:36 brouard
127: *** empty log message ***
128:
1.336 brouard 129: Revision 1.335 2022/08/31 08:23:16 brouard
130: Summary: improvements...
131:
1.335 brouard 132: Revision 1.334 2022/08/25 09:08:41 brouard
133: Summary: In progress for quantitative
134:
1.334 brouard 135: Revision 1.333 2022/08/21 09:10:30 brouard
136: * src/imach.c (Module): Version 0.99r33 A lot of changes in
137: reassigning covariates: my first idea was that people will always
138: use the first covariate V1 into the model but in fact they are
139: producing data with many covariates and can use an equation model
140: with some of the covariate; it means that in a model V2+V3 instead
141: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
142: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
143: the equation model is restricted to two variables only (V2, V3)
144: and the combination for V2 should be codtabm(k,1) instead of
145: (codtabm(k,2), and the code should be
146: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
147: made. All of these should be simplified once a day like we did in
148: hpxij() for example by using precov[nres] which is computed in
149: decoderesult for each nres of each resultline. Loop should be done
150: on the equation model globally by distinguishing only product with
151: age (which are changing with age) and no more on type of
152: covariates, single dummies, single covariates.
153:
1.333 brouard 154: Revision 1.332 2022/08/21 09:06:25 brouard
155: Summary: Version 0.99r33
156:
157: * src/imach.c (Module): Version 0.99r33 A lot of changes in
158: reassigning covariates: my first idea was that people will always
159: use the first covariate V1 into the model but in fact they are
160: producing data with many covariates and can use an equation model
161: with some of the covariate; it means that in a model V2+V3 instead
162: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
163: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
164: the equation model is restricted to two variables only (V2, V3)
165: and the combination for V2 should be codtabm(k,1) instead of
166: (codtabm(k,2), and the code should be
167: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
168: made. All of these should be simplified once a day like we did in
169: hpxij() for example by using precov[nres] which is computed in
170: decoderesult for each nres of each resultline. Loop should be done
171: on the equation model globally by distinguishing only product with
172: age (which are changing with age) and no more on type of
173: covariates, single dummies, single covariates.
174:
1.332 brouard 175: Revision 1.331 2022/08/07 05:40:09 brouard
176: *** empty log message ***
177:
1.331 brouard 178: Revision 1.330 2022/08/06 07:18:25 brouard
179: Summary: last 0.99r31
180:
181: * imach.c (Module): Version of imach using partly decoderesult to rebuild xpxij function
182:
1.330 brouard 183: Revision 1.329 2022/08/03 17:29:54 brouard
184: * imach.c (Module): Many errors in graphs fixed with Vn*age covariates.
185:
1.329 brouard 186: Revision 1.328 2022/07/27 17:40:48 brouard
187: Summary: valgrind bug fixed by initializing to zero DummyV as well as Tage
188:
1.328 brouard 189: Revision 1.327 2022/07/27 14:47:35 brouard
190: Summary: Still a problem for one-step probabilities in case of quantitative variables
191:
1.327 brouard 192: Revision 1.326 2022/07/26 17:33:55 brouard
193: Summary: some test with nres=1
194:
1.326 brouard 195: Revision 1.325 2022/07/25 14:27:23 brouard
196: Summary: r30
197:
198: * imach.c (Module): Error cptcovn instead of nsd in bmij (was
199: coredumped, revealed by Feiuno, thank you.
200:
1.325 brouard 201: Revision 1.324 2022/07/23 17:44:26 brouard
202: *** empty log message ***
203:
1.324 brouard 204: Revision 1.323 2022/07/22 12:30:08 brouard
205: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
206:
1.323 brouard 207: Revision 1.322 2022/07/22 12:27:48 brouard
208: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
209:
1.322 brouard 210: Revision 1.321 2022/07/22 12:04:24 brouard
211: Summary: r28
212:
213: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
214:
1.321 brouard 215: Revision 1.320 2022/06/02 05:10:11 brouard
216: *** empty log message ***
217:
1.320 brouard 218: Revision 1.319 2022/06/02 04:45:11 brouard
219: * imach.c (Module): Adding the Wald tests from the log to the main
220: htm for better display of the maximum likelihood estimators.
221:
1.319 brouard 222: Revision 1.318 2022/05/24 08:10:59 brouard
223: * imach.c (Module): Some attempts to find a bug of wrong estimates
224: of confidencce intervals with product in the equation modelC
225:
1.318 brouard 226: Revision 1.317 2022/05/15 15:06:23 brouard
227: * imach.c (Module): Some minor improvements
228:
1.317 brouard 229: Revision 1.316 2022/05/11 15:11:31 brouard
230: Summary: r27
231:
1.316 brouard 232: Revision 1.315 2022/05/11 15:06:32 brouard
233: *** empty log message ***
234:
1.315 brouard 235: Revision 1.314 2022/04/13 17:43:09 brouard
236: * imach.c (Module): Adding link to text data files
237:
1.314 brouard 238: Revision 1.313 2022/04/11 15:57:42 brouard
239: * imach.c (Module): Error in rewriting the 'r' file with yearsfproj or yearsbproj fixed
240:
1.313 brouard 241: Revision 1.312 2022/04/05 21:24:39 brouard
242: *** empty log message ***
243:
1.312 brouard 244: Revision 1.311 2022/04/05 21:03:51 brouard
245: Summary: Fixed quantitative covariates
246:
247: Fixed covariates (dummy or quantitative)
248: with missing values have never been allowed but are ERRORS and
249: program quits. Standard deviations of fixed covariates were
250: wrongly computed. Mean and standard deviations of time varying
251: covariates are still not computed.
252:
1.311 brouard 253: Revision 1.310 2022/03/17 08:45:53 brouard
254: Summary: 99r25
255:
256: Improving detection of errors: result lines should be compatible with
257: the model.
258:
1.310 brouard 259: Revision 1.309 2021/05/20 12:39:14 brouard
260: Summary: Version 0.99r24
261:
1.309 brouard 262: Revision 1.308 2021/03/31 13:11:57 brouard
263: Summary: Version 0.99r23
264:
265:
266: * imach.c (Module): Still bugs in the result loop. Thank to Holly Benett
267:
1.308 brouard 268: Revision 1.307 2021/03/08 18:11:32 brouard
269: Summary: 0.99r22 fixed bug on result:
270:
1.307 brouard 271: Revision 1.306 2021/02/20 15:44:02 brouard
272: Summary: Version 0.99r21
273:
274: * imach.c (Module): Fix bug on quitting after result lines!
275: (Module): Version 0.99r21
276:
1.306 brouard 277: Revision 1.305 2021/02/20 15:28:30 brouard
278: * imach.c (Module): Fix bug on quitting after result lines!
279:
1.305 brouard 280: Revision 1.304 2021/02/12 11:34:20 brouard
281: * imach.c (Module): The use of a Windows BOM (huge) file is now an error
282:
1.304 brouard 283: Revision 1.303 2021/02/11 19:50:15 brouard
284: * (Module): imach.c Someone entered 'results:' instead of 'result:'. Now it is an error which is printed.
285:
1.303 brouard 286: Revision 1.302 2020/02/22 21:00:05 brouard
287: * (Module): imach.c Update mle=-3 (for computing Life expectancy
288: and life table from the data without any state)
289:
1.302 brouard 290: Revision 1.301 2019/06/04 13:51:20 brouard
291: Summary: Error in 'r'parameter file backcast yearsbproj instead of yearsfproj
292:
1.301 brouard 293: Revision 1.300 2019/05/22 19:09:45 brouard
294: Summary: version 0.99r19 of May 2019
295:
1.300 brouard 296: Revision 1.299 2019/05/22 18:37:08 brouard
297: Summary: Cleaned 0.99r19
298:
1.299 brouard 299: Revision 1.298 2019/05/22 18:19:56 brouard
300: *** empty log message ***
301:
1.298 brouard 302: Revision 1.297 2019/05/22 17:56:10 brouard
303: Summary: Fix bug by moving date2dmy and nhstepm which gaefin=-1
304:
1.297 brouard 305: Revision 1.296 2019/05/20 13:03:18 brouard
306: Summary: Projection syntax simplified
307:
308:
309: We can now start projections, forward or backward, from the mean date
310: of inteviews up to or down to a number of years of projection:
311: prevforecast=1 yearsfproj=15.3 mobil_average=0
312: or
313: prevforecast=1 starting-proj-date=1/1/2007 final-proj-date=12/31/2017 mobil_average=0
314: or
315: prevbackcast=1 yearsbproj=12.3 mobil_average=1
316: or
317: prevbackcast=1 starting-back-date=1/10/1999 final-back-date=1/1/1985 mobil_average=1
318:
1.296 brouard 319: Revision 1.295 2019/05/18 09:52:50 brouard
320: Summary: doxygen tex bug
321:
1.295 brouard 322: Revision 1.294 2019/05/16 14:54:33 brouard
323: Summary: There was some wrong lines added
324:
1.294 brouard 325: Revision 1.293 2019/05/09 15:17:34 brouard
326: *** empty log message ***
327:
1.293 brouard 328: Revision 1.292 2019/05/09 14:17:20 brouard
329: Summary: Some updates
330:
1.292 brouard 331: Revision 1.291 2019/05/09 13:44:18 brouard
332: Summary: Before ncovmax
333:
1.291 brouard 334: Revision 1.290 2019/05/09 13:39:37 brouard
335: Summary: 0.99r18 unlimited number of individuals
336:
337: The number n which was limited to 20,000 cases is now unlimited, from firstobs to lastobs. If the number is too for the virtual memory, probably an error will occur.
338:
1.290 brouard 339: Revision 1.289 2018/12/13 09:16:26 brouard
340: Summary: Bug for young ages (<-30) will be in r17
341:
1.289 brouard 342: Revision 1.288 2018/05/02 20:58:27 brouard
343: Summary: Some bugs fixed
344:
1.288 brouard 345: Revision 1.287 2018/05/01 17:57:25 brouard
346: Summary: Bug fixed by providing frequencies only for non missing covariates
347:
1.287 brouard 348: Revision 1.286 2018/04/27 14:27:04 brouard
349: Summary: some minor bugs
350:
1.286 brouard 351: Revision 1.285 2018/04/21 21:02:16 brouard
352: Summary: Some bugs fixed, valgrind tested
353:
1.285 brouard 354: Revision 1.284 2018/04/20 05:22:13 brouard
355: Summary: Computing mean and stdeviation of fixed quantitative variables
356:
1.284 brouard 357: Revision 1.283 2018/04/19 14:49:16 brouard
358: Summary: Some minor bugs fixed
359:
1.283 brouard 360: Revision 1.282 2018/02/27 22:50:02 brouard
361: *** empty log message ***
362:
1.282 brouard 363: Revision 1.281 2018/02/27 19:25:23 brouard
364: Summary: Adding second argument for quitting
365:
1.281 brouard 366: Revision 1.280 2018/02/21 07:58:13 brouard
367: Summary: 0.99r15
368:
369: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
370:
1.280 brouard 371: Revision 1.279 2017/07/20 13:35:01 brouard
372: Summary: temporary working
373:
1.279 brouard 374: Revision 1.278 2017/07/19 14:09:02 brouard
375: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
376:
1.278 brouard 377: Revision 1.277 2017/07/17 08:53:49 brouard
378: Summary: BOM files can be read now
379:
1.277 brouard 380: Revision 1.276 2017/06/30 15:48:31 brouard
381: Summary: Graphs improvements
382:
1.276 brouard 383: Revision 1.275 2017/06/30 13:39:33 brouard
384: Summary: Saito's color
385:
1.275 brouard 386: Revision 1.274 2017/06/29 09:47:08 brouard
387: Summary: Version 0.99r14
388:
1.274 brouard 389: Revision 1.273 2017/06/27 11:06:02 brouard
390: Summary: More documentation on projections
391:
1.273 brouard 392: Revision 1.272 2017/06/27 10:22:40 brouard
393: Summary: Color of backprojection changed from 6 to 5(yellow)
394:
1.272 brouard 395: Revision 1.271 2017/06/27 10:17:50 brouard
396: Summary: Some bug with rint
397:
1.271 brouard 398: Revision 1.270 2017/05/24 05:45:29 brouard
399: *** empty log message ***
400:
1.270 brouard 401: Revision 1.269 2017/05/23 08:39:25 brouard
402: Summary: Code into subroutine, cleanings
403:
1.269 brouard 404: Revision 1.268 2017/05/18 20:09:32 brouard
405: Summary: backprojection and confidence intervals of backprevalence
406:
1.268 brouard 407: Revision 1.267 2017/05/13 10:25:05 brouard
408: Summary: temporary save for backprojection
409:
1.267 brouard 410: Revision 1.266 2017/05/13 07:26:12 brouard
411: Summary: Version 0.99r13 (improvements and bugs fixed)
412:
1.266 brouard 413: Revision 1.265 2017/04/26 16:22:11 brouard
414: Summary: imach 0.99r13 Some bugs fixed
415:
1.265 brouard 416: Revision 1.264 2017/04/26 06:01:29 brouard
417: Summary: Labels in graphs
418:
1.264 brouard 419: Revision 1.263 2017/04/24 15:23:15 brouard
420: Summary: to save
421:
1.263 brouard 422: Revision 1.262 2017/04/18 16:48:12 brouard
423: *** empty log message ***
424:
1.262 brouard 425: Revision 1.261 2017/04/05 10:14:09 brouard
426: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
427:
1.261 brouard 428: Revision 1.260 2017/04/04 17:46:59 brouard
429: Summary: Gnuplot indexations fixed (humm)
430:
1.260 brouard 431: Revision 1.259 2017/04/04 13:01:16 brouard
432: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
433:
1.259 brouard 434: Revision 1.258 2017/04/03 10:17:47 brouard
435: Summary: Version 0.99r12
436:
437: Some cleanings, conformed with updated documentation.
438:
1.258 brouard 439: Revision 1.257 2017/03/29 16:53:30 brouard
440: Summary: Temp
441:
1.257 brouard 442: Revision 1.256 2017/03/27 05:50:23 brouard
443: Summary: Temporary
444:
1.256 brouard 445: Revision 1.255 2017/03/08 16:02:28 brouard
446: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
447:
1.255 brouard 448: Revision 1.254 2017/03/08 07:13:00 brouard
449: Summary: Fixing data parameter line
450:
1.254 brouard 451: Revision 1.253 2016/12/15 11:59:41 brouard
452: Summary: 0.99 in progress
453:
1.253 brouard 454: Revision 1.252 2016/09/15 21:15:37 brouard
455: *** empty log message ***
456:
1.252 brouard 457: Revision 1.251 2016/09/15 15:01:13 brouard
458: Summary: not working
459:
1.251 brouard 460: Revision 1.250 2016/09/08 16:07:27 brouard
461: Summary: continue
462:
1.250 brouard 463: Revision 1.249 2016/09/07 17:14:18 brouard
464: Summary: Starting values from frequencies
465:
1.249 brouard 466: Revision 1.248 2016/09/07 14:10:18 brouard
467: *** empty log message ***
468:
1.248 brouard 469: Revision 1.247 2016/09/02 11:11:21 brouard
470: *** empty log message ***
471:
1.247 brouard 472: Revision 1.246 2016/09/02 08:49:22 brouard
473: *** empty log message ***
474:
1.246 brouard 475: Revision 1.245 2016/09/02 07:25:01 brouard
476: *** empty log message ***
477:
1.245 brouard 478: Revision 1.244 2016/09/02 07:17:34 brouard
479: *** empty log message ***
480:
1.244 brouard 481: Revision 1.243 2016/09/02 06:45:35 brouard
482: *** empty log message ***
483:
1.243 brouard 484: Revision 1.242 2016/08/30 15:01:20 brouard
485: Summary: Fixing a lots
486:
1.242 brouard 487: Revision 1.241 2016/08/29 17:17:25 brouard
488: Summary: gnuplot problem in Back projection to fix
489:
1.241 brouard 490: Revision 1.240 2016/08/29 07:53:18 brouard
491: Summary: Better
492:
1.240 brouard 493: Revision 1.239 2016/08/26 15:51:03 brouard
494: Summary: Improvement in Powell output in order to copy and paste
495:
496: Author:
497:
1.239 brouard 498: Revision 1.238 2016/08/26 14:23:35 brouard
499: Summary: Starting tests of 0.99
500:
1.238 brouard 501: Revision 1.237 2016/08/26 09:20:19 brouard
502: Summary: to valgrind
503:
1.237 brouard 504: Revision 1.236 2016/08/25 10:50:18 brouard
505: *** empty log message ***
506:
1.236 brouard 507: Revision 1.235 2016/08/25 06:59:23 brouard
508: *** empty log message ***
509:
1.235 brouard 510: Revision 1.234 2016/08/23 16:51:20 brouard
511: *** empty log message ***
512:
1.234 brouard 513: Revision 1.233 2016/08/23 07:40:50 brouard
514: Summary: not working
515:
1.233 brouard 516: Revision 1.232 2016/08/22 14:20:21 brouard
517: Summary: not working
518:
1.232 brouard 519: Revision 1.231 2016/08/22 07:17:15 brouard
520: Summary: not working
521:
1.231 brouard 522: Revision 1.230 2016/08/22 06:55:53 brouard
523: Summary: Not working
524:
1.230 brouard 525: Revision 1.229 2016/07/23 09:45:53 brouard
526: Summary: Completing for func too
527:
1.229 brouard 528: Revision 1.228 2016/07/22 17:45:30 brouard
529: Summary: Fixing some arrays, still debugging
530:
1.227 brouard 531: Revision 1.226 2016/07/12 18:42:34 brouard
532: Summary: temp
533:
1.226 brouard 534: Revision 1.225 2016/07/12 08:40:03 brouard
535: Summary: saving but not running
536:
1.225 brouard 537: Revision 1.224 2016/07/01 13:16:01 brouard
538: Summary: Fixes
539:
1.224 brouard 540: Revision 1.223 2016/02/19 09:23:35 brouard
541: Summary: temporary
542:
1.223 brouard 543: Revision 1.222 2016/02/17 08:14:50 brouard
544: Summary: Probably last 0.98 stable version 0.98r6
545:
1.222 brouard 546: Revision 1.221 2016/02/15 23:35:36 brouard
547: Summary: minor bug
548:
1.220 brouard 549: Revision 1.219 2016/02/15 00:48:12 brouard
550: *** empty log message ***
551:
1.219 brouard 552: Revision 1.218 2016/02/12 11:29:23 brouard
553: Summary: 0.99 Back projections
554:
1.218 brouard 555: Revision 1.217 2015/12/23 17:18:31 brouard
556: Summary: Experimental backcast
557:
1.217 brouard 558: Revision 1.216 2015/12/18 17:32:11 brouard
559: Summary: 0.98r4 Warning and status=-2
560:
561: Version 0.98r4 is now:
562: - displaying an error when status is -1, date of interview unknown and date of death known;
563: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
564: Older changes concerning s=-2, dating from 2005 have been supersed.
565:
1.216 brouard 566: Revision 1.215 2015/12/16 08:52:24 brouard
567: Summary: 0.98r4 working
568:
1.215 brouard 569: Revision 1.214 2015/12/16 06:57:54 brouard
570: Summary: temporary not working
571:
1.214 brouard 572: Revision 1.213 2015/12/11 18:22:17 brouard
573: Summary: 0.98r4
574:
1.213 brouard 575: Revision 1.212 2015/11/21 12:47:24 brouard
576: Summary: minor typo
577:
1.212 brouard 578: Revision 1.211 2015/11/21 12:41:11 brouard
579: Summary: 0.98r3 with some graph of projected cross-sectional
580:
581: Author: Nicolas Brouard
582:
1.211 brouard 583: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 584: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 585: Summary: Adding ftolpl parameter
586: Author: N Brouard
587:
588: We had difficulties to get smoothed confidence intervals. It was due
589: to the period prevalence which wasn't computed accurately. The inner
590: parameter ftolpl is now an outer parameter of the .imach parameter
591: file after estepm. If ftolpl is small 1.e-4 and estepm too,
592: computation are long.
593:
1.209 brouard 594: Revision 1.208 2015/11/17 14:31:57 brouard
595: Summary: temporary
596:
1.208 brouard 597: Revision 1.207 2015/10/27 17:36:57 brouard
598: *** empty log message ***
599:
1.207 brouard 600: Revision 1.206 2015/10/24 07:14:11 brouard
601: *** empty log message ***
602:
1.206 brouard 603: Revision 1.205 2015/10/23 15:50:53 brouard
604: Summary: 0.98r3 some clarification for graphs on likelihood contributions
605:
1.205 brouard 606: Revision 1.204 2015/10/01 16:20:26 brouard
607: Summary: Some new graphs of contribution to likelihood
608:
1.204 brouard 609: Revision 1.203 2015/09/30 17:45:14 brouard
610: Summary: looking at better estimation of the hessian
611:
612: Also a better criteria for convergence to the period prevalence And
613: therefore adding the number of years needed to converge. (The
614: prevalence in any alive state shold sum to one
615:
1.203 brouard 616: Revision 1.202 2015/09/22 19:45:16 brouard
617: Summary: Adding some overall graph on contribution to likelihood. Might change
618:
1.202 brouard 619: Revision 1.201 2015/09/15 17:34:58 brouard
620: Summary: 0.98r0
621:
622: - Some new graphs like suvival functions
623: - Some bugs fixed like model=1+age+V2.
624:
1.201 brouard 625: Revision 1.200 2015/09/09 16:53:55 brouard
626: Summary: Big bug thanks to Flavia
627:
628: Even model=1+age+V2. did not work anymore
629:
1.200 brouard 630: Revision 1.199 2015/09/07 14:09:23 brouard
631: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
632:
1.199 brouard 633: Revision 1.198 2015/09/03 07:14:39 brouard
634: Summary: 0.98q5 Flavia
635:
1.198 brouard 636: Revision 1.197 2015/09/01 18:24:39 brouard
637: *** empty log message ***
638:
1.197 brouard 639: Revision 1.196 2015/08/18 23:17:52 brouard
640: Summary: 0.98q5
641:
1.196 brouard 642: Revision 1.195 2015/08/18 16:28:39 brouard
643: Summary: Adding a hack for testing purpose
644:
645: After reading the title, ftol and model lines, if the comment line has
646: a q, starting with #q, the answer at the end of the run is quit. It
647: permits to run test files in batch with ctest. The former workaround was
648: $ echo q | imach foo.imach
649:
1.195 brouard 650: Revision 1.194 2015/08/18 13:32:00 brouard
651: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
652:
1.194 brouard 653: Revision 1.193 2015/08/04 07:17:42 brouard
654: Summary: 0.98q4
655:
1.193 brouard 656: Revision 1.192 2015/07/16 16:49:02 brouard
657: Summary: Fixing some outputs
658:
1.192 brouard 659: Revision 1.191 2015/07/14 10:00:33 brouard
660: Summary: Some fixes
661:
1.191 brouard 662: Revision 1.190 2015/05/05 08:51:13 brouard
663: Summary: Adding digits in output parameters (7 digits instead of 6)
664:
665: Fix 1+age+.
666:
1.190 brouard 667: Revision 1.189 2015/04/30 14:45:16 brouard
668: Summary: 0.98q2
669:
1.189 brouard 670: Revision 1.188 2015/04/30 08:27:53 brouard
671: *** empty log message ***
672:
1.188 brouard 673: Revision 1.187 2015/04/29 09:11:15 brouard
674: *** empty log message ***
675:
1.187 brouard 676: Revision 1.186 2015/04/23 12:01:52 brouard
677: Summary: V1*age is working now, version 0.98q1
678:
679: Some codes had been disabled in order to simplify and Vn*age was
680: working in the optimization phase, ie, giving correct MLE parameters,
681: but, as usual, outputs were not correct and program core dumped.
682:
1.186 brouard 683: Revision 1.185 2015/03/11 13:26:42 brouard
684: Summary: Inclusion of compile and links command line for Intel Compiler
685:
1.185 brouard 686: Revision 1.184 2015/03/11 11:52:39 brouard
687: Summary: Back from Windows 8. Intel Compiler
688:
1.184 brouard 689: Revision 1.183 2015/03/10 20:34:32 brouard
690: Summary: 0.98q0, trying with directest, mnbrak fixed
691:
692: We use directest instead of original Powell test; probably no
693: incidence on the results, but better justifications;
694: We fixed Numerical Recipes mnbrak routine which was wrong and gave
695: wrong results.
696:
1.183 brouard 697: Revision 1.182 2015/02/12 08:19:57 brouard
698: Summary: Trying to keep directest which seems simpler and more general
699: Author: Nicolas Brouard
700:
1.182 brouard 701: Revision 1.181 2015/02/11 23:22:24 brouard
702: Summary: Comments on Powell added
703:
704: Author:
705:
1.181 brouard 706: Revision 1.180 2015/02/11 17:33:45 brouard
707: Summary: Finishing move from main to function (hpijx and prevalence_limit)
708:
1.180 brouard 709: Revision 1.179 2015/01/04 09:57:06 brouard
710: Summary: back to OS/X
711:
1.179 brouard 712: Revision 1.178 2015/01/04 09:35:48 brouard
713: *** empty log message ***
714:
1.178 brouard 715: Revision 1.177 2015/01/03 18:40:56 brouard
716: Summary: Still testing ilc32 on OSX
717:
1.177 brouard 718: Revision 1.176 2015/01/03 16:45:04 brouard
719: *** empty log message ***
720:
1.176 brouard 721: Revision 1.175 2015/01/03 16:33:42 brouard
722: *** empty log message ***
723:
1.175 brouard 724: Revision 1.174 2015/01/03 16:15:49 brouard
725: Summary: Still in cross-compilation
726:
1.174 brouard 727: Revision 1.173 2015/01/03 12:06:26 brouard
728: Summary: trying to detect cross-compilation
729:
1.173 brouard 730: Revision 1.172 2014/12/27 12:07:47 brouard
731: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
732:
1.172 brouard 733: Revision 1.171 2014/12/23 13:26:59 brouard
734: Summary: Back from Visual C
735:
736: Still problem with utsname.h on Windows
737:
1.171 brouard 738: Revision 1.170 2014/12/23 11:17:12 brouard
739: Summary: Cleaning some \%% back to %%
740:
741: The escape was mandatory for a specific compiler (which one?), but too many warnings.
742:
1.170 brouard 743: Revision 1.169 2014/12/22 23:08:31 brouard
744: Summary: 0.98p
745:
746: Outputs some informations on compiler used, OS etc. Testing on different platforms.
747:
1.169 brouard 748: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 749: Summary: update
1.169 brouard 750:
1.168 brouard 751: Revision 1.167 2014/12/22 13:50:56 brouard
752: Summary: Testing uname and compiler version and if compiled 32 or 64
753:
754: Testing on Linux 64
755:
1.167 brouard 756: Revision 1.166 2014/12/22 11:40:47 brouard
757: *** empty log message ***
758:
1.166 brouard 759: Revision 1.165 2014/12/16 11:20:36 brouard
760: Summary: After compiling on Visual C
761:
762: * imach.c (Module): Merging 1.61 to 1.162
763:
1.165 brouard 764: Revision 1.164 2014/12/16 10:52:11 brouard
765: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
766:
767: * imach.c (Module): Merging 1.61 to 1.162
768:
1.164 brouard 769: Revision 1.163 2014/12/16 10:30:11 brouard
770: * imach.c (Module): Merging 1.61 to 1.162
771:
1.163 brouard 772: Revision 1.162 2014/09/25 11:43:39 brouard
773: Summary: temporary backup 0.99!
774:
1.162 brouard 775: Revision 1.1 2014/09/16 11:06:58 brouard
776: Summary: With some code (wrong) for nlopt
777:
778: Author:
779:
780: Revision 1.161 2014/09/15 20:41:41 brouard
781: Summary: Problem with macro SQR on Intel compiler
782:
1.161 brouard 783: Revision 1.160 2014/09/02 09:24:05 brouard
784: *** empty log message ***
785:
1.160 brouard 786: Revision 1.159 2014/09/01 10:34:10 brouard
787: Summary: WIN32
788: Author: Brouard
789:
1.159 brouard 790: Revision 1.158 2014/08/27 17:11:51 brouard
791: *** empty log message ***
792:
1.158 brouard 793: Revision 1.157 2014/08/27 16:26:55 brouard
794: Summary: Preparing windows Visual studio version
795: Author: Brouard
796:
797: In order to compile on Visual studio, time.h is now correct and time_t
798: and tm struct should be used. difftime should be used but sometimes I
799: just make the differences in raw time format (time(&now).
800: Trying to suppress #ifdef LINUX
801: Add xdg-open for __linux in order to open default browser.
802:
1.157 brouard 803: Revision 1.156 2014/08/25 20:10:10 brouard
804: *** empty log message ***
805:
1.156 brouard 806: Revision 1.155 2014/08/25 18:32:34 brouard
807: Summary: New compile, minor changes
808: Author: Brouard
809:
1.155 brouard 810: Revision 1.154 2014/06/20 17:32:08 brouard
811: Summary: Outputs now all graphs of convergence to period prevalence
812:
1.154 brouard 813: Revision 1.153 2014/06/20 16:45:46 brouard
814: Summary: If 3 live state, convergence to period prevalence on same graph
815: Author: Brouard
816:
1.153 brouard 817: Revision 1.152 2014/06/18 17:54:09 brouard
818: Summary: open browser, use gnuplot on same dir than imach if not found in the path
819:
1.152 brouard 820: Revision 1.151 2014/06/18 16:43:30 brouard
821: *** empty log message ***
822:
1.151 brouard 823: Revision 1.150 2014/06/18 16:42:35 brouard
824: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
825: Author: brouard
826:
1.150 brouard 827: Revision 1.149 2014/06/18 15:51:14 brouard
828: Summary: Some fixes in parameter files errors
829: Author: Nicolas Brouard
830:
1.149 brouard 831: Revision 1.148 2014/06/17 17:38:48 brouard
832: Summary: Nothing new
833: Author: Brouard
834:
835: Just a new packaging for OS/X version 0.98nS
836:
1.148 brouard 837: Revision 1.147 2014/06/16 10:33:11 brouard
838: *** empty log message ***
839:
1.147 brouard 840: Revision 1.146 2014/06/16 10:20:28 brouard
841: Summary: Merge
842: Author: Brouard
843:
844: Merge, before building revised version.
845:
1.146 brouard 846: Revision 1.145 2014/06/10 21:23:15 brouard
847: Summary: Debugging with valgrind
848: Author: Nicolas Brouard
849:
850: Lot of changes in order to output the results with some covariates
851: After the Edimburgh REVES conference 2014, it seems mandatory to
852: improve the code.
853: No more memory valgrind error but a lot has to be done in order to
854: continue the work of splitting the code into subroutines.
855: Also, decodemodel has been improved. Tricode is still not
856: optimal. nbcode should be improved. Documentation has been added in
857: the source code.
858:
1.144 brouard 859: Revision 1.143 2014/01/26 09:45:38 brouard
860: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
861:
862: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
863: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
864:
1.143 brouard 865: Revision 1.142 2014/01/26 03:57:36 brouard
866: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
867:
868: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
869:
1.142 brouard 870: Revision 1.141 2014/01/26 02:42:01 brouard
871: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
872:
1.141 brouard 873: Revision 1.140 2011/09/02 10:37:54 brouard
874: Summary: times.h is ok with mingw32 now.
875:
1.140 brouard 876: Revision 1.139 2010/06/14 07:50:17 brouard
877: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
878: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
879:
1.139 brouard 880: Revision 1.138 2010/04/30 18:19:40 brouard
881: *** empty log message ***
882:
1.138 brouard 883: Revision 1.137 2010/04/29 18:11:38 brouard
884: (Module): Checking covariates for more complex models
885: than V1+V2. A lot of change to be done. Unstable.
886:
1.137 brouard 887: Revision 1.136 2010/04/26 20:30:53 brouard
888: (Module): merging some libgsl code. Fixing computation
889: of likelione (using inter/intrapolation if mle = 0) in order to
890: get same likelihood as if mle=1.
891: Some cleaning of code and comments added.
892:
1.136 brouard 893: Revision 1.135 2009/10/29 15:33:14 brouard
894: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
895:
1.135 brouard 896: Revision 1.134 2009/10/29 13:18:53 brouard
897: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
898:
1.134 brouard 899: Revision 1.133 2009/07/06 10:21:25 brouard
900: just nforces
901:
1.133 brouard 902: Revision 1.132 2009/07/06 08:22:05 brouard
903: Many tings
904:
1.132 brouard 905: Revision 1.131 2009/06/20 16:22:47 brouard
906: Some dimensions resccaled
907:
1.131 brouard 908: Revision 1.130 2009/05/26 06:44:34 brouard
909: (Module): Max Covariate is now set to 20 instead of 8. A
910: lot of cleaning with variables initialized to 0. Trying to make
911: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
912:
1.130 brouard 913: Revision 1.129 2007/08/31 13:49:27 lievre
914: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
915:
1.129 lievre 916: Revision 1.128 2006/06/30 13:02:05 brouard
917: (Module): Clarifications on computing e.j
918:
1.128 brouard 919: Revision 1.127 2006/04/28 18:11:50 brouard
920: (Module): Yes the sum of survivors was wrong since
921: imach-114 because nhstepm was no more computed in the age
922: loop. Now we define nhstepma in the age loop.
923: (Module): In order to speed up (in case of numerous covariates) we
924: compute health expectancies (without variances) in a first step
925: and then all the health expectancies with variances or standard
926: deviation (needs data from the Hessian matrices) which slows the
927: computation.
928: In the future we should be able to stop the program is only health
929: expectancies and graph are needed without standard deviations.
930:
1.127 brouard 931: Revision 1.126 2006/04/28 17:23:28 brouard
932: (Module): Yes the sum of survivors was wrong since
933: imach-114 because nhstepm was no more computed in the age
934: loop. Now we define nhstepma in the age loop.
935: Version 0.98h
936:
1.126 brouard 937: Revision 1.125 2006/04/04 15:20:31 lievre
938: Errors in calculation of health expectancies. Age was not initialized.
939: Forecasting file added.
940:
941: Revision 1.124 2006/03/22 17:13:53 lievre
942: Parameters are printed with %lf instead of %f (more numbers after the comma).
943: The log-likelihood is printed in the log file
944:
945: Revision 1.123 2006/03/20 10:52:43 brouard
946: * imach.c (Module): <title> changed, corresponds to .htm file
947: name. <head> headers where missing.
948:
949: * imach.c (Module): Weights can have a decimal point as for
950: English (a comma might work with a correct LC_NUMERIC environment,
951: otherwise the weight is truncated).
952: Modification of warning when the covariates values are not 0 or
953: 1.
954: Version 0.98g
955:
956: Revision 1.122 2006/03/20 09:45:41 brouard
957: (Module): Weights can have a decimal point as for
958: English (a comma might work with a correct LC_NUMERIC environment,
959: otherwise the weight is truncated).
960: Modification of warning when the covariates values are not 0 or
961: 1.
962: Version 0.98g
963:
964: Revision 1.121 2006/03/16 17:45:01 lievre
965: * imach.c (Module): Comments concerning covariates added
966:
967: * imach.c (Module): refinements in the computation of lli if
968: status=-2 in order to have more reliable computation if stepm is
969: not 1 month. Version 0.98f
970:
971: Revision 1.120 2006/03/16 15:10:38 lievre
972: (Module): refinements in the computation of lli if
973: status=-2 in order to have more reliable computation if stepm is
974: not 1 month. Version 0.98f
975:
976: Revision 1.119 2006/03/15 17:42:26 brouard
977: (Module): Bug if status = -2, the loglikelihood was
978: computed as likelihood omitting the logarithm. Version O.98e
979:
980: Revision 1.118 2006/03/14 18:20:07 brouard
981: (Module): varevsij Comments added explaining the second
982: table of variances if popbased=1 .
983: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
984: (Module): Function pstamp added
985: (Module): Version 0.98d
986:
987: Revision 1.117 2006/03/14 17:16:22 brouard
988: (Module): varevsij Comments added explaining the second
989: table of variances if popbased=1 .
990: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
991: (Module): Function pstamp added
992: (Module): Version 0.98d
993:
994: Revision 1.116 2006/03/06 10:29:27 brouard
995: (Module): Variance-covariance wrong links and
996: varian-covariance of ej. is needed (Saito).
997:
998: Revision 1.115 2006/02/27 12:17:45 brouard
999: (Module): One freematrix added in mlikeli! 0.98c
1000:
1001: Revision 1.114 2006/02/26 12:57:58 brouard
1002: (Module): Some improvements in processing parameter
1003: filename with strsep.
1004:
1005: Revision 1.113 2006/02/24 14:20:24 brouard
1006: (Module): Memory leaks checks with valgrind and:
1007: datafile was not closed, some imatrix were not freed and on matrix
1008: allocation too.
1009:
1010: Revision 1.112 2006/01/30 09:55:26 brouard
1011: (Module): Back to gnuplot.exe instead of wgnuplot.exe
1012:
1013: Revision 1.111 2006/01/25 20:38:18 brouard
1014: (Module): Lots of cleaning and bugs added (Gompertz)
1015: (Module): Comments can be added in data file. Missing date values
1016: can be a simple dot '.'.
1017:
1018: Revision 1.110 2006/01/25 00:51:50 brouard
1019: (Module): Lots of cleaning and bugs added (Gompertz)
1020:
1021: Revision 1.109 2006/01/24 19:37:15 brouard
1022: (Module): Comments (lines starting with a #) are allowed in data.
1023:
1024: Revision 1.108 2006/01/19 18:05:42 lievre
1025: Gnuplot problem appeared...
1026: To be fixed
1027:
1028: Revision 1.107 2006/01/19 16:20:37 brouard
1029: Test existence of gnuplot in imach path
1030:
1031: Revision 1.106 2006/01/19 13:24:36 brouard
1032: Some cleaning and links added in html output
1033:
1034: Revision 1.105 2006/01/05 20:23:19 lievre
1035: *** empty log message ***
1036:
1037: Revision 1.104 2005/09/30 16:11:43 lievre
1038: (Module): sump fixed, loop imx fixed, and simplifications.
1039: (Module): If the status is missing at the last wave but we know
1040: that the person is alive, then we can code his/her status as -2
1041: (instead of missing=-1 in earlier versions) and his/her
1042: contributions to the likelihood is 1 - Prob of dying from last
1043: health status (= 1-p13= p11+p12 in the easiest case of somebody in
1044: the healthy state at last known wave). Version is 0.98
1045:
1046: Revision 1.103 2005/09/30 15:54:49 lievre
1047: (Module): sump fixed, loop imx fixed, and simplifications.
1048:
1049: Revision 1.102 2004/09/15 17:31:30 brouard
1050: Add the possibility to read data file including tab characters.
1051:
1052: Revision 1.101 2004/09/15 10:38:38 brouard
1053: Fix on curr_time
1054:
1055: Revision 1.100 2004/07/12 18:29:06 brouard
1056: Add version for Mac OS X. Just define UNIX in Makefile
1057:
1058: Revision 1.99 2004/06/05 08:57:40 brouard
1059: *** empty log message ***
1060:
1061: Revision 1.98 2004/05/16 15:05:56 brouard
1062: New version 0.97 . First attempt to estimate force of mortality
1063: directly from the data i.e. without the need of knowing the health
1064: state at each age, but using a Gompertz model: log u =a + b*age .
1065: This is the basic analysis of mortality and should be done before any
1066: other analysis, in order to test if the mortality estimated from the
1067: cross-longitudinal survey is different from the mortality estimated
1068: from other sources like vital statistic data.
1069:
1070: The same imach parameter file can be used but the option for mle should be -3.
1071:
1.324 brouard 1072: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 1073: former routines in order to include the new code within the former code.
1074:
1075: The output is very simple: only an estimate of the intercept and of
1076: the slope with 95% confident intervals.
1077:
1078: Current limitations:
1079: A) Even if you enter covariates, i.e. with the
1080: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
1081: B) There is no computation of Life Expectancy nor Life Table.
1082:
1083: Revision 1.97 2004/02/20 13:25:42 lievre
1084: Version 0.96d. Population forecasting command line is (temporarily)
1085: suppressed.
1086:
1087: Revision 1.96 2003/07/15 15:38:55 brouard
1088: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
1089: rewritten within the same printf. Workaround: many printfs.
1090:
1091: Revision 1.95 2003/07/08 07:54:34 brouard
1092: * imach.c (Repository):
1093: (Repository): Using imachwizard code to output a more meaningful covariance
1094: matrix (cov(a12,c31) instead of numbers.
1095:
1096: Revision 1.94 2003/06/27 13:00:02 brouard
1097: Just cleaning
1098:
1099: Revision 1.93 2003/06/25 16:33:55 brouard
1100: (Module): On windows (cygwin) function asctime_r doesn't
1101: exist so I changed back to asctime which exists.
1102: (Module): Version 0.96b
1103:
1104: Revision 1.92 2003/06/25 16:30:45 brouard
1105: (Module): On windows (cygwin) function asctime_r doesn't
1106: exist so I changed back to asctime which exists.
1107:
1108: Revision 1.91 2003/06/25 15:30:29 brouard
1109: * imach.c (Repository): Duplicated warning errors corrected.
1110: (Repository): Elapsed time after each iteration is now output. It
1111: helps to forecast when convergence will be reached. Elapsed time
1112: is stamped in powell. We created a new html file for the graphs
1113: concerning matrix of covariance. It has extension -cov.htm.
1114:
1115: Revision 1.90 2003/06/24 12:34:15 brouard
1116: (Module): Some bugs corrected for windows. Also, when
1117: mle=-1 a template is output in file "or"mypar.txt with the design
1118: of the covariance matrix to be input.
1119:
1120: Revision 1.89 2003/06/24 12:30:52 brouard
1121: (Module): Some bugs corrected for windows. Also, when
1122: mle=-1 a template is output in file "or"mypar.txt with the design
1123: of the covariance matrix to be input.
1124:
1125: Revision 1.88 2003/06/23 17:54:56 brouard
1126: * imach.c (Repository): Create a sub-directory where all the secondary files are. Only imach, htm, gp and r(imach) are on the main directory. Correct time and other things.
1127:
1128: Revision 1.87 2003/06/18 12:26:01 brouard
1129: Version 0.96
1130:
1131: Revision 1.86 2003/06/17 20:04:08 brouard
1132: (Module): Change position of html and gnuplot routines and added
1133: routine fileappend.
1134:
1135: Revision 1.85 2003/06/17 13:12:43 brouard
1136: * imach.c (Repository): Check when date of death was earlier that
1137: current date of interview. It may happen when the death was just
1138: prior to the death. In this case, dh was negative and likelihood
1139: was wrong (infinity). We still send an "Error" but patch by
1140: assuming that the date of death was just one stepm after the
1141: interview.
1142: (Repository): Because some people have very long ID (first column)
1143: we changed int to long in num[] and we added a new lvector for
1144: memory allocation. But we also truncated to 8 characters (left
1145: truncation)
1146: (Repository): No more line truncation errors.
1147:
1148: Revision 1.84 2003/06/13 21:44:43 brouard
1149: * imach.c (Repository): Replace "freqsummary" at a correct
1150: place. It differs from routine "prevalence" which may be called
1151: many times. Probs is memory consuming and must be used with
1152: parcimony.
1153: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
1154:
1155: Revision 1.83 2003/06/10 13:39:11 lievre
1156: *** empty log message ***
1157:
1158: Revision 1.82 2003/06/05 15:57:20 brouard
1159: Add log in imach.c and fullversion number is now printed.
1160:
1161: */
1162: /*
1163: Interpolated Markov Chain
1164:
1165: Short summary of the programme:
1166:
1.227 brouard 1167: This program computes Healthy Life Expectancies or State-specific
1168: (if states aren't health statuses) Expectancies from
1169: cross-longitudinal data. Cross-longitudinal data consist in:
1170:
1171: -1- a first survey ("cross") where individuals from different ages
1172: are interviewed on their health status or degree of disability (in
1173: the case of a health survey which is our main interest)
1174:
1175: -2- at least a second wave of interviews ("longitudinal") which
1176: measure each change (if any) in individual health status. Health
1177: expectancies are computed from the time spent in each health state
1178: according to a model. More health states you consider, more time is
1179: necessary to reach the Maximum Likelihood of the parameters involved
1180: in the model. The simplest model is the multinomial logistic model
1181: where pij is the probability to be observed in state j at the second
1182: wave conditional to be observed in state i at the first
1183: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
1184: etc , where 'age' is age and 'sex' is a covariate. If you want to
1185: have a more complex model than "constant and age", you should modify
1186: the program where the markup *Covariates have to be included here
1187: again* invites you to do it. More covariates you add, slower the
1.126 brouard 1188: convergence.
1189:
1190: The advantage of this computer programme, compared to a simple
1191: multinomial logistic model, is clear when the delay between waves is not
1192: identical for each individual. Also, if a individual missed an
1193: intermediate interview, the information is lost, but taken into
1194: account using an interpolation or extrapolation.
1195:
1196: hPijx is the probability to be observed in state i at age x+h
1197: conditional to the observed state i at age x. The delay 'h' can be
1198: split into an exact number (nh*stepm) of unobserved intermediate
1199: states. This elementary transition (by month, quarter,
1200: semester or year) is modelled as a multinomial logistic. The hPx
1201: matrix is simply the matrix product of nh*stepm elementary matrices
1202: and the contribution of each individual to the likelihood is simply
1203: hPijx.
1204:
1205: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 1206: of the life expectancies. It also computes the period (stable) prevalence.
1207:
1208: Back prevalence and projections:
1.227 brouard 1209:
1210: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
1211: double agemaxpar, double ftolpl, int *ncvyearp, double
1212: dateprev1,double dateprev2, int firstpass, int lastpass, int
1213: mobilavproj)
1214:
1215: Computes the back prevalence limit for any combination of
1216: covariate values k at any age between ageminpar and agemaxpar and
1217: returns it in **bprlim. In the loops,
1218:
1219: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
1220: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
1221:
1222: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 1223: Computes for any combination of covariates k and any age between bage and fage
1224: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
1225: oldm=oldms;savm=savms;
1.227 brouard 1226:
1.267 brouard 1227: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 1228: Computes the transition matrix starting at age 'age' over
1229: 'nhstepm*hstepm*stepm' months (i.e. until
1230: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 1231: nhstepm*hstepm matrices.
1232:
1233: Returns p3mat[i][j][h] after calling
1234: p3mat[i][j][h]=matprod2(newm,
1235: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
1236: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
1237: oldm);
1.226 brouard 1238:
1239: Important routines
1240:
1241: - func (or funcone), computes logit (pij) distinguishing
1242: o fixed variables (single or product dummies or quantitative);
1243: o varying variables by:
1244: (1) wave (single, product dummies, quantitative),
1245: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
1246: % fixed dummy (treated) or quantitative (not done because time-consuming);
1247: % varying dummy (not done) or quantitative (not done);
1248: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
1249: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
1250: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
1.364 ! brouard 1251: o There are 2**cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, eliminating 1 1 if
1.226 brouard 1252: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 1253:
1.226 brouard 1254:
1255:
1.324 brouard 1256: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
1257: Institut national d'études démographiques, Paris.
1.126 brouard 1258: This software have been partly granted by Euro-REVES, a concerted action
1259: from the European Union.
1260: It is copyrighted identically to a GNU software product, ie programme and
1261: software can be distributed freely for non commercial use. Latest version
1262: can be accessed at http://euroreves.ined.fr/imach .
1263:
1264: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
1265: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
1266:
1267: **********************************************************************/
1268: /*
1269: main
1270: read parameterfile
1271: read datafile
1272: concatwav
1273: freqsummary
1274: if (mle >= 1)
1275: mlikeli
1276: print results files
1277: if mle==1
1278: computes hessian
1279: read end of parameter file: agemin, agemax, bage, fage, estepm
1280: begin-prev-date,...
1281: open gnuplot file
1282: open html file
1.145 brouard 1283: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
1284: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
1285: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
1286: freexexit2 possible for memory heap.
1287:
1288: h Pij x | pij_nom ficrestpij
1289: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
1290: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
1291: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
1292:
1293: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
1294: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
1295: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
1296: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
1297: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
1298:
1.126 brouard 1299: forecasting if prevfcast==1 prevforecast call prevalence()
1300: health expectancies
1301: Variance-covariance of DFLE
1302: prevalence()
1303: movingaverage()
1304: varevsij()
1305: if popbased==1 varevsij(,popbased)
1306: total life expectancies
1307: Variance of period (stable) prevalence
1308: end
1309: */
1310:
1.187 brouard 1311: /* #define DEBUG */
1312: /* #define DEBUGBRENT */
1.203 brouard 1313: /* #define DEBUGLINMIN */
1314: /* #define DEBUGHESS */
1315: #define DEBUGHESSIJ
1.224 brouard 1316: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 1317: #define POWELL /* Instead of NLOPT */
1.224 brouard 1318: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 1319: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
1320: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.319 brouard 1321: /* #define FLATSUP *//* Suppresses directions where likelihood is flat */
1.359 brouard 1322: /* #define POWELLORIGINCONJUGATE /\* Don't use conjugate but biggest decrease if valuable *\/ */
1323: /* #define NOTMINFIT */
1.126 brouard 1324:
1325: #include <math.h>
1326: #include <stdio.h>
1327: #include <stdlib.h>
1328: #include <string.h>
1.226 brouard 1329: #include <ctype.h>
1.159 brouard 1330:
1331: #ifdef _WIN32
1332: #include <io.h>
1.172 brouard 1333: #include <windows.h>
1334: #include <tchar.h>
1.159 brouard 1335: #else
1.126 brouard 1336: #include <unistd.h>
1.159 brouard 1337: #endif
1.126 brouard 1338:
1339: #include <limits.h>
1340: #include <sys/types.h>
1.171 brouard 1341:
1342: #if defined(__GNUC__)
1343: #include <sys/utsname.h> /* Doesn't work on Windows */
1344: #endif
1345:
1.126 brouard 1346: #include <sys/stat.h>
1347: #include <errno.h>
1.159 brouard 1348: /* extern int errno; */
1.126 brouard 1349:
1.157 brouard 1350: /* #ifdef LINUX */
1351: /* #include <time.h> */
1352: /* #include "timeval.h" */
1353: /* #else */
1354: /* #include <sys/time.h> */
1355: /* #endif */
1356:
1.126 brouard 1357: #include <time.h>
1358:
1.136 brouard 1359: #ifdef GSL
1360: #include <gsl/gsl_errno.h>
1361: #include <gsl/gsl_multimin.h>
1362: #endif
1363:
1.167 brouard 1364:
1.162 brouard 1365: #ifdef NLOPT
1366: #include <nlopt.h>
1367: typedef struct {
1368: double (* function)(double [] );
1369: } myfunc_data ;
1370: #endif
1371:
1.126 brouard 1372: /* #include <libintl.h> */
1373: /* #define _(String) gettext (String) */
1374:
1.349 brouard 1375: #define MAXLINE 16384 /* Was 256 and 1024 and 2048. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1376:
1377: #define GNUPLOTPROGRAM "gnuplot"
1.343 brouard 1378: #define GNUPLOTVERSION 5.1
1379: double gnuplotversion=GNUPLOTVERSION;
1.126 brouard 1380: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1.329 brouard 1381: #define FILENAMELENGTH 256
1.126 brouard 1382:
1383: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1384: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1385:
1.349 brouard 1386: #define MAXPARM 216 /**< Maximum number of parameters for the optimization was 128 */
1.144 brouard 1387: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1388:
1389: #define NINTERVMAX 8
1.144 brouard 1390: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1391: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.325 brouard 1392: #define NCOVMAX 30 /**< Maximum number of covariates used in the model, including generated covariates V1*V2 or V1*age */
1.197 brouard 1393: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1394: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1395: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1396: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1397: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1398: /* #define AGESUP 130 */
1.288 brouard 1399: /* #define AGESUP 150 */
1400: #define AGESUP 200
1.268 brouard 1401: #define AGEINF 0
1.218 brouard 1402: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1403: #define AGEBASE 40
1.194 brouard 1404: #define AGEOVERFLOW 1.e20
1.164 brouard 1405: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1406: #ifdef _WIN32
1407: #define DIRSEPARATOR '\\'
1408: #define CHARSEPARATOR "\\"
1409: #define ODIRSEPARATOR '/'
1410: #else
1.126 brouard 1411: #define DIRSEPARATOR '/'
1412: #define CHARSEPARATOR "/"
1413: #define ODIRSEPARATOR '\\'
1414: #endif
1415:
1.364 ! brouard 1416: /* $Id: imach.c,v 1.363 2024/06/28 09:31:55 brouard Exp $ */
1.126 brouard 1417: /* $State: Exp $ */
1.196 brouard 1418: #include "version.h"
1419: char version[]=__IMACH_VERSION__;
1.360 brouard 1420: char copyright[]="April 2024,INED-EUROREVES-Institut de longevite-Japan Society for the Promotion of Science (Grant-in-Aid for Scientific Research 25293121), Intel Software 2015-2020, Nihon University 2021-202, INED 2000-2024";
1.364 ! brouard 1421: char fullversion[]="$Revision: 1.363 $ $Date: 2024/06/28 09:31:55 $";
1.126 brouard 1422: char strstart[80];
1423: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1424: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.342 brouard 1425: int debugILK=0; /* debugILK is set by a #d in a comment line */
1.187 brouard 1426: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.330 brouard 1427: /* Number of covariates model (1)=V2+V1+ V3*age+V2*V4 */
1428: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
1.335 brouard 1429: int cptcovn=0; /**< cptcovn decodemodel: number of covariates k of the models excluding age*products =6 and age*age but including products */
1.330 brouard 1430: int cptcovt=0; /**< cptcovt: total number of covariates of the model (2) nbocc(+)+1 = 8 excepting constant and age and age*age */
1.335 brouard 1431: int cptcovs=0; /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
1432: int cptcovsnq=0; /**< cptcovsnq number of SIMPLE covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1433: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1.349 brouard 1434: int cptcovprodage=0; /**< Number of fixed covariates with age: V3*age or V2*V3*age 1 */
1435: int cptcovprodvage=0; /**< Number of varying covariates with age: V7*age or V7*V6*age */
1436: int cptcovdageprod=0; /**< Number of doubleproducts with age, since 0.99r44 only: age*Vn*Vm for gnuplot printing*/
1.145 brouard 1437: int cptcovprodnoage=0; /**< Number of covariate products without age */
1.335 brouard 1438: int cptcoveff=0; /* Total number of single dummy covariates (fixed or time varying) to vary for printing results (2**cptcoveff combinations of dummies)(computed in tricode as cptcov) */
1.233 brouard 1439: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1440: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.339 brouard 1441: int ncovvt=0; /* Total number of effective (wave) varying covariates (dummy or quantitative or products [without age]) in the model */
1.349 brouard 1442: int ncovvta=0; /* +age*V6 + age*V7+ age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 Total number of expandend products [with age]) in the model */
1443: int ncovta=0; /*age*V3*V2 +age*V2+agev3+ageV4 +age*V6 + age*V7+ age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 Total number of expandend products [with age]) in the model */
1444: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (single or product, dummy or quantitative) in the model */
1445: int ncovva=0; /* +age*V6 + age*V7+ge*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 Total number of effective (wave and stepm) varying with age covariates (single or product, dummy or quantitative) in the model */
1.234 brouard 1446: int nsd=0; /**< Total number of single dummy variables (output) */
1447: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1448: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1449: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1450: int ntveff=0; /**< ntveff number of effective time varying variables */
1451: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1452: int cptcov=0; /* Working variable */
1.334 brouard 1453: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs+1 declared globally ;*/
1.290 brouard 1454: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1455: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.302 brouard 1456: int npar=NPARMAX; /* Number of parameters (nlstate+ndeath-1)*nlstate*ncovmodel; */
1.126 brouard 1457: int nlstate=2; /* Number of live states */
1458: int ndeath=1; /* Number of dead states */
1.130 brouard 1459: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.339 brouard 1460: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable*/
1461: int ncovcolt=0; /* ncovcolt=ncovcol+nqv+ntv+nqtv; total of covariates in the data, not in the model equation*/
1.126 brouard 1462: int popbased=0;
1463:
1464: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1465: int maxwav=0; /* Maxim number of waves */
1466: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1467: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1.359 brouard 1468: int gipmx = 0;
1469: double gsw = 0; /* Global variables on the number of contributions
1.126 brouard 1470: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1471: int mle=1, weightopt=0;
1.126 brouard 1472: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1473: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1474: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1475: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1476: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1477: int selected(int kvar); /* Is covariate kvar selected for printing results */
1478:
1.130 brouard 1479: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1480: double **matprod2(); /* test */
1.126 brouard 1481: double **oldm, **newm, **savm; /* Working pointers to matrices */
1482: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1483: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1484:
1.136 brouard 1485: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1486: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1487: FILE *ficlog, *ficrespow;
1.130 brouard 1488: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1489: double fretone; /* Only one call to likelihood */
1.130 brouard 1490: long ipmx=0; /* Number of contributions */
1.126 brouard 1491: double sw; /* Sum of weights */
1492: char filerespow[FILENAMELENGTH];
1493: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1494: FILE *ficresilk;
1495: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1496: FILE *ficresprobmorprev;
1497: FILE *fichtm, *fichtmcov; /* Html File */
1498: FILE *ficreseij;
1499: char filerese[FILENAMELENGTH];
1500: FILE *ficresstdeij;
1501: char fileresstde[FILENAMELENGTH];
1502: FILE *ficrescveij;
1503: char filerescve[FILENAMELENGTH];
1504: FILE *ficresvij;
1505: char fileresv[FILENAMELENGTH];
1.269 brouard 1506:
1.126 brouard 1507: char title[MAXLINE];
1.234 brouard 1508: char model[MAXLINE]; /**< The model line */
1.217 brouard 1509: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1510: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1511: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1512: char command[FILENAMELENGTH];
1513: int outcmd=0;
1514:
1.217 brouard 1515: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1516: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1517: char filelog[FILENAMELENGTH]; /* Log file */
1518: char filerest[FILENAMELENGTH];
1519: char fileregp[FILENAMELENGTH];
1520: char popfile[FILENAMELENGTH];
1521:
1522: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1523:
1.157 brouard 1524: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1525: /* struct timezone tzp; */
1526: /* extern int gettimeofday(); */
1527: struct tm tml, *gmtime(), *localtime();
1528:
1529: extern time_t time();
1530:
1531: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1532: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1.349 brouard 1533: time_t rlast_btime; /* raw time */
1.157 brouard 1534: struct tm tm;
1535:
1.126 brouard 1536: char strcurr[80], strfor[80];
1537:
1538: char *endptr;
1539: long lval;
1540: double dval;
1541:
1.362 brouard 1542: /* This for praxis gegen */
1543: /* int prin=1; */
1544: double h0=0.25;
1545: double macheps;
1546: double ffmin;
1547:
1.126 brouard 1548: #define NR_END 1
1549: #define FREE_ARG char*
1550: #define FTOL 1.0e-10
1551:
1552: #define NRANSI
1.240 brouard 1553: #define ITMAX 200
1554: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1555:
1556: #define TOL 2.0e-4
1557:
1558: #define CGOLD 0.3819660
1559: #define ZEPS 1.0e-10
1560: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1561:
1562: #define GOLD 1.618034
1563: #define GLIMIT 100.0
1564: #define TINY 1.0e-20
1565:
1566: static double maxarg1,maxarg2;
1567: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1568: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1569:
1570: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1571: #define rint(a) floor(a+0.5)
1.166 brouard 1572: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1573: #define mytinydouble 1.0e-16
1.166 brouard 1574: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1575: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1576: /* static double dsqrarg; */
1577: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1578: static double sqrarg;
1579: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1580: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1581: int agegomp= AGEGOMP;
1582:
1583: int imx;
1584: int stepm=1;
1585: /* Stepm, step in month: minimum step interpolation*/
1586:
1587: int estepm;
1588: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1589:
1590: int m,nb;
1591: long *num;
1.197 brouard 1592: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1593: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1594: covariate for which somebody answered excluding
1595: undefined. Usually 2: 0 and 1. */
1596: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1597: covariate for which somebody answered including
1598: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1599: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1600: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1601: double ***mobaverage, ***mobaverages; /* New global variable */
1.332 brouard 1602: double **precov; /* New global variable to store for each resultline, values of model covariates given by the resultlines (in order to speed up) */
1.126 brouard 1603: double *ageexmed,*agecens;
1604: double dateintmean=0;
1.296 brouard 1605: double anprojd, mprojd, jprojd; /* For eventual projections */
1606: double anprojf, mprojf, jprojf;
1.126 brouard 1607:
1.296 brouard 1608: double anbackd, mbackd, jbackd; /* For eventual backprojections */
1609: double anbackf, mbackf, jbackf;
1610: double jintmean,mintmean,aintmean;
1.126 brouard 1611: double *weight;
1612: int **s; /* Status */
1.141 brouard 1613: double *agedc;
1.145 brouard 1614: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1615: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1616: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1617: double **coqvar; /* Fixed quantitative covariate nqv */
1.341 brouard 1618: double ***cotvar; /* Time varying covariate start at ncovcol + nqv + (1 to ntv) */
1.225 brouard 1619: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1620: double idx;
1621: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.319 brouard 1622: /* Some documentation */
1623: /* Design original data
1624: * V1 V2 V3 V4 V5 V6 V7 V8 Weight ddb ddth d1st s1 V9 V10 V11 V12 s2 V9 V10 V11 V12
1625: * < ncovcol=6 > nqv=2 (V7 V8) dv dv dv qtv dv dv dvv qtv
1626: * ntv=3 nqtv=1
1.330 brouard 1627: * cptcovn number of covariates (not including constant and age or age*age) = number of plus sign + 1 = 10+1=11
1.319 brouard 1628: * For time varying covariate, quanti or dummies
1629: * cotqvar[wav][iv(1 to nqtv)][i]= [1][12][i]=(V12) quanti
1.341 brouard 1630: * cotvar[wav][ncovcol+nqv+ iv(1 to nqtv)][i]= [(1 to nqtv)][i]=(V12) quanti
1.319 brouard 1631: * cotvar[wav][iv(1 to ntv)][i]= [1][1][i]=(V9) dummies at wav 1
1632: * cotvar[wav][iv(1 to ntv)][i]= [1][2][i]=(V10) dummies at wav 1
1.332 brouard 1633: * covar[Vk,i], value of the Vkth fixed covariate dummy or quanti for individual i:
1.319 brouard 1634: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
1635: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 + V9 + V9*age + V10
1636: * k= 1 2 3 4 5 6 7 8 9 10 11
1637: */
1638: /* According to the model, more columns can be added to covar by the product of covariates */
1.318 brouard 1639: /* ncovcol=1(Males=0 Females=1) nqv=1(raedyrs) ntv=2(withoutiadl=0 withiadl=1, witoutadl=0 withoutadl=1) nqtv=1(bmi) nlstate=3 ndeath=1
1640: # States 1=Coresidence, 2 Living alone, 3 Institution
1641: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1642: */
1.349 brouard 1643: /* V5+V4+ V3+V4*V3 +V5*age+V2 +V1*V2+V1*age+V1+V4*V3*age */
1644: /* kmodel 1 2 3 4 5 6 7 8 9 10 */
1645: /*Typevar[k]= 0 0 0 2 1 0 2 1 0 3 *//*0 for simple covariate (dummy, quantitative,*/
1646: /* fixed or varying), 1 for age product, 2 for*/
1647: /* product without age, 3 for age and double product */
1648: /*Dummy[k]= 1 0 0 1 3 1 1 2 0 3 *//*Dummy[k] 0=dummy (0 1), 1 quantitative */
1649: /*(single or product without age), 2 dummy*/
1650: /* with age product, 3 quant with age product*/
1651: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 6 */
1652: /* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */
1653: /*TnsdVar[Tvar] 1 2 3 */
1654: /*Tvaraff[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1655: /*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1656: /*TvarsDind[nsd] 2 3 9 */ /* position K of single dummy cova */
1657: /* nsq 1 2 */ /* Counting single quantit tv */
1658: /* TvarsQ[k] 5 2 */ /* Number of single quantitative cova */
1659: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1660: /* Tprod[i]=k 1 2 */ /* Position in model of the ith prod without age */
1661: /* cptcovage 1 2 3 */ /* Counting cov*age in the model equation */
1662: /* Tage[cptcovage]=k 5 8 10 */ /* Position in the model of ith cov*age */
1.350 brouard 1663: /* model="V2+V3+V4+V6+V7+V6*V2+V7*V2+V6*V3+V7*V3+V6*V4+V7*V4+age*V2+age*V3+age*V4+age*V6+age*V7+age*V6*V2+age*V6*V3+age*V7*V3+age*V6*V4+age*V7*V4\r"*/
1664: /* p Tvard[1][1]@21 = {6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0}*/
1.354 brouard 1665: /* p Tvard[2][1]@21 = {7, 2, 6, 3, 7, 3, 6, 4, 7, 4, 0 <repeats 11 times>} */
1.350 brouard 1666: /* p Tvardk[1][1]@24 = {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4, 0, 0}*/
1667: /* p Tvardk[1][1]@22 = {0, 0, 0, 0, 0, 0, 0, 0, 6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4, 0, 0} */
1.349 brouard 1668: /* Tvard[1][1]@4={4,3,1,2} V4*V3 V1*V2 */ /* Position in model of the ith prod without age */
1.330 brouard 1669: /* Tvardk[4][1]=4;Tvardk[4][2]=3;Tvardk[7][1]=1;Tvardk[7][2]=2 */ /* Variables of a prod at position in the model equation*/
1.319 brouard 1670: /* TvarF TvarF[1]=Tvar[6]=2, TvarF[2]=Tvar[7]=7, TvarF[3]=Tvar[9]=1 ID of fixed covariates or product V2, V1*V2, V1 */
1.320 brouard 1671: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.234 brouard 1672: /* Type */
1673: /* V 1 2 3 4 5 */
1674: /* F F V V V */
1675: /* D Q D D Q */
1676: /* */
1677: int *TvarsD;
1.330 brouard 1678: int *TnsdVar;
1.234 brouard 1679: int *TvarsDind;
1680: int *TvarsQ;
1681: int *TvarsQind;
1682:
1.318 brouard 1683: #define MAXRESULTLINESPONE 10+1
1.235 brouard 1684: int nresult=0;
1.258 brouard 1685: int parameterline=0; /* # of the parameter (type) line */
1.334 brouard 1686: int TKresult[MAXRESULTLINESPONE]; /* TKresult[nres]=k for each resultline nres give the corresponding combination of dummies */
1687: int resultmodel[MAXRESULTLINESPONE][NCOVMAX];/* resultmodel[k1]=k3: k1th position in the model corresponds to the k3 position in the resultline */
1688: int modelresult[MAXRESULTLINESPONE][NCOVMAX];/* modelresult[k3]=k1: k1th position in the model corresponds to the k3 position in the resultline */
1689: int Tresult[MAXRESULTLINESPONE][NCOVMAX];/* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1690: int Tinvresult[MAXRESULTLINESPONE][NCOVMAX];/* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1691: double TinvDoQresult[MAXRESULTLINESPONE][NCOVMAX];/* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.334 brouard 1692: int Tvresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1693: double Tqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.318 brouard 1694: double Tqinvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
1.332 brouard 1695: int Tvqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.318 brouard 1696:
1697: /* ncovcol=1(Males=0 Females=1) nqv=1(raedyrs) ntv=2(withoutiadl=0 withiadl=1, witoutadl=0 withoutadl=1) nqtv=1(bmi) nlstate=3 ndeath=1
1698: # States 1=Coresidence, 2 Living alone, 3 Institution
1699: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1700: */
1.234 brouard 1701: /* int *TDvar; /\**< TDvar[1]=4, TDvarF[2]=3, TDvar[3]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
1.232 brouard 1702: int *TvarF; /**< TvarF[1]=Tvar[6]=2, TvarF[2]=Tvar[7]=7, TvarF[3]=Tvar[9]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1703: int *TvarFind; /**< TvarFind[1]=6, TvarFind[2]=7, Tvarind[3]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1704: int *TvarV; /**< TvarV[1]=Tvar[1]=5, TvarV[2]=Tvar[2]=4 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1705: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1706: int *TvarA; /**< TvarA[1]=Tvar[5]=5, TvarA[2]=Tvar[8]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1707: int *TvarAind; /**< TvarindA[1]=5, TvarAind[2]=8 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 1708: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1709: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1710: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1711: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1712: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1713: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1714: int *TvarVQ; /* TvarVQ[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple time varying quantitative variable */
1715: int *TvarVQind; /* TvarVQind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple time varying quantitative variable */
1.339 brouard 1716: int *TvarVV; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1717: int *TvarVVind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1.349 brouard 1718: int *TvarVVA; /* We count ncovvt time varying covariates (single or products with age) and put their name into TvarVVA */
1719: int *TvarVVAind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1720: int *TvarAVVA; /* We count ALL ncovta time varying covariates (single or products with age) and put their name into TvarVVA */
1721: int *TvarAVVAind; /* We count ALL ncovta time varying covariates (single or products without age) and put their name into TvarVV */
1.339 brouard 1722: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
1.349 brouard 1723: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age */
1724: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
1725: /* TvarVV={3,1,3,1,3}, for V3 and then the product V1*V3 is decomposed into V1 and V3 */
1726: /* TvarVVind={2,5,5,6,6}, for V3 and then the product V1*V3 is decomposed into V1 and V3 and V1*V3*age into 6,6 */
1.230 brouard 1727: int *Tvarsel; /**< Selected covariates for output */
1728: double *Tvalsel; /**< Selected modality value of covariate for output */
1.349 brouard 1729: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product, 3 age*Vn*Vm */
1.227 brouard 1730: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1731: int *Dummy; /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
1.238 brouard 1732: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1733: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1734: int *Tage;
1.227 brouard 1735: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1736: int *Tmodelind; /** Tmodelind[Tvaraff[3]]=9 for V1 position,Tvaraff[1]@9={4, 3, 1, 0, 0, 0, 0, 0, 0}, model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.230 brouard 1737: int *TmodelInvind; /** Tmodelind[Tvaraff[3]]=9 for V1 position,Tvaraff[1]@9={4, 3, 1, 0, 0, 0, 0, 0, 0}, model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1738: int *TmodelInvQind; /** Tmodelqind[1]=1 for V5(quantitative varying) position,Tvaraff[1]@9={4, 3, 1, 0, 0, 0, 0, 0, 0}, model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.145 brouard 1739: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1740: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1741: int **Tvard;
1.330 brouard 1742: int **Tvardk;
1.227 brouard 1743: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1744: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1745: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1746: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1747: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1748: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1749: double *lsurv, *lpop, *tpop;
1750:
1.231 brouard 1751: #define FD 1; /* Fixed dummy covariate */
1752: #define FQ 2; /* Fixed quantitative covariate */
1753: #define FP 3; /* Fixed product covariate */
1754: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1755: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1756: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1757: #define VD 10; /* Varying dummy covariate */
1758: #define VQ 11; /* Varying quantitative covariate */
1759: #define VP 12; /* Varying product covariate */
1760: #define VPDD 13; /* Varying product dummy*dummy covariate */
1761: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1762: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1763: #define APFD 16; /* Age product * fixed dummy covariate */
1764: #define APFQ 17; /* Age product * fixed quantitative covariate */
1765: #define APVD 18; /* Age product * varying dummy covariate */
1766: #define APVQ 19; /* Age product * varying quantitative covariate */
1767:
1768: #define FTYPE 1; /* Fixed covariate */
1769: #define VTYPE 2; /* Varying covariate (loop in wave) */
1770: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1771:
1772: struct kmodel{
1773: int maintype; /* main type */
1774: int subtype; /* subtype */
1775: };
1776: struct kmodel modell[NCOVMAX];
1777:
1.143 brouard 1778: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1779: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1780:
1781: /**************** split *************************/
1782: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1783: {
1784: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1785: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1786: */
1787: char *ss; /* pointer */
1.186 brouard 1788: int l1=0, l2=0; /* length counters */
1.126 brouard 1789:
1790: l1 = strlen(path ); /* length of path */
1791: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1792: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1793: if ( ss == NULL ) { /* no directory, so determine current directory */
1794: strcpy( name, path ); /* we got the fullname name because no directory */
1795: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1796: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1797: /* get current working directory */
1798: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1799: #ifdef WIN32
1800: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1801: #else
1802: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1803: #endif
1.126 brouard 1804: return( GLOCK_ERROR_GETCWD );
1805: }
1806: /* got dirc from getcwd*/
1807: printf(" DIRC = %s \n",dirc);
1.205 brouard 1808: } else { /* strip directory from path */
1.126 brouard 1809: ss++; /* after this, the filename */
1810: l2 = strlen( ss ); /* length of filename */
1811: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1812: strcpy( name, ss ); /* save file name */
1813: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1814: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1815: printf(" DIRC2 = %s \n",dirc);
1816: }
1817: /* We add a separator at the end of dirc if not exists */
1818: l1 = strlen( dirc ); /* length of directory */
1819: if( dirc[l1-1] != DIRSEPARATOR ){
1820: dirc[l1] = DIRSEPARATOR;
1821: dirc[l1+1] = 0;
1822: printf(" DIRC3 = %s \n",dirc);
1823: }
1824: ss = strrchr( name, '.' ); /* find last / */
1825: if (ss >0){
1826: ss++;
1827: strcpy(ext,ss); /* save extension */
1828: l1= strlen( name);
1829: l2= strlen(ss)+1;
1830: strncpy( finame, name, l1-l2);
1831: finame[l1-l2]= 0;
1832: }
1833:
1834: return( 0 ); /* we're done */
1835: }
1836:
1837:
1838: /******************************************/
1839:
1840: void replace_back_to_slash(char *s, char*t)
1841: {
1842: int i;
1843: int lg=0;
1844: i=0;
1845: lg=strlen(t);
1846: for(i=0; i<= lg; i++) {
1847: (s[i] = t[i]);
1848: if (t[i]== '\\') s[i]='/';
1849: }
1850: }
1851:
1.132 brouard 1852: char *trimbb(char *out, char *in)
1.137 brouard 1853: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1854: char *s;
1855: s=out;
1856: while (*in != '\0'){
1.137 brouard 1857: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1858: in++;
1859: }
1860: *out++ = *in++;
1861: }
1862: *out='\0';
1863: return s;
1864: }
1865:
1.351 brouard 1866: char *trimbtab(char *out, char *in)
1867: { /* Trim blanks or tabs in line but keeps first blanks if line starts with blanks */
1868: char *s;
1869: s=out;
1870: while (*in != '\0'){
1871: while( (*in == ' ' || *in == '\t')){ /* && *(in+1) != '\0'){*/
1872: in++;
1873: }
1874: *out++ = *in++;
1875: }
1876: *out='\0';
1877: return s;
1878: }
1879:
1.187 brouard 1880: /* char *substrchaine(char *out, char *in, char *chain) */
1881: /* { */
1882: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1883: /* char *s, *t; */
1884: /* t=in;s=out; */
1885: /* while ((*in != *chain) && (*in != '\0')){ */
1886: /* *out++ = *in++; */
1887: /* } */
1888:
1889: /* /\* *in matches *chain *\/ */
1890: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1891: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1892: /* } */
1893: /* in--; chain--; */
1894: /* while ( (*in != '\0')){ */
1895: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1896: /* *out++ = *in++; */
1897: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1898: /* } */
1899: /* *out='\0'; */
1900: /* out=s; */
1901: /* return out; */
1902: /* } */
1903: char *substrchaine(char *out, char *in, char *chain)
1904: {
1905: /* Substract chain 'chain' from 'in', return and output 'out' */
1.349 brouard 1906: /* in="V1+V1*age+age*age+V2", chain="+age*age" out="V1+V1*age+V2" */
1.187 brouard 1907:
1908: char *strloc;
1909:
1.349 brouard 1910: strcpy (out, in); /* out="V1+V1*age+age*age+V2" */
1911: strloc = strstr(out, chain); /* strloc points to out at "+age*age+V2" */
1912: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out); /* strloc=+age*age+V2 chain="+age*age", out="V1+V1*age+age*age+V2" */
1.187 brouard 1913: if(strloc != NULL){
1.349 brouard 1914: /* will affect out */ /* strloc+strlen(chain)=|+V2 = "V1+V1*age+age*age|+V2" */ /* Will also work in Unicodek */
1915: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1); /* move number of bytes corresponding to the length of "+V2" which is 3, plus one is 4 (including the null)*/
1916: /* equivalent to strcpy (strloc, strloc +strlen(chain)) if no overlap; Copies from "+V2" to V1+V1*age+ */
1.187 brouard 1917: }
1.349 brouard 1918: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out); /* strloc=+V2 chain="+age*age", in="V1+V1*age+age*age+V2", out="V1+V1*age+V2" */
1.187 brouard 1919: return out;
1920: }
1921:
1922:
1.145 brouard 1923: char *cutl(char *blocc, char *alocc, char *in, char occ)
1924: {
1.187 brouard 1925: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.349 brouard 1926: and alocc starts after first occurence of char 'occ' : ex cutl(blocc,alocc,"abcdef2ghi2j",'2')
1.310 brouard 1927: gives alocc="abcdef" and blocc="ghi2j".
1.145 brouard 1928: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1929: */
1.160 brouard 1930: char *s, *t;
1.145 brouard 1931: t=in;s=in;
1932: while ((*in != occ) && (*in != '\0')){
1933: *alocc++ = *in++;
1934: }
1935: if( *in == occ){
1936: *(alocc)='\0';
1937: s=++in;
1938: }
1939:
1940: if (s == t) {/* occ not found */
1941: *(alocc-(in-s))='\0';
1942: in=s;
1943: }
1944: while ( *in != '\0'){
1945: *blocc++ = *in++;
1946: }
1947:
1948: *blocc='\0';
1949: return t;
1950: }
1.137 brouard 1951: char *cutv(char *blocc, char *alocc, char *in, char occ)
1952: {
1.187 brouard 1953: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1954: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1955: gives blocc="abcdef2ghi" and alocc="j".
1956: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1957: */
1958: char *s, *t;
1959: t=in;s=in;
1960: while (*in != '\0'){
1961: while( *in == occ){
1962: *blocc++ = *in++;
1963: s=in;
1964: }
1965: *blocc++ = *in++;
1966: }
1967: if (s == t) /* occ not found */
1968: *(blocc-(in-s))='\0';
1969: else
1970: *(blocc-(in-s)-1)='\0';
1971: in=s;
1972: while ( *in != '\0'){
1973: *alocc++ = *in++;
1974: }
1975:
1976: *alocc='\0';
1977: return s;
1978: }
1979:
1.126 brouard 1980: int nbocc(char *s, char occ)
1981: {
1982: int i,j=0;
1983: int lg=20;
1984: i=0;
1985: lg=strlen(s);
1986: for(i=0; i<= lg; i++) {
1.234 brouard 1987: if (s[i] == occ ) j++;
1.126 brouard 1988: }
1989: return j;
1990: }
1991:
1.349 brouard 1992: int nboccstr(char *textin, char *chain)
1993: {
1994: /* Counts the number of occurence of "chain" in string textin */
1995: /* in="+V7*V4+age*V2+age*V3+age*V4" chain="age" */
1996: char *strloc;
1997:
1998: int i,j=0;
1999:
2000: i=0;
2001:
2002: strloc=textin; /* strloc points to "^+V7*V4+age+..." in textin */
2003: for(;;) {
2004: strloc= strstr(strloc,chain); /* strloc points to first character of chain in textin if found. Example strloc points^ to "+V7*V4+^age" in textin */
2005: if(strloc != NULL){
2006: strloc = strloc+strlen(chain); /* strloc points to "+V7*V4+age^" in textin */
2007: j++;
2008: }else
2009: break;
2010: }
2011: return j;
2012:
2013: }
1.137 brouard 2014: /* void cutv(char *u,char *v, char*t, char occ) */
2015: /* { */
2016: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
2017: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
2018: /* gives u="abcdef2ghi" and v="j" *\/ */
2019: /* int i,lg,j,p=0; */
2020: /* i=0; */
2021: /* lg=strlen(t); */
2022: /* for(j=0; j<=lg-1; j++) { */
2023: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
2024: /* } */
1.126 brouard 2025:
1.137 brouard 2026: /* for(j=0; j<p; j++) { */
2027: /* (u[j] = t[j]); */
2028: /* } */
2029: /* u[p]='\0'; */
1.126 brouard 2030:
1.137 brouard 2031: /* for(j=0; j<= lg; j++) { */
2032: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
2033: /* } */
2034: /* } */
1.126 brouard 2035:
1.160 brouard 2036: #ifdef _WIN32
2037: char * strsep(char **pp, const char *delim)
2038: {
2039: char *p, *q;
2040:
2041: if ((p = *pp) == NULL)
2042: return 0;
2043: if ((q = strpbrk (p, delim)) != NULL)
2044: {
2045: *pp = q + 1;
2046: *q = '\0';
2047: }
2048: else
2049: *pp = 0;
2050: return p;
2051: }
2052: #endif
2053:
1.126 brouard 2054: /********************** nrerror ********************/
2055:
2056: void nrerror(char error_text[])
2057: {
2058: fprintf(stderr,"ERREUR ...\n");
2059: fprintf(stderr,"%s\n",error_text);
2060: exit(EXIT_FAILURE);
2061: }
2062: /*********************** vector *******************/
2063: double *vector(int nl, int nh)
2064: {
2065: double *v;
2066: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
2067: if (!v) nrerror("allocation failure in vector");
2068: return v-nl+NR_END;
2069: }
2070:
2071: /************************ free vector ******************/
2072: void free_vector(double*v, int nl, int nh)
2073: {
2074: free((FREE_ARG)(v+nl-NR_END));
2075: }
2076:
2077: /************************ivector *******************************/
2078: int *ivector(long nl,long nh)
2079: {
2080: int *v;
2081: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
2082: if (!v) nrerror("allocation failure in ivector");
2083: return v-nl+NR_END;
2084: }
2085:
2086: /******************free ivector **************************/
2087: void free_ivector(int *v, long nl, long nh)
2088: {
2089: free((FREE_ARG)(v+nl-NR_END));
2090: }
2091:
2092: /************************lvector *******************************/
2093: long *lvector(long nl,long nh)
2094: {
2095: long *v;
2096: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
2097: if (!v) nrerror("allocation failure in ivector");
2098: return v-nl+NR_END;
2099: }
2100:
2101: /******************free lvector **************************/
2102: void free_lvector(long *v, long nl, long nh)
2103: {
2104: free((FREE_ARG)(v+nl-NR_END));
2105: }
2106:
2107: /******************* imatrix *******************************/
2108: int **imatrix(long nrl, long nrh, long ncl, long nch)
2109: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
2110: {
2111: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
2112: int **m;
2113:
2114: /* allocate pointers to rows */
2115: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
2116: if (!m) nrerror("allocation failure 1 in matrix()");
2117: m += NR_END;
2118: m -= nrl;
2119:
2120:
2121: /* allocate rows and set pointers to them */
2122: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
2123: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2124: m[nrl] += NR_END;
2125: m[nrl] -= ncl;
2126:
2127: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
2128:
2129: /* return pointer to array of pointers to rows */
2130: return m;
2131: }
2132:
2133: /****************** free_imatrix *************************/
2134: void free_imatrix(m,nrl,nrh,ncl,nch)
2135: int **m;
2136: long nch,ncl,nrh,nrl;
2137: /* free an int matrix allocated by imatrix() */
2138: {
2139: free((FREE_ARG) (m[nrl]+ncl-NR_END));
2140: free((FREE_ARG) (m+nrl-NR_END));
2141: }
2142:
2143: /******************* matrix *******************************/
2144: double **matrix(long nrl, long nrh, long ncl, long nch)
2145: {
2146: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
2147: double **m;
2148:
2149: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
2150: if (!m) nrerror("allocation failure 1 in matrix()");
2151: m += NR_END;
2152: m -= nrl;
2153:
2154: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
2155: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2156: m[nrl] += NR_END;
2157: m[nrl] -= ncl;
2158:
2159: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2160: return m;
1.145 brouard 2161: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
2162: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
2163: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 2164: */
2165: }
2166:
2167: /*************************free matrix ************************/
2168: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
2169: {
2170: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2171: free((FREE_ARG)(m+nrl-NR_END));
2172: }
2173:
2174: /******************* ma3x *******************************/
2175: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
2176: {
2177: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
2178: double ***m;
2179:
2180: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
2181: if (!m) nrerror("allocation failure 1 in matrix()");
2182: m += NR_END;
2183: m -= nrl;
2184:
2185: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
2186: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2187: m[nrl] += NR_END;
2188: m[nrl] -= ncl;
2189:
2190: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2191:
2192: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
2193: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
2194: m[nrl][ncl] += NR_END;
2195: m[nrl][ncl] -= nll;
2196: for (j=ncl+1; j<=nch; j++)
2197: m[nrl][j]=m[nrl][j-1]+nlay;
2198:
2199: for (i=nrl+1; i<=nrh; i++) {
2200: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
2201: for (j=ncl+1; j<=nch; j++)
2202: m[i][j]=m[i][j-1]+nlay;
2203: }
2204: return m;
2205: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
2206: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
2207: */
2208: }
2209:
2210: /*************************free ma3x ************************/
2211: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
2212: {
2213: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
2214: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2215: free((FREE_ARG)(m+nrl-NR_END));
2216: }
2217:
2218: /*************** function subdirf ***********/
2219: char *subdirf(char fileres[])
2220: {
2221: /* Caution optionfilefiname is hidden */
2222: strcpy(tmpout,optionfilefiname);
2223: strcat(tmpout,"/"); /* Add to the right */
2224: strcat(tmpout,fileres);
2225: return tmpout;
2226: }
2227:
2228: /*************** function subdirf2 ***********/
2229: char *subdirf2(char fileres[], char *preop)
2230: {
1.314 brouard 2231: /* Example subdirf2(optionfilefiname,"FB_") with optionfilefiname="texte", result="texte/FB_texte"
2232: Errors in subdirf, 2, 3 while printing tmpout is
1.315 brouard 2233: rewritten within the same printf. Workaround: many printfs */
1.126 brouard 2234: /* Caution optionfilefiname is hidden */
2235: strcpy(tmpout,optionfilefiname);
2236: strcat(tmpout,"/");
2237: strcat(tmpout,preop);
2238: strcat(tmpout,fileres);
2239: return tmpout;
2240: }
2241:
2242: /*************** function subdirf3 ***********/
2243: char *subdirf3(char fileres[], char *preop, char *preop2)
2244: {
2245:
2246: /* Caution optionfilefiname is hidden */
2247: strcpy(tmpout,optionfilefiname);
2248: strcat(tmpout,"/");
2249: strcat(tmpout,preop);
2250: strcat(tmpout,preop2);
2251: strcat(tmpout,fileres);
2252: return tmpout;
2253: }
1.213 brouard 2254:
2255: /*************** function subdirfext ***********/
2256: char *subdirfext(char fileres[], char *preop, char *postop)
2257: {
2258:
2259: strcpy(tmpout,preop);
2260: strcat(tmpout,fileres);
2261: strcat(tmpout,postop);
2262: return tmpout;
2263: }
1.126 brouard 2264:
1.213 brouard 2265: /*************** function subdirfext3 ***********/
2266: char *subdirfext3(char fileres[], char *preop, char *postop)
2267: {
2268:
2269: /* Caution optionfilefiname is hidden */
2270: strcpy(tmpout,optionfilefiname);
2271: strcat(tmpout,"/");
2272: strcat(tmpout,preop);
2273: strcat(tmpout,fileres);
2274: strcat(tmpout,postop);
2275: return tmpout;
2276: }
2277:
1.162 brouard 2278: char *asc_diff_time(long time_sec, char ascdiff[])
2279: {
2280: long sec_left, days, hours, minutes;
2281: days = (time_sec) / (60*60*24);
2282: sec_left = (time_sec) % (60*60*24);
2283: hours = (sec_left) / (60*60) ;
2284: sec_left = (sec_left) %(60*60);
2285: minutes = (sec_left) /60;
2286: sec_left = (sec_left) % (60);
2287: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
2288: return ascdiff;
2289: }
2290:
1.126 brouard 2291: /***************** f1dim *************************/
2292: extern int ncom;
2293: extern double *pcom,*xicom;
2294: extern double (*nrfunc)(double []);
2295:
2296: double f1dim(double x)
2297: {
2298: int j;
2299: double f;
2300: double *xt;
2301:
2302: xt=vector(1,ncom);
2303: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
2304: f=(*nrfunc)(xt);
2305: free_vector(xt,1,ncom);
2306: return f;
2307: }
2308:
2309: /*****************brent *************************/
2310: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 2311: {
2312: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
2313: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
2314: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
2315: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
2316: * returned function value.
2317: */
1.126 brouard 2318: int iter;
2319: double a,b,d,etemp;
1.159 brouard 2320: double fu=0,fv,fw,fx;
1.164 brouard 2321: double ftemp=0.;
1.126 brouard 2322: double p,q,r,tol1,tol2,u,v,w,x,xm;
2323: double e=0.0;
2324:
2325: a=(ax < cx ? ax : cx);
2326: b=(ax > cx ? ax : cx);
2327: x=w=v=bx;
2328: fw=fv=fx=(*f)(x);
2329: for (iter=1;iter<=ITMAX;iter++) {
2330: xm=0.5*(a+b);
2331: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
2332: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
2333: printf(".");fflush(stdout);
2334: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 2335: #ifdef DEBUGBRENT
1.126 brouard 2336: printf("br %d,x=%.10e xm=%.10e b=%.10e a=%.10e tol=%.10e tol1=%.10e tol2=%.10e x-xm=%.10e fx=%.12e fu=%.12e,fw=%.12e,ftemp=%.12e,ftol=%.12e\n",iter,x,xm,b,a,tol,tol1,tol2,(x-xm),fx,fu,fw,ftemp,ftol);
2337: fprintf(ficlog,"br %d,x=%.10e xm=%.10e b=%.10e a=%.10e tol=%.10e tol1=%.10e tol2=%.10e x-xm=%.10e fx=%.12e fu=%.12e,fw=%.12e,ftemp=%.12e,ftol=%.12e\n",iter,x,xm,b,a,tol,tol1,tol2,(x-xm),fx,fu,fw,ftemp,ftol);
2338: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
2339: #endif
2340: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
2341: *xmin=x;
2342: return fx;
2343: }
2344: ftemp=fu;
2345: if (fabs(e) > tol1) {
2346: r=(x-w)*(fx-fv);
2347: q=(x-v)*(fx-fw);
2348: p=(x-v)*q-(x-w)*r;
2349: q=2.0*(q-r);
2350: if (q > 0.0) p = -p;
2351: q=fabs(q);
2352: etemp=e;
2353: e=d;
2354: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 2355: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 2356: else {
1.224 brouard 2357: d=p/q;
2358: u=x+d;
2359: if (u-a < tol2 || b-u < tol2)
2360: d=SIGN(tol1,xm-x);
1.126 brouard 2361: }
2362: } else {
2363: d=CGOLD*(e=(x >= xm ? a-x : b-x));
2364: }
2365: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
2366: fu=(*f)(u);
2367: if (fu <= fx) {
2368: if (u >= x) a=x; else b=x;
2369: SHFT(v,w,x,u)
1.183 brouard 2370: SHFT(fv,fw,fx,fu)
2371: } else {
2372: if (u < x) a=u; else b=u;
2373: if (fu <= fw || w == x) {
1.224 brouard 2374: v=w;
2375: w=u;
2376: fv=fw;
2377: fw=fu;
1.183 brouard 2378: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 2379: v=u;
2380: fv=fu;
1.183 brouard 2381: }
2382: }
1.126 brouard 2383: }
2384: nrerror("Too many iterations in brent");
2385: *xmin=x;
2386: return fx;
2387: }
2388:
2389: /****************** mnbrak ***********************/
2390:
2391: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
2392: double (*func)(double))
1.183 brouard 2393: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
2394: the downhill direction (defined by the function as evaluated at the initial points) and returns
2395: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
2396: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
2397: */
1.126 brouard 2398: double ulim,u,r,q, dum;
2399: double fu;
1.187 brouard 2400:
2401: double scale=10.;
2402: int iterscale=0;
2403:
2404: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
2405: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
2406:
2407:
2408: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
2409: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
2410: /* *bx = *ax - (*ax - *bx)/scale; */
2411: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
2412: /* } */
2413:
1.126 brouard 2414: if (*fb > *fa) {
2415: SHFT(dum,*ax,*bx,dum)
1.183 brouard 2416: SHFT(dum,*fb,*fa,dum)
2417: }
1.126 brouard 2418: *cx=(*bx)+GOLD*(*bx-*ax);
2419: *fc=(*func)(*cx);
1.183 brouard 2420: #ifdef DEBUG
1.224 brouard 2421: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
2422: fprintf(ficlog,"mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
1.183 brouard 2423: #endif
1.224 brouard 2424: while (*fb > *fc) { /* Declining a,b,c with fa> fb > fc. If fc=inf it exits and if flat fb=fc it exits too.*/
1.126 brouard 2425: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 2426: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 2427: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 2428: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
2429: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
2430: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 2431: fu=(*func)(u);
1.163 brouard 2432: #ifdef DEBUG
2433: /* f(x)=A(x-u)**2+f(u) */
2434: double A, fparabu;
2435: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2436: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 2437: printf("\nmnbrak (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf), (*u=%.12f, fu=%.12lf, fparabu=%.12f, q=%lf < %lf=r)\n",*ax,*fa,*bx,*fb,*cx,*fc,u,fu, fparabu,q,r);
2438: fprintf(ficlog,"\nmnbrak (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf), (*u=%.12f, fu=%.12lf, fparabu=%.12f, q=%lf < %lf=r)\n",*ax,*fa,*bx,*fb,*cx,*fc,u,fu, fparabu,q,r);
1.183 brouard 2439: /* And thus,it can be that fu > *fc even if fparabu < *fc */
2440: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
2441: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
2442: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 2443: #endif
1.184 brouard 2444: #ifdef MNBRAKORIGINAL
1.183 brouard 2445: #else
1.191 brouard 2446: /* if (fu > *fc) { */
2447: /* #ifdef DEBUG */
2448: /* printf("mnbrak4 fu > fc \n"); */
2449: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
2450: /* #endif */
2451: /* /\* SHFT(u,*cx,*cx,u) /\\* ie a=c, c=u and u=c; in that case, next SHFT(a,b,c,u) will give a=b=b, b=c=u, c=u=c and *\\/ *\/ */
2452: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2453: /* dum=u; /\* Shifting c and u *\/ */
2454: /* u = *cx; */
2455: /* *cx = dum; */
2456: /* dum = fu; */
2457: /* fu = *fc; */
2458: /* *fc =dum; */
2459: /* } else { /\* end *\/ */
2460: /* #ifdef DEBUG */
2461: /* printf("mnbrak3 fu < fc \n"); */
2462: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2463: /* #endif */
2464: /* dum=u; /\* Shifting c and u *\/ */
2465: /* u = *cx; */
2466: /* *cx = dum; */
2467: /* dum = fu; */
2468: /* fu = *fc; */
2469: /* *fc =dum; */
2470: /* } */
1.224 brouard 2471: #ifdef DEBUGMNBRAK
2472: double A, fparabu;
2473: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2474: fparabu= *fa - A*(*ax-u)*(*ax-u);
2475: printf("\nmnbrak35 ax=%lf fa=%lf bx=%lf fb=%lf, u=%lf fp=%lf fu=%lf < or >= fc=%lf cx=%lf, q=%lf < %lf=r \n",*ax, *fa, *bx,*fb,u,fparabu,fu,*fc,*cx,q,r);
2476: fprintf(ficlog,"\nmnbrak35 ax=%lf fa=%lf bx=%lf fb=%lf, u=%lf fp=%lf fu=%lf < or >= fc=%lf cx=%lf, q=%lf < %lf=r \n",*ax, *fa, *bx,*fb,u,fparabu,fu,*fc,*cx,q,r);
1.183 brouard 2477: #endif
1.191 brouard 2478: dum=u; /* Shifting c and u */
2479: u = *cx;
2480: *cx = dum;
2481: dum = fu;
2482: fu = *fc;
2483: *fc =dum;
1.183 brouard 2484: #endif
1.162 brouard 2485: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2486: #ifdef DEBUG
1.224 brouard 2487: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2488: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2489: #endif
1.126 brouard 2490: fu=(*func)(u);
2491: if (fu < *fc) {
1.183 brouard 2492: #ifdef DEBUG
1.224 brouard 2493: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2494: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2495: #endif
2496: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2497: SHFT(*fb,*fc,fu,(*func)(u))
2498: #ifdef DEBUG
2499: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2500: #endif
2501: }
1.162 brouard 2502: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2503: #ifdef DEBUG
1.224 brouard 2504: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2505: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2506: #endif
1.126 brouard 2507: u=ulim;
2508: fu=(*func)(u);
1.183 brouard 2509: } else { /* u could be left to b (if r > q parabola has a maximum) */
2510: #ifdef DEBUG
1.224 brouard 2511: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2512: fprintf(ficlog,"\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
1.183 brouard 2513: #endif
1.126 brouard 2514: u=(*cx)+GOLD*(*cx-*bx);
2515: fu=(*func)(u);
1.224 brouard 2516: #ifdef DEBUG
2517: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2518: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2519: #endif
1.183 brouard 2520: } /* end tests */
1.126 brouard 2521: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2522: SHFT(*fa,*fb,*fc,fu)
2523: #ifdef DEBUG
1.224 brouard 2524: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2525: fprintf(ficlog, "\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
1.183 brouard 2526: #endif
2527: } /* end while; ie return (a, b, c, fa, fb, fc) such that a < b < c with f(a) > f(b) and fb < f(c) */
1.126 brouard 2528: }
2529:
2530: /*************** linmin ************************/
1.162 brouard 2531: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2532: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2533: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2534: the value of func at the returned location p . This is actually all accomplished by calling the
2535: routines mnbrak and brent .*/
1.126 brouard 2536: int ncom;
2537: double *pcom,*xicom;
2538: double (*nrfunc)(double []);
2539:
1.224 brouard 2540: #ifdef LINMINORIGINAL
1.126 brouard 2541: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2542: #else
2543: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2544: #endif
1.126 brouard 2545: {
2546: double brent(double ax, double bx, double cx,
2547: double (*f)(double), double tol, double *xmin);
2548: double f1dim(double x);
2549: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2550: double *fc, double (*func)(double));
2551: int j;
2552: double xx,xmin,bx,ax;
2553: double fx,fb,fa;
1.187 brouard 2554:
1.203 brouard 2555: #ifdef LINMINORIGINAL
2556: #else
2557: double scale=10., axs, xxs; /* Scale added for infinity */
2558: #endif
2559:
1.126 brouard 2560: ncom=n;
2561: pcom=vector(1,n);
2562: xicom=vector(1,n);
2563: nrfunc=func;
2564: for (j=1;j<=n;j++) {
2565: pcom[j]=p[j];
1.202 brouard 2566: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2567: }
1.187 brouard 2568:
1.203 brouard 2569: #ifdef LINMINORIGINAL
2570: xx=1.;
2571: #else
2572: axs=0.0;
2573: xxs=1.;
2574: do{
2575: xx= xxs;
2576: #endif
1.187 brouard 2577: ax=0.;
2578: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2579: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2580: /* xt[x,j]=pcom[j]+x*xicom[j] f(ax) = f(xt(a,j=1,n)) = f(p(j) + 0 * xi(j)) and f(xx) = f(xt(x, j=1,n)) = f(p(j) + 1 * xi(j)) */
2581: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2582: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2583: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2584: /* Find a bracket a,x,b in direction n=xi ie xicom, order may change. Scale is [0:xxs*xi[j]] et non plus [0:xi[j]]*/
1.203 brouard 2585: #ifdef LINMINORIGINAL
2586: #else
2587: if (fx != fx){
1.224 brouard 2588: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2589: printf("|");
2590: fprintf(ficlog,"|");
1.203 brouard 2591: #ifdef DEBUGLINMIN
1.224 brouard 2592: printf("\nLinmin NAN : input [axs=%lf:xxs=%lf], mnbrak outputs fx=%lf <(fb=%lf and fa=%lf) with xx=%lf in [ax=%lf:bx=%lf] \n", axs, xxs, fx,fb, fa, xx, ax, bx);
1.203 brouard 2593: #endif
2594: }
1.224 brouard 2595: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2596: #endif
2597:
1.191 brouard 2598: #ifdef DEBUGLINMIN
2599: printf("\nLinmin after mnbrak: ax=%12.7f xx=%12.7f bx=%12.7f fa=%12.2f fx=%12.2f fb=%12.2f\n", ax,xx,bx,fa,fx,fb);
1.202 brouard 2600: fprintf(ficlog,"\nLinmin after mnbrak: ax=%12.7f xx=%12.7f bx=%12.7f fa=%12.2f fx=%12.2f fb=%12.2f\n", ax,xx,bx,fa,fx,fb);
1.191 brouard 2601: #endif
1.224 brouard 2602: #ifdef LINMINORIGINAL
2603: #else
1.317 brouard 2604: if(fb == fx){ /* Flat function in the direction */
2605: xmin=xx;
1.224 brouard 2606: *flat=1;
1.317 brouard 2607: }else{
1.224 brouard 2608: *flat=0;
2609: #endif
2610: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2611: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2612: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2613: /* fmin = f(p[j] + xmin * xi[j]) */
2614: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2615: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2616: #ifdef DEBUG
1.224 brouard 2617: printf("retour brent from bracket (a=%lf fa=%lf, xx=%lf fx=%lf, b=%lf fb=%lf): fret=%lf xmin=%lf\n",ax,fa,xx,fx,bx,fb,*fret,xmin);
2618: fprintf(ficlog,"retour brent from bracket (a=%lf fa=%lf, xx=%lf fx=%lf, b=%lf fb=%lf): fret=%lf xmin=%lf\n",ax,fa,xx,fx,bx,fb,*fret,xmin);
2619: #endif
2620: #ifdef LINMINORIGINAL
2621: #else
2622: }
1.126 brouard 2623: #endif
1.191 brouard 2624: #ifdef DEBUGLINMIN
2625: printf("linmin end ");
1.202 brouard 2626: fprintf(ficlog,"linmin end ");
1.191 brouard 2627: #endif
1.126 brouard 2628: for (j=1;j<=n;j++) {
1.203 brouard 2629: #ifdef LINMINORIGINAL
2630: xi[j] *= xmin;
2631: #else
2632: #ifdef DEBUGLINMIN
2633: if(xxs <1.0)
2634: printf(" before xi[%d]=%12.8f", j,xi[j]);
2635: #endif
2636: xi[j] *= xmin*xxs; /* xi rescaled by xmin and number of loops: if xmin=-1.237 and xi=(1,0,...,0) xi=(-1.237,0,...,0) */
2637: #ifdef DEBUGLINMIN
2638: if(xxs <1.0)
2639: printf(" after xi[%d]=%12.8f, xmin=%12.8f, ax=%12.8f, xx=%12.8f, bx=%12.8f, xxs=%12.8f", j,xi[j], xmin, ax, xx, bx,xxs );
2640: #endif
2641: #endif
1.187 brouard 2642: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2643: }
1.191 brouard 2644: #ifdef DEBUGLINMIN
1.203 brouard 2645: printf("\n");
1.191 brouard 2646: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2647: fprintf(ficlog,"Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.191 brouard 2648: for (j=1;j<=n;j++) {
1.202 brouard 2649: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2650: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2651: if(j % ncovmodel == 0){
1.191 brouard 2652: printf("\n");
1.202 brouard 2653: fprintf(ficlog,"\n");
2654: }
1.191 brouard 2655: }
1.203 brouard 2656: #else
1.191 brouard 2657: #endif
1.126 brouard 2658: free_vector(xicom,1,n);
2659: free_vector(pcom,1,n);
2660: }
2661:
1.359 brouard 2662: /**** praxis gegen ****/
2663:
2664: /* This has been tested by Visual C from Microsoft and works */
2665: /* meaning tha valgrind could be wrong */
2666: /*********************************************************************/
2667: /* f u n c t i o n p r a x i s */
2668: /* */
2669: /* praxis is a general purpose routine for the minimization of a */
2670: /* function in several variables. the algorithm used is a modifi- */
2671: /* cation of conjugate gradient search method by powell. the changes */
2672: /* are due to r.p. brent, who gives an algol-w program, which served */
2673: /* as a basis for this function. */
2674: /* */
2675: /* references: */
2676: /* - powell, m.j.d., 1964. an efficient method for finding */
2677: /* the minimum of a function in several variables without */
2678: /* calculating derivatives, computer journal, 7, 155-162 */
2679: /* - brent, r.p., 1973. algorithms for minimization without */
2680: /* derivatives, prentice hall, englewood cliffs. */
2681: /* */
2682: /* problems, suggestions or improvements are always wellcome */
2683: /* karl gegenfurtner 07/08/87 */
2684: /* c - version */
2685: /*********************************************************************/
2686: /* */
2687: /* usage: min = praxis(tol, macheps, h, n, prin, x, func) */
2688: /* macheps has been suppressed because it is replaced by DBL_EPSILON */
2689: /* and if it was an argument of praxis (as it is in original brent) */
2690: /* it should be declared external */
2691: /* usage: min = praxis(tol, h, n, prin, x, func) */
2692: /* was min = praxis(fun, x, n); */
2693: /* */
2694: /* fun the function to be minimized. fun is called from */
2695: /* praxis with x and n as arguments */
2696: /* x a double array containing the initial guesses for */
2697: /* the minimum, which will contain the solution on */
2698: /* return */
2699: /* n an integer specifying the number of unknown */
2700: /* parameters */
2701: /* min praxis returns the least calculated value of fun */
2702: /* */
2703: /* some additional global variables control some more aspects of */
2704: /* the inner workings of praxis. setting them is optional, they */
2705: /* are all set to some reasonable default values given below. */
2706: /* */
2707: /* prin controls the printed output from the routine. */
2708: /* 0 -> no output */
2709: /* 1 -> print only starting and final values */
2710: /* 2 -> detailed map of the minimization process */
2711: /* 3 -> print also eigenvalues and vectors of the */
2712: /* search directions */
2713: /* the default value is 1 */
2714: /* tol is the tolerance allowed for the precision of the */
2715: /* solution. praxis returns if the criterion */
2716: /* 2 * ||x[k]-x[k-1]|| <= sqrt(macheps) * ||x[k]|| + tol */
2717: /* is fulfilled more than ktm times. */
2718: /* the default value depends on the machine precision */
2719: /* ktm see just above. default is 1, and a value of 4 leads */
2720: /* to a very(!) cautious stopping criterion. */
2721: /* h0 or step is a steplength parameter and should be set equal */
2722: /* to the expected distance from the solution. */
2723: /* exceptionally small or large values of step lead to */
2724: /* slower convergence on the first few iterations */
2725: /* the default value for step is 1.0 */
2726: /* scbd is a scaling parameter. 1.0 is the default and */
2727: /* indicates no scaling. if the scales for the different */
2728: /* parameters are very different, scbd should be set to */
2729: /* a value of about 10.0. */
2730: /* illc should be set to true (1) if the problem is known to */
2731: /* be ill-conditioned. the default is false (0). this */
2732: /* variable is automatically set, when praxis finds */
2733: /* the problem to be ill-conditioned during iterations. */
2734: /* maxfun is the maximum number of calls to fun allowed. praxis */
2735: /* will return after maxfun calls to fun even when the */
2736: /* minimum is not yet found. the default value of 0 */
2737: /* indicates no limit on the number of calls. */
2738: /* this return condition is only checked every n */
2739: /* iterations. */
2740: /* */
2741: /*********************************************************************/
2742:
2743: #include <math.h>
2744: #include <stdio.h>
2745: #include <stdlib.h>
2746: #include <float.h> /* for DBL_EPSILON */
2747: /* #include "machine.h" */
2748:
2749:
2750: /* extern void minfit(int n, double eps, double tol, double **ab, double q[]); */
2751: /* extern void minfit(int n, double eps, double tol, double ab[N][N], double q[]); */
2752: /* control parameters */
2753: /* control parameters */
2754: #define SQREPSILON 1.0e-19
2755: /* #define EPSILON 1.0e-8 */ /* in main */
2756:
2757: double tol = SQREPSILON,
2758: scbd = 1.0,
2759: step = 1.0;
2760: int ktm = 1,
2761: /* prin = 2, */
2762: maxfun = 0,
2763: illc = 0;
2764:
2765: /* some global variables */
2766: static int i, j, k, k2, nl, nf, kl, kt;
2767: /* static double s; */
2768: double sl, dn, dmin,
2769: fx, f1, lds, ldt, sf, df,
2770: qf1, qd0, qd1, qa, qb, qc,
2771: m2, m4, small_windows, vsmall, large,
2772: vlarge, ldfac, t2;
2773: /* static double d[N], y[N], z[N], */
2774: /* q0[N], q1[N], v[N][N]; */
2775:
2776: static double *d, *y, *z;
2777: static double *q0, *q1, **v;
2778: double *tflin; /* used in flin: return (*fun)(tflin, n); */
2779: double *e; /* used in minfit, don't konw how to free memory and thus made global */
2780: /* static double s, sl, dn, dmin, */
2781: /* fx, f1, lds, ldt, sf, df, */
2782: /* qf1, qd0, qd1, qa, qb, qc, */
2783: /* m2, m4, small, vsmall, large, */
2784: /* vlarge, ldfac, t2; */
2785: /* static double d[N], y[N], z[N], */
2786: /* q0[N], q1[N], v[N][N]; */
2787:
2788: /* these will be set by praxis to point to it's arguments */
2789: static int prin; /* added */
2790: static int n;
2791: static double *x;
2792: static double (*fun)();
2793: /* static double (*fun)(double *x, int n); */
2794:
2795: /* these will be set by praxis to the global control parameters */
2796: /* static double h, macheps, t; */
2797: extern double macheps;
2798: static double h;
2799: static double t;
2800:
2801: static double
2802: drandom() /* return random no between 0 and 1 */
2803: {
2804: return (double)(rand()%(8192*2))/(double)(8192*2);
2805: }
2806:
2807: static void sort() /* d and v in descending order */
2808: {
2809: int k, i, j;
2810: double s;
2811:
2812: for (i=1; i<=n-1; i++) {
2813: k = i; s = d[i];
2814: for (j=i+1; j<=n; j++) {
2815: if (d[j] > s) {
2816: k = j;
2817: s = d[j];
2818: }
2819: }
2820: if (k > i) {
2821: d[k] = d[i];
2822: d[i] = s;
2823: for (j=1; j<=n; j++) {
2824: s = v[j][i];
2825: v[j][i] = v[j][k];
2826: v[j][k] = s;
2827: }
2828: }
2829: }
2830: }
2831:
2832: double randbrent ( int *naught )
2833: {
2834: double ran1, ran3[127], half;
2835: int ran2, q, r, i, j;
2836: int init=0; /* false */
2837: double rr;
2838: /* REAL*8 RAN1,RAN3(127),HALF */
2839:
2840: /* INTEGER RAN2,Q,R */
2841: /* LOGICAL INIT */
2842: /* DATA INIT/.FALSE./ */
2843: /* IF (INIT) GO TO 3 */
2844: if(!init){
2845: /* R = MOD(NAUGHT,8190) + 1 *//* 1804289383 rand () */
2846: r = *naught % 8190 + 1;/* printf(" naught r %d %d",*naught,r); */
2847: ran2=127;
2848: for(i=ran2; i>0; i--){
2849: /* RAN2 = 128 */
2850: /* DO 2 I=1,127 */
2851: ran2 = ran2-1;
2852: /* RAN2 = RAN2 - 1 */
2853: ran1 = -pow(2.0,55);
2854: /* RAN1 = -2.D0**55 */
2855: /* DO 1 J=1,7 */
2856: for(j=1; j<=7;j++){
2857: /* R = MOD(1756*R,8191) */
2858: r = (1756*r) % 8191;/* printf(" i=%d (1756*r)%8191=%d",j,r); */
2859: q=r/32;
2860: /* Q = R/32 */
2861: /* 1 RAN1 = (RAN1 + Q)*(1.0D0/256) */
2862: ran1 =(ran1+q)*(1.0/256);
2863: }
2864: /* 2 RAN3(RAN2) = RAN1 */
2865: ran3[ran2] = ran1; /* printf(" ran2=%d ran1=%.7g \n",ran2,ran1); */
2866: }
2867: /* INIT = .TRUE. */
2868: init=1;
2869: /* 3 IF (RAN2.EQ.1) RAN2 = 128 */
2870: }
2871: if(ran2 == 0) ran2 = 126;
2872: else ran2 = ran2 -1;
2873: /* RAN2 = RAN2 - 1 */
2874: /* RAN1 = RAN1 + RAN3(RAN2) */
2875: ran1 = ran1 + ran3[ran2];/* printf("BIS ran2=%d ran1=%.7g \n",ran2,ran1); */
2876: half= 0.5;
2877: /* HALF = .5D0 */
2878: /* IF (RAN1.GE.0.D0) HALF = -HALF */
2879: if(ran1 >= 0.) half =-half;
2880: ran1 = ran1 +half;
2881: ran3[ran2] = ran1;
2882: rr= ran1+0.5;
2883: /* RAN1 = RAN1 + HALF */
2884: /* RAN3(RAN2) = RAN1 */
2885: /* RANDOM = RAN1 + .5D0 */
2886: /* r = ( ( double ) ( *seed ) ) * 4.656612875E-10; */
2887: return rr;
2888: }
2889: static void matprint(char *s, double **v, int m, int n)
2890: /* char *s; */
2891: /* double v[N][N]; */
2892: {
2893: #define INCX 8
2894: int i;
2895:
2896: int i2hi;
2897: int ihi;
2898: int ilo;
2899: int i2lo;
2900: int jlo=1;
2901: int j;
2902: int j2hi;
2903: int jhi;
2904: int j2lo;
2905: ilo=1;
2906: ihi=n;
2907: jlo=1;
2908: jhi=n;
2909:
2910: printf ("\n" );
2911: printf ("%s\n", s );
2912: for ( j2lo = jlo; j2lo <= jhi; j2lo = j2lo + INCX )
2913: {
2914: j2hi = j2lo + INCX - 1;
2915: if ( n < j2hi )
2916: {
2917: j2hi = n;
2918: }
2919: if ( jhi < j2hi )
2920: {
2921: j2hi = jhi;
2922: }
2923:
2924: /* fprintf ( ficlog, "\n" ); */
2925: printf ("\n" );
2926: /*
2927: For each column J in the current range...
2928:
2929: Write the header.
2930: */
2931: /* fprintf ( ficlog, " Col: "); */
2932: printf ("Col:");
2933: for ( j = j2lo; j <= j2hi; j++ )
2934: {
2935: /* fprintf ( ficlog, " %7d ", j - 1 ); */
2936: /* printf (" %9d ", j - 1 ); */
2937: printf (" %9d ", j );
2938: }
2939: /* fprintf ( ficlog, "\n" ); */
2940: /* fprintf ( ficlog, " Row\n" ); */
2941: /* fprintf ( ficlog, "\n" ); */
2942: printf ("\n" );
2943: printf (" Row\n" );
2944: printf ("\n" );
2945: /*
2946: Determine the range of the rows in this strip.
2947: */
2948: if ( 1 < ilo ){
2949: i2lo = ilo;
2950: }else{
2951: i2lo = 1;
2952: }
2953: if ( m < ihi ){
2954: i2hi = m;
2955: }else{
2956: i2hi = ihi;
2957: }
2958:
2959: for ( i = i2lo; i <= i2hi; i++ ){
2960: /*
2961: Print out (up to) 5 entries in row I, that lie in the current strip.
2962: */
2963: /* fprintf ( ficlog, "%5d:", i - 1 ); */
2964: /* printf ("%5d:", i - 1 ); */
2965: printf ("%5d:", i );
2966: for ( j = j2lo; j <= j2hi; j++ )
2967: {
2968: /* fprintf ( ficlog, " %14g", a[i-1+(j-1)*m] ); */
2969: /* printf ("%14.7g ", a[i-1+(j-1)*m] ); */
2970: /* printf("%14.7f ", v[i-1][j-1]); */
2971: printf("%14.7f ", v[i][j]);
2972: /* fprintf ( stdout, " %14g", a[i-1+(j-1)*m] ); */
2973: }
2974: /* fprintf ( ficlog, "\n" ); */
2975: printf ("\n" );
2976: }
2977: }
2978:
2979: /* printf("%s\n", s); */
2980: /* for (k=0; k<n; k++) { */
2981: /* for (i=0; i<n; i++) { */
2982: /* /\* printf("%20.10e ", v[k][i]); *\/ */
2983: /* } */
2984: /* printf("\n"); */
2985: /* } */
2986: #undef INCX
2987: }
2988:
2989: void vecprint(char *s, double *x, int n)
2990: /* char *s; */
2991: /* double x[N]; */
2992: {
2993: int i=0;
2994:
2995: printf(" %s", s);
2996: /* for (i=0; i<n; i++) */
2997: for (i=1; i<=n; i++)
2998: printf (" %14.7g", x[i] );
2999: /* printf(" %8d: %14g\n", i, x[i]); */
3000: printf ("\n" );
3001: }
3002:
3003: static void print() /* print a line of traces */
3004: {
3005:
3006:
3007: printf("\n");
3008: /* printf("... chi square reduced to ... %20.10e\n", fx); */
3009: /* printf("... after %u function calls ...\n", nf); */
3010: /* printf("... including %u linear searches ...\n", nl); */
3011: printf("%10d %10d%14.7g",nl, nf, fx);
3012: vecprint("... current values of x ...", x, n);
3013: }
3014: /* static void print2(int n, double *x, int prin, double fx, int nf, int nl) */ /* print a line of traces */
3015: static void print2() /* print a line of traces */
3016: {
3017: int i; double fmin=0.;
3018:
3019: /* printf("\n"); */
3020: /* printf("... chi square reduced to ... %20.10e\n", fx); */
3021: /* printf("... after %u function calls ...\n", nf); */
3022: /* printf("... including %u linear searches ...\n", nl); */
3023: /* printf("%10d %10d%14.7g",nl, nf, fx); */
1.363 brouard 3024: /* printf ( "\n" ); */
1.359 brouard 3025: printf ( " Linear searches %d", nl );
1.364 ! brouard 3026: fprintf (ficlog, " Linear searches %d", nl );
1.359 brouard 3027: /* printf ( " Linear searches %d\n", nl ); */
3028: /* printf ( " Function evaluations %d\n", nf ); */
3029: /* printf ( " Function value FX = %g\n", fx ); */
3030: printf ( " Function evaluations %d", nf );
3031: printf ( " Function value FX = %.12lf\n", fx );
1.363 brouard 3032: fprintf (ficlog, " Function evaluations %d", nf );
3033: fprintf (ficlog, " Function value FX = %.12lf\n", fx );
1.359 brouard 3034: #ifdef DEBUGPRAX
3035: printf("n=%d prin=%d\n",n,prin);
3036: #endif
1.363 brouard 3037: /* if(fx <= fmin) printf(" UNDEFINED "); else printf("%14.7g",log(fx-fmin)); */
1.359 brouard 3038: if ( n <= 4 || 2 < prin )
3039: {
3040: /* for(i=1;i<=n;i++)printf("%14.7g",x[i-1]); */
1.363 brouard 3041: for(i=1;i<=n;i++){
1.364 ! brouard 3042: printf(" %14.7g",x[i]);
! 3043: fprintf(ficlog," %14.7g",x[i]);
1.363 brouard 3044: }
1.359 brouard 3045: /* r8vec_print ( n, x, " X:" ); */
3046: }
3047: printf("\n");
1.363 brouard 3048: fprintf(ficlog,"\n");
1.359 brouard 3049: }
3050:
3051:
3052: /* #ifdef MSDOS */
3053: /* static double tflin[N]; */
3054: /* #endif */
3055:
3056: static double flin(double l, int j)
3057: /* double l; */
3058: {
3059: int i;
3060: /* #ifndef MSDOS */
3061: /* double tflin[N]; */
3062: /* #endif */
3063: /* double *tflin; */ /* Be careful to put tflin on a vector n */
3064:
3065: /* j is used from 0 to n-1 and can be -1 for parabolic search */
3066:
3067: /* if (j != -1) { /\* linear search *\/ */
3068: if (j > 0) { /* linear search */
3069: /* for (i=0; i<n; i++){ */
3070: for (i=1; i<=n; i++){
3071: tflin[i] = x[i] + l *v[i][j];
3072: #ifdef DEBUGPRAX
3073: /* printf(" flin i=%14d t=%14.7f x=%14.7f l=%14.7f v[%d,%d]=%14.7f nf=%14d\n",i+1, tflin[i],x[i],l,i,j,v[i][j],nf); */
3074: printf(" flin i=%14d t=%14.7f x=%14.7f l=%14.7f v[%d,%d]=%14.7f nf=%14d\n",i, tflin[i],x[i],l,i,j,v[i][j],nf);
3075: #endif
3076: }
3077: }
3078: else { /* search along parabolic space curve */
3079: qa = l*(l-qd1)/(qd0*(qd0+qd1));
3080: qb = (l+qd0)*(qd1-l)/(qd0*qd1);
3081: qc = l*(l+qd0)/(qd1*(qd0+qd1));
3082: #ifdef DEBUGPRAX
3083: printf(" search along a parabolic space curve. j=%14d nf=%14d l=%14.7f qd0=%14.7f qd1=%14.7f\n",j,nf,l,qd0,qd1);
3084: #endif
3085: /* for (i=0; i<n; i++){ */
3086: for (i=1; i<=n; i++){
3087: tflin[i] = qa*q0[i]+qb*x[i]+qc*q1[i];
3088: #ifdef DEBUGPRAX
3089: /* printf(" parabole i=%14d t(i)=%14.7f q0=%14.7f x=%14.7f q1=%14.7f\n",i+1,tflin[i],q0[i],x[i],q1[i]); */
3090: printf(" parabole i=%14d t(i)=%14.7e q0=%14.7e x=%14.7e q1=%14.7e\n",i,tflin[i],q0[i],x[i],q1[i]);
3091: #endif
3092: }
3093: }
3094: nf++;
3095:
3096: #ifdef NR_SHIFT
3097: return (*fun)((tflin-1), n);
3098: #else
3099: /* return (*fun)(tflin, n);*/
3100: return (*fun)(tflin);
3101: #endif
3102: }
3103:
3104: void minny(int j, int nits, double *d2, double *x1, double f1, int fk)
3105: /* double *d2, *x1, f1; */
3106: {
3107: /* here j is from 0 to n-1 and can be -1 for parabolic search */
3108: /* MINIMIZES F FROM X IN THE DIRECTION V(*,J) */
3109: /* UNLESS J<1, WHEN A QUADRATIC SEARCH IS DONE */
3110: /* IN THE PLANE DEFINED BY Q0, Q1 AND X. */
3111: /* D2 AN APPROXIMATION TO HALF F'' (OR ZERO), */
3112: /* X1 AN ESTIMATE OF DISTANCE TO MINIMUM, */
3113: /* RETURNED AS THE DISTANCE FOUND. */
3114: /* IF FK = TRUE THEN F1 IS FLIN(X1), OTHERWISE */
3115: /* X1 AND F1 ARE IGNORED ON ENTRY UNLESS FINAL */
3116: /* FX > F1. NITS CONTROLS THE NUMBER OF TIMES */
3117: /* AN ATTEMPT IS MADE TO HALVE THE INTERVAL. */
3118: /* SIDE EFFECTS: USES AND ALTERS X, FX, NF, NL. */
3119: /* IF J < 1 USES VARIABLES Q... . */
3120: /* USES H, N, T, M2, M4, LDT, DMIN, MACHEPS; */
3121: int k, i, dz;
3122: double x2, xm, f0, f2, fm, d1, t2, sf1, sx1;
3123: double s;
3124: double macheps;
3125: macheps=pow(16.0,-13.0);
3126: sf1 = f1; sx1 = *x1;
3127: k = 0; xm = 0.0; fm = f0 = fx; dz = *d2 < macheps;
3128: /* h=1.0;*/ /* To be revised */
3129: #ifdef DEBUGPRAX
3130: /* printf("min macheps=%14g h=%14g step=%14g t=%14g fx=%14g\n",macheps,h, step,t, fx); */
3131: /* Where is fx coming from */
3132: printf(" min macheps=%14g h=%14g t=%14g fx=%.9lf dirj=%d\n",macheps, h, t, fx, j);
3133: matprint(" min vectors:",v,n,n);
3134: #endif
3135: /* find step size */
3136: s = 0.;
3137: /* for (i=0; i<n; i++) s += x[i]*x[i]; */
3138: for (i=1; i<=n; i++) s += x[i]*x[i];
3139: s = sqrt(s);
3140: if (dz)
3141: t2 = m4*sqrt(fabs(fx)/dmin + s*ldt) + m2*ldt;
3142: else
3143: t2 = m4*sqrt(fabs(fx)/(*d2) + s*ldt) + m2*ldt;
3144: s = s*m4 + t;
3145: if (dz && t2 > s) t2 = s;
3146: if (t2 < small_windows) t2 = small_windows;
3147: if (t2 > 0.01*h) t2 = 0.01 * h;
3148: if (fk && f1 <= fm) {
3149: xm = *x1;
3150: fm = f1;
3151: }
3152: #ifdef DEBUGPRAX
3153: printf(" additional flin X1=%14.7f t2=%14.7f *f1=%14.7f fm=%14.7f fk=%d\n",*x1,t2,f1,fm,fk);
3154: #endif
3155: if (!fk || fabs(*x1) < t2) {
3156: *x1 = (*x1 >= 0 ? t2 : -t2);
3157: /* *x1 = (*x1 > 0 ? t2 : -t2); */ /* kind of error */
3158: #ifdef DEBUGPRAX
3159: printf(" additional flin X1=%16.10e dirj=%d fk=%d\n",*x1, j, fk);
3160: #endif
3161: f1 = flin(*x1, j);
3162: #ifdef DEBUGPRAX
3163: printf(" after flin f1=%18.12e dirj=%d fk=%d\n",f1, j,fk);
3164: #endif
3165: }
3166: if (f1 <= fm) {
3167: xm = *x1;
3168: fm = f1;
3169: }
3170: L0: /*L0 loop or next */
3171: /*
3172: Evaluate FLIN at another point and estimate the second derivative.
3173: */
3174: if (dz) {
3175: x2 = (f0 < f1 ? -(*x1) : 2*(*x1));
3176: #ifdef DEBUGPRAX
3177: printf(" additional second flin x2=%14.8e x1=%14.8e f0=%14.8e f1=%18.12e dirj=%d\n",x2,*x1,f0,f1,j);
3178: #endif
3179: f2 = flin(x2, j);
3180: #ifdef DEBUGPRAX
3181: printf(" additional second flin x2=%16.10e x1=%16.10e f1=%18.12e f0=%18.10e f2=%18.10e fm=%18.10e\n",x2, *x1, f1,f0,f2,fm);
3182: #endif
3183: if (f2 <= fm) {
3184: xm = x2;
3185: fm = f2;
3186: }
3187: /* d2 is the curvature or double difference f1 doesn't seem to be accurately computed */
3188: *d2 = (x2*(f1-f0) - (*x1)*(f2-f0))/((*x1)*x2*((*x1)-x2));
3189: #ifdef DEBUGPRAX
3190: double d11,d12;
3191: d11=(f1-f0)/(*x1);d12=(f2-f0)/x2;
3192: printf(" d11=%18.12e d12=%18.12e d11-d12=%18.12e x1-x2=%18.12e (d11-d12)/(x2-(*x1))=%18.12e\n", d11 ,d12, d11-d12, x2-(*x1), (d11-d12)/(x2-(*x1)));
3193: printf(" original computing f1=%18.12e *d2=%16.10e f0=%18.12e f1-f0=%16.10e f2-f0=%16.10e\n",f1,*d2,f0,f1-f0, f2-f0);
3194: double ff1=7.783920622852e+04;
3195: double f1mf0=9.0344736236e-05;
3196: *d2 = (f1mf0)/ (*x1)/((*x1)-x2) - (f2-f0)/x2/((*x1)-x2);
3197: /* *d2 = (ff1-f0)/ (*x1)/((*x1)-x2) - (f2-f0)/x2/((*x1)-x2); */
3198: printf(" simpliff computing *d2=%16.10e f1mf0=%18.12e,f1=f0+f1mf0=%18.12e\n",*d2,f1mf0,f0+f1mf0);
3199: *d2 = ((f1-f0)/ (*x1) - (f2-f0)/x2)/((*x1)-x2);
3200: printf(" overlifi computing *d2=%16.10e\n",*d2);
3201: #endif
3202: *d2 = ((f1-f0)/ (*x1) - (f2-f0)/x2)/((*x1)-x2);
3203: }
3204: #ifdef DEBUGPRAX
3205: printf(" additional second flin xm=%14.8e fm=%14.8e *d2=%14.8e\n",xm, fm,*d2);
3206: #endif
3207: /*
3208: Estimate the first derivative at 0.
3209: */
3210: d1 = (f1-f0)/(*x1) - *x1**d2; dz = 1;
3211: /*
3212: Predict the minimum.
3213: */
3214: if (*d2 <= small_windows) {
3215: x2 = (d1 < 0 ? h : -h);
3216: }
3217: else {
3218: x2 = - 0.5*d1/(*d2);
3219: }
3220: #ifdef DEBUGPRAX
3221: printf(" AT d1=%14.8e d2=%14.8e small=%14.8e dz=%d x1=%14.8e x2=%14.8e\n",d1,*d2,small_windows,dz,*x1,x2);
3222: #endif
3223: if (fabs(x2) > h)
3224: x2 = (x2 > 0 ? h : -h);
3225: L1: /* L1 or try loop */
3226: #ifdef DEBUGPRAX
3227: printf(" AT predicted minimum flin x2=%14.8e x1=%14.8e K=%14d NITS=%14d dirj=%d\n",x2,*x1,k,nits,j);
3228: #endif
3229: f2 = flin(x2, j); /* x[i]+x2*v[i][j] */
3230: #ifdef DEBUGPRAX
3231: printf(" after flin f0=%14.8e f1=%14.8e f2=%14.8e fm=%14.8e\n",f0,f1,f2, fm);
3232: #endif
3233: if ((k < nits) && (f2 > f0)) {
3234: #ifdef DEBUGPRAX
3235: printf(" NO SUCCESS SO TRY AGAIN;\n");
3236: #endif
3237: k++;
3238: if ((f0 < f1) && (*x1*x2 > 0.0))
3239: goto L0; /* or next */
3240: x2 *= 0.5;
3241: goto L1;
3242: }
3243: nl++;
3244: #ifdef DEBUGPRAX
3245: printf(" bebeBE end of min x1=%14.8e x2=%14.8e f1=%14.8e f2=%14.8e f0=%14.8e fm=%14.8e d2=%14.8e\n",*x1, x2, f1, f2, f0, fm, *d2);
3246: #endif
3247: if (f2 > fm) x2 = xm; else fm = f2;
3248: if (fabs(x2*(x2-*x1)) > small_windows) {
3249: *d2 = (x2*(f1-f0) - *x1*(fm-f0))/(*x1*x2*(*x1-x2));
3250: }
3251: else {
3252: if (k > 0) *d2 = 0;
3253: }
3254: #ifdef DEBUGPRAX
1.362 brouard 3255: printf(" bebe end of min x1 might be very wrong x1=%14.8e fx=%14.8e d2=%14.8e\n",*x1, fx, *d2);
1.359 brouard 3256: #endif
3257: if (*d2 <= small_windows) *d2 = small_windows;
3258: *x1 = x2; fx = fm;
3259: if (sf1 < fx) {
3260: fx = sf1;
3261: *x1 = sx1;
3262: }
3263: /*
3264: Update X for linear search.
3265: */
3266: #ifdef DEBUGPRAX
3267: printf(" end of min x1=%14.8e fx=%14.8e d2=%14.8e\n",*x1, fx, *d2);
3268: #endif
3269:
3270: /* if (j != -1) */
3271: /* for (i=0; i<n; i++) */
3272: /* x[i] += (*x1)*v[i][j]; */
3273: if (j > 0)
3274: for (i=1; i<=n; i++)
3275: x[i] += (*x1)*v[i][j];
3276: }
3277:
3278: void quad() /* look for a minimum along the curve q0, q1, q2 */
3279: {
3280: int i;
3281: double l, s;
3282:
3283: s = fx; fx = qf1; qf1 = s; qd1 = 0.0;
3284: /* for (i=0; i<n; i++) { */
3285: for (i=1; i<=n; i++) {
3286: s = x[i]; l = q1[i]; x[i] = l; q1[i] = s;
3287: qd1 = qd1 + (s-l)*(s-l);
3288: }
3289: s = 0.0; qd1 = sqrt(qd1); l = qd1;
3290: #ifdef DEBUGPRAX
3291: printf(" QUAD after sqrt qd1=%14.8e \n",qd1);
3292: #endif
3293:
3294: if (qd0>0.0 && qd1>0.0 &&nl>=3*n*n) {
3295: #ifdef DEBUGPRAX
3296: printf(" QUAD before min value=%14.8e \n",qf1);
3297: #endif
3298: /* min(-1, 2, &s, &l, qf1, 1); */
3299: minny(0, 2, &s, &l, qf1, 1);
3300: qa = l*(l-qd1)/(qd0*(qd0+qd1));
3301: qb = (l+qd0)*(qd1-l)/(qd0*qd1);
3302: qc = l*(l+qd0)/(qd1*(qd0+qd1));
3303: }
3304: else {
3305: fx = qf1; qa = qb = 0.0; qc = 1.0;
3306: }
3307: #ifdef DEBUGPRAX
3308: printf("after eventual min qd0=%14.8e qd1=%14.8e nl=%d\n",qd0, qd1,nl);
3309: #endif
3310: qd0 = qd1;
3311: /* for (i=0; i<n; i++) { */
3312: for (i=1; i<=n; i++) {
3313: s = q0[i]; q0[i] = x[i];
3314: x[i] = qa*s + qb*x[i] + qc*q1[i];
3315: }
3316: #ifdef DEBUGQUAD
3317: vecprint ( " X after QUAD:" , x, n );
3318: #endif
3319: }
3320:
3321: /* void minfit(int n, double eps, double tol, double ab[N][N], double q[]) */
3322: void minfit(int n, double eps, double tol, double **ab, double q[])
3323: /* int n; */
3324: /* double eps, tol, ab[N][N], q[N]; */
3325: {
3326: int l, kt, l2, i, j, k;
3327: double c, f, g, h, s, x, y, z;
3328: /* double eps; */
3329: /* #ifndef MSDOS */
3330: /* double e[N]; /\* plenty of stack on a vax *\/ */
3331: /* #endif */
3332: /* double *e; */
3333: /* e=vector(0,n-1); /\* should be freed somewhere but gotos *\/ */
3334:
3335: /* householder's reduction to bidiagonal form */
3336:
3337: if(n==1){
3338: /* q[1-1]=ab[1-1][1-1]; */
3339: /* ab[1-1][1-1]=1.0; */
3340: q[1]=ab[1][1];
3341: ab[1][1]=1.0;
3342: return; /* added from hardt */
3343: }
3344: /* eps=macheps; */ /* added */
3345: x = g = 0.0;
3346: #ifdef DEBUGPRAX
3347: matprint (" HOUSE holder:", ab, n, n);
3348: #endif
3349:
3350: /* for (i=0; i<n; i++) { /\* FOR I := 1 UNTIL N DO *\/ */
3351: for (i=1; i<=n; i++) { /* FOR I := 1 UNTIL N DO */
3352: e[i] = g; s = 0.0; l = i+1;
3353: /* for (j=i; j<n; j++) /\* FOR J := I UNTIL N DO S := S*AB(J,I)**2; *\/ /\* not correct *\/ */
3354: for (j=i; j<=n; j++) /* FOR J := I UNTIL N DO S := S*AB(J,I)**2; */ /* not correct */
3355: s += ab[j][i] * ab[j][i];
3356: #ifdef DEBUGPRAXFIN
3357: printf("i=%d s=%d %.7g tol=%.7g",i,s,tol);
3358: #endif
3359: if (s < tol) {
3360: g = 0.0;
3361: }
3362: else {
3363: /* f = ab[i][i]; */
3364: f = ab[i][i];
3365: if (f < 0.0)
3366: g = sqrt(s);
3367: else
3368: g = -sqrt(s);
3369: /* h = f*g - s; ab[i][i] = f - g; */
3370: h = f*g - s; ab[i][i] = f - g;
3371: /* for (j=l; j<n; j++) { */ /* FOR J := L UNTIL N DO */ /* wrong */
3372: for (j=l; j<=n; j++) {
3373: f = 0.0;
3374: /* for (k=i; k<n; k++) /\* FOR K := I UNTIL N DO *\/ /\* wrong *\/ */
3375: for (k=i; k<=n; k++) /* FOR K := I UNTIL N DO */
3376: /* f += ab[k][i] * ab[k][j]; */
3377: f += ab[k][i] * ab[k][j];
3378: f /= h;
3379: for (k=i; k<=n; k++) /* FOR K := I UNTIL N DO */
3380: /* for (k=i; k<n; k++)/\* FOR K := I UNTIL N DO *\/ /\* wrong *\/ */
3381: ab[k][j] += f * ab[k][i];
3382: /* ab[k][j] += f * ab[k][i]; */
3383: #ifdef DEBUGPRAX
3384: printf("Holder J=%d F=%.7g",j,f);
3385: #endif
3386: }
3387: } /* end s */
3388: /* q[i] = g; s = 0.0; */
3389: q[i] = g; s = 0.0;
3390: #ifdef DEBUGPRAX
3391: printf(" I Q=%d %.7g",i,q[i]);
3392: #endif
3393:
3394: /* if (i < n) */
3395: /* if (i <= n) /\* I is always lower or equal to n wasn't in golub reinsch*\/ */
3396: /* for (j=l; j<n; j++) */
3397: for (j=l; j<=n; j++)
3398: s += ab[i][j] * ab[i][j];
3399: /* s += ab[i][j] * ab[i][j]; */
3400: if (s < tol) {
3401: g = 0.0;
3402: }
3403: else {
3404: if(i<n)
3405: /* f = ab[i][i+1]; */ /* Brent golub overflow */
3406: f = ab[i][i+1];
3407: if (f < 0.0)
3408: g = sqrt(s);
3409: else
3410: g = - sqrt(s);
3411: h = f*g - s;
3412: /* h = f*g - s; ab[i][i+1] = f - g; */ /* Overflow for i=n Error in Golub too but not Burkardt*/
3413: /* for (j=l; j<n; j++) */
3414: /* e[j] = ab[i][j]/h; */
3415: if(i<n){
3416: ab[i][i+1] = f - g;
3417: for (j=l; j<=n; j++)
3418: e[j] = ab[i][j]/h;
3419: /* for (j=l; j<n; j++) { */
3420: for (j=l; j<=n; j++) {
3421: s = 0.0;
3422: /* for (k=l; k<n; k++) s += ab[j][k]*ab[i][k]; */
3423: for (k=l; k<=n; k++) s += ab[j][k]*ab[i][k];
3424: /* for (k=l; k<n; k++) ab[j][k] += s * e[k]; */
3425: for (k=l; k<=n; k++) ab[j][k] += s * e[k];
3426: } /* END J */
3427: } /* END i <n */
3428: } /* end s */
3429: /* y = fabs(q[i]) + fabs(e[i]); */
3430: y = fabs(q[i]) + fabs(e[i]);
3431: if (y > x) x = y;
3432: #ifdef DEBUGPRAX
3433: printf(" I Y=%d %.7g",i,y);
3434: #endif
3435: #ifdef DEBUGPRAX
3436: printf(" i=%d e(i) %.7g",i,e[i]);
3437: #endif
3438: } /* end i */
3439: /*
3440: Accumulation of right hand transformations */
3441: /* for (i=n-1; i >= 0; i--) { */ /* FOR I := N STEP -1 UNTIL 1 DO */
3442: /* We should avoid the overflow in Golub */
3443: /* ab[n-1][n-1] = 1.0; */
3444: /* g = e[n-1]; */
3445: ab[n][n] = 1.0;
3446: g = e[n];
3447: l = n;
3448:
3449: /* for (i=n; i >= 1; i--) { */
3450: for (i=n-1; i >= 1; i--) { /* n-1 loops, different from brent and golub*/
3451: if (g != 0.0) {
3452: /* h = ab[i-1][i]*g; */
3453: h = ab[i][i+1]*g;
3454: for (j=l; j<=n; j++) ab[j][i] = ab[i][j] / h;
3455: for (j=l; j<=n; j++) {
3456: /* h = ab[i][i+1]*g; */
3457: /* for (j=l; j<n; j++) ab[j][i] = ab[i][j] / h; */
3458: /* for (j=l; j<n; j++) { */
3459: s = 0.0;
3460: /* for (k=l; k<n; k++) s += ab[i][k] * ab[k][j]; */
3461: /* for (k=l; k<n; k++) ab[k][j] += s * ab[k][i]; */
3462: for (k=l; k<=n; k++) s += ab[i][k] * ab[k][j];
3463: for (k=l; k<=n; k++) ab[k][j] += s * ab[k][i];
3464: }/* END J */
3465: }/* END G */
3466: /* for (j=l; j<n; j++) */
3467: /* ab[i][j] = ab[j][i] = 0.0; */
3468: /* ab[i][i] = 1.0; g = e[i]; l = i; */
3469: for (j=l; j<=n; j++)
3470: ab[i][j] = ab[j][i] = 0.0;
3471: ab[i][i] = 1.0; g = e[i]; l = i;
3472: }/* END I */
3473: #ifdef DEBUGPRAX
3474: matprint (" HOUSE accumulation:",ab,n, n );
3475: #endif
3476:
3477: /* diagonalization to bidiagonal form */
3478: eps *= x;
3479: /* for (k=n-1; k>= 0; k--) { */
3480: for (k=n; k>= 1; k--) {
3481: kt = 0;
3482: TestFsplitting:
3483: #ifdef DEBUGPRAX
3484: printf(" TestFsplitting: k=%d kt=%d\n",k,kt);
3485: /* for(i=1;i<=n;i++)printf(" e(%d)=%.14f",i,e[i]);printf("\n"); */
3486: #endif
3487: kt = kt+1;
3488: /* TestFsplitting: */
3489: /* if (++kt > 30) { */
3490: if (kt > 30) {
3491: e[k] = 0.0;
3492: fprintf(stderr, "\n+++ MINFIT - Fatal error\n");
3493: fprintf ( stderr, " The QR algorithm failed to converge.\n" );
3494: }
3495: /* for (l2=k; l2>=0; l2--) { */
3496: for (l2=k; l2>=1; l2--) {
3497: l = l2;
3498: #ifdef DEBUGPRAX
3499: printf(" l e(l)< eps %d %.7g %.7g ",l,e[l], eps);
3500: #endif
3501: /* if (fabs(e[l]) <= eps) */
3502: if (fabs(e[l]) <= eps)
3503: goto TestFconvergence;
3504: /* if (fabs(q[l-1]) <= eps)*/ /* missing if ( 1 < l ){ *//* printf(" q(l-1)< eps %d %.7g %.7g ",l-1,q[l-2], eps); */
3505: if (fabs(q[l-1]) <= eps)
3506: break; /* goto Cancellation; */
3507: }
3508: Cancellation:
3509: #ifdef DEBUGPRAX
3510: printf(" Cancellation:\n");
3511: #endif
3512: c = 0.0; s = 1.0;
3513: for (i=l; i<=k; i++) {
3514: f = s * e[i]; e[i] *= c;
3515: /* f = s * e[i]; e[i] *= c; */
3516: if (fabs(f) <= eps)
3517: goto TestFconvergence;
3518: /* g = q[i]; */
3519: g = q[i];
3520: if (fabs(f) < fabs(g)) {
3521: double fg = f/g;
3522: h = fabs(g)*sqrt(1.0+fg*fg);
3523: }
3524: else {
3525: double gf = g/f;
3526: h = (f!=0.0 ? fabs(f)*sqrt(1.0+gf*gf) : 0.0);
3527: }
3528: /* COMMENT: THE ABOVE REPLACES Q(I):=H:=LONGSQRT(G*G+F*F) */
3529: /* WHICH MAY GIVE INCORRECT RESULTS IF THE */
3530: /* SQUARES UNDERFLOW OR IF F = G = 0; */
3531:
3532: /* q[i] = h; */
3533: q[i] = h;
3534: if (h == 0.0) { h = 1.0; g = 1.0; }
3535: c = g/h; s = -f/h;
3536: }
3537: TestFconvergence:
3538: #ifdef DEBUGPRAX
3539: printf(" TestFconvergence: l=%d k=%d\n",l,k);
3540: #endif
3541: /* z = q[k]; */
3542: z = q[k];
3543: if (l == k)
3544: goto Convergence;
3545: /* shift from bottom 2x2 minor */
3546: /* x = q[l]; y = q[k-l]; g = e[k-1]; h = e[k]; */ /* Error */
3547: x = q[l]; y = q[k-1]; g = e[k-1]; h = e[k];
3548: f = ((y-z)*(y+z) + (g-h)*(g+h)) / (2.0*h*y);
3549: g = sqrt(f*f+1.0);
3550: if (f <= 0.0)
3551: f = ((x-z)*(x+z) + h*(y/(f-g)-h))/x;
3552: else
3553: f = ((x-z)*(x+z) + h*(y/(f+g)-h))/x;
3554: /* next qr transformation */
3555: s = c = 1.0;
3556: for (i=l+1; i<=k; i++) {
3557: #ifdef DEBUGPRAXQR
3558: printf(" Before Mid TestFconvergence: l+1=%d i=%d k=%d h=%.6e e(i)=%14.8f e(i-1)=%14.8f\n",l+1,i,k, h, e[i],e[i-1]);
3559: #endif
3560: /* g = e[i]; y = q[i]; h = s*g; g *= c; */
3561: g = e[i]; y = q[i]; h = s*g; g *= c;
3562: if (fabs(f) < fabs(h)) {
3563: double fh = f/h;
3564: z = fabs(h) * sqrt(1.0 + fh*fh);
3565: }
3566: else {
3567: double hf = h/f;
3568: z = (f!=0.0 ? fabs(f)*sqrt(1.0+hf*hf) : 0.0);
3569: }
3570: /* e[i-1] = z; */
3571: e[i-1] = z;
3572: #ifdef DEBUGPRAXQR
3573: printf(" Mid TestFconvergence: l+1=%d i=%d k=%d h=%.6e e(i)=%14.8f e(i-1)=%14.8f\n",l+1,i,k, h, e[i],e[i-1]);
3574: #endif
3575: if (z == 0.0)
3576: f = z = 1.0;
3577: c = f/z; s = h/z;
3578: f = x*c + g*s; g = - x*s + g*c; h = y*s;
3579: y *= c;
3580: /* for (j=0; j<n; j++) { */
3581: /* x = ab[j][i-1]; z = ab[j][i]; */
3582: /* ab[j][i-1] = x*c + z*s; */
3583: /* ab[j][i] = - x*s + z*c; */
3584: /* } */
3585: for (j=1; j<=n; j++) {
3586: x = ab[j][i-1]; z = ab[j][i];
3587: ab[j][i-1] = x*c + z*s;
3588: ab[j][i] = - x*s + z*c;
3589: }
3590: if (fabs(f) < fabs(h)) {
3591: double fh = f/h;
3592: z = fabs(h) * sqrt(1.0 + fh*fh);
3593: }
3594: else {
3595: double hf = h/f;
3596: z = (f!=0.0 ? fabs(f)*sqrt(1.0+hf*hf) : 0.0);
3597: }
3598: #ifdef DEBUGPRAXQR
3599: printf(" qr transformation z f h=%.7g %.7g %.7g i=%d k=%d\n",z,f,h, i, k);
3600: #endif
3601: q[i-1] = z;
3602: if (z == 0.0)
3603: z = f = 1.0;
3604: c = f/z; s = h/z;
3605: f = c*g + s*y; /* f can be very small */
3606: x = - s*g + c*y;
3607: }
3608: /* e[l] = 0.0; e[k] = f; q[k] = x; */
3609: e[l] = 0.0; e[k] = f; q[k] = x;
3610: #ifdef DEBUGPRAXQR
3611: printf(" aftermid loop l=%d k=%d e(l)=%7g e(k)=%.7g q(k)=%.7g x=%.7g\n",l,k,e[l],e[k],q[k],x);
3612: #endif
3613: goto TestFsplitting;
3614: Convergence:
3615: #ifdef DEBUGPRAX
3616: printf(" Convergence:\n");
3617: #endif
3618: if (z < 0.0) {
3619: /* q[k] = - z; */
3620: /* for (j=0; j<n; j++) ab[j][k] = - ab[j][k]; */
3621: q[k] = - z;
3622: for (j=1; j<=n; j++) ab[j][k] = - ab[j][k];
3623: }/* END Z */
3624: }/* END K */
3625: } /* END MINFIT */
3626:
3627:
3628: double praxis(double tol, double macheps, double h0, int _n, int _prin, double *_x, double (*_fun)(double *_x))
3629: /* double praxis(double tol, double macheps, double h0, int _n, int _prin, double *_x, double (*_fun)(double *_x, int _n)) */
3630: /* double praxis(double (*_fun)(), double _x[], int _n) */
3631: /* double (*_fun)(); */
3632: /* double _x[N]; */
3633: /* double (*_fun)(); */
3634: /* double _x[N]; */
3635: {
3636: /* init global extern variables and parameters */
3637: /* double *d, *y, *z, */
3638: /* *q0, *q1, **v; */
3639: /* double *tflin; /\* used in flin: return (*fun)(tflin, n); *\/ */
3640: /* double *e; /\* used in minfit, don't konw how to free memory and thus made global *\/ */
3641:
3642:
3643: int seed; /* added */
3644: int biter=0;
3645: double r;
3646: double randbrent( int (*));
3647: double s, sf;
3648:
3649: h = h0; /* step; */
3650: t = tol;
3651: scbd = 1.0;
3652: illc = 0;
3653: ktm = 1;
3654:
3655: macheps = DBL_EPSILON;
3656: /* prin=4; */
3657: #ifdef DEBUGPRAX
3658: printf("Praxis macheps=%14g h=%14g step=%14g tol=%14g\n",macheps,h, h0,tol);
3659: #endif
3660: n = _n;
3661: x = _x;
3662: prin = _prin;
3663: fun = _fun;
3664: d=vector(1, n);
3665: y=vector(1, n);
3666: z=vector(1, n);
3667: q0=vector(1, n);
3668: q1=vector(1, n);
3669: e=vector(1, n);
3670: tflin=vector(1, n);
3671: v=matrix(1, n, 1, n);
3672: for(i=1;i<=n;i++){d[i]=y[i]=z[i]=q0[0]=e[i]=tflin[i]=0.;}
3673: small_windows = (macheps) * (macheps); vsmall = small_windows*small_windows;
3674: large = 1.0/small_windows; vlarge = 1.0/vsmall;
3675: m2 = sqrt(macheps); m4 = sqrt(m2);
3676: seed = 123456789; /* added */
3677: ldfac = (illc ? 0.1 : 0.01);
3678: for(i=1;i<=n;i++) z[i]=0.; /* Was missing in Gegenfurtner as well as Brent's algol or fortran */
3679: nl = kt = 0; nf = 1;
3680: #ifdef NR_SHIFT
3681: fx = (*fun)((x-1), n);
3682: #else
3683: fx = (*fun)(x);
3684: #endif
3685: qf1 = fx;
3686: t2 = small_windows + fabs(t); t = t2; dmin = small_windows;
3687: #ifdef DEBUGPRAX
3688: printf("praxis2 macheps=%14g h=%14g step=%14g small=%14g t=%14g\n",macheps,h, h0,small_windows, t);
3689: #endif
3690: if (h < 100.0*t) h = 100.0*t;
3691: #ifdef DEBUGPRAX
3692: printf("praxis3 macheps=%14g h=%14g step=%14g small=%14g t=%14g\n",macheps,h, h0,small_windows, t);
3693: #endif
3694: ldt = h;
3695: /* for (i=0; i<n; i++) for (j=0; j<n; j++) */
3696: for (i=1; i<=n; i++) for (j=1; j<=n; j++)
3697: v[i][j] = (i == j ? 1.0 : 0.0);
3698: d[1] = 0.0; qd0 = 0.0;
3699: /* for (i=0; i<n; i++) q1[i] = x[i]; */
3700: for (i=1; i<=n; i++) q1[i] = x[i];
3701: if (prin > 1) {
3702: printf("\n------------- enter function praxis -----------\n");
3703: printf("... current parameter settings ...\n");
3704: printf("... scaling ... %20.10e\n", scbd);
3705: printf("... tol ... %20.10e\n", t);
3706: printf("... maxstep ... %20.10e\n", h);
3707: printf("... illc ... %20u\n", illc);
3708: printf("... ktm ... %20u\n", ktm);
3709: printf("... maxfun ... %20u\n", maxfun);
3710: }
3711: if (prin) print2();
3712:
3713: mloop:
3714: biter++; /* Added to count the loops */
3715: /* sf = d[0]; */
3716: /* s = d[0] = 0.0; */
3717: printf("\n Big iteration %d \n",biter);
3718: fprintf(ficlog,"\n Big iteration %d \n",biter);
3719: sf = d[1];
3720: s = d[1] = 0.0;
3721:
3722: /* minimize along first direction V(*,1) */
3723: #ifdef DEBUGPRAX
3724: printf(" Minimize along the first direction V(*,1). illc=%d\n",illc);
3725: /* fprintf(ficlog," Minimize along the first direction V(*,1).\n"); */
3726: #endif
3727: #ifdef DEBUGPRAX2
3728: printf("praxis4 macheps=%14g h=%14g step=%14g small=%14g t=%14g\n",macheps,h, h0,small_windows, t);
3729: #endif
3730: /* min(0, 2, &d[0], &s, fx, 0); /\* mac heps not global *\/ */
1.362 brouard 3731: minny(1, 2, &d[1], &s, fx, 0); /* mac heps not global it seems that fx doesn't correspond to f(s=*x1) */
1.359 brouard 3732: #ifdef DEBUGPRAX
3733: printf("praxis5 macheps=%14g h=%14g looks at sign of s=%14g fx=%14g\n",macheps,h, s,fx);
3734: #endif
3735: if (s <= 0.0)
3736: /* for (i=0; i < n; i++) */
3737: for (i=1; i <= n; i++)
3738: v[i][1] = -v[i][1];
3739: /* if ((sf <= (0.9 * d[0])) || ((0.9 * sf) >= d[0])) */
3740: if ((sf <= (0.9 * d[1])) || ((0.9 * sf) >= d[1]))
3741: /* for (i=1; i<n; i++) */
3742: for (i=2; i<=n; i++)
3743: d[i] = 0.0;
3744: /* for (k=1; k<n; k++) { */
3745: for (k=2; k<=n; k++) {
3746: /*
3747: The inner loop starts here.
3748: */
3749: #ifdef DEBUGPRAX
3750: printf(" The inner loop here from k=%d to n=%d.\n",k,n);
3751: /* fprintf(ficlog," The inner loop here from k=%d to n=%d.\n",k,n); */
3752: #endif
3753: /* for (i=0; i<n; i++) */
3754: for (i=1; i<=n; i++)
3755: y[i] = x[i];
3756: sf = fx;
3757: #ifdef DEBUGPRAX
3758: printf(" illc=%d and kt=%d and ktm=%d\n", illc, kt, ktm);
3759: #endif
3760: illc = illc || (kt > 0);
3761: next:
3762: kl = k;
3763: df = 0.0;
3764: if (illc) { /* random step to get off resolution valley */
3765: #ifdef DEBUGPRAX
3766: printf(" A random step follows, to avoid resolution valleys.\n");
3767: matprint(" before rand, vectors:",v,n,n);
3768: #endif
3769: for (i=1; i<=n; i++) {
3770: #ifdef NOBRENTRAND
3771: r = drandom();
3772: #else
3773: seed=i;
3774: /* seed=i+1; */
3775: #ifdef DEBUGRAND
3776: printf(" Random seed=%d, brent i=%d",seed,i); /* YYYY i=5 j=1 vji= -0.0001170073 */
3777: #endif
3778: r = randbrent ( &seed );
3779: #endif
3780: #ifdef DEBUGRAND
3781: printf(" Random r=%.7g \n",r);
3782: #endif
3783: z[i] = (0.1 * ldt + t2 * pow(10.0,(double)kt)) * (r - 0.5);
3784: /* z[i] = (0.1 * ldt + t2 * pow(10.0,(double)kt)) * (drandom() - 0.5); */
3785:
3786: s = z[i];
3787: for (j=1; j <= n; j++)
3788: x[j] += s * v[j][i];
3789: }
3790: #ifdef DEBUGRAND
3791: matprint(" after rand, vectors:",v,n,n);
3792: #endif
3793: #ifdef NR_SHIFT
3794: fx = (*fun)((x-1), n);
3795: #else
3796: fx = (*fun)(x, n);
3797: #endif
3798: /* fx = (*func) ( (x-1) ); *//* This for func which is computed from x[1] and not from x[0] xm1=(x-1)*/
3799: nf++;
3800: }
3801: /* minimize along non-conjugate directions */
3802: #ifdef DEBUGPRAX
3803: printf(" Minimize along the 'non-conjugate' directions (dots printed) V(*,%d),...,V(*,%d).\n",k,n);
3804: /* fprintf(ficlog," Minimize along the 'non-conjugate' directions (dots printed) V(*,%d),...,V(*,%d).\n",k,n); */
3805: #endif
3806: /* for (k2=k; k2<n; k2++) { /\* Be careful here k2 <=n ? *\/ */
3807: for (k2=k; k2<=n; k2++) { /* Be careful here k2 <=n ? */
3808: sl = fx;
3809: s = 0.0;
3810: #ifdef DEBUGPRAX
3811: printf(" Minimize along the 'NON-CONJUGATE' true direction k2=%14d fx=%14.7f\n",k2, fx);
3812: matprint(" before min vectors:",v,n,n);
3813: #endif
3814: /* min(k2, 2, &d[k2], &s, fx, 0); */
3815: /* jsearch=k2-1; */
3816: /* min(jsearch, 2, &d[jsearch], &s, fx, 0); */
3817: minny(k2, 2, &d[k2], &s, fx, 0);
3818: #ifdef DEBUGPRAX
3819: printf(" . D(%d)=%14.7f d[k2]=%14.7f z[k2]=%14.7f illc=%14d fx=%14.7f\n",k2,d[k2],d[k2],z[k2],illc,fx);
3820: #endif
3821: if (illc) {
3822: /* double szk = s + z[k2]; */
3823: /* s = d[k2] * szk*szk; */
3824: double szk = s + z[k2];
3825: s = d[k2] * szk*szk;
3826: }
3827: else
3828: s = sl - fx;
3829: /* if (df < s) { */
3830: if (df <= s) {
3831: df = s;
3832: kl = k2;
3833: #ifdef DEBUGPRAX
3834: printf(" df=%.7g and choose kl=%d \n",df,kl); /* UUUU */
3835: #endif
3836: }
3837: } /* end loop k2 */
3838: /*
3839: If there was not much improvement on the first try, set
3840: ILLC = true and start the inner loop again.
3841: */
3842: #ifdef DEBUGPRAX
3843: printf(" If there was not much improvement on the first try, set ILLC = true and start the inner loop again. illc=%d\n",illc);
3844: /* fprintf(ficlog," If there was not much improvement on the first try, set ILLC = true and start the inner loop again.\n"); */
3845: #endif
3846: if (!illc && (df < fabs(100.0 * (macheps) * fx))) {
3847: #ifdef DEBUGPRAX
3848: printf("\n NO SUCCESS because DF is small, starts inner loop with same K(=%d), fabs( 100.0 * machep(=%.10e) * fx(=%.9e) )=%.9e > df(=%.9e) break illc=%d\n", k, macheps, fx, fabs ( 100.0 * macheps * fx ), df, illc);
3849: #endif
3850: illc = 1;
3851: goto next;
3852: }
3853: #ifdef DEBUGPRAX
3854: printf("\n SUCCESS, BREAKS inner loop K(=%d) because DF is big, fabs( 100.0 * machep(=%.10e) * fx(=%.9e) )=%.9e <= df(=%.9e) break illc=%d\n", k, macheps, fx, fabs ( 100.0 * macheps * fx ), df, illc);
3855: #endif
3856:
3857: /* if ((k == 1) && (prin > 1)){ /\* be careful k=2 *\/ */
3858: if ((k == 2) && (prin > 1)){ /* be careful k=2 */
3859: #ifdef DEBUGPRAX
3860: printf(" NEW D The second difference array d:\n" );
3861: /* fprintf(ficlog, " NEW D The second difference array d:\n" ); */
3862: #endif
3863: vecprint(" NEW D The second difference array d:",d,n);
3864: }
3865: /* minimize along conjugate directions */
3866: /*
3867: Minimize along the "conjugate" directions V(*,1),...,V(*,K-1).
3868: */
3869: #ifdef DEBUGPRAX
3870: printf("Minimize along the 'conjugate' directions V(*,1),...,V(*,K-1=%d).\n",k-1);
3871: /* fprintf(ficlog,"Minimize along the 'conjugate' directions V(*,1),...,V(*,K-1=%d).\n",k-1); */
3872: #endif
3873: /* for (k2=0; k2<=k-1; k2++) { */
3874: for (k2=1; k2<=k-1; k2++) {
3875: s = 0.0;
3876: /* min(k2-1, 2, &d[k2-1], &s, fx, 0); */
3877: minny(k2, 2, &d[k2], &s, fx, 0);
3878: }
3879: f1 = fx;
3880: fx = sf;
3881: lds = 0.0;
3882: /* for (i=0; i<n; i++) { */
3883: for (i=1; i<=n; i++) {
3884: sl = x[i];
3885: x[i] = y[i];
3886: y[i] = sl - y[i];
3887: sl = y[i];
3888: lds = lds + sl*sl;
3889: }
3890: lds = sqrt(lds);
3891: #ifdef DEBUGPRAX
3892: printf("Minimization done 'conjugate', shifted all points, computed lds=%.8f\n",lds);
3893: #endif
3894: /*
3895: Discard direction V(*,kl).
3896:
3897: If no random step was taken, V(*,KL) is the "non-conjugate"
3898: direction along which the greatest improvement was made.
3899: */
3900: if (lds > small_windows) {
3901: #ifdef DEBUGPRAX
3902: printf("lds big enough to throw direction V(*,kl=%d). If no random step was taken, V(*,KL) is the 'non-conjugate' direction along which the greatest improvement was made.\n",kl);
3903: matprint(" before shift new conjugate vectors:",v,n,n);
3904: #endif
3905: for (i=kl-1; i>=k; i--) {
3906: /* for (j=0; j < n; j++) */
3907: for (j=1; j <= n; j++)
3908: /* v[j][i+1] = v[j][i]; */ /* This is v[j][i+1]=v[j][i] i=kl-1 to k */
3909: v[j][i+1] = v[j][i]; /* This is v[j][i+1]=v[j][i] i=kl-1 to k */
3910: /* v[j][i+1] = v[j][i]; */
3911: /* d[i+1] = d[i];*/ /* last is d[k+1]= d[k] */
3912: d[i+1] = d[i]; /* last is d[k]= d[k-1] */
3913: }
3914: #ifdef DEBUGPRAX
3915: matprint(" after shift new conjugate vectors:",v,n,n);
3916: #endif /* d[k] = 0.0; */
3917: d[k] = 0.0;
3918: for (i=1; i <= n; i++)
3919: v[i][k] = y[i] / lds;
3920: /* v[i][k] = y[i] / lds; */
3921: #ifdef DEBUGPRAX
3922: printf("Minimize along the new 'conjugate' direction V(*,k=%d), which is the normalized vector: (new x) - (old x). d2=%14.7g lds=%.10f\n",k,d[k],lds);
3923: /* fprintf(ficlog,"Minimize along the new 'conjugate' direction V(*,k=%d), which is the normalized vector: (new x) - (old x).\n",k); */
3924: matprint(" before min new conjugate vectors:",v,n,n);
3925: #endif
3926: /* min(k-1, 4, &d[k-1], &lds, f1, 1); */
3927: minny(k, 4, &d[k], &lds, f1, 1);
3928: #ifdef DEBUGPRAX
3929: printf(" after min d(k)=%d %.7g lds=%14f\n",k,d[k],lds);
3930: matprint(" after min vectors:",v,n,n);
3931: #endif
3932: if (lds <= 0.0) {
3933: lds = -lds;
3934: #ifdef DEBUGPRAX
3935: printf(" lds changed sign lds=%.14f k=%d\n",lds,k);
3936: #endif
3937: /* for (i=0; i<n; i++) */
3938: /* v[i][k] = -v[i][k]; */
3939: for (i=1; i<=n; i++)
3940: v[i][k] = -v[i][k];
3941: }
3942: }
3943: ldt = ldfac * ldt;
3944: if (ldt < lds)
3945: ldt = lds;
3946: if (prin > 0){
3947: #ifdef DEBUGPRAX
3948: printf(" k=%d",k);
3949: /* fprintf(ficlog," k=%d",k); */
3950: #endif
3951: print2();/* n, x, prin, fx, nf, nl ); */
3952: }
3953: t2 = 0.0;
3954: /* for (i=0; i<n; i++) */
3955: for (i=1; i<=n; i++)
3956: t2 += x[i]*x[i];
3957: t2 = m2 * sqrt(t2) + t;
3958: /*
3959: See whether the length of the step taken since starting the
3960: inner loop exceeds half the tolerance.
3961: */
3962: #ifdef DEBUGPRAX
3963: printf("See if step length exceeds half the tolerance.\n"); /* ZZZZZ */
3964: /* fprintf(ficlog,"See if step length exceeds half the tolerance.\n"); */
3965: #endif
3966: if (ldt > (0.5 * t2))
3967: kt = 0;
3968: else
3969: kt++;
3970: #ifdef DEBUGPRAX
3971: printf("if kt=%d >? ktm=%d gotoL2 loop\n",kt,ktm);
3972: #endif
3973: if (kt > ktm){
3974: if ( 0 < prin ){
3975: /* printf("\nr8vec_print\n X:\n"); */
3976: /* fprintf(ficlog,"\nr8vec_print\n X:\n"); */
3977: vecprint ("END X:", x, n );
3978: }
3979: goto fret;
3980: }
3981: #ifdef DEBUGPRAX
3982: matprint(" end of L2 loop vectors:",v,n,n);
3983: #endif
3984:
3985: }
3986: /* printf("The inner loop ends here.\n"); */
3987: /* fprintf(ficlog,"The inner loop ends here.\n"); */
3988: /*
3989: The inner loop ends here.
3990:
3991: Try quadratic extrapolation in case we are in a curved valley.
3992: */
3993: #ifdef DEBUGPRAX
3994: printf("Try QUAD ratic extrapolation in case we are in a curved valley.\n");
3995: #endif
3996: /* try quadratic extrapolation in case */
3997: /* we are stuck in a curved valley */
3998: quad();
3999: dn = 0.0;
4000: /* for (i=0; i<n; i++) { */
4001: for (i=1; i<=n; i++) {
4002: d[i] = 1.0 / sqrt(d[i]);
4003: if (dn < d[i])
4004: dn = d[i];
4005: }
4006: if (prin > 2)
4007: matprint(" NEW DIRECTIONS vectors:",v,n,n);
4008: /* for (j=0; j<n; j++) { */
4009: for (j=1; j<=n; j++) {
4010: s = d[j] / dn;
4011: /* for (i=0; i < n; i++) */
4012: for (i=1; i <= n; i++)
4013: v[i][j] *= s;
4014: }
4015:
4016: if (scbd > 1.0) { /* scale axis to reduce condition number */
4017: #ifdef DEBUGPRAX
4018: printf("Scale the axes to try to reduce the condition number.\n");
4019: #endif
4020: /* fprintf(ficlog,"Scale the axes to try to reduce the condition number.\n"); */
4021: s = vlarge;
4022: /* for (i=0; i<n; i++) { */
4023: for (i=1; i<=n; i++) {
4024: sl = 0.0;
4025: /* for (j=0; j < n; j++) */
4026: for (j=1; j <= n; j++)
4027: sl += v[i][j]*v[i][j];
4028: z[i] = sqrt(sl);
4029: if (z[i] < m4)
4030: z[i] = m4;
4031: if (s > z[i])
4032: s = z[i];
4033: }
4034: /* for (i=0; i<n; i++) { */
4035: for (i=1; i<=n; i++) {
4036: sl = s / z[i];
4037: z[i] = 1.0 / sl;
4038: if (z[i] > scbd) {
4039: sl = 1.0 / scbd;
4040: z[i] = scbd;
4041: }
4042: }
4043: }
4044: for (i=1; i<=n; i++)
4045: /* for (j=0; j<=i-1; j++) { */
4046: /* for (j=1; j<=i; j++) { */
4047: for (j=1; j<=i-1; j++) {
4048: s = v[i][j];
4049: v[i][j] = v[j][i];
4050: v[j][i] = s;
4051: }
4052: #ifdef DEBUGPRAX
4053: printf(" Calculate a new set of orthogonal directions before repeating the main loop.\n Transpose V for MINFIT:...\n");
4054: #endif
4055: /*
4056: MINFIT finds the singular value decomposition of V.
4057:
4058: This gives the principal values and principal directions of the
4059: approximating quadratic form without squaring the condition number.
4060: */
4061: #ifdef DEBUGPRAX
4062: printf(" MINFIT finds the singular value decomposition of V. \n This gives the principal values and principal directions of the\n approximating quadratic form without squaring the condition number...\n");
4063: #endif
4064:
4065: minfit(n, macheps, vsmall, v, d);
4066: /* for(i=0; i<n;i++)printf(" %14.7g",d[i]); */
4067: /* v is overwritten with R. */
4068: /*
4069: Unscale the axes.
4070: */
4071: if (scbd > 1.0) {
4072: #ifdef DEBUGPRAX
4073: printf(" Unscale the axes.\n");
4074: #endif
4075: /* for (i=0; i<n; i++) { */
4076: for (i=1; i<=n; i++) {
4077: s = z[i];
4078: /* for (j=0; j<n; j++) */
4079: for (j=1; j<=n; j++)
4080: v[i][j] *= s;
4081: }
4082: /* for (i=0; i<n; i++) { */
4083: for (i=1; i<=n; i++) {
4084: s = 0.0;
4085: /* for (j=0; j<n; j++) */
4086: for (j=1; j<=n; j++)
4087: s += v[j][i]*v[j][i];
4088: s = sqrt(s);
4089: d[i] *= s;
4090: s = 1.0 / s;
4091: /* for (j=0; j<n; j++) */
4092: for (j=1; j<=n; j++)
4093: v[j][i] *= s;
4094: }
4095: }
4096: /* for (i=0; i<n; i++) { */
4097: double dni; /* added for compatibility with buckhardt but not brent */
4098: for (i=1; i<=n; i++) {
4099: dni=dn*d[i]; /* added for compatibility with buckhardt but not brent */
4100: if ((dn * d[i]) > large)
4101: d[i] = vsmall;
4102: else if ((dn * d[i]) < small_windows)
4103: d[i] = vlarge;
4104: else
4105: d[i] = 1.0 / dni / dni; /* added for compatibility with buckhardt but not brent */
4106: /* d[i] = pow(dn * d[i],-2.0); */
4107: }
4108: #ifdef DEBUGPRAX
4109: vecprint ("\n Before sort Eigenvalues of a:",d,n );
4110: #endif
4111:
4112: sort(); /* the new eigenvalues and eigenvectors */
4113: #ifdef DEBUGPRAX
4114: vecprint( " After sort the eigenvalues ....\n", d, n);
4115: matprint( " After sort the eigenvectors....\n", v, n,n);
4116: #endif
4117: #ifdef DEBUGPRAX
4118: printf(" Determine the smallest eigenvalue.\n");
4119: #endif
4120: /* dmin = d[n-1]; */
4121: dmin = d[n];
4122: if (dmin < small_windows)
4123: dmin = small_windows;
4124: /*
4125: The ratio of the smallest to largest eigenvalue determines whether
4126: the system is ill conditioned.
4127: */
4128:
4129: /* illc = (m2 * d[0]) > dmin; */
4130: illc = (m2 * d[1]) > dmin;
4131: #ifdef DEBUGPRAX
4132: printf(" The ratio of the smallest to largest eigenvalue determines whether\n the system is ill conditioned=%d . dmin=%.10lf < m2=%.10lf * d[1]=%.10lf \n",illc, dmin,m2, d[1]);
4133: #endif
4134:
4135: if ((prin > 2) && (scbd > 1.0))
4136: vecprint("\n The scale factors:",z,n);
4137: if (prin > 2)
4138: vecprint(" Principal values (EIGEN VALUES OF A) of the quadratic form:",d,n);
4139: if (prin > 2)
4140: matprint(" The principal axes (EIGEN VECTORS OF A:",v,n, n);
4141:
4142: if ((maxfun > 0) && (nf > maxfun)) {
4143: if (prin)
4144: printf("\n... maximum number of function calls reached ...\n");
4145: goto fret;
4146: }
4147: #ifdef DEBUGPRAX
4148: printf("Goto main loop\n");
4149: #endif
4150: goto mloop; /* back to main loop */
4151:
4152: fret:
4153: if (prin > 0) {
4154: vecprint("\n X:", x, n);
4155: /* printf("\n... ChiSq reduced to %20.10e ...\n", fx); */
4156: /* printf("... after %20u function calls.\n", nf); */
4157: }
4158: free_vector(d, 1, n);
4159: free_vector(y, 1, n);
4160: free_vector(z, 1, n);
4161: free_vector(q0, 1, n);
4162: free_vector(q1, 1, n);
4163: free_matrix(v, 1, n, 1, n);
4164: /* double *d, *y, *z, */
4165: /* *q0, *q1, **v; */
4166: free_vector(tflin, 1, n);
4167: /* double *tflin; /\* used in flin: return (*fun)(tflin, n); *\/ */
4168: free_vector(e, 1, n);
4169: /* double *e; /\* used in minfit, don't konw how to free memory and thus made global *\/ */
4170:
4171: return(fx);
4172: }
4173:
4174: /* end praxis gegen */
1.126 brouard 4175:
4176: /*************** powell ************************/
1.162 brouard 4177: /*
1.317 brouard 4178: Minimization of a function func of n variables. Input consists in an initial starting point
4179: p[1..n] ; an initial matrix xi[1..n][1..n] whose columns contain the initial set of di-
4180: rections (usually the n unit vectors); and ftol, the fractional tolerance in the function value
4181: such that failure to decrease by more than this amount in one iteration signals doneness. On
1.162 brouard 4182: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
4183: function value at p , and iter is the number of iterations taken. The routine linmin is used.
4184: */
1.224 brouard 4185: #ifdef LINMINORIGINAL
4186: #else
4187: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 4188: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 4189: #endif
1.126 brouard 4190: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
4191: double (*func)(double []))
4192: {
1.224 brouard 4193: #ifdef LINMINORIGINAL
4194: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 4195: double (*func)(double []));
1.224 brouard 4196: #else
1.241 brouard 4197: void linmin(double p[], double xi[], int n, double *fret,
4198: double (*func)(double []),int *flat);
1.224 brouard 4199: #endif
1.239 brouard 4200: int i,ibig,j,jk,k;
1.126 brouard 4201: double del,t,*pt,*ptt,*xit;
1.181 brouard 4202: double directest;
1.126 brouard 4203: double fp,fptt;
4204: double *xits;
4205: int niterf, itmp;
1.349 brouard 4206: int Bigter=0, nBigterf=1;
4207:
1.126 brouard 4208: pt=vector(1,n);
4209: ptt=vector(1,n);
4210: xit=vector(1,n);
4211: xits=vector(1,n);
4212: *fret=(*func)(p);
4213: for (j=1;j<=n;j++) pt[j]=p[j];
1.338 brouard 4214: rcurr_time = time(NULL);
4215: fp=(*fret); /* Initialisation */
1.126 brouard 4216: for (*iter=1;;++(*iter)) {
4217: ibig=0;
4218: del=0.0;
1.157 brouard 4219: rlast_time=rcurr_time;
1.349 brouard 4220: rlast_btime=rcurr_time;
1.157 brouard 4221: /* (void) gettimeofday(&curr_time,&tzp); */
4222: rcurr_time = time(NULL);
4223: curr_time = *localtime(&rcurr_time);
1.337 brouard 4224: /* printf("\nPowell iter=%d -2*LL=%.12f gain=%.12f=%.3g %ld sec. %ld sec.",*iter,*fret, fp-*fret,fp-*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout); */
4225: /* fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f gain=%.12f=%.3g %ld sec. %ld sec.",*iter,*fret, fp-*fret,fp-*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog); */
1.359 brouard 4226: /* Bigter=(*iter - *iter % ncovmodel)/ncovmodel +1; /\* Big iteration, i.e on ncovmodel cycle *\/ */
4227: Bigter=(*iter - (*iter-1) % n)/n +1; /* Big iteration, i.e on ncovmodel cycle */
1.349 brouard 4228: printf("\nPowell iter=%d Big Iter=%d -2*LL=%.12f gain=%.3lg %ld sec. %ld sec.",*iter,Bigter,*fret,fp-*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
4229: fprintf(ficlog,"\nPowell iter=%d Big Iter=%d -2*LL=%.12f gain=%.3lg %ld sec. %ld sec.",*iter,Bigter,*fret,fp-*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
4230: fprintf(ficrespow,"%d %d %.12f %d",*iter,Bigter, *fret,curr_time.tm_sec-start_time.tm_sec);
1.324 brouard 4231: fp=(*fret); /* From former iteration or initial value */
1.192 brouard 4232: for (i=1;i<=n;i++) {
1.126 brouard 4233: fprintf(ficrespow," %.12lf", p[i]);
4234: }
1.239 brouard 4235: fprintf(ficrespow,"\n");fflush(ficrespow);
4236: printf("\n#model= 1 + age ");
4237: fprintf(ficlog,"\n#model= 1 + age ");
4238: if(nagesqr==1){
1.241 brouard 4239: printf(" + age*age ");
4240: fprintf(ficlog," + age*age ");
1.239 brouard 4241: }
1.362 brouard 4242: for(j=1;j <=ncovmodel-2-nagesqr;j++){
1.239 brouard 4243: if(Typevar[j]==0) {
4244: printf(" + V%d ",Tvar[j]);
4245: fprintf(ficlog," + V%d ",Tvar[j]);
4246: }else if(Typevar[j]==1) {
4247: printf(" + V%d*age ",Tvar[j]);
4248: fprintf(ficlog," + V%d*age ",Tvar[j]);
4249: }else if(Typevar[j]==2) {
4250: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
4251: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 4252: }else if(Typevar[j]==3) {
4253: printf(" + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
4254: fprintf(ficlog," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.239 brouard 4255: }
4256: }
1.126 brouard 4257: printf("\n");
1.239 brouard 4258: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
4259: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 4260: fprintf(ficlog,"\n");
1.239 brouard 4261: for(i=1,jk=1; i <=nlstate; i++){
4262: for(k=1; k <=(nlstate+ndeath); k++){
4263: if (k != i) {
4264: printf("%d%d ",i,k);
4265: fprintf(ficlog,"%d%d ",i,k);
4266: for(j=1; j <=ncovmodel; j++){
4267: printf("%12.7f ",p[jk]);
4268: fprintf(ficlog,"%12.7f ",p[jk]);
4269: jk++;
4270: }
4271: printf("\n");
4272: fprintf(ficlog,"\n");
4273: }
4274: }
4275: }
1.241 brouard 4276: if(*iter <=3 && *iter >1){
1.157 brouard 4277: tml = *localtime(&rcurr_time);
4278: strcpy(strcurr,asctime(&tml));
4279: rforecast_time=rcurr_time;
1.126 brouard 4280: itmp = strlen(strcurr);
4281: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 4282: strcurr[itmp-1]='\0';
1.162 brouard 4283: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 4284: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.349 brouard 4285: for(nBigterf=1;nBigterf<=31;nBigterf+=10){
4286: niterf=nBigterf*ncovmodel;
4287: /* rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time); */
1.241 brouard 4288: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
4289: forecast_time = *localtime(&rforecast_time);
4290: strcpy(strfor,asctime(&forecast_time));
4291: itmp = strlen(strfor);
4292: if(strfor[itmp-1]=='\n')
4293: strfor[itmp-1]='\0';
1.349 brouard 4294: printf(" - if your program needs %d BIG iterations (%d iterations) to converge, convergence will be \n reached in %s i.e.\n on %s (current time is %s);\n",nBigterf, niterf, asc_diff_time(rforecast_time-rcurr_time,tmpout),strfor,strcurr);
4295: fprintf(ficlog," - if your program needs %d BIG iterations (%d iterations) to converge, convergence will be \n reached in %s i.e.\n on %s (current time is %s);\n",nBigterf, niterf, asc_diff_time(rforecast_time-rcurr_time,tmpout),strfor,strcurr);
1.126 brouard 4296: }
4297: }
1.359 brouard 4298: for (i=1;i<=n;i++) { /* For each direction i, maximisation after loading directions */
4299: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales. xi is not changed but one dim xit */
4300:
4301: fptt=(*fret); /* Computes likelihood for parameters xit */
1.126 brouard 4302: #ifdef DEBUG
1.203 brouard 4303: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
4304: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 4305: #endif
1.203 brouard 4306: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 4307: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 4308: #ifdef LINMINORIGINAL
1.359 brouard 4309: linmin(p,xit,n,fret,func); /* New point i minimizing in direction xit, i has coordinates p[j].*/
1.357 brouard 4310: /* xit[j] gives the n coordinates of direction i as input.*/
4311: /* *fret gives the maximum value on direction xit */
1.224 brouard 4312: #else
4313: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.359 brouard 4314: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.224 brouard 4315: #endif
1.359 brouard 4316: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 4317: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.359 brouard 4318: /* because that direction will be replaced unless the gain del is small */
4319: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
4320: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
4321: /* with the new direction. */
4322: del=fabs(fptt-(*fret));
4323: ibig=i;
1.126 brouard 4324: }
4325: #ifdef DEBUG
4326: printf("%d %.12e",i,(*fret));
4327: fprintf(ficlog,"%d %.12e",i,(*fret));
4328: for (j=1;j<=n;j++) {
1.359 brouard 4329: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
4330: printf(" x(%d)=%.12e",j,xit[j]);
4331: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 4332: }
4333: for(j=1;j<=n;j++) {
1.359 brouard 4334: printf(" p(%d)=%.12e",j,p[j]);
4335: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 4336: }
4337: printf("\n");
4338: fprintf(ficlog,"\n");
4339: #endif
1.187 brouard 4340: } /* end loop on each direction i */
1.357 brouard 4341: /* Convergence test will use last linmin estimation (fret) and compare to former iteration (fp) */
1.188 brouard 4342: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.359 brouard 4343: /* New value of last point Pn is not computed, P(n-1) */
1.319 brouard 4344: for(j=1;j<=n;j++) {
4345: if(flatdir[j] >0){
4346: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
4347: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
1.302 brouard 4348: }
1.319 brouard 4349: /* printf("\n"); */
4350: /* fprintf(ficlog,"\n"); */
4351: }
1.243 brouard 4352: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
4353: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 4354: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
4355: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
4356: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
4357: /* decreased of more than 3.84 */
4358: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
4359: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
4360: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 4361:
1.188 brouard 4362: /* Starting the program with initial values given by a former maximization will simply change */
4363: /* the scales of the directions and the directions, because the are reset to canonical directions */
4364: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
4365: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 4366: #ifdef DEBUG
4367: int k[2],l;
4368: k[0]=1;
4369: k[1]=-1;
4370: printf("Max: %.12e",(*func)(p));
4371: fprintf(ficlog,"Max: %.12e",(*func)(p));
4372: for (j=1;j<=n;j++) {
4373: printf(" %.12e",p[j]);
4374: fprintf(ficlog," %.12e",p[j]);
4375: }
4376: printf("\n");
4377: fprintf(ficlog,"\n");
4378: for(l=0;l<=1;l++) {
4379: for (j=1;j<=n;j++) {
4380: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
4381: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
4382: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
4383: }
4384: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
4385: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
4386: }
4387: #endif
4388:
4389: free_vector(xit,1,n);
4390: free_vector(xits,1,n);
4391: free_vector(ptt,1,n);
4392: free_vector(pt,1,n);
4393: return;
1.192 brouard 4394: } /* enough precision */
1.240 brouard 4395: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.359 brouard 4396: for (j=1;j<=n;j++) { /* Computes the extrapolated point and value f3, P_0 + 2 (P_n-P_0)=2Pn-P0 and xit is direction Pn-P0 */
1.126 brouard 4397: ptt[j]=2.0*p[j]-pt[j];
1.359 brouard 4398: xit[j]=p[j]-pt[j]; /* Coordinate j of last direction xi_n=P_n-P_0 */
4399: #ifdef DEBUG
4400: printf("\n %d xit=%12.7g p=%12.7g pt=%12.7g ",j,xit[j],p[j],pt[j]);
4401: #endif
4402: pt[j]=p[j]; /* New P0 is Pn */
4403: }
4404: #ifdef DEBUG
4405: printf("\n");
4406: #endif
1.181 brouard 4407: fptt=(*func)(ptt); /* f_3 */
1.359 brouard 4408: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in directions until some iterations are done */
1.224 brouard 4409: if (*iter <=4) {
1.225 brouard 4410: #else
4411: #endif
1.224 brouard 4412: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 4413: #else
1.161 brouard 4414: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 4415: #endif
1.162 brouard 4416: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 4417: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 4418: /* Let f"(x2) be the 2nd derivative equal everywhere. */
4419: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
4420: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 4421: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
4422: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
4423: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 4424: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 4425: /* Even if f3 <f1, directest can be negative and t >0 */
4426: /* mu² and del² are equal when f3=f1 */
1.359 brouard 4427: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
4428: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
4429: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
4430: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 4431: #ifdef NRCORIGINAL
4432: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
4433: #else
4434: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del); /* Intel compiler doesn't work on one line; bug reported */
1.161 brouard 4435: t= t- del*SQR(fp-fptt);
1.183 brouard 4436: #endif
1.202 brouard 4437: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 4438: #ifdef DEBUG
1.181 brouard 4439: printf("t1= %.12lf, t2= %.12lf, t=%.12lf directest=%.12lf\n", 2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del),del*SQR(fp-fptt),t,directest);
4440: fprintf(ficlog,"t1= %.12lf, t2= %.12lf, t=%.12lf directest=%.12lf\n", 2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del),del*SQR(fp-fptt),t,directest);
1.161 brouard 4441: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
4442: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
4443: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
4444: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
4445: printf("tt= %.12lf, t=%.12lf\n",2.0*(fp-2.0*(*fret)+fptt)*(fp-(*fret)-del)*(fp-(*fret)-del)-del*(fp-fptt)*(fp-fptt),t);
4446: fprintf(ficlog, "tt= %.12lf, t=%.12lf\n",2.0*(fp-2.0*(*fret)+fptt)*(fp-(*fret)-del)*(fp-(*fret)-del)-del*(fp-fptt)*(fp-fptt),t);
4447: #endif
1.183 brouard 4448: #ifdef POWELLORIGINAL
4449: if (t < 0.0) { /* Then we use it for new direction */
1.361 brouard 4450: #else /* Not POWELLOriginal but Brouard's */
1.182 brouard 4451: if (directest*t < 0.0) { /* Contradiction between both tests */
1.359 brouard 4452: printf("directest= %.12lf (if <0 we include P0 Pn as new direction), t= %.12lf, f1= %.12lf,f2= %.12lf,f3= %.12lf, del= %.12lf\n",directest, t, fp,(*fret),fptt,del);
1.192 brouard 4453: printf("f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
1.224 brouard 4454: fprintf(ficlog,"directest= %.12lf (if directest<0 or t<0 we include P0 Pn as new direction), t= %.12lf, f1= %.12lf,f2= %.12lf,f3= %.12lf, del= %.12lf\n",directest, t, fp,(*fret),fptt, del);
1.192 brouard 4455: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
4456: }
1.361 brouard 4457: if (directest < 0.0) { /* Then we use (P0, Pn) for new direction Xi_n or Xi_iBig */
1.181 brouard 4458: #endif
1.191 brouard 4459: #ifdef DEBUGLINMIN
1.234 brouard 4460: printf("Before linmin in direction P%d-P0\n",n);
4461: for (j=1;j<=n;j++) {
4462: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
4463: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
4464: if(j % ncovmodel == 0){
4465: printf("\n");
4466: fprintf(ficlog,"\n");
4467: }
4468: }
1.224 brouard 4469: #endif
4470: #ifdef LINMINORIGINAL
1.234 brouard 4471: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 4472: #else
1.234 brouard 4473: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
4474: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 4475: #endif
1.234 brouard 4476:
1.191 brouard 4477: #ifdef DEBUGLINMIN
1.234 brouard 4478: for (j=1;j<=n;j++) {
4479: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
4480: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
4481: if(j % ncovmodel == 0){
4482: printf("\n");
4483: fprintf(ficlog,"\n");
4484: }
4485: }
1.224 brouard 4486: #endif
1.234 brouard 4487: for (j=1;j<=n;j++) {
4488: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
4489: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
4490: }
1.361 brouard 4491:
4492: /* #else */
4493: /* for (i=1;i<=n-1;i++) { */
4494: /* for (j=1;j<=n;j++) { */
4495: /* xi[j][i]=xi[j][i+1]; /\* Standard method of conjugate directions, not Powell who changes the nth direction by p0 pn . *\/ */
4496: /* } */
4497: /* } */
4498: /* for (j=1;j<=n;j++) { */
4499: /* xi[j][n]=xit[j]; /\* and this nth direction by the by the average p_0 p_n *\/ */
4500: /* } */
4501: /* /\* for (j=1;j<=n-1;j++) { *\/ */
4502: /* /\* xi[j][1]=xi[j][j+1]; /\\* Standard method of conjugate directions *\\/ *\/ */
4503: /* /\* xi[j][n]=xit[j]; /\\* and this nth direction by the by the average p_0 p_n *\\/ *\/ */
4504: /* /\* } *\/ */
4505: /* #endif */
1.224 brouard 4506: #ifdef LINMINORIGINAL
4507: #else
1.234 brouard 4508: for (j=1, flatd=0;j<=n;j++) {
4509: if(flatdir[j]>0)
4510: flatd++;
4511: }
4512: if(flatd >0){
1.255 brouard 4513: printf("%d flat directions: ",flatd);
4514: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 4515: for (j=1;j<=n;j++) {
4516: if(flatdir[j]>0){
4517: printf("%d ",j);
4518: fprintf(ficlog,"%d ",j);
4519: }
4520: }
4521: printf("\n");
4522: fprintf(ficlog,"\n");
1.319 brouard 4523: #ifdef FLATSUP
4524: free_vector(xit,1,n);
4525: free_vector(xits,1,n);
4526: free_vector(ptt,1,n);
4527: free_vector(pt,1,n);
4528: return;
4529: #endif
1.361 brouard 4530: } /* endif(flatd >0) */
4531: #endif /* LINMINORIGINAL */
1.234 brouard 4532: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
4533: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
4534:
1.126 brouard 4535: #ifdef DEBUG
1.234 brouard 4536: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
4537: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
4538: for(j=1;j<=n;j++){
4539: printf(" %lf",xit[j]);
4540: fprintf(ficlog," %lf",xit[j]);
4541: }
4542: printf("\n");
4543: fprintf(ficlog,"\n");
1.126 brouard 4544: #endif
1.192 brouard 4545: } /* end of t or directest negative */
1.359 brouard 4546: printf(" Directest is positive, P_n-P_0 does not increase the conjugacy. n=%d\n",n);
4547: fprintf(ficlog," Directest is positive, P_n-P_0 does not increase the conjugacy. n=%d\n",n);
1.224 brouard 4548: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 4549: #else
1.234 brouard 4550: } /* end if (fptt < fp) */
1.192 brouard 4551: #endif
1.225 brouard 4552: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 4553: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 4554: #else
1.224 brouard 4555: #endif
1.234 brouard 4556: } /* loop iteration */
1.126 brouard 4557: }
1.234 brouard 4558:
1.126 brouard 4559: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 4560:
1.235 brouard 4561: double **prevalim(double **prlim, int nlstate, double x[], double age, double **oldm, double **savm, double ftolpl, int *ncvyear, int ij, int nres)
1.234 brouard 4562: {
1.338 brouard 4563: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij . Nicely done
1.279 brouard 4564: * (and selected quantitative values in nres)
4565: * by left multiplying the unit
4566: * matrix by transitions matrix until convergence is reached with precision ftolpl
4567: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
4568: * Wx is row vector: population in state 1, population in state 2, population dead
4569: * or prevalence in state 1, prevalence in state 2, 0
4570: * newm is the matrix after multiplications, its rows are identical at a factor.
4571: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
4572: * Output is prlim.
4573: * Initial matrix pimij
4574: */
1.206 brouard 4575: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
4576: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
4577: /* 0, 0 , 1} */
4578: /*
4579: * and after some iteration: */
4580: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
4581: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
4582: /* 0, 0 , 1} */
4583: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
4584: /* {0.51571254859325999, 0.4842874514067399, */
4585: /* 0.51326036147820708, 0.48673963852179264} */
4586: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 4587:
1.332 brouard 4588: int i, ii,j,k, k1;
1.209 brouard 4589: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 4590: /* double **matprod2(); */ /* test */
1.218 brouard 4591: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 4592: double **newm;
1.209 brouard 4593: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 4594: int ncvloop=0;
1.288 brouard 4595: int first=0;
1.169 brouard 4596:
1.209 brouard 4597: min=vector(1,nlstate);
4598: max=vector(1,nlstate);
4599: meandiff=vector(1,nlstate);
4600:
1.218 brouard 4601: /* Starting with matrix unity */
1.126 brouard 4602: for (ii=1;ii<=nlstate+ndeath;ii++)
4603: for (j=1;j<=nlstate+ndeath;j++){
4604: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4605: }
1.169 brouard 4606:
4607: cov[1]=1.;
4608:
4609: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 4610: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 4611: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 4612: ncvloop++;
1.126 brouard 4613: newm=savm;
4614: /* Covariates have to be included here again */
1.138 brouard 4615: cov[2]=agefin;
1.319 brouard 4616: if(nagesqr==1){
4617: cov[3]= agefin*agefin;
4618: }
1.332 brouard 4619: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
4620: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
4621: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 4622: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 4623: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
4624: }else{
4625: cov[2+nagesqr+k1]=precov[nres][k1];
4626: }
4627: }/* End of loop on model equation */
4628:
4629: /* Start of old code (replaced by a loop on position in the model equation */
4630: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only of the model *\/ */
4631: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
4632: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; *\/ */
4633: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TnsdVar[TvarsD[k]])]; */
4634: /* /\* model = 1 +age + V1*V3 + age*V1 + V2 + V1 + age*V2 + V3 + V3*age + V1*V2 */
4635: /* * k 1 2 3 4 5 6 7 8 */
4636: /* *cov[] 1 2 3 4 5 6 7 8 9 10 */
4637: /* *TypeVar[k] 2 1 0 0 1 0 1 2 */
4638: /* *Dummy[k] 0 2 0 0 2 0 2 0 */
4639: /* *Tvar[k] 4 1 2 1 2 3 3 5 */
4640: /* *nsd=3 (1) (2) (3) */
4641: /* *TvarsD[nsd] [1]=2 1 3 */
4642: /* *TnsdVar [2]=2 [1]=1 [3]=3 */
4643: /* *TvarsDind[nsd](=k) [1]=3 [2]=4 [3]=6 */
4644: /* *Tage[] [1]=1 [2]=2 [3]=3 */
4645: /* *Tvard[] [1][1]=1 [2][1]=1 */
4646: /* * [1][2]=3 [2][2]=2 */
4647: /* *Tprod[](=k) [1]=1 [2]=8 */
4648: /* *TvarsDp(=Tvar) [1]=1 [2]=2 [3]=3 [4]=5 */
4649: /* *TvarD (=k) [1]=1 [2]=3 [3]=4 [3]=6 [4]=6 */
4650: /* *TvarsDpType */
4651: /* *si model= 1 + age + V3 + V2*age + V2 + V3*age */
4652: /* * nsd=1 (1) (2) */
4653: /* *TvarsD[nsd] 3 2 */
4654: /* *TnsdVar (3)=1 (2)=2 */
4655: /* *TvarsDind[nsd](=k) [1]=1 [2]=3 */
4656: /* *Tage[] [1]=2 [2]= 3 */
4657: /* *\/ */
4658: /* /\* cov[++k1]=nbcode[TvarsD[k]][codtabm(ij,k)]; *\/ */
4659: /* /\* printf("prevalim Dummy combi=%d k=%d TvarsD[%d]=V%d TvarsDind[%d]=%d nbcode=%d cov=%lf codtabm(%d,Tvar[%d])=%d \n",ij,k, k, TvarsD[k],k,TvarsDind[k],nbcode[TvarsD[k]][codtabm(ij,k)],cov[2+nagesqr+TvarsDind[k]], ij, k, codtabm(ij,k)); *\/ */
4660: /* } */
4661: /* for (k=1; k<=nsq;k++) { /\* For single quantitative varying covariates only of the model *\/ */
4662: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
4663: /* /\* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline *\/ */
4664: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
4665: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][resultmodel[nres][k1]] */
4666: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
4667: /* /\* printf("prevalim Quantitative k=%d TvarsQind[%d]=%d, TvarsQ[%d]=V%d,Tqresult[%d][%d]=%f\n",k,k,TvarsQind[k],k,TvarsQ[k],nres,k,Tqresult[nres][k]); *\/ */
4668: /* } */
4669: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
4670: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
4671: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
4672: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
4673: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
4674: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
4675: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
4676: /* } */
4677: /* /\* printf("prevalim Age combi=%d k=%d Tage[%d]=V%d Tqresult[%d][%d]=%f\n",ij,k,k,Tage[k],nres,k,Tqresult[nres][k]); *\/ */
4678: /* } */
4679: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
4680: /* /\* printf("prevalim Prod ij=%d k=%d Tprod[%d]=%d Tvard[%d][1]=V%d, Tvard[%d][2]=V%d\n",ij,k,k,Tprod[k], k,Tvard[k][1], k,Tvard[k][2]); *\/ */
4681: /* if(Dummy[Tvard[k][1]]==0){ */
4682: /* if(Dummy[Tvard[k][2]]==0){ */
4683: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
4684: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
4685: /* }else{ */
4686: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
4687: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
4688: /* } */
4689: /* }else{ */
4690: /* if(Dummy[Tvard[k][2]]==0){ */
4691: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
4692: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
4693: /* }else{ */
4694: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
4695: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
4696: /* } */
4697: /* } */
4698: /* } /\* End product without age *\/ */
4699: /* ENd of old code */
1.138 brouard 4700: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
4701: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
4702: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 4703: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
4704: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.319 brouard 4705: /* age and covariate values of ij are in 'cov' */
1.142 brouard 4706: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 4707:
1.126 brouard 4708: savm=oldm;
4709: oldm=newm;
1.209 brouard 4710:
4711: for(j=1; j<=nlstate; j++){
4712: max[j]=0.;
4713: min[j]=1.;
4714: }
4715: for(i=1;i<=nlstate;i++){
4716: sumnew=0;
4717: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
4718: for(j=1; j<=nlstate; j++){
4719: prlim[i][j]= newm[i][j]/(1-sumnew);
4720: max[j]=FMAX(max[j],prlim[i][j]);
4721: min[j]=FMIN(min[j],prlim[i][j]);
4722: }
4723: }
4724:
1.126 brouard 4725: maxmax=0.;
1.209 brouard 4726: for(j=1; j<=nlstate; j++){
4727: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
4728: maxmax=FMAX(maxmax,meandiff[j]);
4729: /* printf(" age= %d meandiff[%d]=%f, agefin=%d max[%d]=%f min[%d]=%f maxmax=%f\n", (int)age, j, meandiff[j],(int)agefin, j, max[j], j, min[j],maxmax); */
1.169 brouard 4730: } /* j loop */
1.203 brouard 4731: *ncvyear= (int)age- (int)agefin;
1.208 brouard 4732: /* printf("maxmax=%lf maxmin=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, maxmin, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.126 brouard 4733: if(maxmax < ftolpl){
1.209 brouard 4734: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
4735: free_vector(min,1,nlstate);
4736: free_vector(max,1,nlstate);
4737: free_vector(meandiff,1,nlstate);
1.126 brouard 4738: return prlim;
4739: }
1.288 brouard 4740: } /* agefin loop */
1.208 brouard 4741: /* After some age loop it doesn't converge */
1.288 brouard 4742: if(!first){
4743: first=1;
4744: printf("Warning: the stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.d years and %d loops. Try to lower 'ftolpl'. Youngest age to start was %d=(%d-%d). Others in log file only...\n", (int)age, maxmax, ftolpl, *ncvyear, ncvloop, (int)(agefin+stepm/YEARM), (int)(age-stepm/YEARM), (int)delaymax);
1.317 brouard 4745: fprintf(ficlog, "Warning: the stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.d years and %d loops. Try to lower 'ftolpl'. Youngest age to start was %d=(%d-%d).\n", (int)age, maxmax, ftolpl, *ncvyear, ncvloop, (int)(agefin+stepm/YEARM), (int)(age-stepm/YEARM), (int)delaymax);
4746: }else if (first >=1 && first <10){
4747: fprintf(ficlog, "Warning: the stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.d years and %d loops. Try to lower 'ftolpl'. Youngest age to start was %d=(%d-%d).\n", (int)age, maxmax, ftolpl, *ncvyear, ncvloop, (int)(agefin+stepm/YEARM), (int)(age-stepm/YEARM), (int)delaymax);
4748: first++;
4749: }else if (first ==10){
4750: fprintf(ficlog, "Warning: the stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.d years and %d loops. Try to lower 'ftolpl'. Youngest age to start was %d=(%d-%d).\n", (int)age, maxmax, ftolpl, *ncvyear, ncvloop, (int)(agefin+stepm/YEARM), (int)(age-stepm/YEARM), (int)delaymax);
4751: printf("Warning: the stable prevalence dit not converge. This warning came too often, IMaCh will stop notifying, even in its log file. Look at the graphs to appreciate the non convergence.\n");
4752: fprintf(ficlog,"Warning: the stable prevalence no convergence; too many cases, giving up noticing, even in log file\n");
4753: first++;
1.288 brouard 4754: }
4755:
1.359 brouard 4756: /* Try to lower 'ftol', for example from 1.e-8 to 6.e-9.\n", ftolpl,
4757: * (int)age, (int)delaymax, (int)agefin, ncvloop,
4758: * (int)age-(int)agefin); */
1.209 brouard 4759: free_vector(min,1,nlstate);
4760: free_vector(max,1,nlstate);
4761: free_vector(meandiff,1,nlstate);
1.208 brouard 4762:
1.169 brouard 4763: return prlim; /* should not reach here */
1.126 brouard 4764: }
4765:
1.217 brouard 4766:
4767: /**** Back Prevalence limit (stable or period prevalence) ****************/
4768:
1.218 brouard 4769: /* double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ageminpar, double agemaxpar, double **oldm, double **savm, double **dnewm, double **doldm, double **dsavm, double ftolpl, int *ncvyear, int ij) */
4770: /* double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double **oldm, double **savm, double **dnewm, double **doldm, double **dsavm, double ftolpl, int *ncvyear, int ij) */
1.242 brouard 4771: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 4772: {
1.264 brouard 4773: /* Computes the prevalence limit in each live state at age x and for covariate combination ij (<=2**cptcoveff) by left multiplying the unit
1.217 brouard 4774: matrix by transitions matrix until convergence is reached with precision ftolpl */
4775: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
4776: /* Wx is row vector: population in state 1, population in state 2, population dead */
4777: /* or prevalence in state 1, prevalence in state 2, 0 */
4778: /* newm is the matrix after multiplications, its rows are identical at a factor */
4779: /* Initial matrix pimij */
4780: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
4781: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
4782: /* 0, 0 , 1} */
4783: /*
4784: * and after some iteration: */
4785: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
4786: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
4787: /* 0, 0 , 1} */
4788: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
4789: /* {0.51571254859325999, 0.4842874514067399, */
4790: /* 0.51326036147820708, 0.48673963852179264} */
4791: /* If we start from prlim again, prlim tends to a constant matrix */
4792:
1.359 brouard 4793: int i, ii,j, k1;
1.247 brouard 4794: int first=0;
1.217 brouard 4795: double *min, *max, *meandiff, maxmax,sumnew=0.;
4796: /* double **matprod2(); */ /* test */
4797: double **out, cov[NCOVMAX+1], **bmij();
4798: double **newm;
1.218 brouard 4799: double **dnewm, **doldm, **dsavm; /* for use */
4800: double **oldm, **savm; /* for use */
4801:
1.217 brouard 4802: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
4803: int ncvloop=0;
4804:
4805: min=vector(1,nlstate);
4806: max=vector(1,nlstate);
4807: meandiff=vector(1,nlstate);
4808:
1.266 brouard 4809: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
4810: oldm=oldms; savm=savms;
4811:
4812: /* Starting with matrix unity */
4813: for (ii=1;ii<=nlstate+ndeath;ii++)
4814: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 4815: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4816: }
4817:
4818: cov[1]=1.;
4819:
4820: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
4821: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 4822: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 4823: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
4824: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 4825: ncvloop++;
1.218 brouard 4826: newm=savm; /* oldm should be kept from previous iteration or unity at start */
4827: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 4828: /* Covariates have to be included here again */
4829: cov[2]=agefin;
1.319 brouard 4830: if(nagesqr==1){
1.217 brouard 4831: cov[3]= agefin*agefin;;
1.319 brouard 4832: }
1.332 brouard 4833: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 4834: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 4835: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.242 brouard 4836: }else{
1.332 brouard 4837: cov[2+nagesqr+k1]=precov[nres][k1];
1.242 brouard 4838: }
1.332 brouard 4839: }/* End of loop on model equation */
4840:
4841: /* Old code */
4842:
4843: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
4844: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
4845: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; */
4846: /* /\* printf("bprevalim Dummy agefin=%.0f combi=%d k=%d TvarsD[%d]=V%d TvarsDind[%d]=%d nbcode=%d cov[%d]=%lf codtabm(%d,Tvar[%d])=%d \n",agefin,ij,k, k, TvarsD[k],k,TvarsDind[k],nbcode[TvarsD[k]][codtabm(ij,k)],2+nagesqr+TvarsDind[k],cov[2+nagesqr+TvarsDind[k]], ij, k, codtabm(ij,k)); *\/ */
4847: /* } */
4848: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
4849: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
4850: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
4851: /* /\* /\\* printf("prevalim ij=%d k=%d Tvar[%d]=%d nbcode=%d cov=%lf codtabm(%d,Tvar[%d])=%d \n",ij,k, k, Tvar[k],nbcode[Tvar[k]][codtabm(ij,Tvar[k])],cov[2+k], ij, k, codtabm(ij,Tvar[k])]); *\\/ *\/ */
4852: /* /\* } *\/ */
4853: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
4854: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
4855: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
4856: /* /\* printf("prevalim Quantitative k=%d TvarsQind[%d]=%d, TvarsQ[%d]=V%d,Tqresult[%d][%d]=%f\n",k,k,TvarsQind[k],k,TvarsQ[k],nres,k,Tqresult[nres][k]); *\/ */
4857: /* } */
4858: /* /\* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; *\/ */
4859: /* /\* for (k=1; k<=cptcovprod;k++) /\\* Useless *\\/ *\/ */
4860: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\\/ *\/ */
4861: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
4862: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
4863: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age *\\/ ERROR ???*\/ */
4864: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
4865: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
4866: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
4867: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
4868: /* } */
4869: /* /\* printf("prevalim Age combi=%d k=%d Tage[%d]=V%d Tqresult[%d][%d]=%f\n",ij,k,k,Tage[k],nres,k,Tqresult[nres][k]); *\/ */
4870: /* } */
4871: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
4872: /* /\* printf("prevalim Prod ij=%d k=%d Tprod[%d]=%d Tvard[%d][1]=V%d, Tvard[%d][2]=V%d\n",ij,k,k,Tprod[k], k,Tvard[k][1], k,Tvard[k][2]); *\/ */
4873: /* if(Dummy[Tvard[k][1]]==0){ */
4874: /* if(Dummy[Tvard[k][2]]==0){ */
4875: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
4876: /* }else{ */
4877: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
4878: /* } */
4879: /* }else{ */
4880: /* if(Dummy[Tvard[k][2]]==0){ */
4881: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
4882: /* }else{ */
4883: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
4884: /* } */
4885: /* } */
4886: /* } */
1.217 brouard 4887:
4888: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
4889: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
4890: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
4891: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
4892: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 4893: /* ij should be linked to the correct index of cov */
4894: /* age and covariate values ij are in 'cov', but we need to pass
4895: * ij for the observed prevalence at age and status and covariate
4896: * number: prevacurrent[(int)agefin][ii][ij]
4897: */
4898: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, ageminpar, agemaxpar, dnewm, doldm, dsavm,ij)); /\* Bug Valgrind *\/ */
4899: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij)); /\* Bug Valgrind *\/ */
4900: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij)); /* Bug Valgrind */
1.268 brouard 4901: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 4902: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
4903: /* for(i=1; i<=nlstate+ndeath; i++) { */
4904: /* printf("%d newm= ",i); */
4905: /* for(j=1;j<=nlstate+ndeath;j++) { */
4906: /* printf("%f ",newm[i][j]); */
4907: /* } */
4908: /* printf("oldm * "); */
4909: /* for(j=1;j<=nlstate+ndeath;j++) { */
4910: /* printf("%f ",oldm[i][j]); */
4911: /* } */
1.268 brouard 4912: /* printf(" bmmij "); */
1.266 brouard 4913: /* for(j=1;j<=nlstate+ndeath;j++) { */
4914: /* printf("%f ",pmmij[i][j]); */
4915: /* } */
4916: /* printf("\n"); */
4917: /* } */
4918: /* } */
1.217 brouard 4919: savm=oldm;
4920: oldm=newm;
1.266 brouard 4921:
1.217 brouard 4922: for(j=1; j<=nlstate; j++){
4923: max[j]=0.;
4924: min[j]=1.;
4925: }
4926: for(j=1; j<=nlstate; j++){
4927: for(i=1;i<=nlstate;i++){
1.234 brouard 4928: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
4929: bprlim[i][j]= newm[i][j];
4930: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
4931: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 4932: }
4933: }
1.218 brouard 4934:
1.217 brouard 4935: maxmax=0.;
4936: for(i=1; i<=nlstate; i++){
1.318 brouard 4937: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column, could be nan! */
1.217 brouard 4938: maxmax=FMAX(maxmax,meandiff[i]);
4939: /* printf("Back age= %d meandiff[%d]=%f, agefin=%d max[%d]=%f min[%d]=%f maxmax=%f\n", (int)age, i, meandiff[i],(int)agefin, i, max[i], i, min[i],maxmax); */
1.268 brouard 4940: } /* i loop */
1.217 brouard 4941: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 4942: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 4943: if(maxmax < ftolpl){
1.220 brouard 4944: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 4945: free_vector(min,1,nlstate);
4946: free_vector(max,1,nlstate);
4947: free_vector(meandiff,1,nlstate);
4948: return bprlim;
4949: }
1.288 brouard 4950: } /* agefin loop */
1.217 brouard 4951: /* After some age loop it doesn't converge */
1.288 brouard 4952: if(!first){
1.247 brouard 4953: first=1;
4954: printf("Warning: the back stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.0f years. Try to lower 'ftolpl'. Others in log file only...\n\
4955: Oldest age to start was %d-%d=%d, ncvloop=%d, ncvyear=%d\n", (int)age, maxmax, ftolpl, delaymax, (int)age, (int)delaymax, (int)agefin, ncvloop, *ncvyear);
4956: }
4957: fprintf(ficlog,"Warning: the back stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.0f years. Try to lower 'ftolpl'. \n\
1.217 brouard 4958: Oldest age to start was %d-%d=%d, ncvloop=%d, ncvyear=%d\n", (int)age, maxmax, ftolpl, delaymax, (int)age, (int)delaymax, (int)agefin, ncvloop, *ncvyear);
4959: /* Try to lower 'ftol', for example from 1.e-8 to 6.e-9.\n", ftolpl, (int)age, (int)delaymax, (int)agefin, ncvloop, (int)age-(int)agefin); */
4960: free_vector(min,1,nlstate);
4961: free_vector(max,1,nlstate);
4962: free_vector(meandiff,1,nlstate);
4963:
4964: return bprlim; /* should not reach here */
4965: }
4966:
1.126 brouard 4967: /*************** transition probabilities ***************/
4968:
4969: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
4970: {
1.138 brouard 4971: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 4972: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 4973: model to the ncovmodel covariates (including constant and age).
4974: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
4975: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
4976: ncth covariate in the global vector x is given by the formula:
4977: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
4978: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
4979: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
4980: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 4981: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 4982: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 4983: Sum on j ps[i][j] should equal to 1.
1.138 brouard 4984: */
4985: double s1, lnpijopii;
1.126 brouard 4986: /*double t34;*/
1.164 brouard 4987: int i,j, nc, ii, jj;
1.126 brouard 4988:
1.223 brouard 4989: for(i=1; i<= nlstate; i++){
4990: for(j=1; j<i;j++){
4991: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
4992: /*lnpijopii += param[i][j][nc]*cov[nc];*/
4993: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
4994: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
4995: }
4996: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 4997: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 4998: }
4999: for(j=i+1; j<=nlstate+ndeath;j++){
5000: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
5001: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
5002: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
5003: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
5004: }
5005: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 5006: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 5007: }
5008: }
1.218 brouard 5009:
1.223 brouard 5010: for(i=1; i<= nlstate; i++){
5011: s1=0;
5012: for(j=1; j<i; j++){
1.339 brouard 5013: /* printf("debug1 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 5014: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
5015: }
5016: for(j=i+1; j<=nlstate+ndeath; j++){
1.339 brouard 5017: /* printf("debug2 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 5018: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
5019: }
5020: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
5021: ps[i][i]=1./(s1+1.);
5022: /* Computing other pijs */
5023: for(j=1; j<i; j++)
1.325 brouard 5024: ps[i][j]= exp(ps[i][j])*ps[i][i];/* Bug valgrind */
1.223 brouard 5025: for(j=i+1; j<=nlstate+ndeath; j++)
5026: ps[i][j]= exp(ps[i][j])*ps[i][i];
5027: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
5028: } /* end i */
1.218 brouard 5029:
1.223 brouard 5030: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
5031: for(jj=1; jj<= nlstate+ndeath; jj++){
5032: ps[ii][jj]=0;
5033: ps[ii][ii]=1;
5034: }
5035: }
1.294 brouard 5036:
5037:
1.223 brouard 5038: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
5039: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
5040: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
5041: /* } */
5042: /* printf("\n "); */
5043: /* } */
5044: /* printf("\n ");printf("%lf ",cov[2]);*/
5045: /*
5046: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 5047: goto end;*/
1.266 brouard 5048: return ps; /* Pointer is unchanged since its call */
1.126 brouard 5049: }
5050:
1.218 brouard 5051: /*************** backward transition probabilities ***************/
5052:
5053: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ageminpar, double agemaxpar, double ***dnewm, double **doldm, double **dsavm, int ij ) */
5054: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
5055: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
5056: {
1.302 brouard 5057: /* Computes the backward probability at age agefin, cov[2], and covariate combination 'ij'. In fact cov is already filled and x too.
1.266 brouard 5058: * Call to pmij(cov and x), call to cross prevalence, sums and inverses, left multiply, and returns in **ps as well as **bmij.
1.222 brouard 5059: */
1.359 brouard 5060: int ii, j;
1.222 brouard 5061:
1.359 brouard 5062: double **pmij();
1.222 brouard 5063: double sumnew=0.;
1.218 brouard 5064: double agefin;
1.292 brouard 5065: double k3=0.; /* constant of the w_x diagonal matrix (in order for B to sum to 1 even for death state) */
1.222 brouard 5066: double **dnewm, **dsavm, **doldm;
5067: double **bbmij;
5068:
1.218 brouard 5069: doldm=ddoldms; /* global pointers */
1.222 brouard 5070: dnewm=ddnewms;
5071: dsavm=ddsavms;
1.318 brouard 5072:
5073: /* Debug */
5074: /* printf("Bmij ij=%d, cov[2}=%f\n", ij, cov[2]); */
1.222 brouard 5075: agefin=cov[2];
1.268 brouard 5076: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 5077: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 5078: the observed prevalence (with this covariate ij) at beginning of transition */
5079: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 5080:
5081: /* P_x */
1.325 brouard 5082: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm *//* Bug valgrind */
1.268 brouard 5083: /* outputs pmmij which is a stochastic matrix in row */
5084:
5085: /* Diag(w_x) */
1.292 brouard 5086: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 5087: sumnew=0.;
1.269 brouard 5088: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 5089: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.297 brouard 5090: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 5091: sumnew+=prevacurrent[(int)agefin][ii][ij];
5092: }
5093: if(sumnew >0.01){ /* At least some value in the prevalence */
5094: for (ii=1;ii<=nlstate+ndeath;ii++){
5095: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 5096: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 5097: }
5098: }else{
5099: for (ii=1;ii<=nlstate+ndeath;ii++){
5100: for (j=1;j<=nlstate+ndeath;j++)
5101: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
5102: }
5103: /* if(sumnew <0.9){ */
5104: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
5105: /* } */
5106: }
5107: k3=0.0; /* We put the last diagonal to 0 */
5108: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
5109: doldm[ii][ii]= k3;
5110: }
5111: /* End doldm, At the end doldm is diag[(w_i)] */
5112:
1.292 brouard 5113: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
5114: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 5115:
1.292 brouard 5116: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 5117: /* w1 p11 + w2 p21 only on live states N1./N..*N11/N1. + N2./N..*N21/N2.=(N11+N21)/N..=N.1/N.. */
1.222 brouard 5118: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 5119: sumnew=0.;
1.222 brouard 5120: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 5121: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 5122: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 5123: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 5124: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 5125: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 5126: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 5127: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 5128: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 5129: /* }else */
1.268 brouard 5130: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
5131: } /*End ii */
5132: } /* End j, At the end dsavm is diag[1/(w_1p1i+w_2 p2i)] for ALL states even if the sum is only for live states */
5133:
1.292 brouard 5134: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 5135: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 5136: /* end bmij */
1.266 brouard 5137: return ps; /*pointer is unchanged */
1.218 brouard 5138: }
1.217 brouard 5139: /*************** transition probabilities ***************/
5140:
1.218 brouard 5141: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 5142: {
5143: /* According to parameters values stored in x and the covariate's values stored in cov,
5144: computes the probability to be observed in state j being in state i by appying the
5145: model to the ncovmodel covariates (including constant and age).
5146: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
5147: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
5148: ncth covariate in the global vector x is given by the formula:
5149: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
5150: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
5151: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
5152: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
5153: Outputs ps[i][j] the probability to be observed in j being in j according to
5154: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
5155: */
5156: double s1, lnpijopii;
5157: /*double t34;*/
5158: int i,j, nc, ii, jj;
5159:
1.234 brouard 5160: for(i=1; i<= nlstate; i++){
5161: for(j=1; j<i;j++){
5162: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
5163: /*lnpijopii += param[i][j][nc]*cov[nc];*/
5164: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
5165: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
5166: }
5167: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
5168: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
5169: }
5170: for(j=i+1; j<=nlstate+ndeath;j++){
5171: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
5172: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
5173: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
5174: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
5175: }
5176: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
5177: }
5178: }
5179:
5180: for(i=1; i<= nlstate; i++){
5181: s1=0;
5182: for(j=1; j<i; j++){
5183: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
5184: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
5185: }
5186: for(j=i+1; j<=nlstate+ndeath; j++){
5187: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
5188: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
5189: }
5190: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
5191: ps[i][i]=1./(s1+1.);
5192: /* Computing other pijs */
5193: for(j=1; j<i; j++)
5194: ps[i][j]= exp(ps[i][j])*ps[i][i];
5195: for(j=i+1; j<=nlstate+ndeath; j++)
5196: ps[i][j]= exp(ps[i][j])*ps[i][i];
5197: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
5198: } /* end i */
5199:
5200: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
5201: for(jj=1; jj<= nlstate+ndeath; jj++){
5202: ps[ii][jj]=0;
5203: ps[ii][ii]=1;
5204: }
5205: }
1.296 brouard 5206: /* Added for prevbcast */ /* Transposed matrix too */
1.234 brouard 5207: for(jj=1; jj<= nlstate+ndeath; jj++){
5208: s1=0.;
5209: for(ii=1; ii<= nlstate+ndeath; ii++){
5210: s1+=ps[ii][jj];
5211: }
5212: for(ii=1; ii<= nlstate; ii++){
5213: ps[ii][jj]=ps[ii][jj]/s1;
5214: }
5215: }
5216: /* Transposition */
5217: for(jj=1; jj<= nlstate+ndeath; jj++){
5218: for(ii=jj; ii<= nlstate+ndeath; ii++){
5219: s1=ps[ii][jj];
5220: ps[ii][jj]=ps[jj][ii];
5221: ps[jj][ii]=s1;
5222: }
5223: }
5224: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
5225: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
5226: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
5227: /* } */
5228: /* printf("\n "); */
5229: /* } */
5230: /* printf("\n ");printf("%lf ",cov[2]);*/
5231: /*
5232: for(i=1; i<= npar; i++) printf("%f ",x[i]);
5233: goto end;*/
5234: return ps;
1.217 brouard 5235: }
5236:
5237:
1.126 brouard 5238: /**************** Product of 2 matrices ******************/
5239:
1.145 brouard 5240: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 5241: {
5242: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
5243: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
5244: /* in, b, out are matrice of pointers which should have been initialized
5245: before: only the contents of out is modified. The function returns
5246: a pointer to pointers identical to out */
1.145 brouard 5247: int i, j, k;
1.126 brouard 5248: for(i=nrl; i<= nrh; i++)
1.145 brouard 5249: for(k=ncolol; k<=ncoloh; k++){
5250: out[i][k]=0.;
5251: for(j=ncl; j<=nch; j++)
5252: out[i][k] +=in[i][j]*b[j][k];
5253: }
1.126 brouard 5254: return out;
5255: }
5256:
5257:
5258: /************* Higher Matrix Product ***************/
5259:
1.235 brouard 5260: double ***hpxij(double ***po, int nhstepm, double age, int hstepm, double *x, int nlstate, int stepm, double **oldm, double **savm, int ij, int nres )
1.126 brouard 5261: {
1.336 brouard 5262: /* Already optimized with precov.
5263: Computes the transition matrix starting at age 'age' and dummies values in each resultline (loop on ij to find the corresponding combination) to over
1.126 brouard 5264: 'nhstepm*hstepm*stepm' months (i.e. until
5265: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
5266: nhstepm*hstepm matrices.
5267: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
5268: (typically every 2 years instead of every month which is too big
5269: for the memory).
5270: Model is determined by parameters x and covariates have to be
5271: included manually here.
5272:
5273: */
5274:
1.359 brouard 5275: int i, j, d, h, k1;
1.131 brouard 5276: double **out, cov[NCOVMAX+1];
1.126 brouard 5277: double **newm;
1.187 brouard 5278: double agexact;
1.359 brouard 5279: /*double agebegin, ageend;*/
1.126 brouard 5280:
5281: /* Hstepm could be zero and should return the unit matrix */
5282: for (i=1;i<=nlstate+ndeath;i++)
5283: for (j=1;j<=nlstate+ndeath;j++){
5284: oldm[i][j]=(i==j ? 1.0 : 0.0);
5285: po[i][j][0]=(i==j ? 1.0 : 0.0);
5286: }
5287: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
5288: for(h=1; h <=nhstepm; h++){
5289: for(d=1; d <=hstepm; d++){
5290: newm=savm;
5291: /* Covariates have to be included here again */
5292: cov[1]=1.;
1.214 brouard 5293: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 5294: cov[2]=agexact;
1.319 brouard 5295: if(nagesqr==1){
1.227 brouard 5296: cov[3]= agexact*agexact;
1.319 brouard 5297: }
1.330 brouard 5298: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
5299: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
5300: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 5301: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 5302: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
5303: }else{
5304: cov[2+nagesqr+k1]=precov[nres][k1];
5305: }
5306: }/* End of loop on model equation */
5307: /* Old code */
5308: /* if( Dummy[k1]==0 && Typevar[k1]==0 ){ /\* Single dummy *\/ */
5309: /* /\* V(Tvarsel)=Tvalsel=Tresult[nres][pos](value); V(Tvresult[nres][pos] (variable): V(variable)=value) *\/ */
5310: /* /\* for (k=1; k<=nsd;k++) { /\\* For single dummy covariates only *\\/ *\/ */
5311: /* /\* /\\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\\/ *\/ */
5312: /* /\* codtabm(ij,k) (1 & (ij-1) >> (k-1))+1 *\/ */
5313: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
5314: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
5315: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
5316: /* /\* nsd 1 2 3 *\/ /\* Counting single dummies covar fixed or tv *\/ */
5317: /* /\*TvarsD[nsd] 4 3 1 *\/ /\* ID of single dummy cova fixed or timevary*\/ */
5318: /* /\*TvarsDind[k] 2 3 9 *\/ /\* position K of single dummy cova *\/ */
5319: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];or [codtabm(ij,TnsdVar[TvarsD[k]] *\/ */
5320: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
5321: /* /\* printf("hpxij Dummy combi=%d k=%d TvarsD[%d]=V%d TvarsDind[%d]=%d nbcode=%d cov=%lf codtabm(%d,TnsdVar[TvarsD[%d])=%d \n",ij,k, k, TvarsD[k],k,TvarsDind[k],nbcode[TvarsD[k]][codtabm(ij,TnsdVar[TvarsD[k]])],cov[2+nagesqr+TvarsDind[k]], ij, k, codtabm(ij,TnsdVar[TvarsD[k]])); *\/ */
5322: /* printf("hpxij Dummy combi=%d k1=%d Tvar[%d]=V%d cov[2+%d+%d]=%lf resultmodel[nres][%d]=%d nres/nresult=%d/%d \n",ij,k1,k1, Tvar[k1],nagesqr,k1,cov[2+nagesqr+k1],k1,resultmodel[nres][k1],nres,nresult); */
5323: /* printf("hpxij new Dummy precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
5324: /* }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /\* Single quantitative variables *\/ */
5325: /* /\* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline *\/ */
5326: /* cov[2+nagesqr+k1]=Tqresult[nres][resultmodel[nres][k1]]; */
5327: /* /\* for (k=1; k<=nsq;k++) { /\\* For single varying covariates only *\\/ *\/ */
5328: /* /\* /\\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\\/ *\/ */
5329: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
5330: /* printf("hPxij Quantitative k1=%d resultmodel[nres][%d]=%d,Tqresult[%d][%d]=%f\n",k1,k1,resultmodel[nres][k1],nres,resultmodel[nres][k1],Tqresult[nres][resultmodel[nres][k1]]); */
5331: /* printf("hpxij new Quanti precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
5332: /* }else if( Dummy[k1]==2 ){ /\* For dummy with age product *\/ */
5333: /* /\* Tvar[k1] Variable in the age product age*V1 is 1 *\/ */
5334: /* /\* [Tinvresult[nres][V1] is its value in the resultline nres *\/ */
5335: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvar[k1]]*cov[2]; */
5336: /* printf("DhPxij Dummy with age k1=%d Tvar[%d]=%d TinvDoQresult[nres=%d][%d]=%.f age=%.2f,cov[2+%d+%d]=%.3f\n",k1,k1,Tvar[k1],nres,TinvDoQresult[nres][Tvar[k1]],cov[2],nagesqr,k1,cov[2+nagesqr+k1]); */
5337: /* printf("hpxij new Dummy with age product precov[nres=%d][k1=%d]=%.4f * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
5338:
5339: /* /\* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; *\/ */
5340: /* /\* for (k=1; k<=cptcovage;k++){ /\\* For product with age V1+V1*age +V4 +age*V3 *\\/ *\/ */
5341: /* /\* 1+2 Tage[1]=2 TVar[2]=1 Dummy[2]=2, Tage[2]=4 TVar[4]=3 Dummy[4]=3 quant*\/ */
5342: /* /\* *\/ */
1.330 brouard 5343: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
5344: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
5345: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
1.332 brouard 5346: /* /\*cptcovage=2 1 2 *\/ */
5347: /* /\*Tage[k]= 5 8 *\/ */
5348: /* }else if( Dummy[k1]==3 ){ /\* For quant with age product *\/ */
5349: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
5350: /* printf("QhPxij Quant with age k1=%d resultmodel[nres][%d]=%d,Tqresult[%d][%d]=%f\n",k1,k1,resultmodel[nres][k1],nres,resultmodel[nres][k1],Tqresult[nres][resultmodel[nres][k1]]); */
5351: /* printf("hpxij new Quanti with age product precov[nres=%d][k1=%d] * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
5352: /* /\* if(Dummy[Tage[k]]== 2){ /\\* dummy with age *\\/ *\/ */
5353: /* /\* /\\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\\* dummy with age *\\\/ *\\/ *\/ */
5354: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\\/ *\/ */
5355: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\\/ *\/ */
5356: /* /\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\/ */
5357: /* /\* printf("hPxij Age combi=%d k=%d cptcovage=%d Tage[%d]=%d Tvar[Tage[%d]]=V%d nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[Tvar[Tage[k]]]])]=%d nres=%d\n",ij,k,cptcovage,k,Tage[k],k,Tvar[Tage[k]], nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[Tvar[Tage[k]]])],nres); *\/ */
5358: /* /\* } else if(Dummy[Tage[k]]== 3){ /\\* quantitative with age *\\/ *\/ */
5359: /* /\* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; *\/ */
5360: /* /\* } *\/ */
5361: /* /\* printf("hPxij Age combi=%d k=%d Tage[%d]=V%d Tqresult[%d][%d]=%f\n",ij,k,k,Tage[k],nres,k,Tqresult[nres][k]); *\/ */
5362: /* }else if(Typevar[k1]==2 ){ /\* For product (not with age) *\/ */
5363: /* /\* for (k=1; k<=cptcovprod;k++){ /\\* For product without age *\\/ *\/ */
5364: /* /\* /\\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\\/ *\/ */
5365: /* /\* /\\* k 1 2 3 4 5 6 7 8 9 *\\/ *\/ */
5366: /* /\* /\\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\\/ *\/ */
5367: /* /\* /\\*cptcovprod=1 1 2 *\\/ *\/ */
5368: /* /\* /\\*Tprod[]= 4 7 *\\/ *\/ */
5369: /* /\* /\\*Tvard[][1] 4 1 *\\/ *\/ */
5370: /* /\* /\\*Tvard[][2] 3 2 *\\/ *\/ */
1.330 brouard 5371:
1.332 brouard 5372: /* /\* printf("hPxij Prod ij=%d k=%d Tprod[%d]=%d Tvard[%d][1]=V%d, Tvard[%d][2]=V%d nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])]=%d nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][1])]=%d\n",ij,k,k,Tprod[k], k,Tvard[k][1], k,Tvard[k][2],nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])],nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]); *\/ */
5373: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
5374: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]]; */
5375: /* printf("hPxij Prod ij=%d k1=%d cov[2+%d+%d]=%.5f Tvard[%d][1]=V%d * Tvard[%d][2]=V%d ; TinvDoQresult[nres][Tvardk[k1][1]]=%.4f * TinvDoQresult[nres][Tvardk[k1][1]]=%.4f\n",ij,k1,nagesqr,k1,cov[2+nagesqr+k1],k1,Tvardk[k1][1], k1,Tvardk[k1][2], TinvDoQresult[nres][Tvardk[k1][1]], TinvDoQresult[nres][Tvardk[k1][2]]); */
5376: /* printf("hpxij new Product no age product precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
5377:
5378: /* /\* if(Dummy[Tvardk[k1][1]]==0){ *\/ */
5379: /* /\* if(Dummy[Tvardk[k1][2]]==0){ /\\* Product of dummies *\\/ *\/ */
5380: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
5381: /* /\* cov[2+nagesqr+k1]=Tinvresult[nres][Tvardk[k1][1]] * Tinvresult[nres][Tvardk[k1][2]]; *\/ */
5382: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,TnsdVar[Tvard[k][1]])] * nbcode[Tvard[k][2]][codtabm(ij,TnsdVar[Tvard[k][2]])]; *\/ */
5383: /* /\* }else{ /\\* Product of dummy by quantitative *\\/ *\/ */
5384: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,TnsdVar[Tvard[k][1]])] * Tqresult[nres][k]; *\/ */
5385: /* /\* cov[2+nagesqr+k1]=Tresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]]; *\/ */
5386: /* /\* } *\/ */
5387: /* /\* }else{ /\\* Product of quantitative by...*\\/ *\/ */
5388: /* /\* if(Dummy[Tvard[k][2]]==0){ /\\* quant by dummy *\\/ *\/ */
5389: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][Tvard[k][1]]; *\\/ *\/ */
5390: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
5391: /* /\* }else{ /\\* Product of two quant *\\/ *\/ */
5392: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\\/ *\/ */
5393: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
5394: /* /\* } *\/ */
5395: /* /\* }/\\*end of products quantitative *\\/ *\/ */
5396: /* }/\*end of products *\/ */
5397: /* } /\* End of loop on model equation *\/ */
1.235 brouard 5398: /* for (k=1; k<=cptcovn;k++) */
5399: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
5400: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
5401: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
5402: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
5403: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 5404:
5405:
1.126 brouard 5406: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
5407: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.319 brouard 5408: /* right multiplication of oldm by the current matrix */
1.126 brouard 5409: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
5410: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 5411: /* if((int)age == 70){ */
5412: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
5413: /* for(i=1; i<=nlstate+ndeath; i++) { */
5414: /* printf("%d pmmij ",i); */
5415: /* for(j=1;j<=nlstate+ndeath;j++) { */
5416: /* printf("%f ",pmmij[i][j]); */
5417: /* } */
5418: /* printf(" oldm "); */
5419: /* for(j=1;j<=nlstate+ndeath;j++) { */
5420: /* printf("%f ",oldm[i][j]); */
5421: /* } */
5422: /* printf("\n"); */
5423: /* } */
5424: /* } */
1.126 brouard 5425: savm=oldm;
5426: oldm=newm;
5427: }
5428: for(i=1; i<=nlstate+ndeath; i++)
5429: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 5430: po[i][j][h]=newm[i][j];
5431: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 5432: }
1.128 brouard 5433: /*printf("h=%d ",h);*/
1.126 brouard 5434: } /* end h */
1.267 brouard 5435: /* printf("\n H=%d \n",h); */
1.126 brouard 5436: return po;
5437: }
5438:
1.217 brouard 5439: /************* Higher Back Matrix Product ***************/
1.218 brouard 5440: /* double ***hbxij(double ***po, int nhstepm, double age, int hstepm, double *x, double ***prevacurrent, int nlstate, int stepm, double **oldm, double **savm, double **dnewm, double **doldm, double **dsavm, int ij ) */
1.267 brouard 5441: double ***hbxij(double ***po, int nhstepm, double age, int hstepm, double *x, double ***prevacurrent, int nlstate, int stepm, int ij, int nres )
1.217 brouard 5442: {
1.332 brouard 5443: /* For dummy covariates given in each resultline (for historical, computes the corresponding combination ij),
5444: computes the transition matrix starting at age 'age' over
1.217 brouard 5445: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 5446: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
5447: nhstepm*hstepm matrices.
5448: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
5449: (typically every 2 years instead of every month which is too big
1.217 brouard 5450: for the memory).
1.218 brouard 5451: Model is determined by parameters x and covariates have to be
1.266 brouard 5452: included manually here. Then we use a call to bmij(x and cov)
5453: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 5454: */
1.217 brouard 5455:
1.359 brouard 5456: int i, j, d, h, k1;
1.266 brouard 5457: double **out, cov[NCOVMAX+1], **bmij();
5458: double **newm, ***newmm;
1.217 brouard 5459: double agexact;
1.359 brouard 5460: /*double agebegin, ageend;*/
1.222 brouard 5461: double **oldm, **savm;
1.217 brouard 5462:
1.266 brouard 5463: newmm=po; /* To be saved */
5464: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 5465: /* Hstepm could be zero and should return the unit matrix */
5466: for (i=1;i<=nlstate+ndeath;i++)
5467: for (j=1;j<=nlstate+ndeath;j++){
5468: oldm[i][j]=(i==j ? 1.0 : 0.0);
5469: po[i][j][0]=(i==j ? 1.0 : 0.0);
5470: }
5471: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
5472: for(h=1; h <=nhstepm; h++){
5473: for(d=1; d <=hstepm; d++){
5474: newm=savm;
5475: /* Covariates have to be included here again */
5476: cov[1]=1.;
1.271 brouard 5477: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 5478: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
1.318 brouard 5479: /* Debug */
5480: /* printf("hBxij age=%lf, agexact=%lf\n", age, agexact); */
1.217 brouard 5481: cov[2]=agexact;
1.332 brouard 5482: if(nagesqr==1){
1.222 brouard 5483: cov[3]= agexact*agexact;
1.332 brouard 5484: }
5485: /** New code */
5486: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 5487: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 5488: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.325 brouard 5489: }else{
1.332 brouard 5490: cov[2+nagesqr+k1]=precov[nres][k1];
1.325 brouard 5491: }
1.332 brouard 5492: }/* End of loop on model equation */
5493: /** End of new code */
5494: /** This was old code */
5495: /* for (k=1; k<=nsd;k++){ /\* For single dummy covariates only *\//\* cptcovn error *\/ */
5496: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
5497: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
5498: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])];/\* Bug valgrind *\/ */
5499: /* /\* printf("hbxij Dummy agexact=%.0f combi=%d k=%d TvarsD[%d]=V%d TvarsDind[%d]=%d nbcode=%d cov[%d]=%lf codtabm(%d,Tvar[%d])=%d \n",agexact,ij,k, k, TvarsD[k],k,TvarsDind[k],nbcode[TvarsD[k]][codtabm(ij,k)],2+nagesqr+TvarsDind[k],cov[2+nagesqr+TvarsDind[k]], ij, k, codtabm(ij,k)); *\/ */
5500: /* } */
5501: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
5502: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
5503: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
5504: /* /\* printf("hPxij Quantitative k=%d TvarsQind[%d]=%d, TvarsQ[%d]=V%d,Tqresult[%d][%d]=%f\n",k,k,TvarsQind[k],k,TvarsQ[k],nres,k,Tqresult[nres][k]); *\/ */
5505: /* } */
5506: /* for (k=1; k<=cptcovage;k++){ /\* Should start at cptcovn+1 *\//\* For product with age *\/ */
5507: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age error!!!*\\/ *\/ */
5508: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
5509: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
5510: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
5511: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
5512: /* } */
5513: /* /\* printf("hBxij Age combi=%d k=%d Tage[%d]=V%d Tqresult[%d][%d]=%f\n",ij,k,k,Tage[k],nres,k,Tqresult[nres][k]); *\/ */
5514: /* } */
5515: /* for (k=1; k<=cptcovprod;k++){ /\* Useless because included in cptcovn *\/ */
5516: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])]*nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
5517: /* if(Dummy[Tvard[k][1]]==0){ */
5518: /* if(Dummy[Tvard[k][2]]==0){ */
5519: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][1])]; */
5520: /* }else{ */
5521: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
5522: /* } */
5523: /* }else{ */
5524: /* if(Dummy[Tvard[k][2]]==0){ */
5525: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
5526: /* }else{ */
5527: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
5528: /* } */
5529: /* } */
5530: /* } */
5531: /* /\*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*\/ */
5532: /* /\*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*\/ */
5533: /** End of old code */
5534:
1.218 brouard 5535: /* Careful transposed matrix */
1.266 brouard 5536: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 5537: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 5538: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 5539: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.325 brouard 5540: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);/* Bug valgrind */
1.217 brouard 5541: /* if((int)age == 70){ */
5542: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
5543: /* for(i=1; i<=nlstate+ndeath; i++) { */
5544: /* printf("%d pmmij ",i); */
5545: /* for(j=1;j<=nlstate+ndeath;j++) { */
5546: /* printf("%f ",pmmij[i][j]); */
5547: /* } */
5548: /* printf(" oldm "); */
5549: /* for(j=1;j<=nlstate+ndeath;j++) { */
5550: /* printf("%f ",oldm[i][j]); */
5551: /* } */
5552: /* printf("\n"); */
5553: /* } */
5554: /* } */
5555: savm=oldm;
5556: oldm=newm;
5557: }
5558: for(i=1; i<=nlstate+ndeath; i++)
5559: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 5560: po[i][j][h]=newm[i][j];
1.268 brouard 5561: /* if(h==nhstepm) */
5562: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 5563: }
1.268 brouard 5564: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 5565: } /* end h */
1.268 brouard 5566: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 5567: return po;
5568: }
5569:
5570:
1.162 brouard 5571: #ifdef NLOPT
5572: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
5573: double fret;
5574: double *xt;
5575: int j;
5576: myfunc_data *d2 = (myfunc_data *) pd;
5577: /* xt = (p1-1); */
5578: xt=vector(1,n);
5579: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
5580:
5581: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
5582: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
5583: printf("Function = %.12lf ",fret);
5584: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
5585: printf("\n");
5586: free_vector(xt,1,n);
5587: return fret;
5588: }
5589: #endif
1.126 brouard 5590:
5591: /*************** log-likelihood *************/
5592: double func( double *x)
5593: {
1.336 brouard 5594: int i, ii, j, k, mi, d, kk, kf=0;
1.226 brouard 5595: int ioffset=0;
1.339 brouard 5596: int ipos=0,iposold=0,ncovv=0;
5597:
1.340 brouard 5598: double cotvarv, cotvarvold;
1.226 brouard 5599: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
5600: double **out;
5601: double lli; /* Individual log likelihood */
5602: int s1, s2;
1.228 brouard 5603: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
1.336 brouard 5604:
1.226 brouard 5605: double bbh, survp;
5606: double agexact;
1.336 brouard 5607: double agebegin, ageend;
1.226 brouard 5608: /*extern weight */
5609: /* We are differentiating ll according to initial status */
5610: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
5611: /*for(i=1;i<imx;i++)
5612: printf(" %d\n",s[4][i]);
5613: */
1.162 brouard 5614:
1.226 brouard 5615: ++countcallfunc;
1.162 brouard 5616:
1.226 brouard 5617: cov[1]=1.;
1.126 brouard 5618:
1.226 brouard 5619: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 5620: ioffset=0;
1.226 brouard 5621: if(mle==1){
5622: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
5623: /* Computes the values of the ncovmodel covariates of the model
5624: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
5625: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
5626: to be observed in j being in i according to the model.
5627: */
1.243 brouard 5628: ioffset=2+nagesqr ;
1.233 brouard 5629: /* Fixed */
1.345 brouard 5630: for (kf=1; kf<=ncovf;kf++){ /* For each fixed covariate dummy or quant or prod */
1.319 brouard 5631: /* # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi */
5632: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
5633: /* TvarF[1]=Tvar[6]=2, TvarF[2]=Tvar[7]=7, TvarF[3]=Tvar[9]=1 ID of fixed covariates or product V2, V1*V2, V1 */
1.320 brouard 5634: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.336 brouard 5635: cov[ioffset+TvarFind[kf]]=covar[Tvar[TvarFind[kf]]][i];/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, only V1 is fixed (TvarFind[1]=6)*/
1.319 brouard 5636: /* V1*V2 (7) TvarFind[2]=7, TvarFind[3]=9 */
1.234 brouard 5637: }
1.226 brouard 5638: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
1.319 brouard 5639: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
1.226 brouard 5640: has been calculated etc */
5641: /* For an individual i, wav[i] gives the number of effective waves */
5642: /* We compute the contribution to Likelihood of each effective transition
5643: mw[mi][i] is real wave of the mi th effectve wave */
5644: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
5645: s2=s[mw[mi+1][i]][i];
1.341 brouard 5646: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i] because now is moved after nvocol+nqv
1.226 brouard 5647: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
5648: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
5649: */
1.336 brouard 5650: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
5651: /* Wave varying (but not age varying) */
1.339 brouard 5652: /* for(k=1; k <= ncovv ; k++){ /\* Varying covariates in the model (single and product but no age )"V5+V4+V3+V4*V3+V5*age+V1*age+V1" +TvarVind 1,2,3,4(V4*V3) Tvar[1]@7{5, 4, 3, 6, 5, 1, 1 ; 6 because the created covar is after V5 and is 6, minus 1+1, 3,2,1,4 positions in cotvar*\/ */
5653: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; but where is the crossproduct? *\/ */
5654: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
5655: /* } */
1.340 brouard 5656: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age )*/
5657: itv=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
5658: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
1.345 brouard 5659: if(FixedV[itv]!=0){ /* Not a fixed covariate */
1.341 brouard 5660: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]][i]; /* cotvar[wav][ncovcol+nqv+iv][i] */
1.340 brouard 5661: }else{ /* fixed covariate */
1.345 brouard 5662: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
1.340 brouard 5663: }
1.339 brouard 5664: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 brouard 5665: cotvarvold=cotvarv;
5666: }else{ /* A second product */
5667: cotvarv=cotvarv*cotvarvold;
1.339 brouard 5668: }
5669: iposold=ipos;
1.340 brouard 5670: cov[ioffset+ipos]=cotvarv;
1.234 brouard 5671: }
1.339 brouard 5672: /* for products of time varying to be done */
1.234 brouard 5673: for (ii=1;ii<=nlstate+ndeath;ii++)
5674: for (j=1;j<=nlstate+ndeath;j++){
5675: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
5676: savm[ii][j]=(ii==j ? 1.0 : 0.0);
5677: }
1.336 brouard 5678:
5679: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
5680: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
1.234 brouard 5681: for(d=0; d<dh[mi][i]; d++){
5682: newm=savm;
5683: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
5684: cov[2]=agexact;
5685: if(nagesqr==1)
5686: cov[3]= agexact*agexact; /* Should be changed here */
1.349 brouard 5687: /* for (kk=1; kk<=cptcovage;kk++) { */
5688: /* if(!FixedV[Tvar[Tage[kk]]]) */
5689: /* cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /\* Tage[kk] gives the data-covariate associated with age *\/ */
5690: /* else */
5691: /* cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]*agexact; /\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */
5692: /* } */
5693: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
5694: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
5695: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
5696: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
5697: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
5698: }else{ /* fixed covariate */
5699: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
5700: }
5701: if(ipos!=iposold){ /* Not a product or first of a product */
5702: cotvarvold=cotvarv;
5703: }else{ /* A second product */
5704: cotvarv=cotvarv*cotvarvold;
5705: }
5706: iposold=ipos;
5707: cov[ioffset+ipos]=cotvarv*agexact;
5708: /* For products */
1.234 brouard 5709: }
1.349 brouard 5710:
1.234 brouard 5711: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
5712: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
5713: savm=oldm;
5714: oldm=newm;
5715: } /* end mult */
5716:
5717: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
5718: /* But now since version 0.9 we anticipate for bias at large stepm.
5719: * If stepm is larger than one month (smallest stepm) and if the exact delay
5720: * (in months) between two waves is not a multiple of stepm, we rounded to
5721: * the nearest (and in case of equal distance, to the lowest) interval but now
5722: * we keep into memory the bias bh[mi][i] and also the previous matrix product
5723: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
5724: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 5725: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
5726: * -stepm/2 to stepm/2 .
5727: * For stepm=1 the results are the same as for previous versions of Imach.
5728: * For stepm > 1 the results are less biased than in previous versions.
5729: */
1.234 brouard 5730: s1=s[mw[mi][i]][i];
5731: s2=s[mw[mi+1][i]][i];
5732: bbh=(double)bh[mi][i]/(double)stepm;
5733: /* bias bh is positive if real duration
5734: * is higher than the multiple of stepm and negative otherwise.
5735: */
5736: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
5737: if( s2 > nlstate){
5738: /* i.e. if s2 is a death state and if the date of death is known
5739: then the contribution to the likelihood is the probability to
5740: die between last step unit time and current step unit time,
5741: which is also equal to probability to die before dh
5742: minus probability to die before dh-stepm .
5743: In version up to 0.92 likelihood was computed
5744: as if date of death was unknown. Death was treated as any other
5745: health state: the date of the interview describes the actual state
5746: and not the date of a change in health state. The former idea was
5747: to consider that at each interview the state was recorded
5748: (healthy, disable or death) and IMaCh was corrected; but when we
5749: introduced the exact date of death then we should have modified
5750: the contribution of an exact death to the likelihood. This new
5751: contribution is smaller and very dependent of the step unit
5752: stepm. It is no more the probability to die between last interview
5753: and month of death but the probability to survive from last
5754: interview up to one month before death multiplied by the
5755: probability to die within a month. Thanks to Chris
5756: Jackson for correcting this bug. Former versions increased
5757: mortality artificially. The bad side is that we add another loop
5758: which slows down the processing. The difference can be up to 10%
5759: lower mortality.
5760: */
5761: /* If, at the beginning of the maximization mostly, the
5762: cumulative probability or probability to be dead is
5763: constant (ie = 1) over time d, the difference is equal to
5764: 0. out[s1][3] = savm[s1][3]: probability, being at state
5765: s1 at precedent wave, to be dead a month before current
5766: wave is equal to probability, being at state s1 at
5767: precedent wave, to be dead at mont of the current
5768: wave. Then the observed probability (that this person died)
5769: is null according to current estimated parameter. In fact,
5770: it should be very low but not zero otherwise the log go to
5771: infinity.
5772: */
1.183 brouard 5773: /* #ifdef INFINITYORIGINAL */
5774: /* lli=log(out[s1][s2] - savm[s1][s2]); */
5775: /* #else */
5776: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
5777: /* lli=log(mytinydouble); */
5778: /* else */
5779: /* lli=log(out[s1][s2] - savm[s1][s2]); */
5780: /* #endif */
1.226 brouard 5781: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 5782:
1.226 brouard 5783: } else if ( s2==-1 ) { /* alive */
5784: for (j=1,survp=0. ; j<=nlstate; j++)
5785: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
5786: /*survp += out[s1][j]; */
5787: lli= log(survp);
5788: }
1.336 brouard 5789: /* else if (s2==-4) { */
5790: /* for (j=3,survp=0. ; j<=nlstate; j++) */
5791: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
5792: /* lli= log(survp); */
5793: /* } */
5794: /* else if (s2==-5) { */
5795: /* for (j=1,survp=0. ; j<=2; j++) */
5796: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
5797: /* lli= log(survp); */
5798: /* } */
1.226 brouard 5799: else{
5800: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
5801: /* lli= (savm[s1][s2]>(double)1.e-8 ?log((1.+bbh)*out[s1][s2]- bbh*(savm[s1][s2])):log((1.+bbh)*out[s1][s2]));*/ /* linear interpolation */
5802: }
5803: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
5804: /*if(lli ==000.0)*/
1.340 brouard 5805: /* printf("num[i], i=%d, bbh= %f lli=%f savm=%f out=%f %d\n",bbh,lli,savm[s1][s2], out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]],i); */
1.226 brouard 5806: ipmx +=1;
5807: sw += weight[i];
5808: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
5809: /* if (lli < log(mytinydouble)){ */
5810: /* printf("Close to inf lli = %.10lf < %.10lf i= %d mi= %d, s[%d][i]=%d s1=%d s2=%d\n", lli,log(mytinydouble), i, mi,mw[mi][i], s[mw[mi][i]][i], s1,s2); */
5811: /* fprintf(ficlog,"Close to inf lli = %.10lf i= %d mi= %d, s[mw[mi][i]][i]=%d\n", lli, i, mi,s[mw[mi][i]][i]); */
5812: /* } */
5813: } /* end of wave */
5814: } /* end of individual */
5815: } else if(mle==2){
5816: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.319 brouard 5817: ioffset=2+nagesqr ;
5818: for (k=1; k<=ncovf;k++)
5819: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];
1.226 brouard 5820: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 5821: for(k=1; k <= ncovv ; k++){
1.341 brouard 5822: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; /* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
1.319 brouard 5823: }
1.226 brouard 5824: for (ii=1;ii<=nlstate+ndeath;ii++)
5825: for (j=1;j<=nlstate+ndeath;j++){
5826: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
5827: savm[ii][j]=(ii==j ? 1.0 : 0.0);
5828: }
5829: for(d=0; d<=dh[mi][i]; d++){
5830: newm=savm;
5831: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
5832: cov[2]=agexact;
5833: if(nagesqr==1)
5834: cov[3]= agexact*agexact;
5835: for (kk=1; kk<=cptcovage;kk++) {
5836: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
5837: }
5838: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
5839: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
5840: savm=oldm;
5841: oldm=newm;
5842: } /* end mult */
5843:
5844: s1=s[mw[mi][i]][i];
5845: s2=s[mw[mi+1][i]][i];
5846: bbh=(double)bh[mi][i]/(double)stepm;
5847: lli= (savm[s1][s2]>(double)1.e-8 ?log((1.+bbh)*out[s1][s2]- bbh*(savm[s1][s2])):log((1.+bbh)*out[s1][s2])); /* linear interpolation */
5848: ipmx +=1;
5849: sw += weight[i];
5850: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
5851: } /* end of wave */
5852: } /* end of individual */
5853: } else if(mle==3){ /* exponential inter-extrapolation */
5854: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
5855: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
5856: for(mi=1; mi<= wav[i]-1; mi++){
5857: for (ii=1;ii<=nlstate+ndeath;ii++)
5858: for (j=1;j<=nlstate+ndeath;j++){
5859: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
5860: savm[ii][j]=(ii==j ? 1.0 : 0.0);
5861: }
5862: for(d=0; d<dh[mi][i]; d++){
5863: newm=savm;
5864: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
5865: cov[2]=agexact;
5866: if(nagesqr==1)
5867: cov[3]= agexact*agexact;
5868: for (kk=1; kk<=cptcovage;kk++) {
1.340 brouard 5869: if(!FixedV[Tvar[Tage[kk]]])
5870: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
5871: else
1.341 brouard 5872: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]*agexact; /* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
1.226 brouard 5873: }
5874: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
5875: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
5876: savm=oldm;
5877: oldm=newm;
5878: } /* end mult */
5879:
5880: s1=s[mw[mi][i]][i];
5881: s2=s[mw[mi+1][i]][i];
5882: bbh=(double)bh[mi][i]/(double)stepm;
5883: lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2])); /* exponential inter-extrapolation */
5884: ipmx +=1;
5885: sw += weight[i];
5886: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
5887: } /* end of wave */
5888: } /* end of individual */
5889: }else if (mle==4){ /* ml=4 no inter-extrapolation */
5890: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
5891: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
5892: for(mi=1; mi<= wav[i]-1; mi++){
5893: for (ii=1;ii<=nlstate+ndeath;ii++)
5894: for (j=1;j<=nlstate+ndeath;j++){
5895: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
5896: savm[ii][j]=(ii==j ? 1.0 : 0.0);
5897: }
5898: for(d=0; d<dh[mi][i]; d++){
5899: newm=savm;
5900: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
5901: cov[2]=agexact;
5902: if(nagesqr==1)
5903: cov[3]= agexact*agexact;
5904: for (kk=1; kk<=cptcovage;kk++) {
5905: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
5906: }
1.126 brouard 5907:
1.226 brouard 5908: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
5909: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
5910: savm=oldm;
5911: oldm=newm;
5912: } /* end mult */
5913:
5914: s1=s[mw[mi][i]][i];
5915: s2=s[mw[mi+1][i]][i];
5916: if( s2 > nlstate){
5917: lli=log(out[s1][s2] - savm[s1][s2]);
5918: } else if ( s2==-1 ) { /* alive */
5919: for (j=1,survp=0. ; j<=nlstate; j++)
5920: survp += out[s1][j];
5921: lli= log(survp);
5922: }else{
5923: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
5924: }
5925: ipmx +=1;
5926: sw += weight[i];
5927: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.343 brouard 5928: /* printf("num[i]=%09ld, i=%6d s1=%1d s2=%1d mi=%1d mw=%1d dh=%3d prob=%10.6f w=%6.4f out=%10.6f sav=%10.6f\n",num[i],i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2])); */
1.226 brouard 5929: } /* end of wave */
5930: } /* end of individual */
5931: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
5932: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
5933: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
5934: for(mi=1; mi<= wav[i]-1; mi++){
5935: for (ii=1;ii<=nlstate+ndeath;ii++)
5936: for (j=1;j<=nlstate+ndeath;j++){
5937: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
5938: savm[ii][j]=(ii==j ? 1.0 : 0.0);
5939: }
5940: for(d=0; d<dh[mi][i]; d++){
5941: newm=savm;
5942: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
5943: cov[2]=agexact;
5944: if(nagesqr==1)
5945: cov[3]= agexact*agexact;
5946: for (kk=1; kk<=cptcovage;kk++) {
1.340 brouard 5947: if(!FixedV[Tvar[Tage[kk]]])
5948: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
5949: else
1.341 brouard 5950: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]*agexact; /* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
1.226 brouard 5951: }
1.126 brouard 5952:
1.226 brouard 5953: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
5954: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
5955: savm=oldm;
5956: oldm=newm;
5957: } /* end mult */
5958:
5959: s1=s[mw[mi][i]][i];
5960: s2=s[mw[mi+1][i]][i];
5961: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
5962: ipmx +=1;
5963: sw += weight[i];
5964: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
5965: /*printf("i=%6d s1=%1d s2=%1d mi=%1d mw=%1d dh=%3d prob=%10.6f w=%6.4f out=%10.6f sav=%10.6f\n",i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],out[s1][s2],savm[s1][s2]);*/
5966: } /* end of wave */
5967: } /* end of individual */
5968: } /* End of if */
5969: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
5970: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
5971: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
5972: return -l;
1.126 brouard 5973: }
5974:
5975: /*************** log-likelihood *************/
5976: double funcone( double *x)
5977: {
1.228 brouard 5978: /* Same as func but slower because of a lot of printf and if */
1.359 brouard 5979: int i, ii, j, k, mi, d, kv=0, kf=0;
1.228 brouard 5980: int ioffset=0;
1.339 brouard 5981: int ipos=0,iposold=0,ncovv=0;
5982:
1.340 brouard 5983: double cotvarv, cotvarvold;
1.131 brouard 5984: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 5985: double **out;
5986: double lli; /* Individual log likelihood */
5987: double llt;
5988: int s1, s2;
1.228 brouard 5989: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
5990:
1.126 brouard 5991: double bbh, survp;
1.187 brouard 5992: double agexact;
1.214 brouard 5993: double agebegin, ageend;
1.126 brouard 5994: /*extern weight */
5995: /* We are differentiating ll according to initial status */
5996: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
5997: /*for(i=1;i<imx;i++)
5998: printf(" %d\n",s[4][i]);
5999: */
6000: cov[1]=1.;
6001:
6002: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 6003: ioffset=0;
6004: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.336 brouard 6005: /* Computes the values of the ncovmodel covariates of the model
6006: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
6007: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
6008: to be observed in j being in i according to the model.
6009: */
1.243 brouard 6010: /* ioffset=2+nagesqr+cptcovage; */
6011: ioffset=2+nagesqr;
1.232 brouard 6012: /* Fixed */
1.224 brouard 6013: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 6014: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
1.349 brouard 6015: for (kf=1; kf<=ncovf;kf++){ /* V2 + V3 + V4 Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */
1.339 brouard 6016: /* printf("Debug3 TvarFind[%d]=%d",kf, TvarFind[kf]); */
6017: /* printf(" Tvar[TvarFind[kf]]=%d", Tvar[TvarFind[kf]]); */
6018: /* printf(" i=%d covar[Tvar[TvarFind[kf]]][i]=%f\n",i,covar[Tvar[TvarFind[kf]]][i]); */
1.335 brouard 6019: cov[ioffset+TvarFind[kf]]=covar[Tvar[TvarFind[kf]]][i];/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, only V1 is fixed (k=6)*/
1.232 brouard 6020: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
6021: /* cov[2+6]=covar[Tvar[6]][i]; */
6022: /* cov[2+6]=covar[2][i]; V2 */
6023: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
6024: /* cov[2+7]=covar[Tvar[7]][i]; */
6025: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
6026: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
6027: /* cov[2+9]=covar[Tvar[9]][i]; */
6028: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 6029: }
1.336 brouard 6030: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
6031: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
6032: has been calculated etc */
6033: /* For an individual i, wav[i] gives the number of effective waves */
6034: /* We compute the contribution to Likelihood of each effective transition
6035: mw[mi][i] is real wave of the mi th effectve wave */
6036: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
6037: s2=s[mw[mi+1][i]][i];
1.341 brouard 6038: And the iv th varying covariate in the DATA is the cotvar[mw[mi+1][i]][ncovcol+nqv+iv][i]
1.336 brouard 6039: */
6040: /* This part may be useless now because everythin should be in covar */
1.232 brouard 6041: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
6042: /* cov[++ioffset]=coqvar[TvarFQ[k]][i];/\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, only V2 and V1*V2 is fixed (k=6 and 7?)*\/ */
6043: /* } */
1.231 brouard 6044: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
6045: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
6046: /* } */
1.225 brouard 6047:
1.233 brouard 6048:
6049: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.339 brouard 6050: /* Wave varying (but not age varying) *//* V1+V3+age*V1+age*V3+V1*V3 with V4 tv and V5 tvq k= 1 to 5 and extra at V(5+1)=6 for V1*V3 */
6051: /* for(k=1; k <= ncovv ; k++){ /\* Varying covariates (single and product but no age )*\/ */
6052: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; *\/ */
6053: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
6054: /* } */
6055:
6056: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
6057: /* model V1+V3+age*V1+age*V3+V1*V3 */
6058: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
6059: /* TvarVV[1]=V3 (first time varying in the model equation, TvarVV[2]=V1 (in V1*V3) TvarVV[3]=3(V3) */
6060: /* We need the position of the time varying or product in the model */
6061: /* TvarVVind={2,5,5}, for V3 at position 2 and then the product V1*V3 is decomposed into V1 and V3 but at same position 5 */
6062: /* TvarVV gives the variable name */
1.340 brouard 6063: /* Other example V1 + V3 + V5 + age*V1 + age*V3 + age*V5 + V1*V3 + V3*V5 + V1*V5
6064: * k= 1 2 3 4 5 6 7 8 9
6065: * varying 1 2 3 4 5
6066: * ncovv 1 2 3 4 5 6 7 8
1.343 brouard 6067: * TvarVV[ncovv] V3 5 1 3 3 5 1 5
1.340 brouard 6068: * TvarVVind 2 3 7 7 8 8 9 9
6069: * TvarFind[k] 1 0 0 0 0 0 0 0 0
6070: */
1.345 brouard 6071: /* Other model ncovcol=5 nqv=0 ntv=3 nqtv=0 nlstate=3
1.349 brouard 6072: * V2 V3 V4 are fixed V6 V7 are timevarying so V8 and V5 are not in the model and product column will start at 9 Tvar[(v6*V2)6]=9
1.345 brouard 6073: * FixedV[ncovcol+qv+ntv+nqtv] V5
1.349 brouard 6074: * 3 V1 V2 V3 V4 V5 V6 V7 V8 V3*V2 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
6075: * 0 0 0 0 0 1 1 1 0, 0, 1,1, 1, 0, 1, 0, 1, 0, 1, 0}
6076: * 3 0 0 0 0 0 1 1 1 0, 1 1 1 1 1}
6077: * model= V2 + V3 + V4 + V6 + V7 + V6*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
6078: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
6079: * +age*V6*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
6080: * model2= V2 + V3 + V4 + V6 + V7 + V3*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
6081: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
6082: * +age*V3*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
6083: * model3= V2 + V3 + V4 + V6 + V7 + age*V3*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
6084: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
6085: * +V3*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
6086: * kmodel 1 2 3 4 5 6 7 8 9 10 11
6087: * 12 13 14 15 16
6088: * 17 18 19 20 21
6089: * Tvar[kmodel] 2 3 4 6 7 9 10 11 12 13 14
6090: * 2 3 4 6 7
6091: * 9 11 12 13 14
6092: * cptcovage=5+5 total of covariates with age
6093: * Tage[cptcovage] age*V2=12 13 14 15 16
6094: *1 17 18 19 20 21 gives the position in model of covariates associated with age
6095: *3 Tage[cptcovage] age*V3*V2=6
6096: *3 age*V2=12 13 14 15 16
6097: *3 age*V6*V3=18 19 20 21
6098: * Tvar[Tage[cptcovage]] Tvar[12]=2 3 4 6 Tvar[16]=7(age*V7)
6099: * Tvar[17]age*V6*V2=9 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14
6100: * 2 Tvar[17]age*V3*V2=9 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14
6101: * 3 Tvar[Tage[cptcovage]] Tvar[6]=9 Tvar[12]=2 3 4 6 Tvar[16]=7(age*V7)
6102: * 3 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14
6103: * 3 Tage[cptcovage] age*V3*V2=6 age*V2=12 age*V3 13 14 15 16
6104: * age*V6*V3=18 19 20 21 gives the position in model of covariates associated with age
6105: * 3 Tvar[17]age*V3*V2=9 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14
6106: * Tvar= {2, 3, 4, 6, 7,
6107: * 9, 10, 11, 12, 13, 14,
6108: * Tvar[12]=2, 3, 4, 6, 7,
6109: * Tvar[17]=9, 11, 12, 13, 14}
6110: * Typevar[1]@21 = {0, 0, 0, 0, 0,
6111: * 2, 2, 2, 2, 2, 2,
6112: * 3 3, 2, 2, 2, 2, 2,
6113: * 1, 1, 1, 1, 1,
6114: * 3, 3, 3, 3, 3}
6115: * 3 2, 3, 3, 3, 3}
6116: * p Tposprod[1]@21 {0, 0, 0, 0, 0, 1, 2, 3, 4, 5, 6, 0, 0, 0, 0, 0, 1, 3, 4, 5, 6} Id of the prod at position k in the model
6117: * p Tprod[1]@21 {6, 7, 8, 9, 10, 11, 0 <repeats 15 times>}
6118: * 3 Tposprod[1]@21 {0, 0, 0, 0, 0, 1, 2, 3, 4, 5, 6, 0, 0, 0, 0, 0, 1, 3, 4, 5, 6}
6119: * 3 Tprod[1]@21 {17, 7, 8, 9, 10, 11, 0 <repeats 15 times>}
6120: * cptcovprod=11 (6+5)
6121: * FixedV[Tvar[Tage[cptcovage]]]] FixedV[2]=0 FixedV[3]=0 0 1 (age*V7)Tvar[16]=1 FixedV[absolute] not [kmodel]
6122: * FixedV[Tvar[17]=FixedV[age*V6*V2]=FixedV[9]=1 1 1 1 1
6123: * 3 FixedV[Tvar[17]=FixedV[age*V3*V2]=FixedV[9]=0 [11]=1 1 1 1
6124: * FixedV[] V1=0 V2=0 V3=0 v4=0 V5=0 V6=1 V7=1 v8=1 OK then model dependent
6125: * 9=1 [V7*V2]=[10]=1 11=1 12=1 13=1 14=1
6126: * 3 9=0 [V7*V2]=[10]=1 11=1 12=1 13=1 14=1
6127: * cptcovdageprod=5 for gnuplot printing
6128: * cptcovprodvage=6
6129: * ncova=15 1 2 3 4 5
6130: * 6 7 8 9 10 11 12 13 14 15
6131: * TvarA 2 3 4 6 7
6132: * 6 2 6 7 7 3 6 4 7 4
6133: * TvaAind 12 12 13 13 14 14 15 15 16 16
1.345 brouard 6134: * ncovf 1 2 3
1.349 brouard 6135: * V6 V7 V6*V2 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
6136: * ncovvt=14 1 2 3 4 5 6 7 8 9 10 11 12 13 14
6137: * TvarVV[1]@14 = itv {V6=6, 7, V6*V2=6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
6138: * TvarVVind[1]@14= {4, 5, 6, 6, 7, 7, 8, 8, 9, 9, 10, 10, 11, 11}
6139: * 3 ncovvt=12 V6 V7 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
6140: * 3 TvarVV[1]@12 = itv {6, 7, V7*V2=7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
6141: * 3 1 2 3 4 5 6 7 8 9 10 11 12
6142: * TvarVVind[1]@12= {V6 is in k=4, 5, 7,(4isV2)=7, 8, 8, 9, 9, 10,10, 11,11}TvarVVind[12]=k=11
6143: * TvarV 6, 7, 9, 10, 11, 12, 13, 14
6144: * 3 cptcovprodvage=6
6145: * 3 ncovta=15 +age*V3*V2+age*V2+agev3+ageV4 +age*V6 + age*V7 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
6146: * 3 TvarAVVA[1]@15= itva 3 2 2 3 4 6 7 6 3 7 3 6 4 7 4
6147: * 3 ncovta 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
1.354 brouard 6148: *?TvarAVVAind[1]@15= V3 is in k=2 1 1 2 3 4 5 4,2 5,2, 4,3 5 3}TvarVVAind[]
1.349 brouard 6149: * TvarAVVAind[1]@15= V3 is in k=6 6 12 13 14 15 16 18 18 19,19, 20,20 21,21}TvarVVAind[]
6150: * 3 ncovvta=10 +age*V6 + age*V7 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
6151: * 3 we want to compute =cotvar[mw[mi][i]][TvarVVA[ncovva]][i] at position TvarVVAind[ncovva]
6152: * 3 TvarVVA[1]@10= itva 6 7 6 3 7 3 6 4 7 4
6153: * 3 ncovva 1 2 3 4 5 6 7 8 9 10
6154: * TvarVVAind[1]@10= V6 is in k=4 5 8,8 9, 9, 10,10 11 11}TvarVVAind[]
6155: * TvarVVAind[1]@10= 15 16 18,18 19,19, 20,20 21 21}TvarVVAind[]
6156: * TvarVA V3*V2=6 6 , 1, 2, 11, 12, 13, 14
1.345 brouard 6157: * TvarFind[1]@14= {1, 2, 3, 0 <repeats 12 times>}
1.349 brouard 6158: * Tvar[1]@21= {2, 3, 4, 6, 7, 9, 10, 11, 12, 13, 14,
6159: * 2, 3, 4, 6, 7,
6160: * 6, 8, 9, 10, 11}
1.345 brouard 6161: * TvarFind[itv] 0 0 0
6162: * FixedV[itv] 1 1 1 0 1 0 1 0 1 0 0
1.354 brouard 6163: *? FixedV[itv] 1 1 1 0 1 0 1 0 1 0 1 0 1 0
1.345 brouard 6164: * Tvar[TvarFind[ncovf]]=[1]=2 [2]=3 [4]=4
6165: * Tvar[TvarFind[itv]] [0]=? ?ncovv 1 à ncovvt]
6166: * Not a fixed cotvar[mw][itv][i] 6 7 6 2 7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
1.349 brouard 6167: * fixed covar[itv] [6] [7] [6][2]
1.345 brouard 6168: */
6169:
1.349 brouard 6170: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* V6 V7 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4 Time varying covariates (single and extended product but no age) including individual from products, product is computed dynamically */
6171: itv=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, or fixed covariate of a varying product after exploding product Vn*Vm into Vn and then Vm */
1.340 brouard 6172: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
1.345 brouard 6173: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
6174: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
1.354 brouard 6175: /* printf("DEBUG ncovv=%d, Varying TvarVV[ncovv]=%d\n",ncovv, TvarVV[ncovv]); */
1.345 brouard 6176: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
1.354 brouard 6177: /* printf("DEBUG Varying cov[ioffset+ipos=%d]=%g \n",ioffset+ipos,cotvarv); */
1.340 brouard 6178: }else{ /* fixed covariate */
1.345 brouard 6179: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
1.354 brouard 6180: /* printf("DEBUG ncovv=%d, Fixed TvarVV[ncovv]=%d\n",ncovv, TvarVV[ncovv]); */
1.349 brouard 6181: cotvarv=covar[itv][i]; /* Good: In V6*V3, 3 is fixed at position of the data */
1.354 brouard 6182: /* printf("DEBUG Fixed cov[ioffset+ipos=%d]=%g \n",ioffset+ipos,cotvarv); */
1.340 brouard 6183: }
1.339 brouard 6184: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 brouard 6185: cotvarvold=cotvarv;
6186: }else{ /* A second product */
6187: cotvarv=cotvarv*cotvarvold;
1.339 brouard 6188: }
6189: iposold=ipos;
1.340 brouard 6190: cov[ioffset+ipos]=cotvarv;
1.354 brouard 6191: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
1.339 brouard 6192: /* For products */
6193: }
6194: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates single *\/ */
6195: /* iv=TvarVDind[itv]; /\* iv, position in the model equation of time varying covariate itv *\/ */
6196: /* /\* "V1+V3+age*V1+age*V3+V1*V3" with V3 time varying *\/ */
6197: /* /\* 1 2 3 4 5 *\/ */
6198: /* /\*itv 1 *\/ */
6199: /* /\* TvarVInd[1]= 2 *\/ */
6200: /* /\* iv= Tvar[Tmodelind[itv]]-ncovcol-nqv; /\\* Counting the # varying covariate from 1 to ntveff *\\/ *\/ */
6201: /* /\* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; *\/ */
6202: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; *\/ */
6203: /* /\* k=ioffset-2-nagesqr-cptcovage+itv; /\\* position in simple model *\\/ *\/ */
6204: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; *\/ */
6205: /* cov[ioffset+iv]=cotvar[mw[mi][i]][itv][i]; */
6206: /* /\* printf(" i=%d,mi=%d,itv=%d,TmodelInvind[itv]=%d,cotvar[mw[mi][i]][itv][i]=%f\n", i, mi, itv, TvarVDind[itv],cotvar[mw[mi][i]][itv][i]); *\/ */
6207: /* } */
1.232 brouard 6208: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 6209: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
6210: /* /\* printf(" i=%d,mi=%d,iqtv=%d,TmodelInvQind[iqtv]=%d,cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]=%f\n", i, mi, iqtv, TmodelInvQind[iqtv],cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]); *\/ */
6211: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 6212: /* } */
1.126 brouard 6213: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 6214: for (j=1;j<=nlstate+ndeath;j++){
6215: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
6216: savm[ii][j]=(ii==j ? 1.0 : 0.0);
6217: }
1.214 brouard 6218:
6219: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
6220: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
6221: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 6222: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 6223: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
6224: and mw[mi+1][i]. dh depends on stepm.*/
6225: newm=savm;
1.247 brouard 6226: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 6227: cov[2]=agexact;
6228: if(nagesqr==1)
6229: cov[3]= agexact*agexact;
1.349 brouard 6230: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
6231: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
6232: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
6233: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
6234: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
6235: /* printf("DEBUG ncovva=%d, Varying TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
6236: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
6237: }else{ /* fixed covariate */
6238: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
6239: /* printf("DEBUG ncovva=%d, Fixed TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
6240: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
6241: }
6242: if(ipos!=iposold){ /* Not a product or first of a product */
6243: cotvarvold=cotvarv;
6244: }else{ /* A second product */
6245: /* printf("DEBUG * \n"); */
6246: cotvarv=cotvarv*cotvarvold;
6247: }
6248: iposold=ipos;
6249: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
6250: cov[ioffset+ipos]=cotvarv*agexact;
6251: /* For products */
1.242 brouard 6252: }
1.349 brouard 6253:
1.242 brouard 6254: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
6255: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
6256: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
6257: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
6258: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
6259: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
6260: savm=oldm;
6261: oldm=newm;
1.126 brouard 6262: } /* end mult */
1.336 brouard 6263: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
6264: /* But now since version 0.9 we anticipate for bias at large stepm.
6265: * If stepm is larger than one month (smallest stepm) and if the exact delay
6266: * (in months) between two waves is not a multiple of stepm, we rounded to
6267: * the nearest (and in case of equal distance, to the lowest) interval but now
6268: * we keep into memory the bias bh[mi][i] and also the previous matrix product
6269: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
6270: * probability in order to take into account the bias as a fraction of the way
6271: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
6272: * -stepm/2 to stepm/2 .
6273: * For stepm=1 the results are the same as for previous versions of Imach.
6274: * For stepm > 1 the results are less biased than in previous versions.
6275: */
1.126 brouard 6276: s1=s[mw[mi][i]][i];
6277: s2=s[mw[mi+1][i]][i];
1.217 brouard 6278: /* if(s2==-1){ */
1.268 brouard 6279: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 6280: /* /\* exit(1); *\/ */
6281: /* } */
1.126 brouard 6282: bbh=(double)bh[mi][i]/(double)stepm;
6283: /* bias is positive if real duration
6284: * is higher than the multiple of stepm and negative otherwise.
6285: */
6286: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 6287: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 6288: } else if ( s2==-1 ) { /* alive */
1.242 brouard 6289: for (j=1,survp=0. ; j<=nlstate; j++)
6290: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
6291: lli= log(survp);
1.126 brouard 6292: }else if (mle==1){
1.242 brouard 6293: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 6294: } else if(mle==2){
1.242 brouard 6295: lli= (savm[s1][s2]>(double)1.e-8 ?log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]):log((1.+bbh)*out[s1][s2])); /* linear interpolation */
1.126 brouard 6296: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 6297: lli= (savm[s1][s2]>(double)1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2])); /* exponential inter-extrapolation */
1.126 brouard 6298: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 6299: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 6300: } else{ /* mle=0 back to 1 */
1.242 brouard 6301: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
6302: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 6303: } /* End of if */
6304: ipmx +=1;
6305: sw += weight[i];
6306: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.342 brouard 6307: /* Printing covariates values for each contribution for checking */
1.343 brouard 6308: /* printf("num[i]=%09ld, i=%6d s1=%1d s2=%1d mi=%1d mw=%1d dh=%3d prob=%10.6f w=%6.4f out=%10.6f sav=%10.6f\n",num[i],i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2])); */
1.126 brouard 6309: if(globpr){
1.246 brouard 6310: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 6311: %11.6f %11.6f %11.6f ", \
1.242 brouard 6312: num[i], agebegin, ageend, i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],weight[i]*gipmx/gsw,
1.268 brouard 6313: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.343 brouard 6314: /* printf("%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\ */
6315: /* %11.6f %11.6f %11.6f ", \ */
6316: /* num[i], agebegin, ageend, i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],weight[i]*gipmx/gsw, */
6317: /* 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2])); */
1.242 brouard 6318: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
6319: llt +=ll[k]*gipmx/gsw;
6320: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
1.335 brouard 6321: /* printf(" %10.6f",-ll[k]*gipmx/gsw); */
1.242 brouard 6322: }
1.343 brouard 6323: fprintf(ficresilk," %10.6f ", -llt);
1.335 brouard 6324: /* printf(" %10.6f\n", -llt); */
1.342 brouard 6325: /* if(debugILK){ /\* debugILK is set by a #d in a comment line *\/ */
1.343 brouard 6326: /* fprintf(ficresilk,"%09ld ", num[i]); */ /* not necessary */
6327: for (kf=1; kf<=ncovf;kf++){ /* Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */
6328: fprintf(ficresilk," %g",covar[Tvar[TvarFind[kf]]][i]);
6329: }
6330: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age) including individual from products */
6331: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
6332: if(ipos!=iposold){ /* Not a product or first of a product */
6333: fprintf(ficresilk," %g",cov[ioffset+ipos]);
6334: /* printf(" %g",cov[ioffset+ipos]); */
6335: }else{
6336: fprintf(ficresilk,"*");
6337: /* printf("*"); */
1.342 brouard 6338: }
1.343 brouard 6339: iposold=ipos;
6340: }
1.349 brouard 6341: /* for (kk=1; kk<=cptcovage;kk++) { */
6342: /* if(!FixedV[Tvar[Tage[kk]]]){ */
6343: /* fprintf(ficresilk," %g*age",covar[Tvar[Tage[kk]]][i]); */
6344: /* /\* printf(" %g*age",covar[Tvar[Tage[kk]]][i]); *\/ */
6345: /* }else{ */
6346: /* fprintf(ficresilk," %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */
6347: /* /\* printf(" %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/\\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\\/ *\/ */
6348: /* } */
6349: /* } */
6350: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
6351: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
6352: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
6353: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
6354: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
6355: /* printf("DEBUG ncovva=%d, Varying TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
6356: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
6357: }else{ /* fixed covariate */
6358: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
6359: /* printf("DEBUG ncovva=%d, Fixed TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
6360: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
6361: }
6362: if(ipos!=iposold){ /* Not a product or first of a product */
6363: cotvarvold=cotvarv;
6364: }else{ /* A second product */
6365: /* printf("DEBUG * \n"); */
6366: cotvarv=cotvarv*cotvarvold;
1.342 brouard 6367: }
1.349 brouard 6368: cotvarv=cotvarv*agexact;
6369: fprintf(ficresilk," %g*age",cotvarv);
6370: iposold=ipos;
6371: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
6372: cov[ioffset+ipos]=cotvarv;
6373: /* For products */
1.343 brouard 6374: }
6375: /* printf("\n"); */
1.342 brouard 6376: /* } /\* End debugILK *\/ */
6377: fprintf(ficresilk,"\n");
6378: } /* End if globpr */
1.335 brouard 6379: } /* end of wave */
6380: } /* end of individual */
6381: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
1.232 brouard 6382: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
1.335 brouard 6383: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
6384: if(globpr==0){ /* First time we count the contributions and weights */
6385: gipmx=ipmx;
6386: gsw=sw;
6387: }
1.343 brouard 6388: return -l;
1.126 brouard 6389: }
6390:
6391:
6392: /*************** function likelione ***********/
1.292 brouard 6393: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 6394: {
6395: /* This routine should help understanding what is done with
6396: the selection of individuals/waves and
6397: to check the exact contribution to the likelihood.
6398: Plotting could be done.
1.342 brouard 6399: */
6400: void pstamp(FILE *ficres);
1.343 brouard 6401: int k, kf, kk, kvar, ncovv, iposold, ipos;
1.126 brouard 6402:
6403: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 6404: strcpy(fileresilk,"ILK_");
1.202 brouard 6405: strcat(fileresilk,fileresu);
1.126 brouard 6406: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
6407: printf("Problem with resultfile: %s\n", fileresilk);
6408: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
6409: }
1.342 brouard 6410: pstamp(ficresilk);fprintf(ficresilk,"# model=1+age+%s\n",model);
1.214 brouard 6411: fprintf(ficresilk, "#individual(line's_record) count ageb ageend s1 s2 wave# effective_wave# number_of_matrices_product pij weight weight/gpw -2ln(pij)*weight 0pij_x 0pij_(x-stepm) cumulating_loglikeli_by_health_state(reweighted=-2ll*weightXnumber_of_contribs/sum_of_weights) and_total\n");
6412: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 6413: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
6414: for(k=1; k<=nlstate; k++)
6415: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
1.342 brouard 6416: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total) ");
6417:
6418: /* if(debugILK){ /\* debugILK is set by a #d in a comment line *\/ */
6419: for(kf=1;kf <= ncovf; kf++){
6420: fprintf(ficresilk,"V%d",Tvar[TvarFind[kf]]);
6421: /* printf("V%d",Tvar[TvarFind[kf]]); */
6422: }
6423: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){
1.343 brouard 6424: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
1.342 brouard 6425: if(ipos!=iposold){ /* Not a product or first of a product */
6426: /* printf(" %d",ipos); */
6427: fprintf(ficresilk," V%d",TvarVV[ncovv]);
6428: }else{
6429: /* printf("*"); */
6430: fprintf(ficresilk,"*");
1.343 brouard 6431: }
1.342 brouard 6432: iposold=ipos;
6433: }
6434: for (kk=1; kk<=cptcovage;kk++) {
6435: if(!FixedV[Tvar[Tage[kk]]]){
6436: /* printf(" %d*age(Fixed)",Tvar[Tage[kk]]); */
6437: fprintf(ficresilk," %d*age(Fixed)",Tvar[Tage[kk]]);
6438: }else{
6439: fprintf(ficresilk," %d*age(Varying)",Tvar[Tage[kk]]);/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
6440: /* printf(" %d*age(Varying)",Tvar[Tage[kk]]);/\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */
6441: }
6442: }
6443: /* } /\* End if debugILK *\/ */
6444: /* printf("\n"); */
6445: fprintf(ficresilk,"\n");
6446: } /* End glogpri */
1.126 brouard 6447:
1.292 brouard 6448: *fretone=(*func)(p);
1.126 brouard 6449: if(*globpri !=0){
6450: fclose(ficresilk);
1.205 brouard 6451: if (mle ==0)
6452: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
6453: else if(mle >=1)
6454: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
6455: fprintf(fichtm," You should at least run with mle >= 1 to get starting values corresponding to the optimized parameters in order to visualize the real contribution of each individual/wave: <a href=\"%s\">%s</a><br>\n",subdirf(fileresilk),subdirf(fileresilk));
1.274 brouard 6456: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 6457:
1.207 brouard 6458: fprintf(fichtm,"<br>- The function drawn is -2Log(L) in Log scale: by state of origin <a href=\"%s-ori.png\">%s-ori.png</a><br> \
1.343 brouard 6459: <img src=\"%s-ori.png\">\n",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 6460: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.343 brouard 6461: <img src=\"%s-dest.png\">\n",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
6462:
6463: for (k=1; k<= nlstate ; k++) {
6464: fprintf(fichtm,"<br>- Probability p<sub>%dj</sub> by origin %d and destination j. Dot's sizes are related to corresponding weight: <a href=\"%s-p%dj.png\">%s-p%dj.png</a><br>\n \
6465: <img src=\"%s-p%dj.png\">\n",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
6466: for(kf=1; kf <= ncovf; kf++){ /* For each simple dummy covariate of the model */
1.350 brouard 6467: kvar=Tvar[TvarFind[kf]]; /* variable */
6468: fprintf(fichtm,"<br>- Probability p<sub>%dj</sub> by origin %d and destination j with colored covariate V%d. Same dot size of all points but with a different color for transitions with dummy variable V%d=1 at beginning of transition (keeping former color for V%d=0): ",k,k,Tvar[TvarFind[kf]],Tvar[TvarFind[kf]],Tvar[TvarFind[kf]]);
6469: fprintf(fichtm,"<a href=\"%s-p%dj-%d.png\">%s-p%dj-%d.png</a><br>",subdirf2(optionfilefiname,"ILK_"),k,kvar,subdirf2(optionfilefiname,"ILK_"),k,kvar);
6470: fprintf(fichtm,"<img src=\"%s-p%dj-%d.png\">",subdirf2(optionfilefiname,"ILK_"),k,Tvar[TvarFind[kf]]);
1.343 brouard 6471: }
6472: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Loop on the time varying extended covariates (with extension of Vn*Vm */
6473: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
6474: kvar=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
6475: /* printf("DebugILK fichtm ncovv=%d, kvar=TvarVV[ncovv]=V%d, ipos=TvarVVind[ncovv]=%d, Dummy[ipos]=%d, Typevar[ipos]=%d\n", ncovv,kvar,ipos,Dummy[ipos],Typevar[ipos]); */
6476: if(ipos!=iposold){ /* Not a product or first of a product */
6477: /* fprintf(ficresilk," V%d",TvarVV[ncovv]); */
6478: /* printf(" DebugILK fichtm ipos=%d != iposold=%d\n", ipos, iposold); */
6479: if(Dummy[ipos]==0 && Typevar[ipos]==0){ /* Only if dummy time varying: Dummy(0, 1=quant singor prod without age,2 dummy*age, 3quant*age) Typevar (0 single, 1=*age,2=Vn*vm) */
6480: fprintf(fichtm,"<br>- Probability p<sub>%dj</sub> by origin %d and destination j with colored time varying dummy covariate V%d. Same dot size of all points but with a different color for transitions with dummy variable V%d=1 at beginning of transition (keeping former color for V%d=0): <a href=\"%s-p%dj.png\">%s-p%dj.png</a><br> \
6481: <img src=\"%s-p%dj-%d.png\">",k,k,kvar,kvar,kvar,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,kvar);
6482: } /* End only for dummies time varying (single?) */
6483: }else{ /* Useless product */
6484: /* printf("*"); */
6485: /* fprintf(ficresilk,"*"); */
6486: }
6487: iposold=ipos;
6488: } /* For each time varying covariate */
6489: } /* End loop on states */
6490:
6491: /* if(debugILK){ */
6492: /* for(kf=1; kf <= ncovf; kf++){ /\* For each simple dummy covariate of the model *\/ */
6493: /* /\* kvar=Tvar[TvarFind[kf]]; *\/ /\* variable *\/ */
6494: /* for (k=1; k<= nlstate ; k++) { */
6495: /* fprintf(fichtm,"<br>- Probability p<sub>%dj</sub> by origin %d and destination j with colored covariate V%. Same dot size of all points but with a different color for transitions with dummy variable V%d=1 at beginning of transition (keeping former color for V%d=0): <a href=\"%s-p%dj.png\">%s-p%dj.png</a><br> \ */
6496: /* <img src=\"%s-p%dj-%d.png\">",k,k,Tvar[TvarFind[kf]],Tvar[TvarFind[kf]],Tvar[TvarFind[kf]],subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,Tvar[TvarFind[kf]]); */
6497: /* } */
6498: /* } */
6499: /* for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /\* Loop on the time varying extended covariates (with extension of Vn*Vm *\/ */
6500: /* ipos=TvarVVind[ncovv]; /\* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate *\/ */
6501: /* kvar=TvarVV[ncovv]; /\* TvarVV={3, 1, 3} gives the name of each varying covariate *\/ */
6502: /* /\* printf("DebugILK fichtm ncovv=%d, kvar=TvarVV[ncovv]=V%d, ipos=TvarVVind[ncovv]=%d, Dummy[ipos]=%d, Typevar[ipos]=%d\n", ncovv,kvar,ipos,Dummy[ipos],Typevar[ipos]); *\/ */
6503: /* if(ipos!=iposold){ /\* Not a product or first of a product *\/ */
6504: /* /\* fprintf(ficresilk," V%d",TvarVV[ncovv]); *\/ */
6505: /* /\* printf(" DebugILK fichtm ipos=%d != iposold=%d\n", ipos, iposold); *\/ */
6506: /* if(Dummy[ipos]==0 && Typevar[ipos]==0){ /\* Only if dummy time varying: Dummy(0, 1=quant singor prod without age,2 dummy*age, 3quant*age) Typevar (0 single, 1=*age,2=Vn*vm) *\/ */
6507: /* for (k=1; k<= nlstate ; k++) { */
6508: /* fprintf(fichtm,"<br>- Probability p<sub>%dj</sub> by origin %d and destination j. Same dot size of all points but with a different color for transitions with dummy variable V%d=1 at beginning of transition (keeping former color for V%d=0): <a href=\"%s-p%dj.png\">%s-p%dj.png</a><br> \ */
6509: /* <img src=\"%s-p%dj-%d.png\">",k,k,kvar,kvar,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,kvar); */
6510: /* } /\* End state *\/ */
6511: /* } /\* End only for dummies time varying (single?) *\/ */
6512: /* }else{ /\* Useless product *\/ */
6513: /* /\* printf("*"); *\/ */
6514: /* /\* fprintf(ficresilk,"*"); *\/ */
6515: /* } */
6516: /* iposold=ipos; */
6517: /* } /\* For each time varying covariate *\/ */
6518: /* }/\* End debugILK *\/ */
1.207 brouard 6519: fflush(fichtm);
1.343 brouard 6520: }/* End globpri */
1.126 brouard 6521: return;
6522: }
6523:
6524:
6525: /*********** Maximum Likelihood Estimation ***************/
6526:
6527: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
6528: {
1.359 brouard 6529: int i,j, jkk=0, iter=0;
1.126 brouard 6530: double **xi;
1.359 brouard 6531: /*double fret;*/
6532: /*double fretone;*/ /* Only one call to likelihood */
1.126 brouard 6533: /* char filerespow[FILENAMELENGTH];*/
1.354 brouard 6534:
1.359 brouard 6535: /*double * p1;*/ /* Shifted parameters from 0 instead of 1 */
1.162 brouard 6536: #ifdef NLOPT
6537: int creturn;
6538: nlopt_opt opt;
6539: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
6540: double *lb;
6541: double minf; /* the minimum objective value, upon return */
1.354 brouard 6542:
1.162 brouard 6543: myfunc_data dinst, *d = &dinst;
6544: #endif
6545:
6546:
1.126 brouard 6547: xi=matrix(1,npar,1,npar);
1.357 brouard 6548: for (i=1;i<=npar;i++) /* Starting with canonical directions j=1,n xi[i=1,n][j] */
1.126 brouard 6549: for (j=1;j<=npar;j++)
6550: xi[i][j]=(i==j ? 1.0 : 0.0);
1.359 brouard 6551: printf("Powell-prax\n"); fprintf(ficlog,"Powell-prax\n");
1.201 brouard 6552: strcpy(filerespow,"POW_");
1.126 brouard 6553: strcat(filerespow,fileres);
6554: if((ficrespow=fopen(filerespow,"w"))==NULL) {
6555: printf("Problem with resultfile: %s\n", filerespow);
6556: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
6557: }
6558: fprintf(ficrespow,"# Powell\n# iter -2*LL");
6559: for (i=1;i<=nlstate;i++)
6560: for(j=1;j<=nlstate+ndeath;j++)
6561: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
6562: fprintf(ficrespow,"\n");
1.162 brouard 6563: #ifdef POWELL
1.319 brouard 6564: #ifdef LINMINORIGINAL
6565: #else /* LINMINORIGINAL */
6566:
6567: flatdir=ivector(1,npar);
6568: for (j=1;j<=npar;j++) flatdir[j]=0;
6569: #endif /*LINMINORIGINAL */
6570:
6571: #ifdef FLATSUP
6572: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
6573: /* reorganizing p by suppressing flat directions */
6574: for(i=1, jk=1; i <=nlstate; i++){
6575: for(k=1; k <=(nlstate+ndeath); k++){
6576: if (k != i) {
6577: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
6578: if(flatdir[jk]==1){
6579: printf(" To be skipped %d%d flatdir[%d]=%d ",i,k,jk, flatdir[jk]);
6580: }
6581: for(j=1; j <=ncovmodel; j++){
6582: printf("%12.7f ",p[jk]);
6583: jk++;
6584: }
6585: printf("\n");
6586: }
6587: }
6588: }
6589: /* skipping */
6590: /* for(i=1, jk=1, jkk=1;(flatdir[jk]==0)&& (i <=nlstate); i++){ */
6591: for(i=1, jk=1, jkk=1;i <=nlstate; i++){
6592: for(k=1; k <=(nlstate+ndeath); k++){
6593: if (k != i) {
6594: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
6595: if(flatdir[jk]==1){
6596: printf(" To be skipped %d%d flatdir[%d]=%d jk=%d p[%d] ",i,k,jk, flatdir[jk],jk, jk);
6597: for(j=1; j <=ncovmodel; jk++,j++){
6598: printf(" p[%d]=%12.7f",jk, p[jk]);
6599: /*q[jjk]=p[jk];*/
6600: }
6601: }else{
6602: printf(" To be kept %d%d flatdir[%d]=%d jk=%d q[%d]=p[%d] ",i,k,jk, flatdir[jk],jk, jkk, jk);
6603: for(j=1; j <=ncovmodel; jk++,jkk++,j++){
6604: printf(" p[%d]=%12.7f=q[%d]",jk, p[jk],jkk);
6605: /*q[jjk]=p[jk];*/
6606: }
6607: }
6608: printf("\n");
6609: }
6610: fflush(stdout);
6611: }
6612: }
6613: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
6614: #else /* FLATSUP */
1.359 brouard 6615: /* powell(p,xi,npar,ftol,&iter,&fret,func);*/
6616: /* praxis ( t0, h0, n, prin, x, beale_f ); */
1.364 ! brouard 6617: int prin=4;
1.362 brouard 6618: /* double h0=0.25; */
6619: /* double macheps; */
6620: /* double fmin; */
1.359 brouard 6621: macheps=pow(16.0,-13.0);
6622: /* #include "praxis.h" */
6623: /* Be careful that praxis start at x[0] and powell start at p[1] */
6624: /* praxis ( ftol, h0, npar, prin, p, func ); */
6625: /* p1= (p+1); */ /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
6626: printf("Praxis Gegenfurtner \n");
6627: fprintf(ficlog, "Praxis Gegenfurtner\n");fflush(ficlog);
6628: /* praxis ( ftol, h0, npar, prin, p1, func ); */
6629: /* fmin = praxis(1.e-5,macheps, h, n, prin, x, func); */
1.362 brouard 6630: ffmin = praxis(ftol,macheps, h0, npar, prin, p, func);
1.359 brouard 6631: printf("End Praxis\n");
1.319 brouard 6632: #endif /* FLATSUP */
6633:
6634: #ifdef LINMINORIGINAL
6635: #else
6636: free_ivector(flatdir,1,npar);
6637: #endif /* LINMINORIGINAL*/
6638: #endif /* POWELL */
1.126 brouard 6639:
1.162 brouard 6640: #ifdef NLOPT
6641: #ifdef NEWUOA
6642: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
6643: #else
6644: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
6645: #endif
6646: lb=vector(0,npar-1);
6647: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
6648: nlopt_set_lower_bounds(opt, lb);
6649: nlopt_set_initial_step1(opt, 0.1);
6650:
6651: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
6652: d->function = func;
6653: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
6654: nlopt_set_min_objective(opt, myfunc, d);
6655: nlopt_set_xtol_rel(opt, ftol);
6656: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
6657: printf("nlopt failed! %d\n",creturn);
6658: }
6659: else {
6660: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
6661: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
6662: iter=1; /* not equal */
6663: }
6664: nlopt_destroy(opt);
6665: #endif
1.319 brouard 6666: #ifdef FLATSUP
6667: /* npared = npar -flatd/ncovmodel; */
6668: /* xired= matrix(1,npared,1,npared); */
6669: /* paramred= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); */
6670: /* powell(pred,xired,npared,ftol,&iter,&fret,flatdir,func); */
6671: /* free_matrix(xire,1,npared,1,npared); */
6672: #else /* FLATSUP */
6673: #endif /* FLATSUP */
1.126 brouard 6674: free_matrix(xi,1,npar,1,npar);
6675: fclose(ficrespow);
1.203 brouard 6676: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
6677: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 6678: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 6679:
6680: }
6681:
6682: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 6683: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 6684: {
6685: double **a,**y,*x,pd;
1.203 brouard 6686: /* double **hess; */
1.164 brouard 6687: int i, j;
1.126 brouard 6688: int *indx;
6689:
6690: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 6691: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 6692: void lubksb(double **a, int npar, int *indx, double b[]) ;
6693: void ludcmp(double **a, int npar, int *indx, double *d) ;
6694: double gompertz(double p[]);
1.203 brouard 6695: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 6696:
6697: printf("\nCalculation of the hessian matrix. Wait...\n");
6698: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
6699: for (i=1;i<=npar;i++){
1.203 brouard 6700: printf("%d-",i);fflush(stdout);
6701: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 6702:
6703: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
6704:
6705: /* printf(" %f ",p[i]);
6706: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
6707: }
6708:
6709: for (i=1;i<=npar;i++) {
6710: for (j=1;j<=npar;j++) {
6711: if (j>i) {
1.203 brouard 6712: printf(".%d-%d",i,j);fflush(stdout);
6713: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
6714: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 6715:
6716: hess[j][i]=hess[i][j];
6717: /*printf(" %lf ",hess[i][j]);*/
6718: }
6719: }
6720: }
6721: printf("\n");
6722: fprintf(ficlog,"\n");
6723:
6724: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
6725: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
6726:
6727: a=matrix(1,npar,1,npar);
6728: y=matrix(1,npar,1,npar);
6729: x=vector(1,npar);
6730: indx=ivector(1,npar);
6731: for (i=1;i<=npar;i++)
6732: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
6733: ludcmp(a,npar,indx,&pd);
6734:
6735: for (j=1;j<=npar;j++) {
6736: for (i=1;i<=npar;i++) x[i]=0;
6737: x[j]=1;
6738: lubksb(a,npar,indx,x);
6739: for (i=1;i<=npar;i++){
6740: matcov[i][j]=x[i];
6741: }
6742: }
6743:
6744: printf("\n#Hessian matrix#\n");
6745: fprintf(ficlog,"\n#Hessian matrix#\n");
6746: for (i=1;i<=npar;i++) {
6747: for (j=1;j<=npar;j++) {
1.203 brouard 6748: printf("%.6e ",hess[i][j]);
6749: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 6750: }
6751: printf("\n");
6752: fprintf(ficlog,"\n");
6753: }
6754:
1.203 brouard 6755: /* printf("\n#Covariance matrix#\n"); */
6756: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
6757: /* for (i=1;i<=npar;i++) { */
6758: /* for (j=1;j<=npar;j++) { */
6759: /* printf("%.6e ",matcov[i][j]); */
6760: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
6761: /* } */
6762: /* printf("\n"); */
6763: /* fprintf(ficlog,"\n"); */
6764: /* } */
6765:
1.126 brouard 6766: /* Recompute Inverse */
1.203 brouard 6767: /* for (i=1;i<=npar;i++) */
6768: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
6769: /* ludcmp(a,npar,indx,&pd); */
6770:
6771: /* printf("\n#Hessian matrix recomputed#\n"); */
6772:
6773: /* for (j=1;j<=npar;j++) { */
6774: /* for (i=1;i<=npar;i++) x[i]=0; */
6775: /* x[j]=1; */
6776: /* lubksb(a,npar,indx,x); */
6777: /* for (i=1;i<=npar;i++){ */
6778: /* y[i][j]=x[i]; */
6779: /* printf("%.3e ",y[i][j]); */
6780: /* fprintf(ficlog,"%.3e ",y[i][j]); */
6781: /* } */
6782: /* printf("\n"); */
6783: /* fprintf(ficlog,"\n"); */
6784: /* } */
6785:
6786: /* Verifying the inverse matrix */
6787: #ifdef DEBUGHESS
6788: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 6789:
1.203 brouard 6790: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
6791: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 6792:
6793: for (j=1;j<=npar;j++) {
6794: for (i=1;i<=npar;i++){
1.203 brouard 6795: printf("%.2f ",y[i][j]);
6796: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 6797: }
6798: printf("\n");
6799: fprintf(ficlog,"\n");
6800: }
1.203 brouard 6801: #endif
1.126 brouard 6802:
6803: free_matrix(a,1,npar,1,npar);
6804: free_matrix(y,1,npar,1,npar);
6805: free_vector(x,1,npar);
6806: free_ivector(indx,1,npar);
1.203 brouard 6807: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 6808:
6809:
6810: }
6811:
6812: /*************** hessian matrix ****************/
6813: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 6814: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 6815: int i;
6816: int l=1, lmax=20;
1.203 brouard 6817: double k1,k2, res, fx;
1.132 brouard 6818: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 6819: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
6820: int k=0,kmax=10;
6821: double l1;
6822:
6823: fx=func(x);
6824: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 6825: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 6826: l1=pow(10,l);
6827: delts=delt;
6828: for(k=1 ; k <kmax; k=k+1){
6829: delt = delta*(l1*k);
6830: p2[theta]=x[theta] +delt;
1.145 brouard 6831: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 6832: p2[theta]=x[theta]-delt;
6833: k2=func(p2)-fx;
6834: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 6835: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 6836:
1.203 brouard 6837: #ifdef DEBUGHESSII
1.126 brouard 6838: printf("%d %d k1=%.12e k2=%.12e xk1=%.12e xk2=%.12e delt=%.12e res=%.12e l=%d k=%d,fx=%.12e\n",theta,theta,k1,k2,x[theta]+delt,x[theta]-delt,delt,res, l, k,fx);
6839: fprintf(ficlog,"%d %d k1=%.12e k2=%.12e xk1=%.12e xk2=%.12e delt=%.12e res=%.12e l=%d k=%d,fx=%.12e\n",theta,theta,k1,k2,x[theta]+delt,x[theta]-delt,delt,res, l, k,fx);
6840: #endif
6841: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
6842: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
6843: k=kmax;
6844: }
6845: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 6846: k=kmax; l=lmax*10;
1.126 brouard 6847: }
6848: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
6849: delts=delt;
6850: }
1.203 brouard 6851: } /* End loop k */
1.126 brouard 6852: }
6853: delti[theta]=delts;
6854: return res;
6855:
6856: }
6857:
1.203 brouard 6858: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 6859: {
6860: int i;
1.164 brouard 6861: int l=1, lmax=20;
1.126 brouard 6862: double k1,k2,k3,k4,res,fx;
1.132 brouard 6863: double p2[MAXPARM+1];
1.203 brouard 6864: int k, kmax=1;
6865: double v1, v2, cv12, lc1, lc2;
1.208 brouard 6866:
6867: int firstime=0;
1.203 brouard 6868:
1.126 brouard 6869: fx=func(x);
1.203 brouard 6870: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 6871: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 6872: p2[thetai]=x[thetai]+delti[thetai]*k;
6873: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 6874: k1=func(p2)-fx;
6875:
1.203 brouard 6876: p2[thetai]=x[thetai]+delti[thetai]*k;
6877: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 6878: k2=func(p2)-fx;
6879:
1.203 brouard 6880: p2[thetai]=x[thetai]-delti[thetai]*k;
6881: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 6882: k3=func(p2)-fx;
6883:
1.203 brouard 6884: p2[thetai]=x[thetai]-delti[thetai]*k;
6885: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 6886: k4=func(p2)-fx;
1.203 brouard 6887: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
6888: if(k1*k2*k3*k4 <0.){
1.208 brouard 6889: firstime=1;
1.203 brouard 6890: kmax=kmax+10;
1.208 brouard 6891: }
6892: if(kmax >=10 || firstime ==1){
1.354 brouard 6893: /* What are the thetai and thetaj? thetai/ncovmodel thetai=(thetai-thetai%ncovmodel)/ncovmodel +thetai%ncovmodel=(line,pos) */
1.246 brouard 6894: printf("Warning: directions %d-%d, you are not estimating the Hessian at the exact maximum likelihood; you could increase ftol=%.2e\n",thetai,thetaj, ftol);
6895: fprintf(ficlog,"Warning: directions %d-%d, you are not estimating the Hessian at the exact maximum likelihood; you could increase ftol=%.2e\n",thetai,thetaj, ftol);
1.203 brouard 6896: printf("%d %d k=%d, k1=%.12e k2=%.12e k3=%.12e k4=%.12e delti*k=%.12e deltj*k=%.12e, xi-de*k=%.12e xj-de*k=%.12e res=%.12e k1234=%.12e,k1-2=%.12e,k3-4=%.12e\n",thetai,thetaj,k,k1,k2,k3,k4,delti[thetai]/k,delti[thetaj]/k,x[thetai]-delti[thetai]/k,x[thetaj]-delti[thetaj]/k, res,k1-k2-k3+k4,k1-k2,k3-k4);
6897: fprintf(ficlog,"%d %d k=%d, k1=%.12e k2=%.12e k3=%.12e k4=%.12e delti*k=%.12e deltj*k=%.12e, xi-de*k=%.12e xj-de*k=%.12e res=%.12e k1234=%.12e,k1-2=%.12e,k3-4=%.12e\n",thetai,thetaj,k,k1,k2,k3,k4,delti[thetai]/k,delti[thetaj]/k,x[thetai]-delti[thetai]/k,x[thetaj]-delti[thetaj]/k, res,k1-k2-k3+k4,k1-k2,k3-k4);
6898: }
6899: #ifdef DEBUGHESSIJ
6900: v1=hess[thetai][thetai];
6901: v2=hess[thetaj][thetaj];
6902: cv12=res;
6903: /* Computing eigen value of Hessian matrix */
6904: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6905: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6906: if ((lc2 <0) || (lc1 <0) ){
6907: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
6908: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
6909: printf("%d %d k=%d, k1=%.12e k2=%.12e k3=%.12e k4=%.12e delti/k=%.12e deltj/k=%.12e, xi-de/k=%.12e xj-de/k=%.12e res=%.12e k1234=%.12e,k1-2=%.12e,k3-4=%.12e\n",thetai,thetaj,k,k1,k2,k3,k4,delti[thetai]/k,delti[thetaj]/k,x[thetai]-delti[thetai]/k,x[thetaj]-delti[thetaj]/k, res,k1-k2-k3+k4,k1-k2,k3-k4);
6910: fprintf(ficlog,"%d %d k=%d, k1=%.12e k2=%.12e k3=%.12e k4=%.12e delti/k=%.12e deltj/k=%.12e, xi-de/k=%.12e xj-de/k=%.12e res=%.12e k1234=%.12e,k1-2=%.12e,k3-4=%.12e\n",thetai,thetaj,k,k1,k2,k3,k4,delti[thetai]/k,delti[thetaj]/k,x[thetai]-delti[thetai]/k,x[thetaj]-delti[thetaj]/k, res,k1-k2-k3+k4,k1-k2,k3-k4);
6911: }
1.126 brouard 6912: #endif
6913: }
6914: return res;
6915: }
6916:
1.203 brouard 6917: /* Not done yet: Was supposed to fix if not exactly at the maximum */
6918: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
6919: /* { */
6920: /* int i; */
6921: /* int l=1, lmax=20; */
6922: /* double k1,k2,k3,k4,res,fx; */
6923: /* double p2[MAXPARM+1]; */
6924: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
6925: /* int k=0,kmax=10; */
6926: /* double l1; */
6927:
6928: /* fx=func(x); */
6929: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
6930: /* l1=pow(10,l); */
6931: /* delts=delt; */
6932: /* for(k=1 ; k <kmax; k=k+1){ */
6933: /* delt = delti*(l1*k); */
6934: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
6935: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
6936: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
6937: /* k1=func(p2)-fx; */
6938:
6939: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
6940: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
6941: /* k2=func(p2)-fx; */
6942:
6943: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
6944: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
6945: /* k3=func(p2)-fx; */
6946:
6947: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
6948: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
6949: /* k4=func(p2)-fx; */
6950: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
6951: /* #ifdef DEBUGHESSIJ */
6952: /* printf("%d %d k=%d, k1=%.12e k2=%.12e k3=%.12e k4=%.12e delti/k=%.12e deltj/k=%.12e, xi-de/k=%.12e xj-de/k=%.12e res=%.12e k1234=%.12e,k1-2=%.12e,k3-4=%.12e\n",thetai,thetaj,k,k1,k2,k3,k4,delti[thetai]/k,delti[thetaj]/k,x[thetai]-delti[thetai]/k,x[thetaj]-delti[thetaj]/k, res,k1-k2-k3+k4,k1-k2,k3-k4); */
6953: /* fprintf(ficlog,"%d %d k=%d, k1=%.12e k2=%.12e k3=%.12e k4=%.12e delti/k=%.12e deltj/k=%.12e, xi-de/k=%.12e xj-de/k=%.12e res=%.12e k1234=%.12e,k1-2=%.12e,k3-4=%.12e\n",thetai,thetaj,k,k1,k2,k3,k4,delti[thetai]/k,delti[thetaj]/k,x[thetai]-delti[thetai]/k,x[thetaj]-delti[thetaj]/k, res,k1-k2-k3+k4,k1-k2,k3-k4); */
6954: /* #endif */
6955: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
6956: /* k=kmax; */
6957: /* } */
6958: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
6959: /* k=kmax; l=lmax*10; */
6960: /* } */
6961: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
6962: /* delts=delt; */
6963: /* } */
6964: /* } /\* End loop k *\/ */
6965: /* } */
6966: /* delti[theta]=delts; */
6967: /* return res; */
6968: /* } */
6969:
6970:
1.126 brouard 6971: /************** Inverse of matrix **************/
6972: void ludcmp(double **a, int n, int *indx, double *d)
6973: {
6974: int i,imax,j,k;
6975: double big,dum,sum,temp;
6976: double *vv;
6977:
6978: vv=vector(1,n);
6979: *d=1.0;
6980: for (i=1;i<=n;i++) {
6981: big=0.0;
6982: for (j=1;j<=n;j++)
6983: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 6984: if (big == 0.0){
6985: printf(" Singular Hessian matrix at row %d:\n",i);
6986: for (j=1;j<=n;j++) {
6987: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
6988: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
6989: }
6990: fflush(ficlog);
6991: fclose(ficlog);
6992: nrerror("Singular matrix in routine ludcmp");
6993: }
1.126 brouard 6994: vv[i]=1.0/big;
6995: }
6996: for (j=1;j<=n;j++) {
6997: for (i=1;i<j;i++) {
6998: sum=a[i][j];
6999: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
7000: a[i][j]=sum;
7001: }
7002: big=0.0;
7003: for (i=j;i<=n;i++) {
7004: sum=a[i][j];
7005: for (k=1;k<j;k++)
7006: sum -= a[i][k]*a[k][j];
7007: a[i][j]=sum;
7008: if ( (dum=vv[i]*fabs(sum)) >= big) {
7009: big=dum;
7010: imax=i;
7011: }
7012: }
7013: if (j != imax) {
7014: for (k=1;k<=n;k++) {
7015: dum=a[imax][k];
7016: a[imax][k]=a[j][k];
7017: a[j][k]=dum;
7018: }
7019: *d = -(*d);
7020: vv[imax]=vv[j];
7021: }
7022: indx[j]=imax;
7023: if (a[j][j] == 0.0) a[j][j]=TINY;
7024: if (j != n) {
7025: dum=1.0/(a[j][j]);
7026: for (i=j+1;i<=n;i++) a[i][j] *= dum;
7027: }
7028: }
7029: free_vector(vv,1,n); /* Doesn't work */
7030: ;
7031: }
7032:
7033: void lubksb(double **a, int n, int *indx, double b[])
7034: {
7035: int i,ii=0,ip,j;
7036: double sum;
7037:
7038: for (i=1;i<=n;i++) {
7039: ip=indx[i];
7040: sum=b[ip];
7041: b[ip]=b[i];
7042: if (ii)
7043: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
7044: else if (sum) ii=i;
7045: b[i]=sum;
7046: }
7047: for (i=n;i>=1;i--) {
7048: sum=b[i];
7049: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
7050: b[i]=sum/a[i][i];
7051: }
7052: }
7053:
7054: void pstamp(FILE *fichier)
7055: {
1.196 brouard 7056: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 7057: }
7058:
1.297 brouard 7059: void date2dmy(double date,double *day, double *month, double *year){
7060: double yp=0., yp1=0., yp2=0.;
7061:
7062: yp1=modf(date,&yp);/* extracts integral of date in yp and
7063: fractional in yp1 */
7064: *year=yp;
7065: yp2=modf((yp1*12),&yp);
7066: *month=yp;
7067: yp1=modf((yp2*30.5),&yp);
7068: *day=yp;
7069: if(*day==0) *day=1;
7070: if(*month==0) *month=1;
7071: }
7072:
1.253 brouard 7073:
7074:
1.126 brouard 7075: /************ Frequencies ********************/
1.251 brouard 7076: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 7077: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
7078: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 7079: { /* Some frequencies as well as proposing some starting values */
1.332 brouard 7080: /* Frequencies of any combination of dummy covariate used in the model equation */
1.265 brouard 7081: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 7082: int iind=0, iage=0;
7083: int mi; /* Effective wave */
7084: int first;
7085: double ***freq; /* Frequencies */
1.268 brouard 7086: double *x, *y, a=0.,b=0.,r=1., sa=0., sb=0.; /* for regression, y=b+m*x and r is the correlation coefficient */
7087: int no=0, linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb);
1.284 brouard 7088: double *meanq, *stdq, *idq;
1.226 brouard 7089: double **meanqt;
7090: double *pp, **prop, *posprop, *pospropt;
7091: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
7092: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
7093: double agebegin, ageend;
7094:
7095: pp=vector(1,nlstate);
1.251 brouard 7096: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 7097: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
7098: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
7099: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
7100: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 7101: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 7102: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 7103: meanqt=matrix(1,lastpass,1,nqtveff);
7104: strcpy(fileresp,"P_");
7105: strcat(fileresp,fileresu);
7106: /*strcat(fileresphtm,fileresu);*/
7107: if((ficresp=fopen(fileresp,"w"))==NULL) {
7108: printf("Problem with prevalence resultfile: %s\n", fileresp);
7109: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
7110: exit(0);
7111: }
1.240 brouard 7112:
1.226 brouard 7113: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
7114: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
7115: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
7116: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
7117: fflush(ficlog);
7118: exit(70);
7119: }
7120: else{
7121: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 7122: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 7123: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 7124: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
7125: }
1.319 brouard 7126: fprintf(ficresphtm,"Current page is file <a href=\"%s\">%s</a><br>\n\n<h4>Frequencies (weight=%d) and prevalence by age at begin of transition and dummy covariate value at beginning of transition</h4>\n",fileresphtm, fileresphtm, weightopt);
1.240 brouard 7127:
1.226 brouard 7128: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
7129: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
7130: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
7131: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
7132: fflush(ficlog);
7133: exit(70);
1.240 brouard 7134: } else{
1.226 brouard 7135: fprintf(ficresphtmfr,"<html><head>\n<title>IMaCh PHTM_Frequency table %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.319 brouard 7136: ,<hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 7137: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 7138: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
7139: }
1.319 brouard 7140: fprintf(ficresphtmfr,"Current page is file <a href=\"%s\">%s</a><br>\n\n<h4>(weight=%d) frequencies of all effective transitions of the model, by age at begin of transition, and covariate value at the begin of transition (if the covariate is a varying covariate) </h4>Unknown status is -1<br/>\n",fileresphtmfr, fileresphtmfr,weightopt);
1.240 brouard 7141:
1.253 brouard 7142: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
7143: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 7144: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 7145: j1=0;
1.126 brouard 7146:
1.227 brouard 7147: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
1.335 brouard 7148: j=cptcoveff; /* Only simple dummy covariates used in the model */
1.330 brouard 7149: /* j=cptcovn; /\* Only dummy covariates of the model *\/ */
1.226 brouard 7150: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 7151:
7152:
1.226 brouard 7153: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
7154: reference=low_education V1=0,V2=0
7155: med_educ V1=1 V2=0,
7156: high_educ V1=0 V2=1
1.330 brouard 7157: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcovn
1.226 brouard 7158: */
1.249 brouard 7159: dateintsum=0;
7160: k2cpt=0;
7161:
1.253 brouard 7162: if(cptcoveff == 0 )
1.265 brouard 7163: nl=1; /* Constant and age model only */
1.253 brouard 7164: else
7165: nl=2;
1.265 brouard 7166:
7167: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
7168: /* Loop on nj=1 or 2 if dummy covariates j!=0
1.335 brouard 7169: * Loop on j1(1 to 2**cptcoveff) covariate combination
1.265 brouard 7170: * freq[s1][s2][iage] =0.
7171: * Loop on iind
7172: * ++freq[s1][s2][iage] weighted
7173: * end iind
7174: * if covariate and j!0
7175: * headers Variable on one line
7176: * endif cov j!=0
7177: * header of frequency table by age
7178: * Loop on age
7179: * pp[s1]+=freq[s1][s2][iage] weighted
7180: * pos+=freq[s1][s2][iage] weighted
7181: * Loop on s1 initial state
7182: * fprintf(ficresp
7183: * end s1
7184: * end age
7185: * if j!=0 computes starting values
7186: * end compute starting values
7187: * end j1
7188: * end nl
7189: */
1.253 brouard 7190: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
7191: if(nj==1)
7192: j=0; /* First pass for the constant */
1.265 brouard 7193: else{
1.335 brouard 7194: j=cptcoveff; /* Other passes for the covariate values number of simple covariates in the model V2+V1 =2 (simple dummy fixed or time varying) */
1.265 brouard 7195: }
1.251 brouard 7196: first=1;
1.332 brouard 7197: for (j1 = 1; j1 <= (int) pow(2,j); j1++){ /* Loop on all dummy covariates combination of the model, ie excluding quantitatives, V4=0, V3=0 for example, fixed or varying covariates */
1.251 brouard 7198: posproptt=0.;
1.330 brouard 7199: /*printf("cptcovn=%d Tvaraff=%d", cptcovn,Tvaraff[1]);
1.251 brouard 7200: scanf("%d", i);*/
7201: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 7202: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 7203: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 7204: freq[i][s2][m]=0;
1.251 brouard 7205:
7206: for (i=1; i<=nlstate; i++) {
1.240 brouard 7207: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 7208: prop[i][m]=0;
7209: posprop[i]=0;
7210: pospropt[i]=0;
7211: }
1.283 brouard 7212: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 7213: idq[z1]=0.;
7214: meanq[z1]=0.;
7215: stdq[z1]=0.;
1.283 brouard 7216: }
7217: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 7218: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 7219: /* meanqt[m][z1]=0.; */
7220: /* } */
7221: /* } */
1.251 brouard 7222: /* dateintsum=0; */
7223: /* k2cpt=0; */
7224:
1.265 brouard 7225: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 7226: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
7227: bool=1;
7228: if(j !=0){
7229: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
1.335 brouard 7230: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
7231: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
1.251 brouard 7232: /* if(Tvaraff[z1] ==-20){ */
7233: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
7234: /* }else if(Tvaraff[z1] ==-10){ */
7235: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
1.330 brouard 7236: /* }else */ /* TODO TODO codtabm(j1,z1) or codtabm(j1,Tvaraff[z1]]z1)*/
1.335 brouard 7237: /* if( iind >=imx-3) printf("Searching error iind=%d Tvaraff[z1]=%d covar[Tvaraff[z1]][iind]=%.f TnsdVar[Tvaraff[z1]]=%d, cptcoveff=%d, cptcovs=%d \n",iind, Tvaraff[z1], covar[Tvaraff[z1]][iind],TnsdVar[Tvaraff[z1]],cptcoveff, cptcovs); */
7238: if(Tvaraff[z1]<1 || Tvaraff[z1]>=NCOVMAX)
1.338 brouard 7239: printf("Error Tvaraff[z1]=%d<1 or >=%d, cptcoveff=%d model=1+age+%s\n",Tvaraff[z1],NCOVMAX, cptcoveff, model);
1.332 brouard 7240: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]){ /* for combination j1 of covariates */
1.265 brouard 7241: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 7242: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
1.332 brouard 7243: /* printf("bool=%d i=%d, z1=%d, Tvaraff[%d]=%d, covar[Tvarff][%d]=%2f, codtabm(%d,%d)=%d, nbcode[Tvaraff][codtabm(%d,%d)=%d, j1=%d\n", */
7244: /* bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),*/
7245: /* j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
1.251 brouard 7246: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
7247: } /* Onlyf fixed */
7248: } /* end z1 */
1.335 brouard 7249: } /* cptcoveff > 0 */
1.251 brouard 7250: } /* end any */
7251: }/* end j==0 */
1.265 brouard 7252: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 7253: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 7254: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 7255: m=mw[mi][iind];
7256: if(j!=0){
7257: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
1.335 brouard 7258: for (z1=1; z1<=cptcoveff; z1++) {
1.251 brouard 7259: if( Fixed[Tmodelind[z1]]==1){
1.341 brouard 7260: /* iv= Tvar[Tmodelind[z1]]-ncovcol-nqv; /\* Good *\/ */
7261: iv= Tvar[Tmodelind[z1]]; /* Good *//* because cotvar starts now at first at ncovcol+nqv+ntv */
1.332 brouard 7262: if (cotvar[m][iv][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) /* iv=1 to ntv, right modality. If covariate's
1.251 brouard 7263: value is -1, we don't select. It differs from the
7264: constant and age model which counts them. */
7265: bool=0; /* not selected */
7266: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
1.334 brouard 7267: /* i1=Tvaraff[z1]; */
7268: /* i2=TnsdVar[i1]; */
7269: /* i3=nbcode[i1][i2]; */
7270: /* i4=covar[i1][iind]; */
7271: /* if(i4 != i3){ */
7272: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) { /* Bug valgrind */
1.251 brouard 7273: bool=0;
7274: }
7275: }
7276: }
7277: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
7278: } /* end j==0 */
7279: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 7280: if(bool==1){ /*Selected */
1.251 brouard 7281: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
7282: and mw[mi+1][iind]. dh depends on stepm. */
7283: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
7284: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
7285: if(m >=firstpass && m <=lastpass){
7286: k2=anint[m][iind]+(mint[m][iind]/12.);
7287: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
7288: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
7289: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
7290: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
7291: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
7292: if (m<lastpass) {
7293: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
7294: /* printf(" num=%ld m=%d, iind=%d s1=%d s2=%d agev at m=%d\n", num[iind], m, iind,s[m][iind],s[m+1][iind], (int)agev[m][iind]); */
7295: if(s[m][iind]==-1)
7296: printf(" num=%ld m=%d, iind=%d s1=%d s2=%d agev at m=%d agebegin=%.2f ageend=%.2f, agemed=%d\n", num[iind], m, iind,s[m][iind],s[m+1][iind], (int)agev[m][iind],agebegin, ageend, (int)((agebegin+ageend)/2.));
7297: freq[s[m][iind]][s[m+1][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
1.311 brouard 7298: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean on known values only */
7299: if(!isnan(covar[ncovcol+z1][iind])){
1.332 brouard 7300: idq[z1]=idq[z1]+weight[iind];
7301: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
7302: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; *//*error*/
7303: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
1.311 brouard 7304: }
1.284 brouard 7305: }
1.251 brouard 7306: /* if((int)agev[m][iind] == 55) */
7307: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
7308: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
7309: freq[s[m][iind]][s[m+1][iind]][iagemax+3] += weight[iind]; /* Total is in iagemax+3 *//* At age of beginning of transition, where status is known */
1.234 brouard 7310: }
1.251 brouard 7311: } /* end if between passes */
7312: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
7313: dateintsum=dateintsum+k2; /* on all covariates ?*/
7314: k2cpt++;
7315: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 7316: }
1.251 brouard 7317: }else{
7318: bool=1;
7319: }/* end bool 2 */
7320: } /* end m */
1.284 brouard 7321: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
7322: /* idq[z1]=idq[z1]+weight[iind]; */
7323: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
7324: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
7325: /* } */
1.251 brouard 7326: } /* end bool */
7327: } /* end iind = 1 to imx */
1.319 brouard 7328: /* prop[s][age] is fed for any initial and valid live state as well as
1.251 brouard 7329: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
7330:
7331:
7332: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.335 brouard 7333: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
1.265 brouard 7334: pstamp(ficresp);
1.335 brouard 7335: if (cptcoveff>0 && j!=0){
1.265 brouard 7336: pstamp(ficresp);
1.251 brouard 7337: printf( "\n#********** Variable ");
7338: fprintf(ficresp, "\n#********** Variable ");
7339: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
7340: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
7341: fprintf(ficlog, "\n#********** Variable ");
1.340 brouard 7342: for (z1=1; z1<=cptcoveff; z1++){
1.251 brouard 7343: if(!FixedV[Tvaraff[z1]]){
1.330 brouard 7344: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7345: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7346: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7347: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7348: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.250 brouard 7349: }else{
1.330 brouard 7350: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7351: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7352: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7353: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7354: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.251 brouard 7355: }
7356: }
7357: printf( "**********\n#");
7358: fprintf(ficresp, "**********\n#");
7359: fprintf(ficresphtm, "**********</h3>\n");
7360: fprintf(ficresphtmfr, "**********</h3>\n");
7361: fprintf(ficlog, "**********\n");
7362: }
1.284 brouard 7363: /*
7364: Printing means of quantitative variables if any
7365: */
7366: for (z1=1; z1<= nqfveff; z1++) {
1.311 brouard 7367: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.3g (weighted) individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.312 brouard 7368: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
1.284 brouard 7369: if(weightopt==1){
7370: printf(" Weighted mean and standard deviation of");
7371: fprintf(ficlog," Weighted mean and standard deviation of");
7372: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
7373: }
1.311 brouard 7374: /* mu = \frac{w x}{\sum w}
7375: var = \frac{\sum w (x-mu)^2}{\sum w} = \frac{w x^2}{\sum w} - mu^2
7376: */
7377: printf(" fixed quantitative variable V%d on %.3g (weighted) representatives of the population : %8.5g (%8.5g)\n", ncovcol+z1, idq[z1],meanq[z1]/idq[z1], sqrt(stdq[z1]/idq[z1]-meanq[z1]*meanq[z1]/idq[z1]/idq[z1]));
7378: fprintf(ficlog," fixed quantitative variable V%d on %.3g (weighted) representatives of the population : %8.5g (%8.5g)\n", ncovcol+z1, idq[z1],meanq[z1]/idq[z1], sqrt(stdq[z1]/idq[z1]-meanq[z1]*meanq[z1]/idq[z1]/idq[z1]));
7379: fprintf(ficresphtmfr," fixed quantitative variable V%d on %.3g (weighted) representatives of the population : %8.5g (%8.5g)<p>\n", ncovcol+z1, idq[z1],meanq[z1]/idq[z1], sqrt(stdq[z1]/idq[z1]-meanq[z1]*meanq[z1]/idq[z1]/idq[z1]));
1.284 brouard 7380: }
7381: /* for (z1=1; z1<= nqtveff; z1++) { */
7382: /* for(m=1;m<=lastpass;m++){ */
7383: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
7384: /* } */
7385: /* } */
1.283 brouard 7386:
1.251 brouard 7387: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.335 brouard 7388: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
1.265 brouard 7389: fprintf(ficresp, " Age");
1.335 brouard 7390: if(nj==2) for (z1=1; z1<=cptcoveff; z1++) {
7391: printf(" V%d=%d, z1=%d, Tvaraff[z1]=%d, j1=%d, TnsdVar[Tvaraff[%d]]=%d |",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])], z1, Tvaraff[z1], j1,z1,TnsdVar[Tvaraff[z1]]);
7392: fprintf(ficresp, " V%d=%d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7393: }
1.251 brouard 7394: for(i=1; i<=nlstate;i++) {
1.335 brouard 7395: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 7396: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
7397: }
1.335 brouard 7398: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 7399: fprintf(ficresphtm, "\n");
7400:
7401: /* Header of frequency table by age */
7402: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
7403: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 7404: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 7405: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 7406: if(s2!=0 && m!=0)
7407: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 7408: }
1.226 brouard 7409: }
1.251 brouard 7410: fprintf(ficresphtmfr, "\n");
7411:
7412: /* For each age */
7413: for(iage=iagemin; iage <= iagemax+3; iage++){
7414: fprintf(ficresphtm,"<tr>");
7415: if(iage==iagemax+1){
7416: fprintf(ficlog,"1");
7417: fprintf(ficresphtmfr,"<tr><th>0</th> ");
7418: }else if(iage==iagemax+2){
7419: fprintf(ficlog,"0");
7420: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
7421: }else if(iage==iagemax+3){
7422: fprintf(ficlog,"Total");
7423: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
7424: }else{
1.240 brouard 7425: if(first==1){
1.251 brouard 7426: first=0;
7427: printf("See log file for details...\n");
7428: }
7429: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
7430: fprintf(ficlog,"Age %d", iage);
7431: }
1.265 brouard 7432: for(s1=1; s1 <=nlstate ; s1++){
7433: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
7434: pp[s1] += freq[s1][m][iage];
1.251 brouard 7435: }
1.265 brouard 7436: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 7437: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 7438: pos += freq[s1][m][iage];
7439: if(pp[s1]>=1.e-10){
1.251 brouard 7440: if(first==1){
1.265 brouard 7441: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 7442: }
1.265 brouard 7443: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 7444: }else{
7445: if(first==1)
1.265 brouard 7446: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
7447: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 7448: }
7449: }
7450:
1.265 brouard 7451: for(s1=1; s1 <=nlstate ; s1++){
7452: /* posprop[s1]=0; */
7453: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
7454: pp[s1] += freq[s1][m][iage];
7455: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
7456:
7457: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
7458: pos += pp[s1]; /* pos is the total number of transitions until this age */
7459: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
7460: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
7461: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
7462: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
7463: }
7464:
7465: /* Writing ficresp */
1.335 brouard 7466: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 7467: if( iage <= iagemax){
7468: fprintf(ficresp," %d",iage);
7469: }
7470: }else if( nj==2){
7471: if( iage <= iagemax){
7472: fprintf(ficresp," %d",iage);
1.335 brouard 7473: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.265 brouard 7474: }
1.240 brouard 7475: }
1.265 brouard 7476: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 7477: if(pos>=1.e-5){
1.251 brouard 7478: if(first==1)
1.265 brouard 7479: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
7480: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 7481: }else{
7482: if(first==1)
1.265 brouard 7483: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
7484: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 7485: }
7486: if( iage <= iagemax){
7487: if(pos>=1.e-5){
1.335 brouard 7488: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 7489: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
7490: }else if( nj==2){
7491: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
7492: }
7493: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
7494: /*probs[iage][s1][j1]= pp[s1]/pos;*/
7495: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
7496: } else{
1.335 brouard 7497: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
1.265 brouard 7498: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 7499: }
1.240 brouard 7500: }
1.265 brouard 7501: pospropt[s1] +=posprop[s1];
7502: } /* end loop s1 */
1.251 brouard 7503: /* pospropt=0.; */
1.265 brouard 7504: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 7505: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 7506: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 7507: if(first==1){
1.265 brouard 7508: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 7509: }
1.265 brouard 7510: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
7511: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 7512: }
1.265 brouard 7513: if(s1!=0 && m!=0)
7514: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 7515: }
1.265 brouard 7516: } /* end loop s1 */
1.251 brouard 7517: posproptt=0.;
1.265 brouard 7518: for(s1=1; s1 <=nlstate; s1++){
7519: posproptt += pospropt[s1];
1.251 brouard 7520: }
7521: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 7522: fprintf(ficresphtm,"</tr>\n");
1.335 brouard 7523: if((cptcoveff==0 && nj==1)|| nj==2 ) {
1.265 brouard 7524: if(iage <= iagemax)
7525: fprintf(ficresp,"\n");
1.240 brouard 7526: }
1.251 brouard 7527: if(first==1)
7528: printf("Others in log...\n");
7529: fprintf(ficlog,"\n");
7530: } /* end loop age iage */
1.265 brouard 7531:
1.251 brouard 7532: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 7533: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 7534: if(posproptt < 1.e-5){
1.265 brouard 7535: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 7536: }else{
1.265 brouard 7537: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 7538: }
1.226 brouard 7539: }
1.251 brouard 7540: fprintf(ficresphtm,"</tr>\n");
7541: fprintf(ficresphtm,"</table>\n");
7542: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 7543: if(posproptt < 1.e-5){
1.251 brouard 7544: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
7545: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 7546: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
7547: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 7548: invalidvarcomb[j1]=1;
1.226 brouard 7549: }else{
1.338 brouard 7550: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced (or no resultline).</p>",j1);
1.251 brouard 7551: invalidvarcomb[j1]=0;
1.226 brouard 7552: }
1.251 brouard 7553: fprintf(ficresphtmfr,"</table>\n");
7554: fprintf(ficlog,"\n");
7555: if(j!=0){
7556: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 7557: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 7558: for(k=1; k <=(nlstate+ndeath); k++){
7559: if (k != i) {
1.265 brouard 7560: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 7561: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 7562: if(j1==1){ /* All dummy covariates to zero */
7563: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
7564: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 7565: printf("%d%d ",i,k);
7566: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 7567: printf("%12.7f ln(%.0f/%.0f)= %f, OR=%f sd=%f \n",p[s1],freq[i][k][iagemax+3],freq[i][i][iagemax+3], log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]),freq[i][k][iagemax+3]/freq[i][i][iagemax+3], sqrt(1/freq[i][k][iagemax+3]+1/freq[i][i][iagemax+3]));
7568: fprintf(ficlog,"%12.7f ln(%.0f/%.0f)= %12.7f \n",p[s1],freq[i][k][iagemax+3],freq[i][i][iagemax+3], log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]));
7569: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 7570: }
1.253 brouard 7571: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
7572: for(iage=iagemin; iage <= iagemax+3; iage++){
7573: x[iage]= (double)iage;
7574: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 7575: /* printf("i=%d, k=%d, s1=%d, j1=%d, jj=%d, y[%d]=%f\n",i,k,s1,j1,jj, iage, y[iage]); */
1.253 brouard 7576: }
1.268 brouard 7577: /* Some are not finite, but linreg will ignore these ages */
7578: no=0;
1.253 brouard 7579: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 7580: pstart[s1]=b;
7581: pstart[s1-1]=a;
1.252 brouard 7582: }else if( j1!=1 && (j1==2 || (log(j1-1.)/log(2.)-(int)(log(j1-1.)/log(2.))) <0.010) && ( TvarsDind[(int)(log(j1-1.)/log(2.))+1]+2+nagesqr == jj) && Dummy[jj-2-nagesqr]==0){ /* We want only if the position, jj, in model corresponds to unique covariate equal to 1 in j1 combination */
7583: printf("j1=%d, jj=%d, (int)(log(j1-1.)/log(2.))+1=%d, TvarsDind[(int)(log(j1-1.)/log(2.))+1]=%d\n",j1, jj,(int)(log(j1-1.)/log(2.))+1,TvarsDind[(int)(log(j1-1.)/log(2.))+1]);
7584: printf("j1=%d, jj=%d, (log(j1-1.)/log(2.))+1=%f, TvarsDind[(int)(log(j1-1.)/log(2.))+1]=%d\n",j1, jj,(log(j1-1.)/log(2.))+1,TvarsDind[(int)(log(j1-1.)/log(2.))+1]);
1.265 brouard 7585: pstart[s1]= log((freq[i][k][iagemax+3]/freq[i][i][iagemax+3])/(freq[i][k][iagemax+4]/freq[i][i][iagemax+4]));
1.252 brouard 7586: printf("%d%d ",i,k);
7587: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 7588: printf("s1=%d,i=%d,k=%d,p[%d]=%12.7f ln((%.0f/%.0f)/(%.0f/%.0f))= %f, OR=%f sd=%f \n",s1,i,k,s1,p[s1],freq[i][k][iagemax+3],freq[i][i][iagemax+3],freq[i][k][iagemax+4],freq[i][i][iagemax+4], log((freq[i][k][iagemax+3]/freq[i][i][iagemax+3])/(freq[i][k][iagemax+4]/freq[i][i][iagemax+4])),(freq[i][k][iagemax+3]/freq[i][i][iagemax+3])/(freq[i][k][iagemax+4]/freq[i][i][iagemax+4]), sqrt(1/freq[i][k][iagemax+3]+1/freq[i][i][iagemax+3]+1/freq[i][k][iagemax+4]+1/freq[i][i][iagemax+4]));
1.251 brouard 7589: }else{ /* Other cases, like quantitative fixed or varying covariates */
7590: ;
7591: }
7592: /* printf("%12.7f )", param[i][jj][k]); */
7593: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 7594: s1++;
1.251 brouard 7595: } /* end jj */
7596: } /* end k!= i */
7597: } /* end k */
1.265 brouard 7598: } /* end i, s1 */
1.251 brouard 7599: } /* end j !=0 */
7600: } /* end selected combination of covariate j1 */
7601: if(j==0){ /* We can estimate starting values from the occurences in each case */
7602: printf("#Freqsummary: Starting values for the constants:\n");
7603: fprintf(ficlog,"\n");
1.265 brouard 7604: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 7605: for(k=1; k <=(nlstate+ndeath); k++){
7606: if (k != i) {
7607: printf("%d%d ",i,k);
7608: fprintf(ficlog,"%d%d ",i,k);
7609: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 7610: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 7611: if(jj==1){ /* Age has to be done */
1.265 brouard 7612: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
7613: printf("%12.7f ln(%.0f/%.0f)= %12.7f ",p[s1],freq[i][k][iagemax+3],freq[i][i][iagemax+3], log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]));
7614: fprintf(ficlog,"%12.7f ln(%.0f/%.0f)= %12.7f ",p[s1],freq[i][k][iagemax+3],freq[i][i][iagemax+3], log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]));
1.251 brouard 7615: }
7616: /* printf("%12.7f )", param[i][jj][k]); */
7617: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 7618: s1++;
1.250 brouard 7619: }
1.251 brouard 7620: printf("\n");
7621: fprintf(ficlog,"\n");
1.250 brouard 7622: }
7623: }
1.284 brouard 7624: } /* end of state i */
1.251 brouard 7625: printf("#Freqsummary\n");
7626: fprintf(ficlog,"\n");
1.265 brouard 7627: for(s1=-1; s1 <=nlstate+ndeath; s1++){
7628: for(s2=-1; s2 <=nlstate+ndeath; s2++){
7629: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
7630: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
7631: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
7632: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
7633: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
7634: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 7635: /* } */
7636: }
1.265 brouard 7637: } /* end loop s1 */
1.251 brouard 7638:
7639: printf("\n");
7640: fprintf(ficlog,"\n");
7641: } /* end j=0 */
1.249 brouard 7642: } /* end j */
1.252 brouard 7643:
1.253 brouard 7644: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 7645: for(i=1, jk=1; i <=nlstate; i++){
7646: for(j=1; j <=nlstate+ndeath; j++){
7647: if(j!=i){
7648: /*ca[0]= k+'a'-1;ca[1]='\0';*/
7649: printf("%1d%1d",i,j);
7650: fprintf(ficparo,"%1d%1d",i,j);
7651: for(k=1; k<=ncovmodel;k++){
7652: /* printf(" %lf",param[i][j][k]); */
7653: /* fprintf(ficparo," %lf",param[i][j][k]); */
7654: p[jk]=pstart[jk];
7655: printf(" %f ",pstart[jk]);
7656: fprintf(ficparo," %f ",pstart[jk]);
7657: jk++;
7658: }
7659: printf("\n");
7660: fprintf(ficparo,"\n");
7661: }
7662: }
7663: }
7664: } /* end mle=-2 */
1.226 brouard 7665: dateintmean=dateintsum/k2cpt;
1.296 brouard 7666: date2dmy(dateintmean,&jintmean,&mintmean,&aintmean);
1.240 brouard 7667:
1.226 brouard 7668: fclose(ficresp);
7669: fclose(ficresphtm);
7670: fclose(ficresphtmfr);
1.283 brouard 7671: free_vector(idq,1,nqfveff);
1.226 brouard 7672: free_vector(meanq,1,nqfveff);
1.284 brouard 7673: free_vector(stdq,1,nqfveff);
1.226 brouard 7674: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 7675: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
7676: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 7677: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 7678: free_vector(pospropt,1,nlstate);
7679: free_vector(posprop,1,nlstate);
1.251 brouard 7680: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 7681: free_vector(pp,1,nlstate);
7682: /* End of freqsummary */
7683: }
1.126 brouard 7684:
1.268 brouard 7685: /* Simple linear regression */
7686: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
7687:
7688: /* y=a+bx regression */
7689: double sumx = 0.0; /* sum of x */
7690: double sumx2 = 0.0; /* sum of x**2 */
7691: double sumxy = 0.0; /* sum of x * y */
7692: double sumy = 0.0; /* sum of y */
7693: double sumy2 = 0.0; /* sum of y**2 */
7694: double sume2 = 0.0; /* sum of square or residuals */
7695: double yhat;
7696:
7697: double denom=0;
7698: int i;
7699: int ne=*no;
7700:
7701: for ( i=ifi, ne=0;i<=ila;i++) {
7702: if(!isfinite(x[i]) || !isfinite(y[i])){
7703: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
7704: continue;
7705: }
7706: ne=ne+1;
7707: sumx += x[i];
7708: sumx2 += x[i]*x[i];
7709: sumxy += x[i] * y[i];
7710: sumy += y[i];
7711: sumy2 += y[i]*y[i];
7712: denom = (ne * sumx2 - sumx*sumx);
7713: /* printf("ne=%d, i=%d,x[%d]=%f, y[%d]=%f sumx=%f, sumx2=%f, sumxy=%f, sumy=%f, sumy2=%f, denom=%f\n",ne,i,i,x[i],i,y[i], sumx, sumx2,sumxy, sumy, sumy2,denom); */
7714: }
7715:
7716: denom = (ne * sumx2 - sumx*sumx);
7717: if (denom == 0) {
7718: // vertical, slope m is infinity
7719: *b = INFINITY;
7720: *a = 0;
7721: if (r) *r = 0;
7722: return 1;
7723: }
7724:
7725: *b = (ne * sumxy - sumx * sumy) / denom;
7726: *a = (sumy * sumx2 - sumx * sumxy) / denom;
7727: if (r!=NULL) {
7728: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
7729: sqrt((sumx2 - sumx*sumx/ne) *
7730: (sumy2 - sumy*sumy/ne));
7731: }
7732: *no=ne;
7733: for ( i=ifi, ne=0;i<=ila;i++) {
7734: if(!isfinite(x[i]) || !isfinite(y[i])){
7735: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
7736: continue;
7737: }
7738: ne=ne+1;
7739: yhat = y[i] - *a -*b* x[i];
7740: sume2 += yhat * yhat ;
7741:
7742: denom = (ne * sumx2 - sumx*sumx);
7743: /* printf("ne=%d, i=%d,x[%d]=%f, y[%d]=%f sumx=%f, sumx2=%f, sumxy=%f, sumy=%f, sumy2=%f, denom=%f\n",ne,i,i,x[i],i,y[i], sumx, sumx2,sumxy, sumy, sumy2,denom); */
7744: }
7745: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
7746: *sa= *sb * sqrt(sumx2/ne);
7747:
7748: return 0;
7749: }
7750:
1.126 brouard 7751: /************ Prevalence ********************/
1.227 brouard 7752: void prevalence(double ***probs, double agemin, double agemax, int **s, double **agev, int nlstate, int imx, int *Tvar, int **nbcode, int *ncodemax,double **mint,double **anint, double dateprev1,double dateprev2, int firstpass, int lastpass)
7753: {
7754: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
7755: in each health status at the date of interview (if between dateprev1 and dateprev2).
7756: We still use firstpass and lastpass as another selection.
7757: */
1.126 brouard 7758:
1.227 brouard 7759: int i, m, jk, j1, bool, z1,j, iv;
7760: int mi; /* Effective wave */
7761: int iage;
1.359 brouard 7762: double agebegin; /*, ageend;*/
1.227 brouard 7763:
7764: double **prop;
7765: double posprop;
7766: double y2; /* in fractional years */
7767: int iagemin, iagemax;
7768: int first; /** to stop verbosity which is redirected to log file */
7769:
7770: iagemin= (int) agemin;
7771: iagemax= (int) agemax;
7772: /*pp=vector(1,nlstate);*/
1.251 brouard 7773: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 7774: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
7775: j1=0;
1.222 brouard 7776:
1.227 brouard 7777: /*j=cptcoveff;*/
7778: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 7779:
1.288 brouard 7780: first=0;
1.335 brouard 7781: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of simple dummy covariates */
1.227 brouard 7782: for (i=1; i<=nlstate; i++)
1.251 brouard 7783: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 7784: prop[i][iage]=0.0;
7785: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
7786: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
7787: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
7788:
7789: for (i=1; i<=imx; i++) { /* Each individual */
7790: bool=1;
7791: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
7792: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
7793: m=mw[mi][i];
7794: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
7795: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
7796: for (z1=1; z1<=cptcoveff; z1++){
7797: if( Fixed[Tmodelind[z1]]==1){
1.341 brouard 7798: iv= Tvar[Tmodelind[z1]];/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
1.332 brouard 7799: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) /* iv=1 to ntv, right modality */
1.227 brouard 7800: bool=0;
7801: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
1.332 brouard 7802: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) {
1.227 brouard 7803: bool=0;
7804: }
7805: }
7806: if(bool==1){ /* Otherwise we skip that wave/person */
7807: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
7808: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
7809: if(m >=firstpass && m <=lastpass){
7810: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
7811: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
7812: if(agev[m][i]==0) agev[m][i]=iagemax+1;
7813: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 7814: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 7815: printf("Error on individual # %d agev[m][i]=%f <%d-%d or > %d+3+%d m=%d; either change agemin or agemax or fix data\n",i, agev[m][i],iagemin,AGEMARGE, iagemax,AGEMARGE,m);
7816: exit(1);
7817: }
7818: if (s[m][i]>0 && s[m][i]<=nlstate) {
7819: /*if(i>4620) printf(" i=%d m=%d s[m][i]=%d (int)agev[m][i]=%d weight[i]=%f prop=%f\n",i,m,s[m][i],(int)agev[m][m],weight[i],prop[s[m][i]][(int)agev[m][i]]);*/
7820: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
7821: prop[s[m][i]][iagemax+3] += weight[i];
7822: } /* end valid statuses */
7823: } /* end selection of dates */
7824: } /* end selection of waves */
7825: } /* end bool */
7826: } /* end wave */
7827: } /* end individual */
7828: for(i=iagemin; i <= iagemax+3; i++){
7829: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
7830: posprop += prop[jk][i];
7831: }
7832:
7833: for(jk=1; jk <=nlstate ; jk++){
7834: if( i <= iagemax){
7835: if(posprop>=1.e-5){
7836: probs[i][jk][j1]= prop[jk][i]/posprop;
7837: } else{
1.288 brouard 7838: if(!first){
7839: first=1;
1.266 brouard 7840: printf("Warning Observed prevalence doesn't sum to 1 for state %d: probs[%d][%d][%d]=%lf because of lack of cases\nSee others in log file...\n",jk,i,jk, j1,probs[i][jk][j1]);
7841: }else{
1.288 brouard 7842: fprintf(ficlog,"Warning Observed prevalence doesn't sum to 1 for state %d: probs[%d][%d][%d]=%lf because of lack of cases.\n",jk,i,jk, j1,probs[i][jk][j1]);
1.227 brouard 7843: }
7844: }
7845: }
7846: }/* end jk */
7847: }/* end i */
1.222 brouard 7848: /*} *//* end i1 */
1.227 brouard 7849: } /* end j1 */
1.222 brouard 7850:
1.227 brouard 7851: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
7852: /*free_vector(pp,1,nlstate);*/
1.251 brouard 7853: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 7854: } /* End of prevalence */
1.126 brouard 7855:
7856: /************* Waves Concatenation ***************/
7857:
7858: void concatwav(int wav[], int **dh, int **bh, int **mw, int **s, double *agedc, double **agev, int firstpass, int lastpass, int imx, int nlstate, int stepm)
7859: {
1.298 brouard 7860: /* Concatenates waves: wav[i] is the number of effective (useful waves in the sense that a non interview is useless) of individual i.
1.126 brouard 7861: Death is a valid wave (if date is known).
7862: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
7863: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
1.298 brouard 7864: and mw[mi+1][i]. dh depends on stepm. s[m][i] exists for any wave from firstpass to lastpass
1.227 brouard 7865: */
1.126 brouard 7866:
1.224 brouard 7867: int i=0, mi=0, m=0, mli=0;
1.126 brouard 7868: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
7869: double sum=0., jmean=0.;*/
1.224 brouard 7870: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 7871: int j, k=0,jk, ju, jl;
7872: double sum=0.;
7873: first=0;
1.214 brouard 7874: firstwo=0;
1.217 brouard 7875: firsthree=0;
1.218 brouard 7876: firstfour=0;
1.164 brouard 7877: jmin=100000;
1.126 brouard 7878: jmax=-1;
7879: jmean=0.;
1.224 brouard 7880:
7881: /* Treating live states */
1.214 brouard 7882: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 7883: mi=0; /* First valid wave */
1.227 brouard 7884: mli=0; /* Last valid wave */
1.309 brouard 7885: m=firstpass; /* Loop on waves */
7886: while(s[m][i] <= nlstate){ /* a live state or unknown state */
1.227 brouard 7887: if(m >firstpass && s[m][i]==s[m-1][i] && mint[m][i]==mint[m-1][i] && anint[m][i]==anint[m-1][i]){/* Two succesive identical information on wave m */
7888: mli=m-1;/* mw[++mi][i]=m-1; */
7889: }else if(s[m][i]>=1 || s[m][i]==-4 || s[m][i]==-5){ /* Since 0.98r4 if status=-2 vital status is really unknown, wave should be skipped */
1.309 brouard 7890: mw[++mi][i]=m; /* Valid wave: incrementing mi and updating mi; mw[mi] is the wave number of mi_th valid transition */
1.227 brouard 7891: mli=m;
1.224 brouard 7892: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
7893: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 7894: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 7895: }
1.309 brouard 7896: else{ /* m = lastpass, eventual special issue with warning */
1.224 brouard 7897: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 7898: break;
1.224 brouard 7899: #else
1.317 brouard 7900: if(s[m][i]==-1 && (int) andc[i] == 9999 && (int)anint[m][i] != 9999){ /* no death date and known date of interview, case -2 (vital status unknown is warned later */
1.227 brouard 7901: if(firsthree == 0){
1.302 brouard 7902: printf("Information! Unknown status for individual %ld line=%d occurred at last wave %d at known date %d/%d. Please, check if your unknown date of death %d/%d means a live state %d at wave %d. This case(%d)/wave(%d) contributes to the likelihood as 1-p_{%d%d} .\nOthers in log file only\n",num[i],i,lastpass,(int)mint[m][i],(int)anint[m][i], (int) moisdc[i], (int) andc[i], s[m][i], m, i, m, s[m][i], nlstate+ndeath);
1.227 brouard 7903: firsthree=1;
1.317 brouard 7904: }else if(firsthree >=1 && firsthree < 10){
7905: fprintf(ficlog,"Information! Unknown status for individual %ld line=%d occurred at last wave %d at known date %d/%d. Please, check if your unknown date of death %d/%d means a live state %d at wave %d. This case(%d)/wave(%d) contributes to the likelihood as 1-p_{%d%d} .\n",num[i],i,lastpass,(int)mint[m][i],(int)anint[m][i], (int) moisdc[i], (int) andc[i], s[m][i], m, i, m, s[m][i], nlstate+ndeath);
7906: firsthree++;
7907: }else if(firsthree == 10){
7908: printf("Information, too many Information flags: no more reported to log either\n");
7909: fprintf(ficlog,"Information, too many Information flags: no more reported to log either\n");
7910: firsthree++;
7911: }else{
7912: firsthree++;
1.227 brouard 7913: }
1.309 brouard 7914: mw[++mi][i]=m; /* Valid transition with unknown status */
1.227 brouard 7915: mli=m;
7916: }
7917: if(s[m][i]==-2){ /* Vital status is really unknown */
7918: nbwarn++;
1.309 brouard 7919: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified?not a transition */
1.227 brouard 7920: printf("Warning! Vital status for individual %ld (line=%d) at last wave %d interviewed at date %d/%d is unknown %d. Please, check if the vital status and the date of death %d/%d are really unknown. This case (%d)/wave (%d) is skipped, no contribution to likelihood.\nOthers in log file only\n",num[i],i,lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], (int) moisdc[i], (int) andc[i], i, m);
7921: fprintf(ficlog,"Warning! Vital status for individual %ld (line=%d) at last wave %d interviewed at date %d/%d is unknown %d. Please, check if the vital status and the date of death %d/%d are really unknown. This case (%d)/wave (%d) is skipped, no contribution to likelihood.\n",num[i],i,lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], (int) moisdc[i], (int) andc[i], i, m);
7922: }
7923: break;
7924: }
7925: break;
1.224 brouard 7926: #endif
1.227 brouard 7927: }/* End m >= lastpass */
1.126 brouard 7928: }/* end while */
1.224 brouard 7929:
1.227 brouard 7930: /* mi is the last effective wave, m is lastpass, mw[j][i] gives the # of j-th effective wave for individual i */
1.216 brouard 7931: /* After last pass */
1.224 brouard 7932: /* Treating death states */
1.214 brouard 7933: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 7934: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
7935: /* } */
1.126 brouard 7936: mi++; /* Death is another wave */
7937: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 7938: /* Only death is a correct wave */
1.126 brouard 7939: mw[mi][i]=m;
1.257 brouard 7940: } /* else not in a death state */
1.224 brouard 7941: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 7942: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 7943: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.309 brouard 7944: if((andc[i]+moisdc[i]/12.) <=(anint[m][i]+mint[m][i]/12.)){ /* month of death occured before last wave month and status should have been death instead of -1 */
1.227 brouard 7945: nbwarn++;
7946: if(firstfiv==0){
1.309 brouard 7947: printf("Warning! Death for individual %ld line=%d occurred at %d/%d before last wave %d, interviewed on %d/%d and should have been coded as death instead of '%d'. This case (%d)/wave (%d) is contributing to likelihood.\nOthers in log file only\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], i,m );
1.227 brouard 7948: firstfiv=1;
7949: }else{
1.309 brouard 7950: fprintf(ficlog,"Warning! Death for individual %ld line=%d occurred at %d/%d before last wave %d, interviewed on %d/%d and should have been coded as death instead of '%d'. This case (%d)/wave (%d) is contributing to likelihood.\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], i,m );
1.227 brouard 7951: }
1.309 brouard 7952: s[m][i]=nlstate+1; /* Fixing the status as death. Be careful if multiple death states */
7953: }else{ /* Month of Death occured afer last wave month, potential bias */
1.227 brouard 7954: nberr++;
7955: if(firstwo==0){
1.309 brouard 7956: printf("Error! Death for individual %ld line=%d occurred at %d/%d after last wave %d interviewed at %d/%d with status %d. Potential bias if other individuals are still alive on this date but ignored. This case (%d)/wave (%d) is skipped, no contribution to likelihood. Please add a new fictitious wave at the date of last vital status scan, with a dead status. See documentation\nOthers in log file only\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], i,m );
1.227 brouard 7957: firstwo=1;
7958: }
1.309 brouard 7959: fprintf(ficlog,"Error! Death for individual %ld line=%d occurred at %d/%d after last wave %d interviewed at %d/%d with status %d. Potential bias if other individuals are still alive on this date but ignored. This case (%d)/wave (%d) is skipped, no contribution to likelihood. Please add a new fictitious wave at the date of last vital status scan, with a dead status. See documentation\n\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], i,m );
1.227 brouard 7960: }
1.257 brouard 7961: }else{ /* if date of interview is unknown */
1.227 brouard 7962: /* death is known but not confirmed by death status at any wave */
7963: if(firstfour==0){
1.309 brouard 7964: printf("Error! Death for individual %ld line=%d occurred %d/%d but not confirmed by any death status for any wave, including last wave %d at unknown date %d/%d with status %d. Potential bias if other individuals are still alive at this date but ignored. This case (%d)/wave (%d) is skipped, no contribution to likelihood.\nOthers in log file only\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], i,m );
1.227 brouard 7965: firstfour=1;
7966: }
1.309 brouard 7967: fprintf(ficlog,"Error! Death for individual %ld line=%d occurred %d/%d but not confirmed by any death status for any wave, including last wave %d at unknown date %d/%d with status %d. Potential bias if other individuals are still alive at this date but ignored. This case (%d)/wave (%d) is skipped, no contribution to likelihood.\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], i,m );
1.214 brouard 7968: }
1.224 brouard 7969: } /* end if date of death is known */
7970: #endif
1.309 brouard 7971: wav[i]=mi; /* mi should be the last effective wave (or mli), */
7972: /* wav[i]=mw[mi][i]; */
1.126 brouard 7973: if(mi==0){
7974: nbwarn++;
7975: if(first==0){
1.227 brouard 7976: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
7977: first=1;
1.126 brouard 7978: }
7979: if(first==1){
1.227 brouard 7980: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 7981: }
7982: } /* end mi==0 */
7983: } /* End individuals */
1.214 brouard 7984: /* wav and mw are no more changed */
1.223 brouard 7985:
1.317 brouard 7986: printf("Information, you have to check %d informations which haven't been logged!\n",firsthree);
7987: fprintf(ficlog,"Information, you have to check %d informations which haven't been logged!\n",firsthree);
7988:
7989:
1.126 brouard 7990: for(i=1; i<=imx; i++){
7991: for(mi=1; mi<wav[i];mi++){
7992: if (stepm <=0)
1.227 brouard 7993: dh[mi][i]=1;
1.126 brouard 7994: else{
1.260 brouard 7995: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 7996: if (agedc[i] < 2*AGESUP) {
7997: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
7998: if(j==0) j=1; /* Survives at least one month after exam */
7999: else if(j<0){
8000: nberr++;
1.359 brouard 8001: printf("Error! Negative delay (%d to death) between waves %d and %d of individual %ld (around line %d) who is aged %.1f with statuses from %d to %d\n ",j,mw[mi][i],mw[mi+1][i],num[i], i,agev[mw[mi][i]][i],s[mw[mi][i]][i] ,s[mw[mi+1][i]][i]);
1.227 brouard 8002: j=1; /* Temporary Dangerous patch */
8003: printf(" We assumed that the date of interview was correct (and not the date of death) and postponed the death %d month(s) (one stepm) after the interview. You MUST fix the contradiction between dates.\n",stepm);
1.359 brouard 8004: fprintf(ficlog,"Error! Negative delay (%d to death) between waves %d and %d of individual %ld (around line %d) who is aged %.1f with statuses from %d to %d\n ",j,mw[mi][i],mw[mi+1][i],num[i], i,agev[mw[mi][i]][i],s[mw[mi][i]][i] ,s[mw[mi+1][i]][i]);
1.227 brouard 8005: fprintf(ficlog," We assumed that the date of interview was correct (and not the date of death) and postponed the death %d month(s) (one stepm) after the interview. You MUST fix the contradiction between dates.\n",stepm);
8006: }
8007: k=k+1;
8008: if (j >= jmax){
8009: jmax=j;
8010: ijmax=i;
8011: }
8012: if (j <= jmin){
8013: jmin=j;
8014: ijmin=i;
8015: }
8016: sum=sum+j;
8017: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
8018: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
8019: }
8020: }
8021: else{
8022: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 8023: /* if (j<0) printf("%d %lf %lf %d %d %d\n", i,agev[mw[mi+1][i]][i], agev[mw[mi][i]][i],j,s[mw[mi][i]][i] ,s[mw[mi+1][i]][i]); */
1.223 brouard 8024:
1.227 brouard 8025: k=k+1;
8026: if (j >= jmax) {
8027: jmax=j;
8028: ijmax=i;
8029: }
8030: else if (j <= jmin){
8031: jmin=j;
8032: ijmin=i;
8033: }
8034: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
8035: /*printf("%d %lf %d %d %d\n", i,agev[mw[mi][i]][i],j,s[mw[mi][i]][i] ,s[mw[mi+1][i]][i]);*/
8036: if(j<0){
8037: nberr++;
1.359 brouard 8038: printf("Error! Negative delay (%d) between waves %d and %d of individual %ld (around line %d) who is aged %.1f with statuses from %d to %d\n ",j,mw[mi][i],mw[mi+1][i],num[i], i,agev[mw[mi][i]][i],s[mw[mi][i]][i] ,s[mw[mi+1][i]][i]);
8039: fprintf(ficlog,"Error! Negative delay (%d) between waves %d and %d of individual %ld (around line %d) who is aged %.1f with statuses from %d to %d\n ",j,mw[mi][i],mw[mi+1][i],num[i], i,agev[mw[mi][i]][i],s[mw[mi][i]][i] ,s[mw[mi+1][i]][i]);
1.227 brouard 8040: }
8041: sum=sum+j;
8042: }
8043: jk= j/stepm;
8044: jl= j -jk*stepm;
8045: ju= j -(jk+1)*stepm;
8046: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
8047: if(jl==0){
8048: dh[mi][i]=jk;
8049: bh[mi][i]=0;
8050: }else{ /* We want a negative bias in order to only have interpolation ie
8051: * to avoid the price of an extra matrix product in likelihood */
8052: dh[mi][i]=jk+1;
8053: bh[mi][i]=ju;
8054: }
8055: }else{
8056: if(jl <= -ju){
8057: dh[mi][i]=jk;
8058: bh[mi][i]=jl; /* bias is positive if real duration
8059: * is higher than the multiple of stepm and negative otherwise.
8060: */
8061: }
8062: else{
8063: dh[mi][i]=jk+1;
8064: bh[mi][i]=ju;
8065: }
8066: if(dh[mi][i]==0){
8067: dh[mi][i]=1; /* At least one step */
8068: bh[mi][i]=ju; /* At least one step */
8069: /* printf(" bh=%d ju=%d jl=%d dh=%d jk=%d stepm=%d %d\n",bh[mi][i],ju,jl,dh[mi][i],jk,stepm,i);*/
8070: }
8071: } /* end if mle */
1.126 brouard 8072: }
8073: } /* end wave */
8074: }
8075: jmean=sum/k;
8076: printf("Delay (in months) between two waves Min=%d (for indiviudal %ld) Max=%d (%ld) Mean=%f\n\n ",jmin, num[ijmin], jmax, num[ijmax], jmean);
1.141 brouard 8077: fprintf(ficlog,"Delay (in months) between two waves Min=%d (for indiviudal %d) Max=%d (%d) Mean=%f\n\n ",jmin, ijmin, jmax, ijmax, jmean);
1.227 brouard 8078: }
1.126 brouard 8079:
8080: /*********** Tricode ****************************/
1.220 brouard 8081: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 8082: {
8083: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
8084: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
8085: * Boring subroutine which should only output nbcode[Tvar[j]][k]
8086: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
8087: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
8088: */
1.130 brouard 8089:
1.242 brouard 8090: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
8091: int modmaxcovj=0; /* Modality max of covariates j */
8092: int cptcode=0; /* Modality max of covariates j */
8093: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 8094:
8095:
1.242 brouard 8096: /* cptcoveff=0; */
8097: /* *cptcov=0; */
1.126 brouard 8098:
1.242 brouard 8099: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 8100: for (k=1; k <= maxncov; k++)
8101: for(j=1; j<=2; j++)
8102: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 8103:
1.242 brouard 8104: /* Loop on covariates without age and products and no quantitative variable */
1.335 brouard 8105: for (k=1; k<=cptcovt; k++) { /* cptcovt: total number of covariates of the model (2) nbocc(+)+1 = 8 excepting constant and age and age*age */
1.242 brouard 8106: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
1.343 brouard 8107: /* printf("Testing k=%d, cptcovt=%d\n",k, cptcovt); */
1.349 brouard 8108: if(Dummy[k]==0 && Typevar[k] !=1 && Typevar[k] != 3 && Typevar[k] != 2){ /* Dummy covariate and not age product nor fixed product */
1.242 brouard 8109: switch(Fixed[k]) {
8110: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
1.311 brouard 8111: modmaxcovj=0;
8112: modmincovj=0;
1.242 brouard 8113: for (i=1; i<=imx; i++) { /* Loop on individuals: reads the data file to get the maximum value of the modality of this covariate Vj*/
1.339 brouard 8114: /* printf("Waiting for error tricode Tvar[%d]=%d i=%d (int)(covar[Tvar[k]][i]=%d\n",k,Tvar[k], i, (int)(covar[Tvar[k]][i])); */
1.242 brouard 8115: ij=(int)(covar[Tvar[k]][i]);
8116: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
8117: * If product of Vn*Vm, still boolean *:
8118: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
8119: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
8120: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
8121: modality of the nth covariate of individual i. */
8122: if (ij > modmaxcovj)
8123: modmaxcovj=ij;
8124: else if (ij < modmincovj)
8125: modmincovj=ij;
1.287 brouard 8126: if (ij <0 || ij >1 ){
1.311 brouard 8127: printf("ERROR, IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
8128: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
8129: fflush(ficlog);
8130: exit(1);
1.287 brouard 8131: }
8132: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 8133: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
8134: exit(1);
8135: }else
8136: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
8137: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
8138: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
8139: /* getting the maximum value of the modality of the covariate
8140: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
8141: female ies 1, then modmaxcovj=1.
8142: */
8143: } /* end for loop on individuals i */
8144: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
8145: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
8146: cptcode=modmaxcovj;
8147: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
8148: /*for (i=0; i<=cptcode; i++) {*/
8149: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
8150: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
8151: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
8152: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
8153: if( j != -1){
8154: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
8155: covariate for which somebody answered excluding
8156: undefined. Usually 2: 0 and 1. */
8157: }
8158: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
8159: covariate for which somebody answered including
8160: undefined. Usually 3: -1, 0 and 1. */
8161: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
8162: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
8163: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 8164:
1.242 brouard 8165: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
8166: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
8167: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
8168: /* modmincovj=3; modmaxcovj = 7; */
8169: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
8170: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
8171: /* defining two dummy variables: variables V1_1 and V1_2.*/
8172: /* nbcode[Tvar[j]][ij]=k; */
8173: /* nbcode[Tvar[j]][1]=0; */
8174: /* nbcode[Tvar[j]][2]=1; */
8175: /* nbcode[Tvar[j]][3]=2; */
8176: /* To be continued (not working yet). */
8177: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 8178:
8179: /* for (i=modmincovj; i<=modmaxcovj; i++) { */ /* i= 1 to 2 for dichotomous, or from 1 to 3 or from -1 or 0 to 1 currently*/
8180: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
8181: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
8182: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
8183: /*, could be restored in the future */
8184: for (i=0; i<=1; i++) { /* i= 1 to 2 for dichotomous, or from 1 to 3 or from -1 or 0 to 1 currently*/
1.242 brouard 8185: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
8186: break;
8187: }
8188: ij++;
1.287 brouard 8189: nbcode[Tvar[k]][ij]=i; /* stores the original value of modality i in an array nbcode, ij modality from 1 to last non-nul modality. nbcode[1][1]=0 nbcode[1][2]=1 . Could be -1*/
1.242 brouard 8190: cptcode = ij; /* New max modality for covar j */
8191: } /* end of loop on modality i=-1 to 1 or more */
8192: break;
8193: case 1: /* Testing on varying covariate, could be simple and
8194: * should look at waves or product of fixed *
8195: * varying. No time to test -1, assuming 0 and 1 only */
8196: ij=0;
8197: for(i=0; i<=1;i++){
8198: nbcode[Tvar[k]][++ij]=i;
8199: }
8200: break;
8201: default:
8202: break;
8203: } /* end switch */
8204: } /* end dummy test */
1.349 brouard 8205: if(Dummy[k]==1 && Typevar[k] !=1 && Typevar[k] !=3 && Fixed ==0){ /* Fixed Quantitative covariate and not age product */
1.311 brouard 8206: for (i=1; i<=imx; i++) { /* Loop on individuals: reads the data file to get the maximum value of the modality of this covariate Vj*/
1.335 brouard 8207: if(Tvar[k]<=0 || Tvar[k]>=NCOVMAX){
8208: printf("Error k=%d \n",k);
8209: exit(1);
8210: }
1.311 brouard 8211: if(isnan(covar[Tvar[k]][i])){
8212: printf("ERROR, IMaCh doesn't treat fixed quantitative covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
8213: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
8214: fflush(ficlog);
8215: exit(1);
8216: }
8217: }
1.335 brouard 8218: } /* end Quanti */
1.287 brouard 8219: } /* end of loop on model-covariate k. nbcode[Tvark][1]=-1, nbcode[Tvark][1]=0 and nbcode[Tvark][2]=1 sets the value of covariate k*/
1.242 brouard 8220:
8221: for (k=-1; k< maxncov; k++) Ndum[k]=0;
8222: /* Look at fixed dummy (single or product) covariates to check empty modalities */
8223: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
8224: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
8225: ij=Tvar[i]; /* Tvar 5,4,3,6,5,7,1,4 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V4*age */
8226: Ndum[ij]++; /* Count the # of 1, 2 etc: {1,1,1,2,2,1,1} because V1 once, V2 once, two V4 and V5 in above */
8227: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
8228: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
8229:
8230: ij=0;
8231: /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */
1.335 brouard 8232: for (k=1; k<= cptcovt; k++) { /* cptcovt: total number of covariates of the model (2) nbocc(+)+1 = 8 excepting constant and age and age*age */
8233: /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
1.242 brouard 8234: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
8235: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
1.335 brouard 8236: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy simple and non empty in the model */
8237: /* Typevar[k] =0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
8238: /* Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product*/
1.242 brouard 8239: /* If product not in single variable we don't print results */
8240: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
1.335 brouard 8241: ++ij;/* V5 + V4 + V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V1, *//* V5 quanti, V2 quanti, V4, V3, V1 dummies */
8242: /* k= 1 2 3 4 5 6 7 8 9 */
8243: /* Tvar[k]= 5 4 3 6 5 2 7 1 1 */
8244: /* ij 1 2 3 */
8245: /* Tvaraff[ij]= 4 3 1 */
8246: /* Tmodelind[ij]=2 3 9 */
8247: /* TmodelInvind[ij]=2 1 1 */
1.242 brouard 8248: Tvaraff[ij]=Tvar[k]; /* For printing combination *//* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, Tvar {5, 4, 3, 6, 5, 2, 7, 1, 1} Tvaraff={4, 3, 1} V4, V3, V1*/
8249: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
8250: TmodelInvind[ij]=Tvar[k]- ncovcol-nqv; /* Inverse TmodelInvind[2=V4]=2 second dummy varying cov (V4)4-1-1 {0, 2, 1, } TmodelInvind[3]=1 */
8251: if(Fixed[k]!=0)
8252: anyvaryingduminmodel=1;
8253: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
8254: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
8255: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
8256: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
8257: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
8258: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
8259: }
8260: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
8261: /* ij--; */
8262: /* cptcoveff=ij; /\*Number of total covariates*\/ */
1.335 brouard 8263: *cptcov=ij; /* cptcov= Number of total real effective simple dummies (fixed or time arying) effective (used as cptcoveff in other functions)
1.242 brouard 8264: * because they can be excluded from the model and real
8265: * if in the model but excluded because missing values, but how to get k from ij?*/
8266: for(j=ij+1; j<= cptcovt; j++){
8267: Tvaraff[j]=0;
8268: Tmodelind[j]=0;
8269: }
8270: for(j=ntveff+1; j<= cptcovt; j++){
8271: TmodelInvind[j]=0;
8272: }
8273: /* To be sorted */
8274: ;
8275: }
1.126 brouard 8276:
1.145 brouard 8277:
1.126 brouard 8278: /*********** Health Expectancies ****************/
8279:
1.235 brouard 8280: void evsij(double ***eij, double x[], int nlstate, int stepm, int bage, int fage, double **oldm, double **savm, int cij, int estepm,char strstart[], int nres )
1.126 brouard 8281:
8282: {
8283: /* Health expectancies, no variances */
1.329 brouard 8284: /* cij is the combination in the list of combination of dummy covariates */
8285: /* strstart is a string of time at start of computing */
1.164 brouard 8286: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 8287: int nhstepma, nstepma; /* Decreasing with age */
8288: double age, agelim, hf;
8289: double ***p3mat;
8290: double eip;
8291:
1.238 brouard 8292: /* pstamp(ficreseij); */
1.126 brouard 8293: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
8294: fprintf(ficreseij,"# Age");
8295: for(i=1; i<=nlstate;i++){
8296: for(j=1; j<=nlstate;j++){
8297: fprintf(ficreseij," e%1d%1d ",i,j);
8298: }
8299: fprintf(ficreseij," e%1d. ",i);
8300: }
8301: fprintf(ficreseij,"\n");
8302:
8303:
8304: if(estepm < stepm){
8305: printf ("Problem %d lower than %d\n",estepm, stepm);
8306: }
8307: else hstepm=estepm;
8308: /* We compute the life expectancy from trapezoids spaced every estepm months
8309: * This is mainly to measure the difference between two models: for example
8310: * if stepm=24 months pijx are given only every 2 years and by summing them
8311: * we are calculating an estimate of the Life Expectancy assuming a linear
8312: * progression in between and thus overestimating or underestimating according
8313: * to the curvature of the survival function. If, for the same date, we
8314: * estimate the model with stepm=1 month, we can keep estepm to 24 months
8315: * to compare the new estimate of Life expectancy with the same linear
8316: * hypothesis. A more precise result, taking into account a more precise
8317: * curvature will be obtained if estepm is as small as stepm. */
8318:
8319: /* For example we decided to compute the life expectancy with the smallest unit */
8320: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
8321: nhstepm is the number of hstepm from age to agelim
8322: nstepm is the number of stepm from age to agelin.
1.270 brouard 8323: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 8324: and note for a fixed period like estepm months */
8325: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
8326: survival function given by stepm (the optimization length). Unfortunately it
8327: means that if the survival funtion is printed only each two years of age and if
8328: you sum them up and add 1 year (area under the trapezoids) you won't get the same
8329: results. So we changed our mind and took the option of the best precision.
8330: */
8331: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
8332:
8333: agelim=AGESUP;
8334: /* If stepm=6 months */
8335: /* Computed by stepm unit matrices, product of hstepm matrices, stored
8336: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
8337:
8338: /* nhstepm age range expressed in number of stepm */
8339: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
8340: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
8341: /* if (stepm >= YEARM) hstepm=1;*/
8342: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
8343: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8344:
8345: for (age=bage; age<=fage; age ++){
8346: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
8347: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
8348: /* if (stepm >= YEARM) hstepm=1;*/
8349: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
8350:
8351: /* If stepm=6 months */
8352: /* Computed by stepm unit matrices, product of hstepma matrices, stored
8353: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
1.330 brouard 8354: /* printf("HELLO evsij Entering hpxij age=%d cij=%d hstepm=%d x[1]=%f nres=%d\n",(int) age, cij, hstepm, x[1], nres); */
1.235 brouard 8355: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 8356:
8357: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
8358:
8359: printf("%d|",(int)age);fflush(stdout);
8360: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
8361:
8362: /* Computing expectancies */
8363: for(i=1; i<=nlstate;i++)
8364: for(j=1; j<=nlstate;j++)
8365: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
8366: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
8367:
8368: /* if((int)age==70)printf("i=%2d,j=%2d,h=%2d,age=%3d,%9.4f,%9.4f,%9.4f\n",i,j,h,(int)age,p3mat[i][j][h],hf,eij[i][j][(int)age]);*/
8369:
8370: }
8371:
8372: fprintf(ficreseij,"%3.0f",age );
8373: for(i=1; i<=nlstate;i++){
8374: eip=0;
8375: for(j=1; j<=nlstate;j++){
8376: eip +=eij[i][j][(int)age];
8377: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
8378: }
8379: fprintf(ficreseij,"%9.4f", eip );
8380: }
8381: fprintf(ficreseij,"\n");
8382:
8383: }
8384: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8385: printf("\n");
8386: fprintf(ficlog,"\n");
8387:
8388: }
8389:
1.235 brouard 8390: void cvevsij(double ***eij, double x[], int nlstate, int stepm, int bage, int fage, double **oldm, double **savm, int cij, int estepm,double delti[],double **matcov,char strstart[], int nres )
1.126 brouard 8391:
8392: {
8393: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 8394: to initial status i, ei. .
1.126 brouard 8395: */
1.336 brouard 8396: /* Very time consuming function, but already optimized with precov */
1.126 brouard 8397: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
8398: int nhstepma, nstepma; /* Decreasing with age */
8399: double age, agelim, hf;
8400: double ***p3matp, ***p3matm, ***varhe;
8401: double **dnewm,**doldm;
8402: double *xp, *xm;
8403: double **gp, **gm;
8404: double ***gradg, ***trgradg;
8405: int theta;
8406:
8407: double eip, vip;
8408:
8409: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
8410: xp=vector(1,npar);
8411: xm=vector(1,npar);
8412: dnewm=matrix(1,nlstate*nlstate,1,npar);
8413: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
8414:
8415: pstamp(ficresstdeij);
8416: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
8417: fprintf(ficresstdeij,"# Age");
8418: for(i=1; i<=nlstate;i++){
8419: for(j=1; j<=nlstate;j++)
8420: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
8421: fprintf(ficresstdeij," e%1d. ",i);
8422: }
8423: fprintf(ficresstdeij,"\n");
8424:
8425: pstamp(ficrescveij);
8426: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
8427: fprintf(ficrescveij,"# Age");
8428: for(i=1; i<=nlstate;i++)
8429: for(j=1; j<=nlstate;j++){
8430: cptj= (j-1)*nlstate+i;
8431: for(i2=1; i2<=nlstate;i2++)
8432: for(j2=1; j2<=nlstate;j2++){
8433: cptj2= (j2-1)*nlstate+i2;
8434: if(cptj2 <= cptj)
8435: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
8436: }
8437: }
8438: fprintf(ficrescveij,"\n");
8439:
8440: if(estepm < stepm){
8441: printf ("Problem %d lower than %d\n",estepm, stepm);
8442: }
8443: else hstepm=estepm;
8444: /* We compute the life expectancy from trapezoids spaced every estepm months
8445: * This is mainly to measure the difference between two models: for example
8446: * if stepm=24 months pijx are given only every 2 years and by summing them
8447: * we are calculating an estimate of the Life Expectancy assuming a linear
8448: * progression in between and thus overestimating or underestimating according
8449: * to the curvature of the survival function. If, for the same date, we
8450: * estimate the model with stepm=1 month, we can keep estepm to 24 months
8451: * to compare the new estimate of Life expectancy with the same linear
8452: * hypothesis. A more precise result, taking into account a more precise
8453: * curvature will be obtained if estepm is as small as stepm. */
8454:
8455: /* For example we decided to compute the life expectancy with the smallest unit */
8456: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
8457: nhstepm is the number of hstepm from age to agelim
8458: nstepm is the number of stepm from age to agelin.
8459: Look at hpijx to understand the reason of that which relies in memory size
8460: and note for a fixed period like estepm months */
8461: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
8462: survival function given by stepm (the optimization length). Unfortunately it
8463: means that if the survival funtion is printed only each two years of age and if
8464: you sum them up and add 1 year (area under the trapezoids) you won't get the same
8465: results. So we changed our mind and took the option of the best precision.
8466: */
8467: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
8468:
8469: /* If stepm=6 months */
8470: /* nhstepm age range expressed in number of stepm */
8471: agelim=AGESUP;
8472: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
8473: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
8474: /* if (stepm >= YEARM) hstepm=1;*/
8475: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
8476:
8477: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8478: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8479: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
8480: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
8481: gp=matrix(0,nhstepm,1,nlstate*nlstate);
8482: gm=matrix(0,nhstepm,1,nlstate*nlstate);
8483:
8484: for (age=bage; age<=fage; age ++){
8485: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
8486: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
8487: /* if (stepm >= YEARM) hstepm=1;*/
8488: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 8489:
1.126 brouard 8490: /* If stepm=6 months */
8491: /* Computed by stepm unit matrices, product of hstepma matrices, stored
8492: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
8493:
8494: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 8495:
1.126 brouard 8496: /* Computing Variances of health expectancies */
8497: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
8498: decrease memory allocation */
8499: for(theta=1; theta <=npar; theta++){
8500: for(i=1; i<=npar; i++){
1.222 brouard 8501: xp[i] = x[i] + (i==theta ?delti[theta]:0);
8502: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 8503: }
1.235 brouard 8504: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
8505: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 8506:
1.126 brouard 8507: for(j=1; j<= nlstate; j++){
1.222 brouard 8508: for(i=1; i<=nlstate; i++){
8509: for(h=0; h<=nhstepm-1; h++){
8510: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
8511: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
8512: }
8513: }
1.126 brouard 8514: }
1.218 brouard 8515:
1.126 brouard 8516: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 8517: for(h=0; h<=nhstepm-1; h++){
8518: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
8519: }
1.126 brouard 8520: }/* End theta */
8521:
8522:
8523: for(h=0; h<=nhstepm-1; h++)
8524: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 8525: for(theta=1; theta <=npar; theta++)
8526: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 8527:
1.218 brouard 8528:
1.222 brouard 8529: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 8530: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 8531: varhe[ij][ji][(int)age] =0.;
1.218 brouard 8532:
1.222 brouard 8533: printf("%d|",(int)age);fflush(stdout);
8534: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
8535: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 8536: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 8537: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
8538: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
8539: for(ij=1;ij<=nlstate*nlstate;ij++)
8540: for(ji=1;ji<=nlstate*nlstate;ji++)
8541: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 8542: }
8543: }
1.320 brouard 8544: /* if((int)age ==50){ */
8545: /* printf(" age=%d cij=%d nres=%d varhe[%d][%d]=%f ",(int)age, cij, nres, 1,2,varhe[1][2]); */
8546: /* } */
1.126 brouard 8547: /* Computing expectancies */
1.235 brouard 8548: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 8549: for(i=1; i<=nlstate;i++)
8550: for(j=1; j<=nlstate;j++)
1.222 brouard 8551: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
8552: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 8553:
1.222 brouard 8554: /* if((int)age==70)printf("i=%2d,j=%2d,h=%2d,age=%3d,%9.4f,%9.4f,%9.4f\n",i,j,h,(int)age,p3mat[i][j][h],hf,eij[i][j][(int)age]);*/
1.218 brouard 8555:
1.222 brouard 8556: }
1.269 brouard 8557:
8558: /* Standard deviation of expectancies ij */
1.126 brouard 8559: fprintf(ficresstdeij,"%3.0f",age );
8560: for(i=1; i<=nlstate;i++){
8561: eip=0.;
8562: vip=0.;
8563: for(j=1; j<=nlstate;j++){
1.222 brouard 8564: eip += eij[i][j][(int)age];
8565: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
8566: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
8567: fprintf(ficresstdeij," %9.4f (%.4f)", eij[i][j][(int)age], sqrt(varhe[(j-1)*nlstate+i][(j-1)*nlstate+i][(int)age]) );
1.126 brouard 8568: }
8569: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
8570: }
8571: fprintf(ficresstdeij,"\n");
1.218 brouard 8572:
1.269 brouard 8573: /* Variance of expectancies ij */
1.126 brouard 8574: fprintf(ficrescveij,"%3.0f",age );
8575: for(i=1; i<=nlstate;i++)
8576: for(j=1; j<=nlstate;j++){
1.222 brouard 8577: cptj= (j-1)*nlstate+i;
8578: for(i2=1; i2<=nlstate;i2++)
8579: for(j2=1; j2<=nlstate;j2++){
8580: cptj2= (j2-1)*nlstate+i2;
8581: if(cptj2 <= cptj)
8582: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
8583: }
1.126 brouard 8584: }
8585: fprintf(ficrescveij,"\n");
1.218 brouard 8586:
1.126 brouard 8587: }
8588: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
8589: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
8590: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
8591: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
8592: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8593: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8594: printf("\n");
8595: fprintf(ficlog,"\n");
1.218 brouard 8596:
1.126 brouard 8597: free_vector(xm,1,npar);
8598: free_vector(xp,1,npar);
8599: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
8600: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
8601: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
8602: }
1.218 brouard 8603:
1.126 brouard 8604: /************ Variance ******************/
1.235 brouard 8605: void varevsij(char optionfilefiname[], double ***vareij, double **matcov, double x[], double delti[], int nlstate, int stepm, double bage, double fage, double **oldm, double **savm, double **prlim, double ftolpl, int *ncvyearp, int ij, int estepm, int cptcov, int cptcod, int popbased, int mobilav, char strstart[], int nres)
1.218 brouard 8606: {
1.361 brouard 8607: /** Computes the matrix of variance covariance of health expectancies e.j= sum_i w_i e_ij where w_i depends of popbased,
8608: * either cross-sectional or implied.
8609: * return vareij[i][j][(int)age]=cov(e.i,e.j)=sum_h sum_k trgrad(h_p.i) V(theta) grad(k_p.k) Equation 20
1.279 brouard 8610: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
8611: * double **newm;
8612: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
8613: */
1.218 brouard 8614:
8615: /* int movingaverage(); */
8616: double **dnewm,**doldm;
8617: double **dnewmp,**doldmp;
8618: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 8619: int first=0;
1.218 brouard 8620: int k;
8621: double *xp;
1.279 brouard 8622: double **gp, **gm; /**< for var eij */
8623: double ***gradg, ***trgradg; /**< for var eij */
8624: double **gradgp, **trgradgp; /**< for var p point j */
8625: double *gpp, *gmp; /**< for var p point j */
1.362 brouard 8626: double **varppt; /**< for var p.3 p.death nlstate+1 to nlstate+ndeath */
1.218 brouard 8627: double ***p3mat;
8628: double age,agelim, hf;
8629: /* double ***mobaverage; */
8630: int theta;
8631: char digit[4];
8632: char digitp[25];
8633:
8634: char fileresprobmorprev[FILENAMELENGTH];
8635:
8636: if(popbased==1){
8637: if(mobilav!=0)
8638: strcpy(digitp,"-POPULBASED-MOBILAV_");
8639: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
8640: }
8641: else
8642: strcpy(digitp,"-STABLBASED_");
1.126 brouard 8643:
1.218 brouard 8644: /* if (mobilav!=0) { */
8645: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8646: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
8647: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
8648: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
8649: /* } */
8650: /* } */
8651:
8652: strcpy(fileresprobmorprev,"PRMORPREV-");
8653: sprintf(digit,"%-d",ij);
8654: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
8655: strcat(fileresprobmorprev,digit); /* Tvar to be done */
8656: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
8657: strcat(fileresprobmorprev,fileresu);
8658: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
8659: printf("Problem with resultfile: %s\n", fileresprobmorprev);
8660: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
8661: }
8662: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
8663: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
8664: pstamp(ficresprobmorprev);
8665: fprintf(ficresprobmorprev,"# probabilities of dying before estepm=%d months for people of exact age and weighted probabilities w1*p1j+w2*p2j+... stand dev in()\n",estepm);
1.238 brouard 8666: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
1.337 brouard 8667:
8668: /* We use TinvDoQresult[nres][resultmodel[nres][j] we sort according to the equation model and the resultline: it is a choice */
8669: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ /\* To be done*\/ */
8670: /* fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
8671: /* } */
8672: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */ /* To be done*/
1.344 brouard 8673: /* fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); */
1.337 brouard 8674: fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 8675: }
1.337 brouard 8676: /* for(j=1;j<=cptcoveff;j++) */
8677: /* fprintf(ficresprobmorprev," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,TnsdVar[Tvaraff[j]])]); */
1.238 brouard 8678: fprintf(ficresprobmorprev,"\n");
8679:
1.218 brouard 8680: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
8681: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
8682: fprintf(ficresprobmorprev," p.%-d SE",j);
8683: for(i=1; i<=nlstate;i++)
8684: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
8685: }
8686: fprintf(ficresprobmorprev,"\n");
8687:
8688: fprintf(ficgp,"\n# Routine varevsij");
8689: fprintf(ficgp,"\nunset title \n");
8690: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
8691: fprintf(fichtm,"\n<li><h4> Computing probabilities of dying over estepm months as a weighted average (i.e global mortality independent of initial healh state)</h4></li>\n");
8692: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 8693:
1.361 brouard 8694: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath); /* In fact, currently a double */
1.218 brouard 8695: pstamp(ficresvij);
8696: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
8697: if(popbased==1)
8698: fprintf(ficresvij,"the age specific prevalence observed (cross-sectionally) in the population i.e cross-sectionally\n in each health state (popbased=1) (mobilav=%d\n",mobilav);
8699: else
8700: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
8701: fprintf(ficresvij,"# Age");
8702: for(i=1; i<=nlstate;i++)
8703: for(j=1; j<=nlstate;j++)
8704: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
8705: fprintf(ficresvij,"\n");
8706:
8707: xp=vector(1,npar);
8708: dnewm=matrix(1,nlstate,1,npar);
8709: doldm=matrix(1,nlstate,1,nlstate);
8710: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
8711: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
8712:
8713: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
8714: gpp=vector(nlstate+1,nlstate+ndeath);
8715: gmp=vector(nlstate+1,nlstate+ndeath);
8716: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 8717:
1.218 brouard 8718: if(estepm < stepm){
8719: printf ("Problem %d lower than %d\n",estepm, stepm);
8720: }
8721: else hstepm=estepm;
8722: /* For example we decided to compute the life expectancy with the smallest unit */
8723: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
8724: nhstepm is the number of hstepm from age to agelim
8725: nstepm is the number of stepm from age to agelim.
8726: Look at function hpijx to understand why because of memory size limitations,
8727: we decided (b) to get a life expectancy respecting the most precise curvature of the
8728: survival function given by stepm (the optimization length). Unfortunately it
8729: means that if the survival funtion is printed every two years of age and if
8730: you sum them up and add 1 year (area under the trapezoids) you won't get the same
8731: results. So we changed our mind and took the option of the best precision.
8732: */
8733: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
8734: agelim = AGESUP;
8735: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
8736: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
8737: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
8738: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8739: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
8740: gp=matrix(0,nhstepm,1,nlstate);
8741: gm=matrix(0,nhstepm,1,nlstate);
8742:
8743:
8744: for(theta=1; theta <=npar; theta++){
8745: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
8746: xp[i] = x[i] + (i==theta ?delti[theta]:0);
8747: }
1.279 brouard 8748: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
8749: * returns into prlim .
1.288 brouard 8750: */
1.242 brouard 8751: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 8752:
8753: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 8754: if (popbased==1) {
8755: if(mobilav ==0){
8756: for(i=1; i<=nlstate;i++)
8757: prlim[i][i]=probs[(int)age][i][ij];
8758: }else{ /* mobilav */
8759: for(i=1; i<=nlstate;i++)
8760: prlim[i][i]=mobaverage[(int)age][i][ij];
8761: }
8762: }
1.361 brouard 8763: /**< Computes the shifted plus (gp) transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h.
1.279 brouard 8764: */
8765: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres); /* Returns p3mat[i][j][h] for h=0 to nhstepm */
1.292 brouard 8766: /**< And for each alive state j, sums over i \f$ w^i_x {}{h}_p^{ij}x\f$, which are the probability
1.279 brouard 8767: * at horizon h in state j including mortality.
8768: */
1.218 brouard 8769: for(j=1; j<= nlstate; j++){
8770: for(h=0; h<=nhstepm; h++){
8771: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
1.361 brouard 8772: gp[h][j] += prlim[i][i]*p3mat[i][j][h]; /* gp[h][j]= w_i h_pij */
1.218 brouard 8773: }
8774: }
1.279 brouard 8775: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 8776: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 8777: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 8778: */
1.361 brouard 8779: for(j=nlstate+1;j<=nlstate+ndeath;j++){ /* Currently only once for theta plus p.3(age) Sum_i wi pi3*/
1.218 brouard 8780: for(i=1,gpp[j]=0.; i<= nlstate; i++)
8781: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 8782: }
8783:
8784: /* Again with minus shift */
1.218 brouard 8785:
8786: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
8787: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 8788:
1.242 brouard 8789: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 8790:
8791: if (popbased==1) {
8792: if(mobilav ==0){
8793: for(i=1; i<=nlstate;i++)
8794: prlim[i][i]=probs[(int)age][i][ij];
8795: }else{ /* mobilav */
8796: for(i=1; i<=nlstate;i++)
8797: prlim[i][i]=mobaverage[(int)age][i][ij];
8798: }
8799: }
8800:
1.361 brouard 8801: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres); /* Still minus */
1.218 brouard 8802:
1.361 brouard 8803: for(j=1; j<= nlstate; j++){ /* gm[h][j]= Sum_i of wi * pij = h_p.j */
1.218 brouard 8804: for(h=0; h<=nhstepm; h++){
8805: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
8806: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
8807: }
8808: }
8809: /* This for computing probability of death (h=1 means
8810: computed over hstepm matrices product = hstepm*stepm months)
1.361 brouard 8811: as a weighted average of prlim. j is death. gmp[3]=sum_i w_i*p_i3=p.3 minus theta
1.218 brouard 8812: */
1.361 brouard 8813: for(j=nlstate+1;j<=nlstate+ndeath;j++){ /* Currently only once theta_minus p.3=Sum_i wi pi3*/
1.218 brouard 8814: for(i=1,gmp[j]=0.; i<= nlstate; i++)
8815: gmp[j] += prlim[i][i]*p3mat[i][j][1];
8816: }
1.279 brouard 8817: /* end shifting computations */
8818:
1.361 brouard 8819: /**< Computing gradient of p.j matrix at horizon h and still for one parameter of vector theta
8820: * equation 31 and 32
1.279 brouard 8821: */
1.361 brouard 8822: for(j=1; j<= nlstate; j++) /* computes grad p.j(x, over each h) where p.j is Sum_i w_i*pij(x over h)
8823: * equation 24 */
1.218 brouard 8824: for(h=0; h<=nhstepm; h++){
8825: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
8826: }
1.361 brouard 8827: /**< Gradient of overall mortality p.3 (or p.death)
1.279 brouard 8828: */
1.361 brouard 8829: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* computes grad of p.3 from wi+pi3 grad p.3 (theta) */
1.218 brouard 8830: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
8831: }
8832:
8833: } /* End theta */
1.279 brouard 8834:
1.361 brouard 8835: /* We got the gradient matrix for each theta and each state j of gradg(h]theta][j)=grad(_hp.j(theta) */
8836: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar);
1.218 brouard 8837:
1.361 brouard 8838: for(h=0; h<=nhstepm; h++) /* veij */ /* computes the transposed of grad (_hp.j(theta)*/
1.218 brouard 8839: for(j=1; j<=nlstate;j++)
8840: for(theta=1; theta <=npar; theta++)
8841: trgradg[h][j][theta]=gradg[h][theta][j];
8842:
1.361 brouard 8843: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* computes transposed of grad p.3 (theta)*/
1.218 brouard 8844: for(theta=1; theta <=npar; theta++)
8845: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 8846: /**< as well as its transposed matrix
8847: */
1.218 brouard 8848:
8849: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
8850: for(i=1;i<=nlstate;i++)
8851: for(j=1;j<=nlstate;j++)
8852: vareij[i][j][(int)age] =0.;
1.279 brouard 8853:
8854: /* Computing trgradg by matcov by gradg at age and summing over h
1.361 brouard 8855: * and k (nhstepm) formula 32 of article
8856: * Lievre-Brouard-Heathcote so that for each j, computes the cov(e.j,e.k) (formula 31).
8857: * for given h and k computes trgradg[h](i,j) matcov (theta) gradg(k)(i,j) into vareij[i][j] which is
8858: cov(e.i,e.j) and sums on h and k
8859: * including the covariances.
1.279 brouard 8860: */
8861:
1.218 brouard 8862: for(h=0;h<=nhstepm;h++){
8863: for(k=0;k<=nhstepm;k++){
8864: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
8865: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
8866: for(i=1;i<=nlstate;i++)
8867: for(j=1;j<=nlstate;j++)
1.361 brouard 8868: vareij[i][j][(int)age] += doldm[i][j]*hf*hf; /* This is vareij=sum_h sum_k trgrad(h_pij) V(theta) grad(k_pij)
8869: including the covariances of e.j */
1.218 brouard 8870: }
8871: }
8872:
1.361 brouard 8873: /* Mortality: pptj is p.3 or p.death = trgradgp by cov by gradgp, variance of
8874: * p.3=1-p..=1-sum i p.i overall mortality computed directly because
1.279 brouard 8875: * we compute the grad (wix pijx) instead of grad (pijx),even if
1.361 brouard 8876: * wix is independent of theta.
1.279 brouard 8877: */
1.218 brouard 8878: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
8879: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
8880: for(j=nlstate+1;j<=nlstate+ndeath;j++)
8881: for(i=nlstate+1;i<=nlstate+ndeath;i++)
1.361 brouard 8882: varppt[j][i]=doldmp[j][i]; /* This is the variance of p.3 */
1.218 brouard 8883: /* end ppptj */
8884: /* x centered again */
8885:
1.242 brouard 8886: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 8887:
8888: if (popbased==1) {
8889: if(mobilav ==0){
8890: for(i=1; i<=nlstate;i++)
8891: prlim[i][i]=probs[(int)age][i][ij];
8892: }else{ /* mobilav */
8893: for(i=1; i<=nlstate;i++)
8894: prlim[i][i]=mobaverage[(int)age][i][ij];
8895: }
8896: }
8897:
8898: /* This for computing probability of death (h=1 means
8899: computed over hstepm (estepm) matrices product = hstepm*stepm months)
8900: as a weighted average of prlim.
8901: */
1.235 brouard 8902: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 8903: for(j=nlstate+1;j<=nlstate+ndeath;j++){
8904: for(i=1,gmp[j]=0.;i<= nlstate; i++)
1.361 brouard 8905: gmp[j] += prlim[i][i]*p3mat[i][j][1]; /* gmp[j] is p.3 */
1.218 brouard 8906: }
8907: /* end probability of death */
8908:
8909: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
8910: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
1.361 brouard 8911: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));/* p.3 (STD p.3) */
1.218 brouard 8912: for(i=1; i<=nlstate;i++){
1.361 brouard 8913: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]); /* wi, pi3 */
1.218 brouard 8914: }
8915: }
8916: fprintf(ficresprobmorprev,"\n");
8917:
8918: fprintf(ficresvij,"%.0f ",age );
8919: for(i=1; i<=nlstate;i++)
8920: for(j=1; j<=nlstate;j++){
8921: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
8922: }
8923: fprintf(ficresvij,"\n");
8924: free_matrix(gp,0,nhstepm,1,nlstate);
8925: free_matrix(gm,0,nhstepm,1,nlstate);
8926: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
8927: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
8928: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8929: } /* End age */
8930: free_vector(gpp,nlstate+1,nlstate+ndeath);
8931: free_vector(gmp,nlstate+1,nlstate+ndeath);
8932: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
8933: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
8934: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
8935: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
8936: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
8937: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
8938: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
8939: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
8940: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
8941: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
8942: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
8943: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
8944: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
8945: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
8946: fprintf(fichtm,"\n<br> Probability is computed over estepm=%d months. <br> <img src=\"%s%s.svg\"> <br>\n", estepm,subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
8947: /* fprintf(fichtm,"\n<br> Probability is computed over estepm=%d months and then divided by estepm and multiplied by %.0f in order to have the probability to die over a year <br> <img src=\"varmuptjgr%s%s.svg\"> <br>\n", stepm,YEARM,digitp,digit);
1.126 brouard 8948: */
1.218 brouard 8949: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
8950: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 8951:
1.218 brouard 8952: free_vector(xp,1,npar);
8953: free_matrix(doldm,1,nlstate,1,nlstate);
8954: free_matrix(dnewm,1,nlstate,1,npar);
8955: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
8956: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
8957: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
8958: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8959: fclose(ficresprobmorprev);
8960: fflush(ficgp);
8961: fflush(fichtm);
8962: } /* end varevsij */
1.126 brouard 8963:
8964: /************ Variance of prevlim ******************/
1.269 brouard 8965: void varprevlim(char fileresvpl[], FILE *ficresvpl, double **varpl, double **matcov, double x[], double delti[], int nlstate, int stepm, double bage, double fage, double **oldm, double **savm, double **prlim, double ftolpl, int *ncvyearp, int ij, char strstart[], int nres)
1.126 brouard 8966: {
1.205 brouard 8967: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 8968: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 8969:
1.268 brouard 8970: double **dnewmpar,**doldm;
1.126 brouard 8971: int i, j, nhstepm, hstepm;
8972: double *xp;
8973: double *gp, *gm;
8974: double **gradg, **trgradg;
1.208 brouard 8975: double **mgm, **mgp;
1.126 brouard 8976: double age,agelim;
8977: int theta;
8978:
8979: pstamp(ficresvpl);
1.288 brouard 8980: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 8981: fprintf(ficresvpl,"# Age ");
8982: if(nresult >=1)
8983: fprintf(ficresvpl," Result# ");
1.126 brouard 8984: for(i=1; i<=nlstate;i++)
8985: fprintf(ficresvpl," %1d-%1d",i,i);
8986: fprintf(ficresvpl,"\n");
8987:
8988: xp=vector(1,npar);
1.268 brouard 8989: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 8990: doldm=matrix(1,nlstate,1,nlstate);
8991:
8992: hstepm=1*YEARM; /* Every year of age */
8993: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
8994: agelim = AGESUP;
8995: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
8996: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
8997: if (stepm >= YEARM) hstepm=1;
8998: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
8999: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 9000: mgp=matrix(1,npar,1,nlstate);
9001: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 9002: gp=vector(1,nlstate);
9003: gm=vector(1,nlstate);
9004:
9005: for(theta=1; theta <=npar; theta++){
9006: for(i=1; i<=npar; i++){ /* Computes gradient */
9007: xp[i] = x[i] + (i==theta ?delti[theta]:0);
9008: }
1.288 brouard 9009: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
9010: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
9011: /* else */
9012: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 9013: for(i=1;i<=nlstate;i++){
1.126 brouard 9014: gp[i] = prlim[i][i];
1.208 brouard 9015: mgp[theta][i] = prlim[i][i];
9016: }
1.126 brouard 9017: for(i=1; i<=npar; i++) /* Computes gradient */
9018: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 9019: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
9020: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
9021: /* else */
9022: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 9023: for(i=1;i<=nlstate;i++){
1.126 brouard 9024: gm[i] = prlim[i][i];
1.208 brouard 9025: mgm[theta][i] = prlim[i][i];
9026: }
1.126 brouard 9027: for(i=1;i<=nlstate;i++)
9028: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 9029: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 9030: } /* End theta */
9031:
9032: trgradg =matrix(1,nlstate,1,npar);
9033:
9034: for(j=1; j<=nlstate;j++)
9035: for(theta=1; theta <=npar; theta++)
9036: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 9037: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
9038: /* printf("\nmgm mgp %d ",(int)age); */
9039: /* for(j=1; j<=nlstate;j++){ */
9040: /* printf(" %d ",j); */
9041: /* for(theta=1; theta <=npar; theta++) */
9042: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
9043: /* printf("\n "); */
9044: /* } */
9045: /* } */
9046: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
9047: /* printf("\n gradg %d ",(int)age); */
9048: /* for(j=1; j<=nlstate;j++){ */
9049: /* printf("%d ",j); */
9050: /* for(theta=1; theta <=npar; theta++) */
9051: /* printf("%d %lf ",theta,gradg[theta][j]); */
9052: /* printf("\n "); */
9053: /* } */
9054: /* } */
1.126 brouard 9055:
9056: for(i=1;i<=nlstate;i++)
9057: varpl[i][(int)age] =0.;
1.209 brouard 9058: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 9059: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
9060: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 9061: }else{
1.268 brouard 9062: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
9063: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 9064: }
1.126 brouard 9065: for(i=1;i<=nlstate;i++)
9066: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
9067:
9068: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 9069: if(nresult >=1)
9070: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 9071: for(i=1; i<=nlstate;i++){
1.126 brouard 9072: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 9073: /* for(j=1;j<=nlstate;j++) */
9074: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
9075: }
1.126 brouard 9076: fprintf(ficresvpl,"\n");
9077: free_vector(gp,1,nlstate);
9078: free_vector(gm,1,nlstate);
1.208 brouard 9079: free_matrix(mgm,1,npar,1,nlstate);
9080: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 9081: free_matrix(gradg,1,npar,1,nlstate);
9082: free_matrix(trgradg,1,nlstate,1,npar);
9083: } /* End age */
9084:
9085: free_vector(xp,1,npar);
9086: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 9087: free_matrix(dnewmpar,1,nlstate,1,nlstate);
9088:
9089: }
9090:
9091:
9092: /************ Variance of backprevalence limit ******************/
1.269 brouard 9093: void varbrevlim(char fileresvbl[], FILE *ficresvbl, double **varbpl, double **matcov, double x[], double delti[], int nlstate, int stepm, double bage, double fage, double **oldm, double **savm, double **bprlim, double ftolpl, int mobilavproj, int *ncvyearp, int ij, char strstart[], int nres)
1.268 brouard 9094: {
9095: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
9096: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
9097:
9098: double **dnewmpar,**doldm;
9099: int i, j, nhstepm, hstepm;
9100: double *xp;
9101: double *gp, *gm;
9102: double **gradg, **trgradg;
9103: double **mgm, **mgp;
9104: double age,agelim;
9105: int theta;
9106:
9107: pstamp(ficresvbl);
9108: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
9109: fprintf(ficresvbl,"# Age ");
9110: if(nresult >=1)
9111: fprintf(ficresvbl," Result# ");
9112: for(i=1; i<=nlstate;i++)
9113: fprintf(ficresvbl," %1d-%1d",i,i);
9114: fprintf(ficresvbl,"\n");
9115:
9116: xp=vector(1,npar);
9117: dnewmpar=matrix(1,nlstate,1,npar);
9118: doldm=matrix(1,nlstate,1,nlstate);
9119:
9120: hstepm=1*YEARM; /* Every year of age */
9121: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
9122: agelim = AGEINF;
9123: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
9124: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
9125: if (stepm >= YEARM) hstepm=1;
9126: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
9127: gradg=matrix(1,npar,1,nlstate);
9128: mgp=matrix(1,npar,1,nlstate);
9129: mgm=matrix(1,npar,1,nlstate);
9130: gp=vector(1,nlstate);
9131: gm=vector(1,nlstate);
9132:
9133: for(theta=1; theta <=npar; theta++){
9134: for(i=1; i<=npar; i++){ /* Computes gradient */
9135: xp[i] = x[i] + (i==theta ?delti[theta]:0);
9136: }
9137: if(mobilavproj > 0 )
9138: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
9139: else
9140: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
9141: for(i=1;i<=nlstate;i++){
9142: gp[i] = bprlim[i][i];
9143: mgp[theta][i] = bprlim[i][i];
9144: }
9145: for(i=1; i<=npar; i++) /* Computes gradient */
9146: xp[i] = x[i] - (i==theta ?delti[theta]:0);
9147: if(mobilavproj > 0 )
9148: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
9149: else
9150: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
9151: for(i=1;i<=nlstate;i++){
9152: gm[i] = bprlim[i][i];
9153: mgm[theta][i] = bprlim[i][i];
9154: }
9155: for(i=1;i<=nlstate;i++)
9156: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
9157: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
9158: } /* End theta */
9159:
9160: trgradg =matrix(1,nlstate,1,npar);
9161:
9162: for(j=1; j<=nlstate;j++)
9163: for(theta=1; theta <=npar; theta++)
9164: trgradg[j][theta]=gradg[theta][j];
9165: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
9166: /* printf("\nmgm mgp %d ",(int)age); */
9167: /* for(j=1; j<=nlstate;j++){ */
9168: /* printf(" %d ",j); */
9169: /* for(theta=1; theta <=npar; theta++) */
9170: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
9171: /* printf("\n "); */
9172: /* } */
9173: /* } */
9174: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
9175: /* printf("\n gradg %d ",(int)age); */
9176: /* for(j=1; j<=nlstate;j++){ */
9177: /* printf("%d ",j); */
9178: /* for(theta=1; theta <=npar; theta++) */
9179: /* printf("%d %lf ",theta,gradg[theta][j]); */
9180: /* printf("\n "); */
9181: /* } */
9182: /* } */
9183:
9184: for(i=1;i<=nlstate;i++)
9185: varbpl[i][(int)age] =0.;
9186: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
9187: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
9188: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
9189: }else{
9190: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
9191: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
9192: }
9193: for(i=1;i<=nlstate;i++)
9194: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
9195:
9196: fprintf(ficresvbl,"%.0f ",age );
9197: if(nresult >=1)
9198: fprintf(ficresvbl,"%d ",nres );
9199: for(i=1; i<=nlstate;i++)
9200: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
9201: fprintf(ficresvbl,"\n");
9202: free_vector(gp,1,nlstate);
9203: free_vector(gm,1,nlstate);
9204: free_matrix(mgm,1,npar,1,nlstate);
9205: free_matrix(mgp,1,npar,1,nlstate);
9206: free_matrix(gradg,1,npar,1,nlstate);
9207: free_matrix(trgradg,1,nlstate,1,npar);
9208: } /* End age */
9209:
9210: free_vector(xp,1,npar);
9211: free_matrix(doldm,1,nlstate,1,npar);
9212: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 9213:
9214: }
9215:
9216: /************ Variance of one-step probabilities ******************/
9217: void varprob(char optionfilefiname[], double **matcov, double x[], double delti[], int nlstate, double bage, double fage, int ij, int *Tvar, int **nbcode, int *ncodemax, char strstart[])
1.222 brouard 9218: {
9219: int i, j=0, k1, l1, tj;
9220: int k2, l2, j1, z1;
9221: int k=0, l;
9222: int first=1, first1, first2;
1.326 brouard 9223: int nres=0; /* New */
1.222 brouard 9224: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
9225: double **dnewm,**doldm;
9226: double *xp;
9227: double *gp, *gm;
9228: double **gradg, **trgradg;
9229: double **mu;
9230: double age, cov[NCOVMAX+1];
9231: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
9232: int theta;
9233: char fileresprob[FILENAMELENGTH];
9234: char fileresprobcov[FILENAMELENGTH];
9235: char fileresprobcor[FILENAMELENGTH];
9236: double ***varpij;
9237:
9238: strcpy(fileresprob,"PROB_");
1.356 brouard 9239: strcat(fileresprob,fileresu);
1.222 brouard 9240: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
9241: printf("Problem with resultfile: %s\n", fileresprob);
9242: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
9243: }
9244: strcpy(fileresprobcov,"PROBCOV_");
9245: strcat(fileresprobcov,fileresu);
9246: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
9247: printf("Problem with resultfile: %s\n", fileresprobcov);
9248: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
9249: }
9250: strcpy(fileresprobcor,"PROBCOR_");
9251: strcat(fileresprobcor,fileresu);
9252: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
9253: printf("Problem with resultfile: %s\n", fileresprobcor);
9254: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
9255: }
9256: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
9257: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
9258: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
9259: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
9260: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
9261: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
9262: pstamp(ficresprob);
9263: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
9264: fprintf(ficresprob,"# Age");
9265: pstamp(ficresprobcov);
9266: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
9267: fprintf(ficresprobcov,"# Age");
9268: pstamp(ficresprobcor);
9269: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
9270: fprintf(ficresprobcor,"# Age");
1.126 brouard 9271:
9272:
1.222 brouard 9273: for(i=1; i<=nlstate;i++)
9274: for(j=1; j<=(nlstate+ndeath);j++){
9275: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
9276: fprintf(ficresprobcov," p%1d-%1d ",i,j);
9277: fprintf(ficresprobcor," p%1d-%1d ",i,j);
9278: }
9279: /* fprintf(ficresprob,"\n");
9280: fprintf(ficresprobcov,"\n");
9281: fprintf(ficresprobcor,"\n");
9282: */
9283: xp=vector(1,npar);
9284: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
9285: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
9286: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
9287: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
9288: first=1;
9289: fprintf(ficgp,"\n# Routine varprob");
9290: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
9291: fprintf(fichtm,"\n");
9292:
1.288 brouard 9293: fprintf(fichtm,"\n<li><h4> <a href=\"%s\">Matrix of variance-covariance of one-step probabilities (drawings)</a></h4> this page is important in order to visualize confidence intervals and especially correlation between disability and recovery, or more generally, way in and way back. File %s</li>\n",optionfilehtmcov,optionfilehtmcov);
1.222 brouard 9294: fprintf(fichtmcov,"Current page is file <a href=\"%s\">%s</a><br>\n\n<h4>Matrix of variance-covariance of pairs of step probabilities</h4>\n",optionfilehtmcov, optionfilehtmcov);
9295: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 9296: and drawn. It helps understanding how is the covariance between two incidences.\
9297: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 9298: fprintf(fichtmcov,"\n<br> Contour plot corresponding to x'cov<sup>-1</sup>x = 4 (where x is the column vector (pij,pkl)) are drawn. \
1.126 brouard 9299: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
9300: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
9301: standard deviations wide on each axis. <br>\
9302: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
9303: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
9304: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
9305:
1.222 brouard 9306: cov[1]=1;
9307: /* tj=cptcoveff; */
1.225 brouard 9308: tj = (int) pow(2,cptcoveff);
1.222 brouard 9309: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
9310: j1=0;
1.332 brouard 9311:
9312: for(nres=1;nres <=nresult; nres++){ /* For each resultline */
9313: for(j1=1; j1<=tj;j1++){ /* For any combination of dummy covariates, fixed and varying */
1.342 brouard 9314: /* printf("Varprob TKresult[nres]=%d j1=%d, nres=%d, cptcovn=%d, cptcoveff=%d tj=%d cptcovs=%d\n", TKresult[nres], j1, nres, cptcovn, cptcoveff, tj, cptcovs); */
1.332 brouard 9315: if(tj != 1 && TKresult[nres]!= j1)
9316: continue;
9317:
9318: /* for(j1=1; j1<=tj;j1++){ /\* For each valid combination of covariates or only once*\/ */
9319: /* for(nres=1;nres <=1; nres++){ /\* For each resultline *\/ */
9320: /* /\* for(nres=1;nres <=nresult; nres++){ /\\* For each resultline *\\/ *\/ */
1.222 brouard 9321: if (cptcovn>0) {
1.334 brouard 9322: fprintf(ficresprob, "\n#********** Variable ");
9323: fprintf(ficresprobcov, "\n#********** Variable ");
9324: fprintf(ficgp, "\n#********** Variable ");
9325: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
9326: fprintf(ficresprobcor, "\n#********** Variable ");
9327:
9328: /* Including quantitative variables of the resultline to be done */
9329: for (z1=1; z1<=cptcovs; z1++){ /* Loop on each variable of this resultline */
1.343 brouard 9330: /* printf("Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model); */
1.338 brouard 9331: fprintf(ficlog,"Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model);
9332: /* fprintf(ficlog,"Varprob modelresult[%d][%d]=%d model=1+age+%s resultline[%d]=%s \n",nres, z1, modelresult[nres][z1], model, nres, resultline[nres]); */
1.334 brouard 9333: if(Dummy[modelresult[nres][z1]]==0){/* Dummy variable of the variable in position modelresult in the model corresponding to z1 in resultline */
9334: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed referenced to model equation */
9335: fprintf(ficresprob,"V%d=%d ",Tvresult[nres][z1],Tresult[nres][z1]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
9336: fprintf(ficresprobcov,"V%d=%d ",Tvresult[nres][z1],Tresult[nres][z1]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
9337: fprintf(ficgp,"V%d=%d ",Tvresult[nres][z1],Tresult[nres][z1]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
9338: fprintf(fichtmcov,"V%d=%d ",Tvresult[nres][z1],Tresult[nres][z1]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
9339: fprintf(ficresprobcor,"V%d=%d ",Tvresult[nres][z1],Tresult[nres][z1]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
9340: fprintf(ficresprob,"fixed ");
9341: fprintf(ficresprobcov,"fixed ");
9342: fprintf(ficgp,"fixed ");
9343: fprintf(fichtmcov,"fixed ");
9344: fprintf(ficresprobcor,"fixed ");
9345: }else{
9346: fprintf(ficresprob,"varyi ");
9347: fprintf(ficresprobcov,"varyi ");
9348: fprintf(ficgp,"varyi ");
9349: fprintf(fichtmcov,"varyi ");
9350: fprintf(ficresprobcor,"varyi ");
9351: }
9352: }else if(Dummy[modelresult[nres][z1]]==1){ /* Quanti variable */
9353: /* For each selected (single) quantitative value */
1.337 brouard 9354: fprintf(ficresprob," V%d=%lg ",Tvqresult[nres][z1],Tqresult[nres][z1]);
1.334 brouard 9355: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed */
9356: fprintf(ficresprob,"fixed ");
9357: fprintf(ficresprobcov,"fixed ");
9358: fprintf(ficgp,"fixed ");
9359: fprintf(fichtmcov,"fixed ");
9360: fprintf(ficresprobcor,"fixed ");
9361: }else{
9362: fprintf(ficresprob,"varyi ");
9363: fprintf(ficresprobcov,"varyi ");
9364: fprintf(ficgp,"varyi ");
9365: fprintf(fichtmcov,"varyi ");
9366: fprintf(ficresprobcor,"varyi ");
9367: }
9368: }else{
9369: printf("Error in varprob() Dummy[modelresult[%d][%d]]=%d, modelresult[%d][%d]=V%d cptcovs=%d, cptcoveff=%d \n", nres, z1, Dummy[modelresult[nres][z1]],nres,z1,modelresult[nres][z1],cptcovs, cptcoveff); /* end if dummy or quanti */
9370: fprintf(ficlog,"Error in varprob() Dummy[modelresult[%d][%d]]=%d, modelresult[%d][%d]=V%d cptcovs=%d, cptcoveff=%d \n", nres, z1, Dummy[modelresult[nres][z1]],nres,z1,modelresult[nres][z1],cptcovs, cptcoveff); /* end if dummy or quanti */
9371: exit(1);
9372: }
9373: } /* End loop on variable of this resultline */
9374: /* for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]); */
1.222 brouard 9375: fprintf(ficresprob, "**********\n#\n");
9376: fprintf(ficresprobcov, "**********\n#\n");
9377: fprintf(ficgp, "**********\n#\n");
9378: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
9379: fprintf(ficresprobcor, "**********\n#");
9380: if(invalidvarcomb[j1]){
9381: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
9382: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
9383: continue;
9384: }
9385: }
9386: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
9387: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
9388: gp=vector(1,(nlstate)*(nlstate+ndeath));
9389: gm=vector(1,(nlstate)*(nlstate+ndeath));
1.334 brouard 9390: for (age=bage; age<=fage; age ++){ /* Fo each age we feed the model equation with covariates, using precov as in hpxij() ? */
1.222 brouard 9391: cov[2]=age;
9392: if(nagesqr==1)
9393: cov[3]= age*age;
1.334 brouard 9394: /* New code end of combination but for each resultline */
9395: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 9396: if(Typevar[k1]==1 || Typevar[k1] ==3){ /* A product with age */
1.334 brouard 9397: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.326 brouard 9398: }else{
1.334 brouard 9399: cov[2+nagesqr+k1]=precov[nres][k1];
1.326 brouard 9400: }
1.334 brouard 9401: }/* End of loop on model equation */
9402: /* Old code */
9403: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
9404: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)]; *\/ */
9405: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
9406: /* /\* Here comes the value of the covariate 'j1' after renumbering k with single dummy covariates *\/ */
9407: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(j1,TnsdVar[TvarsD[k]])]; */
9408: /* /\*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*\//\* j1 1 2 3 4 */
9409: /* * 1 1 1 1 1 */
9410: /* * 2 2 1 1 1 */
9411: /* * 3 1 2 1 1 */
9412: /* *\/ */
9413: /* /\* nbcode[1][1]=0 nbcode[1][2]=1;*\/ */
9414: /* } */
9415: /* /\* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
9416: /* /\* ) p nbcode[Tvar[Tage[k]]][(1 & (ij-1) >> (k-1))+1] *\/ */
9417: /* /\*for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; *\/ */
9418: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
9419: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
9420: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(j1,TnsdVar[Tvar[Tage[k]]])]*cov[2]; */
9421: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
9422: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
9423: /* printf("Internal IMaCh error, don't know which value for quantitative covariate with age, Tage[k]%d, k=%d, Tvar[Tage[k]]=V%d, age=%d\n",Tage[k],k ,Tvar[Tage[k]], (int)cov[2]); */
9424: /* /\* cov[2+nagesqr+Tage[k]]=meanq[k]/idq[k]*cov[2];/\\* Using the mean of quantitative variable Tvar[Tage[k]] /\\* Tqresult[nres][k]; *\\/ *\/ */
9425: /* /\* exit(1); *\/ */
9426: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
9427: /* } */
9428: /* /\* cov[2+Tage[k]+nagesqr]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
9429: /* } */
9430: /* for (k=1; k<=cptcovprod;k++){/\* For product without age *\/ */
9431: /* if(Dummy[Tvard[k][1]]==0){ */
9432: /* if(Dummy[Tvard[k][2]]==0){ */
9433: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(j1,TnsdVar[Tvard[k][1]])] * nbcode[Tvard[k][2]][codtabm(j1,TnsdVar[Tvard[k][2]])]; */
9434: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
9435: /* }else{ /\* Should we use the mean of the quantitative variables? *\/ */
9436: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(j1,TnsdVar[Tvard[k][1]])] * Tqresult[nres][resultmodel[nres][k]]; */
9437: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
9438: /* } */
9439: /* }else{ */
9440: /* if(Dummy[Tvard[k][2]]==0){ */
9441: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(j1,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][TnsdVar[Tvard[k][1]]]; */
9442: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
9443: /* }else{ */
9444: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][TnsdVar[Tvard[k][1]]]* Tqinvresult[nres][TnsdVar[Tvard[k][2]]]; */
9445: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
9446: /* } */
9447: /* } */
9448: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
9449: /* } */
1.326 brouard 9450: /* For each age and combination of dummy covariates we slightly move the parameters of delti in order to get the gradient*/
1.222 brouard 9451: for(theta=1; theta <=npar; theta++){
9452: for(i=1; i<=npar; i++)
9453: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 9454:
1.222 brouard 9455: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 9456:
1.222 brouard 9457: k=0;
9458: for(i=1; i<= (nlstate); i++){
9459: for(j=1; j<=(nlstate+ndeath);j++){
9460: k=k+1;
9461: gp[k]=pmmij[i][j];
9462: }
9463: }
1.220 brouard 9464:
1.222 brouard 9465: for(i=1; i<=npar; i++)
9466: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 9467:
1.222 brouard 9468: pmij(pmmij,cov,ncovmodel,xp,nlstate);
9469: k=0;
9470: for(i=1; i<=(nlstate); i++){
9471: for(j=1; j<=(nlstate+ndeath);j++){
9472: k=k+1;
9473: gm[k]=pmmij[i][j];
9474: }
9475: }
1.220 brouard 9476:
1.222 brouard 9477: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
9478: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
9479: }
1.126 brouard 9480:
1.222 brouard 9481: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
9482: for(theta=1; theta <=npar; theta++)
9483: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 9484:
1.222 brouard 9485: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
9486: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 9487:
1.222 brouard 9488: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 9489:
1.222 brouard 9490: k=0;
9491: for(i=1; i<=(nlstate); i++){
9492: for(j=1; j<=(nlstate+ndeath);j++){
9493: k=k+1;
9494: mu[k][(int) age]=pmmij[i][j];
9495: }
9496: }
9497: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
9498: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
9499: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 9500:
1.222 brouard 9501: /*printf("\n%d ",(int)age);
9502: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
9503: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
9504: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
9505: }*/
1.220 brouard 9506:
1.222 brouard 9507: fprintf(ficresprob,"\n%d ",(int)age);
9508: fprintf(ficresprobcov,"\n%d ",(int)age);
9509: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 9510:
1.222 brouard 9511: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
9512: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
9513: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
9514: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
9515: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
9516: }
9517: i=0;
9518: for (k=1; k<=(nlstate);k++){
9519: for (l=1; l<=(nlstate+ndeath);l++){
9520: i++;
9521: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
9522: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
9523: for (j=1; j<=i;j++){
9524: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
9525: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
9526: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
9527: }
9528: }
9529: }/* end of loop for state */
9530: } /* end of loop for age */
9531: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
9532: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
9533: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
9534: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
9535:
9536: /* Confidence intervalle of pij */
9537: /*
9538: fprintf(ficgp,"\nunset parametric;unset label");
9539: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
9540: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
9541: fprintf(fichtm,"\n<br>Probability with confidence intervals expressed in year<sup>-1</sup> :<a href=\"pijgr%s.png\">pijgr%s.png</A>, ",optionfilefiname,optionfilefiname);
9542: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
9543: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
9544: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
9545: */
9546:
9547: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
9548: first1=1;first2=2;
9549: for (k2=1; k2<=(nlstate);k2++){
9550: for (l2=1; l2<=(nlstate+ndeath);l2++){
9551: if(l2==k2) continue;
9552: j=(k2-1)*(nlstate+ndeath)+l2;
9553: for (k1=1; k1<=(nlstate);k1++){
9554: for (l1=1; l1<=(nlstate+ndeath);l1++){
9555: if(l1==k1) continue;
9556: i=(k1-1)*(nlstate+ndeath)+l1;
9557: if(i<=j) continue;
9558: for (age=bage; age<=fage; age ++){
9559: if ((int)age %5==0){
9560: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
9561: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
9562: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
9563: mu1=mu[i][(int) age]/stepm*YEARM ;
9564: mu2=mu[j][(int) age]/stepm*YEARM;
9565: c12=cv12/sqrt(v1*v2);
9566: /* Computing eigen value of matrix of covariance */
9567: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
9568: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
9569: if ((lc2 <0) || (lc1 <0) ){
9570: if(first2==1){
9571: first1=0;
9572: printf("Strange: j1=%d One eigen value of 2x2 matrix of covariance is negative, lc1=%11.3e, lc2=%11.3e, v1=%11.3e, v2=%11.3e, cv12=%11.3e.\n It means that the matrix was not well estimated (varpij), for i=%2d, j=%2d, age=%4d .\n See files %s and %s. Probably WRONG RESULTS. See log file for details...\n", j1, lc1, lc2, v1, v2, cv12, i, j, (int)age,fileresprobcov, fileresprobcor);
9573: }
9574: fprintf(ficlog,"Strange: j1=%d One eigen value of 2x2 matrix of covariance is negative, lc1=%11.3e, lc2=%11.3e, v1=%11.3e, v2=%11.3e, cv12=%11.3e.\n It means that the matrix was not well estimated (varpij), for i=%2d, j=%2d, age=%4d .\n See files %s and %s. Probably WRONG RESULTS.\n", j1, lc1, lc2, v1, v2, cv12, i, j, (int)age,fileresprobcov, fileresprobcor);fflush(ficlog);
9575: /* lc1=fabs(lc1); */ /* If we want to have them positive */
9576: /* lc2=fabs(lc2); */
9577: }
1.220 brouard 9578:
1.222 brouard 9579: /* Eigen vectors */
1.280 brouard 9580: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
9581: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
9582: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
9583: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
9584: }else
9585: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 9586: /*v21=sqrt(1.-v11*v11); *//* error */
9587: v21=(lc1-v1)/cv12*v11;
9588: v12=-v21;
9589: v22=v11;
9590: tnalp=v21/v11;
9591: if(first1==1){
9592: first1=0;
9593: printf("%d %d%d-%d%d mu %.4e %.4e Var %.4e %.4e cor %.3f cov %.4e Eig %.3e %.3e 1stv %.3f %.3f tang %.3f\nOthers in log...\n",(int) age,k1,l1,k2,l2,mu1,mu2,v1,v2,c12,cv12,lc1,lc2,v11,v21,tnalp);
9594: }
9595: fprintf(ficlog,"%d %d%d-%d%d mu %.4e %.4e Var %.4e %.4e cor %.3f cov %.4e Eig %.3e %.3e 1stv %.3f %.3f tan %.3f\n",(int) age,k1,l1,k2,l2,mu1,mu2,v1,v2,c12,cv12,lc1,lc2,v11,v21,tnalp);
9596: /*printf(fignu*/
9597: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
9598: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
9599: if(first==1){
9600: first=0;
9601: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
9602: fprintf(ficgp,"\nset parametric;unset label");
9603: fprintf(ficgp,"\nset log y;set log x; set xlabel \"p%1d%1d (year-1)\";set ylabel \"p%1d%1d (year-1)\"",k1,l1,k2,l2);
9604: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 9605: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 9606: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 9607: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 9608: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
9609: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
9610: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
9611: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
9612: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
9613: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
9614: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
9615: fprintf(ficgp,"\nplot [-pi:pi] %11.3e+ %.3f*(%11.3e*%11.3e*cos(t)+%11.3e*%11.3e*sin(t)), %11.3e +%.3f*(%11.3e*%11.3e*cos(t)+%11.3e*%11.3e*sin(t)) not", \
1.280 brouard 9616: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
9617: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 9618: }else{
9619: first=0;
9620: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
9621: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
9622: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
9623: fprintf(ficgp,"\nreplot %11.3e+ %.3f*(%11.3e*%11.3e*cos(t)+%11.3e*%11.3e*sin(t)), %11.3e +%.3f*(%11.3e*%11.3e*cos(t)+%11.3e*%11.3e*sin(t)) not", \
1.266 brouard 9624: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
9625: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 9626: }/* if first */
9627: } /* age mod 5 */
9628: } /* end loop age */
9629: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
9630: first=1;
9631: } /*l12 */
9632: } /* k12 */
9633: } /*l1 */
9634: }/* k1 */
1.332 brouard 9635: } /* loop on combination of covariates j1 */
1.326 brouard 9636: } /* loop on nres */
1.222 brouard 9637: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
9638: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
9639: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
9640: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
9641: free_vector(xp,1,npar);
9642: fclose(ficresprob);
9643: fclose(ficresprobcov);
9644: fclose(ficresprobcor);
9645: fflush(ficgp);
9646: fflush(fichtmcov);
9647: }
1.126 brouard 9648:
9649:
9650: /******************* Printing html file ***********/
1.201 brouard 9651: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 9652: int lastpass, int stepm, int weightopt, char model[],\
9653: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.296 brouard 9654: int popforecast, int mobilav, int prevfcast, int mobilavproj, int prevbcast, int estepm , \
9655: double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \
9656: double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){
1.359 brouard 9657: int jj1, k1, cpt, nres;
1.319 brouard 9658: /* In fact some results are already printed in fichtm which is open */
1.126 brouard 9659: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
9660: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
9661: </ul>");
1.319 brouard 9662: /* fprintf(fichtm,"<ul><li> model=1+age+%s\n \ */
9663: /* </ul>", model); */
1.214 brouard 9664: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
9665: fprintf(fichtm,"<li>- Observed frequency between two states (during the period defined between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf): <a href=\"%s\">%s</a> (html file)<br/>\n",
9666: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
1.332 brouard 9667: fprintf(fichtm,"<li> - Observed prevalence (cross-sectional prevalence) in each state (during the period defined between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf): <a href=\"%s\">%s</a> (html file) ",
1.213 brouard 9668: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
9669: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 9670: fprintf(fichtm,"\
9671: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 9672: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 9673: fprintf(fichtm,"\
1.217 brouard 9674: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
9675: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
9676: fprintf(fichtm,"\
1.288 brouard 9677: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 9678: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 9679: fprintf(fichtm,"\
1.288 brouard 9680: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 9681: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
9682: fprintf(fichtm,"\
1.211 brouard 9683: - (a) Life expectancies by health status at initial age, e<sub>i.</sub> (b) health expectancies by health status at initial age, e<sub>ij</sub> . If one or more covariates are included, specific tables for each value of the covariate are output in sequences within the same file (estepm=%2d months): \
1.126 brouard 9684: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 9685: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 9686: if(prevfcast==1){
9687: fprintf(fichtm,"\
9688: - Prevalence projections by age and states: \
1.201 brouard 9689: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 9690: }
1.126 brouard 9691:
9692:
1.225 brouard 9693: m=pow(2,cptcoveff);
1.222 brouard 9694: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 9695:
1.317 brouard 9696: fprintf(fichtm," \n<ul><li><b>Graphs (first order)</b></li><p>");
1.264 brouard 9697:
9698: jj1=0;
9699:
9700: fprintf(fichtm," \n<ul>");
1.337 brouard 9701: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
9702: /* k1=nres; */
1.338 brouard 9703: k1=TKresult[nres];
9704: if(TKresult[nres]==0)k1=1; /* To be checked for no result */
1.337 brouard 9705: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
9706: /* if(m != 1 && TKresult[nres]!= k1) */
9707: /* continue; */
1.264 brouard 9708: jj1++;
9709: if (cptcovn > 0) {
9710: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
1.337 brouard 9711: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
9712: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 9713: }
1.337 brouard 9714: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
9715: /* fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
9716: /* } */
9717: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9718: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
9719: /* } */
1.264 brouard 9720: fprintf(fichtm,"\">");
9721:
9722: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
9723: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 9724: for (cpt=1; cpt<=cptcovs;cpt++){
9725: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 9726: }
1.337 brouard 9727: /* fprintf(fichtm,"************ Results for covariates"); */
9728: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
9729: /* fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
9730: /* } */
9731: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9732: /* fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
9733: /* } */
1.264 brouard 9734: if(invalidvarcomb[k1]){
9735: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
9736: continue;
9737: }
9738: fprintf(fichtm,"</a></li>");
9739: } /* cptcovn >0 */
9740: }
1.317 brouard 9741: fprintf(fichtm," \n</ul>");
1.264 brouard 9742:
1.222 brouard 9743: jj1=0;
1.237 brouard 9744:
1.337 brouard 9745: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
9746: /* k1=nres; */
1.338 brouard 9747: k1=TKresult[nres];
9748: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9749: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
9750: /* if(m != 1 && TKresult[nres]!= k1) */
9751: /* continue; */
1.220 brouard 9752:
1.222 brouard 9753: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
9754: jj1++;
9755: if (cptcovn > 0) {
1.264 brouard 9756: fprintf(fichtm,"\n<p><a name=\"rescov");
1.337 brouard 9757: for (cpt=1; cpt<=cptcovs;cpt++){
9758: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 9759: }
1.337 brouard 9760: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9761: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
9762: /* } */
1.264 brouard 9763: fprintf(fichtm,"\"</a>");
9764:
1.222 brouard 9765: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 9766: for (cpt=1; cpt<=cptcovs;cpt++){
9767: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
9768: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 9769: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
9770: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 9771: }
1.230 brouard 9772: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.338 brouard 9773: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.222 brouard 9774: if(invalidvarcomb[k1]){
9775: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
9776: printf("\nCombination (%d) ignored because no cases \n",k1);
9777: continue;
9778: }
9779: }
9780: /* aij, bij */
1.259 brouard 9781: fprintf(fichtm,"<br>- Logit model (yours is: logit(pij)=log(pij/pii)= aij+ bij age+%s) as a function of age: <a href=\"%s_%d-1-%d.svg\">%s_%d-1-%d.svg</a><br> \
1.241 brouard 9782: <img src=\"%s_%d-1-%d.svg\">",model,subdirf2(optionfilefiname,"PE_"),k1,nres,subdirf2(optionfilefiname,"PE_"),k1,nres,subdirf2(optionfilefiname,"PE_"),k1,nres);
1.222 brouard 9783: /* Pij */
1.241 brouard 9784: fprintf(fichtm,"<br>\n- P<sub>ij</sub> or conditional probabilities to be observed in state j being in state i, %d (stepm) months before: <a href=\"%s_%d-2-%d.svg\">%s_%d-2-%d.svg</a><br> \
9785: <img src=\"%s_%d-2-%d.svg\">",stepm,subdirf2(optionfilefiname,"PE_"),k1,nres,subdirf2(optionfilefiname,"PE_"),k1,nres,subdirf2(optionfilefiname,"PE_"),k1,nres);
1.222 brouard 9786: /* Quasi-incidences */
9787: fprintf(fichtm,"<br>\n- I<sub>ij</sub> or Conditional probabilities to be observed in state j being in state i %d (stepm) months\
1.220 brouard 9788: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 9789: incidence (rates) are the limit when h tends to zero of the ratio of the probability <sub>h</sub>P<sub>ij</sub> \
1.241 brouard 9790: divided by h: <sub>h</sub>P<sub>ij</sub>/h : <a href=\"%s_%d-3-%d.svg\">%s_%d-3-%d.svg</a><br> \
9791: <img src=\"%s_%d-3-%d.svg\">",stepm,subdirf2(optionfilefiname,"PE_"),k1,nres,subdirf2(optionfilefiname,"PE_"),k1,nres,subdirf2(optionfilefiname,"PE_"),k1,nres);
1.222 brouard 9792: /* Survival functions (period) in state j */
9793: for(cpt=1; cpt<=nlstate;cpt++){
1.359 brouard 9794: fprintf(fichtm,"<br>\n- Survival functions in state %d. And probability to be observed in state %d being in state (1 to %d) at different ages. Mean times spent in state (or Life Expectancy or Health Expectancy etc.) are the areas under each curve. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br>", cpt, cpt, nlstate, subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.329 brouard 9795: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
9796: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.222 brouard 9797: }
9798: /* State specific survival functions (period) */
9799: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 9800: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
1.359 brouard 9801: And probability to be observed in various states (up to %d) being in state %d at different ages. Mean times spent in state (or Life Expectancy or Health Expectancy etc.) are the areas under each curve. \
1.329 brouard 9802: <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> ", cpt, nlstate, cpt, subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres,subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
9803: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
9804: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.222 brouard 9805: }
1.288 brouard 9806: /* Period (forward stable) prevalence in each health state */
1.222 brouard 9807: for(cpt=1; cpt<=nlstate;cpt++){
1.359 brouard 9808: fprintf(fichtm,"<br>\n- Convergence to period (stable) prevalence in state %d. Or probability for a person being in state (1 to %d) at different ages, to be alive in state %d some years after. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br>", cpt, nlstate, cpt, subdirf2(optionfilefiname,"P_"),cpt,k1,nres,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.338 brouard 9809: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
1.329 brouard 9810: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.222 brouard 9811: }
1.296 brouard 9812: if(prevbcast==1){
1.288 brouard 9813: /* Backward prevalence in each health state */
1.222 brouard 9814: for(cpt=1; cpt<=nlstate;cpt++){
1.338 brouard 9815: fprintf(fichtm,"<br>\n- Convergence to mixed (stable) back prevalence in state %d. Or probability for a person to be in state %d at a younger age, knowing that she/he was in state (1 to %d) at different older ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br>", cpt, cpt, nlstate, subdirf2(optionfilefiname,"PB_"),cpt,k1,nres,subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
9816: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJB_"),subdirf2(optionfilefiname,"PIJB_"));
9817: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.222 brouard 9818: }
1.217 brouard 9819: }
1.222 brouard 9820: if(prevfcast==1){
1.288 brouard 9821: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 9822: for(cpt=1; cpt<=nlstate;cpt++){
1.314 brouard 9823: fprintf(fichtm,"<br>\n- Projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), from year %.1f up to year %.1f tending to period (stable) forward prevalence in state %d. Or probability to be in state %d being in an observed weighted state (from 1 to %d). <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a>", dateprev1, dateprev2, mobilavproj, dateprojd, dateprojf, cpt, cpt, nlstate, subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
9824: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"F_"),subdirf2(optionfilefiname,"F_"));
9825: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",
9826: subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 9827: }
9828: }
1.296 brouard 9829: if(prevbcast==1){
1.268 brouard 9830: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
9831: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 9832: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
1.359 brouard 9833: from year %.1f up to year %.1f (probably close to stable [mixed] back prevalence in state %d). Randomness in cross-sectional prevalence is not taken into \
9834: account but can visually be appreciated. Or probability to have been in an state %d, knowing that the person was in either state (1 or %d) \
1.314 brouard 9835: with weights corresponding to observed prevalence at different ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a>", dateprev1, dateprev2, mobilavproj, dateback1, dateback2, cpt, cpt, nlstate, subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
9836: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"FB_"),subdirf2(optionfilefiname,"FB_"));
9837: fprintf(fichtm," <img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
1.268 brouard 9838: }
9839: }
1.220 brouard 9840:
1.222 brouard 9841: for(cpt=1; cpt<=nlstate;cpt++) {
1.314 brouard 9842: fprintf(fichtm,"\n<br>- Life expectancy by health state (%d) at initial age and its decomposition into health expectancies in each alive state (1 to %d) (or area under each survival functions): <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a>",cpt,nlstate,subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres,subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
9843: fprintf(fichtm," (data from text file <a href=\"%s.txt\"> %s.txt</a>)\n<br>",subdirf2(optionfilefiname,"E_"),subdirf2(optionfilefiname,"E_"));
9844: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres );
1.222 brouard 9845: }
9846: /* } /\* end i1 *\/ */
1.337 brouard 9847: }/* End k1=nres */
1.222 brouard 9848: fprintf(fichtm,"</ul>");
1.126 brouard 9849:
1.222 brouard 9850: fprintf(fichtm,"\
1.126 brouard 9851: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 9852: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 9853: - 95%% confidence intervals and Wald tests of the estimated parameters are in the log file if optimization has been done (mle != 0).<br> \
1.197 brouard 9854: But because parameters are usually highly correlated (a higher incidence of disability \
9855: and a higher incidence of recovery can give very close observed transition) it might \
9856: be very useful to look not only at linear confidence intervals estimated from the \
9857: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
9858: (parameters) of the logistic regression, it might be more meaningful to visualize the \
9859: covariance matrix of the one-step probabilities. \
9860: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 9861:
1.222 brouard 9862: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
9863: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
9864: fprintf(fichtm,"\
1.126 brouard 9865: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 9866: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 9867:
1.222 brouard 9868: fprintf(fichtm,"\
1.126 brouard 9869: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 9870: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
9871: fprintf(fichtm,"\
1.126 brouard 9872: - Variances and covariances of health expectancies by age and <b>initial health status</b> (cov(e<sup>ij</sup>,e<sup>kl</sup>)(estepm=%2d months): \
9873: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 9874: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 9875: fprintf(fichtm,"\
1.126 brouard 9876: - (a) Health expectancies by health status at initial age (e<sup>ij</sup>) and standard errors (in parentheses) (b) life expectancies and standard errors (e<sup>i.</sup>=e<sup>i1</sup>+e<sup>i2</sup>+...)(estepm=%2d months): \
9877: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 9878: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 9879: fprintf(fichtm,"\
1.288 brouard 9880: - Variances and covariances of health expectancies by age. Status (i) based health expectancies (in state j), e<sup>ij</sup> are weighted by the forward (period) prevalences in each state i (if popbased=1, an additional computation is done using the cross-sectional prevalences, i.e population based) (estepm=%d months): <a href=\"%s\">%s</a><br>\n",
1.222 brouard 9881: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
9882: fprintf(fichtm,"\
1.128 brouard 9883: - Total life expectancy and total health expectancies to be spent in each health state e<sup>.j</sup> with their standard errors (if popbased=1, an additional computation is done using the cross-sectional prevalences, i.e population based) (estepm=%d months): <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 9884: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
9885: fprintf(fichtm,"\
1.288 brouard 9886: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 9887: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 9888:
9889: /* if(popforecast==1) fprintf(fichtm,"\n */
9890: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
9891: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
9892: /* <br>",fileres,fileres,fileres,fileres); */
9893: /* else */
1.338 brouard 9894: /* fprintf(fichtm,"\n No population forecast: popforecast = %d (instead of 1) or stepm = %d (instead of 1) or model=1+age+%s (instead of .)<br><br></li>\n",popforecast, stepm, model); */
1.222 brouard 9895: fflush(fichtm);
1.126 brouard 9896:
1.225 brouard 9897: m=pow(2,cptcoveff);
1.222 brouard 9898: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 9899:
1.317 brouard 9900: fprintf(fichtm," <ul><li><b>Graphs (second order)</b></li><p>");
9901:
9902: jj1=0;
9903:
9904: fprintf(fichtm," \n<ul>");
1.337 brouard 9905: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
9906: /* k1=nres; */
1.338 brouard 9907: k1=TKresult[nres];
1.337 brouard 9908: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
9909: /* if(m != 1 && TKresult[nres]!= k1) */
9910: /* continue; */
1.317 brouard 9911: jj1++;
9912: if (cptcovn > 0) {
9913: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescovsecond");
1.337 brouard 9914: for (cpt=1; cpt<=cptcovs;cpt++){
9915: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 9916: }
9917: fprintf(fichtm,"\">");
9918:
9919: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
9920: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 9921: for (cpt=1; cpt<=cptcovs;cpt++){
9922: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 9923: }
9924: if(invalidvarcomb[k1]){
9925: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
9926: continue;
9927: }
9928: fprintf(fichtm,"</a></li>");
9929: } /* cptcovn >0 */
1.337 brouard 9930: } /* End nres */
1.317 brouard 9931: fprintf(fichtm," \n</ul>");
9932:
1.222 brouard 9933: jj1=0;
1.237 brouard 9934:
1.241 brouard 9935: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9936: /* k1=nres; */
1.338 brouard 9937: k1=TKresult[nres];
9938: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9939: /* for(k1=1; k1<=m;k1++){ */
9940: /* if(m != 1 && TKresult[nres]!= k1) */
9941: /* continue; */
1.222 brouard 9942: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
9943: jj1++;
1.126 brouard 9944: if (cptcovn > 0) {
1.317 brouard 9945: fprintf(fichtm,"\n<p><a name=\"rescovsecond");
1.337 brouard 9946: for (cpt=1; cpt<=cptcovs;cpt++){
9947: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 9948: }
9949: fprintf(fichtm,"\"</a>");
9950:
1.126 brouard 9951: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 9952: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcoveff number of variables */
9953: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
9954: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 9955: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
1.317 brouard 9956: }
1.237 brouard 9957:
1.338 brouard 9958: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.220 brouard 9959:
1.222 brouard 9960: if(invalidvarcomb[k1]){
9961: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
9962: continue;
9963: }
1.337 brouard 9964: } /* If cptcovn >0 */
1.126 brouard 9965: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 9966: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.314 brouard 9967: prevalence (with 95%% confidence interval) in state (%d): <a href=\"%s_%d-%d-%d.svg\"> %s_%d-%d-%d.svg</a>",mobilav,cpt,subdirf2(optionfilefiname,"V_"),cpt,k1,nres,subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
9968: fprintf(fichtm," (data from text file <a href=\"%s\">%s</a>)\n <br>",subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
9969: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"V_"), cpt,k1,nres);
1.126 brouard 9970: }
9971: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.360 brouard 9972: health expectancies in each live state (1 to %d) with confidence intervals \
9973: on left y-scale as well as proportions of time spent in each live state \
9974: (with confidence intervals) on right y-scale 0 to 100%%.\
9975: If popbased=1 the smooth (due to the model) \
1.128 brouard 9976: true period expectancies (those weighted with period prevalences are also\
9977: drawn in addition to the population based expectancies computed using\
1.314 brouard 9978: observed and cahotic prevalences: <a href=\"%s_%d-%d.svg\">%s_%d-%d.svg</a>",nlstate, subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres);
9979: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>) \n<br>",subdirf2(optionfilefiname,"T_"),subdirf2(optionfilefiname,"T_"));
9980: fprintf(fichtm,"<img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 9981: /* } /\* end i1 *\/ */
1.241 brouard 9982: }/* End nres */
1.222 brouard 9983: fprintf(fichtm,"</ul>");
9984: fflush(fichtm);
1.126 brouard 9985: }
9986:
9987: /******************* Gnuplot file **************/
1.296 brouard 9988: void printinggnuplot(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double bage, double fage , int prevfcast, int prevbcast, char pathc[], double p[], int offyear, int offbyear){
1.126 brouard 9989:
1.354 brouard 9990: char dirfileres[256],optfileres[256];
9991: char gplotcondition[256], gplotlabel[256];
1.343 brouard 9992: int cpt=0,k1=0,i=0,k=0,j=0,jk=0,k2=0,k3=0,k4=0,kf=0,kvar=0,kk=0,ipos=0,iposold=0,ij=0, ijp=0, l=0;
1.211 brouard 9993: int lv=0, vlv=0, kl=0;
1.130 brouard 9994: int ng=0;
1.201 brouard 9995: int vpopbased;
1.223 brouard 9996: int ioffset; /* variable offset for columns */
1.270 brouard 9997: int iyearc=1; /* variable column for year of projection */
9998: int iagec=1; /* variable column for age of projection */
1.235 brouard 9999: int nres=0; /* Index of resultline */
1.266 brouard 10000: int istart=1; /* For starting graphs in projections */
1.219 brouard 10001:
1.126 brouard 10002: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
10003: /* printf("Problem with file %s",optionfilegnuplot); */
10004: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
10005: /* } */
10006:
10007: /*#ifdef windows */
10008: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 10009: /*#endif */
1.225 brouard 10010: m=pow(2,cptcoveff);
1.126 brouard 10011:
1.274 brouard 10012: /* diagram of the model */
10013: fprintf(ficgp,"\n#Diagram of the model \n");
10014: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
10015: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
10016: fprintf(ficgp,"\n#Peripheral arrows\nset for [i=1:%d] for [j=1:%d] arrow i*10+j from cos(pi*((1-(%d/2)*2./%d)/2+(i-1)*2./%d))-(i!=j?(i-j)/abs(i-j)*delta:0), yoff +sin(pi*((1-(%d/2)*2./%d)/2+(i-1)*2./%d)) + (i!=j?(i-j)/abs(i-j)*delta:0) rto -0.95*(cos(pi*((1-(%d/2)*2./%d)/2+(i-1)*2./%d))+(i!=j?(i-j)/abs(i-j)*delta:0) - cos(pi*((1-(%d/2)*2./%d)/2+(j-1)*2./%d)) + (i!=j?(i-j)/abs(i-j)*delta2:0)), -0.95*(sin(pi*((1-(%d/2)*2./%d)/2+(i-1)*2./%d)) + (i!=j?(i-j)/abs(i-j)*delta:0) - sin(pi*((1-(%d/2)*2./%d)/2+(j-1)*2./%d))+( i!=j?(i-j)/abs(i-j)*delta2:0)) ls (i < j? 1:2)\n",nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate);
10017:
1.343 brouard 10018: fprintf(ficgp,"\n#Centripete arrows (turning in other direction (1-i) instead of (i-1)) \nset for [i=1:%d] for [j=1:%d] arrow (%d+1)*10+i from cos(pi*((1-(%d/2)*2./%d)/2+(1-i)*2./%d))-(i!=j?(i-j)/abs(i-j)*delta:0), yoff +sin(pi*((1-(%d/2)*2./%d)/2+(1-i)*2./%d)) + (i!=j?(i-j)/abs(i-j)*delta:0) rto -0.80*(cos(pi*((1-(%d/2)*2./%d)/2+(1-i)*2./%d))+(i!=j?(i-j)/abs(i-j)*delta:0) ), -0.80*(sin(pi*((1-(%d/2)*2./%d)/2+(1-i)*2./%d)) + (i!=j?(i-j)/abs(i-j)*delta:0) + yoff ) ls 4\n",nlstate, nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate);
1.274 brouard 10019: fprintf(ficgp,"\n#show arrow\nunset label\n");
10020: fprintf(ficgp,"\n#States labels, starting from 2 (2-i) instead of (1-i), was (i-1)\nset for [i=1:%d] label i sprintf(\"State %%d\",i) center at cos(pi*((1-(%d/2)*2./%d)/2+(2-i)*2./%d)), yoff+sin(pi*((1-(%d/2)*2./%d)/2+(2-i)*2./%d)) font \"helvetica, 16\" tc rgbcolor \"blue\"\n",nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate);
10021: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
10022: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
10023: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
10024: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
10025:
1.202 brouard 10026: /* Contribution to likelihood */
10027: /* Plot the probability implied in the likelihood */
1.223 brouard 10028: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
10029: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
10030: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
10031: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 10032: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 10033: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
10034: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 10035: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
10036: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
10037: fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$13):6 t \"All sample, transitions colored by destination\" with dots lc variable; set out;\n",subdirf(fileresilk));
10038: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
10039: fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$13):5 t \"All sample, transitions colored by origin\" with dots lc variable; set out;\n\n",subdirf(fileresilk));
10040: for (i=1; i<= nlstate ; i ++) {
10041: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
10042: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
10043: fprintf(ficgp," u 2:($5 == %d && $6==%d ? $10 : 1/0):($12/4.):6 t \"p%d%d\" with points pointtype 7 ps variable lc variable \\\n",i,1,i,1);
10044: for (j=2; j<= nlstate+ndeath ; j ++) {
10045: fprintf(ficgp,",\\\n \"\" u 2:($5 == %d && $6==%d ? $10 : 1/0):($12/4.):6 t \"p%d%d\" with points pointtype 7 ps variable lc variable ",i,j,i,j);
10046: }
10047: fprintf(ficgp,";\nset out; unset ylabel;\n");
10048: }
10049: /* unset log; plot "rrtest1_sorted_4/ILK_rrtest1_sorted_4.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with points lc variable */
10050: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
10051: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
10052: fprintf(ficgp,"\nset out;unset log\n");
10053: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 10054:
1.343 brouard 10055: /* Plot the probability implied in the likelihood by covariate value */
10056: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
10057: /* if(debugILK==1){ */
10058: for(kf=1; kf <= ncovf; kf++){ /* For each simple dummy covariate of the model */
1.347 brouard 10059: kvar=Tvar[TvarFind[kf]]; /* variable name */
10060: /* k=18+Tvar[TvarFind[kf]];/\*offset because there are 18 columns in the ILK_ file but could be placed else where *\/ */
1.350 brouard 10061: /* k=18+kf;/\*offset because there are 18 columns in the ILK_ file *\/ */
1.356 brouard 10062: /* k=19+kf;/\*offset because there are 19 columns in the ILK_ file *\/ */
1.355 brouard 10063: k=16+nlstate+kf;/*offset because there are 19 columns in the ILK_ file, first cov Vn on col 21 with 4 living states */
1.343 brouard 10064: for (i=1; i<= nlstate ; i ++) {
10065: fprintf(ficgp,"\nset out \"%s-p%dj-%d.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i,kvar);
10066: fprintf(ficgp,"unset log;\n# For each simple dummy covariate of the model \n plot \"%s\"",subdirf(fileresilk));
1.348 brouard 10067: if(gnuplotversion >=5.2){ /* Former gnuplot versions do not have variable pointsize!! */
10068: fprintf(ficgp," u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? 7 : 9):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt variable ps 0.4 lc variable \\\n",i,1,k,k,i,1,kvar);
10069: for (j=2; j<= nlstate+ndeath ; j ++) {
10070: fprintf(ficgp,",\\\n \"\" u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? 7 : 9):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt variable ps 0.4 lc variable ",i,j,k,k,i,j,kvar);
10071: }
10072: }else{
10073: fprintf(ficgp," u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt 7 ps 0.4 lc variable \\\n",i,1,k,i,1,kvar);
10074: for (j=2; j<= nlstate+ndeath ; j ++) {
10075: fprintf(ficgp,",\\\n \"\" u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt 7 ps 0.4 lc variable ",i,j,k,i,j,kvar);
10076: }
1.343 brouard 10077: }
10078: fprintf(ficgp,";\nset out; unset ylabel;\n");
10079: }
10080: } /* End of each covariate dummy */
10081: for(ncovv=1, iposold=0, kk=0; ncovv <= ncovvt ; ncovv++){
10082: /* Other example V1 + V3 + V5 + age*V1 + age*V3 + age*V5 + V1*V3 + V3*V5 + V1*V5
10083: * kmodel = 1 2 3 4 5 6 7 8 9
10084: * varying 1 2 3 4 5
10085: * ncovv 1 2 3 4 5 6 7 8
10086: * TvarVV[ncovv] V3 5 1 3 3 5 1 5
10087: * TvarVVind[ncovv]=kmodel 2 3 7 7 8 8 9 9
10088: * TvarFind[kmodel] 1 0 0 0 0 0 0 0 0
10089: * kdata ncovcol=[V1 V2] nqv=0 ntv=[V3 V4] nqtv=V5
10090: * Dummy[kmodel] 0 0 1 2 2 3 1 1 1
10091: */
10092: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
10093: kvar=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
10094: /* printf("DebugILK ficgp ncovv=%d, kvar=TvarVV[ncovv]=%d, ipos=TvarVVind[ncovv]=%d, Dummy[ipos]=%d, Typevar[ipos]=%d\n", ncovv,kvar,ipos,Dummy[ipos],Typevar[ipos]); */
10095: if(ipos!=iposold){ /* Not a product or first of a product */
10096: /* printf(" %d",ipos); */
10097: /* fprintf(ficresilk," V%d",TvarVV[ncovv]); */
10098: /* printf(" DebugILK ficgp suite ipos=%d != iposold=%d\n", ipos, iposold); */
10099: kk++; /* Position of the ncovv column in ILK_ */
10100: k=18+ncovf+kk; /*offset because there are 18 columns in the ILK_ file plus ncovf fixed covariate */
10101: if(Dummy[ipos]==0 && Typevar[ipos]==0){ /* Only if dummy time varying: Dummy(0, 1=quant singor prod without age,2 dummy*age, 3quant*age) Typevar (0 single, 1=*age,2=Vn*vm) */
10102: for (i=1; i<= nlstate ; i ++) {
10103: fprintf(ficgp,"\nset out \"%s-p%dj-%d.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i,kvar);
10104: fprintf(ficgp,"unset log;\n# For each simple dummy covariate of the model \n plot \"%s\"",subdirf(fileresilk));
10105:
1.348 brouard 10106: /* printf("Before DebugILK gnuplotversion=%g >=5.2\n",gnuplotversion); */
1.343 brouard 10107: if(gnuplotversion >=5.2){ /* Former gnuplot versions do not have variable pointsize!! */
10108: /* printf("DebugILK gnuplotversion=%g >=5.2\n",gnuplotversion); */
10109: fprintf(ficgp," u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? 7 : 9):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt variable ps 0.4 lc variable \\\n",i,1,k,k,i,1,kvar);
10110: for (j=2; j<= nlstate+ndeath ; j ++) {
10111: fprintf(ficgp,",\\\n \"\" u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? 7 : 9):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt variable ps 0.4 lc variable ",i,j,k,k,i,j,kvar);
10112: }
10113: }else{
10114: /* printf("DebugILK gnuplotversion=%g <5.2\n",gnuplotversion); */
10115: fprintf(ficgp," u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt 7 ps 0.4 lc variable \\\n",i,1,k,i,1,kvar);
10116: for (j=2; j<= nlstate+ndeath ; j ++) {
10117: fprintf(ficgp,",\\\n \"\" u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt 7 ps 0.4 lc variable ",i,j,k,i,j,kvar);
10118: }
10119: }
10120: fprintf(ficgp,";\nset out; unset ylabel;\n");
10121: }
10122: }/* End if dummy varying */
10123: }else{ /*Product */
10124: /* printf("*"); */
10125: /* fprintf(ficresilk,"*"); */
10126: }
10127: iposold=ipos;
10128: } /* For each time varying covariate */
10129: /* } /\* debugILK==1 *\/ */
10130: /* unset log; plot "rrtest1_sorted_4/ILK_rrtest1_sorted_4.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with points lc variable */
10131: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
10132: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
10133: fprintf(ficgp,"\nset out;unset log\n");
10134: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
10135:
10136:
10137:
1.126 brouard 10138: strcpy(dirfileres,optionfilefiname);
10139: strcpy(optfileres,"vpl");
1.223 brouard 10140: /* 1eme*/
1.238 brouard 10141: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
1.337 brouard 10142: /* for (k1=1; k1<= m ; k1 ++){ /\* For each valid combination of covariate *\/ */
1.236 brouard 10143: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10144: k1=TKresult[nres];
1.338 brouard 10145: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.238 brouard 10146: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.337 brouard 10147: /* if(m != 1 && TKresult[nres]!= k1) */
10148: /* continue; */
1.238 brouard 10149: /* We are interested in selected combination by the resultline */
1.246 brouard 10150: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 10151: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 10152: strcpy(gplotlabel,"(");
1.337 brouard 10153: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10154: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10155: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10156:
10157: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate k get corresponding value lv for combination k1 *\/ */
10158: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the value of the covariate corresponding to k1 combination *\\/ *\/ */
10159: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
10160: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10161: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10162: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10163: /* vlv= nbcode[Tvaraff[k]][lv]; /\* vlv is the value of the covariate lv, 0 or 1 *\/ */
10164: /* /\* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv *\/ */
10165: /* /\* printf(" V%d=%d ",Tvaraff[k],vlv); *\/ */
10166: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10167: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10168: /* } */
10169: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10170: /* /\* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); *\/ */
10171: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
10172: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.264 brouard 10173: }
10174: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 10175: /* printf("\n#\n"); */
1.238 brouard 10176: fprintf(ficgp,"\n#\n");
10177: if(invalidvarcomb[k1]){
1.260 brouard 10178: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 10179: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10180: continue;
10181: }
1.235 brouard 10182:
1.241 brouard 10183: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
10184: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 10185: /* fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel); */
1.338 brouard 10186: fprintf(ficgp,"set title \"Alive state %d %s model=1+age+%s\" font \"Helvetica,12\"\n",cpt,gplotlabel,model);
1.260 brouard 10187: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \nset ter svg size 640, 480\nplot [%.f:%.f] \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",ageminpar,fage,subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
10188: /* fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \nset ter svg size 640, 480\nplot [%.f:%.f] \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",ageminpar,fage,subdirf2(fileresu,"VPL_"),k1-1,k1-1,nres); */
10189: /* k1-1 error should be nres-1*/
1.238 brouard 10190: for (i=1; i<= nlstate ; i ++) {
10191: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
10192: else fprintf(ficgp," %%*lf (%%*lf)");
10193: }
1.288 brouard 10194: fprintf(ficgp,"\" t\"Forward prevalence\" w l lt 0,\"%s\" every :::%d::%d u 1:($2==%d ? $3+1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 10195: for (i=1; i<= nlstate ; i ++) {
10196: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
10197: else fprintf(ficgp," %%*lf (%%*lf)");
10198: }
1.260 brouard 10199: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 10200: for (i=1; i<= nlstate ; i ++) {
10201: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
10202: else fprintf(ficgp," %%*lf (%%*lf)");
10203: }
1.265 brouard 10204: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
10205:
10206: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
10207: if(cptcoveff ==0){
1.271 brouard 10208: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 10209: }else{
10210: kl=0;
10211: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 10212: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
10213: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.265 brouard 10214: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
10215: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
10216: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
10217: vlv= nbcode[Tvaraff[k]][lv];
10218: kl++;
10219: /* kl=6+(cpt-1)*(nlstate+1)+1+(i-1); /\* 6+(1-1)*(2+1)+1+(1-1)=7, 6+(2-1)(2+1)+1+(1-1)=10 *\/ */
10220: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
10221: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
10222: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
10223: if(k==cptcoveff){
10224: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
10225: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
10226: }else{
10227: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
10228: kl++;
10229: }
10230: } /* end covariate */
10231: } /* end if no covariate */
10232:
1.296 brouard 10233: if(prevbcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
1.238 brouard 10234: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 10235: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 10236: if(cptcoveff ==0){
1.245 brouard 10237: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 10238: }else{
10239: kl=0;
10240: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 10241: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
10242: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.238 brouard 10243: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
10244: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
10245: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 10246: /* vlv= nbcode[Tvaraff[k]][lv]; */
10247: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.223 brouard 10248: kl++;
1.238 brouard 10249: /* kl=6+(cpt-1)*(nlstate+1)+1+(i-1); /\* 6+(1-1)*(2+1)+1+(1-1)=7, 6+(2-1)(2+1)+1+(1-1)=10 *\/ */
10250: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
10251: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
10252: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
10253: if(k==cptcoveff){
1.245 brouard 10254: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 10255: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 10256: }else{
1.332 brouard 10257: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]);
1.238 brouard 10258: kl++;
10259: }
10260: } /* end covariate */
10261: } /* end if no covariate */
1.296 brouard 10262: if(prevbcast == 1){
1.268 brouard 10263: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
10264: /* k1-1 error should be nres-1*/
10265: for (i=1; i<= nlstate ; i ++) {
10266: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
10267: else fprintf(ficgp," %%*lf (%%*lf)");
10268: }
1.271 brouard 10269: fprintf(ficgp,"\" t\"Backward (stable) prevalence\" w l lt 6 dt 3,\"%s\" every :::%d::%d u 1:($2==%d ? $3+1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
1.268 brouard 10270: for (i=1; i<= nlstate ; i ++) {
10271: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
10272: else fprintf(ficgp," %%*lf (%%*lf)");
10273: }
1.276 brouard 10274: fprintf(ficgp,"\" t\"95%% CI\" w l lt 4,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
1.268 brouard 10275: for (i=1; i<= nlstate ; i ++) {
10276: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
10277: else fprintf(ficgp," %%*lf (%%*lf)");
10278: }
1.274 brouard 10279: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 10280: } /* end if backprojcast */
1.296 brouard 10281: } /* end if prevbcast */
1.276 brouard 10282: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
10283: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 10284: } /* nres */
1.337 brouard 10285: /* } /\* k1 *\/ */
1.201 brouard 10286: } /* cpt */
1.235 brouard 10287:
10288:
1.126 brouard 10289: /*2 eme*/
1.337 brouard 10290: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 10291: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10292: k1=TKresult[nres];
1.338 brouard 10293: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 10294: /* if(m != 1 && TKresult[nres]!= k1) */
10295: /* continue; */
1.238 brouard 10296: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 10297: strcpy(gplotlabel,"(");
1.337 brouard 10298: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10299: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10300: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10301: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
10302: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
10303: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
10304: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10305: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10306: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10307: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
10308: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10309: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10310: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10311: /* } */
10312: /* /\* for(k=1; k <= ncovds; k++){ *\/ */
10313: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10314: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
10315: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
10316: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 10317: }
1.264 brouard 10318: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 10319: fprintf(ficgp,"\n#\n");
1.223 brouard 10320: if(invalidvarcomb[k1]){
10321: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10322: continue;
10323: }
1.219 brouard 10324:
1.241 brouard 10325: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 10326: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 10327: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
10328: if(vpopbased==0){
1.360 brouard 10329: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nunset ytics; unset y2tics; set ytics nomirror; set y2tics 0,10,100;set y2range [0:100];\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 10330: }else
1.238 brouard 10331: fprintf(ficgp,"\nreplot ");
1.360 brouard 10332: for (i=1; i<= nlstate+1 ; i ++) { /* For state i-1=0 is LE, while i-1=1 to nlstate are origin state */
1.238 brouard 10333: k=2*i;
1.360 brouard 10334: fprintf(ficgp,"\"%s\" every :::%d::%d u 1:($2==%d && $4!=0 ?$4 : 1/0) \"%%lf %%lf %%lf",subdirf2(fileresu,"T_"),nres-1,nres-1, vpopbased); /* for fixed variables age, popbased, mobilav */
10335: for (j=1; j<= nlstate+1 ; j ++) { /* e.. e.1 e.2 again j-1 is the state of end, wlim_i eij*/
10336: if (j==i) fprintf(ficgp," %%lf (%%lf)"); /* We want to read e.. i=1,j=1, e.1 i=2,j=2, e.2 i=3,j=3 */
10337: else fprintf(ficgp," %%*lf (%%*lf)"); /* skipping that field with a star */
1.238 brouard 10338: }
10339: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
1.360 brouard 10340: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1); /* state=i-1=1 to nlstate */
1.261 brouard 10341: fprintf(ficgp,"\"%s\" every :::%d::%d u 1:($2==%d && $4!=0 ? $4-$5*2 : 1/0) \"%%lf %%lf %%lf",subdirf2(fileresu,"T_"),nres-1,nres-1,vpopbased);
1.238 brouard 10342: for (j=1; j<= nlstate+1 ; j ++) {
10343: if (j==i) fprintf(ficgp," %%lf (%%lf)");
10344: else fprintf(ficgp," %%*lf (%%*lf)");
10345: }
10346: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 10347: fprintf(ficgp,"\"%s\" every :::%d::%d u 1:($2==%d && $4!=0 ? $4+$5*2 : 1/0) \"%%lf %%lf %%lf",subdirf2(fileresu,"T_"),nres-1,nres-1,vpopbased);
1.238 brouard 10348: for (j=1; j<= nlstate+1 ; j ++) {
10349: if (j==i) fprintf(ficgp," %%lf (%%lf)");
10350: else fprintf(ficgp," %%*lf (%%*lf)");
10351: }
1.360 brouard 10352: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0,\\\n"); /* ,\\\n added for th percentage graphs */
1.238 brouard 10353: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
10354: } /* state */
1.360 brouard 10355: /* again for the percentag spent in state i-1=1 to i-1=nlstate */
10356: for (i=2; i<= nlstate+1 ; i ++) { /* For state i-1=0 is LE, while i-1=1 to nlstate are origin state */
10357: k=2*i;
10358: fprintf(ficgp,"\"%s\" every :::%d::%d u 1:($2==%d && ($4)<=1 && ($4)>=0 ?($4)*100. : 1/0) \"%%lf %%lf %%lf",subdirf2(fileresu,"T_"),nres-1,nres-1, vpopbased); /* for fixed variables age, popbased, mobilav */
10359: for (j=1; j<= nlstate ; j ++)
10360: fprintf(ficgp," %%*lf (%%*lf)"); /* Skipping TLE and LE to read %LE only */
10361: for (j=1; j<= nlstate+1 ; j ++) { /* e.. e.1 e.2 again j-1 is the state of end, wlim_i eij*/
10362: if (j==i) fprintf(ficgp," %%lf (%%lf)"); /* We want to read e.. i=1,j=1, e.1 i=2,j=2, e.2 i=3,j=3 */
10363: else fprintf(ficgp," %%*lf (%%*lf)"); /* skipping that field with a star */
10364: }
10365: if (i== 1) fprintf(ficgp,"\" t\"%%TLE\" w l lt %d axis x1y2, \\\n",i); /* Not used */
10366: else fprintf(ficgp,"\" t\"%%LE in state (%d)\" w l lw 2 lt %d axis x1y2, \\\n",i-1,i+1); /* state=i-1=1 to nlstate */
10367: fprintf(ficgp,"\"%s\" every :::%d::%d u 1:($2==%d && ($4-$5*2)<=1 && ($4-$5*2)>=0? ($4-$5*2)*100. : 1/0) \"%%lf %%lf %%lf",subdirf2(fileresu,"T_"),nres-1,nres-1,vpopbased);
10368: for (j=1; j<= nlstate ; j ++)
10369: fprintf(ficgp," %%*lf (%%*lf)"); /* Skipping TLE and LE to read %LE only */
10370: for (j=1; j<= nlstate+1 ; j ++) {
10371: if (j==i) fprintf(ficgp," %%lf (%%lf)");
10372: else fprintf(ficgp," %%*lf (%%*lf)");
10373: }
10374: fprintf(ficgp,"\" t\"\" w l lt 0 axis x1y2,");
10375: fprintf(ficgp,"\"%s\" every :::%d::%d u 1:($2==%d && ($4+$5*2)<=1 && ($4+$5*2)>=0 ? ($4+$5*2)*100. : 1/0) \"%%lf %%lf %%lf",subdirf2(fileresu,"T_"),nres-1,nres-1,vpopbased);
10376: for (j=1; j<= nlstate ; j ++)
10377: fprintf(ficgp," %%*lf (%%*lf)"); /* Skipping TLE and LE to read %LE only */
10378: for (j=1; j<= nlstate+1 ; j ++) {
10379: if (j==i) fprintf(ficgp," %%lf (%%lf)");
10380: else fprintf(ficgp," %%*lf (%%*lf)");
10381: }
10382: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0 axis x1y2");
10383: else fprintf(ficgp,"\" t\"\" w l lt 0 axis x1y2,\\\n");
10384: } /* state for percent */
1.238 brouard 10385: } /* vpopbased */
1.264 brouard 10386: fprintf(ficgp,"\nset out;set out \"%s_%d-%d.svg\"; replot; set out; unset label;\n",subdirf2(optionfilefiname,"E_"),k1,nres); /* Buggy gnuplot */
1.238 brouard 10387: } /* end nres */
1.337 brouard 10388: /* } /\* k1 end 2 eme*\/ */
1.238 brouard 10389:
10390:
10391: /*3eme*/
1.337 brouard 10392: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 10393: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10394: k1=TKresult[nres];
1.338 brouard 10395: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 10396: /* if(m != 1 && TKresult[nres]!= k1) */
10397: /* continue; */
1.238 brouard 10398:
1.332 brouard 10399: for (cpt=1; cpt<= nlstate ; cpt ++) { /* Fragile no verification of covariate values */
1.261 brouard 10400: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 10401: strcpy(gplotlabel,"(");
1.337 brouard 10402: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10403: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10404: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10405: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
10406: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
10407: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
10408: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10409: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10410: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10411: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
10412: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10413: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10414: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10415: /* } */
10416: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10417: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
10418: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
10419: }
1.264 brouard 10420: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 10421: fprintf(ficgp,"\n#\n");
10422: if(invalidvarcomb[k1]){
10423: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10424: continue;
10425: }
10426:
10427: /* k=2+nlstate*(2*cpt-2); */
10428: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 10429: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 10430: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 10431: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 10432: plot [%.f:%.f] \"%s\" every :::%d::%d u 1:%d t \"e%d1\" w l",ageminpar,fage,subdirf2(fileresu,"E_"),nres-1,nres-1,k,cpt);
1.238 brouard 10433: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
10434: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
10435: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
10436: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
10437: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
10438: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 10439:
1.238 brouard 10440: */
10441: for (i=1; i< nlstate ; i ++) {
1.261 brouard 10442: fprintf(ficgp," ,\"%s\" every :::%d::%d u 1:%d t \"e%d%d\" w l",subdirf2(fileresu,"E_"),nres-1,nres-1,k+i,cpt,i+1);
1.238 brouard 10443: /* fprintf(ficgp," ,\"%s\" every :::%d::%d u 1:%d t \"e%d%d\" w l",subdirf2(fileres,"e"),k1-1,k1-1,k+2*i,cpt,i+1);*/
1.219 brouard 10444:
1.238 brouard 10445: }
1.261 brouard 10446: fprintf(ficgp," ,\"%s\" every :::%d::%d u 1:%d t \"e%d.\" w l",subdirf2(fileresu,"E_"),nres-1,nres-1,k+nlstate,cpt);
1.238 brouard 10447: }
1.264 brouard 10448: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 10449: } /* end nres */
1.337 brouard 10450: /* } /\* end kl 3eme *\/ */
1.126 brouard 10451:
1.223 brouard 10452: /* 4eme */
1.201 brouard 10453: /* Survival functions (period) from state i in state j by initial state i */
1.337 brouard 10454: /* for (k1=1; k1<=m; k1++){ /\* For each covariate and each value *\/ */
1.238 brouard 10455: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10456: k1=TKresult[nres];
1.338 brouard 10457: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 10458: /* if(m != 1 && TKresult[nres]!= k1) */
10459: /* continue; */
1.238 brouard 10460: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 10461: strcpy(gplotlabel,"(");
1.337 brouard 10462: fprintf(ficgp,"\n#\n#\n# Survival functions in state %d : 'LIJ_' files, cov=%d state=%d", cpt, k1, cpt);
10463: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10464: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10465: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10466: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
10467: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
10468: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
10469: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10470: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10471: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10472: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
10473: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10474: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10475: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10476: /* } */
10477: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10478: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
10479: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 10480: }
1.264 brouard 10481: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 10482: fprintf(ficgp,"\n#\n");
10483: if(invalidvarcomb[k1]){
10484: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10485: continue;
1.223 brouard 10486: }
1.238 brouard 10487:
1.241 brouard 10488: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 10489: fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
1.238 brouard 10490: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
10491: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
10492: k=3;
10493: for (i=1; i<= nlstate ; i ++){
10494: if(i==1){
10495: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
10496: }else{
10497: fprintf(ficgp,", '' ");
10498: }
10499: l=(nlstate+ndeath)*(i-1)+1;
10500: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
10501: for (j=2; j<= nlstate+ndeath ; j ++)
10502: fprintf(ficgp,"+$%d",k+l+j-1);
10503: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
10504: } /* nlstate */
1.264 brouard 10505: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 10506: } /* end cpt state*/
10507: } /* end nres */
1.337 brouard 10508: /* } /\* end covariate k1 *\/ */
1.238 brouard 10509:
1.220 brouard 10510: /* 5eme */
1.201 brouard 10511: /* Survival functions (period) from state i in state j by final state j */
1.337 brouard 10512: /* for (k1=1; k1<= m ; k1++){ /\* For each covariate combination if any *\/ */
1.238 brouard 10513: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10514: k1=TKresult[nres];
1.338 brouard 10515: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 10516: /* if(m != 1 && TKresult[nres]!= k1) */
10517: /* continue; */
1.238 brouard 10518: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 10519: strcpy(gplotlabel,"(");
1.238 brouard 10520: fprintf(ficgp,"\n#\n#\n# Survival functions in state j and all livestates from state i by final state j: 'lij' files, cov=%d state=%d",k1, cpt);
1.337 brouard 10521: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10522: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10523: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10524: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
10525: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
10526: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
10527: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10528: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10529: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10530: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
10531: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10532: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10533: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10534: /* } */
10535: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10536: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
10537: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 10538: }
1.264 brouard 10539: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 10540: fprintf(ficgp,"\n#\n");
10541: if(invalidvarcomb[k1]){
10542: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10543: continue;
10544: }
1.227 brouard 10545:
1.241 brouard 10546: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 10547: fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
1.238 brouard 10548: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
10549: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
10550: k=3;
10551: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
10552: if(j==1)
10553: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
10554: else
10555: fprintf(ficgp,", '' ");
10556: l=(nlstate+ndeath)*(cpt-1) +j;
10557: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
10558: /* for (i=2; i<= nlstate+ndeath ; i ++) */
10559: /* fprintf(ficgp,"+$%d",k+l+i-1); */
10560: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
10561: } /* nlstate */
10562: fprintf(ficgp,", '' ");
10563: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
10564: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
10565: l=(nlstate+ndeath)*(cpt-1) +j;
10566: if(j < nlstate)
10567: fprintf(ficgp,"$%d +",k+l);
10568: else
10569: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
10570: }
1.264 brouard 10571: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 10572: } /* end cpt state*/
1.337 brouard 10573: /* } /\* end covariate *\/ */
1.238 brouard 10574: } /* end nres */
1.227 brouard 10575:
1.220 brouard 10576: /* 6eme */
1.202 brouard 10577: /* CV preval stable (period) for each covariate */
1.337 brouard 10578: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 10579: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10580: k1=TKresult[nres];
1.338 brouard 10581: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 10582: /* if(m != 1 && TKresult[nres]!= k1) */
10583: /* continue; */
1.255 brouard 10584: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 10585: strcpy(gplotlabel,"(");
1.288 brouard 10586: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 10587: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10588: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10589: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10590: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
10591: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
10592: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
10593: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10594: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10595: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10596: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
10597: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10598: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10599: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10600: /* } */
10601: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10602: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
10603: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 10604: }
1.264 brouard 10605: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 10606: fprintf(ficgp,"\n#\n");
1.223 brouard 10607: if(invalidvarcomb[k1]){
1.227 brouard 10608: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10609: continue;
1.223 brouard 10610: }
1.227 brouard 10611:
1.241 brouard 10612: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 10613: fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
1.126 brouard 10614: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 10615: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 10616: k=3; /* Offset */
1.255 brouard 10617: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 10618: if(i==1)
10619: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
10620: else
10621: fprintf(ficgp,", '' ");
1.255 brouard 10622: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 10623: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
10624: for (j=2; j<= nlstate ; j ++)
10625: fprintf(ficgp,"+$%d",k+l+j-1);
10626: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 10627: } /* nlstate */
1.264 brouard 10628: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 10629: } /* end cpt state*/
10630: } /* end covariate */
1.227 brouard 10631:
10632:
1.220 brouard 10633: /* 7eme */
1.296 brouard 10634: if(prevbcast == 1){
1.288 brouard 10635: /* CV backward prevalence for each covariate */
1.337 brouard 10636: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 10637: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10638: k1=TKresult[nres];
1.338 brouard 10639: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 10640: /* if(m != 1 && TKresult[nres]!= k1) */
10641: /* continue; */
1.268 brouard 10642: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 10643: strcpy(gplotlabel,"(");
1.288 brouard 10644: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 10645: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10646: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10647: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10648: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
10649: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
10650: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
10651: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10652: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10653: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10654: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
10655: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10656: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10657: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10658: /* } */
10659: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10660: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
10661: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 10662: }
1.264 brouard 10663: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 10664: fprintf(ficgp,"\n#\n");
10665: if(invalidvarcomb[k1]){
10666: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10667: continue;
10668: }
10669:
1.241 brouard 10670: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 10671: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
1.227 brouard 10672: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 10673: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 10674: k=3; /* Offset */
1.268 brouard 10675: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 10676: if(i==1)
10677: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
10678: else
10679: fprintf(ficgp,", '' ");
10680: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 10681: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.324 brouard 10682: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
10683: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l+(cpt-1)+i-1); /\* a vérifier *\/ */
1.255 brouard 10684: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 10685: /* for (j=2; j<= nlstate ; j ++) */
10686: /* fprintf(ficgp,"+$%d",k+l+j-1); */
10687: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 10688: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 10689: } /* nlstate */
1.264 brouard 10690: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 10691: } /* end cpt state*/
10692: } /* end covariate */
1.296 brouard 10693: } /* End if prevbcast */
1.218 brouard 10694:
1.223 brouard 10695: /* 8eme */
1.218 brouard 10696: if(prevfcast==1){
1.288 brouard 10697: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 10698:
1.337 brouard 10699: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 10700: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10701: k1=TKresult[nres];
1.338 brouard 10702: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 10703: /* if(m != 1 && TKresult[nres]!= k1) */
10704: /* continue; */
1.211 brouard 10705: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 10706: strcpy(gplotlabel,"(");
1.288 brouard 10707: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 10708: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10709: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10710: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10711: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
10712: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
10713: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
10714: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10715: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10716: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10717: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
10718: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10719: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10720: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10721: /* } */
10722: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10723: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
10724: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 10725: }
1.264 brouard 10726: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 10727: fprintf(ficgp,"\n#\n");
10728: if(invalidvarcomb[k1]){
10729: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10730: continue;
10731: }
10732:
10733: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 10734: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 10735: fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
1.227 brouard 10736: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 10737: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 10738:
10739: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
10740: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
10741: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
10742: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 10743: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
10744: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
10745: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
10746: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 10747: if(i==istart){
1.227 brouard 10748: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
10749: }else{
10750: fprintf(ficgp,",\\\n '' ");
10751: }
10752: if(cptcoveff ==0){ /* No covariate */
10753: ioffset=2; /* Age is in 2 */
10754: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
10755: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
10756: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
10757: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
10758: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 10759: if(i==nlstate+1){
1.270 brouard 10760: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 10761: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
10762: fprintf(ficgp,",\\\n '' ");
10763: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 10764: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 10765: offyear, \
1.268 brouard 10766: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 10767: }else
1.227 brouard 10768: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
10769: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
10770: }else{ /* more than 2 covariates */
1.270 brouard 10771: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
10772: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
10773: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
10774: iyearc=ioffset-1;
10775: iagec=ioffset;
1.227 brouard 10776: fprintf(ficgp," u %d:(",ioffset);
10777: kl=0;
10778: strcpy(gplotcondition,"(");
1.351 brouard 10779: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate writing the chain of conditions *\/ */
1.332 brouard 10780: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
1.351 brouard 10781: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10782: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
10783: lv=Tvresult[nres][k];
10784: vlv=TinvDoQresult[nres][Tvresult[nres][k]];
1.227 brouard 10785: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
10786: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
10787: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 10788: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
1.351 brouard 10789: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
1.227 brouard 10790: kl++;
1.364 ! brouard 10791: /* Problem with quantitative variables TinvDoQresult[nres] */
1.351 brouard 10792: /* sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); */
1.364 ! brouard 10793: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%lg " ,kl,lv, kl+1, vlv );/* Solved but quantitative must be shifted */
1.227 brouard 10794: kl++;
1.351 brouard 10795: if(k <cptcovs && cptcovs>1)
1.227 brouard 10796: sprintf(gplotcondition+strlen(gplotcondition)," && ");
10797: }
10798: strcpy(gplotcondition+strlen(gplotcondition),")");
10799: /* kl=6+(cpt-1)*(nlstate+1)+1+(i-1); /\* 6+(1-1)*(2+1)+1+(1-1)=7, 6+(2-1)(2+1)+1+(1-1)=10 *\/ */
10800: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
10801: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
10802: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
10803: if(i==nlstate+1){
1.270 brouard 10804: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
10805: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 10806: fprintf(ficgp,",\\\n '' ");
1.364 ! brouard 10807: fprintf(ficgp," u %d:(",iagec); /* Below iyearc should be increades if quantitative variable in the reult line */
! 10808: /* $7==6 && $8==2.47 ) && (($9-$10) == 1953 ) ? $12/(1.-$24) : 1/0):7 with labels center not */
! 10809: /* but was && $7==6 && $8==2 ) && (($7-$8) == 1953 ) ? $12/(1.-$24) : 1/0):7 with labels center not */
1.270 brouard 10810: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
10811: iyearc, iagec, offyear, \
10812: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 10813: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
1.227 brouard 10814: }else{
10815: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
10816: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
10817: }
10818: } /* end if covariate */
10819: } /* nlstate */
1.264 brouard 10820: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 10821: } /* end cpt state*/
10822: } /* end covariate */
10823: } /* End if prevfcast */
1.227 brouard 10824:
1.296 brouard 10825: if(prevbcast==1){
1.268 brouard 10826: /* Back projection from cross-sectional to stable (mixed) for each covariate */
10827:
1.337 brouard 10828: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.268 brouard 10829: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10830: k1=TKresult[nres];
1.338 brouard 10831: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 10832: /* if(m != 1 && TKresult[nres]!= k1) */
10833: /* continue; */
1.268 brouard 10834: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
10835: strcpy(gplotlabel,"(");
10836: fprintf(ficgp,"\n#\n#\n#Back projection of prevalence to stable (mixed) back prevalence: 'BPROJ_' files, covariatecombination#=%d originstate=%d",k1, cpt);
1.337 brouard 10837: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10838: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10839: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10840: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
10841: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
10842: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
10843: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10844: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10845: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10846: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
10847: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10848: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10849: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10850: /* } */
10851: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10852: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
10853: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.268 brouard 10854: }
10855: strcpy(gplotlabel+strlen(gplotlabel),")");
10856: fprintf(ficgp,"\n#\n");
10857: if(invalidvarcomb[k1]){
10858: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10859: continue;
10860: }
10861:
10862: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
10863: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
10864: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
10865: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
10866: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
10867:
10868: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
10869: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
10870: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
10871: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
10872: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
10873: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
10874: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
10875: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
10876: if(i==istart){
10877: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
10878: }else{
10879: fprintf(ficgp,",\\\n '' ");
10880: }
1.351 brouard 10881: /* if(cptcoveff ==0){ /\* No covariate *\/ */
10882: if(cptcovs ==0){ /* No covariate */
1.268 brouard 10883: ioffset=2; /* Age is in 2 */
10884: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
10885: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
10886: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
10887: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
10888: fprintf(ficgp," u %d:(", ioffset);
10889: if(i==nlstate+1){
1.270 brouard 10890: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 10891: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
10892: fprintf(ficgp,",\\\n '' ");
10893: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 10894: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 10895: offbyear, \
10896: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
10897: }else
10898: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
10899: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
10900: }else{ /* more than 2 covariates */
1.270 brouard 10901: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
10902: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
10903: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
10904: iyearc=ioffset-1;
10905: iagec=ioffset;
1.268 brouard 10906: fprintf(ficgp," u %d:(",ioffset);
10907: kl=0;
10908: strcpy(gplotcondition,"(");
1.337 brouard 10909: for (k=1; k<=cptcovs; k++){ /* For each covariate k of the resultline, get corresponding value lv for combination k1 */
1.338 brouard 10910: if(Dummy[modelresult[nres][k]]==0){ /* To be verified */
1.337 brouard 10911: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate writing the chain of conditions *\/ */
10912: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
10913: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
10914: lv=Tvresult[nres][k];
10915: vlv=TinvDoQresult[nres][Tvresult[nres][k]];
10916: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
10917: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
10918: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
10919: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
10920: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10921: kl++;
10922: /* sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); */
10923: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%lg " ,kl,Tvresult[nres][k], kl+1,TinvDoQresult[nres][Tvresult[nres][k]]);
10924: kl++;
1.338 brouard 10925: if(k <cptcovs && cptcovs>1)
1.337 brouard 10926: sprintf(gplotcondition+strlen(gplotcondition)," && ");
10927: }
1.268 brouard 10928: }
10929: strcpy(gplotcondition+strlen(gplotcondition),")");
10930: /* kl=6+(cpt-1)*(nlstate+1)+1+(i-1); /\* 6+(1-1)*(2+1)+1+(1-1)=7, 6+(2-1)(2+1)+1+(1-1)=10 *\/ */
10931: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
10932: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
10933: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
10934: if(i==nlstate+1){
1.270 brouard 10935: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
10936: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 10937: fprintf(ficgp,",\\\n '' ");
1.270 brouard 10938: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 10939: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 10940: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
10941: iyearc,iagec,offbyear, \
10942: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 10943: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
10944: }else{
10945: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
10946: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
10947: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
10948: }
10949: } /* end if covariate */
10950: } /* nlstate */
10951: fprintf(ficgp,"\nset out; unset label;\n");
10952: } /* end cpt state*/
10953: } /* end covariate */
1.296 brouard 10954: } /* End if prevbcast */
1.268 brouard 10955:
1.227 brouard 10956:
1.238 brouard 10957: /* 9eme writing MLE parameters */
10958: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 10959: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 10960: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 10961: for(k=1; k <=(nlstate+ndeath); k++){
10962: if (k != i) {
1.227 brouard 10963: fprintf(ficgp,"# current state %d\n",k);
10964: for(j=1; j <=ncovmodel; j++){
10965: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
10966: jk++;
10967: }
10968: fprintf(ficgp,"\n");
1.126 brouard 10969: }
10970: }
1.223 brouard 10971: }
1.187 brouard 10972: fprintf(ficgp,"##############\n#\n");
1.227 brouard 10973:
1.145 brouard 10974: /*goto avoid;*/
1.238 brouard 10975: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
10976: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 10977: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
10978: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
10979: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
10980: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
10981: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
10982: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
10983: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
10984: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
10985: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
10986: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
10987: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
10988: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
10989: fprintf(ficgp,"#\n");
1.223 brouard 10990: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 10991: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.338 brouard 10992: fprintf(ficgp,"#model=1+age+%s \n",model);
1.238 brouard 10993: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.351 brouard 10994: /* fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/\* to be checked *\/ */
10995: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcovs,m);/* to be checked */
1.337 brouard 10996: /* for(k1=1; k1 <=m; k1++) /\* For each combination of covariate *\/ */
1.237 brouard 10997: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10998: /* k1=nres; */
1.338 brouard 10999: k1=TKresult[nres];
11000: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 11001: fprintf(ficgp,"\n\n# Resultline k1=%d ",k1);
1.264 brouard 11002: strcpy(gplotlabel,"(");
1.276 brouard 11003: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.337 brouard 11004: for (k=1; k<=cptcovs; k++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
11005: /* for each resultline nres, and position k, Tvresult[nres][k] gives the name of the variable and
11006: TinvDoQresult[nres][Tvresult[nres][k]] gives its value double or integer) */
11007: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
11008: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
11009: }
11010: /* if(m != 1 && TKresult[nres]!= k1) */
11011: /* continue; */
11012: /* fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1); */
11013: /* strcpy(gplotlabel,"("); */
11014: /* /\*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*\/ */
11015: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
11016: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
11017: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
11018: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
11019: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
11020: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
11021: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
11022: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
11023: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
11024: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
11025: /* } */
11026: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
11027: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
11028: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
11029: /* } */
1.264 brouard 11030: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 11031: fprintf(ficgp,"\n#\n");
1.264 brouard 11032: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 11033: fprintf(ficgp,"\nset key outside ");
11034: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
11035: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 11036: fprintf(ficgp,"\nset ter svg size 640, 480 ");
11037: if (ng==1){
11038: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
11039: fprintf(ficgp,"\nunset log y");
11040: }else if (ng==2){
11041: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
11042: fprintf(ficgp,"\nset log y");
11043: }else if (ng==3){
11044: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
11045: fprintf(ficgp,"\nset log y");
11046: }else
11047: fprintf(ficgp,"\nunset title ");
11048: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
11049: i=1;
11050: for(k2=1; k2<=nlstate; k2++) {
11051: k3=i;
11052: for(k=1; k<=(nlstate+ndeath); k++) {
11053: if (k != k2){
11054: switch( ng) {
11055: case 1:
11056: if(nagesqr==0)
11057: fprintf(ficgp," p%d+p%d*x",i,i+1);
11058: else /* nagesqr =1 */
11059: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
11060: break;
11061: case 2: /* ng=2 */
11062: if(nagesqr==0)
11063: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
11064: else /* nagesqr =1 */
11065: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
11066: break;
11067: case 3:
11068: if(nagesqr==0)
11069: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
11070: else /* nagesqr =1 */
11071: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
11072: break;
11073: }
11074: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 11075: ijp=1; /* product no age */
11076: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
11077: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 11078: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.329 brouard 11079: switch(Typevar[j]){
11080: case 1:
11081: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
11082: if(j==Tage[ij]) { /* Product by age To be looked at!!*//* Bug valgrind */
11083: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
11084: if(DummyV[j]==0){/* Bug valgrind */
11085: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
11086: }else{ /* quantitative */
11087: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
11088: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
11089: }
11090: ij++;
1.268 brouard 11091: }
1.237 brouard 11092: }
1.329 brouard 11093: }
11094: break;
11095: case 2:
11096: if(cptcovprod >0){
11097: if(j==Tprod[ijp]) { /* */
11098: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
11099: if(ijp <=cptcovprod) { /* Product */
11100: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
11101: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
11102: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],nbcode[Tvard[ijp][2]][codtabm(k1,j)]); */
11103: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
11104: }else{ /* Vn is dummy and Vm is quanti */
11105: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
11106: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
11107: }
11108: }else{ /* Vn*Vm Vn is quanti */
11109: if(DummyV[Tvard[ijp][2]]==0){
11110: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
11111: }else{ /* Both quanti */
11112: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
11113: }
1.268 brouard 11114: }
1.329 brouard 11115: ijp++;
1.237 brouard 11116: }
1.329 brouard 11117: } /* end Tprod */
11118: }
11119: break;
1.349 brouard 11120: case 3:
11121: if(cptcovdageprod >0){
11122: /* if(j==Tprod[ijp]) { */ /* not necessary */
11123: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
1.350 brouard 11124: if(ijp <=cptcovprod) { /* Product Vn*Vm and age*VN*Vm*/
11125: if(DummyV[Tvardk[ijp][1]]==0){/* Vn is dummy */
11126: if(DummyV[Tvardk[ijp][2]]==0){/* Vn and Vm are dummy */
1.349 brouard 11127: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],nbcode[Tvard[ijp][2]][codtabm(k1,j)]); */
11128: fprintf(ficgp,"+p%d*%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
11129: }else{ /* Vn is dummy and Vm is quanti */
11130: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
1.350 brouard 11131: fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvardk[ijp][1]],Tqinvresult[nres][Tvardk[ijp][2]]);
1.349 brouard 11132: }
1.350 brouard 11133: }else{ /* age* Vn*Vm Vn is quanti HERE */
1.349 brouard 11134: if(DummyV[Tvard[ijp][2]]==0){
1.350 brouard 11135: fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvardk[ijp][2]],Tqinvresult[nres][Tvardk[ijp][1]]);
1.349 brouard 11136: }else{ /* Both quanti */
1.350 brouard 11137: fprintf(ficgp,"+p%d*%f*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvardk[ijp][1]],Tqinvresult[nres][Tvardk[ijp][2]]);
1.349 brouard 11138: }
11139: }
11140: ijp++;
11141: }
11142: /* } */ /* end Tprod */
11143: }
11144: break;
1.329 brouard 11145: case 0:
11146: /* simple covariate */
1.264 brouard 11147: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 11148: if(Dummy[j]==0){
11149: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
11150: }else{ /* quantitative */
11151: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 11152: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 11153: }
1.329 brouard 11154: /* end simple */
11155: break;
11156: default:
11157: break;
11158: } /* end switch */
1.237 brouard 11159: } /* end j */
1.329 brouard 11160: }else{ /* k=k2 */
11161: if(ng !=1 ){ /* For logit formula of log p11 is more difficult to get */
11162: fprintf(ficgp," (1.");i=i-ncovmodel;
11163: }else
11164: i=i-ncovmodel;
1.223 brouard 11165: }
1.227 brouard 11166:
1.223 brouard 11167: if(ng != 1){
11168: fprintf(ficgp,")/(1");
1.227 brouard 11169:
1.264 brouard 11170: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 11171: if(nagesqr==0)
1.264 brouard 11172: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 11173: else /* nagesqr =1 */
1.264 brouard 11174: fprintf(ficgp,"+exp(p%d+p%d*x+p%d*x*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1,k3+(cpt-1)*ncovmodel+1+nagesqr);
1.217 brouard 11175:
1.223 brouard 11176: ij=1;
1.329 brouard 11177: ijp=1;
11178: /* for(j=3; j <=ncovmodel-nagesqr; j++){ */
11179: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
11180: switch(Typevar[j]){
11181: case 1:
11182: if(cptcovage >0){
11183: if(j==Tage[ij]) { /* Bug valgrind */
11184: if(ij <=cptcovage) { /* Bug valgrind */
11185: if(DummyV[j]==0){/* Bug valgrind */
11186: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]); */
11187: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,nbcode[Tvar[j]][codtabm(k1,j)]); */
11188: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]);
11189: /* fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);; */
11190: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
11191: }else{ /* quantitative */
11192: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
11193: fprintf(ficgp,"+p%d*%f*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
11194: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
11195: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
11196: }
11197: ij++;
11198: }
11199: }
11200: }
11201: break;
11202: case 2:
11203: if(cptcovprod >0){
11204: if(j==Tprod[ijp]) { /* */
11205: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
11206: if(ijp <=cptcovprod) { /* Product */
11207: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
11208: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
11209: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],nbcode[Tvard[ijp][2]][codtabm(k1,j)]); */
11210: fprintf(ficgp,"+p%d*%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
11211: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
11212: }else{ /* Vn is dummy and Vm is quanti */
11213: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
11214: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
11215: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
11216: }
11217: }else{ /* Vn*Vm Vn is quanti */
11218: if(DummyV[Tvard[ijp][2]]==0){
11219: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
11220: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
11221: }else{ /* Both quanti */
11222: fprintf(ficgp,"+p%d*%f*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
11223: /* fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
11224: }
11225: }
11226: ijp++;
11227: }
11228: } /* end Tprod */
11229: } /* end if */
11230: break;
1.349 brouard 11231: case 3:
11232: if(cptcovdageprod >0){
11233: /* if(j==Tprod[ijp]) { /\* *\/ */
11234: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
11235: if(ijp <=cptcovprod) { /* Product */
1.350 brouard 11236: if(DummyV[Tvardk[ijp][1]]==0){/* Vn is dummy */
11237: if(DummyV[Tvardk[ijp][2]]==0){/* Vn and Vm are dummy */
1.349 brouard 11238: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],nbcode[Tvard[ijp][2]][codtabm(k1,j)]); */
1.350 brouard 11239: fprintf(ficgp,"+p%d*%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvardk[ijp][1]],Tinvresult[nres][Tvardk[ijp][2]]);
1.349 brouard 11240: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
11241: }else{ /* Vn is dummy and Vm is quanti */
11242: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
1.350 brouard 11243: fprintf(ficgp,"+p%d*%d*%f*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvardk[ijp][1]],Tqinvresult[nres][Tvardk[ijp][2]]);
1.349 brouard 11244: /* fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
11245: }
11246: }else{ /* Vn*Vm Vn is quanti */
1.350 brouard 11247: if(DummyV[Tvardk[ijp][2]]==0){
11248: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvardk[ijp][2]],Tqinvresult[nres][Tvardk[ijp][1]]);
1.349 brouard 11249: /* fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
11250: }else{ /* Both quanti */
1.350 brouard 11251: fprintf(ficgp,"+p%d*%f*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvardk[ijp][1]],Tqinvresult[nres][Tvardk[ijp][2]]);
1.349 brouard 11252: /* fprintf(ficgp,"+p%d*%f*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
11253: }
11254: }
11255: ijp++;
11256: }
11257: /* } /\* end Tprod *\/ */
11258: } /* end if */
11259: break;
1.329 brouard 11260: case 0:
11261: /* simple covariate */
11262: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
11263: if(Dummy[j]==0){
11264: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
11265: fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]); /* */
11266: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
11267: }else{ /* quantitative */
11268: fprintf(ficgp,"+p%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* */
11269: /* fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* *\/ */
11270: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
11271: }
11272: /* end simple */
11273: /* fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);/\* Valgrind bug nbcode *\/ */
11274: break;
11275: default:
11276: break;
11277: } /* end switch */
1.223 brouard 11278: }
11279: fprintf(ficgp,")");
11280: }
11281: fprintf(ficgp,")");
11282: if(ng ==2)
1.276 brouard 11283: fprintf(ficgp," w l lw 2 lt (%d*%d+%d)%%%d+1 dt %d t \"p%d%d\" ", nlstate+ndeath, k2, k, nlstate+ndeath, k2, k2,k);
1.223 brouard 11284: else /* ng= 3 */
1.276 brouard 11285: fprintf(ficgp," w l lw 2 lt (%d*%d+%d)%%%d+1 dt %d t \"i%d%d\" ", nlstate+ndeath, k2, k, nlstate+ndeath, k2, k2,k);
1.329 brouard 11286: }else{ /* end ng <> 1 */
1.223 brouard 11287: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 11288: fprintf(ficgp," w l lw 2 lt (%d*%d+%d)%%%d+1 dt %d t \"logit(p%d%d)\" ", nlstate+ndeath, k2, k, nlstate+ndeath, k2, k2,k);
1.223 brouard 11289: }
11290: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
11291: fprintf(ficgp,",");
11292: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
11293: fprintf(ficgp,",");
11294: i=i+ncovmodel;
11295: } /* end k */
11296: } /* end k2 */
1.276 brouard 11297: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
11298: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.337 brouard 11299: } /* end resultline */
1.223 brouard 11300: } /* end ng */
11301: /* avoid: */
11302: fflush(ficgp);
1.126 brouard 11303: } /* end gnuplot */
11304:
11305:
11306: /*************** Moving average **************/
1.219 brouard 11307: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 11308: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 11309:
1.222 brouard 11310: int i, cpt, cptcod;
11311: int modcovmax =1;
11312: int mobilavrange, mob;
11313: int iage=0;
1.288 brouard 11314: int firstA1=0, firstA2=0;
1.222 brouard 11315:
1.266 brouard 11316: double sum=0., sumr=0.;
1.222 brouard 11317: double age;
1.266 brouard 11318: double *sumnewp, *sumnewm, *sumnewmr;
11319: double *agemingood, *agemaxgood;
11320: double *agemingoodr, *agemaxgoodr;
1.222 brouard 11321:
11322:
1.278 brouard 11323: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
11324: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 11325:
11326: sumnewp = vector(1,ncovcombmax);
11327: sumnewm = vector(1,ncovcombmax);
1.266 brouard 11328: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 11329: agemingood = vector(1,ncovcombmax);
1.266 brouard 11330: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 11331: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 11332: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 11333:
11334: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 11335: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 11336: sumnewp[cptcod]=0.;
1.266 brouard 11337: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
11338: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 11339: }
11340: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
11341:
1.266 brouard 11342: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
11343: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 11344: else mobilavrange=mobilav;
11345: for (age=bage; age<=fage; age++)
11346: for (i=1; i<=nlstate;i++)
11347: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
11348: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
11349: /* We keep the original values on the extreme ages bage, fage and for
11350: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
11351: we use a 5 terms etc. until the borders are no more concerned.
11352: */
11353: for (mob=3;mob <=mobilavrange;mob=mob+2){
11354: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 11355: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
11356: sumnewm[cptcod]=0.;
11357: for (i=1; i<=nlstate;i++){
1.222 brouard 11358: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
11359: for (cpt=1;cpt<=(mob-1)/2;cpt++){
11360: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
11361: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
11362: }
11363: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 11364: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
11365: } /* end i */
11366: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
11367: } /* end cptcod */
1.222 brouard 11368: }/* end age */
11369: }/* end mob */
1.266 brouard 11370: }else{
11371: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 11372: return -1;
1.266 brouard 11373: }
11374:
11375: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 11376: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
11377: if(invalidvarcomb[cptcod]){
11378: printf("\nCombination (%d) ignored because no cases \n",cptcod);
11379: continue;
11380: }
1.219 brouard 11381:
1.266 brouard 11382: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
11383: sumnewm[cptcod]=0.;
11384: sumnewmr[cptcod]=0.;
11385: for (i=1; i<=nlstate;i++){
11386: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
11387: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
11388: }
11389: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
11390: agemingoodr[cptcod]=age;
11391: }
11392: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
11393: agemingood[cptcod]=age;
11394: }
11395: } /* age */
11396: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 11397: sumnewm[cptcod]=0.;
1.266 brouard 11398: sumnewmr[cptcod]=0.;
1.222 brouard 11399: for (i=1; i<=nlstate;i++){
11400: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 11401: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
11402: }
11403: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
11404: agemaxgoodr[cptcod]=age;
1.222 brouard 11405: }
11406: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 11407: agemaxgood[cptcod]=age;
11408: }
11409: } /* age */
11410: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
11411: /* but they will change */
1.288 brouard 11412: firstA1=0;firstA2=0;
1.266 brouard 11413: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
11414: sumnewm[cptcod]=0.;
11415: sumnewmr[cptcod]=0.;
11416: for (i=1; i<=nlstate;i++){
11417: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
11418: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
11419: }
11420: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
11421: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
11422: agemaxgoodr[cptcod]=age; /* age min */
11423: for (i=1; i<=nlstate;i++)
11424: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
11425: }else{ /* bad we change the value with the values of good ages */
11426: for (i=1; i<=nlstate;i++){
11427: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
11428: } /* i */
11429: } /* end bad */
11430: }else{
11431: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
11432: agemaxgood[cptcod]=age;
11433: }else{ /* bad we change the value with the values of good ages */
11434: for (i=1; i<=nlstate;i++){
11435: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
11436: } /* i */
11437: } /* end bad */
11438: }/* end else */
11439: sum=0.;sumr=0.;
11440: for (i=1; i<=nlstate;i++){
11441: sum+=mobaverage[(int)age][i][cptcod];
11442: sumr+=probs[(int)age][i][cptcod];
11443: }
11444: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 11445: if(!firstA1){
11446: firstA1=1;
11447: printf("Moving average A1: For this combination of covariate cptcod=%d, we can't get a smoothed prevalence which sums to one (%f) at any descending age! age=%d, could you increase bage=%d. Others in log file...\n",cptcod,sumr, (int)age, (int)bage);
11448: }
11449: fprintf(ficlog,"Moving average A1: For this combination of covariate cptcod=%d, we can't get a smoothed prevalence which sums to one (%f) at any descending age! age=%d, could you increase bage=%d\n",cptcod,sumr, (int)age, (int)bage);
1.266 brouard 11450: } /* end bad */
11451: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
11452: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 11453: if(!firstA2){
11454: firstA2=1;
11455: printf("Moving average A2: For this combination of covariate cptcod=%d, the raw prevalence doesn't sums to one (%f) even with smoothed values at young ages! age=%d, could you increase bage=%d. Others in log file...\n",cptcod,sumr, (int)age, (int)bage);
11456: }
11457: fprintf(ficlog,"Moving average A2: For this combination of covariate cptcod=%d, the raw prevalence doesn't sums to one (%f) even with smoothed values at young ages! age=%d, could you increase bage=%d\n",cptcod,sumr, (int)age, (int)bage);
1.222 brouard 11458: } /* end bad */
11459: }/* age */
1.266 brouard 11460:
11461: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 11462: sumnewm[cptcod]=0.;
1.266 brouard 11463: sumnewmr[cptcod]=0.;
1.222 brouard 11464: for (i=1; i<=nlstate;i++){
11465: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 11466: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
11467: }
11468: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
11469: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
11470: agemingoodr[cptcod]=age;
11471: for (i=1; i<=nlstate;i++)
11472: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
11473: }else{ /* bad we change the value with the values of good ages */
11474: for (i=1; i<=nlstate;i++){
11475: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
11476: } /* i */
11477: } /* end bad */
11478: }else{
11479: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
11480: agemingood[cptcod]=age;
11481: }else{ /* bad */
11482: for (i=1; i<=nlstate;i++){
11483: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
11484: } /* i */
11485: } /* end bad */
11486: }/* end else */
11487: sum=0.;sumr=0.;
11488: for (i=1; i<=nlstate;i++){
11489: sum+=mobaverage[(int)age][i][cptcod];
11490: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 11491: }
1.266 brouard 11492: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 11493: printf("Moving average B1: For this combination of covariate cptcod=%d, we can't get a smoothed prevalence which sums to one (%f) at any descending age! age=%d, could you decrease fage=%d?\n",cptcod, sum, (int) age, (int)fage);
1.266 brouard 11494: } /* end bad */
11495: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
11496: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 11497: printf("Moving average B2: For this combination of covariate cptcod=%d, the raw prevalence doesn't sums to one (%f) even with smoothed values at young ages! age=%d, could you increase fage=%d\n",cptcod,sumr, (int)age, (int)fage);
1.222 brouard 11498: } /* end bad */
11499: }/* age */
1.266 brouard 11500:
1.222 brouard 11501:
11502: for (age=bage; age<=fage; age++){
1.235 brouard 11503: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 11504: sumnewp[cptcod]=0.;
11505: sumnewm[cptcod]=0.;
11506: for (i=1; i<=nlstate;i++){
11507: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
11508: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
11509: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
11510: }
11511: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
11512: }
11513: /* printf("\n"); */
11514: /* } */
1.266 brouard 11515:
1.222 brouard 11516: /* brutal averaging */
1.266 brouard 11517: /* for (i=1; i<=nlstate;i++){ */
11518: /* for (age=1; age<=bage; age++){ */
11519: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
11520: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
11521: /* } */
11522: /* for (age=fage; age<=AGESUP; age++){ */
11523: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
11524: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
11525: /* } */
11526: /* } /\* end i status *\/ */
11527: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
11528: /* for (age=1; age<=AGESUP; age++){ */
11529: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
11530: /* mobaverage[(int)age][i][cptcod]=0.; */
11531: /* } */
11532: /* } */
1.222 brouard 11533: }/* end cptcod */
1.266 brouard 11534: free_vector(agemaxgoodr,1, ncovcombmax);
11535: free_vector(agemaxgood,1, ncovcombmax);
11536: free_vector(agemingood,1, ncovcombmax);
11537: free_vector(agemingoodr,1, ncovcombmax);
11538: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 11539: free_vector(sumnewm,1, ncovcombmax);
11540: free_vector(sumnewp,1, ncovcombmax);
11541: return 0;
11542: }/* End movingaverage */
1.218 brouard 11543:
1.126 brouard 11544:
1.296 brouard 11545:
1.126 brouard 11546: /************** Forecasting ******************/
1.296 brouard 11547: /* void prevforecast(char fileres[], double dateintmean, double anprojd, double mprojd, double jprojd, double ageminpar, double agemax, double dateprev1, double dateprev2, int mobilav, double ***prev, double bage, double fage, int firstpass, int lastpass, double anprojf, double p[], int cptcoveff)*/
11548: void prevforecast(char fileres[], double dateintmean, double dateprojd, double dateprojf, double ageminpar, double agemax, double dateprev1, double dateprev2, int mobilav, double ***prev, double bage, double fage, int firstpass, int lastpass, double p[], int cptcoveff){
11549: /* dateintemean, mean date of interviews
11550: dateprojd, year, month, day of starting projection
11551: dateprojf date of end of projection;year of end of projection (same day and month as proj1).
1.126 brouard 11552: agemin, agemax range of age
11553: dateprev1 dateprev2 range of dates during which prevalence is computed
11554: */
1.296 brouard 11555: /* double anprojd, mprojd, jprojd; */
11556: /* double anprojf, mprojf, jprojf; */
1.359 brouard 11557: int yearp, stepsize, hstepm, nhstepm, j, k, i, h, nres=0;
1.126 brouard 11558: double agec; /* generic age */
1.359 brouard 11559: double agelim, ppij;
11560: /*double *popcount;*/
1.126 brouard 11561: double ***p3mat;
1.218 brouard 11562: /* double ***mobaverage; */
1.126 brouard 11563: char fileresf[FILENAMELENGTH];
11564:
11565: agelim=AGESUP;
1.211 brouard 11566: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
11567: in each health status at the date of interview (if between dateprev1 and dateprev2).
11568: We still use firstpass and lastpass as another selection.
11569: */
1.214 brouard 11570: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
11571: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 11572:
1.201 brouard 11573: strcpy(fileresf,"F_");
11574: strcat(fileresf,fileresu);
1.126 brouard 11575: if((ficresf=fopen(fileresf,"w"))==NULL) {
11576: printf("Problem with forecast resultfile: %s\n", fileresf);
11577: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
11578: }
1.235 brouard 11579: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
11580: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 11581:
1.225 brouard 11582: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 11583:
11584:
11585: stepsize=(int) (stepm+YEARM-1)/YEARM;
11586: if (stepm<=12) stepsize=1;
11587: if(estepm < stepm){
11588: printf ("Problem %d lower than %d\n",estepm, stepm);
11589: }
1.270 brouard 11590: else{
11591: hstepm=estepm;
11592: }
11593: if(estepm > stepm){ /* Yes every two year */
11594: stepsize=2;
11595: }
1.296 brouard 11596: hstepm=hstepm/stepm;
1.126 brouard 11597:
1.296 brouard 11598:
11599: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
11600: /* fractional in yp1 *\/ */
11601: /* aintmean=yp; */
11602: /* yp2=modf((yp1*12),&yp); */
11603: /* mintmean=yp; */
11604: /* yp1=modf((yp2*30.5),&yp); */
11605: /* jintmean=yp; */
11606: /* if(jintmean==0) jintmean=1; */
11607: /* if(mintmean==0) mintmean=1; */
1.126 brouard 11608:
1.296 brouard 11609:
11610: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */
11611: /* date2dmy(dateprojd,&jprojd, &mprojd, &anprojd); */
11612: /* date2dmy(dateprojf,&jprojf, &mprojf, &anprojf); */
1.351 brouard 11613: /* i1=pow(2,cptcoveff); */
11614: /* if (cptcovn < 1){i1=1;} */
1.126 brouard 11615:
1.296 brouard 11616: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.126 brouard 11617:
11618: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 11619:
1.126 brouard 11620: /* if (h==(int)(YEARM*yearp)){ */
1.351 brouard 11621: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
11622: k=TKresult[nres];
11623: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
11624: /* for(k=1; k<=i1;k++){ /\* We want to find the combination k corresponding to the values of the dummies given in this resut line (to be cleaned one day) *\/ */
11625: /* if(i1 != 1 && TKresult[nres]!= k) */
11626: /* continue; */
11627: /* if(invalidvarcomb[k]){ */
11628: /* printf("\nCombination (%d) projection ignored because no cases \n",k); */
11629: /* continue; */
11630: /* } */
1.227 brouard 11631: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
1.351 brouard 11632: for(j=1;j<=cptcovs;j++){
11633: /* for(j=1;j<=cptcoveff;j++) { */
11634: /* /\* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); *\/ */
11635: /* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11636: /* } */
11637: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
11638: /* fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
11639: /* } */
11640: fprintf(ficresf," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.235 brouard 11641: }
1.351 brouard 11642:
1.227 brouard 11643: fprintf(ficresf," yearproj age");
11644: for(j=1; j<=nlstate+ndeath;j++){
11645: for(i=1; i<=nlstate;i++)
11646: fprintf(ficresf," p%d%d",i,j);
11647: fprintf(ficresf," wp.%d",j);
11648: }
1.296 brouard 11649: for (yearp=0; yearp<=(anprojf-anprojd);yearp +=stepsize) {
1.227 brouard 11650: fprintf(ficresf,"\n");
1.296 brouard 11651: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jprojd,mprojd,anprojd+yearp);
1.270 brouard 11652: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
11653: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 11654: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
11655: nhstepm = nhstepm/hstepm;
11656: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11657: oldm=oldms;savm=savms;
1.268 brouard 11658: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 11659: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 11660: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 11661: for (h=0; h<=nhstepm; h++){
11662: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 11663: break;
11664: }
11665: }
11666: fprintf(ficresf,"\n");
1.351 brouard 11667: /* for(j=1;j<=cptcoveff;j++) */
11668: for(j=1;j<=cptcovs;j++)
11669: fprintf(ficresf,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.332 brouard 11670: /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Tvaraff not correct *\/ */
1.351 brouard 11671: /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /\* TnsdVar[Tvaraff] correct *\/ */
1.296 brouard 11672: fprintf(ficresf,"%.f %.f ",anprojd+yearp,agec+h*hstepm/YEARM*stepm);
1.268 brouard 11673:
11674: for(j=1; j<=nlstate+ndeath;j++) {
11675: ppij=0.;
11676: for(i=1; i<=nlstate;i++) {
1.278 brouard 11677: if (mobilav>=1)
11678: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
11679: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
11680: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
11681: }
1.268 brouard 11682: fprintf(ficresf," %.3f", p3mat[i][j][h]);
11683: } /* end i */
11684: fprintf(ficresf," %.3f", ppij);
11685: }/* end j */
1.227 brouard 11686: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11687: } /* end agec */
1.266 brouard 11688: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
11689: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 11690: } /* end yearp */
11691: } /* end k */
1.219 brouard 11692:
1.126 brouard 11693: fclose(ficresf);
1.215 brouard 11694: printf("End of Computing forecasting \n");
11695: fprintf(ficlog,"End of Computing forecasting\n");
11696:
1.126 brouard 11697: }
11698:
1.269 brouard 11699: /************** Back Forecasting ******************/
1.296 brouard 11700: /* void prevbackforecast(char fileres[], double ***prevacurrent, double anback1, double mback1, double jback1, double ageminpar, double agemax, double dateprev1, double dateprev2, int mobilav, double bage, double fage, int firstpass, int lastpass, double anback2, double p[], int cptcoveff){ */
11701: void prevbackforecast(char fileres[], double ***prevacurrent, double dateintmean, double dateprojd, double dateprojf, double ageminpar, double agemax, double dateprev1, double dateprev2, int mobilav, double bage, double fage, int firstpass, int lastpass, double p[], int cptcoveff){
11702: /* back1, year, month, day of starting backprojection
1.267 brouard 11703: agemin, agemax range of age
11704: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 11705: anback2 year of end of backprojection (same day and month as back1).
11706: prevacurrent and prev are prevalences.
1.267 brouard 11707: */
1.359 brouard 11708: int yearp, stepsize, hstepm, nhstepm, j, k, i, h, nres=0;
1.267 brouard 11709: double agec; /* generic age */
1.359 brouard 11710: double agelim, ppij, ppi; /* ,jintmean,mintmean,aintmean;*/
11711: /*double *popcount;*/
1.267 brouard 11712: double ***p3mat;
11713: /* double ***mobaverage; */
11714: char fileresfb[FILENAMELENGTH];
11715:
1.268 brouard 11716: agelim=AGEINF;
1.267 brouard 11717: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
11718: in each health status at the date of interview (if between dateprev1 and dateprev2).
11719: We still use firstpass and lastpass as another selection.
11720: */
11721: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
11722: /* firstpass, lastpass, stepm, weightopt, model); */
11723:
11724: /*Do we need to compute prevalence again?*/
11725:
11726: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
11727:
11728: strcpy(fileresfb,"FB_");
11729: strcat(fileresfb,fileresu);
11730: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
11731: printf("Problem with back forecast resultfile: %s\n", fileresfb);
11732: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
11733: }
11734: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
11735: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
11736:
11737: if (cptcoveff==0) ncodemax[cptcoveff]=1;
11738:
11739:
11740: stepsize=(int) (stepm+YEARM-1)/YEARM;
11741: if (stepm<=12) stepsize=1;
11742: if(estepm < stepm){
11743: printf ("Problem %d lower than %d\n",estepm, stepm);
11744: }
1.270 brouard 11745: else{
11746: hstepm=estepm;
11747: }
11748: if(estepm >= stepm){ /* Yes every two year */
11749: stepsize=2;
11750: }
1.267 brouard 11751:
11752: hstepm=hstepm/stepm;
1.296 brouard 11753: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
11754: /* fractional in yp1 *\/ */
11755: /* aintmean=yp; */
11756: /* yp2=modf((yp1*12),&yp); */
11757: /* mintmean=yp; */
11758: /* yp1=modf((yp2*30.5),&yp); */
11759: /* jintmean=yp; */
11760: /* if(jintmean==0) jintmean=1; */
11761: /* if(mintmean==0) jintmean=1; */
1.267 brouard 11762:
1.351 brouard 11763: /* i1=pow(2,cptcoveff); */
11764: /* if (cptcovn < 1){i1=1;} */
1.267 brouard 11765:
1.296 brouard 11766: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
11767: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 11768:
11769: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
11770:
1.351 brouard 11771: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
11772: k=TKresult[nres];
11773: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
11774: /* for(k=1; k<=i1;k++){ */
11775: /* if(i1 != 1 && TKresult[nres]!= k) */
11776: /* continue; */
11777: /* if(invalidvarcomb[k]){ */
11778: /* printf("\nCombination (%d) projection ignored because no cases \n",k); */
11779: /* continue; */
11780: /* } */
1.268 brouard 11781: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.351 brouard 11782: for(j=1;j<=cptcovs;j++){
11783: /* for(j=1;j<=cptcoveff;j++) { */
11784: /* fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11785: /* } */
11786: fprintf(ficresfb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.267 brouard 11787: }
1.351 brouard 11788: /* fprintf(ficrespij,"******\n"); */
11789: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
11790: /* fprintf(ficresfb," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
11791: /* } */
1.267 brouard 11792: fprintf(ficresfb," yearbproj age");
11793: for(j=1; j<=nlstate+ndeath;j++){
11794: for(i=1; i<=nlstate;i++)
1.268 brouard 11795: fprintf(ficresfb," b%d%d",i,j);
11796: fprintf(ficresfb," b.%d",j);
1.267 brouard 11797: }
1.296 brouard 11798: for (yearp=0; yearp>=(anbackf-anbackd);yearp -=stepsize) {
1.267 brouard 11799: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
11800: fprintf(ficresfb,"\n");
1.296 brouard 11801: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jbackd,mbackd,anbackd+yearp);
1.273 brouard 11802: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 11803: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
11804: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 11805: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 11806: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 11807: nhstepm = nhstepm/hstepm;
11808: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11809: oldm=oldms;savm=savms;
1.268 brouard 11810: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 11811: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 11812: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 11813: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
11814: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
11815: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 11816: for (h=0; h<=nhstepm; h++){
1.268 brouard 11817: if (h*hstepm/YEARM*stepm ==-yearp) {
11818: break;
11819: }
11820: }
11821: fprintf(ficresfb,"\n");
1.351 brouard 11822: /* for(j=1;j<=cptcoveff;j++) */
11823: for(j=1;j<=cptcovs;j++)
11824: fprintf(ficresfb,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11825: /* fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.296 brouard 11826: fprintf(ficresfb,"%.f %.f ",anbackd+yearp,agec-h*hstepm/YEARM*stepm);
1.268 brouard 11827: for(i=1; i<=nlstate+ndeath;i++) {
11828: ppij=0.;ppi=0.;
11829: for(j=1; j<=nlstate;j++) {
11830: /* if (mobilav==1) */
1.269 brouard 11831: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
11832: ppi=ppi+prevacurrent[(int)agec][j][k];
11833: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
11834: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 11835: /* else { */
11836: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
11837: /* } */
1.268 brouard 11838: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
11839: } /* end j */
11840: if(ppi <0.99){
11841: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
11842: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
11843: }
11844: fprintf(ficresfb," %.3f", ppij);
11845: }/* end j */
1.267 brouard 11846: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11847: } /* end agec */
11848: } /* end yearp */
11849: } /* end k */
1.217 brouard 11850:
1.267 brouard 11851: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 11852:
1.267 brouard 11853: fclose(ficresfb);
11854: printf("End of Computing Back forecasting \n");
11855: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 11856:
1.267 brouard 11857: }
1.217 brouard 11858:
1.269 brouard 11859: /* Variance of prevalence limit: varprlim */
11860: void varprlim(char fileresu[], int nresult, double ***prevacurrent, int mobilavproj, double bage, double fage, double **prlim, int *ncvyearp, double ftolpl, double p[], double **matcov, double *delti, int stepm, int cptcoveff){
1.288 brouard 11861: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 11862:
11863: char fileresvpl[FILENAMELENGTH];
11864: FILE *ficresvpl;
11865: double **oldm, **savm;
11866: double **varpl; /* Variances of prevalence limits by age */
11867: int i1, k, nres, j ;
11868:
11869: strcpy(fileresvpl,"VPL_");
11870: strcat(fileresvpl,fileresu);
11871: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 11872: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 11873: exit(0);
11874: }
1.288 brouard 11875: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
11876: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 11877:
11878: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
11879: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
11880:
11881: i1=pow(2,cptcoveff);
11882: if (cptcovn < 1){i1=1;}
11883:
1.337 brouard 11884: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
11885: k=TKresult[nres];
1.338 brouard 11886: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 11887: /* for(k=1; k<=i1;k++){ /\* We find the combination equivalent to result line values of dummies *\/ */
1.269 brouard 11888: if(i1 != 1 && TKresult[nres]!= k)
11889: continue;
11890: fprintf(ficresvpl,"\n#****** ");
11891: printf("\n#****** ");
11892: fprintf(ficlog,"\n#****** ");
1.337 brouard 11893: for(j=1;j<=cptcovs;j++) {
11894: fprintf(ficresvpl,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11895: fprintf(ficlog,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11896: printf("V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11897: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11898: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.269 brouard 11899: }
1.337 brouard 11900: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
11901: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
11902: /* fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
11903: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
11904: /* } */
1.269 brouard 11905: fprintf(ficresvpl,"******\n");
11906: printf("******\n");
11907: fprintf(ficlog,"******\n");
11908:
11909: varpl=matrix(1,nlstate,(int) bage, (int) fage);
11910: oldm=oldms;savm=savms;
11911: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
11912: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
11913: /*}*/
11914: }
11915:
11916: fclose(ficresvpl);
1.288 brouard 11917: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
11918: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 11919:
11920: }
11921: /* Variance of back prevalence: varbprlim */
11922: void varbprlim(char fileresu[], int nresult, double ***prevacurrent, int mobilavproj, double bage, double fage, double **bprlim, int *ncvyearp, double ftolpl, double p[], double **matcov, double *delti, int stepm, int cptcoveff){
11923: /*------- Variance of back (stable) prevalence------*/
11924:
11925: char fileresvbl[FILENAMELENGTH];
11926: FILE *ficresvbl;
11927:
11928: double **oldm, **savm;
11929: double **varbpl; /* Variances of back prevalence limits by age */
11930: int i1, k, nres, j ;
11931:
11932: strcpy(fileresvbl,"VBL_");
11933: strcat(fileresvbl,fileresu);
11934: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
11935: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
11936: exit(0);
11937: }
11938: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
11939: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
11940:
11941:
11942: i1=pow(2,cptcoveff);
11943: if (cptcovn < 1){i1=1;}
11944:
1.337 brouard 11945: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
11946: k=TKresult[nres];
1.338 brouard 11947: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 11948: /* for(k=1; k<=i1;k++){ */
11949: /* if(i1 != 1 && TKresult[nres]!= k) */
11950: /* continue; */
1.269 brouard 11951: fprintf(ficresvbl,"\n#****** ");
11952: printf("\n#****** ");
11953: fprintf(ficlog,"\n#****** ");
1.337 brouard 11954: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */
1.338 brouard 11955: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
11956: fprintf(ficresvbl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
11957: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
1.337 brouard 11958: /* for(j=1;j<=cptcoveff;j++) { */
11959: /* fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11960: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11961: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11962: /* } */
11963: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
11964: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
11965: /* fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
11966: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
1.269 brouard 11967: }
11968: fprintf(ficresvbl,"******\n");
11969: printf("******\n");
11970: fprintf(ficlog,"******\n");
11971:
11972: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
11973: oldm=oldms;savm=savms;
11974:
11975: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
11976: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
11977: /*}*/
11978: }
11979:
11980: fclose(ficresvbl);
11981: printf("done variance-covariance of back prevalence\n");fflush(stdout);
11982: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
11983:
11984: } /* End of varbprlim */
11985:
1.126 brouard 11986: /************** Forecasting *****not tested NB*************/
1.227 brouard 11987: /* void populforecast(char fileres[], double anpyram,double mpyram,double jpyram,double ageminpar, double agemax,double dateprev1, double dateprev2s, int mobilav, double agedeb, double fage, int popforecast, char popfile[], double anpyram1,double p[], int i2){ */
1.126 brouard 11988:
1.227 brouard 11989: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
11990: /* int *popage; */
11991: /* double calagedatem, agelim, kk1, kk2; */
11992: /* double *popeffectif,*popcount; */
11993: /* double ***p3mat,***tabpop,***tabpopprev; */
11994: /* /\* double ***mobaverage; *\/ */
11995: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 11996:
1.227 brouard 11997: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
11998: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
11999: /* agelim=AGESUP; */
12000: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 12001:
1.227 brouard 12002: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 12003:
12004:
1.227 brouard 12005: /* strcpy(filerespop,"POP_"); */
12006: /* strcat(filerespop,fileresu); */
12007: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
12008: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
12009: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
12010: /* } */
12011: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
12012: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 12013:
1.227 brouard 12014: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 12015:
1.227 brouard 12016: /* /\* if (mobilav!=0) { *\/ */
12017: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
12018: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
12019: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
12020: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
12021: /* /\* } *\/ */
12022: /* /\* } *\/ */
1.126 brouard 12023:
1.227 brouard 12024: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
12025: /* if (stepm<=12) stepsize=1; */
1.126 brouard 12026:
1.227 brouard 12027: /* agelim=AGESUP; */
1.126 brouard 12028:
1.227 brouard 12029: /* hstepm=1; */
12030: /* hstepm=hstepm/stepm; */
1.218 brouard 12031:
1.227 brouard 12032: /* if (popforecast==1) { */
12033: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
12034: /* printf("Problem with population file : %s\n",popfile);exit(0); */
12035: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
12036: /* } */
12037: /* popage=ivector(0,AGESUP); */
12038: /* popeffectif=vector(0,AGESUP); */
12039: /* popcount=vector(0,AGESUP); */
1.126 brouard 12040:
1.227 brouard 12041: /* i=1; */
12042: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 12043:
1.227 brouard 12044: /* imx=i; */
12045: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
12046: /* } */
1.218 brouard 12047:
1.227 brouard 12048: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
12049: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
12050: /* k=k+1; */
12051: /* fprintf(ficrespop,"\n#******"); */
12052: /* for(j=1;j<=cptcoveff;j++) { */
12053: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
12054: /* } */
12055: /* fprintf(ficrespop,"******\n"); */
12056: /* fprintf(ficrespop,"# Age"); */
12057: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
12058: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 12059:
1.227 brouard 12060: /* for (cpt=0; cpt<=0;cpt++) { */
12061: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 12062:
1.227 brouard 12063: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
12064: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
12065: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 12066:
1.227 brouard 12067: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
12068: /* oldm=oldms;savm=savms; */
12069: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 12070:
1.227 brouard 12071: /* for (h=0; h<=nhstepm; h++){ */
12072: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
12073: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
12074: /* } */
12075: /* for(j=1; j<=nlstate+ndeath;j++) { */
12076: /* kk1=0.;kk2=0; */
12077: /* for(i=1; i<=nlstate;i++) { */
12078: /* if (mobilav==1) */
12079: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
12080: /* else { */
12081: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
12082: /* } */
12083: /* } */
12084: /* if (h==(int)(calagedatem+12*cpt)){ */
12085: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
12086: /* /\*fprintf(ficrespop," %.3f", kk1); */
12087: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
12088: /* } */
12089: /* } */
12090: /* for(i=1; i<=nlstate;i++){ */
12091: /* kk1=0.; */
12092: /* for(j=1; j<=nlstate;j++){ */
12093: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
12094: /* } */
12095: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
12096: /* } */
1.218 brouard 12097:
1.227 brouard 12098: /* if (h==(int)(calagedatem+12*cpt)) */
12099: /* for(j=1; j<=nlstate;j++) */
12100: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
12101: /* } */
12102: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
12103: /* } */
12104: /* } */
1.218 brouard 12105:
1.227 brouard 12106: /* /\******\/ */
1.218 brouard 12107:
1.227 brouard 12108: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
12109: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
12110: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
12111: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
12112: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 12113:
1.227 brouard 12114: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
12115: /* oldm=oldms;savm=savms; */
12116: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
12117: /* for (h=0; h<=nhstepm; h++){ */
12118: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
12119: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
12120: /* } */
12121: /* for(j=1; j<=nlstate+ndeath;j++) { */
12122: /* kk1=0.;kk2=0; */
12123: /* for(i=1; i<=nlstate;i++) { */
12124: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
12125: /* } */
12126: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
12127: /* } */
12128: /* } */
12129: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
12130: /* } */
12131: /* } */
12132: /* } */
12133: /* } */
1.218 brouard 12134:
1.227 brouard 12135: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 12136:
1.227 brouard 12137: /* if (popforecast==1) { */
12138: /* free_ivector(popage,0,AGESUP); */
12139: /* free_vector(popeffectif,0,AGESUP); */
12140: /* free_vector(popcount,0,AGESUP); */
12141: /* } */
12142: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
12143: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
12144: /* fclose(ficrespop); */
12145: /* } /\* End of popforecast *\/ */
1.218 brouard 12146:
1.126 brouard 12147: int fileappend(FILE *fichier, char *optionfich)
12148: {
12149: if((fichier=fopen(optionfich,"a"))==NULL) {
12150: printf("Problem with file: %s\n", optionfich);
12151: fprintf(ficlog,"Problem with file: %s\n", optionfich);
12152: return (0);
12153: }
12154: fflush(fichier);
12155: return (1);
12156: }
12157:
12158:
12159: /**************** function prwizard **********************/
12160: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
12161: {
12162:
12163: /* Wizard to print covariance matrix template */
12164:
1.164 brouard 12165: char ca[32], cb[32];
12166: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 12167: int numlinepar;
12168:
12169: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
12170: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
12171: for(i=1; i <=nlstate; i++){
12172: jj=0;
12173: for(j=1; j <=nlstate+ndeath; j++){
12174: if(j==i) continue;
12175: jj++;
12176: /*ca[0]= k+'a'-1;ca[1]='\0';*/
12177: printf("%1d%1d",i,j);
12178: fprintf(ficparo,"%1d%1d",i,j);
12179: for(k=1; k<=ncovmodel;k++){
12180: /* printf(" %lf",param[i][j][k]); */
12181: /* fprintf(ficparo," %lf",param[i][j][k]); */
12182: printf(" 0.");
12183: fprintf(ficparo," 0.");
12184: }
12185: printf("\n");
12186: fprintf(ficparo,"\n");
12187: }
12188: }
12189: printf("# Scales (for hessian or gradient estimation)\n");
12190: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
12191: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
12192: for(i=1; i <=nlstate; i++){
12193: jj=0;
12194: for(j=1; j <=nlstate+ndeath; j++){
12195: if(j==i) continue;
12196: jj++;
12197: fprintf(ficparo,"%1d%1d",i,j);
12198: printf("%1d%1d",i,j);
12199: fflush(stdout);
12200: for(k=1; k<=ncovmodel;k++){
12201: /* printf(" %le",delti3[i][j][k]); */
12202: /* fprintf(ficparo," %le",delti3[i][j][k]); */
12203: printf(" 0.");
12204: fprintf(ficparo," 0.");
12205: }
12206: numlinepar++;
12207: printf("\n");
12208: fprintf(ficparo,"\n");
12209: }
12210: }
12211: printf("# Covariance matrix\n");
12212: /* # 121 Var(a12)\n\ */
12213: /* # 122 Cov(b12,a12) Var(b12)\n\ */
12214: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
12215: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
12216: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
12217: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
12218: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
12219: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
12220: fflush(stdout);
12221: fprintf(ficparo,"# Covariance matrix\n");
12222: /* # 121 Var(a12)\n\ */
12223: /* # 122 Cov(b12,a12) Var(b12)\n\ */
12224: /* # ...\n\ */
12225: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
12226:
12227: for(itimes=1;itimes<=2;itimes++){
12228: jj=0;
12229: for(i=1; i <=nlstate; i++){
12230: for(j=1; j <=nlstate+ndeath; j++){
12231: if(j==i) continue;
12232: for(k=1; k<=ncovmodel;k++){
12233: jj++;
12234: ca[0]= k+'a'-1;ca[1]='\0';
12235: if(itimes==1){
12236: printf("#%1d%1d%d",i,j,k);
12237: fprintf(ficparo,"#%1d%1d%d",i,j,k);
12238: }else{
12239: printf("%1d%1d%d",i,j,k);
12240: fprintf(ficparo,"%1d%1d%d",i,j,k);
12241: /* printf(" %.5le",matcov[i][j]); */
12242: }
12243: ll=0;
12244: for(li=1;li <=nlstate; li++){
12245: for(lj=1;lj <=nlstate+ndeath; lj++){
12246: if(lj==li) continue;
12247: for(lk=1;lk<=ncovmodel;lk++){
12248: ll++;
12249: if(ll<=jj){
12250: cb[0]= lk +'a'-1;cb[1]='\0';
12251: if(ll<jj){
12252: if(itimes==1){
12253: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12254: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12255: }else{
12256: printf(" 0.");
12257: fprintf(ficparo," 0.");
12258: }
12259: }else{
12260: if(itimes==1){
12261: printf(" Var(%s%1d%1d)",ca,i,j);
12262: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
12263: }else{
12264: printf(" 0.");
12265: fprintf(ficparo," 0.");
12266: }
12267: }
12268: }
12269: } /* end lk */
12270: } /* end lj */
12271: } /* end li */
12272: printf("\n");
12273: fprintf(ficparo,"\n");
12274: numlinepar++;
12275: } /* end k*/
12276: } /*end j */
12277: } /* end i */
12278: } /* end itimes */
12279:
12280: } /* end of prwizard */
12281: /******************* Gompertz Likelihood ******************************/
12282: double gompertz(double x[])
12283: {
1.302 brouard 12284: double A=0.0,B=0.,L=0.0,sump=0.,num=0.;
1.126 brouard 12285: int i,n=0; /* n is the size of the sample */
12286:
1.220 brouard 12287: for (i=1;i<=imx ; i++) {
1.126 brouard 12288: sump=sump+weight[i];
12289: /* sump=sump+1;*/
12290: num=num+1;
12291: }
1.302 brouard 12292: L=0.0;
12293: /* agegomp=AGEGOMP; */
1.126 brouard 12294: /* for (i=0; i<=imx; i++)
12295: if (wav[i]>0) printf("i=%d ageex=%lf agecens=%lf agedc=%lf cens=%d %d\n" ,i,ageexmed[i],agecens[i],agedc[i],cens[i],wav[i]);*/
12296:
1.302 brouard 12297: for (i=1;i<=imx ; i++) {
12298: /* mu(a)=mu(agecomp)*exp(teta*(age-agegomp))
12299: mu(a)=x[1]*exp(x[2]*(age-agegomp)); x[1] and x[2] are per year.
12300: * L= Product mu(agedeces)exp(-\int_ageexam^agedc mu(u) du ) for a death between agedc (in month)
12301: * and agedc +1 month, cens[i]=0: log(x[1]/YEARM)
12302: * +
12303: * exp(-\int_ageexam^agecens mu(u) du ) when censored, cens[i]=1
12304: */
12305: if (wav[i] > 1 || agedc[i] < AGESUP) {
12306: if (cens[i] == 1){
12307: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
12308: } else if (cens[i] == 0){
1.126 brouard 12309: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
1.362 brouard 12310: +log(fabs(x[1])/YEARM) +x[2]*(agedc[i]-agegomp)+log(YEARM);
12311: /* +log(x[1]/YEARM) +x[2]*(agedc[i]-agegomp)+log(YEARM); */ /* To be seen */
1.302 brouard 12312: } else
12313: printf("Gompertz cens[%d] neither 1 nor 0\n",i);
1.126 brouard 12314: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
1.302 brouard 12315: L=L+A*weight[i];
1.126 brouard 12316: /* printf("\ni=%d A=%f L=%lf x[1]=%lf x[2]=%lf ageex=%lf agecens=%lf cens=%d agedc=%lf weight=%lf\n",i,A,L,x[1],x[2],ageexmed[i]*12,agecens[i]*12,cens[i],agedc[i]*12,weight[i]);*/
1.302 brouard 12317: }
12318: }
1.126 brouard 12319:
1.302 brouard 12320: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
1.126 brouard 12321:
12322: return -2*L*num/sump;
12323: }
12324:
1.136 brouard 12325: #ifdef GSL
12326: /******************* Gompertz_f Likelihood ******************************/
12327: double gompertz_f(const gsl_vector *v, void *params)
12328: {
1.302 brouard 12329: double A=0.,B=0.,LL=0.0,sump=0.,num=0.;
1.136 brouard 12330: double *x= (double *) v->data;
12331: int i,n=0; /* n is the size of the sample */
12332:
12333: for (i=0;i<=imx-1 ; i++) {
12334: sump=sump+weight[i];
12335: /* sump=sump+1;*/
12336: num=num+1;
12337: }
12338:
12339:
12340: /* for (i=0; i<=imx; i++)
12341: if (wav[i]>0) printf("i=%d ageex=%lf agecens=%lf agedc=%lf cens=%d %d\n" ,i,ageexmed[i],agecens[i],agedc[i],cens[i],wav[i]);*/
12342: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
12343: for (i=1;i<=imx ; i++)
12344: {
12345: if (cens[i] == 1 && wav[i]>1)
12346: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
12347:
12348: if (cens[i] == 0 && wav[i]>1)
12349: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
12350: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
12351:
12352: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
12353: if (wav[i] > 1 ) { /* ??? */
12354: LL=LL+A*weight[i];
12355: /* printf("\ni=%d A=%f L=%lf x[1]=%lf x[2]=%lf ageex=%lf agecens=%lf cens=%d agedc=%lf weight=%lf\n",i,A,L,x[1],x[2],ageexmed[i]*12,agecens[i]*12,cens[i],agedc[i]*12,weight[i]);*/
12356: }
12357: }
12358:
12359: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
12360: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
12361:
12362: return -2*LL*num/sump;
12363: }
12364: #endif
12365:
1.126 brouard 12366: /******************* Printing html file ***********/
1.201 brouard 12367: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 12368: int lastpass, int stepm, int weightopt, char model[],\
12369: int imx, double p[],double **matcov,double agemortsup){
12370: int i,k;
12371:
12372: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
12373: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
12374: for (i=1;i<=2;i++)
12375: fprintf(fichtm," p[%d] = %lf [%f ; %f]<br>\n",i,p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.199 brouard 12376: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 12377: fprintf(fichtm,"</ul>");
12378:
12379: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
12380:
12381: fprintf(fichtm,"\nAge l<inf>x</inf> q<inf>x</inf> d(x,x+1) L<inf>x</inf> T<inf>x</inf> e<infx</inf><br>");
12382:
12383: for (k=agegomp;k<(agemortsup-2);k++)
12384: fprintf(fichtm,"%d %.0lf %lf %.0lf %.0lf %.0lf %lf<br>\n",k,lsurv[k],p[1]*exp(p[2]*(k-agegomp)),(p[1]*exp(p[2]*(k-agegomp)))*lsurv[k],lpop[k],tpop[k],tpop[k]/lsurv[k]);
12385:
12386:
12387: fflush(fichtm);
12388: }
12389:
12390: /******************* Gnuplot file **************/
1.201 brouard 12391: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 12392:
12393: char dirfileres[132],optfileres[132];
1.164 brouard 12394:
1.359 brouard 12395: /*int ng;*/
1.126 brouard 12396:
12397:
12398: /*#ifdef windows */
12399: fprintf(ficgp,"cd \"%s\" \n",pathc);
12400: /*#endif */
12401:
12402:
12403: strcpy(dirfileres,optionfilefiname);
12404: strcpy(optfileres,"vpl");
1.199 brouard 12405: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 12406: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 12407: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 12408: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 12409: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
12410:
12411: }
12412:
1.136 brouard 12413: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
12414: {
1.126 brouard 12415:
1.136 brouard 12416: /*-------- data file ----------*/
12417: FILE *fic;
12418: char dummy[]=" ";
1.359 brouard 12419: int i = 0, j = 0, n = 0, iv = 0;/* , v;*/
1.223 brouard 12420: int lstra;
1.136 brouard 12421: int linei, month, year,iout;
1.302 brouard 12422: int noffset=0; /* This is the offset if BOM data file */
1.136 brouard 12423: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 12424: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 12425: char *stratrunc;
1.223 brouard 12426:
1.349 brouard 12427: /* DummyV=ivector(-1,NCOVMAX); /\* 1 to 3 *\/ */
12428: /* FixedV=ivector(-1,NCOVMAX); /\* 1 to 3 *\/ */
1.339 brouard 12429:
12430: ncovcolt=ncovcol+nqv+ntv+nqtv; /* total of covariates in the data, not in the model equation */
12431:
1.136 brouard 12432: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 12433: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
12434: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 12435: }
1.126 brouard 12436:
1.302 brouard 12437: /* Is it a BOM UTF-8 Windows file? */
12438: /* First data line */
12439: linei=0;
12440: while(fgets(line, MAXLINE, fic)) {
12441: noffset=0;
12442: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
12443: {
12444: noffset=noffset+3;
12445: printf("# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);fflush(stdout);
12446: fprintf(ficlog,"# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);
12447: fflush(ficlog); return 1;
12448: }
12449: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
12450: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
12451: {
12452: noffset=noffset+2;
1.304 brouard 12453: printf("# Error Data file '%s' is a huge UTF16BE BOM file, please convert to UTF8 or ascii file (for example with dos2unix) and rerun.\n",datafile);fflush(stdout);
12454: fprintf(ficlog,"# Error Data file '%s' is a huge UTF16BE BOM file, please convert to UTF8 or ascii file (for example with dos2unix) and rerun.\n",datafile);
1.302 brouard 12455: fflush(ficlog); return 1;
12456: }
12457: else if( line[0] == 0 && line[1] == 0)
12458: {
12459: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
12460: noffset=noffset+4;
1.304 brouard 12461: printf("# Error Data file '%s' is a huge UTF16BE BOM file, please convert to UTF8 or ascii file (for example with dos2unix) and rerun.\n",datafile);fflush(stdout);
12462: fprintf(ficlog,"# Error Data file '%s' is a huge UTF16BE BOM file, please convert to UTF8 or ascii file (for example with dos2unix) and rerun.\n",datafile);
1.302 brouard 12463: fflush(ficlog); return 1;
12464: }
12465: } else{
12466: ;/*printf(" Not a BOM file\n");*/
12467: }
12468: /* If line starts with a # it is a comment */
12469: if (line[noffset] == '#') {
12470: linei=linei+1;
12471: break;
12472: }else{
12473: break;
12474: }
12475: }
12476: fclose(fic);
12477: if((fic=fopen(datafile,"r"))==NULL) {
12478: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
12479: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
12480: }
12481: /* Not a Bom file */
12482:
1.136 brouard 12483: i=1;
12484: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
12485: linei=linei+1;
12486: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
12487: if(line[j] == '\t')
12488: line[j] = ' ';
12489: }
12490: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
12491: ;
12492: };
12493: line[j+1]=0; /* Trims blanks at end of line */
12494: if(line[0]=='#'){
12495: fprintf(ficlog,"Comment line\n%s\n",line);
12496: printf("Comment line\n%s\n",line);
12497: continue;
12498: }
12499: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 12500: strcpy(line, linetmp);
1.223 brouard 12501:
12502: /* Loops on waves */
12503: for (j=maxwav;j>=1;j--){
12504: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 12505: cutv(stra, strb, line, ' ');
12506: if(strb[0]=='.') { /* Missing value */
12507: lval=-1;
12508: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
1.341 brouard 12509: cotvar[j][ncovcol+nqv+ntv+iv][i]=-1; /* For performance reasons */
1.238 brouard 12510: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
12511: printf("Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be the %d th quantitative value out of %d measured at wave %d. If missing, you should remove this individual or impute a value. Exiting.\n", strb, linei,i,line,iv, nqtv, j);
12512: fprintf(ficlog,"Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be the %d th quantitative value out of %d measured at wave %d. If missing, you should remove this individual or impute a value. Exiting.\n", strb, linei,i,line,iv, nqtv, j);fflush(ficlog);
12513: return 1;
12514: }
12515: }else{
12516: errno=0;
12517: /* what_kind_of_number(strb); */
12518: dval=strtod(strb,&endptr);
12519: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
12520: /* if(strb != endptr && *endptr == '\0') */
12521: /* dval=dlval; */
12522: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
12523: if( strb[0]=='\0' || (*endptr != '\0')){
12524: printf("Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be the %d th quantitative value out of %d measured at wave %d. Setting maxwav=%d might be wrong. Exiting.\n", strb, linei,i,line,iv, nqtv, j,maxwav);
12525: fprintf(ficlog,"Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be the %d th quantitative value out of %d measured at wave %d. Setting maxwav=%d might be wrong. Exiting.\n", strb, linei,i,line, iv, nqtv, j,maxwav);fflush(ficlog);
12526: return 1;
12527: }
12528: cotqvar[j][iv][i]=dval;
1.341 brouard 12529: cotvar[j][ncovcol+nqv+ntv+iv][i]=dval; /* because cotvar starts now at first ntv */
1.238 brouard 12530: }
12531: strcpy(line,stra);
1.223 brouard 12532: }/* end loop ntqv */
1.225 brouard 12533:
1.223 brouard 12534: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 12535: cutv(stra, strb, line, ' ');
12536: if(strb[0]=='.') { /* Missing value */
12537: lval=-1;
12538: }else{
12539: errno=0;
12540: lval=strtol(strb,&endptr,10);
12541: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
12542: if( strb[0]=='\0' || (*endptr != '\0')){
12543: printf("Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be the %d th dummy covariate out of %d measured at wave %d. Setting maxwav=%d might be wrong. Exiting.\n", strb, linei,i,line,iv, ntv, j,maxwav);
12544: fprintf(ficlog,"Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be the %d dummy covariate out of %d measured wave %d. Setting maxwav=%d might be wrong. Exiting.\n", strb, linei,i,line,iv, ntv,j,maxwav);fflush(ficlog);
12545: return 1;
12546: }
12547: }
12548: if(lval <-1 || lval >1){
12549: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 12550: Should be a value of %d(nth) covariate of wave %d (0 should be the value for the reference and 1\n \
1.223 brouard 12551: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 12552: For example, for multinomial values like 1, 2 and 3,\n \
12553: build V1=0 V2=0 for the reference value (1),\n \
12554: V1=1 V2=0 for (2) \n \
1.223 brouard 12555: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 12556: output of IMaCh is often meaningless.\n \
1.319 brouard 12557: Exiting.\n",lval,linei, i,line,iv,j);
1.238 brouard 12558: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 12559: Should be a value of %d(nth) covariate of wave %d (0 should be the value for the reference and 1\n \
1.223 brouard 12560: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 12561: For example, for multinomial values like 1, 2 and 3,\n \
12562: build V1=0 V2=0 for the reference value (1),\n \
12563: V1=1 V2=0 for (2) \n \
1.223 brouard 12564: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 12565: output of IMaCh is often meaningless.\n \
1.319 brouard 12566: Exiting.\n",lval,linei, i,line,iv,j);fflush(ficlog);
1.238 brouard 12567: return 1;
12568: }
1.341 brouard 12569: cotvar[j][ncovcol+nqv+iv][i]=(double)(lval);
1.238 brouard 12570: strcpy(line,stra);
1.223 brouard 12571: }/* end loop ntv */
1.225 brouard 12572:
1.223 brouard 12573: /* Statuses at wave */
1.137 brouard 12574: cutv(stra, strb, line, ' ');
1.223 brouard 12575: if(strb[0]=='.') { /* Missing value */
1.238 brouard 12576: lval=-1;
1.136 brouard 12577: }else{
1.238 brouard 12578: errno=0;
12579: lval=strtol(strb,&endptr,10);
12580: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
1.347 brouard 12581: if( strb[0]=='\0' || (*endptr != '\0' )){
12582: printf("Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be a status of wave %d. Setting maxwav=%d might be wrong. Exiting.\n", strb, linei,i,line,j,maxwav);
12583: fprintf(ficlog,"Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be a status of wave %d. Setting maxwav=%d might be wrong. Exiting.\n", strb, linei,i,line,j,maxwav);fflush(ficlog);
12584: return 1;
12585: }else if( lval==0 || lval > nlstate+ndeath){
1.348 brouard 12586: printf("Error in data around '%s' at line number %d for individual %d, '%s'\n Should be a state at wave %d. A state should be 1 to %d and not %ld.\n Fix your data file '%s'! Exiting.\n", strb, linei,i,line,j,nlstate+ndeath, lval, datafile);fflush(stdout);
12587: fprintf(ficlog,"Error in data around '%s' at line number %d for individual %d, '%s'\n Should be a state at wave %d. A state should be 1 to %d and not %ld.\n Fix your data file '%s'! Exiting.\n", strb, linei,i,line,j,nlstate+ndeath, lval, datafile); fflush(ficlog);
1.238 brouard 12588: return 1;
12589: }
1.136 brouard 12590: }
1.225 brouard 12591:
1.136 brouard 12592: s[j][i]=lval;
1.225 brouard 12593:
1.223 brouard 12594: /* Date of Interview */
1.136 brouard 12595: strcpy(line,stra);
12596: cutv(stra, strb,line,' ');
1.169 brouard 12597: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 12598: }
1.169 brouard 12599: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 12600: month=99;
12601: year=9999;
1.136 brouard 12602: }else{
1.225 brouard 12603: printf("Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be a date of interview (mm/yyyy or .) at wave %d. Exiting.\n",strb, linei,i, line,j);
12604: fprintf(ficlog,"Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be a date of interview (mm/yyyy or .) at wave %d. Exiting.\n",strb, linei,i, line,j);fflush(ficlog);
12605: return 1;
1.136 brouard 12606: }
12607: anint[j][i]= (double) year;
1.302 brouard 12608: mint[j][i]= (double)month;
12609: /* if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){ */
12610: /* printf("Warning reading data around '%s' at line number %d for individual %d, '%s'\nThe date of interview (%2d/%4d) at wave %d occurred before the date of birth (%2d/%4d).\n",strb, linei,i, line, mint[j][i],anint[j][i], moisnais[i],annais[i]); */
12611: /* fprintf(ficlog,"Warning reading data around '%s' at line number %d for individual %d, '%s'\nThe date of interview (%2d/%4d) at wave %d occurred before the date of birth (%2d/%4d).\n",strb, linei,i, line, mint[j][i],anint[j][i], moisnais[i],annais[i]); */
12612: /* } */
1.136 brouard 12613: strcpy(line,stra);
1.223 brouard 12614: } /* End loop on waves */
1.225 brouard 12615:
1.223 brouard 12616: /* Date of death */
1.136 brouard 12617: cutv(stra, strb,line,' ');
1.169 brouard 12618: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 12619: }
1.169 brouard 12620: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 12621: month=99;
12622: year=9999;
12623: }else{
1.141 brouard 12624: printf("Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be a date of death (mm/yyyy or .). Exiting.\n",strb, linei,i,line);
1.225 brouard 12625: fprintf(ficlog,"Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be a date of death (mm/yyyy or .). Exiting.\n",strb, linei,i,line);fflush(ficlog);
12626: return 1;
1.136 brouard 12627: }
12628: andc[i]=(double) year;
12629: moisdc[i]=(double) month;
12630: strcpy(line,stra);
12631:
1.223 brouard 12632: /* Date of birth */
1.136 brouard 12633: cutv(stra, strb,line,' ');
1.169 brouard 12634: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 12635: }
1.169 brouard 12636: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 12637: month=99;
12638: year=9999;
12639: }else{
1.141 brouard 12640: printf("Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be a date of birth (mm/yyyy or .). Exiting.\n",strb, linei,i,line);
12641: fprintf(ficlog,"Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be a date of birth (mm/yyyy or .). Exiting.\n",strb, linei,i,line);fflush(ficlog);
1.225 brouard 12642: return 1;
1.136 brouard 12643: }
12644: if (year==9999) {
1.141 brouard 12645: printf("Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be a date of birth (mm/yyyy) but at least the year of birth should be given. Exiting.\n",strb, linei,i,line);
12646: fprintf(ficlog,"Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be a date of birth (mm/yyyy) but at least the year of birth should be given. Exiting.\n",strb, linei,i,line);fflush(ficlog);
1.225 brouard 12647: return 1;
12648:
1.136 brouard 12649: }
12650: annais[i]=(double)(year);
1.302 brouard 12651: moisnais[i]=(double)(month);
12652: for (j=1;j<=maxwav;j++){
12653: if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){
12654: printf("Warning reading data around '%s' at line number %d for individual %d, '%s'\nThe date of interview (%2d/%4d) at wave %d occurred before the date of birth (%2d/%4d).\n",strb, linei,i, line, (int)mint[j][i],(int)anint[j][i], j,(int)moisnais[i],(int)annais[i]);
12655: fprintf(ficlog,"Warning reading data around '%s' at line number %d for individual %d, '%s'\nThe date of interview (%2d/%4d) at wave %d occurred before the date of birth (%2d/%4d).\n",strb, linei,i, line, (int)mint[j][i],(int)anint[j][i], j, (int)moisnais[i],(int)annais[i]);
12656: }
12657: }
12658:
1.136 brouard 12659: strcpy(line,stra);
1.225 brouard 12660:
1.223 brouard 12661: /* Sample weight */
1.136 brouard 12662: cutv(stra, strb,line,' ');
12663: errno=0;
12664: dval=strtod(strb,&endptr);
12665: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 12666: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
12667: fprintf(ficlog,"Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
1.136 brouard 12668: fflush(ficlog);
12669: return 1;
12670: }
12671: weight[i]=dval;
12672: strcpy(line,stra);
1.225 brouard 12673:
1.223 brouard 12674: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
12675: cutv(stra, strb, line, ' ');
12676: if(strb[0]=='.') { /* Missing value */
1.225 brouard 12677: lval=-1;
1.311 brouard 12678: coqvar[iv][i]=NAN;
12679: covar[ncovcol+iv][i]=NAN; /* including qvar in standard covar for performance reasons */
1.223 brouard 12680: }else{
1.225 brouard 12681: errno=0;
12682: /* what_kind_of_number(strb); */
12683: dval=strtod(strb,&endptr);
12684: /* if(strb != endptr && *endptr == '\0') */
12685: /* dval=dlval; */
12686: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
12687: if( strb[0]=='\0' || (*endptr != '\0')){
12688: printf("Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be the %d th quantitative value (out of %d) constant for all waves. Setting maxwav=%d might be wrong. Exiting.\n", strb, linei,i,line, iv, nqv, maxwav);
12689: fprintf(ficlog,"Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be the %d th quantitative value (out of %d) constant for all waves. Setting maxwav=%d might be wrong. Exiting.\n", strb, linei,i,line, iv, nqv, maxwav);fflush(ficlog);
12690: return 1;
12691: }
12692: coqvar[iv][i]=dval;
1.226 brouard 12693: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 12694: }
12695: strcpy(line,stra);
12696: }/* end loop nqv */
1.136 brouard 12697:
1.223 brouard 12698: /* Covariate values */
1.136 brouard 12699: for (j=ncovcol;j>=1;j--){
12700: cutv(stra, strb,line,' ');
1.223 brouard 12701: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 12702: lval=-1;
1.136 brouard 12703: }else{
1.225 brouard 12704: errno=0;
12705: lval=strtol(strb,&endptr,10);
12706: if( strb[0]=='\0' || (*endptr != '\0')){
12707: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\nShould be a covariate value (=0 for the reference or 1 for alternative). Exiting.\n",lval, linei,i, line);
12708: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\nShould be a covariate value (=0 for the reference or 1 for alternative). Exiting.\n",lval, linei,i, line);fflush(ficlog);
12709: return 1;
12710: }
1.136 brouard 12711: }
12712: if(lval <-1 || lval >1){
1.225 brouard 12713: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 12714: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
12715: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 12716: For example, for multinomial values like 1, 2 and 3,\n \
12717: build V1=0 V2=0 for the reference value (1),\n \
12718: V1=1 V2=0 for (2) \n \
1.136 brouard 12719: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 12720: output of IMaCh is often meaningless.\n \
1.136 brouard 12721: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 12722: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 12723: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
12724: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 12725: For example, for multinomial values like 1, 2 and 3,\n \
12726: build V1=0 V2=0 for the reference value (1),\n \
12727: V1=1 V2=0 for (2) \n \
1.136 brouard 12728: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 12729: output of IMaCh is often meaningless.\n \
1.136 brouard 12730: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 12731: return 1;
1.136 brouard 12732: }
12733: covar[j][i]=(double)(lval);
12734: strcpy(line,stra);
12735: }
12736: lstra=strlen(stra);
1.225 brouard 12737:
1.136 brouard 12738: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
12739: stratrunc = &(stra[lstra-9]);
12740: num[i]=atol(stratrunc);
12741: }
12742: else
12743: num[i]=atol(stra);
12744: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
12745: printf("%ld %.lf %.lf %.lf %.lf/%.lf %.lf/%.lf %.lf/%.lf %d %.lf/%.lf %d %.lf/%.lf %d %.lf/%.lf %d\n",num[i],(covar[1][i]), (covar[2][i]),weight[i], (moisnais[i]), (annais[i]), (moisdc[i]), (andc[i]), (mint[1][i]), (anint[1][i]), (s[1][i]), (mint[2][i]), (anint[2][i]), (s[2][i]), (mint[3][i]), (anint[3][i]), (s[3][i]), (mint[4][i]), (anint[4][i]), (s[4][i])); ij=ij+1;}*/
12746:
12747: i=i+1;
12748: } /* End loop reading data */
1.225 brouard 12749:
1.136 brouard 12750: *imax=i-1; /* Number of individuals */
12751: fclose(fic);
1.225 brouard 12752:
1.136 brouard 12753: return (0);
1.164 brouard 12754: /* endread: */
1.225 brouard 12755: printf("Exiting readdata: ");
12756: fclose(fic);
12757: return (1);
1.223 brouard 12758: }
1.126 brouard 12759:
1.234 brouard 12760: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 12761: char *p1 = *stri, *p2 = *stri;
1.235 brouard 12762: while (*p2 == ' ')
1.234 brouard 12763: p2++;
12764: /* while ((*p1++ = *p2++) !=0) */
12765: /* ; */
12766: /* do */
12767: /* while (*p2 == ' ') */
12768: /* p2++; */
12769: /* while (*p1++ == *p2++); */
12770: *stri=p2;
1.145 brouard 12771: }
12772:
1.330 brouard 12773: int decoderesult( char resultline[], int nres)
1.230 brouard 12774: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
12775: {
1.235 brouard 12776: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 12777: char resultsav[MAXLINE];
1.330 brouard 12778: /* int resultmodel[MAXLINE]; */
1.334 brouard 12779: /* int modelresult[MAXLINE]; */
1.230 brouard 12780: char stra[80], strb[80], strc[80], strd[80],stre[80];
12781:
1.234 brouard 12782: removefirstspace(&resultline);
1.332 brouard 12783: printf("decoderesult:%s\n",resultline);
1.230 brouard 12784:
1.332 brouard 12785: strcpy(resultsav,resultline);
1.342 brouard 12786: /* printf("Decoderesult resultsav=\"%s\" resultline=\"%s\"\n", resultsav, resultline); */
1.230 brouard 12787: if (strlen(resultsav) >1){
1.334 brouard 12788: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' in this resultline */
1.230 brouard 12789: }
1.353 brouard 12790: if(j == 0 && cptcovs== 0){ /* Resultline but no = and no covariate in the model */
1.253 brouard 12791: TKresult[nres]=0; /* Combination for the nresult and the model */
12792: return (0);
12793: }
1.234 brouard 12794: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
1.353 brouard 12795: fprintf(ficlog,"ERROR: the number of variables in the resultline which is %d, differs from the number %d of single variables used in the model line, 1+age+%s.\n",j, cptcovs, model);fflush(ficlog);
12796: printf("ERROR: the number of variables in the resultline which is %d, differs from the number %d of single variables used in the model line, 1+age+%s.\n",j, cptcovs, model);fflush(stdout);
12797: if(j==0)
12798: return 1;
1.234 brouard 12799: }
1.334 brouard 12800: for(k=1; k<=j;k++){ /* Loop on any covariate of the RESULT LINE */
1.234 brouard 12801: if(nbocc(resultsav,'=') >1){
1.318 brouard 12802: cutl(stra,strb,resultsav,' '); /* keeps in strb after the first ' ' (stra is the rest of the resultline to be analyzed in the next loop *//* resultsav= "V4=1 V5=25.1 V3=0" stra= "V5=25.1 V3=0" strb= "V4=1" */
1.332 brouard 12803: /* If resultsav= "V4= 1 V5=25.1 V3=0" with a blank then strb="V4=" and stra="1 V5=25.1 V3=0" */
1.318 brouard 12804: cutl(strc,strd,strb,'='); /* strb:"V4=1" strc="1" strd="V4" */
1.332 brouard 12805: /* If a blank, then strc="V4=" and strd='\0' */
12806: if(strc[0]=='\0'){
12807: printf("Error in resultline, probably a blank after the \"%s\", \"result:%s\", stra=\"%s\" resultsav=\"%s\"\n",strb,resultline, stra, resultsav);
12808: fprintf(ficlog,"Error in resultline, probably a blank after the \"V%s=\", resultline=%s\n",strb,resultline);
12809: return 1;
12810: }
1.234 brouard 12811: }else
12812: cutl(strc,strd,resultsav,'=');
1.318 brouard 12813: Tvalsel[k]=atof(strc); /* 1 */ /* Tvalsel of k is the float value of the kth covariate appearing in this result line */
1.234 brouard 12814:
1.230 brouard 12815: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
1.318 brouard 12816: Tvarsel[k]=atoi(strc); /* 4 */ /* Tvarsel is the id of the kth covariate in the result line Tvarsel[1] in "V4=1.." is 4.*/
1.230 brouard 12817: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
12818: /* cptcovsel++; */
12819: if (nbocc(stra,'=') >0)
12820: strcpy(resultsav,stra); /* and analyzes it */
12821: }
1.235 brouard 12822: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 12823: /* Feeds resultmodel[nres][k1]=k2 for k1th product covariate with age in the model equation fed by the index k2 of the resutline*/
1.334 brouard 12824: for(k1=1; k1<= cptcovt ;k1++){ /* Loop on MODEL LINE V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.332 brouard 12825: if(Typevar[k1]==0){ /* Single covariate in model */
12826: /* 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.234 brouard 12827: match=0;
1.318 brouard 12828: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
12829: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 12830: modelresult[nres][k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.318 brouard 12831: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
1.234 brouard 12832: break;
12833: }
12834: }
12835: if(match == 0){
1.338 brouard 12836: printf("Error in result line (Dummy single): V%d is missing in result: %s according to model=1+age+%s. Tvar[k1=%d]=%d is different from Tvarsel[k2=%d]=%d.\n",Tvar[k1], resultline, model,k1, Tvar[k1], k2, Tvarsel[k2]);
12837: fprintf(ficlog,"Error in result line (Dummy single): V%d is missing in result: %s according to model=1+age+%s\n",Tvar[k1], resultline, model);
1.310 brouard 12838: return 1;
1.234 brouard 12839: }
1.332 brouard 12840: }else if(Typevar[k1]==1){ /* Product with age We want to get the position k2 in the resultline of the product k1 in the model line*/
12841: /* We feed resultmodel[k1]=k2; */
12842: match=0;
12843: for(k2=1; k2 <=j;k2++){/* Loop on resultline. jth occurence of = signs in the result line. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
12844: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 12845: modelresult[nres][k2]=k1;/* we found a Vn=1 corrresponding to Vn*age in the model modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.332 brouard 12846: resultmodel[nres][k1]=k2; /* Added here */
1.342 brouard 12847: /* printf("Decoderesult first modelresult[k2=%d]=%d (k1) V%d*AGE\n",k2,k1,Tvar[k1]); */
1.332 brouard 12848: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
12849: break;
12850: }
12851: }
12852: if(match == 0){
1.338 brouard 12853: printf("Error in result line (Product with age): V%d is missing in result: %s according to model=1+age+%s (Tvarsel[k2=%d]=%d)\n",Tvar[k1], resultline, model, k2, Tvarsel[k2]);
12854: fprintf(ficlog,"Error in result line (Product with age): V%d is missing in result: %s according to model=1+age+%s (Tvarsel[k2=%d]=%d)\n",Tvar[k1], resultline, model, k2, Tvarsel[k2]);
1.332 brouard 12855: return 1;
12856: }
1.349 brouard 12857: }else if(Typevar[k1]==2 || Typevar[k1]==3){ /* Product with or without age. We want to get the position in the resultline of the product in the model line*/
1.332 brouard 12858: /* resultmodel[nres][of such a Vn * Vm product k1] is not unique, so can't exist, we feed Tvard[k1][1] and [2] */
12859: match=0;
1.342 brouard 12860: /* printf("Decoderesult very first Product Tvardk[k1=%d][1]=%d Tvardk[k1=%d][2]=%d V%d * V%d\n",k1,Tvardk[k1][1],k1,Tvardk[k1][2],Tvardk[k1][1],Tvardk[k1][2]); */
1.332 brouard 12861: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
12862: if(Tvardk[k1][1]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
12863: /* modelresult[k2]=k1; */
1.342 brouard 12864: /* printf("Decoderesult first Product modelresult[k2=%d]=%d (k1) V%d * \n",k2,k1,Tvarsel[k2]); */
1.332 brouard 12865: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
12866: }
12867: }
12868: if(match == 0){
1.349 brouard 12869: printf("Error in result line (Product without age first variable or double product with age): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][1], resultline, model);
12870: fprintf(ficlog,"Error in result line (Product without age first variable or double product with age): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][1], resultline, model);
1.332 brouard 12871: return 1;
12872: }
12873: match=0;
12874: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
12875: if(Tvardk[k1][2]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
12876: /* modelresult[k2]=k1;*/
1.342 brouard 12877: /* printf("Decoderesult second Product modelresult[k2=%d]=%d (k1) * V%d \n ",k2,k1,Tvarsel[k2]); */
1.332 brouard 12878: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
12879: break;
12880: }
12881: }
12882: if(match == 0){
1.349 brouard 12883: printf("Error in result line (Product without age second variable or double product with age): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][2], resultline, model);
12884: fprintf(ficlog,"Error in result line (Product without age second variable or double product with age): V%d is missing in result : %s according to model=1+age+%s\n",Tvardk[k1][2], resultline, model);
1.332 brouard 12885: return 1;
12886: }
12887: }/* End of testing */
1.333 brouard 12888: }/* End loop cptcovt */
1.235 brouard 12889: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 12890: /* Feeds resultmodel[nres][k1]=k2 for single covariate (k1) in the model equation */
1.334 brouard 12891: for(k2=1; k2 <=j;k2++){ /* j or cptcovs is the number of single covariates used either in the model line as well as in the result line (dummy or quantitative)
12892: * Loop on resultline variables: result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 12893: match=0;
1.318 brouard 12894: for(k1=1; k1<= cptcovt ;k1++){ /* loop on model: model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.332 brouard 12895: if(Typevar[k1]==0){ /* Single only */
1.349 brouard 12896: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 What if a product? */
1.330 brouard 12897: resultmodel[nres][k1]=k2; /* k1th position in the model equation corresponds to k2th position in the result line. resultmodel[2]=1 resultmodel[1]=2 resultmodel[3]=3 resultmodel[6]=4 resultmodel[9]=5 */
1.334 brouard 12898: modelresult[nres][k2]=k1; /* k1th position in the model equation corresponds to k2th position in the result line. modelresult[1]=2 modelresult[2]=1 modelresult[3]=3 remodelresult[4]=6 modelresult[5]=9 */
1.234 brouard 12899: ++match;
12900: }
12901: }
12902: }
12903: if(match == 0){
1.338 brouard 12904: printf("Error in result line: variable V%d is missing in model; result: %s, model=1+age+%s\n",Tvarsel[k2], resultline, model);
12905: fprintf(ficlog,"Error in result line: variable V%d is missing in model; result: %s, model=1+age+%s\n",Tvarsel[k2], resultline, model);
1.310 brouard 12906: return 1;
1.234 brouard 12907: }else if(match > 1){
1.338 brouard 12908: printf("Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
12909: fprintf(ficlog,"Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
1.310 brouard 12910: return 1;
1.234 brouard 12911: }
12912: }
1.334 brouard 12913: /* cptcovres=j /\* Number of variables in the resultline is equal to cptcovs and thus useless *\/ */
1.234 brouard 12914: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 12915: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.330 brouard 12916: /* nres=1st result line: V4=1 V5=25.1 V3=0 V2=8 V1=1 */
12917: /* should correspond to the combination 6 of dummy: V4=1, V3=0, V1=1 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 1*1 + 0*2 + 1*4 = 5 + (1offset) = 6*/
12918: /* nres=2nd result line: V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.235 brouard 12919: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
12920: /* 1 0 0 0 */
12921: /* 2 1 0 0 */
12922: /* 3 0 1 0 */
1.330 brouard 12923: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 (nres=2)*/
1.235 brouard 12924: /* 5 0 0 1 */
1.330 brouard 12925: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 (nres=1)*/
1.235 brouard 12926: /* 7 0 1 1 */
12927: /* 8 1 1 1 */
1.237 brouard 12928: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
12929: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
12930: /* V5*age V5 known which value for nres? */
12931: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.334 brouard 12932: for(k1=1, k=0, k4=0, k4q=0; k1 <=cptcovt;k1++){ /* cptcovt number of covariates (excluding 1 and age or age*age) in the MODEL equation.
12933: * loop on position k1 in the MODEL LINE */
1.331 brouard 12934: /* k counting number of combination of single dummies in the equation model */
12935: /* k4 counting single dummies in the equation model */
12936: /* k4q counting single quantitatives in the equation model */
1.344 brouard 12937: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Dummy and Single, fixed or timevarying, k1 is sorting according to MODEL, but k3 to resultline */
1.334 brouard 12938: /* k4+1= (not always if quant in model) position in the resultline V(Tvarsel)=Tvalsel=Tresult[nres][pos](value); V(Tvresult[nres][pos] (variable): V(variable)=value) */
1.332 brouard 12939: /* modelresult[k3]=k1: k3th position in the result line corresponds to the k1 position in the model line (doesn't work with products)*/
1.330 brouard 12940: /* Value in the (current nres) resultline of the variable at the k1th position in the model equation resultmodel[nres][k1]= k3 */
1.332 brouard 12941: /* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline */
12942: /* k3 is the position in the nres result line of the k1th variable of the model equation */
12943: /* Tvarsel[k3]: Name of the variable at the k3th position in the result line. */
12944: /* Tvalsel[k3]: Value of the variable at the k3th position in the result line. */
12945: /* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.334 brouard 12946: /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 12947: /* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1.330 brouard 12948: /* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.332 brouard 12949: k3= resultmodel[nres][k1]; /* From position k1 in model get position k3 in result line */
12950: /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
12951: k2=(int)Tvarsel[k3]; /* from position k3 in resultline get name k2: nres=1 k1=2=>k3=1 Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 (V4); k1=3=>k3=2 Tvarsel[2]=3 (V3)*/
1.330 brouard 12952: k+=Tvalsel[k3]*pow(2,k4); /* nres=1 k1=2 Tvalsel[1]=1 (V4=1); k1=3 k3=2 Tvalsel[2]=0 (V3=0) */
1.334 brouard 12953: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][Name]=Value; stores the value into the name of the variable. */
1.332 brouard 12954: /* Tinvresult[nres][4]=1 */
1.334 brouard 12955: /* Tresult[nres][k4+1]=Tvalsel[k3];/\* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) *\/ */
12956: Tresult[nres][k3]=Tvalsel[k3];/* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) */
12957: /* Tvresult[nres][k4+1]=(int)Tvarsel[k3];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
12958: Tvresult[nres][k3]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
1.237 brouard 12959: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.334 brouard 12960: precov[nres][k1]=Tvalsel[k3]; /* Value from resultline of the variable at the k1 position in the model */
1.342 brouard 12961: /* printf("Decoderesult Dummy k=%d, k1=%d precov[nres=%d][k1=%d]=%.f V(k2=V%d)= Tvalsel[%d]=%d, 2**(%d)\n",k, k1, nres, k1,precov[nres][k1], k2, k3, (int)Tvalsel[k3], k4); */
1.235 brouard 12962: k4++;;
1.331 brouard 12963: }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Quantitative and single */
1.330 brouard 12964: /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.332 brouard 12965: /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.330 brouard 12966: /* Tqinvresult[nres][Name of a quantitative variable]= value of the variable in the result line */
1.332 brouard 12967: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 5 =k3q */
12968: k2q=(int)Tvarsel[k3q]; /* Name of variable at k3q th position in the resultline */
12969: /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.334 brouard 12970: /* Tqresult[nres][k4q+1]=Tvalsel[k3q]; /\* Tqresult[nres][1]=25.1 *\/ */
12971: /* Tvresult[nres][k4q+1]=(int)Tvarsel[k3q];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
12972: /* Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /\* Tvqresult[nres][1]=5 *\/ */
12973: Tqresult[nres][k3q]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
12974: Tvresult[nres][k3q]=(int)Tvarsel[k3q];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
12975: Tvqresult[nres][k3q]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
1.237 brouard 12976: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.330 brouard 12977: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.332 brouard 12978: precov[nres][k1]=Tvalsel[k3q];
1.342 brouard 12979: /* printf("Decoderesult Quantitative nres=%d,precov[nres=%d][k1=%d]=%.f V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, nres, k1,precov[nres][k1], k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]); */
1.235 brouard 12980: k4q++;;
1.350 brouard 12981: }else if( Dummy[k1]==2 ){ /* For dummy with age product "V2+V3+V4+V6+V7+V6*V2+V7*V2+V6*V3+V7*V3+V6*V4+V7*V4+age*V2+age*V3+age*V4+age*V6+age*V7+age*V6*V2+age*V6*V3+age*V7*V3+age*V6*V4+age*V7*V4\r"*/
12982: /* Tvar[k1]; */ /* Age variable */ /* 17 age*V6*V2 ?*/
1.332 brouard 12983: /* Wrong we want the value of variable name Tvar[k1] */
1.350 brouard 12984: if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
12985: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
12986: /* printf("Decoderesult Quantitative or Dummy (not with age) nres=%d k1=%d precov[nres=%d][k1=%d]=%.f V%d(=%.f) * V%d(=%.f) \n",nres, k1, nres, k1,precov[nres][k1], Tvardk[k1][1], TinvDoQresult[nres][Tvardk[k1][1]], Tvardk[k1][2], TinvDoQresult[nres][Tvardk[k1][2]]); */
12987: }else{
12988: k3= resultmodel[nres][k1]; /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
12989: k2=(int)Tvarsel[k3]; /* nres=1 k1=2=>k3=1 Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 (V4); k1=3=>k3=2 Tvarsel[2]=3 (V3)*/
12990: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][4]=1 */
12991: precov[nres][k1]=Tvalsel[k3];
12992: }
1.342 brouard 12993: /* printf("Decoderesult Dummy with age k=%d, k1=%d precov[nres=%d][k1=%d]=%.f Tvar[%d]=V%d k2=Tvarsel[%d]=%d Tvalsel[%d]=%d\n",k, k1, nres, k1,precov[nres][k1], k1, Tvar[k1], k3,(int)Tvarsel[k3], k3, (int)Tvalsel[k3]); */
1.331 brouard 12994: }else if( Dummy[k1]==3 ){ /* For quant with age product */
1.350 brouard 12995: if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
12996: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
12997: /* printf("Decoderesult Quantitative or Dummy (not with age) nres=%d k1=%d precov[nres=%d][k1=%d]=%.f V%d(=%.f) * V%d(=%.f) \n",nres, k1, nres, k1,precov[nres][k1], Tvardk[k1][1], TinvDoQresult[nres][Tvardk[k1][1]], Tvardk[k1][2], TinvDoQresult[nres][Tvardk[k1][2]]); */
12998: }else{
12999: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 25.1=k3q */
13000: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
13001: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* TinvDoQresult[nres][5]=25.1 */
13002: precov[nres][k1]=Tvalsel[k3q];
13003: }
1.342 brouard 13004: /* printf("Decoderesult Quantitative with age nres=%d, k1=%d, precov[nres=%d][k1=%d]=%f Tvar[%d]=V%d V(k2q=%d)= Tvarsel[%d]=%d, Tvalsel[%d]=%f\n",nres, k1, nres, k1,precov[nres][k1], k1, Tvar[k1], k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]); */
1.349 brouard 13005: }else if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
1.332 brouard 13006: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
1.342 brouard 13007: /* printf("Decoderesult Quantitative or Dummy (not with age) nres=%d k1=%d precov[nres=%d][k1=%d]=%.f V%d(=%.f) * V%d(=%.f) \n",nres, k1, nres, k1,precov[nres][k1], Tvardk[k1][1], TinvDoQresult[nres][Tvardk[k1][1]], Tvardk[k1][2], TinvDoQresult[nres][Tvardk[k1][2]]); */
1.330 brouard 13008: }else{
1.332 brouard 13009: printf("Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
13010: fprintf(ficlog,"Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
1.235 brouard 13011: }
13012: }
1.234 brouard 13013:
1.334 brouard 13014: TKresult[nres]=++k; /* Number of combinations of dummies for the nresult and the model =Tvalsel[k3]*pow(2,k4) + 1*/
1.230 brouard 13015: return (0);
13016: }
1.235 brouard 13017:
1.230 brouard 13018: int decodemodel( char model[], int lastobs)
13019: /**< This routine decodes the model and returns:
1.224 brouard 13020: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
13021: * - nagesqr = 1 if age*age in the model, otherwise 0.
13022: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
13023: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
13024: * - cptcovage number of covariates with age*products =2
13025: * - cptcovs number of simple covariates
1.339 brouard 13026: * ncovcolt=ncovcol+nqv+ntv+nqtv total of covariates in the data, not in the model equation
1.224 brouard 13027: * - Tvar[k] is the id of the kth covariate Tvar[1]@12 {1, 2, 3, 8, 10, 11, 8, 3, 7, 8, 5, 6}, thus Tvar[5=V7*V8]=10
1.339 brouard 13028: * which is a new column after the 9 (ncovcol+nqv+ntv+nqtv) variables.
1.319 brouard 13029: * - if k is a product Vn*Vm, covar[k][i] is filled with correct values for each individual
1.224 brouard 13030: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
13031: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
13032: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
13033: */
1.319 brouard 13034: /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 */
1.136 brouard 13035: {
1.359 brouard 13036: int i, j, k, ks;/* , v;*/
1.349 brouard 13037: int n,m;
13038: int j1, k1, k11, k12, k2, k3, k4;
13039: char modelsav[300];
13040: char stra[300], strb[300], strc[300], strd[300],stre[300],strf[300];
1.187 brouard 13041: char *strpt;
1.349 brouard 13042: int **existcomb;
13043:
13044: existcomb=imatrix(1,NCOVMAX,1,NCOVMAX);
13045: for(i=1;i<=NCOVMAX;i++)
13046: for(j=1;j<=NCOVMAX;j++)
13047: existcomb[i][j]=0;
13048:
1.145 brouard 13049: /*removespace(model);*/
1.136 brouard 13050: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.349 brouard 13051: j=0, j1=0, k1=0, k12=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 13052: if (strstr(model,"AGE") !=0){
1.192 brouard 13053: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
13054: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 13055: return 1;
13056: }
1.141 brouard 13057: if (strstr(model,"v") !=0){
1.338 brouard 13058: printf("Error. 'v' must be in upper case 'V' model=1+age+%s ",model);
13059: fprintf(ficlog,"Error. 'v' must be in upper case model=1+age+%s ",model);fflush(ficlog);
1.141 brouard 13060: return 1;
13061: }
1.187 brouard 13062: strcpy(modelsav,model);
13063: if ((strpt=strstr(model,"age*age")) !=0){
1.338 brouard 13064: printf(" strpt=%s, model=1+age+%s\n",strpt, model);
1.187 brouard 13065: if(strpt != model){
1.338 brouard 13066: printf("Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 13067: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 13068: corresponding column of parameters.\n",model);
1.338 brouard 13069: fprintf(ficlog,"Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 13070: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 13071: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 13072: return 1;
1.225 brouard 13073: }
1.187 brouard 13074: nagesqr=1;
13075: if (strstr(model,"+age*age") !=0)
1.234 brouard 13076: substrchaine(modelsav, model, "+age*age");
1.187 brouard 13077: else if (strstr(model,"age*age+") !=0)
1.234 brouard 13078: substrchaine(modelsav, model, "age*age+");
1.187 brouard 13079: else
1.234 brouard 13080: substrchaine(modelsav, model, "age*age");
1.187 brouard 13081: }else
13082: nagesqr=0;
1.349 brouard 13083: if (strlen(modelsav) >1){ /* V2 +V3 +V4 +V6 +V7 +V6*V2 +V7*V2 +V6*V3 +V7*V3 +V6*V4 +V7*V4 +age*V2 +age*V3 +age*V4 +age*V6 +age*V7 +age*V6*V2 +V7*V2 +age*V6*V3 +age*V7*V3 +age*V6*V4 +age*V7*V4 */
1.187 brouard 13084: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
13085: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.351 brouard 13086: cptcovs=0; /**< Number of simple covariates V1 +V1*age +V3 +V3*V4 +age*age => V1 + V3 =4+1-3=2 Wrong */
1.187 brouard 13087: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 13088: * cst, age and age*age
13089: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
13090: /* including age products which are counted in cptcovage.
13091: * but the covariates which are products must be treated
13092: * separately: ncovn=4- 2=2 (V1+V3). */
1.349 brouard 13093: cptcovprod=0; /**< Number of products V1*V2 +v3*age = 2 */
13094: cptcovdageprod=0; /* Number of doouble products with age age*Vn*VM or Vn*age*Vm or Vn*Vm*age */
1.187 brouard 13095: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.349 brouard 13096: cptcovprodage=0;
13097: /* cptcovprodage=nboccstr(modelsav,"age");*/
1.225 brouard 13098:
1.187 brouard 13099: /* Design
13100: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
13101: * < ncovcol=8 >
13102: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
13103: * k= 1 2 3 4 5 6 7 8
13104: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
1.345 brouard 13105: * covar[k,i], are for fixed covariates, value of kth covariate if not including age for individual i:
1.224 brouard 13106: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
13107: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 13108: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
13109: * Tage[++cptcovage]=k
1.345 brouard 13110: * if products, new covar are created after ncovcol + nqv (quanti fixed) with k1
1.187 brouard 13111: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
13112: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
13113: * Tvard[k1][1]=m Tvard[k1][2]=m; Tvard[1][1]=5 (V5) Tvard[1][2]=6 Tvard[2][1]=7 (V7) Tvard[2][2]=8
13114: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
13115: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
13116: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
1.345 brouard 13117: * < ncovcol=8 8 fixed covariate. Additional starts at 9 (V5*V6) and 10(V7*V8) >
1.187 brouard 13118: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
13119: * k= 1 2 3 4 5 6 7 8 9 10 11 12
1.345 brouard 13120: * Tvard[k]= 2 1 3 3 10 11 8 8 5 6 7 8
13121: * p Tvar[1]@12={2, 1, 3, 3, 9, 10, 8, 8}
1.187 brouard 13122: * p Tprod[1]@2={ 6, 5}
13123: *p Tvard[1][1]@4= {7, 8, 5, 6}
13124: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
13125: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
1.319 brouard 13126: *How to reorganize? Tvars(orted)
1.187 brouard 13127: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
13128: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
13129: * {2, 1, 4, 8, 5, 6, 3, 7}
13130: * Struct []
13131: */
1.225 brouard 13132:
1.187 brouard 13133: /* This loop fills the array Tvar from the string 'model'.*/
13134: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
13135: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
13136: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
13137: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
13138: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
13139: /* k=1 Tvar[1]=2 (from V2) */
13140: /* k=5 Tvar[5] */
13141: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 13142: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 13143: /* } */
1.198 brouard 13144: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 13145: /*
13146: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 13147: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
13148: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
13149: }
1.187 brouard 13150: cptcovage=0;
1.351 brouard 13151:
13152: /* First loop in order to calculate */
13153: /* for age*VN*Vm
13154: * Provides, Typevar[k], Tage[cptcovage], existcomb[n][m], FixedV[ncovcolt+k12]
13155: * Tprod[k1]=k Tposprod[k]=k1; Tvard[k1][1] =m;
13156: */
13157: /* Needs FixedV[Tvardk[k][1]] */
13158: /* For others:
13159: * Sets Typevar[k];
13160: * Tvar[k]=ncovcol+nqv+ntv+nqtv+k11;
13161: * Tposprod[k]=k11;
13162: * Tprod[k11]=k;
13163: * Tvardk[k][1] =m;
13164: * Needs FixedV[Tvardk[k][1]] == 0
13165: */
13166:
1.319 brouard 13167: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model line */
13168: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+' cutl from left to right
13169: modelsav==V2+V1+V5*age+V4+V3*age strb=V3*age stra=V2+V1V5*age+V4 */ /* <model> "V5+V4+V3+V4*V3+V5*age+V1*age+V1" strb="V5" stra="V4+V3+V4*V3+V5*age+V1*age+V1" */
13170: if (nbocc(modelsav,'+')==0)
13171: strcpy(strb,modelsav); /* and analyzes it */
1.234 brouard 13172: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
13173: /*scanf("%d",i);*/
1.349 brouard 13174: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V5*age+ V4+V3*age strb=V3*age OR double product with age strb=age*V6*V2 or V6*V2*age or V6*age*V2 */
13175: cutl(strc,strd,strb,'*'); /**< k=1 strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 OR strb=age*V6*V2 strc=V6*V2 strd=age OR c=V2*age OR c=age*V2 */
13176: if(strchr(strc,'*')) { /**< Model with age and DOUBLE product: allowed since 0.99r44, strc=V6*V2 or V2*age or age*V2, strd=age or V6 or V6 */
13177: Typevar[k]=3; /* 3 for age and double product age*Vn*Vm varying of fixed */
13178: if(strstr(strc,"age")!=0) { /* It means that strc=V2*age or age*V2 and thus that strd=Vn */
13179: cutl(stre,strf,strc,'*') ; /* strf=age or Vm, stre=Vm or age. If strc=V6*V2 then strf=V6 and stre=V2 */
13180: strcpy(strc,strb); /* save strb(=age*Vn*Vm) into strc */
13181: /* We want strb=Vn*Vm */
13182: if(strcmp(strf,"age")==0){ /* strf is "age" so that stre=Vm =V2 . */
13183: strcpy(strb,strd);
13184: strcat(strb,"*");
13185: strcat(strb,stre);
13186: }else{ /* strf=Vm If strf=V6 then stre=V2 */
13187: strcpy(strb,strf);
13188: strcat(strb,"*");
13189: strcat(strb,stre);
13190: strcpy(strd,strb); /* in order for strd to not be "age" for next test (will be Vn*Vm */
13191: }
1.351 brouard 13192: /* printf("DEBUG FIXED k=%d, Tage[k]=%d, Tvar[Tage[k]=%d,FixedV[Tvar[Tage[k]]]=%d\n",k,Tage[k],Tvar[Tage[k]],FixedV[Tvar[Tage[k]]]); */
13193: /* FixedV[Tvar[Tage[k]]]=0; /\* HERY not sure if V7*V4*age Fixed might not exist yet*\/ */
1.349 brouard 13194: }else{ /* strc=Vn*Vm (and strd=age) and should be strb=Vn*Vm but want to keep original strb double product */
13195: strcpy(stre,strb); /* save full b in stre */
13196: strcpy(strb,strc); /* save short c in new short b for next block strb=Vn*Vm*/
13197: strcpy(strf,strc); /* save short c in new short f */
13198: cutl(strc,strd,strf,'*'); /* We get strd=Vn and strc=Vm for next block (strb=Vn*Vm)*/
13199: /* strcpy(strc,stre);*/ /* save full e in c for future */
13200: }
13201: cptcovdageprod++; /* double product with age Which product is it? */
13202: /* strcpy(strb,strc); /\* strb was age*V6*V2 or V6*V2*age or V6*age*V2 IS now V6*V2 or V2*age or age*V2 *\/ */
13203: /* cutl(strc,strd,strb,'*'); /\* strd= V6 or V2 or age and strc= V2 or age or V2 *\/ */
1.234 brouard 13204: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
1.349 brouard 13205: n=atoi(stre);
1.234 brouard 13206: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
1.349 brouard 13207: m=atoi(strc);
13208: cptcovage++; /* Counts the number of covariates which include age as a product */
13209: Tage[cptcovage]=k; /* For age*V3*V2 gives the position in model of covariates associated with age Tage[1]=6 HERY too*/
13210: if(existcomb[n][m] == 0){
13211: /* r /home/brouard/Documents/Recherches/REVES/Zachary/Zach-2022/Feinuo_Sun/Feinuo-threeway/femV12V15_3wayintNBe.imach */
13212: printf("Warning in model combination V%d*V%d should exist in the model before adding V%d*V%d*age !\n",n,m,n,m);
13213: fprintf(ficlog,"Warning in model combination V%d*V%d should exist in the model before adding V%d*V%d*age !\n",n,m,n,m);
13214: fflush(ficlog);
13215: k1++; /* The combination Vn*Vm will be in the model so we create it at k1 */
13216: k12++;
13217: existcomb[n][m]=k1;
13218: existcomb[m][n]=k1;
13219: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1;
13220: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2+ age*V6*V3 Gives the k position of the k1 double product Vn*Vm or age*Vn*Vm*/
13221: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 Gives the k1 double product Vn*Vm or age*Vn*Vm at the k position */
13222: Tvard[k1][1] =m; /* m 1 for V1*/
13223: Tvardk[k][1] =m; /* m 1 for V1*/
13224: Tvard[k1][2] =n; /* n 4 for V4*/
13225: Tvardk[k][2] =n; /* n 4 for V4*/
1.351 brouard 13226: /* Tvar[Tage[cptcovage]]=k1;*/ /* Tvar[6=age*V3*V2]=9 (new fixed covariate) */ /* We don't know about Fixed yet HERE */
1.349 brouard 13227: if( FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){ /* If the product is a fixed covariate then we feed the new column with Vn*Vm */
13228: for (i=1; i<=lastobs;i++){/* For fixed product */
13229: /* Computes the new covariate which is a product of
13230: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
13231: covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
13232: }
13233: cptcovprodage++; /* Counting the number of fixed covariate with age */
13234: FixedV[ncovcolt+k12]=0; /* We expand Vn*Vm */
13235: k12++;
13236: FixedV[ncovcolt+k12]=0;
13237: }else{ /*End of FixedV */
13238: cptcovprodvage++; /* Counting the number of varying covariate with age */
13239: FixedV[ncovcolt+k12]=1; /* We expand Vn*Vm */
13240: k12++;
13241: FixedV[ncovcolt+k12]=1;
13242: }
13243: }else{ /* k1 Vn*Vm already exists */
13244: k11=existcomb[n][m];
13245: Tposprod[k]=k11; /* OK */
13246: Tvar[k]=Tvar[Tprod[k11]]; /* HERY */
13247: Tvardk[k][1]=m;
13248: Tvardk[k][2]=n;
13249: if( FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){ /* If the product is a fixed covariate then we feed the new column with Vn*Vm */
13250: /*cptcovage++;*/ /* Counts the number of covariates which include age as a product */
13251: cptcovprodage++; /* Counting the number of fixed covariate with age */
13252: /*Tage[cptcovage]=k;*/ /* For age*V3*V2 Tage[1]=V3*V3=9 HERY too*/
13253: Tvar[Tage[cptcovage]]=k1;
13254: FixedV[ncovcolt+k12]=0; /* We expand Vn*Vm */
13255: k12++;
13256: FixedV[ncovcolt+k12]=0;
13257: }else{ /* Already exists but time varying (and age) */
13258: /*cptcovage++;*/ /* Counts the number of covariates which include age as a product */
13259: /*Tage[cptcovage]=k;*/ /* For age*V3*V2 Tage[1]=V3*V3=9 HERY too*/
13260: /* Tvar[Tage[cptcovage]]=k1; */
13261: cptcovprodvage++;
13262: FixedV[ncovcolt+k12]=1; /* We expand Vn*Vm */
13263: k12++;
13264: FixedV[ncovcolt+k12]=1;
13265: }
13266: }
13267: /* Tage[cptcovage]=k; /\* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
13268: /* Tvar[k]=k11; /\* HERY *\/ */
13269: } else {/* simple product strb=age*Vn so that c=Vn and d=age, or strb=Vn*age so that c=age and d=Vn, or b=Vn*Vm so that c=Vm and d=Vn */
13270: cptcovprod++;
13271: if (strcmp(strc,"age")==0) { /**< Model includes age: strb= Vn*age c=age d=Vn*/
13272: /* covar is not filled and then is empty */
13273: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
13274: Tvar[k]=atoi(stre); /* V2+V1+V5*age+V4+V3*age Tvar[5]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */
13275: Typevar[k]=1; /* 1 for age product */
13276: cptcovage++; /* Counts the number of covariates which include age as a product */
13277: Tage[cptcovage]=k; /* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
13278: if( FixedV[Tvar[k]] == 0){
13279: cptcovprodage++; /* Counting the number of fixed covariate with age */
13280: }else{
13281: cptcovprodvage++; /* Counting the number of fixedvarying covariate with age */
13282: }
13283: /*printf("stre=%s ", stre);*/
13284: } else if (strcmp(strd,"age")==0) { /* strb= age*Vn c=Vn */
13285: cutl(stre,strb,strc,'V');
13286: Tvar[k]=atoi(stre);
13287: Typevar[k]=1; /* 1 for age product */
13288: cptcovage++;
13289: Tage[cptcovage]=k;
13290: if( FixedV[Tvar[k]] == 0){
13291: cptcovprodage++; /* Counting the number of fixed covariate with age */
13292: }else{
13293: cptcovprodvage++; /* Counting the number of fixedvarying covariate with age */
1.339 brouard 13294: }
1.349 brouard 13295: }else{ /* for product Vn*Vm */
13296: Typevar[k]=2; /* 2 for product Vn*Vm */
13297: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
13298: n=atoi(stre);
13299: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
13300: m=atoi(strc);
13301: k1++;
13302: cptcovprodnoage++;
13303: if(existcomb[n][m] != 0 || existcomb[m][n] != 0){
13304: printf("Warning in model combination V%d*V%d already exists in the model in position k1=%d!\n",n,m,existcomb[n][m]);
13305: fprintf(ficlog,"Warning in model combination V%d*V%d already exists in the model in position k1=%d!\n",n,m,existcomb[n][m]);
13306: fflush(ficlog);
13307: k11=existcomb[n][m];
13308: Tvar[k]=ncovcol+nqv+ntv+nqtv+k11;
13309: Tposprod[k]=k11;
13310: Tprod[k11]=k;
13311: Tvardk[k][1] =m; /* m 1 for V1*/
13312: /* Tvard[k11][1] =m; /\* n 4 for V4*\/ */
13313: Tvardk[k][2] =n; /* n 4 for V4*/
13314: /* Tvard[k11][2] =n; /\* n 4 for V4*\/ */
13315: }else{ /* combination Vn*Vm doesn't exist we create it (no age)*/
13316: existcomb[n][m]=k1;
13317: existcomb[m][n]=k1;
13318: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* ncovcolt+k1; For model-covariate k tells which data-covariate to use but
13319: because this model-covariate is a construction we invent a new column
13320: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
13321: If already ncovcol=4 and model= V2 + V1 + V1*V4 + age*V3 + V3*V2
13322: thus after V4 we invent V5 and V6 because age*V3 will be computed in 4
13323: Tvar[3=V1*V4]=4+1=5 Tvar[5=V3*V2]=4 + 2= 6, Tvar[4=age*V3]=3 etc */
13324: /* Please remark that the new variables are model dependent */
13325: /* If we have 4 variable but the model uses only 3, like in
13326: * model= V1 + age*V1 + V2 + V3 + age*V2 + age*V3 + V1*V2 + V1*V3
13327: * k= 1 2 3 4 5 6 7 8
13328: * Tvar[k]=1 1 2 3 2 3 (5 6) (and not 4 5 because of V4 missing)
13329: * Tage[kk] [1]= 2 [2]=5 [3]=6 kk=1 to cptcovage=3
13330: * Tvar[Tage[kk]][1]=2 [2]=2 [3]=3
13331: */
13332: /* We need to feed some variables like TvarVV, but later on next loop because of ncovv (k2) is not correct */
13333: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 +V6*V2*age */
13334: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 */
13335: Tvard[k1][1] =m; /* m 1 for V1*/
13336: Tvardk[k][1] =m; /* m 1 for V1*/
13337: Tvard[k1][2] =n; /* n 4 for V4*/
13338: Tvardk[k][2] =n; /* n 4 for V4*/
13339: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
13340: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
13341: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
13342: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
13343: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
13344: if( FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){ /* If the product is a fixed covariate then we feed the new column with Vn*Vm */
13345: for (i=1; i<=lastobs;i++){/* For fixed product */
13346: /* Computes the new covariate which is a product of
13347: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
13348: covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
13349: }
13350: /* TvarVV[k2]=n; */
13351: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
13352: /* TvarVV[k2+1]=m; */
13353: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
13354: }else{ /* not FixedV */
13355: /* TvarVV[k2]=n; */
13356: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
13357: /* TvarVV[k2+1]=m; */
13358: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
13359: }
13360: } /* End of creation of Vn*Vm if not created by age*Vn*Vm earlier */
13361: } /* End of product Vn*Vm */
13362: } /* End of age*double product or simple product */
13363: }else { /* not a product */
1.234 brouard 13364: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
13365: /* scanf("%d",i);*/
13366: cutl(strd,strc,strb,'V');
13367: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
13368: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
13369: Tvar[k]=atoi(strd);
13370: Typevar[k]=0; /* 0 for simple covariates */
13371: }
13372: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 13373: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 13374: scanf("%d",i);*/
1.187 brouard 13375: } /* end of loop + on total covariates */
1.351 brouard 13376:
13377:
1.187 brouard 13378: } /* end if strlen(modelsave == 0) age*age might exist */
13379: } /* end if strlen(model == 0) */
1.349 brouard 13380: cptcovs=cptcovt - cptcovdageprod - cptcovprod;/**< Number of simple covariates V1 +V1*age +V3 +V3*V4 +age*age + age*v4*V3=> V1 + V3 =4+1-3=2 */
13381:
1.136 brouard 13382: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
13383: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 13384:
1.136 brouard 13385: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 13386: printf("cptcovprod=%d ", cptcovprod);
13387: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
13388: scanf("%d ",i);*/
13389:
13390:
1.230 brouard 13391: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
13392: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 13393: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
13394: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
13395: k = 1 2 3 4 5 6 7 8 9
13396: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
1.319 brouard 13397: Typevar[k]= 0 0 0 2 1 0 2 1 0
1.227 brouard 13398: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
13399: Dummy[k] 1 0 0 0 3 1 1 2 3
13400: Tmodelind[combination of covar]=k;
1.225 brouard 13401: */
13402: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 13403: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 13404: /* Tvar[k] is the value n of Vn with n varying for 1 to nvcol, or p Vp=Vn*Vm for product */
1.226 brouard 13405: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.318 brouard 13406: printf("Model=1+age+%s\n\
1.349 brouard 13407: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product, 3 for double product with age \n\
1.227 brouard 13408: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
13409: Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product\n",model);
1.318 brouard 13410: fprintf(ficlog,"Model=1+age+%s\n\
1.349 brouard 13411: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product, 3 for double product with age \n\
1.227 brouard 13412: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
13413: Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product\n",model);
1.342 brouard 13414: for(k=-1;k<=NCOVMAX; k++){ Fixed[k]=0; Dummy[k]=0;}
13415: for(k=1;k<=NCOVMAX; k++){TvarFind[k]=0; TvarVind[k]=0;}
1.351 brouard 13416:
13417:
13418: /* Second loop for calculating Fixed[k], Dummy[k]*/
13419:
13420:
1.349 brouard 13421: for(k=1, ncovf=0, nsd=0, nsq=0, ncovv=0,ncovva=0,ncovvta=0, ncova=0, ncoveff=0, nqfveff=0, ntveff=0, nqtveff=0, ncovvt=0;k<=cptcovt; k++){ /* or cptocvt loop on k from model */
1.234 brouard 13422: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 13423: Fixed[k]= 0;
13424: Dummy[k]= 0;
1.225 brouard 13425: ncoveff++;
1.232 brouard 13426: ncovf++;
1.234 brouard 13427: nsd++;
13428: modell[k].maintype= FTYPE;
13429: TvarsD[nsd]=Tvar[k];
13430: TvarsDind[nsd]=k;
1.330 brouard 13431: TnsdVar[Tvar[k]]=nsd;
1.234 brouard 13432: TvarF[ncovf]=Tvar[k];
13433: TvarFind[ncovf]=k;
13434: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
13435: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.339 brouard 13436: /* }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /\* Product of fixed dummy (<=ncovcol) covariates For a fixed product k is higher than ncovcol *\/ */
1.240 brouard 13437: }else if( Tvar[k] <=ncovcol+nqv && Typevar[k]==0){/* Remind that product Vn*Vm are added in k Only simple fixed quantitative variable */
1.227 brouard 13438: Fixed[k]= 0;
13439: Dummy[k]= 1;
1.230 brouard 13440: nqfveff++;
1.234 brouard 13441: modell[k].maintype= FTYPE;
13442: modell[k].subtype= FQ;
13443: nsq++;
1.334 brouard 13444: TvarsQ[nsq]=Tvar[k]; /* Gives the variable name (extended to products) of first nsq simple quantitative covariates (fixed or time vary see below */
13445: TvarsQind[nsq]=k; /* Gives the position in the model equation of the first nsq simple quantitative covariates (fixed or time vary) */
1.232 brouard 13446: ncovf++;
1.234 brouard 13447: TvarF[ncovf]=Tvar[k];
13448: TvarFind[ncovf]=k;
1.231 brouard 13449: TvarFQ[nqfveff]=Tvar[k]-ncovcol; /* TvarFQ[1]=V2-1=1st in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1.230 brouard 13450: TvarFQind[nqfveff]=k; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1.242 brouard 13451: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.339 brouard 13452: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
13453: /* model V1+V3+age*V1+age*V3+V1*V3 */
13454: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
13455: ncovvt++;
13456: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
13457: TvarVVind[ncovvt]=k; /* TvarVVind[1]=2 (second position in the model equation */
13458:
1.227 brouard 13459: Fixed[k]= 1;
13460: Dummy[k]= 0;
1.225 brouard 13461: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 13462: modell[k].maintype= VTYPE;
13463: modell[k].subtype= VD;
13464: nsd++;
13465: TvarsD[nsd]=Tvar[k];
13466: TvarsDind[nsd]=k;
1.330 brouard 13467: TnsdVar[Tvar[k]]=nsd; /* To be verified */
1.234 brouard 13468: ncovv++; /* Only simple time varying variables */
13469: TvarV[ncovv]=Tvar[k];
1.242 brouard 13470: TvarVind[ncovv]=k; /* TvarVind[2]=2 TvarVind[3]=3 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Any time varying singele */
1.231 brouard 13471: TvarVD[ntveff]=Tvar[k]; /* TvarVD[1]=V4 TvarVD[2]=V3 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple time varying dummy variable */
13472: TvarVDind[ntveff]=k; /* TvarVDind[1]=2 TvarVDind[2]=3 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple time varying dummy variable */
1.228 brouard 13473: printf("Quasi Tmodelind[%d]=%d,Tvar[Tmodelind[%d]]=V%d, ncovcol=%d, nqv=%d,Tvar[k]- ncovcol-nqv=%d\n",ntveff,k,ntveff,Tvar[k], ncovcol, nqv,Tvar[k]- ncovcol-nqv);
13474: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 13475: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.339 brouard 13476: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
13477: /* model V1+V3+age*V1+age*V3+V1*V3 */
13478: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
13479: ncovvt++;
13480: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
13481: TvarVVind[ncovvt]=k; /* TvarVV[1]=V3 (first time varying in the model equation */
13482:
1.234 brouard 13483: Fixed[k]= 1;
13484: Dummy[k]= 1;
13485: nqtveff++;
13486: modell[k].maintype= VTYPE;
13487: modell[k].subtype= VQ;
13488: ncovv++; /* Only simple time varying variables */
13489: nsq++;
1.334 brouard 13490: TvarsQ[nsq]=Tvar[k]; /* k=1 Tvar=5 nsq=1 TvarsQ[1]=5 */ /* Gives the variable name (extended to products) of first nsq simple quantitative covariates (fixed or time vary here) */
13491: TvarsQind[nsq]=k; /* For single quantitative covariate gives the model position of each single quantitative covariate *//* Gives the position in the model equation of the first nsq simple quantitative covariates (fixed or time vary) */
1.234 brouard 13492: TvarV[ncovv]=Tvar[k];
1.242 brouard 13493: TvarVind[ncovv]=k; /* TvarVind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Any time varying singele */
1.231 brouard 13494: TvarVQ[nqtveff]=Tvar[k]; /* TvarVQ[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple time varying quantitative variable */
13495: TvarVQind[nqtveff]=k; /* TvarVQind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple time varying quantitative variable */
1.234 brouard 13496: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
13497: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
1.349 brouard 13498: /* printf("Quasi TmodelQind[%d]=%d,Tvar[TmodelQind[%d]]=V%d, ncovcol=%d, nqv=%d, ntv=%Ad,Tvar[k]- ncovcol-nqv-ntv=%d\n",nqtveff,k,nqtveff,Tvar[k], ncovcol, nqv, ntv, Tvar[k]- ncovcol-nqv-ntv); */
1.342 brouard 13499: /* printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv); */
1.227 brouard 13500: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 13501: ncova++;
13502: TvarA[ncova]=Tvar[k];
13503: TvarAind[ncova]=k;
1.349 brouard 13504: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
13505: /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
1.231 brouard 13506: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 13507: Fixed[k]= 2;
13508: Dummy[k]= 2;
13509: modell[k].maintype= ATYPE;
13510: modell[k].subtype= APFD;
1.349 brouard 13511: ncovta++;
13512: TvarAVVA[ncovta]=Tvar[k]; /* (2)age*V3 */
13513: TvarAVVAind[ncovta]=k;
1.240 brouard 13514: /* ncoveff++; */
1.227 brouard 13515: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 13516: Fixed[k]= 2;
13517: Dummy[k]= 3;
13518: modell[k].maintype= ATYPE;
13519: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
1.349 brouard 13520: ncovta++;
13521: TvarAVVA[ncovta]=Tvar[k]; /* */
13522: TvarAVVAind[ncovta]=k;
1.240 brouard 13523: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 13524: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 13525: Fixed[k]= 3;
13526: Dummy[k]= 2;
13527: modell[k].maintype= ATYPE;
13528: modell[k].subtype= APVD; /* Product age * varying dummy */
1.349 brouard 13529: ncovva++;
13530: TvarVVA[ncovva]=Tvar[k]; /* (1)+age*V6 + (2)age*V7 */
13531: TvarVVAind[ncovva]=k;
13532: ncovta++;
13533: TvarAVVA[ncovta]=Tvar[k]; /* */
13534: TvarAVVAind[ncovta]=k;
1.240 brouard 13535: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 13536: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 13537: Fixed[k]= 3;
13538: Dummy[k]= 3;
13539: modell[k].maintype= ATYPE;
13540: modell[k].subtype= APVQ; /* Product age * varying quantitative */
1.349 brouard 13541: ncovva++;
13542: TvarVVA[ncovva]=Tvar[k]; /* */
13543: TvarVVAind[ncovva]=k;
13544: ncovta++;
13545: TvarAVVA[ncovta]=Tvar[k]; /* (1)+age*V6 + (2)age*V7 */
13546: TvarAVVAind[ncovta]=k;
1.240 brouard 13547: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 13548: }
1.349 brouard 13549: }else if( Tposprod[k]>0 && Typevar[k]==2){ /* Detects if fixed product no age Vm*Vn */
13550: printf("MEMORY ERRORR k=%d Tposprod[k]=%d, Typevar[k]=%d\n ",k, Tposprod[k], Typevar[k]);
13551: if(FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){ /* Needs a fixed product Product of fixed dummy (<=ncovcol) covariates For a fixed product k is higher than ncovcol V3*V2 */
13552: printf("MEMORY ERRORR k=%d Tvardk[k][1]=%d, Tvardk[k][2]=%d, FixedV[Tvardk[k][1]]=%d,FixedV[Tvardk[k][2]]=%d\n ",k,Tvardk[k][1],Tvardk[k][2],FixedV[Tvardk[k][1]],FixedV[Tvardk[k][2]]);
13553: Fixed[k]= 0;
13554: Dummy[k]= 0;
13555: ncoveff++;
13556: ncovf++;
13557: /* ncovv++; */
13558: /* TvarVV[ncovv]=Tvardk[k][1]; */
13559: /* FixedV[ncovcolt+ncovv]=0; /\* or FixedV[TvarVV[ncovv]]=0 HERE *\/ */
13560: /* ncovv++; */
13561: /* TvarVV[ncovv]=Tvardk[k][2]; */
13562: /* FixedV[ncovcolt+ncovv]=0; /\* or FixedV[TvarVV[ncovv]]=0 HERE *\/ */
13563: modell[k].maintype= FTYPE;
13564: TvarF[ncovf]=Tvar[k];
13565: /* TnsdVar[Tvar[k]]=nsd; */ /* To be done */
13566: TvarFind[ncovf]=k;
13567: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
13568: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
13569: }else{/* product varying Vn * Vm without age, V1+V3+age*V1+age*V3+V1*V3 looking at V1*V3, Typevar={0, 0, 1, 1, 2}, k=5, V1 is fixed, V3 is timevary, V5 is a product */
13570: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
13571: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age*/
13572: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
13573: k1=Tposprod[k]; /* Position in the products of product k, Tposprod={0, 0, 0, 0, 1, 1} k1=1 first product but second time varying because of V3 */
13574: ncovvt++;
13575: TvarVV[ncovvt]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */
13576: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
13577: ncovvt++;
13578: TvarVV[ncovvt]=Tvard[k1][2]; /* TvarVV[3]=V3 */
13579: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
13580:
13581: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
13582: /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
13583:
13584: if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */
13585: if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */
13586: Fixed[k]= 1;
13587: Dummy[k]= 0;
13588: modell[k].maintype= FTYPE;
13589: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
13590: ncovf++; /* Fixed variables without age */
13591: TvarF[ncovf]=Tvar[k];
13592: TvarFind[ncovf]=k;
13593: }else if(Tvard[k1][2] <=ncovcol+nqv){ /* Vm is quanti fixed */
13594: Fixed[k]= 0; /* Fixed product */
13595: Dummy[k]= 1;
13596: modell[k].maintype= FTYPE;
13597: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
13598: ncovf++; /* Varying variables without age */
13599: TvarF[ncovf]=Tvar[k];
13600: TvarFind[ncovf]=k;
13601: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is a time varying dummy covariate */
13602: Fixed[k]= 1;
13603: Dummy[k]= 0;
13604: modell[k].maintype= VTYPE;
13605: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
13606: ncovv++; /* Varying variables without age */
13607: TvarV[ncovv]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */
13608: TvarVind[ncovv]=k;/* TvarVind[1]=5 */
13609: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */
13610: Fixed[k]= 1;
13611: Dummy[k]= 1;
13612: modell[k].maintype= VTYPE;
13613: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
13614: ncovv++; /* Varying variables without age */
13615: TvarV[ncovv]=Tvar[k];
13616: TvarVind[ncovv]=k;
13617: }
13618: }else if(Tvard[k1][1] <=ncovcol+nqv){ /* Vn is fixed quanti */
13619: if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */
13620: Fixed[k]= 0; /* Fixed product */
13621: Dummy[k]= 1;
13622: modell[k].maintype= FTYPE;
13623: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
13624: ncovf++; /* Fixed variables without age */
13625: TvarF[ncovf]=Tvar[k];
13626: TvarFind[ncovf]=k;
13627: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is time varying */
13628: Fixed[k]= 1;
13629: Dummy[k]= 1;
13630: modell[k].maintype= VTYPE;
13631: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
13632: ncovv++; /* Varying variables without age */
13633: TvarV[ncovv]=Tvar[k];
13634: TvarVind[ncovv]=k;
13635: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is time varying quanti */
13636: Fixed[k]= 1;
13637: Dummy[k]= 1;
13638: modell[k].maintype= VTYPE;
13639: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
13640: ncovv++; /* Varying variables without age */
13641: TvarV[ncovv]=Tvar[k];
13642: TvarVind[ncovv]=k;
13643: ncovv++; /* Varying variables without age */
13644: TvarV[ncovv]=Tvar[k];
13645: TvarVind[ncovv]=k;
13646: }
13647: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ /* Vn is time varying dummy */
13648: if(Tvard[k1][2] <=ncovcol){
13649: Fixed[k]= 1;
13650: Dummy[k]= 1;
13651: modell[k].maintype= VTYPE;
13652: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
13653: ncovv++; /* Varying variables without age */
13654: TvarV[ncovv]=Tvar[k];
13655: TvarVind[ncovv]=k;
13656: }else if(Tvard[k1][2] <=ncovcol+nqv){
13657: Fixed[k]= 1;
13658: Dummy[k]= 1;
13659: modell[k].maintype= VTYPE;
13660: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
13661: ncovv++; /* Varying variables without age */
13662: TvarV[ncovv]=Tvar[k];
13663: TvarVind[ncovv]=k;
13664: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
13665: Fixed[k]= 1;
13666: Dummy[k]= 0;
13667: modell[k].maintype= VTYPE;
13668: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
13669: ncovv++; /* Varying variables without age */
13670: TvarV[ncovv]=Tvar[k];
13671: TvarVind[ncovv]=k;
13672: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
13673: Fixed[k]= 1;
13674: Dummy[k]= 1;
13675: modell[k].maintype= VTYPE;
13676: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
13677: ncovv++; /* Varying variables without age */
13678: TvarV[ncovv]=Tvar[k];
13679: TvarVind[ncovv]=k;
13680: }
13681: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ /* Vn is time varying quanti */
13682: if(Tvard[k1][2] <=ncovcol){
13683: Fixed[k]= 1;
13684: Dummy[k]= 1;
13685: modell[k].maintype= VTYPE;
13686: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
13687: ncovv++; /* Varying variables without age */
13688: TvarV[ncovv]=Tvar[k];
13689: TvarVind[ncovv]=k;
13690: }else if(Tvard[k1][2] <=ncovcol+nqv){
13691: Fixed[k]= 1;
13692: Dummy[k]= 1;
13693: modell[k].maintype= VTYPE;
13694: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
13695: ncovv++; /* Varying variables without age */
13696: TvarV[ncovv]=Tvar[k];
13697: TvarVind[ncovv]=k;
13698: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
13699: Fixed[k]= 1;
13700: Dummy[k]= 1;
13701: modell[k].maintype= VTYPE;
13702: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
13703: ncovv++; /* Varying variables without age */
13704: TvarV[ncovv]=Tvar[k];
13705: TvarVind[ncovv]=k;
13706: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
13707: Fixed[k]= 1;
13708: Dummy[k]= 1;
13709: modell[k].maintype= VTYPE;
13710: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
13711: ncovv++; /* Varying variables without age */
13712: TvarV[ncovv]=Tvar[k];
13713: TvarVind[ncovv]=k;
13714: }
13715: }else{
13716: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
13717: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
13718: } /*end k1*/
13719: }
13720: }else if(Typevar[k] == 3){ /* product Vn * Vm with age, V1+V3+age*V1+age*V3+V1*V3 looking at V1*V3, Typevar={0, 0, 1, 1, 2}, k=5, V1 is fixed, V3 is timevary, V5 is a product */
1.339 brouard 13721: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
1.349 brouard 13722: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age*/
13723: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
13724: k1=Tposprod[k]; /* Position in the products of product k, Tposprod={0, 0, 0, 0, 1, 1} k1=1 first product but second time varying because of V3 */
13725: ncova++;
13726: TvarA[ncova]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */
13727: TvarAind[ncova]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
13728: ncova++;
13729: TvarA[ncova]=Tvard[k1][2]; /* TvarVV[3]=V3 */
13730: TvarAind[ncova]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
1.339 brouard 13731:
1.349 brouard 13732: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
13733: /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
13734: if( FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){
13735: ncovta++;
13736: TvarAVVA[ncovta]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
13737: TvarAVVAind[ncovta]=k;
13738: ncovta++;
13739: TvarAVVA[ncovta]=Tvard[k1][2]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
13740: TvarAVVAind[ncovta]=k;
13741: }else{
13742: ncovva++; /* HERY reached */
13743: TvarVVA[ncovva]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
13744: TvarVVAind[ncovva]=k;
13745: ncovva++;
13746: TvarVVA[ncovva]=Tvard[k1][2]; /* */
13747: TvarVVAind[ncovva]=k;
13748: ncovta++;
13749: TvarAVVA[ncovta]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
13750: TvarAVVAind[ncovta]=k;
13751: ncovta++;
13752: TvarAVVA[ncovta]=Tvard[k1][2]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
13753: TvarAVVAind[ncovta]=k;
13754: }
1.339 brouard 13755: if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */
13756: if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */
1.349 brouard 13757: Fixed[k]= 2;
13758: Dummy[k]= 2;
1.240 brouard 13759: modell[k].maintype= FTYPE;
13760: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
1.349 brouard 13761: /* TvarF[ncova]=Tvar[k]; /\* Problem to solve *\/ */
13762: /* TvarFind[ncova]=k; */
1.339 brouard 13763: }else if(Tvard[k1][2] <=ncovcol+nqv){ /* Vm is quanti fixed */
1.349 brouard 13764: Fixed[k]= 2; /* Fixed product */
13765: Dummy[k]= 3;
1.240 brouard 13766: modell[k].maintype= FTYPE;
13767: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
1.349 brouard 13768: /* TvarF[ncova]=Tvar[k]; */
13769: /* TvarFind[ncova]=k; */
1.339 brouard 13770: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is a time varying dummy covariate */
1.349 brouard 13771: Fixed[k]= 3;
13772: Dummy[k]= 2;
1.240 brouard 13773: modell[k].maintype= VTYPE;
13774: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
1.349 brouard 13775: TvarV[ncova]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */
13776: TvarVind[ncova]=k;/* TvarVind[1]=5 */
1.339 brouard 13777: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */
1.349 brouard 13778: Fixed[k]= 3;
13779: Dummy[k]= 3;
1.240 brouard 13780: modell[k].maintype= VTYPE;
13781: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
1.349 brouard 13782: /* ncovv++; /\* Varying variables without age *\/ */
13783: /* TvarV[ncovv]=Tvar[k]; */
13784: /* TvarVind[ncovv]=k; */
1.240 brouard 13785: }
1.339 brouard 13786: }else if(Tvard[k1][1] <=ncovcol+nqv){ /* Vn is fixed quanti */
13787: if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */
1.349 brouard 13788: Fixed[k]= 2; /* Fixed product */
13789: Dummy[k]= 2;
1.240 brouard 13790: modell[k].maintype= FTYPE;
13791: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
1.349 brouard 13792: /* ncova++; /\* Fixed variables with age *\/ */
13793: /* TvarF[ncovf]=Tvar[k]; */
13794: /* TvarFind[ncovf]=k; */
1.339 brouard 13795: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is time varying */
1.349 brouard 13796: Fixed[k]= 2;
13797: Dummy[k]= 3;
1.240 brouard 13798: modell[k].maintype= VTYPE;
13799: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
1.349 brouard 13800: /* ncova++; /\* Varying variables with age *\/ */
13801: /* TvarV[ncova]=Tvar[k]; */
13802: /* TvarVind[ncova]=k; */
1.339 brouard 13803: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is time varying quanti */
1.349 brouard 13804: Fixed[k]= 3;
13805: Dummy[k]= 2;
1.240 brouard 13806: modell[k].maintype= VTYPE;
13807: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
1.349 brouard 13808: ncova++; /* Varying variables without age */
13809: TvarV[ncova]=Tvar[k];
13810: TvarVind[ncova]=k;
13811: /* ncova++; /\* Varying variables without age *\/ */
13812: /* TvarV[ncova]=Tvar[k]; */
13813: /* TvarVind[ncova]=k; */
1.240 brouard 13814: }
1.339 brouard 13815: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ /* Vn is time varying dummy */
1.240 brouard 13816: if(Tvard[k1][2] <=ncovcol){
1.349 brouard 13817: Fixed[k]= 2;
13818: Dummy[k]= 2;
1.240 brouard 13819: modell[k].maintype= VTYPE;
13820: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
1.349 brouard 13821: /* ncova++; /\* Varying variables with age *\/ */
13822: /* TvarV[ncova]=Tvar[k]; */
13823: /* TvarVind[ncova]=k; */
1.240 brouard 13824: }else if(Tvard[k1][2] <=ncovcol+nqv){
1.349 brouard 13825: Fixed[k]= 2;
13826: Dummy[k]= 3;
1.240 brouard 13827: modell[k].maintype= VTYPE;
13828: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
1.349 brouard 13829: /* ncova++; /\* Varying variables with age *\/ */
13830: /* TvarV[ncova]=Tvar[k]; */
13831: /* TvarVind[ncova]=k; */
1.240 brouard 13832: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
1.349 brouard 13833: Fixed[k]= 3;
13834: Dummy[k]= 2;
1.240 brouard 13835: modell[k].maintype= VTYPE;
13836: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
1.349 brouard 13837: /* ncova++; /\* Varying variables with age *\/ */
13838: /* TvarV[ncova]=Tvar[k]; */
13839: /* TvarVind[ncova]=k; */
1.240 brouard 13840: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
1.349 brouard 13841: Fixed[k]= 3;
13842: Dummy[k]= 3;
1.240 brouard 13843: modell[k].maintype= VTYPE;
13844: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
1.349 brouard 13845: /* ncova++; /\* Varying variables with age *\/ */
13846: /* TvarV[ncova]=Tvar[k]; */
13847: /* TvarVind[ncova]=k; */
1.240 brouard 13848: }
1.339 brouard 13849: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ /* Vn is time varying quanti */
1.240 brouard 13850: if(Tvard[k1][2] <=ncovcol){
1.349 brouard 13851: Fixed[k]= 2;
13852: Dummy[k]= 2;
1.240 brouard 13853: modell[k].maintype= VTYPE;
13854: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
1.349 brouard 13855: /* ncova++; /\* Varying variables with age *\/ */
13856: /* TvarV[ncova]=Tvar[k]; */
13857: /* TvarVind[ncova]=k; */
1.240 brouard 13858: }else if(Tvard[k1][2] <=ncovcol+nqv){
1.349 brouard 13859: Fixed[k]= 2;
13860: Dummy[k]= 3;
1.240 brouard 13861: modell[k].maintype= VTYPE;
13862: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
1.349 brouard 13863: /* ncova++; /\* Varying variables with age *\/ */
13864: /* TvarV[ncova]=Tvar[k]; */
13865: /* TvarVind[ncova]=k; */
1.240 brouard 13866: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
1.349 brouard 13867: Fixed[k]= 3;
13868: Dummy[k]= 2;
1.240 brouard 13869: modell[k].maintype= VTYPE;
13870: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
1.349 brouard 13871: /* ncova++; /\* Varying variables with age *\/ */
13872: /* TvarV[ncova]=Tvar[k]; */
13873: /* TvarVind[ncova]=k; */
1.240 brouard 13874: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
1.349 brouard 13875: Fixed[k]= 3;
13876: Dummy[k]= 3;
1.240 brouard 13877: modell[k].maintype= VTYPE;
13878: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
1.349 brouard 13879: /* ncova++; /\* Varying variables with age *\/ */
13880: /* TvarV[ncova]=Tvar[k]; */
13881: /* TvarVind[ncova]=k; */
1.240 brouard 13882: }
1.227 brouard 13883: }else{
1.240 brouard 13884: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
13885: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
13886: } /*end k1*/
1.349 brouard 13887: } else{
1.226 brouard 13888: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
13889: fprintf(ficlog,"Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
1.225 brouard 13890: }
1.342 brouard 13891: /* printf("Decodemodel, k=%d, Tvar[%d]=V%d,Typevar=%d, Fixed=%d, Dummy=%d\n",k, k,Tvar[k],Typevar[k],Fixed[k],Dummy[k]); */
13892: /* printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype); */
1.227 brouard 13893: fprintf(ficlog,"Decodemodel, k=%d, Tvar[%d]=V%d,Typevar=%d, Fixed=%d, Dummy=%d\n",k, k,Tvar[k],Typevar[k],Fixed[k],Dummy[k]);
13894: }
1.349 brouard 13895: ncovvta=ncovva;
1.227 brouard 13896: /* Searching for doublons in the model */
13897: for(k1=1; k1<= cptcovt;k1++){
13898: for(k2=1; k2 <k1;k2++){
1.285 brouard 13899: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
13900: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 13901: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
13902: if(Tvar[k1]==Tvar[k2]){
1.338 brouard 13903: printf("Error duplication in the model=1+age+%s at positions (+) %d and %d, Tvar[%d]=V%d, Tvar[%d]=V%d, Typevar=%d, Fixed=%d, Dummy=%d\n", model, k1,k2, k1, Tvar[k1], k2, Tvar[k2],Typevar[k1],Fixed[k1],Dummy[k1]);
13904: fprintf(ficlog,"Error duplication in the model=1+age+%s at positions (+) %d and %d, Tvar[%d]=V%d, Tvar[%d]=V%d, Typevar=%d, Fixed=%d, Dummy=%d\n", model, k1,k2, k1, Tvar[k1], k2, Tvar[k2],Typevar[k1],Fixed[k1],Dummy[k1]); fflush(ficlog);
1.234 brouard 13905: return(1);
13906: }
13907: }else if (Typevar[k1] ==2){
13908: k3=Tposprod[k1];
13909: k4=Tposprod[k2];
13910: if( ((Tvard[k3][1]== Tvard[k4][1])&&(Tvard[k3][2]== Tvard[k4][2])) || ((Tvard[k3][1]== Tvard[k4][2])&&(Tvard[k3][2]== Tvard[k4][1])) ){
1.338 brouard 13911: printf("Error duplication in the model=1+age+%s at positions (+) %d and %d, V%d*V%d, Typevar=%d, Fixed=%d, Dummy=%d\n",model, k1,k2, Tvard[k3][1], Tvard[k3][2],Typevar[k1],Fixed[Tvar[k1]],Dummy[Tvar[k1]]);
13912: fprintf(ficlog,"Error duplication in the model=1+age+%s at positions (+) %d and %d, V%d*V%d, Typevar=%d, Fixed=%d, Dummy=%d\n",model, k1,k2, Tvard[k3][1], Tvard[k3][2],Typevar[k1],Fixed[Tvar[k1]],Dummy[Tvar[k1]]); fflush(ficlog);
1.234 brouard 13913: return(1);
13914: }
13915: }
1.227 brouard 13916: }
13917: }
1.225 brouard 13918: }
13919: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
13920: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 13921: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
13922: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.349 brouard 13923:
13924: free_imatrix(existcomb,1,NCOVMAX,1,NCOVMAX);
1.137 brouard 13925: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 13926: /*endread:*/
1.225 brouard 13927: printf("Exiting decodemodel: ");
13928: return (1);
1.136 brouard 13929: }
13930:
1.169 brouard 13931: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 13932: {/* Check ages at death */
1.136 brouard 13933: int i, m;
1.218 brouard 13934: int firstone=0;
13935:
1.136 brouard 13936: for (i=1; i<=imx; i++) {
13937: for(m=2; (m<= maxwav); m++) {
13938: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
13939: anint[m][i]=9999;
1.216 brouard 13940: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
13941: s[m][i]=-1;
1.136 brouard 13942: }
13943: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 13944: *nberr = *nberr + 1;
1.218 brouard 13945: if(firstone == 0){
13946: firstone=1;
1.260 brouard 13947: printf("Warning (#%d)! Date of death (month %2d and year %4d) of individual %ld on line %d was unknown but status is a death state %d at wave %d. If you don't know the vital status, please enter -2. If he/she is still alive but don't know the state, please code with '-1 or '.'. Here, we do not believe in a death, skipped.\nOther similar cases in log file\n", *nberr,(int)moisdc[i],(int)andc[i],num[i],i,s[m][i],m);
1.218 brouard 13948: }
1.262 brouard 13949: fprintf(ficlog,"Warning (#%d)! Date of death (month %2d and year %4d) of individual %ld on line %d was unknown but status is a death state %d at wave %d. If you don't know the vital status, please enter -2. If he/she is still alive but don't know the state, please code with '-1 or '.'. Here, we do not believe in a death, skipped.\n", *nberr,(int)moisdc[i],(int)andc[i],num[i],i,s[m][i],m);
1.260 brouard 13950: s[m][i]=-1; /* Droping the death status */
1.136 brouard 13951: }
13952: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 13953: (*nberr)++;
1.259 brouard 13954: printf("Error (#%d)! Month of death of individual %ld on line %d was unknown (%2d) (year of death is %4d) and status is a death state %d at wave %d. Please impute an arbitrary (or not) month and rerun. Currently this transition to death will be skipped (status is set to -2).\nOther similar cases in log file\n", *nberr, num[i],i,(int)moisdc[i],(int)andc[i],s[m][i],m);
1.262 brouard 13955: fprintf(ficlog,"Error (#%d)! Month of death of individual %ld on line %d was unknown (%2d) (year of death is %4d) and status is a death state %d at wave %d. Please impute an arbitrary (or not) month and rerun. Currently this transition to death will be skipped (status is set to -2).\n", *nberr, num[i],i,(int)moisdc[i],(int)andc[i],s[m][i],m);
1.259 brouard 13956: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 13957: }
13958: }
13959: }
13960:
13961: for (i=1; i<=imx; i++) {
13962: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
13963: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 13964: if(s[m][i] >0 || s[m][i]==-1 || s[m][i]==-2 || s[m][i]==-4 || s[m][i]==-5){ /* What if s[m][i]=-1 */
1.136 brouard 13965: if (s[m][i] >= nlstate+1) {
1.169 brouard 13966: if(agedc[i]>0){
13967: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 13968: agev[m][i]=agedc[i];
1.214 brouard 13969: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 13970: }else {
1.136 brouard 13971: if ((int)andc[i]!=9999){
13972: nbwarn++;
13973: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
13974: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
13975: agev[m][i]=-1;
13976: }
13977: }
1.169 brouard 13978: } /* agedc > 0 */
1.214 brouard 13979: } /* end if */
1.136 brouard 13980: else if(s[m][i] !=9){ /* Standard case, age in fractional
13981: years but with the precision of a month */
13982: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
13983: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
13984: agev[m][i]=1;
13985: else if(agev[m][i] < *agemin){
13986: *agemin=agev[m][i];
13987: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
13988: }
13989: else if(agev[m][i] >*agemax){
13990: *agemax=agev[m][i];
1.156 brouard 13991: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 13992: }
13993: /*agev[m][i]=anint[m][i]-annais[i];*/
13994: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 13995: } /* en if 9*/
1.136 brouard 13996: else { /* =9 */
1.214 brouard 13997: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 13998: agev[m][i]=1;
13999: s[m][i]=-1;
14000: }
14001: }
1.214 brouard 14002: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 14003: agev[m][i]=1;
1.214 brouard 14004: else{
14005: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
14006: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
14007: agev[m][i]=0;
14008: }
14009: } /* End for lastpass */
14010: }
1.136 brouard 14011:
14012: for (i=1; i<=imx; i++) {
14013: for(m=firstpass; (m<=lastpass); m++){
14014: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 14015: (*nberr)++;
1.136 brouard 14016: printf("Error: on wave %d of individual %d status %d > (nlstate+ndeath)=(%d+%d)=%d\n",m,i,s[m][i],nlstate, ndeath, nlstate+ndeath);
14017: fprintf(ficlog,"Error: on wave %d of individual %d status %d > (nlstate+ndeath)=(%d+%d)=%d\n",m,i,s[m][i],nlstate, ndeath, nlstate+ndeath);
14018: return 1;
14019: }
14020: }
14021: }
14022:
14023: /*for (i=1; i<=imx; i++){
14024: for (m=firstpass; (m<lastpass); m++){
14025: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
14026: }
14027:
14028: }*/
14029:
14030:
1.139 brouard 14031: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
14032: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 14033:
14034: return (0);
1.164 brouard 14035: /* endread:*/
1.136 brouard 14036: printf("Exiting calandcheckages: ");
14037: return (1);
14038: }
14039:
1.172 brouard 14040: #if defined(_MSC_VER)
14041: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
14042: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
14043: //#include "stdafx.h"
14044: //#include <stdio.h>
14045: //#include <tchar.h>
14046: //#include <windows.h>
14047: //#include <iostream>
14048: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
14049:
14050: LPFN_ISWOW64PROCESS fnIsWow64Process;
14051:
14052: BOOL IsWow64()
14053: {
14054: BOOL bIsWow64 = FALSE;
14055:
14056: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
14057: // (HANDLE, PBOOL);
14058:
14059: //LPFN_ISWOW64PROCESS fnIsWow64Process;
14060:
14061: HMODULE module = GetModuleHandle(_T("kernel32"));
14062: const char funcName[] = "IsWow64Process";
14063: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
14064: GetProcAddress(module, funcName);
14065:
14066: if (NULL != fnIsWow64Process)
14067: {
14068: if (!fnIsWow64Process(GetCurrentProcess(),
14069: &bIsWow64))
14070: //throw std::exception("Unknown error");
14071: printf("Unknown error\n");
14072: }
14073: return bIsWow64 != FALSE;
14074: }
14075: #endif
1.177 brouard 14076:
1.191 brouard 14077: void syscompilerinfo(int logged)
1.292 brouard 14078: {
14079: #include <stdint.h>
14080:
14081: /* #include "syscompilerinfo.h"*/
1.185 brouard 14082: /* command line Intel compiler 32bit windows, XP compatible:*/
14083: /* /GS /W3 /Gy
14084: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
14085: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
14086: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 14087: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
14088: */
14089: /* 64 bits */
1.185 brouard 14090: /*
14091: /GS /W3 /Gy
14092: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
14093: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
14094: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
14095: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
14096: /* Optimization are useless and O3 is slower than O2 */
14097: /*
14098: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
14099: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
14100: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
14101: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
14102: */
1.186 brouard 14103: /* Link is */ /* /OUT:"visual studio
1.185 brouard 14104: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
14105: /PDB:"visual studio
14106: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
14107: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
14108: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
14109: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
14110: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
14111: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
14112: uiAccess='false'"
14113: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
14114: /NOLOGO /TLBID:1
14115: */
1.292 brouard 14116:
14117:
1.177 brouard 14118: #if defined __INTEL_COMPILER
1.178 brouard 14119: #if defined(__GNUC__)
14120: struct utsname sysInfo; /* For Intel on Linux and OS/X */
14121: #endif
1.177 brouard 14122: #elif defined(__GNUC__)
1.179 brouard 14123: #ifndef __APPLE__
1.174 brouard 14124: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 14125: #endif
1.177 brouard 14126: struct utsname sysInfo;
1.178 brouard 14127: int cross = CROSS;
14128: if (cross){
14129: printf("Cross-");
1.191 brouard 14130: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 14131: }
1.174 brouard 14132: #endif
14133:
1.191 brouard 14134: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 14135: #if defined(__clang__)
1.191 brouard 14136: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 14137: #endif
14138: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 14139: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 14140: #endif
14141: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 14142: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 14143: #endif
14144: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 14145: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 14146: #endif
14147: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 14148: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 14149: #endif
14150: #if defined(_MSC_VER)
1.191 brouard 14151: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 14152: #endif
14153: #if defined(__PGI)
1.191 brouard 14154: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 14155: #endif
14156: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 14157: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 14158: #endif
1.191 brouard 14159: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 14160:
1.167 brouard 14161: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
14162: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
14163: // Windows (x64 and x86)
1.191 brouard 14164: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 14165: #elif __unix__ // all unices, not all compilers
14166: // Unix
1.191 brouard 14167: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 14168: #elif __linux__
14169: // linux
1.191 brouard 14170: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 14171: #elif __APPLE__
1.174 brouard 14172: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 14173: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 14174: #endif
14175:
14176: /* __MINGW32__ */
14177: /* __CYGWIN__ */
14178: /* __MINGW64__ */
14179: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
14180: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
14181: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
14182: /* _WIN64 // Defined for applications for Win64. */
14183: /* _M_X64 // Defined for compilations that target x64 processors. */
14184: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 14185:
1.167 brouard 14186: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 14187: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 14188: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 14189: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 14190: #else
1.191 brouard 14191: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 14192: #endif
14193:
1.169 brouard 14194: #if defined(__GNUC__)
14195: # if defined(__GNUC_PATCHLEVEL__)
14196: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
14197: + __GNUC_MINOR__ * 100 \
14198: + __GNUC_PATCHLEVEL__)
14199: # else
14200: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
14201: + __GNUC_MINOR__ * 100)
14202: # endif
1.174 brouard 14203: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 14204: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 14205:
14206: if (uname(&sysInfo) != -1) {
14207: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 14208: if(logged) fprintf(ficlog,"Running on: %s %s %s %s %s\n ",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.176 brouard 14209: }
14210: else
14211: perror("uname() error");
1.179 brouard 14212: //#ifndef __INTEL_COMPILER
14213: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 14214: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 14215: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 14216: #endif
1.169 brouard 14217: #endif
1.172 brouard 14218:
1.286 brouard 14219: // void main ()
1.172 brouard 14220: // {
1.169 brouard 14221: #if defined(_MSC_VER)
1.174 brouard 14222: if (IsWow64()){
1.191 brouard 14223: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
14224: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 14225: }
14226: else{
1.191 brouard 14227: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
14228: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 14229: }
1.172 brouard 14230: // printf("\nPress Enter to continue...");
14231: // getchar();
14232: // }
14233:
1.169 brouard 14234: #endif
14235:
1.167 brouard 14236:
1.219 brouard 14237: }
1.136 brouard 14238:
1.219 brouard 14239: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 14240: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.332 brouard 14241: /* Computes the prevalence limit for each combination of the dummy covariates */
1.235 brouard 14242: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 14243: /* double ftolpl = 1.e-10; */
1.180 brouard 14244: double age, agebase, agelim;
1.203 brouard 14245: double tot;
1.180 brouard 14246:
1.202 brouard 14247: strcpy(filerespl,"PL_");
14248: strcat(filerespl,fileresu);
14249: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 14250: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
14251: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 14252: }
1.288 brouard 14253: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
14254: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 14255: pstamp(ficrespl);
1.288 brouard 14256: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 14257: fprintf(ficrespl,"#Age ");
14258: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
14259: fprintf(ficrespl,"\n");
1.180 brouard 14260:
1.219 brouard 14261: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 14262:
1.219 brouard 14263: agebase=ageminpar;
14264: agelim=agemaxpar;
1.180 brouard 14265:
1.227 brouard 14266: /* i1=pow(2,ncoveff); */
1.234 brouard 14267: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 14268: if (cptcovn < 1){i1=1;}
1.180 brouard 14269:
1.337 brouard 14270: /* for(k=1; k<=i1;k++){ /\* For each combination k of dummy covariates in the model *\/ */
1.238 brouard 14271: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 14272: k=TKresult[nres];
1.338 brouard 14273: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 14274: /* if(i1 != 1 && TKresult[nres]!= k) /\* We found the combination k corresponding to the resultline value of dummies *\/ */
14275: /* continue; */
1.235 brouard 14276:
1.238 brouard 14277: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
14278: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
14279: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
14280: /* k=k+1; */
14281: /* to clean */
1.332 brouard 14282: /*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*/
1.238 brouard 14283: fprintf(ficrespl,"#******");
14284: printf("#******");
14285: fprintf(ficlog,"#******");
1.337 brouard 14286: for(j=1;j<=cptcovs ;j++) {/**< cptcovs number of SIMPLE covariates in the model or resultline V2+V1 =2 (dummy or quantit or time varying) */
1.332 brouard 14287: /* fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Here problem for varying dummy*\/ */
1.337 brouard 14288: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14289: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14290: fprintf(ficrespl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
14291: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
14292: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
14293: }
14294: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
14295: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
14296: /* fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
14297: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
14298: /* } */
1.238 brouard 14299: fprintf(ficrespl,"******\n");
14300: printf("******\n");
14301: fprintf(ficlog,"******\n");
14302: if(invalidvarcomb[k]){
14303: printf("\nCombination (%d) ignored because no case \n",k);
14304: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
14305: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
14306: continue;
14307: }
1.219 brouard 14308:
1.238 brouard 14309: fprintf(ficrespl,"#Age ");
1.337 brouard 14310: /* for(j=1;j<=cptcoveff;j++) { */
14311: /* fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14312: /* } */
14313: for(j=1;j<=cptcovs;j++) { /* New the quanti variable is added */
14314: fprintf(ficrespl,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 14315: }
14316: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
14317: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 14318:
1.238 brouard 14319: for (age=agebase; age<=agelim; age++){
14320: /* for (age=agebase; age<=agebase; age++){ */
1.337 brouard 14321: /**< Computes the prevalence limit in each live state at age x and for covariate combination (k and) nres */
14322: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres); /* Nicely done */
1.238 brouard 14323: fprintf(ficrespl,"%.0f ",age );
1.337 brouard 14324: /* for(j=1;j<=cptcoveff;j++) */
14325: /* fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14326: for(j=1;j<=cptcovs;j++)
14327: fprintf(ficrespl,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 14328: tot=0.;
14329: for(i=1; i<=nlstate;i++){
14330: tot += prlim[i][i];
14331: fprintf(ficrespl," %.5f", prlim[i][i]);
14332: }
14333: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
14334: } /* Age */
14335: /* was end of cptcod */
1.337 brouard 14336: } /* nres */
14337: /* } /\* for each combination *\/ */
1.219 brouard 14338: return 0;
1.180 brouard 14339: }
14340:
1.218 brouard 14341: int back_prevalence_limit(double *p, double **bprlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp, double dateprev1,double dateprev2, int firstpass, int lastpass, int mobilavproj){
1.288 brouard 14342: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 14343:
14344: /* Computes the back prevalence limit for any combination of covariate values
14345: * at any age between ageminpar and agemaxpar
14346: */
1.235 brouard 14347: int i, j, k, i1, nres=0 ;
1.217 brouard 14348: /* double ftolpl = 1.e-10; */
14349: double age, agebase, agelim;
14350: double tot;
1.218 brouard 14351: /* double ***mobaverage; */
14352: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 14353:
14354: strcpy(fileresplb,"PLB_");
14355: strcat(fileresplb,fileresu);
14356: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 14357: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
14358: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 14359: }
1.288 brouard 14360: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
14361: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 14362: pstamp(ficresplb);
1.288 brouard 14363: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 14364: fprintf(ficresplb,"#Age ");
14365: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
14366: fprintf(ficresplb,"\n");
14367:
1.218 brouard 14368:
14369: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
14370:
14371: agebase=ageminpar;
14372: agelim=agemaxpar;
14373:
14374:
1.227 brouard 14375: i1=pow(2,cptcoveff);
1.218 brouard 14376: if (cptcovn < 1){i1=1;}
1.227 brouard 14377:
1.238 brouard 14378: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.338 brouard 14379: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
14380: k=TKresult[nres];
14381: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
14382: /* if(i1 != 1 && TKresult[nres]!= k) */
14383: /* continue; */
14384: /* /\*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*\/ */
1.238 brouard 14385: fprintf(ficresplb,"#******");
14386: printf("#******");
14387: fprintf(ficlog,"#******");
1.338 brouard 14388: for(j=1;j<=cptcovs ;j++) {/**< cptcovs number of SIMPLE covariates in the model or resultline V2+V1 =2 (dummy or quantit or time varying) */
14389: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
14390: fprintf(ficresplb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
14391: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 14392: }
1.338 brouard 14393: /* for(j=1;j<=cptcoveff ;j++) {/\* all covariates *\/ */
14394: /* fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14395: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14396: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14397: /* } */
14398: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
14399: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
14400: /* fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
14401: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
14402: /* } */
1.238 brouard 14403: fprintf(ficresplb,"******\n");
14404: printf("******\n");
14405: fprintf(ficlog,"******\n");
14406: if(invalidvarcomb[k]){
14407: printf("\nCombination (%d) ignored because no cases \n",k);
14408: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
14409: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
14410: continue;
14411: }
1.218 brouard 14412:
1.238 brouard 14413: fprintf(ficresplb,"#Age ");
1.338 brouard 14414: for(j=1;j<=cptcovs;j++) {
14415: fprintf(ficresplb,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 14416: }
14417: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
14418: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 14419:
14420:
1.238 brouard 14421: for (age=agebase; age<=agelim; age++){
14422: /* for (age=agebase; age<=agebase; age++){ */
14423: if(mobilavproj > 0){
14424: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
14425: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 14426: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 14427: }else if (mobilavproj == 0){
14428: printf("There is no chance to get back prevalence limit if data aren't non zero and summing to 1, please try a non null mobil_average(=%d) parameter or mobil_average=-1 if you want to try at your own risk.\n",mobilavproj);
14429: fprintf(ficlog,"There is no chance to get back prevalence limit if data aren't non zero and summing to 1, please try a non null mobil_average(=%d) parameter or mobil_average=-1 if you want to try at your own risk.\n",mobilavproj);
14430: exit(1);
14431: }else{
14432: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 14433: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 14434: /* printf("TOTOT\n"); */
14435: /* exit(1); */
1.238 brouard 14436: }
14437: fprintf(ficresplb,"%.0f ",age );
1.338 brouard 14438: for(j=1;j<=cptcovs;j++)
14439: fprintf(ficresplb,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 14440: tot=0.;
14441: for(i=1; i<=nlstate;i++){
14442: tot += bprlim[i][i];
14443: fprintf(ficresplb," %.5f", bprlim[i][i]);
14444: }
14445: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
14446: } /* Age */
14447: /* was end of cptcod */
1.255 brouard 14448: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.338 brouard 14449: /* } /\* end of any combination *\/ */
1.238 brouard 14450: } /* end of nres */
1.218 brouard 14451: /* hBijx(p, bage, fage); */
14452: /* fclose(ficrespijb); */
14453:
14454: return 0;
1.217 brouard 14455: }
1.218 brouard 14456:
1.180 brouard 14457: int hPijx(double *p, int bage, int fage){
14458: /*------------- h Pij x at various ages ------------*/
1.336 brouard 14459: /* to be optimized with precov */
1.180 brouard 14460: int stepsize;
14461: int agelim;
14462: int hstepm;
14463: int nhstepm;
1.359 brouard 14464: int h, i, i1, j, k, nres=0;
1.180 brouard 14465:
14466: double agedeb;
14467: double ***p3mat;
14468:
1.337 brouard 14469: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
14470: if((ficrespij=fopen(filerespij,"w"))==NULL) {
14471: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
14472: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
14473: }
14474: printf("Computing pij: result on file '%s' \n", filerespij);
14475: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
14476:
14477: stepsize=(int) (stepm+YEARM-1)/YEARM;
14478: /*if (stepm<=24) stepsize=2;*/
14479:
14480: agelim=AGESUP;
14481: hstepm=stepsize*YEARM; /* Every year of age */
14482: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
14483:
14484: /* hstepm=1; aff par mois*/
14485: pstamp(ficrespij);
14486: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
14487: i1= pow(2,cptcoveff);
14488: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
14489: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
14490: /* k=k+1; */
14491: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
14492: k=TKresult[nres];
1.338 brouard 14493: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 14494: /* for(k=1; k<=i1;k++){ */
14495: /* if(i1 != 1 && TKresult[nres]!= k) */
14496: /* continue; */
14497: fprintf(ficrespij,"\n#****** ");
14498: for(j=1;j<=cptcovs;j++){
14499: fprintf(ficrespij," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
14500: /* fprintf(ficrespij,"@wV%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14501: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
14502: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
14503: /* fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
14504: }
14505: fprintf(ficrespij,"******\n");
14506:
14507: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
14508: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
14509: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
14510:
14511: /* nhstepm=nhstepm*YEARM; aff par mois*/
14512:
14513: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
14514: oldm=oldms;savm=savms;
14515: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
14516: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
14517: for(i=1; i<=nlstate;i++)
14518: for(j=1; j<=nlstate+ndeath;j++)
14519: fprintf(ficrespij," %1d-%1d",i,j);
14520: fprintf(ficrespij,"\n");
14521: for (h=0; h<=nhstepm; h++){
14522: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
14523: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.183 brouard 14524: for(i=1; i<=nlstate;i++)
14525: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 14526: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.183 brouard 14527: fprintf(ficrespij,"\n");
14528: }
1.337 brouard 14529: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
14530: fprintf(ficrespij,"\n");
1.180 brouard 14531: }
1.337 brouard 14532: }
14533: /*}*/
14534: return 0;
1.180 brouard 14535: }
1.218 brouard 14536:
14537: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 14538: /*------------- h Bij x at various ages ------------*/
1.336 brouard 14539: /* To be optimized with precov */
1.217 brouard 14540: int stepsize;
1.218 brouard 14541: /* int agelim; */
14542: int ageminl;
1.217 brouard 14543: int hstepm;
14544: int nhstepm;
1.238 brouard 14545: int h, i, i1, j, k, nres;
1.218 brouard 14546:
1.217 brouard 14547: double agedeb;
14548: double ***p3mat;
1.218 brouard 14549:
14550: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
14551: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
14552: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
14553: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
14554: }
14555: printf("Computing pij back: result on file '%s' \n", filerespijb);
14556: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
14557:
14558: stepsize=(int) (stepm+YEARM-1)/YEARM;
14559: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 14560:
1.218 brouard 14561: /* agelim=AGESUP; */
1.289 brouard 14562: ageminl=AGEINF; /* was 30 */
1.218 brouard 14563: hstepm=stepsize*YEARM; /* Every year of age */
14564: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
14565:
14566: /* hstepm=1; aff par mois*/
14567: pstamp(ficrespijb);
1.255 brouard 14568: fprintf(ficrespijb,"#****** h Bij x Back probability to be in state i at age x-h being in j at x: B1j+B2j+...=1 ");
1.227 brouard 14569: i1= pow(2,cptcoveff);
1.218 brouard 14570: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
14571: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
14572: /* k=k+1; */
1.238 brouard 14573: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 14574: k=TKresult[nres];
1.338 brouard 14575: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 14576: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
14577: /* if(i1 != 1 && TKresult[nres]!= k) */
14578: /* continue; */
14579: fprintf(ficrespijb,"\n#****** ");
14580: for(j=1;j<=cptcovs;j++){
1.338 brouard 14581: fprintf(ficrespijb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.337 brouard 14582: /* for(j=1;j<=cptcoveff;j++) */
14583: /* fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14584: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
14585: /* fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
14586: }
14587: fprintf(ficrespijb,"******\n");
14588: if(invalidvarcomb[k]){ /* Is it necessary here? */
14589: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
14590: continue;
14591: }
14592:
14593: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
14594: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
14595: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
14596: nhstepm=(int) rint((agedeb-ageminl)*YEARM/stepm+0.1)-1; /* Typically 20 years = 20*12/6=40 or 55*12/24=27.5-1.1=>27 */
14597: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 or 28*/
14598:
14599: /* nhstepm=nhstepm*YEARM; aff par mois*/
14600:
14601: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
14602: /* and memory limitations if stepm is small */
14603:
14604: /* oldm=oldms;savm=savms; */
14605: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
14606: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);/* Bug valgrind */
14607: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
14608: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
14609: for(i=1; i<=nlstate;i++)
14610: for(j=1; j<=nlstate+ndeath;j++)
14611: fprintf(ficrespijb," %1d-%1d",i,j);
14612: fprintf(ficrespijb,"\n");
14613: for (h=0; h<=nhstepm; h++){
14614: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
14615: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
14616: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
1.217 brouard 14617: for(i=1; i<=nlstate;i++)
14618: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 14619: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);/* Bug valgrind */
1.217 brouard 14620: fprintf(ficrespijb,"\n");
1.337 brouard 14621: }
14622: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
14623: fprintf(ficrespijb,"\n");
14624: } /* end age deb */
14625: /* } /\* end combination *\/ */
1.238 brouard 14626: } /* end nres */
1.218 brouard 14627: return 0;
14628: } /* hBijx */
1.217 brouard 14629:
1.180 brouard 14630:
1.136 brouard 14631: /***********************************************/
14632: /**************** Main Program *****************/
14633: /***********************************************/
14634:
14635: int main(int argc, char *argv[])
14636: {
14637: #ifdef GSL
14638: const gsl_multimin_fminimizer_type *T;
14639: size_t iteri = 0, it;
14640: int rval = GSL_CONTINUE;
14641: int status = GSL_SUCCESS;
14642: double ssval;
14643: #endif
14644: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 14645: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
14646: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 14647: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 14648: int jj, ll, li, lj, lk;
1.136 brouard 14649: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 14650: int num_filled;
1.136 brouard 14651: int itimes;
14652: int NDIM=2;
14653: int vpopbased=0;
1.235 brouard 14654: int nres=0;
1.258 brouard 14655: int endishere=0;
1.277 brouard 14656: int noffset=0;
1.274 brouard 14657: int ncurrv=0; /* Temporary variable */
14658:
1.164 brouard 14659: char ca[32], cb[32];
1.136 brouard 14660: /* FILE *fichtm; *//* Html File */
14661: /* FILE *ficgp;*/ /*Gnuplot File */
14662: struct stat info;
1.191 brouard 14663: double agedeb=0.;
1.194 brouard 14664:
14665: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 14666: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 14667:
1.361 brouard 14668: double stdpercent; /* for computing the std error of percent e.i: e.i/e.. */
1.165 brouard 14669: double fret;
1.191 brouard 14670: double dum=0.; /* Dummy variable */
1.359 brouard 14671: /* double*** p3mat;*/
1.218 brouard 14672: /* double ***mobaverage; */
1.319 brouard 14673: double wald;
1.164 brouard 14674:
1.351 brouard 14675: char line[MAXLINE], linetmp[MAXLINE];
1.197 brouard 14676: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
14677:
1.234 brouard 14678: char modeltemp[MAXLINE];
1.332 brouard 14679: char resultline[MAXLINE], resultlineori[MAXLINE];
1.230 brouard 14680:
1.136 brouard 14681: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 14682: char *tok, *val; /* pathtot */
1.334 brouard 14683: /* int firstobs=1, lastobs=10; /\* nobs = lastobs-firstobs declared globally ;*\/ */
1.359 brouard 14684: int c, h; /* c2; */
1.191 brouard 14685: int jl=0;
14686: int i1, j1, jk, stepsize=0;
1.194 brouard 14687: int count=0;
14688:
1.164 brouard 14689: int *tab;
1.136 brouard 14690: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.296 brouard 14691: /* double anprojd, mprojd, jprojd; /\* For eventual projections *\/ */
14692: /* double anprojf, mprojf, jprojf; */
14693: /* double jintmean,mintmean,aintmean; */
14694: int prvforecast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
14695: int prvbackcast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
14696: double yrfproj= 10.0; /* Number of years of forward projections */
14697: double yrbproj= 10.0; /* Number of years of backward projections */
14698: int prevbcast=0; /* defined as global for mlikeli and mle, replacing backcast */
1.136 brouard 14699: int mobilav=0,popforecast=0;
1.191 brouard 14700: int hstepm=0, nhstepm=0;
1.136 brouard 14701: int agemortsup;
14702: float sumlpop=0.;
14703: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
14704: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
14705:
1.191 brouard 14706: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 14707: double ftolpl=FTOL;
14708: double **prlim;
1.217 brouard 14709: double **bprlim;
1.317 brouard 14710: double ***param; /* Matrix of parameters, param[i][j][k] param=ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel)
14711: state of origin, state of destination including death, for each covariate: constante, age, and V1 V2 etc. */
1.251 brouard 14712: double ***paramstart; /* Matrix of starting parameter values */
14713: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 14714: double **matcov; /* Matrix of covariance */
1.203 brouard 14715: double **hess; /* Hessian matrix */
1.136 brouard 14716: double ***delti3; /* Scale */
14717: double *delti; /* Scale */
14718: double ***eij, ***vareij;
1.359 brouard 14719: //double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 14720:
1.136 brouard 14721: double *epj, vepp;
1.164 brouard 14722:
1.273 brouard 14723: double dateprev1, dateprev2;
1.296 brouard 14724: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0, dateprojd=0, dateprojf=0;
14725: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0, datebackd=0, datebackf=0;
14726:
1.217 brouard 14727:
1.136 brouard 14728: double **ximort;
1.145 brouard 14729: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 14730: int *dcwave;
14731:
1.164 brouard 14732: char z[1]="c";
1.136 brouard 14733:
14734: /*char *strt;*/
14735: char strtend[80];
1.126 brouard 14736:
1.164 brouard 14737:
1.126 brouard 14738: /* setlocale (LC_ALL, ""); */
14739: /* bindtextdomain (PACKAGE, LOCALEDIR); */
14740: /* textdomain (PACKAGE); */
14741: /* setlocale (LC_CTYPE, ""); */
14742: /* setlocale (LC_MESSAGES, ""); */
14743:
14744: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 14745: rstart_time = time(NULL);
14746: /* (void) gettimeofday(&start_time,&tzp);*/
14747: start_time = *localtime(&rstart_time);
1.126 brouard 14748: curr_time=start_time;
1.157 brouard 14749: /*tml = *localtime(&start_time.tm_sec);*/
14750: /* strcpy(strstart,asctime(&tml)); */
14751: strcpy(strstart,asctime(&start_time));
1.126 brouard 14752:
14753: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 14754: /* tp.tm_sec = tp.tm_sec +86400; */
14755: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 14756: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
14757: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
14758: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 14759: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 14760: /* strt=asctime(&tmg); */
14761: /* printf("Time(after) =%s",strstart); */
14762: /* (void) time (&time_value);
14763: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
14764: * tm = *localtime(&time_value);
14765: * strstart=asctime(&tm);
14766: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
14767: */
14768:
14769: nberr=0; /* Number of errors and warnings */
14770: nbwarn=0;
1.184 brouard 14771: #ifdef WIN32
14772: _getcwd(pathcd, size);
14773: #else
1.126 brouard 14774: getcwd(pathcd, size);
1.184 brouard 14775: #endif
1.191 brouard 14776: syscompilerinfo(0);
1.359 brouard 14777: printf("\nIMaCh prax version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 14778: if(argc <=1){
14779: printf("\nEnter the parameter file name: ");
1.205 brouard 14780: if(!fgets(pathr,FILENAMELENGTH,stdin)){
14781: printf("ERROR Empty parameter file name\n");
14782: goto end;
14783: }
1.126 brouard 14784: i=strlen(pathr);
14785: if(pathr[i-1]=='\n')
14786: pathr[i-1]='\0';
1.156 brouard 14787: i=strlen(pathr);
1.205 brouard 14788: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 14789: pathr[i-1]='\0';
1.205 brouard 14790: }
14791: i=strlen(pathr);
14792: if( i==0 ){
14793: printf("ERROR Empty parameter file name\n");
14794: goto end;
14795: }
14796: for (tok = pathr; tok != NULL; ){
1.126 brouard 14797: printf("Pathr |%s|\n",pathr);
14798: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
14799: printf("val= |%s| pathr=%s\n",val,pathr);
14800: strcpy (pathtot, val);
14801: if(pathr[0] == '\0') break; /* Dirty */
14802: }
14803: }
1.281 brouard 14804: else if (argc<=2){
14805: strcpy(pathtot,argv[1]);
14806: }
1.126 brouard 14807: else{
14808: strcpy(pathtot,argv[1]);
1.281 brouard 14809: strcpy(z,argv[2]);
14810: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 14811: }
14812: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
14813: /*cygwin_split_path(pathtot,path,optionfile);
14814: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
14815: /* cutv(path,optionfile,pathtot,'\\');*/
14816:
14817: /* Split argv[0], imach program to get pathimach */
14818: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
14819: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
14820: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
14821: /* strcpy(pathimach,argv[0]); */
14822: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
14823: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
14824: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 14825: #ifdef WIN32
14826: _chdir(path); /* Can be a relative path */
14827: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
14828: #else
1.126 brouard 14829: chdir(path); /* Can be a relative path */
1.184 brouard 14830: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
14831: #endif
14832: printf("Current directory %s!\n",pathcd);
1.126 brouard 14833: strcpy(command,"mkdir ");
14834: strcat(command,optionfilefiname);
14835: if((outcmd=system(command)) != 0){
1.169 brouard 14836: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 14837: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
14838: /* fclose(ficlog); */
14839: /* exit(1); */
14840: }
14841: /* if((imk=mkdir(optionfilefiname))<0){ */
14842: /* perror("mkdir"); */
14843: /* } */
14844:
14845: /*-------- arguments in the command line --------*/
14846:
1.186 brouard 14847: /* Main Log file */
1.126 brouard 14848: strcat(filelog, optionfilefiname);
14849: strcat(filelog,".log"); /* */
14850: if((ficlog=fopen(filelog,"w"))==NULL) {
14851: printf("Problem with logfile %s\n",filelog);
14852: goto end;
14853: }
14854: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 14855: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 14856: fprintf(ficlog,"\nEnter the parameter file name: \n");
14857: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
14858: path=%s \n\
14859: optionfile=%s\n\
14860: optionfilext=%s\n\
1.156 brouard 14861: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 14862:
1.197 brouard 14863: syscompilerinfo(1);
1.167 brouard 14864:
1.126 brouard 14865: printf("Local time (at start):%s",strstart);
14866: fprintf(ficlog,"Local time (at start): %s",strstart);
14867: fflush(ficlog);
14868: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 14869: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 14870:
14871: /* */
14872: strcpy(fileres,"r");
14873: strcat(fileres, optionfilefiname);
1.201 brouard 14874: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 14875: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 14876: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 14877:
1.186 brouard 14878: /* Main ---------arguments file --------*/
1.126 brouard 14879:
14880: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 14881: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
14882: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 14883: fflush(ficlog);
1.149 brouard 14884: /* goto end; */
14885: exit(70);
1.126 brouard 14886: }
14887:
14888: strcpy(filereso,"o");
1.201 brouard 14889: strcat(filereso,fileresu);
1.126 brouard 14890: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
14891: printf("Problem with Output resultfile: %s\n", filereso);
14892: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
14893: fflush(ficlog);
14894: goto end;
14895: }
1.278 brouard 14896: /*-------- Rewriting parameter file ----------*/
14897: strcpy(rfileres,"r"); /* "Rparameterfile */
14898: strcat(rfileres,optionfilefiname); /* Parameter file first name */
14899: strcat(rfileres,"."); /* */
14900: strcat(rfileres,optionfilext); /* Other files have txt extension */
14901: if((ficres =fopen(rfileres,"w"))==NULL) {
14902: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
14903: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
14904: fflush(ficlog);
14905: goto end;
14906: }
14907: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 14908:
1.278 brouard 14909:
1.126 brouard 14910: /* Reads comments: lines beginning with '#' */
14911: numlinepar=0;
1.277 brouard 14912: /* Is it a BOM UTF-8 Windows file? */
14913: /* First parameter line */
1.197 brouard 14914: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 14915: noffset=0;
14916: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
14917: {
14918: noffset=noffset+3;
14919: printf("# File is an UTF8 Bom.\n"); // 0xBF
14920: }
1.302 brouard 14921: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
14922: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
1.277 brouard 14923: {
14924: noffset=noffset+2;
14925: printf("# File is an UTF16BE BOM file\n");
14926: }
14927: else if( line[0] == 0 && line[1] == 0)
14928: {
14929: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
14930: noffset=noffset+4;
14931: printf("# File is an UTF16BE BOM file\n");
14932: }
14933: } else{
14934: ;/*printf(" Not a BOM file\n");*/
14935: }
14936:
1.197 brouard 14937: /* If line starts with a # it is a comment */
1.277 brouard 14938: if (line[noffset] == '#') {
1.197 brouard 14939: numlinepar++;
14940: fputs(line,stdout);
14941: fputs(line,ficparo);
1.278 brouard 14942: fputs(line,ficres);
1.197 brouard 14943: fputs(line,ficlog);
14944: continue;
14945: }else
14946: break;
14947: }
14948: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
14949: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
14950: if (num_filled != 5) {
14951: printf("Should be 5 parameters\n");
1.283 brouard 14952: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 14953: }
1.126 brouard 14954: numlinepar++;
1.197 brouard 14955: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 14956: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
14957: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
14958: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 14959: }
14960: /* Second parameter line */
14961: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 14962: /* while(fscanf(ficpar,"%[^\n]", line)) { */
14963: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 14964: if (line[0] == '#') {
14965: numlinepar++;
1.283 brouard 14966: printf("%s",line);
14967: fprintf(ficres,"%s",line);
14968: fprintf(ficparo,"%s",line);
14969: fprintf(ficlog,"%s",line);
1.197 brouard 14970: continue;
14971: }else
14972: break;
14973: }
1.223 brouard 14974: if((num_filled=sscanf(line,"ftol=%lf stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\n", \
14975: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
14976: if (num_filled != 11) {
14977: printf("Not 11 parameters, for example:ftol=1.e-8 stepm=12 ncovcol=2 nqv=1 ntv=2 nqtv=1 nlstate=2 ndeath=1 maxwav=3 mle=1 weight=1\n");
1.209 brouard 14978: printf("but line=%s\n",line);
1.283 brouard 14979: fprintf(ficlog,"Not 11 parameters, for example:ftol=1.e-8 stepm=12 ncovcol=2 nqv=1 ntv=2 nqtv=1 nlstate=2 ndeath=1 maxwav=3 mle=1 weight=1\n");
14980: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 14981: }
1.286 brouard 14982: if( lastpass > maxwav){
14983: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
14984: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
14985: fflush(ficlog);
14986: goto end;
14987: }
14988: printf("ftol=%e stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\n",ftol, stepm, ncovcol, nqv, ntv, nqtv, nlstate, ndeath, maxwav, mle, weightopt);
1.283 brouard 14989: fprintf(ficparo,"ftol=%e stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\n",ftol, stepm, ncovcol, nqv, ntv, nqtv, nlstate, ndeath, maxwav, mle, weightopt);
1.286 brouard 14990: fprintf(ficres,"ftol=%e stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\n",ftol, stepm, ncovcol, nqv, ntv, nqtv, nlstate, ndeath, maxwav, 0, weightopt);
1.283 brouard 14991: fprintf(ficlog,"ftol=%e stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\n",ftol, stepm, ncovcol, nqv, ntv, nqtv, nlstate, ndeath, maxwav, mle, weightopt);
1.126 brouard 14992: }
1.203 brouard 14993: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 14994: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 14995: /* Third parameter line */
14996: while(fgets(line, MAXLINE, ficpar)) {
14997: /* If line starts with a # it is a comment */
14998: if (line[0] == '#') {
14999: numlinepar++;
1.283 brouard 15000: printf("%s",line);
15001: fprintf(ficres,"%s",line);
15002: fprintf(ficparo,"%s",line);
15003: fprintf(ficlog,"%s",line);
1.197 brouard 15004: continue;
15005: }else
15006: break;
15007: }
1.351 brouard 15008: if((num_filled=sscanf(line,"model=%[^.\n]", model)) !=EOF){ /* Every character after model but dot and return */
15009: if (num_filled != 1){
15010: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
15011: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
15012: model[0]='\0';
15013: goto end;
15014: }else{
15015: trimbtab(linetmp,line); /* Trims multiple blanks in line */
15016: strcpy(line, linetmp);
15017: }
15018: }
15019: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){ /* Every character after 1+age but dot and return */
1.279 brouard 15020: if (num_filled != 1){
1.302 brouard 15021: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
15022: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
1.197 brouard 15023: model[0]='\0';
15024: goto end;
15025: }
15026: else{
15027: if (model[0]=='+'){
15028: for(i=1; i<=strlen(model);i++)
15029: modeltemp[i-1]=model[i];
1.201 brouard 15030: strcpy(model,modeltemp);
1.197 brouard 15031: }
15032: }
1.338 brouard 15033: /* printf(" model=1+age%s modeltemp= %s, model=1+age+%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 15034: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 15035: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
15036: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
15037: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 15038: }
15039: /* fscanf(ficpar,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\nftol=%lf stepm=%d ncovcol=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d model=1+age+%s\n",title, datafile, &lastobs, &firstpass,&lastpass,&ftol, &stepm, &ncovcol, &nlstate,&ndeath, &maxwav, &mle, &weightopt,model); */
15040: /* numlinepar=numlinepar+3; /\* In general *\/ */
15041: /* printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\nftol=%e stepm=%d ncovcol=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\nmodel=1+age+%s\n", title, datafile, lastobs, firstpass,lastpass,ftol, stepm, ncovcol, nlstate,ndeath, maxwav, mle, weightopt,model); */
1.283 brouard 15042: /* fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\nftol=%e stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\nmodel=1+age+%s.\n", title, datafile, lastobs, firstpass,lastpass,ftol,stepm,ncovcol, nqv, ntv, nqtv, nlstate,ndeath,maxwav, mle, weightopt,model); */
15043: /* fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\nftol=%e stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\nmodel=1+age+%s.\n", title, datafile, lastobs, firstpass,lastpass,ftol,stepm,ncovcol, nqv, ntv, nqtv, nlstate,ndeath,maxwav, mle, weightopt,model); */
1.126 brouard 15044: fflush(ficlog);
1.190 brouard 15045: /* if(model[0]=='#'|| model[0]== '\0'){ */
15046: if(model[0]=='#'){
1.279 brouard 15047: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
15048: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
15049: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 15050: if(mle != -1){
1.279 brouard 15051: printf("Fix the model line and run imach with mle=-1 to get a correct template of the parameter vectors and subdiagonal covariance matrix.\n");
1.187 brouard 15052: exit(1);
15053: }
15054: }
1.126 brouard 15055: while((c=getc(ficpar))=='#' && c!= EOF){
15056: ungetc(c,ficpar);
15057: fgets(line, MAXLINE, ficpar);
15058: numlinepar++;
1.195 brouard 15059: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
15060: z[0]=line[1];
1.342 brouard 15061: }else if(line[1]=='d'){ /* For debugging individual values of covariates in ficresilk */
1.343 brouard 15062: debugILK=1;printf("DebugILK\n");
1.195 brouard 15063: }
15064: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 15065: fputs(line, stdout);
15066: //puts(line);
1.126 brouard 15067: fputs(line,ficparo);
15068: fputs(line,ficlog);
15069: }
15070: ungetc(c,ficpar);
15071:
15072:
1.290 brouard 15073: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
15074: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
15075: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
1.341 brouard 15076: /* if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /\**< Time varying covariate (dummy and quantitative)*\/ */
15077: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs); /**< Might be better */
1.136 brouard 15078: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
15079: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
15080: v1+v2*age+v2*v3 makes cptcovn = 3
15081: */
15082: if (strlen(model)>1)
1.187 brouard 15083: ncovmodel=2+nbocc(model,'+')+1; /*Number of variables including intercept and age = cptcovn + intercept + age : v1+v2+v3+v2*v4+v5*age makes 5+2=7,age*age makes 3*/
1.145 brouard 15084: else
1.187 brouard 15085: ncovmodel=2; /* Constant and age */
1.133 brouard 15086: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
15087: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 15088: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
15089: printf("Too complex model for current IMaCh: npar=(nlstate+ndeath-1)*nlstate*ncovmodel=%d >= %d(MAXPARM) or nlstate=%d >= %d(NLSTATEMAX) or ndeath=%d >= %d(NDEATHMAX) or ncovmodel=(k+age+#of+signs)=%d(NCOVMAX) >= %d\n",npar, MAXPARM, nlstate, NLSTATEMAX, ndeath, NDEATHMAX, ncovmodel, NCOVMAX);
15090: fprintf(ficlog,"Too complex model for current IMaCh: %d >=%d(MAXPARM) or %d >=%d(NLSTATEMAX) or %d >=%d(NDEATHMAX) or %d(NCOVMAX) >=%d\n",npar, MAXPARM, nlstate, NLSTATEMAX, ndeath, NDEATHMAX, ncovmodel, NCOVMAX);
15091: fflush(stdout);
15092: fclose (ficlog);
15093: goto end;
15094: }
1.126 brouard 15095: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
15096: delti=delti3[1][1];
15097: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
15098: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 15099: /* We could also provide initial parameters values giving by simple logistic regression
15100: * only one way, that is without matrix product. We will have nlstate maximizations */
15101: /* for(i=1;i<nlstate;i++){ */
15102: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
15103: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
15104: /* } */
1.126 brouard 15105: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 15106: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
15107: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 15108: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
15109: fclose (ficparo);
15110: fclose (ficlog);
15111: goto end;
15112: exit(0);
1.220 brouard 15113: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 15114: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 15115: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
15116: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 15117: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
15118: matcov=matrix(1,npar,1,npar);
1.203 brouard 15119: hess=matrix(1,npar,1,npar);
1.220 brouard 15120: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 15121: /* Read guessed parameters */
1.126 brouard 15122: /* Reads comments: lines beginning with '#' */
15123: while((c=getc(ficpar))=='#' && c!= EOF){
15124: ungetc(c,ficpar);
15125: fgets(line, MAXLINE, ficpar);
15126: numlinepar++;
1.141 brouard 15127: fputs(line,stdout);
1.126 brouard 15128: fputs(line,ficparo);
15129: fputs(line,ficlog);
15130: }
15131: ungetc(c,ficpar);
15132:
15133: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 15134: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 15135: for(i=1; i <=nlstate; i++){
1.234 brouard 15136: j=0;
1.126 brouard 15137: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 15138: if(jj==i) continue;
15139: j++;
1.292 brouard 15140: while((c=getc(ficpar))=='#' && c!= EOF){
15141: ungetc(c,ficpar);
15142: fgets(line, MAXLINE, ficpar);
15143: numlinepar++;
15144: fputs(line,stdout);
15145: fputs(line,ficparo);
15146: fputs(line,ficlog);
15147: }
15148: ungetc(c,ficpar);
1.234 brouard 15149: fscanf(ficpar,"%1d%1d",&i1,&j1);
15150: if ((i1 != i) || (j1 != jj)){
15151: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 15152: It might be a problem of design; if ncovcol and the model are correct\n \
15153: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 15154: exit(1);
15155: }
15156: fprintf(ficparo,"%1d%1d",i1,j1);
15157: if(mle==1)
15158: printf("%1d%1d",i,jj);
15159: fprintf(ficlog,"%1d%1d",i,jj);
15160: for(k=1; k<=ncovmodel;k++){
15161: fscanf(ficpar," %lf",¶m[i][j][k]);
15162: if(mle==1){
15163: printf(" %lf",param[i][j][k]);
15164: fprintf(ficlog," %lf",param[i][j][k]);
15165: }
15166: else
15167: fprintf(ficlog," %lf",param[i][j][k]);
15168: fprintf(ficparo," %lf",param[i][j][k]);
15169: }
15170: fscanf(ficpar,"\n");
15171: numlinepar++;
15172: if(mle==1)
15173: printf("\n");
15174: fprintf(ficlog,"\n");
15175: fprintf(ficparo,"\n");
1.126 brouard 15176: }
15177: }
15178: fflush(ficlog);
1.234 brouard 15179:
1.251 brouard 15180: /* Reads parameters values */
1.126 brouard 15181: p=param[1][1];
1.251 brouard 15182: pstart=paramstart[1][1];
1.126 brouard 15183:
15184: /* Reads comments: lines beginning with '#' */
15185: while((c=getc(ficpar))=='#' && c!= EOF){
15186: ungetc(c,ficpar);
15187: fgets(line, MAXLINE, ficpar);
15188: numlinepar++;
1.141 brouard 15189: fputs(line,stdout);
1.126 brouard 15190: fputs(line,ficparo);
15191: fputs(line,ficlog);
15192: }
15193: ungetc(c,ficpar);
15194:
15195: for(i=1; i <=nlstate; i++){
15196: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 15197: fscanf(ficpar,"%1d%1d",&i1,&j1);
15198: if ( (i1-i) * (j1-j) != 0){
15199: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
15200: exit(1);
15201: }
15202: printf("%1d%1d",i,j);
15203: fprintf(ficparo,"%1d%1d",i1,j1);
15204: fprintf(ficlog,"%1d%1d",i1,j1);
15205: for(k=1; k<=ncovmodel;k++){
15206: fscanf(ficpar,"%le",&delti3[i][j][k]);
15207: printf(" %le",delti3[i][j][k]);
15208: fprintf(ficparo," %le",delti3[i][j][k]);
15209: fprintf(ficlog," %le",delti3[i][j][k]);
15210: }
15211: fscanf(ficpar,"\n");
15212: numlinepar++;
15213: printf("\n");
15214: fprintf(ficparo,"\n");
15215: fprintf(ficlog,"\n");
1.126 brouard 15216: }
15217: }
15218: fflush(ficlog);
1.234 brouard 15219:
1.145 brouard 15220: /* Reads covariance matrix */
1.126 brouard 15221: delti=delti3[1][1];
1.220 brouard 15222:
15223:
1.126 brouard 15224: /* free_ma3x(delti3,1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); */ /* Hasn't to to freed here otherwise delti is no more allocated */
1.220 brouard 15225:
1.126 brouard 15226: /* Reads comments: lines beginning with '#' */
15227: while((c=getc(ficpar))=='#' && c!= EOF){
15228: ungetc(c,ficpar);
15229: fgets(line, MAXLINE, ficpar);
15230: numlinepar++;
1.141 brouard 15231: fputs(line,stdout);
1.126 brouard 15232: fputs(line,ficparo);
15233: fputs(line,ficlog);
15234: }
15235: ungetc(c,ficpar);
1.220 brouard 15236:
1.126 brouard 15237: matcov=matrix(1,npar,1,npar);
1.203 brouard 15238: hess=matrix(1,npar,1,npar);
1.131 brouard 15239: for(i=1; i <=npar; i++)
15240: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 15241:
1.194 brouard 15242: /* Scans npar lines */
1.126 brouard 15243: for(i=1; i <=npar; i++){
1.226 brouard 15244: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 15245: if(count != 3){
1.226 brouard 15246: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 15247: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
15248: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 15249: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 15250: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
15251: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 15252: exit(1);
1.220 brouard 15253: }else{
1.226 brouard 15254: if(mle==1)
15255: printf("%1d%1d%d",i1,j1,jk);
15256: }
15257: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
15258: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 15259: for(j=1; j <=i; j++){
1.226 brouard 15260: fscanf(ficpar," %le",&matcov[i][j]);
15261: if(mle==1){
15262: printf(" %.5le",matcov[i][j]);
15263: }
15264: fprintf(ficlog," %.5le",matcov[i][j]);
15265: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 15266: }
15267: fscanf(ficpar,"\n");
15268: numlinepar++;
15269: if(mle==1)
1.220 brouard 15270: printf("\n");
1.126 brouard 15271: fprintf(ficlog,"\n");
15272: fprintf(ficparo,"\n");
15273: }
1.194 brouard 15274: /* End of read covariance matrix npar lines */
1.126 brouard 15275: for(i=1; i <=npar; i++)
15276: for(j=i+1;j<=npar;j++)
1.226 brouard 15277: matcov[i][j]=matcov[j][i];
1.126 brouard 15278:
15279: if(mle==1)
15280: printf("\n");
15281: fprintf(ficlog,"\n");
15282:
15283: fflush(ficlog);
15284:
15285: } /* End of mle != -3 */
1.218 brouard 15286:
1.186 brouard 15287: /* Main data
15288: */
1.290 brouard 15289: nobs=lastobs-firstobs+1; /* was = lastobs;*/
15290: /* num=lvector(1,n); */
15291: /* moisnais=vector(1,n); */
15292: /* annais=vector(1,n); */
15293: /* moisdc=vector(1,n); */
15294: /* andc=vector(1,n); */
15295: /* weight=vector(1,n); */
15296: /* agedc=vector(1,n); */
15297: /* cod=ivector(1,n); */
15298: /* for(i=1;i<=n;i++){ */
15299: num=lvector(firstobs,lastobs);
15300: moisnais=vector(firstobs,lastobs);
15301: annais=vector(firstobs,lastobs);
15302: moisdc=vector(firstobs,lastobs);
15303: andc=vector(firstobs,lastobs);
15304: weight=vector(firstobs,lastobs);
15305: agedc=vector(firstobs,lastobs);
15306: cod=ivector(firstobs,lastobs);
15307: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 15308: num[i]=0;
15309: moisnais[i]=0;
15310: annais[i]=0;
15311: moisdc[i]=0;
15312: andc[i]=0;
15313: agedc[i]=0;
15314: cod[i]=0;
15315: weight[i]=1.0; /* Equal weights, 1 by default */
15316: }
1.290 brouard 15317: mint=matrix(1,maxwav,firstobs,lastobs);
15318: anint=matrix(1,maxwav,firstobs,lastobs);
1.325 brouard 15319: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
1.336 brouard 15320: /* printf("BUG ncovmodel=%d NCOVMAX=%d 2**ncovmodel=%f BUG\n",ncovmodel,NCOVMAX,pow(2,ncovmodel)); */
1.126 brouard 15321: tab=ivector(1,NCOVMAX);
1.144 brouard 15322: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 15323: ncodemaxwundef=ivector(1,NCOVMAX); /* Number of code per covariate; if - 1 O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.126 brouard 15324:
1.136 brouard 15325: /* Reads data from file datafile */
15326: if (readdata(datafile, firstobs, lastobs, &imx)==1)
15327: goto end;
15328:
15329: /* Calculation of the number of parameters from char model */
1.234 brouard 15330: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 15331: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
15332: k=3 V4 Tvar[k=3]= 4 (from V4)
15333: k=2 V1 Tvar[k=2]= 1 (from V1)
15334: k=1 Tvar[1]=2 (from V2)
1.234 brouard 15335: */
15336:
15337: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
15338: TvarsDind=ivector(1,NCOVMAX); /* */
1.330 brouard 15339: TnsdVar=ivector(1,NCOVMAX); /* */
1.335 brouard 15340: /* for(i=1; i<=NCOVMAX;i++) TnsdVar[i]=3; */
1.234 brouard 15341: TvarsD=ivector(1,NCOVMAX); /* */
15342: TvarsQind=ivector(1,NCOVMAX); /* */
15343: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 15344: TvarF=ivector(1,NCOVMAX); /* */
15345: TvarFind=ivector(1,NCOVMAX); /* */
15346: TvarV=ivector(1,NCOVMAX); /* */
15347: TvarVind=ivector(1,NCOVMAX); /* */
15348: TvarA=ivector(1,NCOVMAX); /* */
15349: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 15350: TvarFD=ivector(1,NCOVMAX); /* */
15351: TvarFDind=ivector(1,NCOVMAX); /* */
15352: TvarFQ=ivector(1,NCOVMAX); /* */
15353: TvarFQind=ivector(1,NCOVMAX); /* */
15354: TvarVD=ivector(1,NCOVMAX); /* */
15355: TvarVDind=ivector(1,NCOVMAX); /* */
15356: TvarVQ=ivector(1,NCOVMAX); /* */
15357: TvarVQind=ivector(1,NCOVMAX); /* */
1.339 brouard 15358: TvarVV=ivector(1,NCOVMAX); /* */
15359: TvarVVind=ivector(1,NCOVMAX); /* */
1.349 brouard 15360: TvarVVA=ivector(1,NCOVMAX); /* */
15361: TvarVVAind=ivector(1,NCOVMAX); /* */
15362: TvarAVVA=ivector(1,NCOVMAX); /* */
15363: TvarAVVAind=ivector(1,NCOVMAX); /* */
1.231 brouard 15364:
1.230 brouard 15365: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 15366: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 15367: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
15368: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
15369: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.349 brouard 15370: DummyV=ivector(-1,NCOVMAX); /* 1 to 3 */
15371: FixedV=ivector(-1,NCOVMAX); /* 1 to 3 */
15372:
1.137 brouard 15373: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
15374: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
15375: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
15376: */
15377: /* For model-covariate k tells which data-covariate to use but
15378: because this model-covariate is a construction we invent a new column
15379: ncovcol + k1
15380: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
15381: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 15382: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
15383: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 15384: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
15385: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 15386: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 15387: */
1.145 brouard 15388: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
15389: Tvard=imatrix(1,NCOVMAX,1,2); /* n=Tvard[k1][1] and m=Tvard[k1][2] gives the couple n,m of the k1 th product Vn*Vm
1.141 brouard 15390: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
15391: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.351 brouard 15392: Tvardk=imatrix(0,NCOVMAX,1,2);
1.145 brouard 15393: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 15394: 4 covariates (3 plus signs)
15395: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
1.328 brouard 15396: */
15397: for(i=1;i<NCOVMAX;i++)
15398: Tage[i]=0;
1.230 brouard 15399: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 15400: * individual dummy, fixed or varying:
15401: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
15402: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 15403: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
15404: * V1 df, V2 qf, V3 & V4 dv, V5 qv
15405: * Tmodelind[1]@9={9,0,3,2,}*/
15406: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
15407: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 15408: * individual quantitative, fixed or varying:
15409: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
15410: * 3, 1, 0, 0, 0, 0, 0, 0},
15411: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.349 brouard 15412:
15413: /* Probably useless zeroes */
15414: for(i=1;i<NCOVMAX;i++){
15415: DummyV[i]=0;
15416: FixedV[i]=0;
15417: }
15418:
15419: for(i=1; i <=ncovcol;i++){
15420: DummyV[i]=0;
15421: FixedV[i]=0;
15422: }
15423: for(i=ncovcol+1; i <=ncovcol+nqv;i++){
15424: DummyV[i]=1;
15425: FixedV[i]=0;
15426: }
15427: for(i=ncovcol+nqv+1; i <=ncovcol+nqv+ntv;i++){
15428: DummyV[i]=0;
15429: FixedV[i]=1;
15430: }
15431: for(i=ncovcol+nqv+ntv+1; i <=ncovcol+nqv+ntv+nqtv;i++){
15432: DummyV[i]=1;
15433: FixedV[i]=1;
15434: }
15435: for(i=1; i <=ncovcol+nqv+ntv+nqtv;i++){
15436: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",i,i,DummyV[i],i,FixedV[i]);
15437: fprintf(ficlog,"Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",i,i,DummyV[i],i,FixedV[i]);
15438: }
15439:
15440:
15441:
1.186 brouard 15442: /* Main decodemodel */
15443:
1.187 brouard 15444:
1.223 brouard 15445: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 15446: goto end;
15447:
1.137 brouard 15448: if((double)(lastobs-imx)/(double)imx > 1.10){
15449: nbwarn++;
15450: printf("Warning: The value of parameter lastobs=%d is big compared to the \n effective number of cases imx=%d, please adjust, \n otherwise you are allocating more memory than necessary.\n",lastobs, imx);
15451: fprintf(ficlog,"Warning: The value of parameter lastobs=%d is big compared to the \n effective number of cases imx=%d, please adjust, \n otherwise you are allocating more memory than necessary.\n",lastobs, imx);
15452: }
1.136 brouard 15453: /* if(mle==1){*/
1.137 brouard 15454: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
15455: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 15456: }
15457:
15458: /*-calculation of age at interview from date of interview and age at death -*/
15459: agev=matrix(1,maxwav,1,imx);
15460:
15461: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
15462: goto end;
15463:
1.126 brouard 15464:
1.136 brouard 15465: agegomp=(int)agemin;
1.290 brouard 15466: free_vector(moisnais,firstobs,lastobs);
15467: free_vector(annais,firstobs,lastobs);
1.126 brouard 15468: /* free_matrix(mint,1,maxwav,1,n);
15469: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 15470: /* free_vector(moisdc,1,n); */
15471: /* free_vector(andc,1,n); */
1.145 brouard 15472: /* */
15473:
1.126 brouard 15474: wav=ivector(1,imx);
1.214 brouard 15475: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
15476: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
15477: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
15478: dh=imatrix(1,lastpass-firstpass+2,1,imx); /* We are adding a wave if status is unknown at last wave but death occurs after last wave.*/
15479: bh=imatrix(1,lastpass-firstpass+2,1,imx);
15480: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 15481:
15482: /* Concatenates waves */
1.214 brouard 15483: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
15484: Death is a valid wave (if date is known).
15485: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
15486: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
15487: and mw[mi+1][i]. dh depends on stepm.
15488: */
15489:
1.126 brouard 15490: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 15491: /* Concatenates waves */
1.145 brouard 15492:
1.290 brouard 15493: free_vector(moisdc,firstobs,lastobs);
15494: free_vector(andc,firstobs,lastobs);
1.215 brouard 15495:
1.126 brouard 15496: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
15497: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
15498: ncodemax[1]=1;
1.145 brouard 15499: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 15500: cptcoveff=0;
1.220 brouard 15501: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
1.335 brouard 15502: tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; as well as calculate cptcoveff or number of total effective dummy covariates*/
1.227 brouard 15503: }
15504:
15505: ncovcombmax=pow(2,cptcoveff);
1.338 brouard 15506: invalidvarcomb=ivector(0, ncovcombmax);
15507: for(i=0;i<ncovcombmax;i++)
1.227 brouard 15508: invalidvarcomb[i]=0;
15509:
1.211 brouard 15510: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 15511: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 15512: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 15513:
1.200 brouard 15514: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 15515: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 15516: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 15517: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
15518: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
15519: * (currently 0 or 1) in the data.
15520: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
15521: * corresponding modality (h,j).
15522: */
15523:
1.145 brouard 15524: h=0;
15525: /*if (cptcovn > 0) */
1.126 brouard 15526: m=pow(2,cptcoveff);
15527:
1.144 brouard 15528: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 15529: * For k=4 covariates, h goes from 1 to m=2**k
15530: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
15531: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.329 brouard 15532: * h\k 1 2 3 4 * h-1\k-1 4 3 2 1
15533: *______________________________ *______________________
15534: * 1 i=1 1 i=1 1 i=1 1 i=1 1 * 0 0 0 0 0
15535: * 2 2 1 1 1 * 1 0 0 0 1
15536: * 3 i=2 1 2 1 1 * 2 0 0 1 0
15537: * 4 2 2 1 1 * 3 0 0 1 1
15538: * 5 i=3 1 i=2 1 2 1 * 4 0 1 0 0
15539: * 6 2 1 2 1 * 5 0 1 0 1
15540: * 7 i=4 1 2 2 1 * 6 0 1 1 0
15541: * 8 2 2 2 1 * 7 0 1 1 1
15542: * 9 i=5 1 i=3 1 i=2 1 2 * 8 1 0 0 0
15543: * 10 2 1 1 2 * 9 1 0 0 1
15544: * 11 i=6 1 2 1 2 * 10 1 0 1 0
15545: * 12 2 2 1 2 * 11 1 0 1 1
15546: * 13 i=7 1 i=4 1 2 2 * 12 1 1 0 0
15547: * 14 2 1 2 2 * 13 1 1 0 1
15548: * 15 i=8 1 2 2 2 * 14 1 1 1 0
15549: * 16 2 2 2 2 * 15 1 1 1 1
15550: */
1.212 brouard 15551: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 15552: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
15553: * and the value of each covariate?
15554: * V1=1, V2=1, V3=2, V4=1 ?
15555: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
15556: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
15557: * In order to get the real value in the data, we use nbcode
15558: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
15559: * We are keeping this crazy system in order to be able (in the future?)
15560: * to have more than 2 values (0 or 1) for a covariate.
15561: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
15562: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
15563: * bbbbbbbb
15564: * 76543210
15565: * h-1 00000101 (6-1=5)
1.219 brouard 15566: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 15567: * &
15568: * 1 00000001 (1)
1.219 brouard 15569: * 00000000 = 1 & ((h-1) >> (k-1))
15570: * +1= 00000001 =1
1.211 brouard 15571: *
15572: * h=14, k=3 => h'=h-1=13, k'=k-1=2
15573: * h' 1101 =2^3+2^2+0x2^1+2^0
15574: * >>k' 11
15575: * & 00000001
15576: * = 00000001
15577: * +1 = 00000010=2 = codtabm(14,3)
15578: * Reverse h=6 and m=16?
15579: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
15580: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
15581: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
15582: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
15583: * V3=decodtabm(14,3,2**4)=2
15584: * h'=13 1101 =2^3+2^2+0x2^1+2^0
15585: *(h-1) >> (j-1) 0011 =13 >> 2
15586: * &1 000000001
15587: * = 000000001
15588: * +1= 000000010 =2
15589: * 2211
15590: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
15591: * V3=2
1.220 brouard 15592: * codtabm and decodtabm are identical
1.211 brouard 15593: */
15594:
1.145 brouard 15595:
15596: free_ivector(Ndum,-1,NCOVMAX);
15597:
15598:
1.126 brouard 15599:
1.186 brouard 15600: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 15601: strcpy(optionfilegnuplot,optionfilefiname);
15602: if(mle==-3)
1.201 brouard 15603: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 15604: strcat(optionfilegnuplot,".gp");
15605:
15606: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
15607: printf("Problem with file %s",optionfilegnuplot);
15608: }
15609: else{
1.204 brouard 15610: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 15611: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 15612: //fprintf(ficgp,"set missing 'NaNq'\n");
15613: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 15614: }
15615: /* fclose(ficgp);*/
1.186 brouard 15616:
15617:
15618: /* Initialisation of --------- index.htm --------*/
1.126 brouard 15619:
15620: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
15621: if(mle==-3)
1.201 brouard 15622: strcat(optionfilehtm,"-MORT_");
1.126 brouard 15623: strcat(optionfilehtm,".htm");
15624: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 15625: printf("Problem with %s \n",optionfilehtm);
15626: exit(0);
1.126 brouard 15627: }
15628:
15629: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
15630: strcat(optionfilehtmcov,"-cov.htm");
15631: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
15632: printf("Problem with %s \n",optionfilehtmcov), exit(0);
15633: }
15634: else{
15635: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
15636: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 15637: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 15638: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
15639: }
15640:
1.335 brouard 15641: fprintf(fichtm,"<html><head>\n<meta charset=\"utf-8\"/><meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n\
15642: <title>IMaCh %s</title></head>\n\
15643: <body><font size=\"7\"><a href=http:/euroreves.ined.fr/imach>IMaCh for Interpolated Markov Chain</a> </font><br>\n\
15644: <font size=\"3\">Sponsored by Copyright (C) 2002-2015 <a href=http://www.ined.fr>INED</a>\
15645: -EUROREVES-Institut de longévité-2013-2022-Japan Society for the Promotion of Sciences 日本学術振興会 \
15646: (<a href=https://www.jsps.go.jp/english/e-grants/>Grant-in-Aid for Scientific Research 25293121</a>) - \
15647: <a href=https://software.intel.com/en-us>Intel Software 2015-2018</a></font><br> \n", optionfilehtm);
15648:
15649: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 15650: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 15651: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.337 brouard 15652: This file: <a href=\"%s\">%s</a></br>Title=%s <br>Datafile=<a href=\"%s\">%s</a> Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\
1.126 brouard 15653: \n\
15654: <hr size=\"2\" color=\"#EC5E5E\">\
15655: <ul><li><h4>Parameter files</h4>\n\
15656: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
15657: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
15658: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
15659: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
15660: - Date and time at start: %s</ul>\n",\
1.335 brouard 15661: version,fullversion,optionfilehtm,optionfilehtm,title,datafile,datafile,firstpass,lastpass,stepm, weightopt, model, \
1.126 brouard 15662: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
15663: fileres,fileres,\
15664: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
15665: fflush(fichtm);
15666:
15667: strcpy(pathr,path);
15668: strcat(pathr,optionfilefiname);
1.184 brouard 15669: #ifdef WIN32
15670: _chdir(optionfilefiname); /* Move to directory named optionfile */
15671: #else
1.126 brouard 15672: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 15673: #endif
15674:
1.126 brouard 15675:
1.220 brouard 15676: /* Calculates basic frequencies. Computes observed prevalence at single age
15677: and for any valid combination of covariates
1.126 brouard 15678: and prints on file fileres'p'. */
1.359 brouard 15679: freqsummary(fileres, p, pstart, (double)agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 15680: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 15681:
15682: fprintf(fichtm,"\n");
1.286 brouard 15683: fprintf(fichtm,"<h4>Parameter line 2</h4><ul><li>Tolerance for the convergence of the likelihood: ftol=%g \n<li>Interval for the elementary matrix (in month): stepm=%d",\
1.274 brouard 15684: ftol, stepm);
15685: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
15686: ncurrv=1;
15687: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
15688: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
15689: ncurrv=i;
15690: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 15691: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 15692: ncurrv=i;
15693: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 15694: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 15695: ncurrv=i;
15696: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
15697: fprintf(fichtm,"\n<li>Weights column \n<br>Number of alive states: nlstate=%d <br>Number of death states (not really implemented): ndeath=%d \n<li>Number of waves: maxwav=%d \n<li>Parameter for maximization (1), using parameter values (0), for design of parameters and variance-covariance matrix: mle=%d \n<li>Does the weight column be taken into account (1), or not (0): weight=%d</ul>\n", \
15698: nlstate, ndeath, maxwav, mle, weightopt);
15699:
15700: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
15701: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
15702:
15703:
1.317 brouard 15704: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Number of (used) observations=%d <br>\n\
1.126 brouard 15705: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
15706: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 15707: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 15708: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 15709: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
15710: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
15711: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
15712: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 15713:
1.126 brouard 15714: /* For Powell, parameters are in a vector p[] starting at p[1]
15715: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
15716: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
15717:
15718: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 15719: /* For mortality only */
1.126 brouard 15720: if (mle==-3){
1.136 brouard 15721: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 15722: for(i=1;i<=NDIM;i++)
15723: for(j=1;j<=NDIM;j++)
15724: ximort[i][j]=0.;
1.186 brouard 15725: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 15726: cens=ivector(firstobs,lastobs);
15727: ageexmed=vector(firstobs,lastobs);
15728: agecens=vector(firstobs,lastobs);
15729: dcwave=ivector(firstobs,lastobs);
1.223 brouard 15730:
1.126 brouard 15731: for (i=1; i<=imx; i++){
15732: dcwave[i]=-1;
15733: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 15734: if (s[m][i]>nlstate) {
15735: dcwave[i]=m;
15736: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
15737: break;
15738: }
1.126 brouard 15739: }
1.226 brouard 15740:
1.126 brouard 15741: for (i=1; i<=imx; i++) {
15742: if (wav[i]>0){
1.226 brouard 15743: ageexmed[i]=agev[mw[1][i]][i];
15744: j=wav[i];
15745: agecens[i]=1.;
15746:
15747: if (ageexmed[i]> 1 && wav[i] > 0){
15748: agecens[i]=agev[mw[j][i]][i];
15749: cens[i]= 1;
15750: }else if (ageexmed[i]< 1)
15751: cens[i]= -1;
15752: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
15753: cens[i]=0 ;
1.126 brouard 15754: }
15755: else cens[i]=-1;
15756: }
15757:
15758: for (i=1;i<=NDIM;i++) {
15759: for (j=1;j<=NDIM;j++)
1.226 brouard 15760: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 15761: }
15762:
1.302 brouard 15763: p[1]=0.0268; p[NDIM]=0.083;
15764: /* printf("%lf %lf", p[1], p[2]); */
1.126 brouard 15765:
15766:
1.136 brouard 15767: #ifdef GSL
15768: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 15769: #else
1.359 brouard 15770: printf("Powell-mort\n"); fprintf(ficlog,"Powell-mort\n");
1.136 brouard 15771: #endif
1.201 brouard 15772: strcpy(filerespow,"POW-MORT_");
15773: strcat(filerespow,fileresu);
1.126 brouard 15774: if((ficrespow=fopen(filerespow,"w"))==NULL) {
15775: printf("Problem with resultfile: %s\n", filerespow);
15776: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
15777: }
1.136 brouard 15778: #ifdef GSL
15779: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 15780: #else
1.126 brouard 15781: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 15782: #endif
1.126 brouard 15783: /* for (i=1;i<=nlstate;i++)
15784: for(j=1;j<=nlstate+ndeath;j++)
15785: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
15786: */
15787: fprintf(ficrespow,"\n");
1.136 brouard 15788: #ifdef GSL
15789: /* gsl starts here */
15790: T = gsl_multimin_fminimizer_nmsimplex;
15791: gsl_multimin_fminimizer *sfm = NULL;
15792: gsl_vector *ss, *x;
15793: gsl_multimin_function minex_func;
15794:
15795: /* Initial vertex size vector */
15796: ss = gsl_vector_alloc (NDIM);
15797:
15798: if (ss == NULL){
15799: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
15800: }
15801: /* Set all step sizes to 1 */
15802: gsl_vector_set_all (ss, 0.001);
15803:
15804: /* Starting point */
1.126 brouard 15805:
1.136 brouard 15806: x = gsl_vector_alloc (NDIM);
15807:
15808: if (x == NULL){
15809: gsl_vector_free(ss);
15810: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
15811: }
15812:
15813: /* Initialize method and iterate */
15814: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 15815: /* gsl_vector_set(x, 0, 0.0268); */
15816: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 15817: gsl_vector_set(x, 0, p[1]);
15818: gsl_vector_set(x, 1, p[2]);
15819:
15820: minex_func.f = &gompertz_f;
15821: minex_func.n = NDIM;
15822: minex_func.params = (void *)&p; /* ??? */
15823:
15824: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
15825: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
15826:
15827: printf("Iterations beginning .....\n\n");
15828: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
15829:
15830: iteri=0;
15831: while (rval == GSL_CONTINUE){
15832: iteri++;
15833: status = gsl_multimin_fminimizer_iterate(sfm);
15834:
15835: if (status) printf("error: %s\n", gsl_strerror (status));
15836: fflush(0);
15837:
15838: if (status)
15839: break;
15840:
15841: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
15842: ssval = gsl_multimin_fminimizer_size (sfm);
15843:
15844: if (rval == GSL_SUCCESS)
15845: printf ("converged to a local maximum at\n");
15846:
15847: printf("%5d ", iteri);
15848: for (it = 0; it < NDIM; it++){
15849: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
15850: }
15851: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
15852: }
15853:
15854: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
15855:
15856: gsl_vector_free(x); /* initial values */
15857: gsl_vector_free(ss); /* inital step size */
15858: for (it=0; it<NDIM; it++){
15859: p[it+1]=gsl_vector_get(sfm->x,it);
15860: fprintf(ficrespow," %.12lf", p[it]);
15861: }
15862: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
15863: #endif
15864: #ifdef POWELL
1.361 brouard 15865: #ifdef LINMINORIGINAL
15866: #else /* LINMINORIGINAL */
15867:
15868: flatdir=ivector(1,npar);
15869: for (j=1;j<=npar;j++) flatdir[j]=0;
15870: #endif /*LINMINORIGINAL */
1.362 brouard 15871: /* powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz); */
15872: /* double h0=0.25; */
15873: macheps=pow(16.0,-13.0);
15874: printf("Praxis Gegenfurtner mle=%d\n",mle);
15875: fprintf(ficlog, "Praxis Gegenfurtner mle=%d\n", mle);fflush(ficlog);
15876: /* ffmin = praxis(ftol,macheps, h0, npar, prin, p, gompertz); */
15877: /* For the Gompertz we use only two parameters */
15878: int _npar=2;
15879: ffmin = praxis(ftol,macheps, h0, _npar, 4, p, gompertz);
15880: printf("End Praxis\n");
1.126 brouard 15881: fclose(ficrespow);
1.361 brouard 15882: #ifdef LINMINORIGINAL
15883: #else
15884: free_ivector(flatdir,1,npar);
15885: #endif /* LINMINORIGINAL*/
1.364 ! brouard 15886: #endif /* POWELL */
1.203 brouard 15887: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 15888:
15889: for(i=1; i <=NDIM; i++)
15890: for(j=i+1;j<=NDIM;j++)
1.359 brouard 15891: matcov[i][j]=matcov[j][i];
1.126 brouard 15892:
15893: printf("\nCovariance matrix\n ");
1.203 brouard 15894: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 15895: for(i=1; i <=NDIM; i++) {
15896: for(j=1;j<=NDIM;j++){
1.220 brouard 15897: printf("%f ",matcov[i][j]);
15898: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 15899: }
1.203 brouard 15900: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 15901: }
15902:
15903: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 15904: for (i=1;i<=NDIM;i++) {
1.126 brouard 15905: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 15906: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
15907: }
1.302 brouard 15908: lsurv=vector(agegomp,AGESUP);
15909: lpop=vector(agegomp,AGESUP);
15910: tpop=vector(agegomp,AGESUP);
1.126 brouard 15911: lsurv[agegomp]=100000;
15912:
15913: for (k=agegomp;k<=AGESUP;k++) {
15914: agemortsup=k;
15915: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
15916: }
15917:
15918: for (k=agegomp;k<agemortsup;k++)
15919: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
15920:
15921: for (k=agegomp;k<agemortsup;k++){
15922: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
15923: sumlpop=sumlpop+lpop[k];
15924: }
15925:
15926: tpop[agegomp]=sumlpop;
15927: for (k=agegomp;k<(agemortsup-3);k++){
15928: /* tpop[k+1]=2;*/
15929: tpop[k+1]=tpop[k]-lpop[k];
15930: }
15931:
15932:
15933: printf("\nAge lx qx dx Lx Tx e(x)\n");
15934: for (k=agegomp;k<(agemortsup-2);k++)
15935: printf("%d %.0lf %lf %.0lf %.0lf %.0lf %lf\n",k,lsurv[k],p[1]*exp(p[2]*(k-agegomp)),(p[1]*exp(p[2]*(k-agegomp)))*lsurv[k],lpop[k],tpop[k],tpop[k]/lsurv[k]);
15936:
15937:
15938: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 15939: ageminpar=50;
15940: agemaxpar=100;
1.194 brouard 15941: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
15942: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
15943: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
15944: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
15945: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
15946: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
15947: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 15948: }else{
15949: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
15950: fprintf(ficlog,"Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
1.201 brouard 15951: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 15952: }
1.201 brouard 15953: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 15954: stepm, weightopt,\
15955: model,imx,p,matcov,agemortsup);
15956:
1.302 brouard 15957: free_vector(lsurv,agegomp,AGESUP);
15958: free_vector(lpop,agegomp,AGESUP);
15959: free_vector(tpop,agegomp,AGESUP);
1.220 brouard 15960: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 15961: free_ivector(dcwave,firstobs,lastobs);
15962: free_vector(agecens,firstobs,lastobs);
15963: free_vector(ageexmed,firstobs,lastobs);
15964: free_ivector(cens,firstobs,lastobs);
1.220 brouard 15965: #ifdef GSL
1.136 brouard 15966: #endif
1.186 brouard 15967: } /* Endof if mle==-3 mortality only */
1.205 brouard 15968: /* Standard */
15969: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
15970: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
15971: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 15972: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 15973: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
15974: for (k=1; k<=npar;k++)
15975: printf(" %d %8.5f",k,p[k]);
15976: printf("\n");
1.205 brouard 15977: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
15978: /* mlikeli uses func not funcone */
1.247 brouard 15979: /* for(i=1;i<nlstate;i++){ */
15980: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
15981: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
15982: /* } */
1.205 brouard 15983: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
15984: }
15985: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
15986: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
15987: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
15988: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
15989: }
15990: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 15991: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
15992: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
1.335 brouard 15993: /* exit(0); */
1.126 brouard 15994: for (k=1; k<=npar;k++)
15995: printf(" %d %8.5f",k,p[k]);
15996: printf("\n");
15997:
15998: /*--------- results files --------------*/
1.283 brouard 15999: /* fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\nftol=%e stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle= 0 weight=%d\nmodel=1+age+%s.\n", title, datafile, lastobs, firstpass,lastpass,ftol, stepm, ncovcol, nqv, ntv, nqtv, nlstate, ndeath, maxwav, weightopt,model); */
1.126 brouard 16000:
16001:
16002: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 16003: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); /* Printing model equation */
1.126 brouard 16004: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 16005:
16006: printf("#model= 1 + age ");
16007: fprintf(ficres,"#model= 1 + age ");
16008: fprintf(ficlog,"#model= 1 + age ");
16009: fprintf(fichtm,"\n<ul><li> model=1+age+%s\n \
16010: </ul>", model);
16011:
16012: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">\n");
16013: fprintf(fichtm, "<tr><th>Model=</th><th>1</th><th>+ age</th>");
16014: if(nagesqr==1){
16015: printf(" + age*age ");
16016: fprintf(ficres," + age*age ");
16017: fprintf(ficlog," + age*age ");
16018: fprintf(fichtm, "<th>+ age*age</th>");
16019: }
1.362 brouard 16020: for(j=1;j <=ncovmodel-2-nagesqr;j++){
1.319 brouard 16021: if(Typevar[j]==0) {
16022: printf(" + V%d ",Tvar[j]);
16023: fprintf(ficres," + V%d ",Tvar[j]);
16024: fprintf(ficlog," + V%d ",Tvar[j]);
16025: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
16026: }else if(Typevar[j]==1) {
16027: printf(" + V%d*age ",Tvar[j]);
16028: fprintf(ficres," + V%d*age ",Tvar[j]);
16029: fprintf(ficlog," + V%d*age ",Tvar[j]);
16030: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
16031: }else if(Typevar[j]==2) {
16032: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
16033: fprintf(ficres," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
16034: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
16035: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 16036: }else if(Typevar[j]==3) { /* TO VERIFY */
16037: printf(" + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
16038: fprintf(ficres," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
16039: fprintf(ficlog," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
16040: fprintf(fichtm, "<th>+ V%d*V%d*age</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.319 brouard 16041: }
16042: }
16043: printf("\n");
16044: fprintf(ficres,"\n");
16045: fprintf(ficlog,"\n");
16046: fprintf(fichtm, "</tr>");
16047: fprintf(fichtm, "\n");
16048:
16049:
1.126 brouard 16050: for(i=1,jk=1; i <=nlstate; i++){
16051: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 16052: if (k != i) {
1.319 brouard 16053: fprintf(fichtm, "<tr>");
1.225 brouard 16054: printf("%d%d ",i,k);
16055: fprintf(ficlog,"%d%d ",i,k);
16056: fprintf(ficres,"%1d%1d ",i,k);
1.319 brouard 16057: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 16058: for(j=1; j <=ncovmodel; j++){
16059: printf("%12.7f ",p[jk]);
16060: fprintf(ficlog,"%12.7f ",p[jk]);
16061: fprintf(ficres,"%12.7f ",p[jk]);
1.319 brouard 16062: fprintf(fichtm, "<td>%12.7f</td>",p[jk]);
1.225 brouard 16063: jk++;
16064: }
16065: printf("\n");
16066: fprintf(ficlog,"\n");
16067: fprintf(ficres,"\n");
1.319 brouard 16068: fprintf(fichtm, "</tr>\n");
1.225 brouard 16069: }
1.126 brouard 16070: }
16071: }
1.319 brouard 16072: /* fprintf(fichtm,"</tr>\n"); */
16073: fprintf(fichtm,"</table>\n");
16074: fprintf(fichtm, "\n");
16075:
1.203 brouard 16076: if(mle != 0){
16077: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 16078: ftolhess=ftol; /* Usually correct */
1.203 brouard 16079: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
16080: printf("Parameters and 95%% confidence intervals\n W is simply the result of the division of the parameter by the square root of covariance of the parameter.\n And Wald-based confidence intervals plus and minus 1.96 * W .\n But be careful that parameters are highly correlated because incidence of disability is highly correlated to incidence of recovery.\n It might be better to visualize the covariance matrix. See the page 'Matrix of variance-covariance of one-step probabilities' and its graphs.\n");
16081: fprintf(ficlog, "Parameters, Wald tests and Wald-based confidence intervals\n W is simply the result of the division of the parameter by the square root of covariance of the parameter.\n And Wald-based confidence intervals plus and minus 1.96 * W \n It might be better to visualize the covariance matrix. See the page 'Matrix of variance-covariance of one-step probabilities' and its graphs.\n");
1.322 brouard 16082: fprintf(fichtm, "\n<p>The Wald test results are output only if the maximimzation of the Likelihood is performed (mle=1)\n</br>Parameters, Wald tests and Wald-based confidence intervals\n</br> W is simply the result of the division of the parameter by the square root of covariance of the parameter.\n</br> And Wald-based confidence intervals plus and minus 1.96 * W \n </br> It might be better to visualize the covariance matrix. See the page '<a href=\"%s\">Matrix of variance-covariance of one-step probabilities and its graphs</a>'.\n</br>",optionfilehtmcov);
1.319 brouard 16083: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">");
16084: fprintf(fichtm, "\n<tr><th>Model=</th><th>1</th><th>+ age</th>");
16085: if(nagesqr==1){
16086: printf(" + age*age ");
16087: fprintf(ficres," + age*age ");
16088: fprintf(ficlog," + age*age ");
16089: fprintf(fichtm, "<th>+ age*age</th>");
16090: }
1.362 brouard 16091: for(j=1;j <=ncovmodel-2-nagesqr;j++){
1.319 brouard 16092: if(Typevar[j]==0) {
16093: printf(" + V%d ",Tvar[j]);
16094: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
16095: }else if(Typevar[j]==1) {
16096: printf(" + V%d*age ",Tvar[j]);
16097: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
16098: }else if(Typevar[j]==2) {
16099: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 16100: }else if(Typevar[j]==3) { /* TO VERIFY */
16101: fprintf(fichtm, "<th>+ V%d*V%d*age</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.319 brouard 16102: }
16103: }
16104: fprintf(fichtm, "</tr>\n");
16105:
1.203 brouard 16106: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 16107: for(k=1; k <=(nlstate+ndeath); k++){
16108: if (k != i) {
1.319 brouard 16109: fprintf(fichtm, "<tr valign=top>");
1.225 brouard 16110: printf("%d%d ",i,k);
16111: fprintf(ficlog,"%d%d ",i,k);
1.319 brouard 16112: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 16113: for(j=1; j <=ncovmodel; j++){
1.319 brouard 16114: wald=p[jk]/sqrt(matcov[jk][jk]);
1.324 brouard 16115: printf("%12.7f(%12.7f) W=%8.3f CI=[%12.7f ; %12.7f] ",p[jk],sqrt(matcov[jk][jk]), p[jk]/sqrt(matcov[jk][jk]), p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk]));
16116: fprintf(ficlog,"%12.7f(%12.7f) W=%8.3f CI=[%12.7f ; %12.7f] ",p[jk],sqrt(matcov[jk][jk]), p[jk]/sqrt(matcov[jk][jk]), p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk]));
1.319 brouard 16117: if(fabs(wald) > 1.96){
1.321 brouard 16118: fprintf(fichtm, "<td><b>%12.7f</b></br> (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
1.319 brouard 16119: }else{
16120: fprintf(fichtm, "<td>%12.7f (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
16121: }
1.324 brouard 16122: fprintf(fichtm,"W=%8.3f</br>",wald);
1.319 brouard 16123: fprintf(fichtm,"[%12.7f;%12.7f]</br></td>", p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk]));
1.225 brouard 16124: jk++;
16125: }
16126: printf("\n");
16127: fprintf(ficlog,"\n");
1.319 brouard 16128: fprintf(fichtm, "</tr>\n");
1.225 brouard 16129: }
16130: }
1.193 brouard 16131: }
1.203 brouard 16132: } /* end of hesscov and Wald tests */
1.319 brouard 16133: fprintf(fichtm,"</table>\n");
1.225 brouard 16134:
1.203 brouard 16135: /* */
1.126 brouard 16136: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
16137: printf("# Scales (for hessian or gradient estimation)\n");
16138: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
16139: for(i=1,jk=1; i <=nlstate; i++){
16140: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 16141: if (j!=i) {
16142: fprintf(ficres,"%1d%1d",i,j);
16143: printf("%1d%1d",i,j);
16144: fprintf(ficlog,"%1d%1d",i,j);
16145: for(k=1; k<=ncovmodel;k++){
16146: printf(" %.5e",delti[jk]);
16147: fprintf(ficlog," %.5e",delti[jk]);
16148: fprintf(ficres," %.5e",delti[jk]);
16149: jk++;
16150: }
16151: printf("\n");
16152: fprintf(ficlog,"\n");
16153: fprintf(ficres,"\n");
16154: }
1.126 brouard 16155: }
16156: }
16157:
16158: fprintf(ficres,"# Covariance matrix \n# 121 Var(a12)\n# 122 Cov(b12,a12) Var(b12)\n# ...\n# 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n");
1.349 brouard 16159: if(mle >= 1) /* Too big for the screen */
1.126 brouard 16160: printf("# Covariance matrix \n# 121 Var(a12)\n# 122 Cov(b12,a12) Var(b12)\n# ...\n# 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n");
16161: fprintf(ficlog,"# Covariance matrix \n# 121 Var(a12)\n# 122 Cov(b12,a12) Var(b12)\n# ...\n# 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n");
16162: /* # 121 Var(a12)\n\ */
16163: /* # 122 Cov(b12,a12) Var(b12)\n\ */
16164: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
16165: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
16166: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
16167: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
16168: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
16169: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
16170:
16171:
16172: /* Just to have a covariance matrix which will be more understandable
16173: even is we still don't want to manage dictionary of variables
16174: */
16175: for(itimes=1;itimes<=2;itimes++){
16176: jj=0;
16177: for(i=1; i <=nlstate; i++){
1.225 brouard 16178: for(j=1; j <=nlstate+ndeath; j++){
16179: if(j==i) continue;
16180: for(k=1; k<=ncovmodel;k++){
16181: jj++;
16182: ca[0]= k+'a'-1;ca[1]='\0';
16183: if(itimes==1){
16184: if(mle>=1)
16185: printf("#%1d%1d%d",i,j,k);
16186: fprintf(ficlog,"#%1d%1d%d",i,j,k);
16187: fprintf(ficres,"#%1d%1d%d",i,j,k);
16188: }else{
16189: if(mle>=1)
16190: printf("%1d%1d%d",i,j,k);
16191: fprintf(ficlog,"%1d%1d%d",i,j,k);
16192: fprintf(ficres,"%1d%1d%d",i,j,k);
16193: }
16194: ll=0;
16195: for(li=1;li <=nlstate; li++){
16196: for(lj=1;lj <=nlstate+ndeath; lj++){
16197: if(lj==li) continue;
16198: for(lk=1;lk<=ncovmodel;lk++){
16199: ll++;
16200: if(ll<=jj){
16201: cb[0]= lk +'a'-1;cb[1]='\0';
16202: if(ll<jj){
16203: if(itimes==1){
16204: if(mle>=1)
16205: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
16206: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
16207: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
16208: }else{
16209: if(mle>=1)
16210: printf(" %.5e",matcov[jj][ll]);
16211: fprintf(ficlog," %.5e",matcov[jj][ll]);
16212: fprintf(ficres," %.5e",matcov[jj][ll]);
16213: }
16214: }else{
16215: if(itimes==1){
16216: if(mle>=1)
16217: printf(" Var(%s%1d%1d)",ca,i,j);
16218: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
16219: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
16220: }else{
16221: if(mle>=1)
16222: printf(" %.7e",matcov[jj][ll]);
16223: fprintf(ficlog," %.7e",matcov[jj][ll]);
16224: fprintf(ficres," %.7e",matcov[jj][ll]);
16225: }
16226: }
16227: }
16228: } /* end lk */
16229: } /* end lj */
16230: } /* end li */
16231: if(mle>=1)
16232: printf("\n");
16233: fprintf(ficlog,"\n");
16234: fprintf(ficres,"\n");
16235: numlinepar++;
16236: } /* end k*/
16237: } /*end j */
1.126 brouard 16238: } /* end i */
16239: } /* end itimes */
16240:
16241: fflush(ficlog);
16242: fflush(ficres);
1.225 brouard 16243: while(fgets(line, MAXLINE, ficpar)) {
16244: /* If line starts with a # it is a comment */
16245: if (line[0] == '#') {
16246: numlinepar++;
16247: fputs(line,stdout);
16248: fputs(line,ficparo);
16249: fputs(line,ficlog);
1.299 brouard 16250: fputs(line,ficres);
1.225 brouard 16251: continue;
16252: }else
16253: break;
16254: }
16255:
1.209 brouard 16256: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
16257: /* ungetc(c,ficpar); */
16258: /* fgets(line, MAXLINE, ficpar); */
16259: /* fputs(line,stdout); */
16260: /* fputs(line,ficparo); */
16261: /* } */
16262: /* ungetc(c,ficpar); */
1.126 brouard 16263:
16264: estepm=0;
1.209 brouard 16265: if((num_filled=sscanf(line,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm, &ftolpl)) !=EOF){
1.225 brouard 16266:
16267: if (num_filled != 6) {
16268: printf("Error: Not 6 parameters in line, for example:agemin=60 agemax=95 bage=55 fage=95 estepm=24 ftolpl=6e-4\n, your line=%s . Probably you are running an older format.\n",line);
16269: fprintf(ficlog,"Error: Not 6 parameters in line, for example:agemin=60 agemax=95 bage=55 fage=95 estepm=24 ftolpl=6e-4\n, your line=%s . Probably you are running an older format.\n",line);
16270: goto end;
16271: }
16272: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
16273: }
16274: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
16275: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
16276:
1.209 brouard 16277: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 16278: if (estepm==0 || estepm < stepm) estepm=stepm;
16279: if (fage <= 2) {
16280: bage = ageminpar;
16281: fage = agemaxpar;
16282: }
16283:
16284: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 16285: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
16286: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 16287:
1.186 brouard 16288: /* Other stuffs, more or less useful */
1.254 brouard 16289: while(fgets(line, MAXLINE, ficpar)) {
16290: /* If line starts with a # it is a comment */
16291: if (line[0] == '#') {
16292: numlinepar++;
16293: fputs(line,stdout);
16294: fputs(line,ficparo);
16295: fputs(line,ficlog);
1.299 brouard 16296: fputs(line,ficres);
1.254 brouard 16297: continue;
16298: }else
16299: break;
16300: }
16301:
16302: if((num_filled=sscanf(line,"begin-prev-date=%lf/%lf/%lf end-prev-date=%lf/%lf/%lf mov_average=%d\n",&jprev1, &mprev1,&anprev1,&jprev2, &mprev2,&anprev2,&mobilav)) !=EOF){
16303:
16304: if (num_filled != 7) {
16305: printf("Error: Not 7 (data)parameters in line but %d, for example:begin-prev-date=1/1/1990 end-prev-date=1/6/2004 mov_average=0\n, your line=%s . Probably you are running an older format.\n",num_filled,line);
16306: fprintf(ficlog,"Error: Not 7 (data)parameters in line but %d, for example:begin-prev-date=1/1/1990 end-prev-date=1/6/2004 mov_average=0\n, your line=%s . Probably you are running an older format.\n",num_filled,line);
16307: goto end;
16308: }
16309: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
16310: fprintf(ficparo,"begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
16311: fprintf(ficres,"begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
16312: fprintf(ficlog,"begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
1.126 brouard 16313: }
1.254 brouard 16314:
16315: while(fgets(line, MAXLINE, ficpar)) {
16316: /* If line starts with a # it is a comment */
16317: if (line[0] == '#') {
16318: numlinepar++;
16319: fputs(line,stdout);
16320: fputs(line,ficparo);
16321: fputs(line,ficlog);
1.299 brouard 16322: fputs(line,ficres);
1.254 brouard 16323: continue;
16324: }else
16325: break;
1.126 brouard 16326: }
16327:
16328:
16329: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
16330: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
16331:
1.254 brouard 16332: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
16333: if (num_filled != 1) {
16334: printf("Error: Not 1 (data)parameters in line but %d, for example:pop_based=0\n, your line=%s . Probably you are running an older format.\n",num_filled,line);
16335: fprintf(ficlog,"Error: Not 1 (data)parameters in line but %d, for example: pop_based=1\n, your line=%s . Probably you are running an older format.\n",num_filled,line);
16336: goto end;
16337: }
16338: printf("pop_based=%d\n",popbased);
16339: fprintf(ficlog,"pop_based=%d\n",popbased);
16340: fprintf(ficparo,"pop_based=%d\n",popbased);
16341: fprintf(ficres,"pop_based=%d\n",popbased);
16342: }
16343:
1.258 brouard 16344: /* Results */
1.359 brouard 16345: /* Value of covariate in each resultine will be computed (if product) and sorted according to model rank */
1.332 brouard 16346: /* It is precov[] because we need the varying age in order to compute the real cov[] of the model equation */
16347: precov=matrix(1,MAXRESULTLINESPONE,1,NCOVMAX+1);
1.307 brouard 16348: endishere=0;
1.258 brouard 16349: nresult=0;
1.308 brouard 16350: parameterline=0;
1.258 brouard 16351: do{
16352: if(!fgets(line, MAXLINE, ficpar)){
16353: endishere=1;
1.308 brouard 16354: parameterline=15;
1.258 brouard 16355: }else if (line[0] == '#') {
16356: /* If line starts with a # it is a comment */
1.254 brouard 16357: numlinepar++;
16358: fputs(line,stdout);
16359: fputs(line,ficparo);
16360: fputs(line,ficlog);
1.299 brouard 16361: fputs(line,ficres);
1.254 brouard 16362: continue;
1.258 brouard 16363: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
16364: parameterline=11;
1.296 brouard 16365: else if(sscanf(line,"prevbackcast=%[^\n]\n",modeltemp))
1.258 brouard 16366: parameterline=12;
1.307 brouard 16367: else if(sscanf(line,"result:%[^\n]\n",modeltemp)){
1.258 brouard 16368: parameterline=13;
1.307 brouard 16369: }
1.258 brouard 16370: else{
16371: parameterline=14;
1.254 brouard 16372: }
1.308 brouard 16373: switch (parameterline){ /* =0 only if only comments */
1.258 brouard 16374: case 11:
1.296 brouard 16375: if((num_filled=sscanf(line,"prevforecast=%d starting-proj-date=%lf/%lf/%lf final-proj-date=%lf/%lf/%lf mobil_average=%d\n",&prevfcast,&jproj1,&mproj1,&anproj1,&jproj2,&mproj2,&anproj2,&mobilavproj)) !=EOF && (num_filled == 8)){
16376: fprintf(ficparo,"prevforecast=%d starting-proj-date=%.lf/%.lf/%.lf final-proj-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevfcast,jproj1,mproj1,anproj1,jproj2,mproj2,anproj2,mobilavproj);
1.258 brouard 16377: printf("prevforecast=%d starting-proj-date=%.lf/%.lf/%.lf final-proj-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevfcast,jproj1,mproj1,anproj1,jproj2,mproj2,anproj2,mobilavproj);
16378: fprintf(ficlog,"prevforecast=%d starting-proj-date=%.lf/%.lf/%.lf final-proj-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevfcast,jproj1,mproj1,anproj1,jproj2,mproj2,anproj2,mobilavproj);
16379: fprintf(ficres,"prevforecast=%d starting-proj-date=%.lf/%.lf/%.lf final-proj-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevfcast,jproj1,mproj1,anproj1,jproj2,mproj2,anproj2,mobilavproj);
16380: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 16381: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
16382: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
1.296 brouard 16383: prvforecast = 1;
16384: }
16385: else if((num_filled=sscanf(line,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",&prevfcast,&yrfproj,&mobilavproj)) !=EOF){/* && (num_filled == 3))*/
1.313 brouard 16386: printf("prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
16387: fprintf(ficlog,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
16388: fprintf(ficres,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
1.296 brouard 16389: prvforecast = 2;
16390: }
16391: else {
16392: printf("Error: Not 8 (data)parameters in line but %d, for example:prevforecast=1 starting-proj-date=1/1/1990 final-proj-date=1/1/2000 mobil_average=0\nnor 3 (data)parameters, for example:prevforecast=1 yearsfproj=10 mobil_average=0. Your line=%s . You are running probably an older format.\n, ",num_filled,line);
16393: fprintf(ficlog,"Error: Not 8 (data)parameters in line but %d, for example:prevforecast=1 starting-proj-date=1/1/1990 final-proj-date=1/1/2000 mobil_average=0\nnor 3 (data)parameters, for example:prevforecast=1 yearproj=10 mobil_average=0. Your line=%s . You are running probably an older format.\n, ",num_filled,line);
16394: goto end;
1.258 brouard 16395: }
1.254 brouard 16396: break;
1.258 brouard 16397: case 12:
1.296 brouard 16398: if((num_filled=sscanf(line,"prevbackcast=%d starting-back-date=%lf/%lf/%lf final-back-date=%lf/%lf/%lf mobil_average=%d\n",&prevbcast,&jback1,&mback1,&anback1,&jback2,&mback2,&anback2,&mobilavproj)) !=EOF && (num_filled == 8)){
16399: fprintf(ficparo,"prevbackcast=%d starting-back-date=%.lf/%.lf/%.lf final-back-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevbcast,jback1,mback1,anback1,jback2,mback2,anback2,mobilavproj);
16400: printf("prevbackcast=%d starting-back-date=%.lf/%.lf/%.lf final-back-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevbcast,jback1,mback1,anback1,jback2,mback2,anback2,mobilavproj);
16401: fprintf(ficlog,"prevbackcast=%d starting-back-date=%.lf/%.lf/%.lf final-back-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevbcast,jback1,mback1,anback1,jback2,mback2,anback2,mobilavproj);
16402: fprintf(ficres,"prevbackcast=%d starting-back-date=%.lf/%.lf/%.lf final-back-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevbcast,jback1,mback1,anback1,jback2,mback2,anback2,mobilavproj);
16403: /* day and month of back2 are not used but only year anback2.*/
1.273 brouard 16404: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
16405: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.296 brouard 16406: prvbackcast = 1;
16407: }
16408: else if((num_filled=sscanf(line,"prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",&prevbcast,&yrbproj,&mobilavproj)) ==3){/* && (num_filled == 3))*/
1.313 brouard 16409: printf("prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
16410: fprintf(ficlog,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
16411: fprintf(ficres,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
1.296 brouard 16412: prvbackcast = 2;
16413: }
16414: else {
16415: printf("Error: Not 8 (data)parameters in line but %d, for example:prevbackcast=1 starting-back-date=1/1/1990 final-back-date=1/1/2000 mobil_average=0\nnor 3 (data)parameters, for example:prevbackcast=1 yearsbproj=10 mobil_average=0. Your line=%s . You are running probably an older format.\n, ",num_filled,line);
16416: fprintf(ficlog,"Error: Not 8 (data)parameters in line but %d, for example:prevbackcast=1 starting-back-date=1/1/1990 final-back-date=1/1/2000 mobil_average=0\nnor 3 (data)parameters, for example:prevbackcast=1 yearbproj=10 mobil_average=0. Your line=%s . You are running probably an older format.\n, ",num_filled,line);
16417: goto end;
1.258 brouard 16418: }
1.230 brouard 16419: break;
1.258 brouard 16420: case 13:
1.332 brouard 16421: num_filled=sscanf(line,"result:%[^\n]\n",resultlineori);
1.307 brouard 16422: nresult++; /* Sum of resultlines */
1.342 brouard 16423: /* printf("Result %d: result:%s\n",nresult, resultlineori); */
1.332 brouard 16424: /* removefirstspace(&resultlineori); */
16425:
16426: if(strstr(resultlineori,"v") !=0){
16427: printf("Error. 'v' must be in upper case 'V' result: %s ",resultlineori);
16428: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultlineori);fflush(ficlog);
16429: return 1;
16430: }
16431: trimbb(resultline, resultlineori); /* Suppressing double blank in the resultline */
1.342 brouard 16432: /* printf("Decoderesult resultline=\"%s\" resultlineori=\"%s\"\n", resultline, resultlineori); */
1.318 brouard 16433: if(nresult > MAXRESULTLINESPONE-1){
16434: printf("ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\nYou can use the 'r' parameter file '%s' which uses option mle=0 to get other results. ",MAXRESULTLINESPONE-1,nresult,rfileres);
16435: fprintf(ficlog,"ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\nYou can use the 'r' parameter file '%s' which uses option mle=0 to get other results. ",MAXRESULTLINESPONE-1,nresult,rfileres);
1.307 brouard 16436: goto end;
16437: }
1.332 brouard 16438:
1.310 brouard 16439: if(!decoderesult(resultline, nresult)){ /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
1.314 brouard 16440: fprintf(ficparo,"result: %s\n",resultline);
16441: fprintf(ficres,"result: %s\n",resultline);
16442: fprintf(ficlog,"result: %s\n",resultline);
1.310 brouard 16443: } else
16444: goto end;
1.307 brouard 16445: break;
16446: case 14:
16447: printf("Error: Unknown command '%s'\n",line);
16448: fprintf(ficlog,"Error: Unknown command '%s'\n",line);
1.314 brouard 16449: if(line[0] == ' ' || line[0] == '\n'){
16450: printf("It should not be an empty line '%s'\n",line);
16451: fprintf(ficlog,"It should not be an empty line '%s'\n",line);
16452: }
1.307 brouard 16453: if(ncovmodel >=2 && nresult==0 ){
16454: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
16455: fprintf(ficlog,"ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 16456: }
1.307 brouard 16457: /* goto end; */
16458: break;
1.308 brouard 16459: case 15:
16460: printf("End of resultlines.\n");
16461: fprintf(ficlog,"End of resultlines.\n");
16462: break;
16463: default: /* parameterline =0 */
1.307 brouard 16464: nresult=1;
16465: decoderesult(".",nresult ); /* No covariate */
1.258 brouard 16466: } /* End switch parameterline */
16467: }while(endishere==0); /* End do */
1.126 brouard 16468:
1.230 brouard 16469: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 16470: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 16471:
16472: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 16473: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 16474: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 16475: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
16476: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 16477: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 16478: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
16479: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 16480: }else{
1.270 brouard 16481: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
1.296 brouard 16482: /* It seems that anprojd which is computed from the mean year at interview which is known yet because of freqsummary */
16483: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */ /* Done in freqsummary */
16484: if(prvforecast==1){
16485: dateprojd=(jproj1+12*mproj1+365*anproj1)/365;
16486: jprojd=jproj1;
16487: mprojd=mproj1;
16488: anprojd=anproj1;
16489: dateprojf=(jproj2+12*mproj2+365*anproj2)/365;
16490: jprojf=jproj2;
16491: mprojf=mproj2;
16492: anprojf=anproj2;
16493: } else if(prvforecast == 2){
16494: dateprojd=dateintmean;
16495: date2dmy(dateprojd,&jprojd, &mprojd, &anprojd);
16496: dateprojf=dateintmean+yrfproj;
16497: date2dmy(dateprojf,&jprojf, &mprojf, &anprojf);
16498: }
16499: if(prvbackcast==1){
16500: datebackd=(jback1+12*mback1+365*anback1)/365;
16501: jbackd=jback1;
16502: mbackd=mback1;
16503: anbackd=anback1;
16504: datebackf=(jback2+12*mback2+365*anback2)/365;
16505: jbackf=jback2;
16506: mbackf=mback2;
16507: anbackf=anback2;
16508: } else if(prvbackcast == 2){
16509: datebackd=dateintmean;
16510: date2dmy(datebackd,&jbackd, &mbackd, &anbackd);
16511: datebackf=dateintmean-yrbproj;
16512: date2dmy(datebackf,&jbackf, &mbackf, &anbackf);
16513: }
16514:
1.350 brouard 16515: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage);/* HERE valgrind Tvard*/
1.220 brouard 16516: }
16517: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.296 brouard 16518: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,prevbcast, estepm, \
16519: jprev1,mprev1,anprev1,dateprev1, dateprojd, datebackd,jprev2,mprev2,anprev2,dateprev2,dateprojf, datebackf);
1.220 brouard 16520:
1.225 brouard 16521: /*------------ free_vector -------------*/
16522: /* chdir(path); */
1.220 brouard 16523:
1.215 brouard 16524: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
16525: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
16526: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
16527: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 16528: free_lvector(num,firstobs,lastobs);
16529: free_vector(agedc,firstobs,lastobs);
1.126 brouard 16530: /*free_matrix(covar,0,NCOVMAX,1,n);*/
16531: /*free_matrix(covar,1,NCOVMAX,1,n);*/
16532: fclose(ficparo);
16533: fclose(ficres);
1.220 brouard 16534:
16535:
1.186 brouard 16536: /* Other results (useful)*/
1.220 brouard 16537:
16538:
1.126 brouard 16539: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 16540: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
16541: prlim=matrix(1,nlstate,1,nlstate);
1.332 brouard 16542: /* Computes the prevalence limit for each combination k of the dummy covariates by calling prevalim(k) */
1.209 brouard 16543: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 16544: fclose(ficrespl);
16545:
16546: /*------------- h Pij x at various ages ------------*/
1.180 brouard 16547: /*#include "hpijx.h"*/
1.332 brouard 16548: /** h Pij x Probability to be in state j at age x+h being in i at x, for each combination k of dummies in the model line or to nres?*/
16549: /* calls hpxij with combination k */
1.180 brouard 16550: hPijx(p, bage, fage);
1.145 brouard 16551: fclose(ficrespij);
1.227 brouard 16552:
1.220 brouard 16553: /* ncovcombmax= pow(2,cptcoveff); */
1.332 brouard 16554: /*-------------- Variance of one-step probabilities for a combination ij or for nres ?---*/
1.145 brouard 16555: k=1;
1.126 brouard 16556: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 16557:
1.269 brouard 16558: /* Prevalence for each covariate combination in probs[age][status][cov] */
16559: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
16560: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 16561: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 16562: for(k=1;k<=ncovcombmax;k++)
16563: probs[i][j][k]=0.;
1.269 brouard 16564: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
16565: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 16566: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 16567: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
16568: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 16569: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 16570: for(k=1;k<=ncovcombmax;k++)
16571: mobaverages[i][j][k]=0.;
1.219 brouard 16572: mobaverage=mobaverages;
16573: if (mobilav!=0) {
1.235 brouard 16574: printf("Movingaveraging observed prevalence\n");
1.258 brouard 16575: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 16576: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
16577: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
16578: printf(" Error in movingaverage mobilav=%d\n",mobilav);
16579: }
1.269 brouard 16580: } else if (mobilavproj !=0) {
1.235 brouard 16581: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 16582: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 16583: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
16584: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
16585: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
16586: }
1.269 brouard 16587: }else{
16588: printf("Internal error moving average\n");
16589: fflush(stdout);
16590: exit(1);
1.219 brouard 16591: }
16592: }/* end if moving average */
1.227 brouard 16593:
1.126 brouard 16594: /*---------- Forecasting ------------------*/
1.296 brouard 16595: if(prevfcast==1){
16596: /* /\* if(stepm ==1){*\/ */
16597: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
16598: /*This done previously after freqsummary.*/
16599: /* dateprojd=(jproj1+12*mproj1+365*anproj1)/365; */
16600: /* dateprojf=(jproj2+12*mproj2+365*anproj2)/365; */
16601:
16602: /* } else if (prvforecast==2){ */
16603: /* /\* if(stepm ==1){*\/ */
16604: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
16605: /* } */
16606: /*prevforecast(fileresu, dateintmean, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);*/
16607: prevforecast(fileresu,dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, p, cptcoveff);
1.126 brouard 16608: }
1.269 brouard 16609:
1.296 brouard 16610: /* Prevbcasting */
16611: if(prevbcast==1){
1.219 brouard 16612: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
16613: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
16614: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
16615:
16616: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
16617:
16618: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 16619:
1.219 brouard 16620: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
16621: fclose(ficresplb);
16622:
1.222 brouard 16623: hBijx(p, bage, fage, mobaverage);
16624: fclose(ficrespijb);
1.219 brouard 16625:
1.296 brouard 16626: /* /\* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, *\/ */
16627: /* /\* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); *\/ */
16628: /* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, */
16629: /* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
16630: prevbackforecast(fileresu, mobaverage, dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2,
16631: mobilavproj, bage, fage, firstpass, lastpass, p, cptcoveff);
16632:
16633:
1.269 brouard 16634: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 16635:
16636:
1.269 brouard 16637: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 16638: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
16639: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
16640: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.296 brouard 16641: } /* end Prevbcasting */
1.268 brouard 16642:
1.186 brouard 16643:
16644: /* ------ Other prevalence ratios------------ */
1.126 brouard 16645:
1.215 brouard 16646: free_ivector(wav,1,imx);
16647: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
16648: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
16649: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 16650:
16651:
1.127 brouard 16652: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 16653:
1.201 brouard 16654: strcpy(filerese,"E_");
16655: strcat(filerese,fileresu);
1.126 brouard 16656: if((ficreseij=fopen(filerese,"w"))==NULL) {
16657: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
16658: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
16659: }
1.208 brouard 16660: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
16661: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 16662:
16663: pstamp(ficreseij);
1.219 brouard 16664:
1.351 brouard 16665: /* i1=pow(2,cptcoveff); /\* Number of combination of dummy covariates *\/ */
16666: /* if (cptcovn < 1){i1=1;} */
1.235 brouard 16667:
1.351 brouard 16668: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
16669: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
16670: /* if(i1 != 1 && TKresult[nres]!= k) */
16671: /* continue; */
1.219 brouard 16672: fprintf(ficreseij,"\n#****** ");
1.235 brouard 16673: printf("\n#****** ");
1.351 brouard 16674: for(j=1;j<=cptcovs;j++){
16675: /* for(j=1;j<=cptcoveff;j++) { */
16676: /* fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
16677: fprintf(ficreseij," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
16678: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
16679: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.235 brouard 16680: }
16681: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.337 brouard 16682: printf(" V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]); /* TvarsQ[j] gives the name of the jth quantitative (fixed or time v) */
16683: fprintf(ficreseij,"V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]);
1.219 brouard 16684: }
16685: fprintf(ficreseij,"******\n");
1.235 brouard 16686: printf("******\n");
1.219 brouard 16687:
16688: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
16689: oldm=oldms;savm=savms;
1.330 brouard 16690: /* printf("HELLO Entering evsij bage=%d fage=%d k=%d estepm=%d nres=%d\n",(int) bage, (int)fage, k, estepm, nres); */
1.235 brouard 16691: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 16692:
1.219 brouard 16693: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 16694: }
16695: fclose(ficreseij);
1.208 brouard 16696: printf("done evsij\n");fflush(stdout);
16697: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 16698:
1.218 brouard 16699:
1.227 brouard 16700: /*---------- State-specific expectancies and variances ------------*/
1.336 brouard 16701: /* Should be moved in a function */
1.201 brouard 16702: strcpy(filerest,"T_");
16703: strcat(filerest,fileresu);
1.127 brouard 16704: if((ficrest=fopen(filerest,"w"))==NULL) {
16705: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
16706: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
16707: }
1.208 brouard 16708: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
16709: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 16710: strcpy(fileresstde,"STDE_");
16711: strcat(fileresstde,fileresu);
1.126 brouard 16712: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 16713: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
16714: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 16715: }
1.227 brouard 16716: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
16717: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 16718:
1.201 brouard 16719: strcpy(filerescve,"CVE_");
16720: strcat(filerescve,fileresu);
1.126 brouard 16721: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 16722: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
16723: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 16724: }
1.227 brouard 16725: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
16726: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 16727:
1.201 brouard 16728: strcpy(fileresv,"V_");
16729: strcat(fileresv,fileresu);
1.126 brouard 16730: if((ficresvij=fopen(fileresv,"w"))==NULL) {
16731: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
16732: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
16733: }
1.227 brouard 16734: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
16735: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 16736:
1.235 brouard 16737: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
16738: if (cptcovn < 1){i1=1;}
16739:
1.334 brouard 16740: for(nres=1; nres <= nresult; nres++) /* For each resultline, find the combination and output results according to the values of dummies and then quanti. */
16741: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying. For each nres and each value at position k
16742: * we know Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline
16743: * Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline
16744: * and Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
16745: /* */
16746: if(i1 != 1 && TKresult[nres]!= k) /* TKresult[nres] is the combination of this nres resultline. All the i1 combinations are not output */
1.235 brouard 16747: continue;
1.359 brouard 16748: printf("\n# model=1+age+%s \n#****** Result for:", model); /* HERE model is empty */
16749: fprintf(ficrest,"\n# model=1+age+%s \n#****** Result for:", model);
16750: fprintf(ficlog,"\n# model=1+age+%s \n#****** Result for:", model);
1.334 brouard 16751: /* It might not be a good idea to mix dummies and quantitative */
16752: /* for(j=1;j<=cptcoveff;j++){ /\* j=resultpos. Could be a loop on cptcovs: number of single dummy covariate in the result line as well as in the model *\/ */
16753: for(j=1;j<=cptcovs;j++){ /* j=resultpos. Could be a loop on cptcovs: number of single covariate (dummy or quantitative) in the result line as well as in the model */
16754: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /\* Output by variables in the resultline *\/ */
16755: /* Tvaraff[j] is the name of the dummy variable in position j in the equation model:
16756: * Tvaraff[1]@9={4, 3, 0, 0, 0, 0, 0, 0, 0}, in model=V5+V4+V3+V4*V3+V5*age
16757: * (V5 is quanti) V4 and V3 are dummies
16758: * TnsdVar[4] is the position 1 and TnsdVar[3]=2 in codtabm(k,l)(V4 V3)=V4 V3
16759: * l=1 l=2
16760: * k=1 1 1 0 0
16761: * k=2 2 1 1 0
16762: * k=3 [1] [2] 0 1
16763: * k=4 2 2 1 1
16764: * If nres=1 result: V3=1 V4=0 then k=3 and outputs
16765: * If nres=2 result: V4=1 V3=0 then k=2 and outputs
16766: * nres=1 =>k=3 j=1 V4= nbcode[4][codtabm(3,1)=1)=0; j=2 V3= nbcode[3][codtabm(3,2)=2]=1
16767: * nres=2 =>k=2 j=1 V4= nbcode[4][codtabm(2,1)=2)=1; j=2 V3= nbcode[3][codtabm(2,2)=1]=0
16768: */
16769: /* Tvresult[nres][j] Name of the variable at position j in this resultline */
16770: /* Tresult[nres][j] Value of this variable at position j could be a float if quantitative */
16771: /* We give up with the combinations!! */
1.342 brouard 16772: /* if(debugILK) */
16773: /* printf("\n j=%d In computing T_ Dummy[modelresult[%d][%d]]=%d, modelresult[%d][%d]=%d cptcovs=%d, cptcoveff=%d Fixed[modelresult[nres][j]]=%d\n", j, nres, j, Dummy[modelresult[nres][j]],nres,j,modelresult[nres][j],cptcovs, cptcoveff,Fixed[modelresult[nres][j]]); /\* end if dummy or quanti *\/ */
1.334 brouard 16774:
16775: if(Dummy[modelresult[nres][j]]==0){/* Dummy variable of the variable in position modelresult in the model corresponding to j in resultline */
1.344 brouard 16776: /* printf("V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][j]); /\* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline *\/ */ /* TinvDoQresult[nres][Name of the variable] */
16777: printf("V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); /* Output of each value for the combination TKresult[nres], ordered by the covariate values in the resultline */
16778: fprintf(ficlog,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
16779: fprintf(ficrest,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
1.334 brouard 16780: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
16781: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
16782: }else{
16783: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
16784: }
16785: /* fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
16786: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
16787: }else if(Dummy[modelresult[nres][j]]==1){ /* Quanti variable */
16788: /* For each selected (single) quantitative value */
1.337 brouard 16789: printf(" V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
16790: fprintf(ficlog," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
16791: fprintf(ficrest," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
1.334 brouard 16792: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
16793: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
16794: }else{
16795: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
16796: }
16797: }else{
16798: printf("Error in computing T_ Dummy[modelresult[%d][%d]]=%d, modelresult[%d][%d]=%d cptcovs=%d, cptcoveff=%d \n", nres, j, Dummy[modelresult[nres][j]],nres,j,modelresult[nres][j],cptcovs, cptcoveff); /* end if dummy or quanti */
16799: fprintf(ficlog,"Error in computing T_ Dummy[modelresult[%d][%d]]=%d, modelresult[%d][%d]=%d cptcovs=%d, cptcoveff=%d \n", nres, j, Dummy[modelresult[nres][j]],nres,j,modelresult[nres][j],cptcovs, cptcoveff); /* end if dummy or quanti */
16800: exit(1);
16801: }
1.335 brouard 16802: } /* End loop for each variable in the resultline */
1.334 brouard 16803: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
16804: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /\* Wrong j is not in the equation model *\/ */
16805: /* fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
16806: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
16807: /* } */
1.208 brouard 16808: fprintf(ficrest,"******\n");
1.227 brouard 16809: fprintf(ficlog,"******\n");
16810: printf("******\n");
1.208 brouard 16811:
16812: fprintf(ficresstdeij,"\n#****** ");
16813: fprintf(ficrescveij,"\n#****** ");
1.337 brouard 16814: /* It could have been: for(j=1;j<=cptcoveff;j++) {printf("V=%d=%lg",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);} */
16815: /* But it won't be sorted and depends on how the resultline is ordered */
1.225 brouard 16816: for(j=1;j<=cptcoveff;j++) {
1.334 brouard 16817: fprintf(ficresstdeij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
16818: /* fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
16819: /* fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
16820: }
16821: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value, TvarsQind gives the position of a quantitative in model equation */
1.337 brouard 16822: fprintf(ficresstdeij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
16823: fprintf(ficrescveij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
1.235 brouard 16824: }
1.208 brouard 16825: fprintf(ficresstdeij,"******\n");
16826: fprintf(ficrescveij,"******\n");
16827:
16828: fprintf(ficresvij,"\n#****** ");
1.238 brouard 16829: /* pstamp(ficresvij); */
1.225 brouard 16830: for(j=1;j<=cptcoveff;j++)
1.335 brouard 16831: fprintf(ficresvij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
16832: /* fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[TnsdVar[Tvaraff[j]]])]); */
1.235 brouard 16833: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.332 brouard 16834: /* fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); /\* To solve *\/ */
1.337 brouard 16835: fprintf(ficresvij," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /* Solved */
1.235 brouard 16836: }
1.208 brouard 16837: fprintf(ficresvij,"******\n");
16838:
16839: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
16840: oldm=oldms;savm=savms;
1.235 brouard 16841: printf(" cvevsij ");
16842: fprintf(ficlog, " cvevsij ");
16843: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 16844: printf(" end cvevsij \n ");
16845: fprintf(ficlog, " end cvevsij \n ");
16846:
16847: /*
16848: */
16849: /* goto endfree; */
16850:
16851: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
16852: pstamp(ficrest);
16853:
1.269 brouard 16854: epj=vector(1,nlstate+1);
1.208 brouard 16855: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 16856: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
16857: cptcod= 0; /* To be deleted */
1.360 brouard 16858: printf("varevsij vpopbased=%d popbased=%d \n",vpopbased,popbased);
16859: fprintf(ficlog, "varevsij vpopbased=%d popbased=%d \n",vpopbased,popbased);
1.361 brouard 16860: /* Call to varevsij to get cov(e.i, e.j)= vareij[i][j][(int)age]=sum_h sum_k trgrad(h_p.i) V(theta) grad(k_p.k) Equation 20 */
16861: /* Depending of popbased which changes the prevalences, either cross-sectional or period */
1.235 brouard 16862: varevsij(optionfilefiname, vareij, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, &ncvyear, k, estepm, cptcov,cptcod,vpopbased,mobilav, strstart, nres); /* cptcod not initialized Intel */
1.360 brouard 16863: fprintf(ficrest,"# Total life expectancy with std error and decomposition into time to be expected in each state\n\
16864: # (these are weighted average of eij where weights are ");
1.227 brouard 16865: if(vpopbased==1)
1.360 brouard 16866: fprintf(ficrest,"the age specific prevalence observed (cross-sectionally) in the population i.e cross-sectionally)\n in each health state (popbased=1) (mobilav=%d)\n",mobilav);
1.227 brouard 16867: else
1.360 brouard 16868: fprintf(ficrest,"the age specific forward period (stable) prevalences in each state) \n");
16869: fprintf(ficrest,"# with proportions of time spent in each state with standard error (on the right of the table.\n ");
1.335 brouard 16870: fprintf(ficrest,"# Age popbased mobilav e.. (std) "); /* Adding covariate values? */
1.227 brouard 16871: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
1.360 brouard 16872: for (i=1;i<=nlstate;i++) fprintf(ficrest," %% e.%d/e.. (std) ",i);
1.227 brouard 16873: fprintf(ficrest,"\n");
16874: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 16875: printf("Computing age specific forward period (stable) prevalences in each health state \n");
16876: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 16877: for(age=bage; age <=fage ;age++){
1.235 brouard 16878: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 16879: if (vpopbased==1) {
16880: if(mobilav ==0){
16881: for(i=1; i<=nlstate;i++)
16882: prlim[i][i]=probs[(int)age][i][k];
16883: }else{ /* mobilav */
16884: for(i=1; i<=nlstate;i++)
16885: prlim[i][i]=mobaverage[(int)age][i][k];
16886: }
16887: }
1.219 brouard 16888:
1.227 brouard 16889: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
16890: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
16891: /* printf(" age %4.0f ",age); */
16892: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
16893: for(i=1, epj[j]=0.;i <=nlstate;i++) {
16894: epj[j] += prlim[i][i]*eij[i][j][(int)age];
16895: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
16896: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
16897: }
1.361 brouard 16898: epj[nlstate+1] +=epj[j]; /* epp=sum_j epj = sum_j sum_i w_i e_ij */
1.227 brouard 16899: }
16900: /* printf(" age %4.0f \n",age); */
1.219 brouard 16901:
1.361 brouard 16902: for(i=1, vepp=0.;i <=nlstate;i++) /* Variance of total life expectancy e.. */
1.227 brouard 16903: for(j=1;j <=nlstate;j++)
1.361 brouard 16904: vepp += vareij[i][j][(int)age]; /* sum_i sum_j cov(e.i, e.j) = var(e..) */
1.227 brouard 16905: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
1.361 brouard 16906: /* vareij[i][j] is the covariance cov(e.i, e.j) and vareij[j][j] is the variance of e.j */
1.227 brouard 16907: for(j=1;j <=nlstate;j++){
16908: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
16909: }
1.360 brouard 16910: /* And proportion of time spent in state j */
16911: /* $$ E[r(X,Y)-E(r(X,Y))]^2=[\frac{1}{\mu_y} -\frac{\mu_x}{{\mu_y}^2}]' Var(X,Y)[\frac{1}{\mu_y} -\frac{\mu_x}{{\mu_y}^2}]$$ */
1.361 brouard 16912: /* \frac{\mu_x^2}{\mu_y^2} ( \frac{\sigma^2_x}{\mu_x^2}-2\frac{\sigma_{xy}}{\mu_x\mu_y} +\frac{\sigma^2_y}{\mu_y^2}) */
16913: /* \frac{e_{.i}^2}{e_{..}^2} ( \frac{\Var e_{.i}}{e_{.i}^2}-2\frac{\Var e_{.i} + \sum_{j\ne i} \Cov e_{.j},e_{.i}}{e_{.i}e_{..}} +\frac{\Var e_{..}}{e_{..}^2})*/
16914: /*\mu_x = epj[j], \sigma^2_x = vareij[j][j][(int)age] and \mu_y=epj[nlstate+1], \sigma^2_y=vepp \sigmaxy= */
16915: /* vareij[j][j][(int)age]/epj[nlstate+1]^2 + vepp/epj[nlstate+1]^4 */
1.360 brouard 16916: for(j=1;j <=nlstate;j++){
16917: /* fprintf(ficrest," %7.3f (%7.3f)", epj[j]/epj[nlstate+1], sqrt( vareij[j][j][(int)age]/epj[j]/epj[j] + vepp/epj[j]/epj[j]/epj[j]/epj[j] )); */
1.361 brouard 16918: /* fprintf(ficrest," %7.3f (%7.3f)", epj[j]/epj[nlstate+1], sqrt( vareij[j][j][(int)age]/epj[j]/epj[j] + vepp/epj[j]/epj[j]/epj[j]/epj[j] )); */
16919:
16920: for(i=1,stdpercent=0.;i<=nlstate;i++){ /* Computing cov(e..,e.j)=cov(sum_i e.i,e.j)=sum_i cov(e.i, e.j) */
16921: stdpercent += vareij[i][j][(int)age];
16922: }
16923: stdpercent= epj[j]*epj[j]/epj[nlstate+1]/epj[nlstate+1]* (vareij[j][j][(int)age]/epj[j]/epj[j]-2.*stdpercent/epj[j]/epj[nlstate+1]+ vepp/epj[nlstate+1]/epj[nlstate+1]);
16924: /* stdpercent= epj[j]*epj[j]/epj[nlstate+1]/epj[nlstate+1]*(vareij[j][j][(int)age]/epj[j]/epj[j] + vepp/epj[nlstate+1]/epj[nlstate+1]); */ /* Without covariance */
16925: /* fprintf(ficrest," %7.3f (%7.3f)", epj[j]/epj[nlstate+1], sqrt( vareij[j][j][(int)age]/epj[nlstate+1]/epj[nlstate+1] + epj[j]*epj[j]*vepp/epj[nlstate+1]/epj[nlstate+1]/epj[nlstate+1]/epj[nlstate+1] )); */
16926: fprintf(ficrest," %7.3f (%7.3f)", epj[j]/epj[nlstate+1], sqrt(stdpercent));
1.360 brouard 16927: }
1.227 brouard 16928: fprintf(ficrest,"\n");
16929: }
1.208 brouard 16930: } /* End vpopbased */
1.269 brouard 16931: free_vector(epj,1,nlstate+1);
1.208 brouard 16932: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
16933: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 16934: printf("done selection\n");fflush(stdout);
16935: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 16936:
1.335 brouard 16937: } /* End k selection or end covariate selection for nres */
1.227 brouard 16938:
16939: printf("done State-specific expectancies\n");fflush(stdout);
16940: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
16941:
1.335 brouard 16942: /* variance-covariance of forward period prevalence */
1.269 brouard 16943: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 16944:
1.227 brouard 16945:
1.290 brouard 16946: free_vector(weight,firstobs,lastobs);
1.351 brouard 16947: free_imatrix(Tvardk,0,NCOVMAX,1,2);
1.227 brouard 16948: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 16949: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
16950: free_matrix(anint,1,maxwav,firstobs,lastobs);
16951: free_matrix(mint,1,maxwav,firstobs,lastobs);
16952: free_ivector(cod,firstobs,lastobs);
1.227 brouard 16953: free_ivector(tab,1,NCOVMAX);
16954: fclose(ficresstdeij);
16955: fclose(ficrescveij);
16956: fclose(ficresvij);
16957: fclose(ficrest);
16958: fclose(ficpar);
16959:
16960:
1.126 brouard 16961: /*---------- End : free ----------------*/
1.219 brouard 16962: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 16963: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
16964: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 16965: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
16966: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 16967: } /* mle==-3 arrives here for freeing */
1.227 brouard 16968: /* endfree:*/
1.359 brouard 16969: if(mle!=-3) free_matrix(precov, 1,MAXRESULTLINESPONE,1,NCOVMAX+1); /* Could be elsewhere ?*/
1.227 brouard 16970: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
16971: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
16972: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.341 brouard 16973: /* if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs); */
16974: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs);
1.290 brouard 16975: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
16976: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
16977: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 16978: free_matrix(matcov,1,npar,1,npar);
16979: free_matrix(hess,1,npar,1,npar);
16980: /*free_vector(delti,1,npar);*/
16981: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
16982: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 16983: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 16984: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
16985:
16986: free_ivector(ncodemax,1,NCOVMAX);
16987: free_ivector(ncodemaxwundef,1,NCOVMAX);
16988: free_ivector(Dummy,-1,NCOVMAX);
16989: free_ivector(Fixed,-1,NCOVMAX);
1.349 brouard 16990: free_ivector(DummyV,-1,NCOVMAX);
16991: free_ivector(FixedV,-1,NCOVMAX);
1.227 brouard 16992: free_ivector(Typevar,-1,NCOVMAX);
16993: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 16994: free_ivector(TvarsQ,1,NCOVMAX);
16995: free_ivector(TvarsQind,1,NCOVMAX);
16996: free_ivector(TvarsD,1,NCOVMAX);
1.330 brouard 16997: free_ivector(TnsdVar,1,NCOVMAX);
1.234 brouard 16998: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 16999: free_ivector(TvarFD,1,NCOVMAX);
17000: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 17001: free_ivector(TvarF,1,NCOVMAX);
17002: free_ivector(TvarFind,1,NCOVMAX);
17003: free_ivector(TvarV,1,NCOVMAX);
17004: free_ivector(TvarVind,1,NCOVMAX);
17005: free_ivector(TvarA,1,NCOVMAX);
17006: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 17007: free_ivector(TvarFQ,1,NCOVMAX);
17008: free_ivector(TvarFQind,1,NCOVMAX);
17009: free_ivector(TvarVD,1,NCOVMAX);
17010: free_ivector(TvarVDind,1,NCOVMAX);
17011: free_ivector(TvarVQ,1,NCOVMAX);
17012: free_ivector(TvarVQind,1,NCOVMAX);
1.349 brouard 17013: free_ivector(TvarAVVA,1,NCOVMAX);
17014: free_ivector(TvarAVVAind,1,NCOVMAX);
17015: free_ivector(TvarVVA,1,NCOVMAX);
17016: free_ivector(TvarVVAind,1,NCOVMAX);
1.339 brouard 17017: free_ivector(TvarVV,1,NCOVMAX);
17018: free_ivector(TvarVVind,1,NCOVMAX);
17019:
1.230 brouard 17020: free_ivector(Tvarsel,1,NCOVMAX);
17021: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 17022: free_ivector(Tposprod,1,NCOVMAX);
17023: free_ivector(Tprod,1,NCOVMAX);
17024: free_ivector(Tvaraff,1,NCOVMAX);
1.338 brouard 17025: free_ivector(invalidvarcomb,0,ncovcombmax);
1.227 brouard 17026: free_ivector(Tage,1,NCOVMAX);
17027: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 17028: free_ivector(TmodelInvind,1,NCOVMAX);
17029: free_ivector(TmodelInvQind,1,NCOVMAX);
1.332 brouard 17030:
1.359 brouard 17031: /* free_matrix(precov, 1,MAXRESULTLINESPONE,1,NCOVMAX+1); /\* Could be elsewhere ?*\/ */
1.332 brouard 17032:
1.227 brouard 17033: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
17034: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 17035: fflush(fichtm);
17036: fflush(ficgp);
17037:
1.227 brouard 17038:
1.126 brouard 17039: if((nberr >0) || (nbwarn>0)){
1.216 brouard 17040: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
17041: fprintf(ficlog,"End of Imach with %d errors and/or warnings %d. Please look at the log file for details.\n",nberr,nbwarn);
1.126 brouard 17042: }else{
17043: printf("End of Imach\n");
17044: fprintf(ficlog,"End of Imach\n");
17045: }
17046: printf("See log file on %s\n",filelog);
17047: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 17048: /*(void) gettimeofday(&end_time,&tzp);*/
17049: rend_time = time(NULL);
17050: end_time = *localtime(&rend_time);
17051: /* tml = *localtime(&end_time.tm_sec); */
17052: strcpy(strtend,asctime(&end_time));
1.126 brouard 17053: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
17054: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 17055: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 17056:
1.157 brouard 17057: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
17058: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
17059: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 17060: /* printf("Total time was %d uSec.\n", total_usecs);*/
17061: /* if(fileappend(fichtm,optionfilehtm)){ */
17062: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
17063: fclose(fichtm);
17064: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
17065: fclose(fichtmcov);
17066: fclose(ficgp);
17067: fclose(ficlog);
17068: /*------ End -----------*/
1.227 brouard 17069:
1.281 brouard 17070:
17071: /* Executes gnuplot */
1.227 brouard 17072:
17073: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 17074: #ifdef WIN32
1.227 brouard 17075: if (_chdir(pathcd) != 0)
17076: printf("Can't move to directory %s!\n",path);
17077: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 17078: #else
1.227 brouard 17079: if(chdir(pathcd) != 0)
17080: printf("Can't move to directory %s!\n", path);
17081: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 17082: #endif
1.126 brouard 17083: printf("Current directory %s!\n",pathcd);
17084: /*strcat(plotcmd,CHARSEPARATOR);*/
17085: sprintf(plotcmd,"gnuplot");
1.157 brouard 17086: #ifdef _WIN32
1.126 brouard 17087: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
17088: #endif
17089: if(!stat(plotcmd,&info)){
1.158 brouard 17090: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 17091: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 17092: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 17093: }else
17094: strcpy(pplotcmd,plotcmd);
1.157 brouard 17095: #ifdef __unix
1.126 brouard 17096: strcpy(plotcmd,GNUPLOTPROGRAM);
17097: if(!stat(plotcmd,&info)){
1.158 brouard 17098: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 17099: }else
17100: strcpy(pplotcmd,plotcmd);
17101: #endif
17102: }else
17103: strcpy(pplotcmd,plotcmd);
17104:
17105: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 17106: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 brouard 17107: strcpy(pplotcmd,plotcmd);
1.227 brouard 17108:
1.126 brouard 17109: if((outcmd=system(plotcmd)) != 0){
1.292 brouard 17110: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 17111: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 17112: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 brouard 17113: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 17114: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 brouard 17115: strcpy(plotcmd,pplotcmd);
17116: }
1.126 brouard 17117: }
1.158 brouard 17118: printf(" Successful, please wait...");
1.126 brouard 17119: while (z[0] != 'q') {
17120: /* chdir(path); */
1.154 brouard 17121: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 17122: scanf("%s",z);
17123: /* if (z[0] == 'c') system("./imach"); */
17124: if (z[0] == 'e') {
1.158 brouard 17125: #ifdef __APPLE__
1.152 brouard 17126: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 17127: #elif __linux
17128: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 17129: #else
1.152 brouard 17130: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 17131: #endif
17132: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
17133: system(pplotcmd);
1.126 brouard 17134: }
17135: else if (z[0] == 'g') system(plotcmd);
17136: else if (z[0] == 'q') exit(0);
17137: }
1.227 brouard 17138: end:
1.126 brouard 17139: while (z[0] != 'q') {
1.195 brouard 17140: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 17141: scanf("%s",z);
17142: }
1.283 brouard 17143: printf("End\n");
1.282 brouard 17144: exit(0);
1.126 brouard 17145: }
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