Annotation of imach/src/imach.c, revision 1.363
1.363 ! brouard 1: /* $Id: imach.c,v 1.362 2024/06/28 08:00:31 brouard Exp $
1.126 brouard 2: $State: Exp $
1.360 brouard 3: $Log: imach.c,v $
1.363 ! brouard 4: Revision 1.362 2024/06/28 08:00:31 brouard
! 5: Summary: 0.99s6
! 6:
! 7: * imach.c (Module): s6 errors with age*age (harmless).
! 8:
1.362 brouard 9: Revision 1.361 2024/05/12 20:29:32 brouard
10: Summary: Version 0.99s5
11:
12: * src/imach.c Version 0.99s5 In fact, the covariance of total life
13: expectancy e.. with a partial life expectancy e.j is high,
14: therefore the complete matrix of variance covariance has to be
15: included in the formula of the standard error of the proportion of
16: total life expectancy spent in a specific state:
17: var(X/Y)=mu_x^2/mu_y^2*(sigma_x^2/mu_x^2 -2
18: sigma_xy/mu_x/mu_y+sigma^2/mu_y^2). Also an error with mle=-3
19: made the program core dump. It is fixed in this version.
20:
1.361 brouard 21: Revision 1.360 2024/04/30 10:59:22 brouard
22: Summary: Version 0.99s4 and estimation of std of e.j/e..
23:
1.360 brouard 24: Revision 1.359 2024/04/24 21:21:17 brouard
25: Summary: First IMaCh version using Brent Praxis software based on Buckhardt and Gegenfürtner C codes
26:
1.359 brouard 27: Revision 1.6 2024/04/24 21:10:29 brouard
28: Summary: First IMaCh version using Brent Praxis software based on Buckhardt and Gegenfürtner C codes
1.358 brouard 29:
1.359 brouard 30: Revision 1.5 2023/10/09 09:10:01 brouard
31: Summary: trying to reconsider
1.357 brouard 32:
1.359 brouard 33: Revision 1.4 2023/06/22 12:50:51 brouard
34: Summary: stil on going
1.357 brouard 35:
1.359 brouard 36: Revision 1.3 2023/06/22 11:28:07 brouard
37: *** empty log message ***
1.356 brouard 38:
1.359 brouard 39: Revision 1.2 2023/06/22 11:22:40 brouard
40: Summary: with svd but not working yet
1.355 brouard 41:
1.354 brouard 42: Revision 1.353 2023/05/08 18:48:22 brouard
43: *** empty log message ***
44:
1.353 brouard 45: Revision 1.352 2023/04/29 10:46:21 brouard
46: *** empty log message ***
47:
1.352 brouard 48: Revision 1.351 2023/04/29 10:43:47 brouard
49: Summary: 099r45
50:
1.351 brouard 51: Revision 1.350 2023/04/24 11:38:06 brouard
52: *** empty log message ***
53:
1.350 brouard 54: Revision 1.349 2023/01/31 09:19:37 brouard
55: Summary: Improvements in models with age*Vn*Vm
56:
1.348 brouard 57: Revision 1.347 2022/09/18 14:36:44 brouard
58: Summary: version 0.99r42
59:
1.347 brouard 60: Revision 1.346 2022/09/16 13:52:36 brouard
61: * src/imach.c (Module): 0.99r41 Was an error when product of timevarying and fixed. Using FixedV[of name] now. Thank you Feinuo
62:
1.346 brouard 63: Revision 1.345 2022/09/16 13:40:11 brouard
64: Summary: Version 0.99r41
65:
66: * imach.c (Module): 0.99r41 Was an error when product of timevarying and fixed. Using FixedV[of name] now. Thank you Feinuo
67:
1.345 brouard 68: Revision 1.344 2022/09/14 19:33:30 brouard
69: Summary: version 0.99r40
70:
71: * imach.c (Module): Fixing names of variables in T_ (thanks to Feinuo)
72:
1.344 brouard 73: Revision 1.343 2022/09/14 14:22:16 brouard
74: Summary: version 0.99r39
75:
76: * imach.c (Module): Version 0.99r39 with colored dummy covariates
77: (fixed or time varying), using new last columns of
78: ILK_parameter.txt file.
79:
1.343 brouard 80: Revision 1.342 2022/09/11 19:54:09 brouard
81: Summary: 0.99r38
82:
83: * imach.c (Module): Adding timevarying products of any kinds,
84: should work before shifting cotvar from ncovcol+nqv columns in
85: order to have a correspondance between the column of cotvar and
86: the id of column.
87: (Module): Some cleaning and adding covariates in ILK.txt
88:
1.342 brouard 89: Revision 1.341 2022/09/11 07:58:42 brouard
90: Summary: Version 0.99r38
91:
92: After adding change in cotvar.
93:
1.341 brouard 94: Revision 1.340 2022/09/11 07:53:11 brouard
95: Summary: Version imach 0.99r37
96:
97: * imach.c (Module): Adding timevarying products of any kinds,
98: should work before shifting cotvar from ncovcol+nqv columns in
99: order to have a correspondance between the column of cotvar and
100: the id of column.
101:
1.340 brouard 102: Revision 1.339 2022/09/09 17:55:22 brouard
103: Summary: version 0.99r37
104:
105: * imach.c (Module): Many improvements for fixing products of fixed
106: timevarying as well as fixed * fixed, and test with quantitative
107: covariate.
108:
1.339 brouard 109: Revision 1.338 2022/09/04 17:40:33 brouard
110: Summary: 0.99r36
111:
112: * imach.c (Module): Now the easy runs i.e. without result or
113: model=1+age only did not work. The defautl combination should be 1
114: and not 0 because everything hasn't been tranformed yet.
115:
1.338 brouard 116: Revision 1.337 2022/09/02 14:26:02 brouard
117: Summary: version 0.99r35
118:
119: * src/imach.c: Version 0.99r35 because it outputs same results with
120: 1+age+V1+V1*age for females and 1+age for females only
121: (education=1 noweight)
122:
1.337 brouard 123: Revision 1.336 2022/08/31 09:52:36 brouard
124: *** empty log message ***
125:
1.336 brouard 126: Revision 1.335 2022/08/31 08:23:16 brouard
127: Summary: improvements...
128:
1.335 brouard 129: Revision 1.334 2022/08/25 09:08:41 brouard
130: Summary: In progress for quantitative
131:
1.334 brouard 132: Revision 1.333 2022/08/21 09:10:30 brouard
133: * src/imach.c (Module): Version 0.99r33 A lot of changes in
134: reassigning covariates: my first idea was that people will always
135: use the first covariate V1 into the model but in fact they are
136: producing data with many covariates and can use an equation model
137: with some of the covariate; it means that in a model V2+V3 instead
138: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
139: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
140: the equation model is restricted to two variables only (V2, V3)
141: and the combination for V2 should be codtabm(k,1) instead of
142: (codtabm(k,2), and the code should be
143: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
144: made. All of these should be simplified once a day like we did in
145: hpxij() for example by using precov[nres] which is computed in
146: decoderesult for each nres of each resultline. Loop should be done
147: on the equation model globally by distinguishing only product with
148: age (which are changing with age) and no more on type of
149: covariates, single dummies, single covariates.
150:
1.333 brouard 151: Revision 1.332 2022/08/21 09:06:25 brouard
152: Summary: Version 0.99r33
153:
154: * src/imach.c (Module): Version 0.99r33 A lot of changes in
155: reassigning covariates: my first idea was that people will always
156: use the first covariate V1 into the model but in fact they are
157: producing data with many covariates and can use an equation model
158: with some of the covariate; it means that in a model V2+V3 instead
159: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
160: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
161: the equation model is restricted to two variables only (V2, V3)
162: and the combination for V2 should be codtabm(k,1) instead of
163: (codtabm(k,2), and the code should be
164: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
165: made. All of these should be simplified once a day like we did in
166: hpxij() for example by using precov[nres] which is computed in
167: decoderesult for each nres of each resultline. Loop should be done
168: on the equation model globally by distinguishing only product with
169: age (which are changing with age) and no more on type of
170: covariates, single dummies, single covariates.
171:
1.332 brouard 172: Revision 1.331 2022/08/07 05:40:09 brouard
173: *** empty log message ***
174:
1.331 brouard 175: Revision 1.330 2022/08/06 07:18:25 brouard
176: Summary: last 0.99r31
177:
178: * imach.c (Module): Version of imach using partly decoderesult to rebuild xpxij function
179:
1.330 brouard 180: Revision 1.329 2022/08/03 17:29:54 brouard
181: * imach.c (Module): Many errors in graphs fixed with Vn*age covariates.
182:
1.329 brouard 183: Revision 1.328 2022/07/27 17:40:48 brouard
184: Summary: valgrind bug fixed by initializing to zero DummyV as well as Tage
185:
1.328 brouard 186: Revision 1.327 2022/07/27 14:47:35 brouard
187: Summary: Still a problem for one-step probabilities in case of quantitative variables
188:
1.327 brouard 189: Revision 1.326 2022/07/26 17:33:55 brouard
190: Summary: some test with nres=1
191:
1.326 brouard 192: Revision 1.325 2022/07/25 14:27:23 brouard
193: Summary: r30
194:
195: * imach.c (Module): Error cptcovn instead of nsd in bmij (was
196: coredumped, revealed by Feiuno, thank you.
197:
1.325 brouard 198: Revision 1.324 2022/07/23 17:44:26 brouard
199: *** empty log message ***
200:
1.324 brouard 201: Revision 1.323 2022/07/22 12:30:08 brouard
202: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
203:
1.323 brouard 204: Revision 1.322 2022/07/22 12:27:48 brouard
205: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
206:
1.322 brouard 207: Revision 1.321 2022/07/22 12:04:24 brouard
208: Summary: r28
209:
210: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
211:
1.321 brouard 212: Revision 1.320 2022/06/02 05:10:11 brouard
213: *** empty log message ***
214:
1.320 brouard 215: Revision 1.319 2022/06/02 04:45:11 brouard
216: * imach.c (Module): Adding the Wald tests from the log to the main
217: htm for better display of the maximum likelihood estimators.
218:
1.319 brouard 219: Revision 1.318 2022/05/24 08:10:59 brouard
220: * imach.c (Module): Some attempts to find a bug of wrong estimates
221: of confidencce intervals with product in the equation modelC
222:
1.318 brouard 223: Revision 1.317 2022/05/15 15:06:23 brouard
224: * imach.c (Module): Some minor improvements
225:
1.317 brouard 226: Revision 1.316 2022/05/11 15:11:31 brouard
227: Summary: r27
228:
1.316 brouard 229: Revision 1.315 2022/05/11 15:06:32 brouard
230: *** empty log message ***
231:
1.315 brouard 232: Revision 1.314 2022/04/13 17:43:09 brouard
233: * imach.c (Module): Adding link to text data files
234:
1.314 brouard 235: Revision 1.313 2022/04/11 15:57:42 brouard
236: * imach.c (Module): Error in rewriting the 'r' file with yearsfproj or yearsbproj fixed
237:
1.313 brouard 238: Revision 1.312 2022/04/05 21:24:39 brouard
239: *** empty log message ***
240:
1.312 brouard 241: Revision 1.311 2022/04/05 21:03:51 brouard
242: Summary: Fixed quantitative covariates
243:
244: Fixed covariates (dummy or quantitative)
245: with missing values have never been allowed but are ERRORS and
246: program quits. Standard deviations of fixed covariates were
247: wrongly computed. Mean and standard deviations of time varying
248: covariates are still not computed.
249:
1.311 brouard 250: Revision 1.310 2022/03/17 08:45:53 brouard
251: Summary: 99r25
252:
253: Improving detection of errors: result lines should be compatible with
254: the model.
255:
1.310 brouard 256: Revision 1.309 2021/05/20 12:39:14 brouard
257: Summary: Version 0.99r24
258:
1.309 brouard 259: Revision 1.308 2021/03/31 13:11:57 brouard
260: Summary: Version 0.99r23
261:
262:
263: * imach.c (Module): Still bugs in the result loop. Thank to Holly Benett
264:
1.308 brouard 265: Revision 1.307 2021/03/08 18:11:32 brouard
266: Summary: 0.99r22 fixed bug on result:
267:
1.307 brouard 268: Revision 1.306 2021/02/20 15:44:02 brouard
269: Summary: Version 0.99r21
270:
271: * imach.c (Module): Fix bug on quitting after result lines!
272: (Module): Version 0.99r21
273:
1.306 brouard 274: Revision 1.305 2021/02/20 15:28:30 brouard
275: * imach.c (Module): Fix bug on quitting after result lines!
276:
1.305 brouard 277: Revision 1.304 2021/02/12 11:34:20 brouard
278: * imach.c (Module): The use of a Windows BOM (huge) file is now an error
279:
1.304 brouard 280: Revision 1.303 2021/02/11 19:50:15 brouard
281: * (Module): imach.c Someone entered 'results:' instead of 'result:'. Now it is an error which is printed.
282:
1.303 brouard 283: Revision 1.302 2020/02/22 21:00:05 brouard
284: * (Module): imach.c Update mle=-3 (for computing Life expectancy
285: and life table from the data without any state)
286:
1.302 brouard 287: Revision 1.301 2019/06/04 13:51:20 brouard
288: Summary: Error in 'r'parameter file backcast yearsbproj instead of yearsfproj
289:
1.301 brouard 290: Revision 1.300 2019/05/22 19:09:45 brouard
291: Summary: version 0.99r19 of May 2019
292:
1.300 brouard 293: Revision 1.299 2019/05/22 18:37:08 brouard
294: Summary: Cleaned 0.99r19
295:
1.299 brouard 296: Revision 1.298 2019/05/22 18:19:56 brouard
297: *** empty log message ***
298:
1.298 brouard 299: Revision 1.297 2019/05/22 17:56:10 brouard
300: Summary: Fix bug by moving date2dmy and nhstepm which gaefin=-1
301:
1.297 brouard 302: Revision 1.296 2019/05/20 13:03:18 brouard
303: Summary: Projection syntax simplified
304:
305:
306: We can now start projections, forward or backward, from the mean date
307: of inteviews up to or down to a number of years of projection:
308: prevforecast=1 yearsfproj=15.3 mobil_average=0
309: or
310: prevforecast=1 starting-proj-date=1/1/2007 final-proj-date=12/31/2017 mobil_average=0
311: or
312: prevbackcast=1 yearsbproj=12.3 mobil_average=1
313: or
314: prevbackcast=1 starting-back-date=1/10/1999 final-back-date=1/1/1985 mobil_average=1
315:
1.296 brouard 316: Revision 1.295 2019/05/18 09:52:50 brouard
317: Summary: doxygen tex bug
318:
1.295 brouard 319: Revision 1.294 2019/05/16 14:54:33 brouard
320: Summary: There was some wrong lines added
321:
1.294 brouard 322: Revision 1.293 2019/05/09 15:17:34 brouard
323: *** empty log message ***
324:
1.293 brouard 325: Revision 1.292 2019/05/09 14:17:20 brouard
326: Summary: Some updates
327:
1.292 brouard 328: Revision 1.291 2019/05/09 13:44:18 brouard
329: Summary: Before ncovmax
330:
1.291 brouard 331: Revision 1.290 2019/05/09 13:39:37 brouard
332: Summary: 0.99r18 unlimited number of individuals
333:
334: 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.
335:
1.290 brouard 336: Revision 1.289 2018/12/13 09:16:26 brouard
337: Summary: Bug for young ages (<-30) will be in r17
338:
1.289 brouard 339: Revision 1.288 2018/05/02 20:58:27 brouard
340: Summary: Some bugs fixed
341:
1.288 brouard 342: Revision 1.287 2018/05/01 17:57:25 brouard
343: Summary: Bug fixed by providing frequencies only for non missing covariates
344:
1.287 brouard 345: Revision 1.286 2018/04/27 14:27:04 brouard
346: Summary: some minor bugs
347:
1.286 brouard 348: Revision 1.285 2018/04/21 21:02:16 brouard
349: Summary: Some bugs fixed, valgrind tested
350:
1.285 brouard 351: Revision 1.284 2018/04/20 05:22:13 brouard
352: Summary: Computing mean and stdeviation of fixed quantitative variables
353:
1.284 brouard 354: Revision 1.283 2018/04/19 14:49:16 brouard
355: Summary: Some minor bugs fixed
356:
1.283 brouard 357: Revision 1.282 2018/02/27 22:50:02 brouard
358: *** empty log message ***
359:
1.282 brouard 360: Revision 1.281 2018/02/27 19:25:23 brouard
361: Summary: Adding second argument for quitting
362:
1.281 brouard 363: Revision 1.280 2018/02/21 07:58:13 brouard
364: Summary: 0.99r15
365:
366: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
367:
1.280 brouard 368: Revision 1.279 2017/07/20 13:35:01 brouard
369: Summary: temporary working
370:
1.279 brouard 371: Revision 1.278 2017/07/19 14:09:02 brouard
372: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
373:
1.278 brouard 374: Revision 1.277 2017/07/17 08:53:49 brouard
375: Summary: BOM files can be read now
376:
1.277 brouard 377: Revision 1.276 2017/06/30 15:48:31 brouard
378: Summary: Graphs improvements
379:
1.276 brouard 380: Revision 1.275 2017/06/30 13:39:33 brouard
381: Summary: Saito's color
382:
1.275 brouard 383: Revision 1.274 2017/06/29 09:47:08 brouard
384: Summary: Version 0.99r14
385:
1.274 brouard 386: Revision 1.273 2017/06/27 11:06:02 brouard
387: Summary: More documentation on projections
388:
1.273 brouard 389: Revision 1.272 2017/06/27 10:22:40 brouard
390: Summary: Color of backprojection changed from 6 to 5(yellow)
391:
1.272 brouard 392: Revision 1.271 2017/06/27 10:17:50 brouard
393: Summary: Some bug with rint
394:
1.271 brouard 395: Revision 1.270 2017/05/24 05:45:29 brouard
396: *** empty log message ***
397:
1.270 brouard 398: Revision 1.269 2017/05/23 08:39:25 brouard
399: Summary: Code into subroutine, cleanings
400:
1.269 brouard 401: Revision 1.268 2017/05/18 20:09:32 brouard
402: Summary: backprojection and confidence intervals of backprevalence
403:
1.268 brouard 404: Revision 1.267 2017/05/13 10:25:05 brouard
405: Summary: temporary save for backprojection
406:
1.267 brouard 407: Revision 1.266 2017/05/13 07:26:12 brouard
408: Summary: Version 0.99r13 (improvements and bugs fixed)
409:
1.266 brouard 410: Revision 1.265 2017/04/26 16:22:11 brouard
411: Summary: imach 0.99r13 Some bugs fixed
412:
1.265 brouard 413: Revision 1.264 2017/04/26 06:01:29 brouard
414: Summary: Labels in graphs
415:
1.264 brouard 416: Revision 1.263 2017/04/24 15:23:15 brouard
417: Summary: to save
418:
1.263 brouard 419: Revision 1.262 2017/04/18 16:48:12 brouard
420: *** empty log message ***
421:
1.262 brouard 422: Revision 1.261 2017/04/05 10:14:09 brouard
423: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
424:
1.261 brouard 425: Revision 1.260 2017/04/04 17:46:59 brouard
426: Summary: Gnuplot indexations fixed (humm)
427:
1.260 brouard 428: Revision 1.259 2017/04/04 13:01:16 brouard
429: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
430:
1.259 brouard 431: Revision 1.258 2017/04/03 10:17:47 brouard
432: Summary: Version 0.99r12
433:
434: Some cleanings, conformed with updated documentation.
435:
1.258 brouard 436: Revision 1.257 2017/03/29 16:53:30 brouard
437: Summary: Temp
438:
1.257 brouard 439: Revision 1.256 2017/03/27 05:50:23 brouard
440: Summary: Temporary
441:
1.256 brouard 442: Revision 1.255 2017/03/08 16:02:28 brouard
443: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
444:
1.255 brouard 445: Revision 1.254 2017/03/08 07:13:00 brouard
446: Summary: Fixing data parameter line
447:
1.254 brouard 448: Revision 1.253 2016/12/15 11:59:41 brouard
449: Summary: 0.99 in progress
450:
1.253 brouard 451: Revision 1.252 2016/09/15 21:15:37 brouard
452: *** empty log message ***
453:
1.252 brouard 454: Revision 1.251 2016/09/15 15:01:13 brouard
455: Summary: not working
456:
1.251 brouard 457: Revision 1.250 2016/09/08 16:07:27 brouard
458: Summary: continue
459:
1.250 brouard 460: Revision 1.249 2016/09/07 17:14:18 brouard
461: Summary: Starting values from frequencies
462:
1.249 brouard 463: Revision 1.248 2016/09/07 14:10:18 brouard
464: *** empty log message ***
465:
1.248 brouard 466: Revision 1.247 2016/09/02 11:11:21 brouard
467: *** empty log message ***
468:
1.247 brouard 469: Revision 1.246 2016/09/02 08:49:22 brouard
470: *** empty log message ***
471:
1.246 brouard 472: Revision 1.245 2016/09/02 07:25:01 brouard
473: *** empty log message ***
474:
1.245 brouard 475: Revision 1.244 2016/09/02 07:17:34 brouard
476: *** empty log message ***
477:
1.244 brouard 478: Revision 1.243 2016/09/02 06:45:35 brouard
479: *** empty log message ***
480:
1.243 brouard 481: Revision 1.242 2016/08/30 15:01:20 brouard
482: Summary: Fixing a lots
483:
1.242 brouard 484: Revision 1.241 2016/08/29 17:17:25 brouard
485: Summary: gnuplot problem in Back projection to fix
486:
1.241 brouard 487: Revision 1.240 2016/08/29 07:53:18 brouard
488: Summary: Better
489:
1.240 brouard 490: Revision 1.239 2016/08/26 15:51:03 brouard
491: Summary: Improvement in Powell output in order to copy and paste
492:
493: Author:
494:
1.239 brouard 495: Revision 1.238 2016/08/26 14:23:35 brouard
496: Summary: Starting tests of 0.99
497:
1.238 brouard 498: Revision 1.237 2016/08/26 09:20:19 brouard
499: Summary: to valgrind
500:
1.237 brouard 501: Revision 1.236 2016/08/25 10:50:18 brouard
502: *** empty log message ***
503:
1.236 brouard 504: Revision 1.235 2016/08/25 06:59:23 brouard
505: *** empty log message ***
506:
1.235 brouard 507: Revision 1.234 2016/08/23 16:51:20 brouard
508: *** empty log message ***
509:
1.234 brouard 510: Revision 1.233 2016/08/23 07:40:50 brouard
511: Summary: not working
512:
1.233 brouard 513: Revision 1.232 2016/08/22 14:20:21 brouard
514: Summary: not working
515:
1.232 brouard 516: Revision 1.231 2016/08/22 07:17:15 brouard
517: Summary: not working
518:
1.231 brouard 519: Revision 1.230 2016/08/22 06:55:53 brouard
520: Summary: Not working
521:
1.230 brouard 522: Revision 1.229 2016/07/23 09:45:53 brouard
523: Summary: Completing for func too
524:
1.229 brouard 525: Revision 1.228 2016/07/22 17:45:30 brouard
526: Summary: Fixing some arrays, still debugging
527:
1.227 brouard 528: Revision 1.226 2016/07/12 18:42:34 brouard
529: Summary: temp
530:
1.226 brouard 531: Revision 1.225 2016/07/12 08:40:03 brouard
532: Summary: saving but not running
533:
1.225 brouard 534: Revision 1.224 2016/07/01 13:16:01 brouard
535: Summary: Fixes
536:
1.224 brouard 537: Revision 1.223 2016/02/19 09:23:35 brouard
538: Summary: temporary
539:
1.223 brouard 540: Revision 1.222 2016/02/17 08:14:50 brouard
541: Summary: Probably last 0.98 stable version 0.98r6
542:
1.222 brouard 543: Revision 1.221 2016/02/15 23:35:36 brouard
544: Summary: minor bug
545:
1.220 brouard 546: Revision 1.219 2016/02/15 00:48:12 brouard
547: *** empty log message ***
548:
1.219 brouard 549: Revision 1.218 2016/02/12 11:29:23 brouard
550: Summary: 0.99 Back projections
551:
1.218 brouard 552: Revision 1.217 2015/12/23 17:18:31 brouard
553: Summary: Experimental backcast
554:
1.217 brouard 555: Revision 1.216 2015/12/18 17:32:11 brouard
556: Summary: 0.98r4 Warning and status=-2
557:
558: Version 0.98r4 is now:
559: - displaying an error when status is -1, date of interview unknown and date of death known;
560: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
561: Older changes concerning s=-2, dating from 2005 have been supersed.
562:
1.216 brouard 563: Revision 1.215 2015/12/16 08:52:24 brouard
564: Summary: 0.98r4 working
565:
1.215 brouard 566: Revision 1.214 2015/12/16 06:57:54 brouard
567: Summary: temporary not working
568:
1.214 brouard 569: Revision 1.213 2015/12/11 18:22:17 brouard
570: Summary: 0.98r4
571:
1.213 brouard 572: Revision 1.212 2015/11/21 12:47:24 brouard
573: Summary: minor typo
574:
1.212 brouard 575: Revision 1.211 2015/11/21 12:41:11 brouard
576: Summary: 0.98r3 with some graph of projected cross-sectional
577:
578: Author: Nicolas Brouard
579:
1.211 brouard 580: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 581: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 582: Summary: Adding ftolpl parameter
583: Author: N Brouard
584:
585: We had difficulties to get smoothed confidence intervals. It was due
586: to the period prevalence which wasn't computed accurately. The inner
587: parameter ftolpl is now an outer parameter of the .imach parameter
588: file after estepm. If ftolpl is small 1.e-4 and estepm too,
589: computation are long.
590:
1.209 brouard 591: Revision 1.208 2015/11/17 14:31:57 brouard
592: Summary: temporary
593:
1.208 brouard 594: Revision 1.207 2015/10/27 17:36:57 brouard
595: *** empty log message ***
596:
1.207 brouard 597: Revision 1.206 2015/10/24 07:14:11 brouard
598: *** empty log message ***
599:
1.206 brouard 600: Revision 1.205 2015/10/23 15:50:53 brouard
601: Summary: 0.98r3 some clarification for graphs on likelihood contributions
602:
1.205 brouard 603: Revision 1.204 2015/10/01 16:20:26 brouard
604: Summary: Some new graphs of contribution to likelihood
605:
1.204 brouard 606: Revision 1.203 2015/09/30 17:45:14 brouard
607: Summary: looking at better estimation of the hessian
608:
609: Also a better criteria for convergence to the period prevalence And
610: therefore adding the number of years needed to converge. (The
611: prevalence in any alive state shold sum to one
612:
1.203 brouard 613: Revision 1.202 2015/09/22 19:45:16 brouard
614: Summary: Adding some overall graph on contribution to likelihood. Might change
615:
1.202 brouard 616: Revision 1.201 2015/09/15 17:34:58 brouard
617: Summary: 0.98r0
618:
619: - Some new graphs like suvival functions
620: - Some bugs fixed like model=1+age+V2.
621:
1.201 brouard 622: Revision 1.200 2015/09/09 16:53:55 brouard
623: Summary: Big bug thanks to Flavia
624:
625: Even model=1+age+V2. did not work anymore
626:
1.200 brouard 627: Revision 1.199 2015/09/07 14:09:23 brouard
628: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
629:
1.199 brouard 630: Revision 1.198 2015/09/03 07:14:39 brouard
631: Summary: 0.98q5 Flavia
632:
1.198 brouard 633: Revision 1.197 2015/09/01 18:24:39 brouard
634: *** empty log message ***
635:
1.197 brouard 636: Revision 1.196 2015/08/18 23:17:52 brouard
637: Summary: 0.98q5
638:
1.196 brouard 639: Revision 1.195 2015/08/18 16:28:39 brouard
640: Summary: Adding a hack for testing purpose
641:
642: After reading the title, ftol and model lines, if the comment line has
643: a q, starting with #q, the answer at the end of the run is quit. It
644: permits to run test files in batch with ctest. The former workaround was
645: $ echo q | imach foo.imach
646:
1.195 brouard 647: Revision 1.194 2015/08/18 13:32:00 brouard
648: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
649:
1.194 brouard 650: Revision 1.193 2015/08/04 07:17:42 brouard
651: Summary: 0.98q4
652:
1.193 brouard 653: Revision 1.192 2015/07/16 16:49:02 brouard
654: Summary: Fixing some outputs
655:
1.192 brouard 656: Revision 1.191 2015/07/14 10:00:33 brouard
657: Summary: Some fixes
658:
1.191 brouard 659: Revision 1.190 2015/05/05 08:51:13 brouard
660: Summary: Adding digits in output parameters (7 digits instead of 6)
661:
662: Fix 1+age+.
663:
1.190 brouard 664: Revision 1.189 2015/04/30 14:45:16 brouard
665: Summary: 0.98q2
666:
1.189 brouard 667: Revision 1.188 2015/04/30 08:27:53 brouard
668: *** empty log message ***
669:
1.188 brouard 670: Revision 1.187 2015/04/29 09:11:15 brouard
671: *** empty log message ***
672:
1.187 brouard 673: Revision 1.186 2015/04/23 12:01:52 brouard
674: Summary: V1*age is working now, version 0.98q1
675:
676: Some codes had been disabled in order to simplify and Vn*age was
677: working in the optimization phase, ie, giving correct MLE parameters,
678: but, as usual, outputs were not correct and program core dumped.
679:
1.186 brouard 680: Revision 1.185 2015/03/11 13:26:42 brouard
681: Summary: Inclusion of compile and links command line for Intel Compiler
682:
1.185 brouard 683: Revision 1.184 2015/03/11 11:52:39 brouard
684: Summary: Back from Windows 8. Intel Compiler
685:
1.184 brouard 686: Revision 1.183 2015/03/10 20:34:32 brouard
687: Summary: 0.98q0, trying with directest, mnbrak fixed
688:
689: We use directest instead of original Powell test; probably no
690: incidence on the results, but better justifications;
691: We fixed Numerical Recipes mnbrak routine which was wrong and gave
692: wrong results.
693:
1.183 brouard 694: Revision 1.182 2015/02/12 08:19:57 brouard
695: Summary: Trying to keep directest which seems simpler and more general
696: Author: Nicolas Brouard
697:
1.182 brouard 698: Revision 1.181 2015/02/11 23:22:24 brouard
699: Summary: Comments on Powell added
700:
701: Author:
702:
1.181 brouard 703: Revision 1.180 2015/02/11 17:33:45 brouard
704: Summary: Finishing move from main to function (hpijx and prevalence_limit)
705:
1.180 brouard 706: Revision 1.179 2015/01/04 09:57:06 brouard
707: Summary: back to OS/X
708:
1.179 brouard 709: Revision 1.178 2015/01/04 09:35:48 brouard
710: *** empty log message ***
711:
1.178 brouard 712: Revision 1.177 2015/01/03 18:40:56 brouard
713: Summary: Still testing ilc32 on OSX
714:
1.177 brouard 715: Revision 1.176 2015/01/03 16:45:04 brouard
716: *** empty log message ***
717:
1.176 brouard 718: Revision 1.175 2015/01/03 16:33:42 brouard
719: *** empty log message ***
720:
1.175 brouard 721: Revision 1.174 2015/01/03 16:15:49 brouard
722: Summary: Still in cross-compilation
723:
1.174 brouard 724: Revision 1.173 2015/01/03 12:06:26 brouard
725: Summary: trying to detect cross-compilation
726:
1.173 brouard 727: Revision 1.172 2014/12/27 12:07:47 brouard
728: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
729:
1.172 brouard 730: Revision 1.171 2014/12/23 13:26:59 brouard
731: Summary: Back from Visual C
732:
733: Still problem with utsname.h on Windows
734:
1.171 brouard 735: Revision 1.170 2014/12/23 11:17:12 brouard
736: Summary: Cleaning some \%% back to %%
737:
738: The escape was mandatory for a specific compiler (which one?), but too many warnings.
739:
1.170 brouard 740: Revision 1.169 2014/12/22 23:08:31 brouard
741: Summary: 0.98p
742:
743: Outputs some informations on compiler used, OS etc. Testing on different platforms.
744:
1.169 brouard 745: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 746: Summary: update
1.169 brouard 747:
1.168 brouard 748: Revision 1.167 2014/12/22 13:50:56 brouard
749: Summary: Testing uname and compiler version and if compiled 32 or 64
750:
751: Testing on Linux 64
752:
1.167 brouard 753: Revision 1.166 2014/12/22 11:40:47 brouard
754: *** empty log message ***
755:
1.166 brouard 756: Revision 1.165 2014/12/16 11:20:36 brouard
757: Summary: After compiling on Visual C
758:
759: * imach.c (Module): Merging 1.61 to 1.162
760:
1.165 brouard 761: Revision 1.164 2014/12/16 10:52:11 brouard
762: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
763:
764: * imach.c (Module): Merging 1.61 to 1.162
765:
1.164 brouard 766: Revision 1.163 2014/12/16 10:30:11 brouard
767: * imach.c (Module): Merging 1.61 to 1.162
768:
1.163 brouard 769: Revision 1.162 2014/09/25 11:43:39 brouard
770: Summary: temporary backup 0.99!
771:
1.162 brouard 772: Revision 1.1 2014/09/16 11:06:58 brouard
773: Summary: With some code (wrong) for nlopt
774:
775: Author:
776:
777: Revision 1.161 2014/09/15 20:41:41 brouard
778: Summary: Problem with macro SQR on Intel compiler
779:
1.161 brouard 780: Revision 1.160 2014/09/02 09:24:05 brouard
781: *** empty log message ***
782:
1.160 brouard 783: Revision 1.159 2014/09/01 10:34:10 brouard
784: Summary: WIN32
785: Author: Brouard
786:
1.159 brouard 787: Revision 1.158 2014/08/27 17:11:51 brouard
788: *** empty log message ***
789:
1.158 brouard 790: Revision 1.157 2014/08/27 16:26:55 brouard
791: Summary: Preparing windows Visual studio version
792: Author: Brouard
793:
794: In order to compile on Visual studio, time.h is now correct and time_t
795: and tm struct should be used. difftime should be used but sometimes I
796: just make the differences in raw time format (time(&now).
797: Trying to suppress #ifdef LINUX
798: Add xdg-open for __linux in order to open default browser.
799:
1.157 brouard 800: Revision 1.156 2014/08/25 20:10:10 brouard
801: *** empty log message ***
802:
1.156 brouard 803: Revision 1.155 2014/08/25 18:32:34 brouard
804: Summary: New compile, minor changes
805: Author: Brouard
806:
1.155 brouard 807: Revision 1.154 2014/06/20 17:32:08 brouard
808: Summary: Outputs now all graphs of convergence to period prevalence
809:
1.154 brouard 810: Revision 1.153 2014/06/20 16:45:46 brouard
811: Summary: If 3 live state, convergence to period prevalence on same graph
812: Author: Brouard
813:
1.153 brouard 814: Revision 1.152 2014/06/18 17:54:09 brouard
815: Summary: open browser, use gnuplot on same dir than imach if not found in the path
816:
1.152 brouard 817: Revision 1.151 2014/06/18 16:43:30 brouard
818: *** empty log message ***
819:
1.151 brouard 820: Revision 1.150 2014/06/18 16:42:35 brouard
821: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
822: Author: brouard
823:
1.150 brouard 824: Revision 1.149 2014/06/18 15:51:14 brouard
825: Summary: Some fixes in parameter files errors
826: Author: Nicolas Brouard
827:
1.149 brouard 828: Revision 1.148 2014/06/17 17:38:48 brouard
829: Summary: Nothing new
830: Author: Brouard
831:
832: Just a new packaging for OS/X version 0.98nS
833:
1.148 brouard 834: Revision 1.147 2014/06/16 10:33:11 brouard
835: *** empty log message ***
836:
1.147 brouard 837: Revision 1.146 2014/06/16 10:20:28 brouard
838: Summary: Merge
839: Author: Brouard
840:
841: Merge, before building revised version.
842:
1.146 brouard 843: Revision 1.145 2014/06/10 21:23:15 brouard
844: Summary: Debugging with valgrind
845: Author: Nicolas Brouard
846:
847: Lot of changes in order to output the results with some covariates
848: After the Edimburgh REVES conference 2014, it seems mandatory to
849: improve the code.
850: No more memory valgrind error but a lot has to be done in order to
851: continue the work of splitting the code into subroutines.
852: Also, decodemodel has been improved. Tricode is still not
853: optimal. nbcode should be improved. Documentation has been added in
854: the source code.
855:
1.144 brouard 856: Revision 1.143 2014/01/26 09:45:38 brouard
857: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
858:
859: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
860: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
861:
1.143 brouard 862: Revision 1.142 2014/01/26 03:57:36 brouard
863: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
864:
865: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
866:
1.142 brouard 867: Revision 1.141 2014/01/26 02:42:01 brouard
868: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
869:
1.141 brouard 870: Revision 1.140 2011/09/02 10:37:54 brouard
871: Summary: times.h is ok with mingw32 now.
872:
1.140 brouard 873: Revision 1.139 2010/06/14 07:50:17 brouard
874: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
875: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
876:
1.139 brouard 877: Revision 1.138 2010/04/30 18:19:40 brouard
878: *** empty log message ***
879:
1.138 brouard 880: Revision 1.137 2010/04/29 18:11:38 brouard
881: (Module): Checking covariates for more complex models
882: than V1+V2. A lot of change to be done. Unstable.
883:
1.137 brouard 884: Revision 1.136 2010/04/26 20:30:53 brouard
885: (Module): merging some libgsl code. Fixing computation
886: of likelione (using inter/intrapolation if mle = 0) in order to
887: get same likelihood as if mle=1.
888: Some cleaning of code and comments added.
889:
1.136 brouard 890: Revision 1.135 2009/10/29 15:33:14 brouard
891: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
892:
1.135 brouard 893: Revision 1.134 2009/10/29 13:18:53 brouard
894: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
895:
1.134 brouard 896: Revision 1.133 2009/07/06 10:21:25 brouard
897: just nforces
898:
1.133 brouard 899: Revision 1.132 2009/07/06 08:22:05 brouard
900: Many tings
901:
1.132 brouard 902: Revision 1.131 2009/06/20 16:22:47 brouard
903: Some dimensions resccaled
904:
1.131 brouard 905: Revision 1.130 2009/05/26 06:44:34 brouard
906: (Module): Max Covariate is now set to 20 instead of 8. A
907: lot of cleaning with variables initialized to 0. Trying to make
908: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
909:
1.130 brouard 910: Revision 1.129 2007/08/31 13:49:27 lievre
911: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
912:
1.129 lievre 913: Revision 1.128 2006/06/30 13:02:05 brouard
914: (Module): Clarifications on computing e.j
915:
1.128 brouard 916: Revision 1.127 2006/04/28 18:11:50 brouard
917: (Module): Yes the sum of survivors was wrong since
918: imach-114 because nhstepm was no more computed in the age
919: loop. Now we define nhstepma in the age loop.
920: (Module): In order to speed up (in case of numerous covariates) we
921: compute health expectancies (without variances) in a first step
922: and then all the health expectancies with variances or standard
923: deviation (needs data from the Hessian matrices) which slows the
924: computation.
925: In the future we should be able to stop the program is only health
926: expectancies and graph are needed without standard deviations.
927:
1.127 brouard 928: Revision 1.126 2006/04/28 17:23:28 brouard
929: (Module): Yes the sum of survivors was wrong since
930: imach-114 because nhstepm was no more computed in the age
931: loop. Now we define nhstepma in the age loop.
932: Version 0.98h
933:
1.126 brouard 934: Revision 1.125 2006/04/04 15:20:31 lievre
935: Errors in calculation of health expectancies. Age was not initialized.
936: Forecasting file added.
937:
938: Revision 1.124 2006/03/22 17:13:53 lievre
939: Parameters are printed with %lf instead of %f (more numbers after the comma).
940: The log-likelihood is printed in the log file
941:
942: Revision 1.123 2006/03/20 10:52:43 brouard
943: * imach.c (Module): <title> changed, corresponds to .htm file
944: name. <head> headers where missing.
945:
946: * imach.c (Module): Weights can have a decimal point as for
947: English (a comma might work with a correct LC_NUMERIC environment,
948: otherwise the weight is truncated).
949: Modification of warning when the covariates values are not 0 or
950: 1.
951: Version 0.98g
952:
953: Revision 1.122 2006/03/20 09:45:41 brouard
954: (Module): Weights can have a decimal point as for
955: English (a comma might work with a correct LC_NUMERIC environment,
956: otherwise the weight is truncated).
957: Modification of warning when the covariates values are not 0 or
958: 1.
959: Version 0.98g
960:
961: Revision 1.121 2006/03/16 17:45:01 lievre
962: * imach.c (Module): Comments concerning covariates added
963:
964: * imach.c (Module): refinements in the computation of lli if
965: status=-2 in order to have more reliable computation if stepm is
966: not 1 month. Version 0.98f
967:
968: Revision 1.120 2006/03/16 15:10:38 lievre
969: (Module): refinements in the computation of lli if
970: status=-2 in order to have more reliable computation if stepm is
971: not 1 month. Version 0.98f
972:
973: Revision 1.119 2006/03/15 17:42:26 brouard
974: (Module): Bug if status = -2, the loglikelihood was
975: computed as likelihood omitting the logarithm. Version O.98e
976:
977: Revision 1.118 2006/03/14 18:20:07 brouard
978: (Module): varevsij Comments added explaining the second
979: table of variances if popbased=1 .
980: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
981: (Module): Function pstamp added
982: (Module): Version 0.98d
983:
984: Revision 1.117 2006/03/14 17:16:22 brouard
985: (Module): varevsij Comments added explaining the second
986: table of variances if popbased=1 .
987: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
988: (Module): Function pstamp added
989: (Module): Version 0.98d
990:
991: Revision 1.116 2006/03/06 10:29:27 brouard
992: (Module): Variance-covariance wrong links and
993: varian-covariance of ej. is needed (Saito).
994:
995: Revision 1.115 2006/02/27 12:17:45 brouard
996: (Module): One freematrix added in mlikeli! 0.98c
997:
998: Revision 1.114 2006/02/26 12:57:58 brouard
999: (Module): Some improvements in processing parameter
1000: filename with strsep.
1001:
1002: Revision 1.113 2006/02/24 14:20:24 brouard
1003: (Module): Memory leaks checks with valgrind and:
1004: datafile was not closed, some imatrix were not freed and on matrix
1005: allocation too.
1006:
1007: Revision 1.112 2006/01/30 09:55:26 brouard
1008: (Module): Back to gnuplot.exe instead of wgnuplot.exe
1009:
1010: Revision 1.111 2006/01/25 20:38:18 brouard
1011: (Module): Lots of cleaning and bugs added (Gompertz)
1012: (Module): Comments can be added in data file. Missing date values
1013: can be a simple dot '.'.
1014:
1015: Revision 1.110 2006/01/25 00:51:50 brouard
1016: (Module): Lots of cleaning and bugs added (Gompertz)
1017:
1018: Revision 1.109 2006/01/24 19:37:15 brouard
1019: (Module): Comments (lines starting with a #) are allowed in data.
1020:
1021: Revision 1.108 2006/01/19 18:05:42 lievre
1022: Gnuplot problem appeared...
1023: To be fixed
1024:
1025: Revision 1.107 2006/01/19 16:20:37 brouard
1026: Test existence of gnuplot in imach path
1027:
1028: Revision 1.106 2006/01/19 13:24:36 brouard
1029: Some cleaning and links added in html output
1030:
1031: Revision 1.105 2006/01/05 20:23:19 lievre
1032: *** empty log message ***
1033:
1034: Revision 1.104 2005/09/30 16:11:43 lievre
1035: (Module): sump fixed, loop imx fixed, and simplifications.
1036: (Module): If the status is missing at the last wave but we know
1037: that the person is alive, then we can code his/her status as -2
1038: (instead of missing=-1 in earlier versions) and his/her
1039: contributions to the likelihood is 1 - Prob of dying from last
1040: health status (= 1-p13= p11+p12 in the easiest case of somebody in
1041: the healthy state at last known wave). Version is 0.98
1042:
1043: Revision 1.103 2005/09/30 15:54:49 lievre
1044: (Module): sump fixed, loop imx fixed, and simplifications.
1045:
1046: Revision 1.102 2004/09/15 17:31:30 brouard
1047: Add the possibility to read data file including tab characters.
1048:
1049: Revision 1.101 2004/09/15 10:38:38 brouard
1050: Fix on curr_time
1051:
1052: Revision 1.100 2004/07/12 18:29:06 brouard
1053: Add version for Mac OS X. Just define UNIX in Makefile
1054:
1055: Revision 1.99 2004/06/05 08:57:40 brouard
1056: *** empty log message ***
1057:
1058: Revision 1.98 2004/05/16 15:05:56 brouard
1059: New version 0.97 . First attempt to estimate force of mortality
1060: directly from the data i.e. without the need of knowing the health
1061: state at each age, but using a Gompertz model: log u =a + b*age .
1062: This is the basic analysis of mortality and should be done before any
1063: other analysis, in order to test if the mortality estimated from the
1064: cross-longitudinal survey is different from the mortality estimated
1065: from other sources like vital statistic data.
1066:
1067: The same imach parameter file can be used but the option for mle should be -3.
1068:
1.324 brouard 1069: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 1070: former routines in order to include the new code within the former code.
1071:
1072: The output is very simple: only an estimate of the intercept and of
1073: the slope with 95% confident intervals.
1074:
1075: Current limitations:
1076: A) Even if you enter covariates, i.e. with the
1077: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
1078: B) There is no computation of Life Expectancy nor Life Table.
1079:
1080: Revision 1.97 2004/02/20 13:25:42 lievre
1081: Version 0.96d. Population forecasting command line is (temporarily)
1082: suppressed.
1083:
1084: Revision 1.96 2003/07/15 15:38:55 brouard
1085: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
1086: rewritten within the same printf. Workaround: many printfs.
1087:
1088: Revision 1.95 2003/07/08 07:54:34 brouard
1089: * imach.c (Repository):
1090: (Repository): Using imachwizard code to output a more meaningful covariance
1091: matrix (cov(a12,c31) instead of numbers.
1092:
1093: Revision 1.94 2003/06/27 13:00:02 brouard
1094: Just cleaning
1095:
1096: Revision 1.93 2003/06/25 16:33:55 brouard
1097: (Module): On windows (cygwin) function asctime_r doesn't
1098: exist so I changed back to asctime which exists.
1099: (Module): Version 0.96b
1100:
1101: Revision 1.92 2003/06/25 16:30:45 brouard
1102: (Module): On windows (cygwin) function asctime_r doesn't
1103: exist so I changed back to asctime which exists.
1104:
1105: Revision 1.91 2003/06/25 15:30:29 brouard
1106: * imach.c (Repository): Duplicated warning errors corrected.
1107: (Repository): Elapsed time after each iteration is now output. It
1108: helps to forecast when convergence will be reached. Elapsed time
1109: is stamped in powell. We created a new html file for the graphs
1110: concerning matrix of covariance. It has extension -cov.htm.
1111:
1112: Revision 1.90 2003/06/24 12:34:15 brouard
1113: (Module): Some bugs corrected for windows. Also, when
1114: mle=-1 a template is output in file "or"mypar.txt with the design
1115: of the covariance matrix to be input.
1116:
1117: Revision 1.89 2003/06/24 12:30:52 brouard
1118: (Module): Some bugs corrected for windows. Also, when
1119: mle=-1 a template is output in file "or"mypar.txt with the design
1120: of the covariance matrix to be input.
1121:
1122: Revision 1.88 2003/06/23 17:54:56 brouard
1123: * 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.
1124:
1125: Revision 1.87 2003/06/18 12:26:01 brouard
1126: Version 0.96
1127:
1128: Revision 1.86 2003/06/17 20:04:08 brouard
1129: (Module): Change position of html and gnuplot routines and added
1130: routine fileappend.
1131:
1132: Revision 1.85 2003/06/17 13:12:43 brouard
1133: * imach.c (Repository): Check when date of death was earlier that
1134: current date of interview. It may happen when the death was just
1135: prior to the death. In this case, dh was negative and likelihood
1136: was wrong (infinity). We still send an "Error" but patch by
1137: assuming that the date of death was just one stepm after the
1138: interview.
1139: (Repository): Because some people have very long ID (first column)
1140: we changed int to long in num[] and we added a new lvector for
1141: memory allocation. But we also truncated to 8 characters (left
1142: truncation)
1143: (Repository): No more line truncation errors.
1144:
1145: Revision 1.84 2003/06/13 21:44:43 brouard
1146: * imach.c (Repository): Replace "freqsummary" at a correct
1147: place. It differs from routine "prevalence" which may be called
1148: many times. Probs is memory consuming and must be used with
1149: parcimony.
1150: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
1151:
1152: Revision 1.83 2003/06/10 13:39:11 lievre
1153: *** empty log message ***
1154:
1155: Revision 1.82 2003/06/05 15:57:20 brouard
1156: Add log in imach.c and fullversion number is now printed.
1157:
1158: */
1159: /*
1160: Interpolated Markov Chain
1161:
1162: Short summary of the programme:
1163:
1.227 brouard 1164: This program computes Healthy Life Expectancies or State-specific
1165: (if states aren't health statuses) Expectancies from
1166: cross-longitudinal data. Cross-longitudinal data consist in:
1167:
1168: -1- a first survey ("cross") where individuals from different ages
1169: are interviewed on their health status or degree of disability (in
1170: the case of a health survey which is our main interest)
1171:
1172: -2- at least a second wave of interviews ("longitudinal") which
1173: measure each change (if any) in individual health status. Health
1174: expectancies are computed from the time spent in each health state
1175: according to a model. More health states you consider, more time is
1176: necessary to reach the Maximum Likelihood of the parameters involved
1177: in the model. The simplest model is the multinomial logistic model
1178: where pij is the probability to be observed in state j at the second
1179: wave conditional to be observed in state i at the first
1180: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
1181: etc , where 'age' is age and 'sex' is a covariate. If you want to
1182: have a more complex model than "constant and age", you should modify
1183: the program where the markup *Covariates have to be included here
1184: again* invites you to do it. More covariates you add, slower the
1.126 brouard 1185: convergence.
1186:
1187: The advantage of this computer programme, compared to a simple
1188: multinomial logistic model, is clear when the delay between waves is not
1189: identical for each individual. Also, if a individual missed an
1190: intermediate interview, the information is lost, but taken into
1191: account using an interpolation or extrapolation.
1192:
1193: hPijx is the probability to be observed in state i at age x+h
1194: conditional to the observed state i at age x. The delay 'h' can be
1195: split into an exact number (nh*stepm) of unobserved intermediate
1196: states. This elementary transition (by month, quarter,
1197: semester or year) is modelled as a multinomial logistic. The hPx
1198: matrix is simply the matrix product of nh*stepm elementary matrices
1199: and the contribution of each individual to the likelihood is simply
1200: hPijx.
1201:
1202: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 1203: of the life expectancies. It also computes the period (stable) prevalence.
1204:
1205: Back prevalence and projections:
1.227 brouard 1206:
1207: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
1208: double agemaxpar, double ftolpl, int *ncvyearp, double
1209: dateprev1,double dateprev2, int firstpass, int lastpass, int
1210: mobilavproj)
1211:
1212: Computes the back prevalence limit for any combination of
1213: covariate values k at any age between ageminpar and agemaxpar and
1214: returns it in **bprlim. In the loops,
1215:
1216: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
1217: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
1218:
1219: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 1220: Computes for any combination of covariates k and any age between bage and fage
1221: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
1222: oldm=oldms;savm=savms;
1.227 brouard 1223:
1.267 brouard 1224: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 1225: Computes the transition matrix starting at age 'age' over
1226: 'nhstepm*hstepm*stepm' months (i.e. until
1227: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 1228: nhstepm*hstepm matrices.
1229:
1230: Returns p3mat[i][j][h] after calling
1231: p3mat[i][j][h]=matprod2(newm,
1232: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
1233: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
1234: oldm);
1.226 brouard 1235:
1236: Important routines
1237:
1238: - func (or funcone), computes logit (pij) distinguishing
1239: o fixed variables (single or product dummies or quantitative);
1240: o varying variables by:
1241: (1) wave (single, product dummies, quantitative),
1242: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
1243: % fixed dummy (treated) or quantitative (not done because time-consuming);
1244: % varying dummy (not done) or quantitative (not done);
1245: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
1246: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
1247: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
1.325 brouard 1248: o There are 2**cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
1.226 brouard 1249: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 1250:
1.226 brouard 1251:
1252:
1.324 brouard 1253: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
1254: Institut national d'études démographiques, Paris.
1.126 brouard 1255: This software have been partly granted by Euro-REVES, a concerted action
1256: from the European Union.
1257: It is copyrighted identically to a GNU software product, ie programme and
1258: software can be distributed freely for non commercial use. Latest version
1259: can be accessed at http://euroreves.ined.fr/imach .
1260:
1261: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
1262: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
1263:
1264: **********************************************************************/
1265: /*
1266: main
1267: read parameterfile
1268: read datafile
1269: concatwav
1270: freqsummary
1271: if (mle >= 1)
1272: mlikeli
1273: print results files
1274: if mle==1
1275: computes hessian
1276: read end of parameter file: agemin, agemax, bage, fage, estepm
1277: begin-prev-date,...
1278: open gnuplot file
1279: open html file
1.145 brouard 1280: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
1281: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
1282: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
1283: freexexit2 possible for memory heap.
1284:
1285: h Pij x | pij_nom ficrestpij
1286: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
1287: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
1288: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
1289:
1290: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
1291: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
1292: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
1293: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
1294: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
1295:
1.126 brouard 1296: forecasting if prevfcast==1 prevforecast call prevalence()
1297: health expectancies
1298: Variance-covariance of DFLE
1299: prevalence()
1300: movingaverage()
1301: varevsij()
1302: if popbased==1 varevsij(,popbased)
1303: total life expectancies
1304: Variance of period (stable) prevalence
1305: end
1306: */
1307:
1.187 brouard 1308: /* #define DEBUG */
1309: /* #define DEBUGBRENT */
1.203 brouard 1310: /* #define DEBUGLINMIN */
1311: /* #define DEBUGHESS */
1312: #define DEBUGHESSIJ
1.224 brouard 1313: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 1314: #define POWELL /* Instead of NLOPT */
1.224 brouard 1315: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 1316: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
1317: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.319 brouard 1318: /* #define FLATSUP *//* Suppresses directions where likelihood is flat */
1.359 brouard 1319: /* #define POWELLORIGINCONJUGATE /\* Don't use conjugate but biggest decrease if valuable *\/ */
1320: /* #define NOTMINFIT */
1.126 brouard 1321:
1322: #include <math.h>
1323: #include <stdio.h>
1324: #include <stdlib.h>
1325: #include <string.h>
1.226 brouard 1326: #include <ctype.h>
1.159 brouard 1327:
1328: #ifdef _WIN32
1329: #include <io.h>
1.172 brouard 1330: #include <windows.h>
1331: #include <tchar.h>
1.159 brouard 1332: #else
1.126 brouard 1333: #include <unistd.h>
1.159 brouard 1334: #endif
1.126 brouard 1335:
1336: #include <limits.h>
1337: #include <sys/types.h>
1.171 brouard 1338:
1339: #if defined(__GNUC__)
1340: #include <sys/utsname.h> /* Doesn't work on Windows */
1341: #endif
1342:
1.126 brouard 1343: #include <sys/stat.h>
1344: #include <errno.h>
1.159 brouard 1345: /* extern int errno; */
1.126 brouard 1346:
1.157 brouard 1347: /* #ifdef LINUX */
1348: /* #include <time.h> */
1349: /* #include "timeval.h" */
1350: /* #else */
1351: /* #include <sys/time.h> */
1352: /* #endif */
1353:
1.126 brouard 1354: #include <time.h>
1355:
1.136 brouard 1356: #ifdef GSL
1357: #include <gsl/gsl_errno.h>
1358: #include <gsl/gsl_multimin.h>
1359: #endif
1360:
1.167 brouard 1361:
1.162 brouard 1362: #ifdef NLOPT
1363: #include <nlopt.h>
1364: typedef struct {
1365: double (* function)(double [] );
1366: } myfunc_data ;
1367: #endif
1368:
1.126 brouard 1369: /* #include <libintl.h> */
1370: /* #define _(String) gettext (String) */
1371:
1.349 brouard 1372: #define MAXLINE 16384 /* Was 256 and 1024 and 2048. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1373:
1374: #define GNUPLOTPROGRAM "gnuplot"
1.343 brouard 1375: #define GNUPLOTVERSION 5.1
1376: double gnuplotversion=GNUPLOTVERSION;
1.126 brouard 1377: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1.329 brouard 1378: #define FILENAMELENGTH 256
1.126 brouard 1379:
1380: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1381: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1382:
1.349 brouard 1383: #define MAXPARM 216 /**< Maximum number of parameters for the optimization was 128 */
1.144 brouard 1384: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1385:
1386: #define NINTERVMAX 8
1.144 brouard 1387: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1388: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.325 brouard 1389: #define NCOVMAX 30 /**< Maximum number of covariates used in the model, including generated covariates V1*V2 or V1*age */
1.197 brouard 1390: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1391: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1392: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1393: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1394: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1395: /* #define AGESUP 130 */
1.288 brouard 1396: /* #define AGESUP 150 */
1397: #define AGESUP 200
1.268 brouard 1398: #define AGEINF 0
1.218 brouard 1399: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1400: #define AGEBASE 40
1.194 brouard 1401: #define AGEOVERFLOW 1.e20
1.164 brouard 1402: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1403: #ifdef _WIN32
1404: #define DIRSEPARATOR '\\'
1405: #define CHARSEPARATOR "\\"
1406: #define ODIRSEPARATOR '/'
1407: #else
1.126 brouard 1408: #define DIRSEPARATOR '/'
1409: #define CHARSEPARATOR "/"
1410: #define ODIRSEPARATOR '\\'
1411: #endif
1412:
1.363 ! brouard 1413: /* $Id: imach.c,v 1.362 2024/06/28 08:00:31 brouard Exp $ */
1.126 brouard 1414: /* $State: Exp $ */
1.196 brouard 1415: #include "version.h"
1416: char version[]=__IMACH_VERSION__;
1.360 brouard 1417: 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";
1.363 ! brouard 1418: char fullversion[]="$Revision: 1.362 $ $Date: 2024/06/28 08:00:31 $";
1.126 brouard 1419: char strstart[80];
1420: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1421: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.342 brouard 1422: int debugILK=0; /* debugILK is set by a #d in a comment line */
1.187 brouard 1423: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.330 brouard 1424: /* Number of covariates model (1)=V2+V1+ V3*age+V2*V4 */
1425: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
1.335 brouard 1426: 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 1427: 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 1428: int cptcovs=0; /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
1429: int cptcovsnq=0; /**< cptcovsnq number of SIMPLE covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1430: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1.349 brouard 1431: int cptcovprodage=0; /**< Number of fixed covariates with age: V3*age or V2*V3*age 1 */
1432: int cptcovprodvage=0; /**< Number of varying covariates with age: V7*age or V7*V6*age */
1433: int cptcovdageprod=0; /**< Number of doubleproducts with age, since 0.99r44 only: age*Vn*Vm for gnuplot printing*/
1.145 brouard 1434: int cptcovprodnoage=0; /**< Number of covariate products without age */
1.335 brouard 1435: 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 1436: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1437: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.339 brouard 1438: int ncovvt=0; /* Total number of effective (wave) varying covariates (dummy or quantitative or products [without age]) in the model */
1.349 brouard 1439: 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 */
1440: 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 */
1441: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (single or product, dummy or quantitative) in the model */
1442: 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 1443: int nsd=0; /**< Total number of single dummy variables (output) */
1444: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1445: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1446: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1447: int ntveff=0; /**< ntveff number of effective time varying variables */
1448: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1449: int cptcov=0; /* Working variable */
1.334 brouard 1450: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs+1 declared globally ;*/
1.290 brouard 1451: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1452: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.302 brouard 1453: int npar=NPARMAX; /* Number of parameters (nlstate+ndeath-1)*nlstate*ncovmodel; */
1.126 brouard 1454: int nlstate=2; /* Number of live states */
1455: int ndeath=1; /* Number of dead states */
1.130 brouard 1456: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.339 brouard 1457: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable*/
1458: int ncovcolt=0; /* ncovcolt=ncovcol+nqv+ntv+nqtv; total of covariates in the data, not in the model equation*/
1.126 brouard 1459: int popbased=0;
1460:
1461: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1462: int maxwav=0; /* Maxim number of waves */
1463: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1464: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1.359 brouard 1465: int gipmx = 0;
1466: double gsw = 0; /* Global variables on the number of contributions
1.126 brouard 1467: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1468: int mle=1, weightopt=0;
1.126 brouard 1469: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1470: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1471: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1472: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1473: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1474: int selected(int kvar); /* Is covariate kvar selected for printing results */
1475:
1.130 brouard 1476: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1477: double **matprod2(); /* test */
1.126 brouard 1478: double **oldm, **newm, **savm; /* Working pointers to matrices */
1479: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1480: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1481:
1.136 brouard 1482: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1483: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1484: FILE *ficlog, *ficrespow;
1.130 brouard 1485: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1486: double fretone; /* Only one call to likelihood */
1.130 brouard 1487: long ipmx=0; /* Number of contributions */
1.126 brouard 1488: double sw; /* Sum of weights */
1489: char filerespow[FILENAMELENGTH];
1490: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1491: FILE *ficresilk;
1492: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1493: FILE *ficresprobmorprev;
1494: FILE *fichtm, *fichtmcov; /* Html File */
1495: FILE *ficreseij;
1496: char filerese[FILENAMELENGTH];
1497: FILE *ficresstdeij;
1498: char fileresstde[FILENAMELENGTH];
1499: FILE *ficrescveij;
1500: char filerescve[FILENAMELENGTH];
1501: FILE *ficresvij;
1502: char fileresv[FILENAMELENGTH];
1.269 brouard 1503:
1.126 brouard 1504: char title[MAXLINE];
1.234 brouard 1505: char model[MAXLINE]; /**< The model line */
1.217 brouard 1506: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1507: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1508: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1509: char command[FILENAMELENGTH];
1510: int outcmd=0;
1511:
1.217 brouard 1512: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1513: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1514: char filelog[FILENAMELENGTH]; /* Log file */
1515: char filerest[FILENAMELENGTH];
1516: char fileregp[FILENAMELENGTH];
1517: char popfile[FILENAMELENGTH];
1518:
1519: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1520:
1.157 brouard 1521: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1522: /* struct timezone tzp; */
1523: /* extern int gettimeofday(); */
1524: struct tm tml, *gmtime(), *localtime();
1525:
1526: extern time_t time();
1527:
1528: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1529: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1.349 brouard 1530: time_t rlast_btime; /* raw time */
1.157 brouard 1531: struct tm tm;
1532:
1.126 brouard 1533: char strcurr[80], strfor[80];
1534:
1535: char *endptr;
1536: long lval;
1537: double dval;
1538:
1.362 brouard 1539: /* This for praxis gegen */
1540: /* int prin=1; */
1541: double h0=0.25;
1542: double macheps;
1543: double ffmin;
1544:
1.126 brouard 1545: #define NR_END 1
1546: #define FREE_ARG char*
1547: #define FTOL 1.0e-10
1548:
1549: #define NRANSI
1.240 brouard 1550: #define ITMAX 200
1551: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1552:
1553: #define TOL 2.0e-4
1554:
1555: #define CGOLD 0.3819660
1556: #define ZEPS 1.0e-10
1557: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1558:
1559: #define GOLD 1.618034
1560: #define GLIMIT 100.0
1561: #define TINY 1.0e-20
1562:
1563: static double maxarg1,maxarg2;
1564: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1565: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1566:
1567: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1568: #define rint(a) floor(a+0.5)
1.166 brouard 1569: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1570: #define mytinydouble 1.0e-16
1.166 brouard 1571: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1572: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1573: /* static double dsqrarg; */
1574: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1575: static double sqrarg;
1576: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1577: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1578: int agegomp= AGEGOMP;
1579:
1580: int imx;
1581: int stepm=1;
1582: /* Stepm, step in month: minimum step interpolation*/
1583:
1584: int estepm;
1585: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1586:
1587: int m,nb;
1588: long *num;
1.197 brouard 1589: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1590: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1591: covariate for which somebody answered excluding
1592: undefined. Usually 2: 0 and 1. */
1593: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1594: covariate for which somebody answered including
1595: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1596: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1597: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1598: double ***mobaverage, ***mobaverages; /* New global variable */
1.332 brouard 1599: 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 1600: double *ageexmed,*agecens;
1601: double dateintmean=0;
1.296 brouard 1602: double anprojd, mprojd, jprojd; /* For eventual projections */
1603: double anprojf, mprojf, jprojf;
1.126 brouard 1604:
1.296 brouard 1605: double anbackd, mbackd, jbackd; /* For eventual backprojections */
1606: double anbackf, mbackf, jbackf;
1607: double jintmean,mintmean,aintmean;
1.126 brouard 1608: double *weight;
1609: int **s; /* Status */
1.141 brouard 1610: double *agedc;
1.145 brouard 1611: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1612: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1613: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1614: double **coqvar; /* Fixed quantitative covariate nqv */
1.341 brouard 1615: double ***cotvar; /* Time varying covariate start at ncovcol + nqv + (1 to ntv) */
1.225 brouard 1616: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1617: double idx;
1618: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.319 brouard 1619: /* Some documentation */
1620: /* Design original data
1621: * V1 V2 V3 V4 V5 V6 V7 V8 Weight ddb ddth d1st s1 V9 V10 V11 V12 s2 V9 V10 V11 V12
1622: * < ncovcol=6 > nqv=2 (V7 V8) dv dv dv qtv dv dv dvv qtv
1623: * ntv=3 nqtv=1
1.330 brouard 1624: * cptcovn number of covariates (not including constant and age or age*age) = number of plus sign + 1 = 10+1=11
1.319 brouard 1625: * For time varying covariate, quanti or dummies
1626: * cotqvar[wav][iv(1 to nqtv)][i]= [1][12][i]=(V12) quanti
1.341 brouard 1627: * cotvar[wav][ncovcol+nqv+ iv(1 to nqtv)][i]= [(1 to nqtv)][i]=(V12) quanti
1.319 brouard 1628: * cotvar[wav][iv(1 to ntv)][i]= [1][1][i]=(V9) dummies at wav 1
1629: * cotvar[wav][iv(1 to ntv)][i]= [1][2][i]=(V10) dummies at wav 1
1.332 brouard 1630: * covar[Vk,i], value of the Vkth fixed covariate dummy or quanti for individual i:
1.319 brouard 1631: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
1632: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 + V9 + V9*age + V10
1633: * k= 1 2 3 4 5 6 7 8 9 10 11
1634: */
1635: /* According to the model, more columns can be added to covar by the product of covariates */
1.318 brouard 1636: /* 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
1637: # States 1=Coresidence, 2 Living alone, 3 Institution
1638: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1639: */
1.349 brouard 1640: /* V5+V4+ V3+V4*V3 +V5*age+V2 +V1*V2+V1*age+V1+V4*V3*age */
1641: /* kmodel 1 2 3 4 5 6 7 8 9 10 */
1642: /*Typevar[k]= 0 0 0 2 1 0 2 1 0 3 *//*0 for simple covariate (dummy, quantitative,*/
1643: /* fixed or varying), 1 for age product, 2 for*/
1644: /* product without age, 3 for age and double product */
1645: /*Dummy[k]= 1 0 0 1 3 1 1 2 0 3 *//*Dummy[k] 0=dummy (0 1), 1 quantitative */
1646: /*(single or product without age), 2 dummy*/
1647: /* with age product, 3 quant with age product*/
1648: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 6 */
1649: /* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */
1650: /*TnsdVar[Tvar] 1 2 3 */
1651: /*Tvaraff[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1652: /*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1653: /*TvarsDind[nsd] 2 3 9 */ /* position K of single dummy cova */
1654: /* nsq 1 2 */ /* Counting single quantit tv */
1655: /* TvarsQ[k] 5 2 */ /* Number of single quantitative cova */
1656: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1657: /* Tprod[i]=k 1 2 */ /* Position in model of the ith prod without age */
1658: /* cptcovage 1 2 3 */ /* Counting cov*age in the model equation */
1659: /* Tage[cptcovage]=k 5 8 10 */ /* Position in the model of ith cov*age */
1.350 brouard 1660: /* 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"*/
1661: /* 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 1662: /* p Tvard[2][1]@21 = {7, 2, 6, 3, 7, 3, 6, 4, 7, 4, 0 <repeats 11 times>} */
1.350 brouard 1663: /* 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}*/
1664: /* 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 1665: /* Tvard[1][1]@4={4,3,1,2} V4*V3 V1*V2 */ /* Position in model of the ith prod without age */
1.330 brouard 1666: /* 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 1667: /* 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 1668: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.234 brouard 1669: /* Type */
1670: /* V 1 2 3 4 5 */
1671: /* F F V V V */
1672: /* D Q D D Q */
1673: /* */
1674: int *TvarsD;
1.330 brouard 1675: int *TnsdVar;
1.234 brouard 1676: int *TvarsDind;
1677: int *TvarsQ;
1678: int *TvarsQind;
1679:
1.318 brouard 1680: #define MAXRESULTLINESPONE 10+1
1.235 brouard 1681: int nresult=0;
1.258 brouard 1682: int parameterline=0; /* # of the parameter (type) line */
1.334 brouard 1683: int TKresult[MAXRESULTLINESPONE]; /* TKresult[nres]=k for each resultline nres give the corresponding combination of dummies */
1684: int resultmodel[MAXRESULTLINESPONE][NCOVMAX];/* resultmodel[k1]=k3: k1th position in the model corresponds to the k3 position in the resultline */
1685: int modelresult[MAXRESULTLINESPONE][NCOVMAX];/* modelresult[k3]=k1: k1th position in the model corresponds to the k3 position in the resultline */
1686: int Tresult[MAXRESULTLINESPONE][NCOVMAX];/* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1687: int Tinvresult[MAXRESULTLINESPONE][NCOVMAX];/* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1688: double TinvDoQresult[MAXRESULTLINESPONE][NCOVMAX];/* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.334 brouard 1689: int Tvresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1690: double Tqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.318 brouard 1691: double Tqinvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
1.332 brouard 1692: int Tvqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.318 brouard 1693:
1694: /* 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
1695: # States 1=Coresidence, 2 Living alone, 3 Institution
1696: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1697: */
1.234 brouard 1698: /* 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 1699: 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 */
1700: 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 */
1701: 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 */
1702: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1703: 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 */
1704: 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 1705: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1706: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1707: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1708: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1709: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1710: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1711: 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 */
1712: 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 1713: int *TvarVV; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1714: int *TvarVVind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1.349 brouard 1715: int *TvarVVA; /* We count ncovvt time varying covariates (single or products with age) and put their name into TvarVVA */
1716: int *TvarVVAind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1717: int *TvarAVVA; /* We count ALL ncovta time varying covariates (single or products with age) and put their name into TvarVVA */
1718: int *TvarAVVAind; /* We count ALL ncovta time varying covariates (single or products without age) and put their name into TvarVV */
1.339 brouard 1719: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
1.349 brouard 1720: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age */
1721: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
1722: /* TvarVV={3,1,3,1,3}, for V3 and then the product V1*V3 is decomposed into V1 and V3 */
1723: /* 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 1724: int *Tvarsel; /**< Selected covariates for output */
1725: double *Tvalsel; /**< Selected modality value of covariate for output */
1.349 brouard 1726: 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 1727: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1728: 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 1729: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1730: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1731: int *Tage;
1.227 brouard 1732: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1733: 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 1734: 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*/
1735: 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 1736: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1737: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1738: int **Tvard;
1.330 brouard 1739: int **Tvardk;
1.227 brouard 1740: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1741: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1742: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1743: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1744: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1745: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1746: double *lsurv, *lpop, *tpop;
1747:
1.231 brouard 1748: #define FD 1; /* Fixed dummy covariate */
1749: #define FQ 2; /* Fixed quantitative covariate */
1750: #define FP 3; /* Fixed product covariate */
1751: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1752: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1753: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1754: #define VD 10; /* Varying dummy covariate */
1755: #define VQ 11; /* Varying quantitative covariate */
1756: #define VP 12; /* Varying product covariate */
1757: #define VPDD 13; /* Varying product dummy*dummy covariate */
1758: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1759: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1760: #define APFD 16; /* Age product * fixed dummy covariate */
1761: #define APFQ 17; /* Age product * fixed quantitative covariate */
1762: #define APVD 18; /* Age product * varying dummy covariate */
1763: #define APVQ 19; /* Age product * varying quantitative covariate */
1764:
1765: #define FTYPE 1; /* Fixed covariate */
1766: #define VTYPE 2; /* Varying covariate (loop in wave) */
1767: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1768:
1769: struct kmodel{
1770: int maintype; /* main type */
1771: int subtype; /* subtype */
1772: };
1773: struct kmodel modell[NCOVMAX];
1774:
1.143 brouard 1775: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1776: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1777:
1778: /**************** split *************************/
1779: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1780: {
1781: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1782: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1783: */
1784: char *ss; /* pointer */
1.186 brouard 1785: int l1=0, l2=0; /* length counters */
1.126 brouard 1786:
1787: l1 = strlen(path ); /* length of path */
1788: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1789: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1790: if ( ss == NULL ) { /* no directory, so determine current directory */
1791: strcpy( name, path ); /* we got the fullname name because no directory */
1792: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1793: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1794: /* get current working directory */
1795: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1796: #ifdef WIN32
1797: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1798: #else
1799: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1800: #endif
1.126 brouard 1801: return( GLOCK_ERROR_GETCWD );
1802: }
1803: /* got dirc from getcwd*/
1804: printf(" DIRC = %s \n",dirc);
1.205 brouard 1805: } else { /* strip directory from path */
1.126 brouard 1806: ss++; /* after this, the filename */
1807: l2 = strlen( ss ); /* length of filename */
1808: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1809: strcpy( name, ss ); /* save file name */
1810: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1811: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1812: printf(" DIRC2 = %s \n",dirc);
1813: }
1814: /* We add a separator at the end of dirc if not exists */
1815: l1 = strlen( dirc ); /* length of directory */
1816: if( dirc[l1-1] != DIRSEPARATOR ){
1817: dirc[l1] = DIRSEPARATOR;
1818: dirc[l1+1] = 0;
1819: printf(" DIRC3 = %s \n",dirc);
1820: }
1821: ss = strrchr( name, '.' ); /* find last / */
1822: if (ss >0){
1823: ss++;
1824: strcpy(ext,ss); /* save extension */
1825: l1= strlen( name);
1826: l2= strlen(ss)+1;
1827: strncpy( finame, name, l1-l2);
1828: finame[l1-l2]= 0;
1829: }
1830:
1831: return( 0 ); /* we're done */
1832: }
1833:
1834:
1835: /******************************************/
1836:
1837: void replace_back_to_slash(char *s, char*t)
1838: {
1839: int i;
1840: int lg=0;
1841: i=0;
1842: lg=strlen(t);
1843: for(i=0; i<= lg; i++) {
1844: (s[i] = t[i]);
1845: if (t[i]== '\\') s[i]='/';
1846: }
1847: }
1848:
1.132 brouard 1849: char *trimbb(char *out, char *in)
1.137 brouard 1850: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1851: char *s;
1852: s=out;
1853: while (*in != '\0'){
1.137 brouard 1854: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1855: in++;
1856: }
1857: *out++ = *in++;
1858: }
1859: *out='\0';
1860: return s;
1861: }
1862:
1.351 brouard 1863: char *trimbtab(char *out, char *in)
1864: { /* Trim blanks or tabs in line but keeps first blanks if line starts with blanks */
1865: char *s;
1866: s=out;
1867: while (*in != '\0'){
1868: while( (*in == ' ' || *in == '\t')){ /* && *(in+1) != '\0'){*/
1869: in++;
1870: }
1871: *out++ = *in++;
1872: }
1873: *out='\0';
1874: return s;
1875: }
1876:
1.187 brouard 1877: /* char *substrchaine(char *out, char *in, char *chain) */
1878: /* { */
1879: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1880: /* char *s, *t; */
1881: /* t=in;s=out; */
1882: /* while ((*in != *chain) && (*in != '\0')){ */
1883: /* *out++ = *in++; */
1884: /* } */
1885:
1886: /* /\* *in matches *chain *\/ */
1887: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1888: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1889: /* } */
1890: /* in--; chain--; */
1891: /* while ( (*in != '\0')){ */
1892: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1893: /* *out++ = *in++; */
1894: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1895: /* } */
1896: /* *out='\0'; */
1897: /* out=s; */
1898: /* return out; */
1899: /* } */
1900: char *substrchaine(char *out, char *in, char *chain)
1901: {
1902: /* Substract chain 'chain' from 'in', return and output 'out' */
1.349 brouard 1903: /* in="V1+V1*age+age*age+V2", chain="+age*age" out="V1+V1*age+V2" */
1.187 brouard 1904:
1905: char *strloc;
1906:
1.349 brouard 1907: strcpy (out, in); /* out="V1+V1*age+age*age+V2" */
1908: strloc = strstr(out, chain); /* strloc points to out at "+age*age+V2" */
1909: 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 1910: if(strloc != NULL){
1.349 brouard 1911: /* will affect out */ /* strloc+strlen(chain)=|+V2 = "V1+V1*age+age*age|+V2" */ /* Will also work in Unicodek */
1912: 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)*/
1913: /* equivalent to strcpy (strloc, strloc +strlen(chain)) if no overlap; Copies from "+V2" to V1+V1*age+ */
1.187 brouard 1914: }
1.349 brouard 1915: 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 1916: return out;
1917: }
1918:
1919:
1.145 brouard 1920: char *cutl(char *blocc, char *alocc, char *in, char occ)
1921: {
1.187 brouard 1922: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.349 brouard 1923: and alocc starts after first occurence of char 'occ' : ex cutl(blocc,alocc,"abcdef2ghi2j",'2')
1.310 brouard 1924: gives alocc="abcdef" and blocc="ghi2j".
1.145 brouard 1925: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1926: */
1.160 brouard 1927: char *s, *t;
1.145 brouard 1928: t=in;s=in;
1929: while ((*in != occ) && (*in != '\0')){
1930: *alocc++ = *in++;
1931: }
1932: if( *in == occ){
1933: *(alocc)='\0';
1934: s=++in;
1935: }
1936:
1937: if (s == t) {/* occ not found */
1938: *(alocc-(in-s))='\0';
1939: in=s;
1940: }
1941: while ( *in != '\0'){
1942: *blocc++ = *in++;
1943: }
1944:
1945: *blocc='\0';
1946: return t;
1947: }
1.137 brouard 1948: char *cutv(char *blocc, char *alocc, char *in, char occ)
1949: {
1.187 brouard 1950: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1951: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1952: gives blocc="abcdef2ghi" and alocc="j".
1953: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1954: */
1955: char *s, *t;
1956: t=in;s=in;
1957: while (*in != '\0'){
1958: while( *in == occ){
1959: *blocc++ = *in++;
1960: s=in;
1961: }
1962: *blocc++ = *in++;
1963: }
1964: if (s == t) /* occ not found */
1965: *(blocc-(in-s))='\0';
1966: else
1967: *(blocc-(in-s)-1)='\0';
1968: in=s;
1969: while ( *in != '\0'){
1970: *alocc++ = *in++;
1971: }
1972:
1973: *alocc='\0';
1974: return s;
1975: }
1976:
1.126 brouard 1977: int nbocc(char *s, char occ)
1978: {
1979: int i,j=0;
1980: int lg=20;
1981: i=0;
1982: lg=strlen(s);
1983: for(i=0; i<= lg; i++) {
1.234 brouard 1984: if (s[i] == occ ) j++;
1.126 brouard 1985: }
1986: return j;
1987: }
1988:
1.349 brouard 1989: int nboccstr(char *textin, char *chain)
1990: {
1991: /* Counts the number of occurence of "chain" in string textin */
1992: /* in="+V7*V4+age*V2+age*V3+age*V4" chain="age" */
1993: char *strloc;
1994:
1995: int i,j=0;
1996:
1997: i=0;
1998:
1999: strloc=textin; /* strloc points to "^+V7*V4+age+..." in textin */
2000: for(;;) {
2001: strloc= strstr(strloc,chain); /* strloc points to first character of chain in textin if found. Example strloc points^ to "+V7*V4+^age" in textin */
2002: if(strloc != NULL){
2003: strloc = strloc+strlen(chain); /* strloc points to "+V7*V4+age^" in textin */
2004: j++;
2005: }else
2006: break;
2007: }
2008: return j;
2009:
2010: }
1.137 brouard 2011: /* void cutv(char *u,char *v, char*t, char occ) */
2012: /* { */
2013: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
2014: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
2015: /* gives u="abcdef2ghi" and v="j" *\/ */
2016: /* int i,lg,j,p=0; */
2017: /* i=0; */
2018: /* lg=strlen(t); */
2019: /* for(j=0; j<=lg-1; j++) { */
2020: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
2021: /* } */
1.126 brouard 2022:
1.137 brouard 2023: /* for(j=0; j<p; j++) { */
2024: /* (u[j] = t[j]); */
2025: /* } */
2026: /* u[p]='\0'; */
1.126 brouard 2027:
1.137 brouard 2028: /* for(j=0; j<= lg; j++) { */
2029: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
2030: /* } */
2031: /* } */
1.126 brouard 2032:
1.160 brouard 2033: #ifdef _WIN32
2034: char * strsep(char **pp, const char *delim)
2035: {
2036: char *p, *q;
2037:
2038: if ((p = *pp) == NULL)
2039: return 0;
2040: if ((q = strpbrk (p, delim)) != NULL)
2041: {
2042: *pp = q + 1;
2043: *q = '\0';
2044: }
2045: else
2046: *pp = 0;
2047: return p;
2048: }
2049: #endif
2050:
1.126 brouard 2051: /********************** nrerror ********************/
2052:
2053: void nrerror(char error_text[])
2054: {
2055: fprintf(stderr,"ERREUR ...\n");
2056: fprintf(stderr,"%s\n",error_text);
2057: exit(EXIT_FAILURE);
2058: }
2059: /*********************** vector *******************/
2060: double *vector(int nl, int nh)
2061: {
2062: double *v;
2063: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
2064: if (!v) nrerror("allocation failure in vector");
2065: return v-nl+NR_END;
2066: }
2067:
2068: /************************ free vector ******************/
2069: void free_vector(double*v, int nl, int nh)
2070: {
2071: free((FREE_ARG)(v+nl-NR_END));
2072: }
2073:
2074: /************************ivector *******************************/
2075: int *ivector(long nl,long nh)
2076: {
2077: int *v;
2078: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
2079: if (!v) nrerror("allocation failure in ivector");
2080: return v-nl+NR_END;
2081: }
2082:
2083: /******************free ivector **************************/
2084: void free_ivector(int *v, long nl, long nh)
2085: {
2086: free((FREE_ARG)(v+nl-NR_END));
2087: }
2088:
2089: /************************lvector *******************************/
2090: long *lvector(long nl,long nh)
2091: {
2092: long *v;
2093: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
2094: if (!v) nrerror("allocation failure in ivector");
2095: return v-nl+NR_END;
2096: }
2097:
2098: /******************free lvector **************************/
2099: void free_lvector(long *v, long nl, long nh)
2100: {
2101: free((FREE_ARG)(v+nl-NR_END));
2102: }
2103:
2104: /******************* imatrix *******************************/
2105: int **imatrix(long nrl, long nrh, long ncl, long nch)
2106: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
2107: {
2108: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
2109: int **m;
2110:
2111: /* allocate pointers to rows */
2112: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
2113: if (!m) nrerror("allocation failure 1 in matrix()");
2114: m += NR_END;
2115: m -= nrl;
2116:
2117:
2118: /* allocate rows and set pointers to them */
2119: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
2120: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2121: m[nrl] += NR_END;
2122: m[nrl] -= ncl;
2123:
2124: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
2125:
2126: /* return pointer to array of pointers to rows */
2127: return m;
2128: }
2129:
2130: /****************** free_imatrix *************************/
2131: void free_imatrix(m,nrl,nrh,ncl,nch)
2132: int **m;
2133: long nch,ncl,nrh,nrl;
2134: /* free an int matrix allocated by imatrix() */
2135: {
2136: free((FREE_ARG) (m[nrl]+ncl-NR_END));
2137: free((FREE_ARG) (m+nrl-NR_END));
2138: }
2139:
2140: /******************* matrix *******************************/
2141: double **matrix(long nrl, long nrh, long ncl, long nch)
2142: {
2143: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
2144: double **m;
2145:
2146: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
2147: if (!m) nrerror("allocation failure 1 in matrix()");
2148: m += NR_END;
2149: m -= nrl;
2150:
2151: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
2152: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2153: m[nrl] += NR_END;
2154: m[nrl] -= ncl;
2155:
2156: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2157: return m;
1.145 brouard 2158: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
2159: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
2160: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 2161: */
2162: }
2163:
2164: /*************************free matrix ************************/
2165: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
2166: {
2167: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2168: free((FREE_ARG)(m+nrl-NR_END));
2169: }
2170:
2171: /******************* ma3x *******************************/
2172: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
2173: {
2174: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
2175: double ***m;
2176:
2177: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
2178: if (!m) nrerror("allocation failure 1 in matrix()");
2179: m += NR_END;
2180: m -= nrl;
2181:
2182: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
2183: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2184: m[nrl] += NR_END;
2185: m[nrl] -= ncl;
2186:
2187: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2188:
2189: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
2190: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
2191: m[nrl][ncl] += NR_END;
2192: m[nrl][ncl] -= nll;
2193: for (j=ncl+1; j<=nch; j++)
2194: m[nrl][j]=m[nrl][j-1]+nlay;
2195:
2196: for (i=nrl+1; i<=nrh; i++) {
2197: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
2198: for (j=ncl+1; j<=nch; j++)
2199: m[i][j]=m[i][j-1]+nlay;
2200: }
2201: return m;
2202: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
2203: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
2204: */
2205: }
2206:
2207: /*************************free ma3x ************************/
2208: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
2209: {
2210: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
2211: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2212: free((FREE_ARG)(m+nrl-NR_END));
2213: }
2214:
2215: /*************** function subdirf ***********/
2216: char *subdirf(char fileres[])
2217: {
2218: /* Caution optionfilefiname is hidden */
2219: strcpy(tmpout,optionfilefiname);
2220: strcat(tmpout,"/"); /* Add to the right */
2221: strcat(tmpout,fileres);
2222: return tmpout;
2223: }
2224:
2225: /*************** function subdirf2 ***********/
2226: char *subdirf2(char fileres[], char *preop)
2227: {
1.314 brouard 2228: /* Example subdirf2(optionfilefiname,"FB_") with optionfilefiname="texte", result="texte/FB_texte"
2229: Errors in subdirf, 2, 3 while printing tmpout is
1.315 brouard 2230: rewritten within the same printf. Workaround: many printfs */
1.126 brouard 2231: /* Caution optionfilefiname is hidden */
2232: strcpy(tmpout,optionfilefiname);
2233: strcat(tmpout,"/");
2234: strcat(tmpout,preop);
2235: strcat(tmpout,fileres);
2236: return tmpout;
2237: }
2238:
2239: /*************** function subdirf3 ***********/
2240: char *subdirf3(char fileres[], char *preop, char *preop2)
2241: {
2242:
2243: /* Caution optionfilefiname is hidden */
2244: strcpy(tmpout,optionfilefiname);
2245: strcat(tmpout,"/");
2246: strcat(tmpout,preop);
2247: strcat(tmpout,preop2);
2248: strcat(tmpout,fileres);
2249: return tmpout;
2250: }
1.213 brouard 2251:
2252: /*************** function subdirfext ***********/
2253: char *subdirfext(char fileres[], char *preop, char *postop)
2254: {
2255:
2256: strcpy(tmpout,preop);
2257: strcat(tmpout,fileres);
2258: strcat(tmpout,postop);
2259: return tmpout;
2260: }
1.126 brouard 2261:
1.213 brouard 2262: /*************** function subdirfext3 ***********/
2263: char *subdirfext3(char fileres[], char *preop, char *postop)
2264: {
2265:
2266: /* Caution optionfilefiname is hidden */
2267: strcpy(tmpout,optionfilefiname);
2268: strcat(tmpout,"/");
2269: strcat(tmpout,preop);
2270: strcat(tmpout,fileres);
2271: strcat(tmpout,postop);
2272: return tmpout;
2273: }
2274:
1.162 brouard 2275: char *asc_diff_time(long time_sec, char ascdiff[])
2276: {
2277: long sec_left, days, hours, minutes;
2278: days = (time_sec) / (60*60*24);
2279: sec_left = (time_sec) % (60*60*24);
2280: hours = (sec_left) / (60*60) ;
2281: sec_left = (sec_left) %(60*60);
2282: minutes = (sec_left) /60;
2283: sec_left = (sec_left) % (60);
2284: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
2285: return ascdiff;
2286: }
2287:
1.126 brouard 2288: /***************** f1dim *************************/
2289: extern int ncom;
2290: extern double *pcom,*xicom;
2291: extern double (*nrfunc)(double []);
2292:
2293: double f1dim(double x)
2294: {
2295: int j;
2296: double f;
2297: double *xt;
2298:
2299: xt=vector(1,ncom);
2300: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
2301: f=(*nrfunc)(xt);
2302: free_vector(xt,1,ncom);
2303: return f;
2304: }
2305:
2306: /*****************brent *************************/
2307: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 2308: {
2309: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
2310: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
2311: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
2312: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
2313: * returned function value.
2314: */
1.126 brouard 2315: int iter;
2316: double a,b,d,etemp;
1.159 brouard 2317: double fu=0,fv,fw,fx;
1.164 brouard 2318: double ftemp=0.;
1.126 brouard 2319: double p,q,r,tol1,tol2,u,v,w,x,xm;
2320: double e=0.0;
2321:
2322: a=(ax < cx ? ax : cx);
2323: b=(ax > cx ? ax : cx);
2324: x=w=v=bx;
2325: fw=fv=fx=(*f)(x);
2326: for (iter=1;iter<=ITMAX;iter++) {
2327: xm=0.5*(a+b);
2328: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
2329: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
2330: printf(".");fflush(stdout);
2331: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 2332: #ifdef DEBUGBRENT
1.126 brouard 2333: 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);
2334: 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);
2335: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
2336: #endif
2337: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
2338: *xmin=x;
2339: return fx;
2340: }
2341: ftemp=fu;
2342: if (fabs(e) > tol1) {
2343: r=(x-w)*(fx-fv);
2344: q=(x-v)*(fx-fw);
2345: p=(x-v)*q-(x-w)*r;
2346: q=2.0*(q-r);
2347: if (q > 0.0) p = -p;
2348: q=fabs(q);
2349: etemp=e;
2350: e=d;
2351: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 2352: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 2353: else {
1.224 brouard 2354: d=p/q;
2355: u=x+d;
2356: if (u-a < tol2 || b-u < tol2)
2357: d=SIGN(tol1,xm-x);
1.126 brouard 2358: }
2359: } else {
2360: d=CGOLD*(e=(x >= xm ? a-x : b-x));
2361: }
2362: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
2363: fu=(*f)(u);
2364: if (fu <= fx) {
2365: if (u >= x) a=x; else b=x;
2366: SHFT(v,w,x,u)
1.183 brouard 2367: SHFT(fv,fw,fx,fu)
2368: } else {
2369: if (u < x) a=u; else b=u;
2370: if (fu <= fw || w == x) {
1.224 brouard 2371: v=w;
2372: w=u;
2373: fv=fw;
2374: fw=fu;
1.183 brouard 2375: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 2376: v=u;
2377: fv=fu;
1.183 brouard 2378: }
2379: }
1.126 brouard 2380: }
2381: nrerror("Too many iterations in brent");
2382: *xmin=x;
2383: return fx;
2384: }
2385:
2386: /****************** mnbrak ***********************/
2387:
2388: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
2389: double (*func)(double))
1.183 brouard 2390: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
2391: the downhill direction (defined by the function as evaluated at the initial points) and returns
2392: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
2393: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
2394: */
1.126 brouard 2395: double ulim,u,r,q, dum;
2396: double fu;
1.187 brouard 2397:
2398: double scale=10.;
2399: int iterscale=0;
2400:
2401: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
2402: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
2403:
2404:
2405: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
2406: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
2407: /* *bx = *ax - (*ax - *bx)/scale; */
2408: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
2409: /* } */
2410:
1.126 brouard 2411: if (*fb > *fa) {
2412: SHFT(dum,*ax,*bx,dum)
1.183 brouard 2413: SHFT(dum,*fb,*fa,dum)
2414: }
1.126 brouard 2415: *cx=(*bx)+GOLD*(*bx-*ax);
2416: *fc=(*func)(*cx);
1.183 brouard 2417: #ifdef DEBUG
1.224 brouard 2418: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
2419: 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 2420: #endif
1.224 brouard 2421: 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 2422: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 2423: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 2424: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 2425: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
2426: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
2427: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 2428: fu=(*func)(u);
1.163 brouard 2429: #ifdef DEBUG
2430: /* f(x)=A(x-u)**2+f(u) */
2431: double A, fparabu;
2432: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2433: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 2434: 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);
2435: 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 2436: /* And thus,it can be that fu > *fc even if fparabu < *fc */
2437: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
2438: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
2439: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 2440: #endif
1.184 brouard 2441: #ifdef MNBRAKORIGINAL
1.183 brouard 2442: #else
1.191 brouard 2443: /* if (fu > *fc) { */
2444: /* #ifdef DEBUG */
2445: /* printf("mnbrak4 fu > fc \n"); */
2446: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
2447: /* #endif */
2448: /* /\* 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 *\\/ *\/ */
2449: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2450: /* dum=u; /\* Shifting c and u *\/ */
2451: /* u = *cx; */
2452: /* *cx = dum; */
2453: /* dum = fu; */
2454: /* fu = *fc; */
2455: /* *fc =dum; */
2456: /* } else { /\* end *\/ */
2457: /* #ifdef DEBUG */
2458: /* printf("mnbrak3 fu < fc \n"); */
2459: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2460: /* #endif */
2461: /* dum=u; /\* Shifting c and u *\/ */
2462: /* u = *cx; */
2463: /* *cx = dum; */
2464: /* dum = fu; */
2465: /* fu = *fc; */
2466: /* *fc =dum; */
2467: /* } */
1.224 brouard 2468: #ifdef DEBUGMNBRAK
2469: double A, fparabu;
2470: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2471: fparabu= *fa - A*(*ax-u)*(*ax-u);
2472: 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);
2473: 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 2474: #endif
1.191 brouard 2475: dum=u; /* Shifting c and u */
2476: u = *cx;
2477: *cx = dum;
2478: dum = fu;
2479: fu = *fc;
2480: *fc =dum;
1.183 brouard 2481: #endif
1.162 brouard 2482: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2483: #ifdef DEBUG
1.224 brouard 2484: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2485: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2486: #endif
1.126 brouard 2487: fu=(*func)(u);
2488: if (fu < *fc) {
1.183 brouard 2489: #ifdef DEBUG
1.224 brouard 2490: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2491: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2492: #endif
2493: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2494: SHFT(*fb,*fc,fu,(*func)(u))
2495: #ifdef DEBUG
2496: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2497: #endif
2498: }
1.162 brouard 2499: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2500: #ifdef DEBUG
1.224 brouard 2501: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2502: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2503: #endif
1.126 brouard 2504: u=ulim;
2505: fu=(*func)(u);
1.183 brouard 2506: } else { /* u could be left to b (if r > q parabola has a maximum) */
2507: #ifdef DEBUG
1.224 brouard 2508: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2509: 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 2510: #endif
1.126 brouard 2511: u=(*cx)+GOLD*(*cx-*bx);
2512: fu=(*func)(u);
1.224 brouard 2513: #ifdef DEBUG
2514: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2515: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2516: #endif
1.183 brouard 2517: } /* end tests */
1.126 brouard 2518: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2519: SHFT(*fa,*fb,*fc,fu)
2520: #ifdef DEBUG
1.224 brouard 2521: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2522: 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 2523: #endif
2524: } /* 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 2525: }
2526:
2527: /*************** linmin ************************/
1.162 brouard 2528: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2529: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2530: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2531: the value of func at the returned location p . This is actually all accomplished by calling the
2532: routines mnbrak and brent .*/
1.126 brouard 2533: int ncom;
2534: double *pcom,*xicom;
2535: double (*nrfunc)(double []);
2536:
1.224 brouard 2537: #ifdef LINMINORIGINAL
1.126 brouard 2538: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2539: #else
2540: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2541: #endif
1.126 brouard 2542: {
2543: double brent(double ax, double bx, double cx,
2544: double (*f)(double), double tol, double *xmin);
2545: double f1dim(double x);
2546: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2547: double *fc, double (*func)(double));
2548: int j;
2549: double xx,xmin,bx,ax;
2550: double fx,fb,fa;
1.187 brouard 2551:
1.203 brouard 2552: #ifdef LINMINORIGINAL
2553: #else
2554: double scale=10., axs, xxs; /* Scale added for infinity */
2555: #endif
2556:
1.126 brouard 2557: ncom=n;
2558: pcom=vector(1,n);
2559: xicom=vector(1,n);
2560: nrfunc=func;
2561: for (j=1;j<=n;j++) {
2562: pcom[j]=p[j];
1.202 brouard 2563: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2564: }
1.187 brouard 2565:
1.203 brouard 2566: #ifdef LINMINORIGINAL
2567: xx=1.;
2568: #else
2569: axs=0.0;
2570: xxs=1.;
2571: do{
2572: xx= xxs;
2573: #endif
1.187 brouard 2574: ax=0.;
2575: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2576: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2577: /* 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)) */
2578: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2579: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2580: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2581: /* 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 2582: #ifdef LINMINORIGINAL
2583: #else
2584: if (fx != fx){
1.224 brouard 2585: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2586: printf("|");
2587: fprintf(ficlog,"|");
1.203 brouard 2588: #ifdef DEBUGLINMIN
1.224 brouard 2589: 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 2590: #endif
2591: }
1.224 brouard 2592: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2593: #endif
2594:
1.191 brouard 2595: #ifdef DEBUGLINMIN
2596: 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 2597: 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 2598: #endif
1.224 brouard 2599: #ifdef LINMINORIGINAL
2600: #else
1.317 brouard 2601: if(fb == fx){ /* Flat function in the direction */
2602: xmin=xx;
1.224 brouard 2603: *flat=1;
1.317 brouard 2604: }else{
1.224 brouard 2605: *flat=0;
2606: #endif
2607: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2608: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2609: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2610: /* fmin = f(p[j] + xmin * xi[j]) */
2611: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2612: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2613: #ifdef DEBUG
1.224 brouard 2614: 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);
2615: 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);
2616: #endif
2617: #ifdef LINMINORIGINAL
2618: #else
2619: }
1.126 brouard 2620: #endif
1.191 brouard 2621: #ifdef DEBUGLINMIN
2622: printf("linmin end ");
1.202 brouard 2623: fprintf(ficlog,"linmin end ");
1.191 brouard 2624: #endif
1.126 brouard 2625: for (j=1;j<=n;j++) {
1.203 brouard 2626: #ifdef LINMINORIGINAL
2627: xi[j] *= xmin;
2628: #else
2629: #ifdef DEBUGLINMIN
2630: if(xxs <1.0)
2631: printf(" before xi[%d]=%12.8f", j,xi[j]);
2632: #endif
2633: 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) */
2634: #ifdef DEBUGLINMIN
2635: if(xxs <1.0)
2636: 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 );
2637: #endif
2638: #endif
1.187 brouard 2639: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2640: }
1.191 brouard 2641: #ifdef DEBUGLINMIN
1.203 brouard 2642: printf("\n");
1.191 brouard 2643: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2644: 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 2645: for (j=1;j<=n;j++) {
1.202 brouard 2646: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2647: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2648: if(j % ncovmodel == 0){
1.191 brouard 2649: printf("\n");
1.202 brouard 2650: fprintf(ficlog,"\n");
2651: }
1.191 brouard 2652: }
1.203 brouard 2653: #else
1.191 brouard 2654: #endif
1.126 brouard 2655: free_vector(xicom,1,n);
2656: free_vector(pcom,1,n);
2657: }
2658:
1.359 brouard 2659: /**** praxis gegen ****/
2660:
2661: /* This has been tested by Visual C from Microsoft and works */
2662: /* meaning tha valgrind could be wrong */
2663: /*********************************************************************/
2664: /* f u n c t i o n p r a x i s */
2665: /* */
2666: /* praxis is a general purpose routine for the minimization of a */
2667: /* function in several variables. the algorithm used is a modifi- */
2668: /* cation of conjugate gradient search method by powell. the changes */
2669: /* are due to r.p. brent, who gives an algol-w program, which served */
2670: /* as a basis for this function. */
2671: /* */
2672: /* references: */
2673: /* - powell, m.j.d., 1964. an efficient method for finding */
2674: /* the minimum of a function in several variables without */
2675: /* calculating derivatives, computer journal, 7, 155-162 */
2676: /* - brent, r.p., 1973. algorithms for minimization without */
2677: /* derivatives, prentice hall, englewood cliffs. */
2678: /* */
2679: /* problems, suggestions or improvements are always wellcome */
2680: /* karl gegenfurtner 07/08/87 */
2681: /* c - version */
2682: /*********************************************************************/
2683: /* */
2684: /* usage: min = praxis(tol, macheps, h, n, prin, x, func) */
2685: /* macheps has been suppressed because it is replaced by DBL_EPSILON */
2686: /* and if it was an argument of praxis (as it is in original brent) */
2687: /* it should be declared external */
2688: /* usage: min = praxis(tol, h, n, prin, x, func) */
2689: /* was min = praxis(fun, x, n); */
2690: /* */
2691: /* fun the function to be minimized. fun is called from */
2692: /* praxis with x and n as arguments */
2693: /* x a double array containing the initial guesses for */
2694: /* the minimum, which will contain the solution on */
2695: /* return */
2696: /* n an integer specifying the number of unknown */
2697: /* parameters */
2698: /* min praxis returns the least calculated value of fun */
2699: /* */
2700: /* some additional global variables control some more aspects of */
2701: /* the inner workings of praxis. setting them is optional, they */
2702: /* are all set to some reasonable default values given below. */
2703: /* */
2704: /* prin controls the printed output from the routine. */
2705: /* 0 -> no output */
2706: /* 1 -> print only starting and final values */
2707: /* 2 -> detailed map of the minimization process */
2708: /* 3 -> print also eigenvalues and vectors of the */
2709: /* search directions */
2710: /* the default value is 1 */
2711: /* tol is the tolerance allowed for the precision of the */
2712: /* solution. praxis returns if the criterion */
2713: /* 2 * ||x[k]-x[k-1]|| <= sqrt(macheps) * ||x[k]|| + tol */
2714: /* is fulfilled more than ktm times. */
2715: /* the default value depends on the machine precision */
2716: /* ktm see just above. default is 1, and a value of 4 leads */
2717: /* to a very(!) cautious stopping criterion. */
2718: /* h0 or step is a steplength parameter and should be set equal */
2719: /* to the expected distance from the solution. */
2720: /* exceptionally small or large values of step lead to */
2721: /* slower convergence on the first few iterations */
2722: /* the default value for step is 1.0 */
2723: /* scbd is a scaling parameter. 1.0 is the default and */
2724: /* indicates no scaling. if the scales for the different */
2725: /* parameters are very different, scbd should be set to */
2726: /* a value of about 10.0. */
2727: /* illc should be set to true (1) if the problem is known to */
2728: /* be ill-conditioned. the default is false (0). this */
2729: /* variable is automatically set, when praxis finds */
2730: /* the problem to be ill-conditioned during iterations. */
2731: /* maxfun is the maximum number of calls to fun allowed. praxis */
2732: /* will return after maxfun calls to fun even when the */
2733: /* minimum is not yet found. the default value of 0 */
2734: /* indicates no limit on the number of calls. */
2735: /* this return condition is only checked every n */
2736: /* iterations. */
2737: /* */
2738: /*********************************************************************/
2739:
2740: #include <math.h>
2741: #include <stdio.h>
2742: #include <stdlib.h>
2743: #include <float.h> /* for DBL_EPSILON */
2744: /* #include "machine.h" */
2745:
2746:
2747: /* extern void minfit(int n, double eps, double tol, double **ab, double q[]); */
2748: /* extern void minfit(int n, double eps, double tol, double ab[N][N], double q[]); */
2749: /* control parameters */
2750: /* control parameters */
2751: #define SQREPSILON 1.0e-19
2752: /* #define EPSILON 1.0e-8 */ /* in main */
2753:
2754: double tol = SQREPSILON,
2755: scbd = 1.0,
2756: step = 1.0;
2757: int ktm = 1,
2758: /* prin = 2, */
2759: maxfun = 0,
2760: illc = 0;
2761:
2762: /* some global variables */
2763: static int i, j, k, k2, nl, nf, kl, kt;
2764: /* static double s; */
2765: double sl, dn, dmin,
2766: fx, f1, lds, ldt, sf, df,
2767: qf1, qd0, qd1, qa, qb, qc,
2768: m2, m4, small_windows, vsmall, large,
2769: vlarge, ldfac, t2;
2770: /* static double d[N], y[N], z[N], */
2771: /* q0[N], q1[N], v[N][N]; */
2772:
2773: static double *d, *y, *z;
2774: static double *q0, *q1, **v;
2775: double *tflin; /* used in flin: return (*fun)(tflin, n); */
2776: double *e; /* used in minfit, don't konw how to free memory and thus made global */
2777: /* static double s, sl, dn, dmin, */
2778: /* fx, f1, lds, ldt, sf, df, */
2779: /* qf1, qd0, qd1, qa, qb, qc, */
2780: /* m2, m4, small, vsmall, large, */
2781: /* vlarge, ldfac, t2; */
2782: /* static double d[N], y[N], z[N], */
2783: /* q0[N], q1[N], v[N][N]; */
2784:
2785: /* these will be set by praxis to point to it's arguments */
2786: static int prin; /* added */
2787: static int n;
2788: static double *x;
2789: static double (*fun)();
2790: /* static double (*fun)(double *x, int n); */
2791:
2792: /* these will be set by praxis to the global control parameters */
2793: /* static double h, macheps, t; */
2794: extern double macheps;
2795: static double h;
2796: static double t;
2797:
2798: static double
2799: drandom() /* return random no between 0 and 1 */
2800: {
2801: return (double)(rand()%(8192*2))/(double)(8192*2);
2802: }
2803:
2804: static void sort() /* d and v in descending order */
2805: {
2806: int k, i, j;
2807: double s;
2808:
2809: for (i=1; i<=n-1; i++) {
2810: k = i; s = d[i];
2811: for (j=i+1; j<=n; j++) {
2812: if (d[j] > s) {
2813: k = j;
2814: s = d[j];
2815: }
2816: }
2817: if (k > i) {
2818: d[k] = d[i];
2819: d[i] = s;
2820: for (j=1; j<=n; j++) {
2821: s = v[j][i];
2822: v[j][i] = v[j][k];
2823: v[j][k] = s;
2824: }
2825: }
2826: }
2827: }
2828:
2829: double randbrent ( int *naught )
2830: {
2831: double ran1, ran3[127], half;
2832: int ran2, q, r, i, j;
2833: int init=0; /* false */
2834: double rr;
2835: /* REAL*8 RAN1,RAN3(127),HALF */
2836:
2837: /* INTEGER RAN2,Q,R */
2838: /* LOGICAL INIT */
2839: /* DATA INIT/.FALSE./ */
2840: /* IF (INIT) GO TO 3 */
2841: if(!init){
2842: /* R = MOD(NAUGHT,8190) + 1 *//* 1804289383 rand () */
2843: r = *naught % 8190 + 1;/* printf(" naught r %d %d",*naught,r); */
2844: ran2=127;
2845: for(i=ran2; i>0; i--){
2846: /* RAN2 = 128 */
2847: /* DO 2 I=1,127 */
2848: ran2 = ran2-1;
2849: /* RAN2 = RAN2 - 1 */
2850: ran1 = -pow(2.0,55);
2851: /* RAN1 = -2.D0**55 */
2852: /* DO 1 J=1,7 */
2853: for(j=1; j<=7;j++){
2854: /* R = MOD(1756*R,8191) */
2855: r = (1756*r) % 8191;/* printf(" i=%d (1756*r)%8191=%d",j,r); */
2856: q=r/32;
2857: /* Q = R/32 */
2858: /* 1 RAN1 = (RAN1 + Q)*(1.0D0/256) */
2859: ran1 =(ran1+q)*(1.0/256);
2860: }
2861: /* 2 RAN3(RAN2) = RAN1 */
2862: ran3[ran2] = ran1; /* printf(" ran2=%d ran1=%.7g \n",ran2,ran1); */
2863: }
2864: /* INIT = .TRUE. */
2865: init=1;
2866: /* 3 IF (RAN2.EQ.1) RAN2 = 128 */
2867: }
2868: if(ran2 == 0) ran2 = 126;
2869: else ran2 = ran2 -1;
2870: /* RAN2 = RAN2 - 1 */
2871: /* RAN1 = RAN1 + RAN3(RAN2) */
2872: ran1 = ran1 + ran3[ran2];/* printf("BIS ran2=%d ran1=%.7g \n",ran2,ran1); */
2873: half= 0.5;
2874: /* HALF = .5D0 */
2875: /* IF (RAN1.GE.0.D0) HALF = -HALF */
2876: if(ran1 >= 0.) half =-half;
2877: ran1 = ran1 +half;
2878: ran3[ran2] = ran1;
2879: rr= ran1+0.5;
2880: /* RAN1 = RAN1 + HALF */
2881: /* RAN3(RAN2) = RAN1 */
2882: /* RANDOM = RAN1 + .5D0 */
2883: /* r = ( ( double ) ( *seed ) ) * 4.656612875E-10; */
2884: return rr;
2885: }
2886: static void matprint(char *s, double **v, int m, int n)
2887: /* char *s; */
2888: /* double v[N][N]; */
2889: {
2890: #define INCX 8
2891: int i;
2892:
2893: int i2hi;
2894: int ihi;
2895: int ilo;
2896: int i2lo;
2897: int jlo=1;
2898: int j;
2899: int j2hi;
2900: int jhi;
2901: int j2lo;
2902: ilo=1;
2903: ihi=n;
2904: jlo=1;
2905: jhi=n;
2906:
2907: printf ("\n" );
2908: printf ("%s\n", s );
2909: for ( j2lo = jlo; j2lo <= jhi; j2lo = j2lo + INCX )
2910: {
2911: j2hi = j2lo + INCX - 1;
2912: if ( n < j2hi )
2913: {
2914: j2hi = n;
2915: }
2916: if ( jhi < j2hi )
2917: {
2918: j2hi = jhi;
2919: }
2920:
2921: /* fprintf ( ficlog, "\n" ); */
2922: printf ("\n" );
2923: /*
2924: For each column J in the current range...
2925:
2926: Write the header.
2927: */
2928: /* fprintf ( ficlog, " Col: "); */
2929: printf ("Col:");
2930: for ( j = j2lo; j <= j2hi; j++ )
2931: {
2932: /* fprintf ( ficlog, " %7d ", j - 1 ); */
2933: /* printf (" %9d ", j - 1 ); */
2934: printf (" %9d ", j );
2935: }
2936: /* fprintf ( ficlog, "\n" ); */
2937: /* fprintf ( ficlog, " Row\n" ); */
2938: /* fprintf ( ficlog, "\n" ); */
2939: printf ("\n" );
2940: printf (" Row\n" );
2941: printf ("\n" );
2942: /*
2943: Determine the range of the rows in this strip.
2944: */
2945: if ( 1 < ilo ){
2946: i2lo = ilo;
2947: }else{
2948: i2lo = 1;
2949: }
2950: if ( m < ihi ){
2951: i2hi = m;
2952: }else{
2953: i2hi = ihi;
2954: }
2955:
2956: for ( i = i2lo; i <= i2hi; i++ ){
2957: /*
2958: Print out (up to) 5 entries in row I, that lie in the current strip.
2959: */
2960: /* fprintf ( ficlog, "%5d:", i - 1 ); */
2961: /* printf ("%5d:", i - 1 ); */
2962: printf ("%5d:", i );
2963: for ( j = j2lo; j <= j2hi; j++ )
2964: {
2965: /* fprintf ( ficlog, " %14g", a[i-1+(j-1)*m] ); */
2966: /* printf ("%14.7g ", a[i-1+(j-1)*m] ); */
2967: /* printf("%14.7f ", v[i-1][j-1]); */
2968: printf("%14.7f ", v[i][j]);
2969: /* fprintf ( stdout, " %14g", a[i-1+(j-1)*m] ); */
2970: }
2971: /* fprintf ( ficlog, "\n" ); */
2972: printf ("\n" );
2973: }
2974: }
2975:
2976: /* printf("%s\n", s); */
2977: /* for (k=0; k<n; k++) { */
2978: /* for (i=0; i<n; i++) { */
2979: /* /\* printf("%20.10e ", v[k][i]); *\/ */
2980: /* } */
2981: /* printf("\n"); */
2982: /* } */
2983: #undef INCX
2984: }
2985:
2986: void vecprint(char *s, double *x, int n)
2987: /* char *s; */
2988: /* double x[N]; */
2989: {
2990: int i=0;
2991:
2992: printf(" %s", s);
2993: /* for (i=0; i<n; i++) */
2994: for (i=1; i<=n; i++)
2995: printf (" %14.7g", x[i] );
2996: /* printf(" %8d: %14g\n", i, x[i]); */
2997: printf ("\n" );
2998: }
2999:
3000: static void print() /* print a line of traces */
3001: {
3002:
3003:
3004: printf("\n");
3005: /* printf("... chi square reduced to ... %20.10e\n", fx); */
3006: /* printf("... after %u function calls ...\n", nf); */
3007: /* printf("... including %u linear searches ...\n", nl); */
3008: printf("%10d %10d%14.7g",nl, nf, fx);
3009: vecprint("... current values of x ...", x, n);
3010: }
3011: /* static void print2(int n, double *x, int prin, double fx, int nf, int nl) */ /* print a line of traces */
3012: static void print2() /* print a line of traces */
3013: {
3014: int i; double fmin=0.;
3015:
3016: /* printf("\n"); */
3017: /* printf("... chi square reduced to ... %20.10e\n", fx); */
3018: /* printf("... after %u function calls ...\n", nf); */
3019: /* printf("... including %u linear searches ...\n", nl); */
3020: /* printf("%10d %10d%14.7g",nl, nf, fx); */
1.363 ! brouard 3021: /* printf ( "\n" ); */
1.359 brouard 3022: printf ( " Linear searches %d", nl );
3023: /* printf ( " Linear searches %d\n", nl ); */
3024: /* printf ( " Function evaluations %d\n", nf ); */
3025: /* printf ( " Function value FX = %g\n", fx ); */
3026: printf ( " Function evaluations %d", nf );
3027: printf ( " Function value FX = %.12lf\n", fx );
1.363 ! brouard 3028: fprintf (ficlog, " Function evaluations %d", nf );
! 3029: fprintf (ficlog, " Function value FX = %.12lf\n", fx );
1.359 brouard 3030: #ifdef DEBUGPRAX
3031: printf("n=%d prin=%d\n",n,prin);
3032: #endif
1.363 ! brouard 3033: /* if(fx <= fmin) printf(" UNDEFINED "); else printf("%14.7g",log(fx-fmin)); */
1.359 brouard 3034: if ( n <= 4 || 2 < prin )
3035: {
3036: /* for(i=1;i<=n;i++)printf("%14.7g",x[i-1]); */
1.363 ! brouard 3037: for(i=1;i<=n;i++){
! 3038: printf("%14.7g",x[i]);
! 3039: fprintf(ficlog,"%14.7g",x[i]);
! 3040: }
1.359 brouard 3041: /* r8vec_print ( n, x, " X:" ); */
3042: }
3043: printf("\n");
1.363 ! brouard 3044: fprintf(ficlog,"\n");
1.359 brouard 3045: }
3046:
3047:
3048: /* #ifdef MSDOS */
3049: /* static double tflin[N]; */
3050: /* #endif */
3051:
3052: static double flin(double l, int j)
3053: /* double l; */
3054: {
3055: int i;
3056: /* #ifndef MSDOS */
3057: /* double tflin[N]; */
3058: /* #endif */
3059: /* double *tflin; */ /* Be careful to put tflin on a vector n */
3060:
3061: /* j is used from 0 to n-1 and can be -1 for parabolic search */
3062:
3063: /* if (j != -1) { /\* linear search *\/ */
3064: if (j > 0) { /* linear search */
3065: /* for (i=0; i<n; i++){ */
3066: for (i=1; i<=n; i++){
3067: tflin[i] = x[i] + l *v[i][j];
3068: #ifdef DEBUGPRAX
3069: /* 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); */
3070: 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);
3071: #endif
3072: }
3073: }
3074: else { /* search along parabolic space curve */
3075: qa = l*(l-qd1)/(qd0*(qd0+qd1));
3076: qb = (l+qd0)*(qd1-l)/(qd0*qd1);
3077: qc = l*(l+qd0)/(qd1*(qd0+qd1));
3078: #ifdef DEBUGPRAX
3079: 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);
3080: #endif
3081: /* for (i=0; i<n; i++){ */
3082: for (i=1; i<=n; i++){
3083: tflin[i] = qa*q0[i]+qb*x[i]+qc*q1[i];
3084: #ifdef DEBUGPRAX
3085: /* 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]); */
3086: 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]);
3087: #endif
3088: }
3089: }
3090: nf++;
3091:
3092: #ifdef NR_SHIFT
3093: return (*fun)((tflin-1), n);
3094: #else
3095: /* return (*fun)(tflin, n);*/
3096: return (*fun)(tflin);
3097: #endif
3098: }
3099:
3100: void minny(int j, int nits, double *d2, double *x1, double f1, int fk)
3101: /* double *d2, *x1, f1; */
3102: {
3103: /* here j is from 0 to n-1 and can be -1 for parabolic search */
3104: /* MINIMIZES F FROM X IN THE DIRECTION V(*,J) */
3105: /* UNLESS J<1, WHEN A QUADRATIC SEARCH IS DONE */
3106: /* IN THE PLANE DEFINED BY Q0, Q1 AND X. */
3107: /* D2 AN APPROXIMATION TO HALF F'' (OR ZERO), */
3108: /* X1 AN ESTIMATE OF DISTANCE TO MINIMUM, */
3109: /* RETURNED AS THE DISTANCE FOUND. */
3110: /* IF FK = TRUE THEN F1 IS FLIN(X1), OTHERWISE */
3111: /* X1 AND F1 ARE IGNORED ON ENTRY UNLESS FINAL */
3112: /* FX > F1. NITS CONTROLS THE NUMBER OF TIMES */
3113: /* AN ATTEMPT IS MADE TO HALVE THE INTERVAL. */
3114: /* SIDE EFFECTS: USES AND ALTERS X, FX, NF, NL. */
3115: /* IF J < 1 USES VARIABLES Q... . */
3116: /* USES H, N, T, M2, M4, LDT, DMIN, MACHEPS; */
3117: int k, i, dz;
3118: double x2, xm, f0, f2, fm, d1, t2, sf1, sx1;
3119: double s;
3120: double macheps;
3121: macheps=pow(16.0,-13.0);
3122: sf1 = f1; sx1 = *x1;
3123: k = 0; xm = 0.0; fm = f0 = fx; dz = *d2 < macheps;
3124: /* h=1.0;*/ /* To be revised */
3125: #ifdef DEBUGPRAX
3126: /* printf("min macheps=%14g h=%14g step=%14g t=%14g fx=%14g\n",macheps,h, step,t, fx); */
3127: /* Where is fx coming from */
3128: printf(" min macheps=%14g h=%14g t=%14g fx=%.9lf dirj=%d\n",macheps, h, t, fx, j);
3129: matprint(" min vectors:",v,n,n);
3130: #endif
3131: /* find step size */
3132: s = 0.;
3133: /* for (i=0; i<n; i++) s += x[i]*x[i]; */
3134: for (i=1; i<=n; i++) s += x[i]*x[i];
3135: s = sqrt(s);
3136: if (dz)
3137: t2 = m4*sqrt(fabs(fx)/dmin + s*ldt) + m2*ldt;
3138: else
3139: t2 = m4*sqrt(fabs(fx)/(*d2) + s*ldt) + m2*ldt;
3140: s = s*m4 + t;
3141: if (dz && t2 > s) t2 = s;
3142: if (t2 < small_windows) t2 = small_windows;
3143: if (t2 > 0.01*h) t2 = 0.01 * h;
3144: if (fk && f1 <= fm) {
3145: xm = *x1;
3146: fm = f1;
3147: }
3148: #ifdef DEBUGPRAX
3149: printf(" additional flin X1=%14.7f t2=%14.7f *f1=%14.7f fm=%14.7f fk=%d\n",*x1,t2,f1,fm,fk);
3150: #endif
3151: if (!fk || fabs(*x1) < t2) {
3152: *x1 = (*x1 >= 0 ? t2 : -t2);
3153: /* *x1 = (*x1 > 0 ? t2 : -t2); */ /* kind of error */
3154: #ifdef DEBUGPRAX
3155: printf(" additional flin X1=%16.10e dirj=%d fk=%d\n",*x1, j, fk);
3156: #endif
3157: f1 = flin(*x1, j);
3158: #ifdef DEBUGPRAX
3159: printf(" after flin f1=%18.12e dirj=%d fk=%d\n",f1, j,fk);
3160: #endif
3161: }
3162: if (f1 <= fm) {
3163: xm = *x1;
3164: fm = f1;
3165: }
3166: L0: /*L0 loop or next */
3167: /*
3168: Evaluate FLIN at another point and estimate the second derivative.
3169: */
3170: if (dz) {
3171: x2 = (f0 < f1 ? -(*x1) : 2*(*x1));
3172: #ifdef DEBUGPRAX
3173: printf(" additional second flin x2=%14.8e x1=%14.8e f0=%14.8e f1=%18.12e dirj=%d\n",x2,*x1,f0,f1,j);
3174: #endif
3175: f2 = flin(x2, j);
3176: #ifdef DEBUGPRAX
3177: 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);
3178: #endif
3179: if (f2 <= fm) {
3180: xm = x2;
3181: fm = f2;
3182: }
3183: /* d2 is the curvature or double difference f1 doesn't seem to be accurately computed */
3184: *d2 = (x2*(f1-f0) - (*x1)*(f2-f0))/((*x1)*x2*((*x1)-x2));
3185: #ifdef DEBUGPRAX
3186: double d11,d12;
3187: d11=(f1-f0)/(*x1);d12=(f2-f0)/x2;
3188: 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)));
3189: 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);
3190: double ff1=7.783920622852e+04;
3191: double f1mf0=9.0344736236e-05;
3192: *d2 = (f1mf0)/ (*x1)/((*x1)-x2) - (f2-f0)/x2/((*x1)-x2);
3193: /* *d2 = (ff1-f0)/ (*x1)/((*x1)-x2) - (f2-f0)/x2/((*x1)-x2); */
3194: printf(" simpliff computing *d2=%16.10e f1mf0=%18.12e,f1=f0+f1mf0=%18.12e\n",*d2,f1mf0,f0+f1mf0);
3195: *d2 = ((f1-f0)/ (*x1) - (f2-f0)/x2)/((*x1)-x2);
3196: printf(" overlifi computing *d2=%16.10e\n",*d2);
3197: #endif
3198: *d2 = ((f1-f0)/ (*x1) - (f2-f0)/x2)/((*x1)-x2);
3199: }
3200: #ifdef DEBUGPRAX
3201: printf(" additional second flin xm=%14.8e fm=%14.8e *d2=%14.8e\n",xm, fm,*d2);
3202: #endif
3203: /*
3204: Estimate the first derivative at 0.
3205: */
3206: d1 = (f1-f0)/(*x1) - *x1**d2; dz = 1;
3207: /*
3208: Predict the minimum.
3209: */
3210: if (*d2 <= small_windows) {
3211: x2 = (d1 < 0 ? h : -h);
3212: }
3213: else {
3214: x2 = - 0.5*d1/(*d2);
3215: }
3216: #ifdef DEBUGPRAX
3217: 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);
3218: #endif
3219: if (fabs(x2) > h)
3220: x2 = (x2 > 0 ? h : -h);
3221: L1: /* L1 or try loop */
3222: #ifdef DEBUGPRAX
3223: printf(" AT predicted minimum flin x2=%14.8e x1=%14.8e K=%14d NITS=%14d dirj=%d\n",x2,*x1,k,nits,j);
3224: #endif
3225: f2 = flin(x2, j); /* x[i]+x2*v[i][j] */
3226: #ifdef DEBUGPRAX
3227: printf(" after flin f0=%14.8e f1=%14.8e f2=%14.8e fm=%14.8e\n",f0,f1,f2, fm);
3228: #endif
3229: if ((k < nits) && (f2 > f0)) {
3230: #ifdef DEBUGPRAX
3231: printf(" NO SUCCESS SO TRY AGAIN;\n");
3232: #endif
3233: k++;
3234: if ((f0 < f1) && (*x1*x2 > 0.0))
3235: goto L0; /* or next */
3236: x2 *= 0.5;
3237: goto L1;
3238: }
3239: nl++;
3240: #ifdef DEBUGPRAX
3241: 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);
3242: #endif
3243: if (f2 > fm) x2 = xm; else fm = f2;
3244: if (fabs(x2*(x2-*x1)) > small_windows) {
3245: *d2 = (x2*(f1-f0) - *x1*(fm-f0))/(*x1*x2*(*x1-x2));
3246: }
3247: else {
3248: if (k > 0) *d2 = 0;
3249: }
3250: #ifdef DEBUGPRAX
1.362 brouard 3251: 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 3252: #endif
3253: if (*d2 <= small_windows) *d2 = small_windows;
3254: *x1 = x2; fx = fm;
3255: if (sf1 < fx) {
3256: fx = sf1;
3257: *x1 = sx1;
3258: }
3259: /*
3260: Update X for linear search.
3261: */
3262: #ifdef DEBUGPRAX
3263: printf(" end of min x1=%14.8e fx=%14.8e d2=%14.8e\n",*x1, fx, *d2);
3264: #endif
3265:
3266: /* if (j != -1) */
3267: /* for (i=0; i<n; i++) */
3268: /* x[i] += (*x1)*v[i][j]; */
3269: if (j > 0)
3270: for (i=1; i<=n; i++)
3271: x[i] += (*x1)*v[i][j];
3272: }
3273:
3274: void quad() /* look for a minimum along the curve q0, q1, q2 */
3275: {
3276: int i;
3277: double l, s;
3278:
3279: s = fx; fx = qf1; qf1 = s; qd1 = 0.0;
3280: /* for (i=0; i<n; i++) { */
3281: for (i=1; i<=n; i++) {
3282: s = x[i]; l = q1[i]; x[i] = l; q1[i] = s;
3283: qd1 = qd1 + (s-l)*(s-l);
3284: }
3285: s = 0.0; qd1 = sqrt(qd1); l = qd1;
3286: #ifdef DEBUGPRAX
3287: printf(" QUAD after sqrt qd1=%14.8e \n",qd1);
3288: #endif
3289:
3290: if (qd0>0.0 && qd1>0.0 &&nl>=3*n*n) {
3291: #ifdef DEBUGPRAX
3292: printf(" QUAD before min value=%14.8e \n",qf1);
3293: #endif
3294: /* min(-1, 2, &s, &l, qf1, 1); */
3295: minny(0, 2, &s, &l, qf1, 1);
3296: qa = l*(l-qd1)/(qd0*(qd0+qd1));
3297: qb = (l+qd0)*(qd1-l)/(qd0*qd1);
3298: qc = l*(l+qd0)/(qd1*(qd0+qd1));
3299: }
3300: else {
3301: fx = qf1; qa = qb = 0.0; qc = 1.0;
3302: }
3303: #ifdef DEBUGPRAX
3304: printf("after eventual min qd0=%14.8e qd1=%14.8e nl=%d\n",qd0, qd1,nl);
3305: #endif
3306: qd0 = qd1;
3307: /* for (i=0; i<n; i++) { */
3308: for (i=1; i<=n; i++) {
3309: s = q0[i]; q0[i] = x[i];
3310: x[i] = qa*s + qb*x[i] + qc*q1[i];
3311: }
3312: #ifdef DEBUGQUAD
3313: vecprint ( " X after QUAD:" , x, n );
3314: #endif
3315: }
3316:
3317: /* void minfit(int n, double eps, double tol, double ab[N][N], double q[]) */
3318: void minfit(int n, double eps, double tol, double **ab, double q[])
3319: /* int n; */
3320: /* double eps, tol, ab[N][N], q[N]; */
3321: {
3322: int l, kt, l2, i, j, k;
3323: double c, f, g, h, s, x, y, z;
3324: /* double eps; */
3325: /* #ifndef MSDOS */
3326: /* double e[N]; /\* plenty of stack on a vax *\/ */
3327: /* #endif */
3328: /* double *e; */
3329: /* e=vector(0,n-1); /\* should be freed somewhere but gotos *\/ */
3330:
3331: /* householder's reduction to bidiagonal form */
3332:
3333: if(n==1){
3334: /* q[1-1]=ab[1-1][1-1]; */
3335: /* ab[1-1][1-1]=1.0; */
3336: q[1]=ab[1][1];
3337: ab[1][1]=1.0;
3338: return; /* added from hardt */
3339: }
3340: /* eps=macheps; */ /* added */
3341: x = g = 0.0;
3342: #ifdef DEBUGPRAX
3343: matprint (" HOUSE holder:", ab, n, n);
3344: #endif
3345:
3346: /* for (i=0; i<n; i++) { /\* FOR I := 1 UNTIL N DO *\/ */
3347: for (i=1; i<=n; i++) { /* FOR I := 1 UNTIL N DO */
3348: e[i] = g; s = 0.0; l = i+1;
3349: /* for (j=i; j<n; j++) /\* FOR J := I UNTIL N DO S := S*AB(J,I)**2; *\/ /\* not correct *\/ */
3350: for (j=i; j<=n; j++) /* FOR J := I UNTIL N DO S := S*AB(J,I)**2; */ /* not correct */
3351: s += ab[j][i] * ab[j][i];
3352: #ifdef DEBUGPRAXFIN
3353: printf("i=%d s=%d %.7g tol=%.7g",i,s,tol);
3354: #endif
3355: if (s < tol) {
3356: g = 0.0;
3357: }
3358: else {
3359: /* f = ab[i][i]; */
3360: f = ab[i][i];
3361: if (f < 0.0)
3362: g = sqrt(s);
3363: else
3364: g = -sqrt(s);
3365: /* h = f*g - s; ab[i][i] = f - g; */
3366: h = f*g - s; ab[i][i] = f - g;
3367: /* for (j=l; j<n; j++) { */ /* FOR J := L UNTIL N DO */ /* wrong */
3368: for (j=l; j<=n; j++) {
3369: f = 0.0;
3370: /* for (k=i; k<n; k++) /\* FOR K := I UNTIL N DO *\/ /\* wrong *\/ */
3371: for (k=i; k<=n; k++) /* FOR K := I UNTIL N DO */
3372: /* f += ab[k][i] * ab[k][j]; */
3373: f += ab[k][i] * ab[k][j];
3374: f /= h;
3375: for (k=i; k<=n; k++) /* FOR K := I UNTIL N DO */
3376: /* for (k=i; k<n; k++)/\* FOR K := I UNTIL N DO *\/ /\* wrong *\/ */
3377: ab[k][j] += f * ab[k][i];
3378: /* ab[k][j] += f * ab[k][i]; */
3379: #ifdef DEBUGPRAX
3380: printf("Holder J=%d F=%.7g",j,f);
3381: #endif
3382: }
3383: } /* end s */
3384: /* q[i] = g; s = 0.0; */
3385: q[i] = g; s = 0.0;
3386: #ifdef DEBUGPRAX
3387: printf(" I Q=%d %.7g",i,q[i]);
3388: #endif
3389:
3390: /* if (i < n) */
3391: /* if (i <= n) /\* I is always lower or equal to n wasn't in golub reinsch*\/ */
3392: /* for (j=l; j<n; j++) */
3393: for (j=l; j<=n; j++)
3394: s += ab[i][j] * ab[i][j];
3395: /* s += ab[i][j] * ab[i][j]; */
3396: if (s < tol) {
3397: g = 0.0;
3398: }
3399: else {
3400: if(i<n)
3401: /* f = ab[i][i+1]; */ /* Brent golub overflow */
3402: f = ab[i][i+1];
3403: if (f < 0.0)
3404: g = sqrt(s);
3405: else
3406: g = - sqrt(s);
3407: h = f*g - s;
3408: /* h = f*g - s; ab[i][i+1] = f - g; */ /* Overflow for i=n Error in Golub too but not Burkardt*/
3409: /* for (j=l; j<n; j++) */
3410: /* e[j] = ab[i][j]/h; */
3411: if(i<n){
3412: ab[i][i+1] = f - g;
3413: for (j=l; j<=n; j++)
3414: e[j] = ab[i][j]/h;
3415: /* for (j=l; j<n; j++) { */
3416: for (j=l; j<=n; j++) {
3417: s = 0.0;
3418: /* for (k=l; k<n; k++) s += ab[j][k]*ab[i][k]; */
3419: for (k=l; k<=n; k++) s += ab[j][k]*ab[i][k];
3420: /* for (k=l; k<n; k++) ab[j][k] += s * e[k]; */
3421: for (k=l; k<=n; k++) ab[j][k] += s * e[k];
3422: } /* END J */
3423: } /* END i <n */
3424: } /* end s */
3425: /* y = fabs(q[i]) + fabs(e[i]); */
3426: y = fabs(q[i]) + fabs(e[i]);
3427: if (y > x) x = y;
3428: #ifdef DEBUGPRAX
3429: printf(" I Y=%d %.7g",i,y);
3430: #endif
3431: #ifdef DEBUGPRAX
3432: printf(" i=%d e(i) %.7g",i,e[i]);
3433: #endif
3434: } /* end i */
3435: /*
3436: Accumulation of right hand transformations */
3437: /* for (i=n-1; i >= 0; i--) { */ /* FOR I := N STEP -1 UNTIL 1 DO */
3438: /* We should avoid the overflow in Golub */
3439: /* ab[n-1][n-1] = 1.0; */
3440: /* g = e[n-1]; */
3441: ab[n][n] = 1.0;
3442: g = e[n];
3443: l = n;
3444:
3445: /* for (i=n; i >= 1; i--) { */
3446: for (i=n-1; i >= 1; i--) { /* n-1 loops, different from brent and golub*/
3447: if (g != 0.0) {
3448: /* h = ab[i-1][i]*g; */
3449: h = ab[i][i+1]*g;
3450: for (j=l; j<=n; j++) ab[j][i] = ab[i][j] / h;
3451: for (j=l; j<=n; j++) {
3452: /* h = ab[i][i+1]*g; */
3453: /* for (j=l; j<n; j++) ab[j][i] = ab[i][j] / h; */
3454: /* for (j=l; j<n; j++) { */
3455: s = 0.0;
3456: /* for (k=l; k<n; k++) s += ab[i][k] * ab[k][j]; */
3457: /* for (k=l; k<n; k++) ab[k][j] += s * ab[k][i]; */
3458: for (k=l; k<=n; k++) s += ab[i][k] * ab[k][j];
3459: for (k=l; k<=n; k++) ab[k][j] += s * ab[k][i];
3460: }/* END J */
3461: }/* END G */
3462: /* for (j=l; j<n; j++) */
3463: /* ab[i][j] = ab[j][i] = 0.0; */
3464: /* ab[i][i] = 1.0; g = e[i]; l = i; */
3465: for (j=l; j<=n; j++)
3466: ab[i][j] = ab[j][i] = 0.0;
3467: ab[i][i] = 1.0; g = e[i]; l = i;
3468: }/* END I */
3469: #ifdef DEBUGPRAX
3470: matprint (" HOUSE accumulation:",ab,n, n );
3471: #endif
3472:
3473: /* diagonalization to bidiagonal form */
3474: eps *= x;
3475: /* for (k=n-1; k>= 0; k--) { */
3476: for (k=n; k>= 1; k--) {
3477: kt = 0;
3478: TestFsplitting:
3479: #ifdef DEBUGPRAX
3480: printf(" TestFsplitting: k=%d kt=%d\n",k,kt);
3481: /* for(i=1;i<=n;i++)printf(" e(%d)=%.14f",i,e[i]);printf("\n"); */
3482: #endif
3483: kt = kt+1;
3484: /* TestFsplitting: */
3485: /* if (++kt > 30) { */
3486: if (kt > 30) {
3487: e[k] = 0.0;
3488: fprintf(stderr, "\n+++ MINFIT - Fatal error\n");
3489: fprintf ( stderr, " The QR algorithm failed to converge.\n" );
3490: }
3491: /* for (l2=k; l2>=0; l2--) { */
3492: for (l2=k; l2>=1; l2--) {
3493: l = l2;
3494: #ifdef DEBUGPRAX
3495: printf(" l e(l)< eps %d %.7g %.7g ",l,e[l], eps);
3496: #endif
3497: /* if (fabs(e[l]) <= eps) */
3498: if (fabs(e[l]) <= eps)
3499: goto TestFconvergence;
3500: /* if (fabs(q[l-1]) <= eps)*/ /* missing if ( 1 < l ){ *//* printf(" q(l-1)< eps %d %.7g %.7g ",l-1,q[l-2], eps); */
3501: if (fabs(q[l-1]) <= eps)
3502: break; /* goto Cancellation; */
3503: }
3504: Cancellation:
3505: #ifdef DEBUGPRAX
3506: printf(" Cancellation:\n");
3507: #endif
3508: c = 0.0; s = 1.0;
3509: for (i=l; i<=k; i++) {
3510: f = s * e[i]; e[i] *= c;
3511: /* f = s * e[i]; e[i] *= c; */
3512: if (fabs(f) <= eps)
3513: goto TestFconvergence;
3514: /* g = q[i]; */
3515: g = q[i];
3516: if (fabs(f) < fabs(g)) {
3517: double fg = f/g;
3518: h = fabs(g)*sqrt(1.0+fg*fg);
3519: }
3520: else {
3521: double gf = g/f;
3522: h = (f!=0.0 ? fabs(f)*sqrt(1.0+gf*gf) : 0.0);
3523: }
3524: /* COMMENT: THE ABOVE REPLACES Q(I):=H:=LONGSQRT(G*G+F*F) */
3525: /* WHICH MAY GIVE INCORRECT RESULTS IF THE */
3526: /* SQUARES UNDERFLOW OR IF F = G = 0; */
3527:
3528: /* q[i] = h; */
3529: q[i] = h;
3530: if (h == 0.0) { h = 1.0; g = 1.0; }
3531: c = g/h; s = -f/h;
3532: }
3533: TestFconvergence:
3534: #ifdef DEBUGPRAX
3535: printf(" TestFconvergence: l=%d k=%d\n",l,k);
3536: #endif
3537: /* z = q[k]; */
3538: z = q[k];
3539: if (l == k)
3540: goto Convergence;
3541: /* shift from bottom 2x2 minor */
3542: /* x = q[l]; y = q[k-l]; g = e[k-1]; h = e[k]; */ /* Error */
3543: x = q[l]; y = q[k-1]; g = e[k-1]; h = e[k];
3544: f = ((y-z)*(y+z) + (g-h)*(g+h)) / (2.0*h*y);
3545: g = sqrt(f*f+1.0);
3546: if (f <= 0.0)
3547: f = ((x-z)*(x+z) + h*(y/(f-g)-h))/x;
3548: else
3549: f = ((x-z)*(x+z) + h*(y/(f+g)-h))/x;
3550: /* next qr transformation */
3551: s = c = 1.0;
3552: for (i=l+1; i<=k; i++) {
3553: #ifdef DEBUGPRAXQR
3554: 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]);
3555: #endif
3556: /* g = e[i]; y = q[i]; h = s*g; g *= c; */
3557: g = e[i]; y = q[i]; h = s*g; g *= c;
3558: if (fabs(f) < fabs(h)) {
3559: double fh = f/h;
3560: z = fabs(h) * sqrt(1.0 + fh*fh);
3561: }
3562: else {
3563: double hf = h/f;
3564: z = (f!=0.0 ? fabs(f)*sqrt(1.0+hf*hf) : 0.0);
3565: }
3566: /* e[i-1] = z; */
3567: e[i-1] = z;
3568: #ifdef DEBUGPRAXQR
3569: 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]);
3570: #endif
3571: if (z == 0.0)
3572: f = z = 1.0;
3573: c = f/z; s = h/z;
3574: f = x*c + g*s; g = - x*s + g*c; h = y*s;
3575: y *= c;
3576: /* for (j=0; j<n; j++) { */
3577: /* x = ab[j][i-1]; z = ab[j][i]; */
3578: /* ab[j][i-1] = x*c + z*s; */
3579: /* ab[j][i] = - x*s + z*c; */
3580: /* } */
3581: for (j=1; j<=n; j++) {
3582: x = ab[j][i-1]; z = ab[j][i];
3583: ab[j][i-1] = x*c + z*s;
3584: ab[j][i] = - x*s + z*c;
3585: }
3586: if (fabs(f) < fabs(h)) {
3587: double fh = f/h;
3588: z = fabs(h) * sqrt(1.0 + fh*fh);
3589: }
3590: else {
3591: double hf = h/f;
3592: z = (f!=0.0 ? fabs(f)*sqrt(1.0+hf*hf) : 0.0);
3593: }
3594: #ifdef DEBUGPRAXQR
3595: printf(" qr transformation z f h=%.7g %.7g %.7g i=%d k=%d\n",z,f,h, i, k);
3596: #endif
3597: q[i-1] = z;
3598: if (z == 0.0)
3599: z = f = 1.0;
3600: c = f/z; s = h/z;
3601: f = c*g + s*y; /* f can be very small */
3602: x = - s*g + c*y;
3603: }
3604: /* e[l] = 0.0; e[k] = f; q[k] = x; */
3605: e[l] = 0.0; e[k] = f; q[k] = x;
3606: #ifdef DEBUGPRAXQR
3607: 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);
3608: #endif
3609: goto TestFsplitting;
3610: Convergence:
3611: #ifdef DEBUGPRAX
3612: printf(" Convergence:\n");
3613: #endif
3614: if (z < 0.0) {
3615: /* q[k] = - z; */
3616: /* for (j=0; j<n; j++) ab[j][k] = - ab[j][k]; */
3617: q[k] = - z;
3618: for (j=1; j<=n; j++) ab[j][k] = - ab[j][k];
3619: }/* END Z */
3620: }/* END K */
3621: } /* END MINFIT */
3622:
3623:
3624: double praxis(double tol, double macheps, double h0, int _n, int _prin, double *_x, double (*_fun)(double *_x))
3625: /* double praxis(double tol, double macheps, double h0, int _n, int _prin, double *_x, double (*_fun)(double *_x, int _n)) */
3626: /* double praxis(double (*_fun)(), double _x[], int _n) */
3627: /* double (*_fun)(); */
3628: /* double _x[N]; */
3629: /* double (*_fun)(); */
3630: /* double _x[N]; */
3631: {
3632: /* init global extern variables and parameters */
3633: /* double *d, *y, *z, */
3634: /* *q0, *q1, **v; */
3635: /* double *tflin; /\* used in flin: return (*fun)(tflin, n); *\/ */
3636: /* double *e; /\* used in minfit, don't konw how to free memory and thus made global *\/ */
3637:
3638:
3639: int seed; /* added */
3640: int biter=0;
3641: double r;
3642: double randbrent( int (*));
3643: double s, sf;
3644:
3645: h = h0; /* step; */
3646: t = tol;
3647: scbd = 1.0;
3648: illc = 0;
3649: ktm = 1;
3650:
3651: macheps = DBL_EPSILON;
3652: /* prin=4; */
3653: #ifdef DEBUGPRAX
3654: printf("Praxis macheps=%14g h=%14g step=%14g tol=%14g\n",macheps,h, h0,tol);
3655: #endif
3656: n = _n;
3657: x = _x;
3658: prin = _prin;
3659: fun = _fun;
3660: d=vector(1, n);
3661: y=vector(1, n);
3662: z=vector(1, n);
3663: q0=vector(1, n);
3664: q1=vector(1, n);
3665: e=vector(1, n);
3666: tflin=vector(1, n);
3667: v=matrix(1, n, 1, n);
3668: for(i=1;i<=n;i++){d[i]=y[i]=z[i]=q0[0]=e[i]=tflin[i]=0.;}
3669: small_windows = (macheps) * (macheps); vsmall = small_windows*small_windows;
3670: large = 1.0/small_windows; vlarge = 1.0/vsmall;
3671: m2 = sqrt(macheps); m4 = sqrt(m2);
3672: seed = 123456789; /* added */
3673: ldfac = (illc ? 0.1 : 0.01);
3674: for(i=1;i<=n;i++) z[i]=0.; /* Was missing in Gegenfurtner as well as Brent's algol or fortran */
3675: nl = kt = 0; nf = 1;
3676: #ifdef NR_SHIFT
3677: fx = (*fun)((x-1), n);
3678: #else
3679: fx = (*fun)(x);
3680: #endif
3681: qf1 = fx;
3682: t2 = small_windows + fabs(t); t = t2; dmin = small_windows;
3683: #ifdef DEBUGPRAX
3684: printf("praxis2 macheps=%14g h=%14g step=%14g small=%14g t=%14g\n",macheps,h, h0,small_windows, t);
3685: #endif
3686: if (h < 100.0*t) h = 100.0*t;
3687: #ifdef DEBUGPRAX
3688: printf("praxis3 macheps=%14g h=%14g step=%14g small=%14g t=%14g\n",macheps,h, h0,small_windows, t);
3689: #endif
3690: ldt = h;
3691: /* for (i=0; i<n; i++) for (j=0; j<n; j++) */
3692: for (i=1; i<=n; i++) for (j=1; j<=n; j++)
3693: v[i][j] = (i == j ? 1.0 : 0.0);
3694: d[1] = 0.0; qd0 = 0.0;
3695: /* for (i=0; i<n; i++) q1[i] = x[i]; */
3696: for (i=1; i<=n; i++) q1[i] = x[i];
3697: if (prin > 1) {
3698: printf("\n------------- enter function praxis -----------\n");
3699: printf("... current parameter settings ...\n");
3700: printf("... scaling ... %20.10e\n", scbd);
3701: printf("... tol ... %20.10e\n", t);
3702: printf("... maxstep ... %20.10e\n", h);
3703: printf("... illc ... %20u\n", illc);
3704: printf("... ktm ... %20u\n", ktm);
3705: printf("... maxfun ... %20u\n", maxfun);
3706: }
3707: if (prin) print2();
3708:
3709: mloop:
3710: biter++; /* Added to count the loops */
3711: /* sf = d[0]; */
3712: /* s = d[0] = 0.0; */
3713: printf("\n Big iteration %d \n",biter);
3714: fprintf(ficlog,"\n Big iteration %d \n",biter);
3715: sf = d[1];
3716: s = d[1] = 0.0;
3717:
3718: /* minimize along first direction V(*,1) */
3719: #ifdef DEBUGPRAX
3720: printf(" Minimize along the first direction V(*,1). illc=%d\n",illc);
3721: /* fprintf(ficlog," Minimize along the first direction V(*,1).\n"); */
3722: #endif
3723: #ifdef DEBUGPRAX2
3724: printf("praxis4 macheps=%14g h=%14g step=%14g small=%14g t=%14g\n",macheps,h, h0,small_windows, t);
3725: #endif
3726: /* min(0, 2, &d[0], &s, fx, 0); /\* mac heps not global *\/ */
1.362 brouard 3727: 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 3728: #ifdef DEBUGPRAX
3729: printf("praxis5 macheps=%14g h=%14g looks at sign of s=%14g fx=%14g\n",macheps,h, s,fx);
3730: #endif
3731: if (s <= 0.0)
3732: /* for (i=0; i < n; i++) */
3733: for (i=1; i <= n; i++)
3734: v[i][1] = -v[i][1];
3735: /* if ((sf <= (0.9 * d[0])) || ((0.9 * sf) >= d[0])) */
3736: if ((sf <= (0.9 * d[1])) || ((0.9 * sf) >= d[1]))
3737: /* for (i=1; i<n; i++) */
3738: for (i=2; i<=n; i++)
3739: d[i] = 0.0;
3740: /* for (k=1; k<n; k++) { */
3741: for (k=2; k<=n; k++) {
3742: /*
3743: The inner loop starts here.
3744: */
3745: #ifdef DEBUGPRAX
3746: printf(" The inner loop here from k=%d to n=%d.\n",k,n);
3747: /* fprintf(ficlog," The inner loop here from k=%d to n=%d.\n",k,n); */
3748: #endif
3749: /* for (i=0; i<n; i++) */
3750: for (i=1; i<=n; i++)
3751: y[i] = x[i];
3752: sf = fx;
3753: #ifdef DEBUGPRAX
3754: printf(" illc=%d and kt=%d and ktm=%d\n", illc, kt, ktm);
3755: #endif
3756: illc = illc || (kt > 0);
3757: next:
3758: kl = k;
3759: df = 0.0;
3760: if (illc) { /* random step to get off resolution valley */
3761: #ifdef DEBUGPRAX
3762: printf(" A random step follows, to avoid resolution valleys.\n");
3763: matprint(" before rand, vectors:",v,n,n);
3764: #endif
3765: for (i=1; i<=n; i++) {
3766: #ifdef NOBRENTRAND
3767: r = drandom();
3768: #else
3769: seed=i;
3770: /* seed=i+1; */
3771: #ifdef DEBUGRAND
3772: printf(" Random seed=%d, brent i=%d",seed,i); /* YYYY i=5 j=1 vji= -0.0001170073 */
3773: #endif
3774: r = randbrent ( &seed );
3775: #endif
3776: #ifdef DEBUGRAND
3777: printf(" Random r=%.7g \n",r);
3778: #endif
3779: z[i] = (0.1 * ldt + t2 * pow(10.0,(double)kt)) * (r - 0.5);
3780: /* z[i] = (0.1 * ldt + t2 * pow(10.0,(double)kt)) * (drandom() - 0.5); */
3781:
3782: s = z[i];
3783: for (j=1; j <= n; j++)
3784: x[j] += s * v[j][i];
3785: }
3786: #ifdef DEBUGRAND
3787: matprint(" after rand, vectors:",v,n,n);
3788: #endif
3789: #ifdef NR_SHIFT
3790: fx = (*fun)((x-1), n);
3791: #else
3792: fx = (*fun)(x, n);
3793: #endif
3794: /* fx = (*func) ( (x-1) ); *//* This for func which is computed from x[1] and not from x[0] xm1=(x-1)*/
3795: nf++;
3796: }
3797: /* minimize along non-conjugate directions */
3798: #ifdef DEBUGPRAX
3799: printf(" Minimize along the 'non-conjugate' directions (dots printed) V(*,%d),...,V(*,%d).\n",k,n);
3800: /* fprintf(ficlog," Minimize along the 'non-conjugate' directions (dots printed) V(*,%d),...,V(*,%d).\n",k,n); */
3801: #endif
3802: /* for (k2=k; k2<n; k2++) { /\* Be careful here k2 <=n ? *\/ */
3803: for (k2=k; k2<=n; k2++) { /* Be careful here k2 <=n ? */
3804: sl = fx;
3805: s = 0.0;
3806: #ifdef DEBUGPRAX
3807: printf(" Minimize along the 'NON-CONJUGATE' true direction k2=%14d fx=%14.7f\n",k2, fx);
3808: matprint(" before min vectors:",v,n,n);
3809: #endif
3810: /* min(k2, 2, &d[k2], &s, fx, 0); */
3811: /* jsearch=k2-1; */
3812: /* min(jsearch, 2, &d[jsearch], &s, fx, 0); */
3813: minny(k2, 2, &d[k2], &s, fx, 0);
3814: #ifdef DEBUGPRAX
3815: 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);
3816: #endif
3817: if (illc) {
3818: /* double szk = s + z[k2]; */
3819: /* s = d[k2] * szk*szk; */
3820: double szk = s + z[k2];
3821: s = d[k2] * szk*szk;
3822: }
3823: else
3824: s = sl - fx;
3825: /* if (df < s) { */
3826: if (df <= s) {
3827: df = s;
3828: kl = k2;
3829: #ifdef DEBUGPRAX
3830: printf(" df=%.7g and choose kl=%d \n",df,kl); /* UUUU */
3831: #endif
3832: }
3833: } /* end loop k2 */
3834: /*
3835: If there was not much improvement on the first try, set
3836: ILLC = true and start the inner loop again.
3837: */
3838: #ifdef DEBUGPRAX
3839: printf(" If there was not much improvement on the first try, set ILLC = true and start the inner loop again. illc=%d\n",illc);
3840: /* fprintf(ficlog," If there was not much improvement on the first try, set ILLC = true and start the inner loop again.\n"); */
3841: #endif
3842: if (!illc && (df < fabs(100.0 * (macheps) * fx))) {
3843: #ifdef DEBUGPRAX
3844: 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);
3845: #endif
3846: illc = 1;
3847: goto next;
3848: }
3849: #ifdef DEBUGPRAX
3850: 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);
3851: #endif
3852:
3853: /* if ((k == 1) && (prin > 1)){ /\* be careful k=2 *\/ */
3854: if ((k == 2) && (prin > 1)){ /* be careful k=2 */
3855: #ifdef DEBUGPRAX
3856: printf(" NEW D The second difference array d:\n" );
3857: /* fprintf(ficlog, " NEW D The second difference array d:\n" ); */
3858: #endif
3859: vecprint(" NEW D The second difference array d:",d,n);
3860: }
3861: /* minimize along conjugate directions */
3862: /*
3863: Minimize along the "conjugate" directions V(*,1),...,V(*,K-1).
3864: */
3865: #ifdef DEBUGPRAX
3866: printf("Minimize along the 'conjugate' directions V(*,1),...,V(*,K-1=%d).\n",k-1);
3867: /* fprintf(ficlog,"Minimize along the 'conjugate' directions V(*,1),...,V(*,K-1=%d).\n",k-1); */
3868: #endif
3869: /* for (k2=0; k2<=k-1; k2++) { */
3870: for (k2=1; k2<=k-1; k2++) {
3871: s = 0.0;
3872: /* min(k2-1, 2, &d[k2-1], &s, fx, 0); */
3873: minny(k2, 2, &d[k2], &s, fx, 0);
3874: }
3875: f1 = fx;
3876: fx = sf;
3877: lds = 0.0;
3878: /* for (i=0; i<n; i++) { */
3879: for (i=1; i<=n; i++) {
3880: sl = x[i];
3881: x[i] = y[i];
3882: y[i] = sl - y[i];
3883: sl = y[i];
3884: lds = lds + sl*sl;
3885: }
3886: lds = sqrt(lds);
3887: #ifdef DEBUGPRAX
3888: printf("Minimization done 'conjugate', shifted all points, computed lds=%.8f\n",lds);
3889: #endif
3890: /*
3891: Discard direction V(*,kl).
3892:
3893: If no random step was taken, V(*,KL) is the "non-conjugate"
3894: direction along which the greatest improvement was made.
3895: */
3896: if (lds > small_windows) {
3897: #ifdef DEBUGPRAX
3898: 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);
3899: matprint(" before shift new conjugate vectors:",v,n,n);
3900: #endif
3901: for (i=kl-1; i>=k; i--) {
3902: /* for (j=0; j < n; j++) */
3903: for (j=1; j <= n; j++)
3904: /* v[j][i+1] = v[j][i]; */ /* This is v[j][i+1]=v[j][i] i=kl-1 to k */
3905: v[j][i+1] = v[j][i]; /* This is v[j][i+1]=v[j][i] i=kl-1 to k */
3906: /* v[j][i+1] = v[j][i]; */
3907: /* d[i+1] = d[i];*/ /* last is d[k+1]= d[k] */
3908: d[i+1] = d[i]; /* last is d[k]= d[k-1] */
3909: }
3910: #ifdef DEBUGPRAX
3911: matprint(" after shift new conjugate vectors:",v,n,n);
3912: #endif /* d[k] = 0.0; */
3913: d[k] = 0.0;
3914: for (i=1; i <= n; i++)
3915: v[i][k] = y[i] / lds;
3916: /* v[i][k] = y[i] / lds; */
3917: #ifdef DEBUGPRAX
3918: 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);
3919: /* fprintf(ficlog,"Minimize along the new 'conjugate' direction V(*,k=%d), which is the normalized vector: (new x) - (old x).\n",k); */
3920: matprint(" before min new conjugate vectors:",v,n,n);
3921: #endif
3922: /* min(k-1, 4, &d[k-1], &lds, f1, 1); */
3923: minny(k, 4, &d[k], &lds, f1, 1);
3924: #ifdef DEBUGPRAX
3925: printf(" after min d(k)=%d %.7g lds=%14f\n",k,d[k],lds);
3926: matprint(" after min vectors:",v,n,n);
3927: #endif
3928: if (lds <= 0.0) {
3929: lds = -lds;
3930: #ifdef DEBUGPRAX
3931: printf(" lds changed sign lds=%.14f k=%d\n",lds,k);
3932: #endif
3933: /* for (i=0; i<n; i++) */
3934: /* v[i][k] = -v[i][k]; */
3935: for (i=1; i<=n; i++)
3936: v[i][k] = -v[i][k];
3937: }
3938: }
3939: ldt = ldfac * ldt;
3940: if (ldt < lds)
3941: ldt = lds;
3942: if (prin > 0){
3943: #ifdef DEBUGPRAX
3944: printf(" k=%d",k);
3945: /* fprintf(ficlog," k=%d",k); */
3946: #endif
3947: print2();/* n, x, prin, fx, nf, nl ); */
3948: }
3949: t2 = 0.0;
3950: /* for (i=0; i<n; i++) */
3951: for (i=1; i<=n; i++)
3952: t2 += x[i]*x[i];
3953: t2 = m2 * sqrt(t2) + t;
3954: /*
3955: See whether the length of the step taken since starting the
3956: inner loop exceeds half the tolerance.
3957: */
3958: #ifdef DEBUGPRAX
3959: printf("See if step length exceeds half the tolerance.\n"); /* ZZZZZ */
3960: /* fprintf(ficlog,"See if step length exceeds half the tolerance.\n"); */
3961: #endif
3962: if (ldt > (0.5 * t2))
3963: kt = 0;
3964: else
3965: kt++;
3966: #ifdef DEBUGPRAX
3967: printf("if kt=%d >? ktm=%d gotoL2 loop\n",kt,ktm);
3968: #endif
3969: if (kt > ktm){
3970: if ( 0 < prin ){
3971: /* printf("\nr8vec_print\n X:\n"); */
3972: /* fprintf(ficlog,"\nr8vec_print\n X:\n"); */
3973: vecprint ("END X:", x, n );
3974: }
3975: goto fret;
3976: }
3977: #ifdef DEBUGPRAX
3978: matprint(" end of L2 loop vectors:",v,n,n);
3979: #endif
3980:
3981: }
3982: /* printf("The inner loop ends here.\n"); */
3983: /* fprintf(ficlog,"The inner loop ends here.\n"); */
3984: /*
3985: The inner loop ends here.
3986:
3987: Try quadratic extrapolation in case we are in a curved valley.
3988: */
3989: #ifdef DEBUGPRAX
3990: printf("Try QUAD ratic extrapolation in case we are in a curved valley.\n");
3991: #endif
3992: /* try quadratic extrapolation in case */
3993: /* we are stuck in a curved valley */
3994: quad();
3995: dn = 0.0;
3996: /* for (i=0; i<n; i++) { */
3997: for (i=1; i<=n; i++) {
3998: d[i] = 1.0 / sqrt(d[i]);
3999: if (dn < d[i])
4000: dn = d[i];
4001: }
4002: if (prin > 2)
4003: matprint(" NEW DIRECTIONS vectors:",v,n,n);
4004: /* for (j=0; j<n; j++) { */
4005: for (j=1; j<=n; j++) {
4006: s = d[j] / dn;
4007: /* for (i=0; i < n; i++) */
4008: for (i=1; i <= n; i++)
4009: v[i][j] *= s;
4010: }
4011:
4012: if (scbd > 1.0) { /* scale axis to reduce condition number */
4013: #ifdef DEBUGPRAX
4014: printf("Scale the axes to try to reduce the condition number.\n");
4015: #endif
4016: /* fprintf(ficlog,"Scale the axes to try to reduce the condition number.\n"); */
4017: s = vlarge;
4018: /* for (i=0; i<n; i++) { */
4019: for (i=1; i<=n; i++) {
4020: sl = 0.0;
4021: /* for (j=0; j < n; j++) */
4022: for (j=1; j <= n; j++)
4023: sl += v[i][j]*v[i][j];
4024: z[i] = sqrt(sl);
4025: if (z[i] < m4)
4026: z[i] = m4;
4027: if (s > z[i])
4028: s = z[i];
4029: }
4030: /* for (i=0; i<n; i++) { */
4031: for (i=1; i<=n; i++) {
4032: sl = s / z[i];
4033: z[i] = 1.0 / sl;
4034: if (z[i] > scbd) {
4035: sl = 1.0 / scbd;
4036: z[i] = scbd;
4037: }
4038: }
4039: }
4040: for (i=1; i<=n; i++)
4041: /* for (j=0; j<=i-1; j++) { */
4042: /* for (j=1; j<=i; j++) { */
4043: for (j=1; j<=i-1; j++) {
4044: s = v[i][j];
4045: v[i][j] = v[j][i];
4046: v[j][i] = s;
4047: }
4048: #ifdef DEBUGPRAX
4049: printf(" Calculate a new set of orthogonal directions before repeating the main loop.\n Transpose V for MINFIT:...\n");
4050: #endif
4051: /*
4052: MINFIT finds the singular value decomposition of V.
4053:
4054: This gives the principal values and principal directions of the
4055: approximating quadratic form without squaring the condition number.
4056: */
4057: #ifdef DEBUGPRAX
4058: 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");
4059: #endif
4060:
4061: minfit(n, macheps, vsmall, v, d);
4062: /* for(i=0; i<n;i++)printf(" %14.7g",d[i]); */
4063: /* v is overwritten with R. */
4064: /*
4065: Unscale the axes.
4066: */
4067: if (scbd > 1.0) {
4068: #ifdef DEBUGPRAX
4069: printf(" Unscale the axes.\n");
4070: #endif
4071: /* for (i=0; i<n; i++) { */
4072: for (i=1; i<=n; i++) {
4073: s = z[i];
4074: /* for (j=0; j<n; j++) */
4075: for (j=1; j<=n; j++)
4076: v[i][j] *= s;
4077: }
4078: /* for (i=0; i<n; i++) { */
4079: for (i=1; i<=n; i++) {
4080: s = 0.0;
4081: /* for (j=0; j<n; j++) */
4082: for (j=1; j<=n; j++)
4083: s += v[j][i]*v[j][i];
4084: s = sqrt(s);
4085: d[i] *= s;
4086: s = 1.0 / s;
4087: /* for (j=0; j<n; j++) */
4088: for (j=1; j<=n; j++)
4089: v[j][i] *= s;
4090: }
4091: }
4092: /* for (i=0; i<n; i++) { */
4093: double dni; /* added for compatibility with buckhardt but not brent */
4094: for (i=1; i<=n; i++) {
4095: dni=dn*d[i]; /* added for compatibility with buckhardt but not brent */
4096: if ((dn * d[i]) > large)
4097: d[i] = vsmall;
4098: else if ((dn * d[i]) < small_windows)
4099: d[i] = vlarge;
4100: else
4101: d[i] = 1.0 / dni / dni; /* added for compatibility with buckhardt but not brent */
4102: /* d[i] = pow(dn * d[i],-2.0); */
4103: }
4104: #ifdef DEBUGPRAX
4105: vecprint ("\n Before sort Eigenvalues of a:",d,n );
4106: #endif
4107:
4108: sort(); /* the new eigenvalues and eigenvectors */
4109: #ifdef DEBUGPRAX
4110: vecprint( " After sort the eigenvalues ....\n", d, n);
4111: matprint( " After sort the eigenvectors....\n", v, n,n);
4112: #endif
4113: #ifdef DEBUGPRAX
4114: printf(" Determine the smallest eigenvalue.\n");
4115: #endif
4116: /* dmin = d[n-1]; */
4117: dmin = d[n];
4118: if (dmin < small_windows)
4119: dmin = small_windows;
4120: /*
4121: The ratio of the smallest to largest eigenvalue determines whether
4122: the system is ill conditioned.
4123: */
4124:
4125: /* illc = (m2 * d[0]) > dmin; */
4126: illc = (m2 * d[1]) > dmin;
4127: #ifdef DEBUGPRAX
4128: 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]);
4129: #endif
4130:
4131: if ((prin > 2) && (scbd > 1.0))
4132: vecprint("\n The scale factors:",z,n);
4133: if (prin > 2)
4134: vecprint(" Principal values (EIGEN VALUES OF A) of the quadratic form:",d,n);
4135: if (prin > 2)
4136: matprint(" The principal axes (EIGEN VECTORS OF A:",v,n, n);
4137:
4138: if ((maxfun > 0) && (nf > maxfun)) {
4139: if (prin)
4140: printf("\n... maximum number of function calls reached ...\n");
4141: goto fret;
4142: }
4143: #ifdef DEBUGPRAX
4144: printf("Goto main loop\n");
4145: #endif
4146: goto mloop; /* back to main loop */
4147:
4148: fret:
4149: if (prin > 0) {
4150: vecprint("\n X:", x, n);
4151: /* printf("\n... ChiSq reduced to %20.10e ...\n", fx); */
4152: /* printf("... after %20u function calls.\n", nf); */
4153: }
4154: free_vector(d, 1, n);
4155: free_vector(y, 1, n);
4156: free_vector(z, 1, n);
4157: free_vector(q0, 1, n);
4158: free_vector(q1, 1, n);
4159: free_matrix(v, 1, n, 1, n);
4160: /* double *d, *y, *z, */
4161: /* *q0, *q1, **v; */
4162: free_vector(tflin, 1, n);
4163: /* double *tflin; /\* used in flin: return (*fun)(tflin, n); *\/ */
4164: free_vector(e, 1, n);
4165: /* double *e; /\* used in minfit, don't konw how to free memory and thus made global *\/ */
4166:
4167: return(fx);
4168: }
4169:
4170: /* end praxis gegen */
1.126 brouard 4171:
4172: /*************** powell ************************/
1.162 brouard 4173: /*
1.317 brouard 4174: Minimization of a function func of n variables. Input consists in an initial starting point
4175: p[1..n] ; an initial matrix xi[1..n][1..n] whose columns contain the initial set of di-
4176: rections (usually the n unit vectors); and ftol, the fractional tolerance in the function value
4177: such that failure to decrease by more than this amount in one iteration signals doneness. On
1.162 brouard 4178: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
4179: function value at p , and iter is the number of iterations taken. The routine linmin is used.
4180: */
1.224 brouard 4181: #ifdef LINMINORIGINAL
4182: #else
4183: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 4184: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 4185: #endif
1.126 brouard 4186: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
4187: double (*func)(double []))
4188: {
1.224 brouard 4189: #ifdef LINMINORIGINAL
4190: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 4191: double (*func)(double []));
1.224 brouard 4192: #else
1.241 brouard 4193: void linmin(double p[], double xi[], int n, double *fret,
4194: double (*func)(double []),int *flat);
1.224 brouard 4195: #endif
1.239 brouard 4196: int i,ibig,j,jk,k;
1.126 brouard 4197: double del,t,*pt,*ptt,*xit;
1.181 brouard 4198: double directest;
1.126 brouard 4199: double fp,fptt;
4200: double *xits;
4201: int niterf, itmp;
1.349 brouard 4202: int Bigter=0, nBigterf=1;
4203:
1.126 brouard 4204: pt=vector(1,n);
4205: ptt=vector(1,n);
4206: xit=vector(1,n);
4207: xits=vector(1,n);
4208: *fret=(*func)(p);
4209: for (j=1;j<=n;j++) pt[j]=p[j];
1.338 brouard 4210: rcurr_time = time(NULL);
4211: fp=(*fret); /* Initialisation */
1.126 brouard 4212: for (*iter=1;;++(*iter)) {
4213: ibig=0;
4214: del=0.0;
1.157 brouard 4215: rlast_time=rcurr_time;
1.349 brouard 4216: rlast_btime=rcurr_time;
1.157 brouard 4217: /* (void) gettimeofday(&curr_time,&tzp); */
4218: rcurr_time = time(NULL);
4219: curr_time = *localtime(&rcurr_time);
1.337 brouard 4220: /* 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); */
4221: /* 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 4222: /* Bigter=(*iter - *iter % ncovmodel)/ncovmodel +1; /\* Big iteration, i.e on ncovmodel cycle *\/ */
4223: Bigter=(*iter - (*iter-1) % n)/n +1; /* Big iteration, i.e on ncovmodel cycle */
1.349 brouard 4224: 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);
4225: 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);
4226: fprintf(ficrespow,"%d %d %.12f %d",*iter,Bigter, *fret,curr_time.tm_sec-start_time.tm_sec);
1.324 brouard 4227: fp=(*fret); /* From former iteration or initial value */
1.192 brouard 4228: for (i=1;i<=n;i++) {
1.126 brouard 4229: fprintf(ficrespow," %.12lf", p[i]);
4230: }
1.239 brouard 4231: fprintf(ficrespow,"\n");fflush(ficrespow);
4232: printf("\n#model= 1 + age ");
4233: fprintf(ficlog,"\n#model= 1 + age ");
4234: if(nagesqr==1){
1.241 brouard 4235: printf(" + age*age ");
4236: fprintf(ficlog," + age*age ");
1.239 brouard 4237: }
1.362 brouard 4238: for(j=1;j <=ncovmodel-2-nagesqr;j++){
1.239 brouard 4239: if(Typevar[j]==0) {
4240: printf(" + V%d ",Tvar[j]);
4241: fprintf(ficlog," + V%d ",Tvar[j]);
4242: }else if(Typevar[j]==1) {
4243: printf(" + V%d*age ",Tvar[j]);
4244: fprintf(ficlog," + V%d*age ",Tvar[j]);
4245: }else if(Typevar[j]==2) {
4246: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
4247: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 4248: }else if(Typevar[j]==3) {
4249: printf(" + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
4250: fprintf(ficlog," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.239 brouard 4251: }
4252: }
1.126 brouard 4253: printf("\n");
1.239 brouard 4254: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
4255: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 4256: fprintf(ficlog,"\n");
1.239 brouard 4257: for(i=1,jk=1; i <=nlstate; i++){
4258: for(k=1; k <=(nlstate+ndeath); k++){
4259: if (k != i) {
4260: printf("%d%d ",i,k);
4261: fprintf(ficlog,"%d%d ",i,k);
4262: for(j=1; j <=ncovmodel; j++){
4263: printf("%12.7f ",p[jk]);
4264: fprintf(ficlog,"%12.7f ",p[jk]);
4265: jk++;
4266: }
4267: printf("\n");
4268: fprintf(ficlog,"\n");
4269: }
4270: }
4271: }
1.241 brouard 4272: if(*iter <=3 && *iter >1){
1.157 brouard 4273: tml = *localtime(&rcurr_time);
4274: strcpy(strcurr,asctime(&tml));
4275: rforecast_time=rcurr_time;
1.126 brouard 4276: itmp = strlen(strcurr);
4277: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 4278: strcurr[itmp-1]='\0';
1.162 brouard 4279: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 4280: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.349 brouard 4281: for(nBigterf=1;nBigterf<=31;nBigterf+=10){
4282: niterf=nBigterf*ncovmodel;
4283: /* rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time); */
1.241 brouard 4284: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
4285: forecast_time = *localtime(&rforecast_time);
4286: strcpy(strfor,asctime(&forecast_time));
4287: itmp = strlen(strfor);
4288: if(strfor[itmp-1]=='\n')
4289: strfor[itmp-1]='\0';
1.349 brouard 4290: 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);
4291: 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 4292: }
4293: }
1.359 brouard 4294: for (i=1;i<=n;i++) { /* For each direction i, maximisation after loading directions */
4295: 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 */
4296:
4297: fptt=(*fret); /* Computes likelihood for parameters xit */
1.126 brouard 4298: #ifdef DEBUG
1.203 brouard 4299: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
4300: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 4301: #endif
1.203 brouard 4302: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 4303: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 4304: #ifdef LINMINORIGINAL
1.359 brouard 4305: linmin(p,xit,n,fret,func); /* New point i minimizing in direction xit, i has coordinates p[j].*/
1.357 brouard 4306: /* xit[j] gives the n coordinates of direction i as input.*/
4307: /* *fret gives the maximum value on direction xit */
1.224 brouard 4308: #else
4309: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.359 brouard 4310: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.224 brouard 4311: #endif
1.359 brouard 4312: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 4313: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.359 brouard 4314: /* because that direction will be replaced unless the gain del is small */
4315: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
4316: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
4317: /* with the new direction. */
4318: del=fabs(fptt-(*fret));
4319: ibig=i;
1.126 brouard 4320: }
4321: #ifdef DEBUG
4322: printf("%d %.12e",i,(*fret));
4323: fprintf(ficlog,"%d %.12e",i,(*fret));
4324: for (j=1;j<=n;j++) {
1.359 brouard 4325: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
4326: printf(" x(%d)=%.12e",j,xit[j]);
4327: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 4328: }
4329: for(j=1;j<=n;j++) {
1.359 brouard 4330: printf(" p(%d)=%.12e",j,p[j]);
4331: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 4332: }
4333: printf("\n");
4334: fprintf(ficlog,"\n");
4335: #endif
1.187 brouard 4336: } /* end loop on each direction i */
1.357 brouard 4337: /* Convergence test will use last linmin estimation (fret) and compare to former iteration (fp) */
1.188 brouard 4338: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.359 brouard 4339: /* New value of last point Pn is not computed, P(n-1) */
1.319 brouard 4340: for(j=1;j<=n;j++) {
4341: if(flatdir[j] >0){
4342: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
4343: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
1.302 brouard 4344: }
1.319 brouard 4345: /* printf("\n"); */
4346: /* fprintf(ficlog,"\n"); */
4347: }
1.243 brouard 4348: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
4349: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 4350: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
4351: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
4352: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
4353: /* decreased of more than 3.84 */
4354: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
4355: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
4356: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 4357:
1.188 brouard 4358: /* Starting the program with initial values given by a former maximization will simply change */
4359: /* the scales of the directions and the directions, because the are reset to canonical directions */
4360: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
4361: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 4362: #ifdef DEBUG
4363: int k[2],l;
4364: k[0]=1;
4365: k[1]=-1;
4366: printf("Max: %.12e",(*func)(p));
4367: fprintf(ficlog,"Max: %.12e",(*func)(p));
4368: for (j=1;j<=n;j++) {
4369: printf(" %.12e",p[j]);
4370: fprintf(ficlog," %.12e",p[j]);
4371: }
4372: printf("\n");
4373: fprintf(ficlog,"\n");
4374: for(l=0;l<=1;l++) {
4375: for (j=1;j<=n;j++) {
4376: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
4377: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
4378: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
4379: }
4380: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
4381: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
4382: }
4383: #endif
4384:
4385: free_vector(xit,1,n);
4386: free_vector(xits,1,n);
4387: free_vector(ptt,1,n);
4388: free_vector(pt,1,n);
4389: return;
1.192 brouard 4390: } /* enough precision */
1.240 brouard 4391: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.359 brouard 4392: 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 4393: ptt[j]=2.0*p[j]-pt[j];
1.359 brouard 4394: xit[j]=p[j]-pt[j]; /* Coordinate j of last direction xi_n=P_n-P_0 */
4395: #ifdef DEBUG
4396: printf("\n %d xit=%12.7g p=%12.7g pt=%12.7g ",j,xit[j],p[j],pt[j]);
4397: #endif
4398: pt[j]=p[j]; /* New P0 is Pn */
4399: }
4400: #ifdef DEBUG
4401: printf("\n");
4402: #endif
1.181 brouard 4403: fptt=(*func)(ptt); /* f_3 */
1.359 brouard 4404: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in directions until some iterations are done */
1.224 brouard 4405: if (*iter <=4) {
1.225 brouard 4406: #else
4407: #endif
1.224 brouard 4408: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 4409: #else
1.161 brouard 4410: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 4411: #endif
1.162 brouard 4412: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 4413: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 4414: /* Let f"(x2) be the 2nd derivative equal everywhere. */
4415: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
4416: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 4417: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
4418: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
4419: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 4420: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 4421: /* Even if f3 <f1, directest can be negative and t >0 */
4422: /* mu² and del² are equal when f3=f1 */
1.359 brouard 4423: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
4424: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
4425: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
4426: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 4427: #ifdef NRCORIGINAL
4428: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
4429: #else
4430: 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 4431: t= t- del*SQR(fp-fptt);
1.183 brouard 4432: #endif
1.202 brouard 4433: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 4434: #ifdef DEBUG
1.181 brouard 4435: 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);
4436: 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 4437: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
4438: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
4439: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
4440: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
4441: 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);
4442: 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);
4443: #endif
1.183 brouard 4444: #ifdef POWELLORIGINAL
4445: if (t < 0.0) { /* Then we use it for new direction */
1.361 brouard 4446: #else /* Not POWELLOriginal but Brouard's */
1.182 brouard 4447: if (directest*t < 0.0) { /* Contradiction between both tests */
1.359 brouard 4448: 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 4449: 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 4450: 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 4451: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
4452: }
1.361 brouard 4453: if (directest < 0.0) { /* Then we use (P0, Pn) for new direction Xi_n or Xi_iBig */
1.181 brouard 4454: #endif
1.191 brouard 4455: #ifdef DEBUGLINMIN
1.234 brouard 4456: printf("Before linmin in direction P%d-P0\n",n);
4457: for (j=1;j<=n;j++) {
4458: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
4459: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
4460: if(j % ncovmodel == 0){
4461: printf("\n");
4462: fprintf(ficlog,"\n");
4463: }
4464: }
1.224 brouard 4465: #endif
4466: #ifdef LINMINORIGINAL
1.234 brouard 4467: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 4468: #else
1.234 brouard 4469: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
4470: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 4471: #endif
1.234 brouard 4472:
1.191 brouard 4473: #ifdef DEBUGLINMIN
1.234 brouard 4474: for (j=1;j<=n;j++) {
4475: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
4476: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
4477: if(j % ncovmodel == 0){
4478: printf("\n");
4479: fprintf(ficlog,"\n");
4480: }
4481: }
1.224 brouard 4482: #endif
1.234 brouard 4483: for (j=1;j<=n;j++) {
4484: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
4485: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
4486: }
1.361 brouard 4487:
4488: /* #else */
4489: /* for (i=1;i<=n-1;i++) { */
4490: /* for (j=1;j<=n;j++) { */
4491: /* xi[j][i]=xi[j][i+1]; /\* Standard method of conjugate directions, not Powell who changes the nth direction by p0 pn . *\/ */
4492: /* } */
4493: /* } */
4494: /* for (j=1;j<=n;j++) { */
4495: /* xi[j][n]=xit[j]; /\* and this nth direction by the by the average p_0 p_n *\/ */
4496: /* } */
4497: /* /\* for (j=1;j<=n-1;j++) { *\/ */
4498: /* /\* xi[j][1]=xi[j][j+1]; /\\* Standard method of conjugate directions *\\/ *\/ */
4499: /* /\* xi[j][n]=xit[j]; /\\* and this nth direction by the by the average p_0 p_n *\\/ *\/ */
4500: /* /\* } *\/ */
4501: /* #endif */
1.224 brouard 4502: #ifdef LINMINORIGINAL
4503: #else
1.234 brouard 4504: for (j=1, flatd=0;j<=n;j++) {
4505: if(flatdir[j]>0)
4506: flatd++;
4507: }
4508: if(flatd >0){
1.255 brouard 4509: printf("%d flat directions: ",flatd);
4510: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 4511: for (j=1;j<=n;j++) {
4512: if(flatdir[j]>0){
4513: printf("%d ",j);
4514: fprintf(ficlog,"%d ",j);
4515: }
4516: }
4517: printf("\n");
4518: fprintf(ficlog,"\n");
1.319 brouard 4519: #ifdef FLATSUP
4520: free_vector(xit,1,n);
4521: free_vector(xits,1,n);
4522: free_vector(ptt,1,n);
4523: free_vector(pt,1,n);
4524: return;
4525: #endif
1.361 brouard 4526: } /* endif(flatd >0) */
4527: #endif /* LINMINORIGINAL */
1.234 brouard 4528: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
4529: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
4530:
1.126 brouard 4531: #ifdef DEBUG
1.234 brouard 4532: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
4533: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
4534: for(j=1;j<=n;j++){
4535: printf(" %lf",xit[j]);
4536: fprintf(ficlog," %lf",xit[j]);
4537: }
4538: printf("\n");
4539: fprintf(ficlog,"\n");
1.126 brouard 4540: #endif
1.192 brouard 4541: } /* end of t or directest negative */
1.359 brouard 4542: printf(" Directest is positive, P_n-P_0 does not increase the conjugacy. n=%d\n",n);
4543: fprintf(ficlog," Directest is positive, P_n-P_0 does not increase the conjugacy. n=%d\n",n);
1.224 brouard 4544: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 4545: #else
1.234 brouard 4546: } /* end if (fptt < fp) */
1.192 brouard 4547: #endif
1.225 brouard 4548: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 4549: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 4550: #else
1.224 brouard 4551: #endif
1.234 brouard 4552: } /* loop iteration */
1.126 brouard 4553: }
1.234 brouard 4554:
1.126 brouard 4555: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 4556:
1.235 brouard 4557: 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 4558: {
1.338 brouard 4559: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij . Nicely done
1.279 brouard 4560: * (and selected quantitative values in nres)
4561: * by left multiplying the unit
4562: * matrix by transitions matrix until convergence is reached with precision ftolpl
4563: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
4564: * Wx is row vector: population in state 1, population in state 2, population dead
4565: * or prevalence in state 1, prevalence in state 2, 0
4566: * newm is the matrix after multiplications, its rows are identical at a factor.
4567: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
4568: * Output is prlim.
4569: * Initial matrix pimij
4570: */
1.206 brouard 4571: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
4572: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
4573: /* 0, 0 , 1} */
4574: /*
4575: * and after some iteration: */
4576: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
4577: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
4578: /* 0, 0 , 1} */
4579: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
4580: /* {0.51571254859325999, 0.4842874514067399, */
4581: /* 0.51326036147820708, 0.48673963852179264} */
4582: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 4583:
1.332 brouard 4584: int i, ii,j,k, k1;
1.209 brouard 4585: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 4586: /* double **matprod2(); */ /* test */
1.218 brouard 4587: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 4588: double **newm;
1.209 brouard 4589: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 4590: int ncvloop=0;
1.288 brouard 4591: int first=0;
1.169 brouard 4592:
1.209 brouard 4593: min=vector(1,nlstate);
4594: max=vector(1,nlstate);
4595: meandiff=vector(1,nlstate);
4596:
1.218 brouard 4597: /* Starting with matrix unity */
1.126 brouard 4598: for (ii=1;ii<=nlstate+ndeath;ii++)
4599: for (j=1;j<=nlstate+ndeath;j++){
4600: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4601: }
1.169 brouard 4602:
4603: cov[1]=1.;
4604:
4605: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 4606: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 4607: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 4608: ncvloop++;
1.126 brouard 4609: newm=savm;
4610: /* Covariates have to be included here again */
1.138 brouard 4611: cov[2]=agefin;
1.319 brouard 4612: if(nagesqr==1){
4613: cov[3]= agefin*agefin;
4614: }
1.332 brouard 4615: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
4616: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
4617: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 4618: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 4619: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
4620: }else{
4621: cov[2+nagesqr+k1]=precov[nres][k1];
4622: }
4623: }/* End of loop on model equation */
4624:
4625: /* Start of old code (replaced by a loop on position in the model equation */
4626: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only of the model *\/ */
4627: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
4628: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; *\/ */
4629: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TnsdVar[TvarsD[k]])]; */
4630: /* /\* model = 1 +age + V1*V3 + age*V1 + V2 + V1 + age*V2 + V3 + V3*age + V1*V2 */
4631: /* * k 1 2 3 4 5 6 7 8 */
4632: /* *cov[] 1 2 3 4 5 6 7 8 9 10 */
4633: /* *TypeVar[k] 2 1 0 0 1 0 1 2 */
4634: /* *Dummy[k] 0 2 0 0 2 0 2 0 */
4635: /* *Tvar[k] 4 1 2 1 2 3 3 5 */
4636: /* *nsd=3 (1) (2) (3) */
4637: /* *TvarsD[nsd] [1]=2 1 3 */
4638: /* *TnsdVar [2]=2 [1]=1 [3]=3 */
4639: /* *TvarsDind[nsd](=k) [1]=3 [2]=4 [3]=6 */
4640: /* *Tage[] [1]=1 [2]=2 [3]=3 */
4641: /* *Tvard[] [1][1]=1 [2][1]=1 */
4642: /* * [1][2]=3 [2][2]=2 */
4643: /* *Tprod[](=k) [1]=1 [2]=8 */
4644: /* *TvarsDp(=Tvar) [1]=1 [2]=2 [3]=3 [4]=5 */
4645: /* *TvarD (=k) [1]=1 [2]=3 [3]=4 [3]=6 [4]=6 */
4646: /* *TvarsDpType */
4647: /* *si model= 1 + age + V3 + V2*age + V2 + V3*age */
4648: /* * nsd=1 (1) (2) */
4649: /* *TvarsD[nsd] 3 2 */
4650: /* *TnsdVar (3)=1 (2)=2 */
4651: /* *TvarsDind[nsd](=k) [1]=1 [2]=3 */
4652: /* *Tage[] [1]=2 [2]= 3 */
4653: /* *\/ */
4654: /* /\* cov[++k1]=nbcode[TvarsD[k]][codtabm(ij,k)]; *\/ */
4655: /* /\* 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)); *\/ */
4656: /* } */
4657: /* for (k=1; k<=nsq;k++) { /\* For single quantitative varying covariates only of the model *\/ */
4658: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
4659: /* /\* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline *\/ */
4660: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
4661: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][resultmodel[nres][k1]] */
4662: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
4663: /* /\* 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]); *\/ */
4664: /* } */
4665: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
4666: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
4667: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
4668: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
4669: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
4670: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
4671: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
4672: /* } */
4673: /* /\* 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]); *\/ */
4674: /* } */
4675: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
4676: /* /\* 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]); *\/ */
4677: /* if(Dummy[Tvard[k][1]]==0){ */
4678: /* if(Dummy[Tvard[k][2]]==0){ */
4679: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
4680: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
4681: /* }else{ */
4682: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
4683: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
4684: /* } */
4685: /* }else{ */
4686: /* if(Dummy[Tvard[k][2]]==0){ */
4687: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
4688: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
4689: /* }else{ */
4690: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
4691: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
4692: /* } */
4693: /* } */
4694: /* } /\* End product without age *\/ */
4695: /* ENd of old code */
1.138 brouard 4696: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
4697: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
4698: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 4699: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
4700: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.319 brouard 4701: /* age and covariate values of ij are in 'cov' */
1.142 brouard 4702: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 4703:
1.126 brouard 4704: savm=oldm;
4705: oldm=newm;
1.209 brouard 4706:
4707: for(j=1; j<=nlstate; j++){
4708: max[j]=0.;
4709: min[j]=1.;
4710: }
4711: for(i=1;i<=nlstate;i++){
4712: sumnew=0;
4713: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
4714: for(j=1; j<=nlstate; j++){
4715: prlim[i][j]= newm[i][j]/(1-sumnew);
4716: max[j]=FMAX(max[j],prlim[i][j]);
4717: min[j]=FMIN(min[j],prlim[i][j]);
4718: }
4719: }
4720:
1.126 brouard 4721: maxmax=0.;
1.209 brouard 4722: for(j=1; j<=nlstate; j++){
4723: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
4724: maxmax=FMAX(maxmax,meandiff[j]);
4725: /* 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 4726: } /* j loop */
1.203 brouard 4727: *ncvyear= (int)age- (int)agefin;
1.208 brouard 4728: /* 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 4729: if(maxmax < ftolpl){
1.209 brouard 4730: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
4731: free_vector(min,1,nlstate);
4732: free_vector(max,1,nlstate);
4733: free_vector(meandiff,1,nlstate);
1.126 brouard 4734: return prlim;
4735: }
1.288 brouard 4736: } /* agefin loop */
1.208 brouard 4737: /* After some age loop it doesn't converge */
1.288 brouard 4738: if(!first){
4739: first=1;
4740: 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 4741: 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);
4742: }else if (first >=1 && first <10){
4743: 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);
4744: first++;
4745: }else if (first ==10){
4746: 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);
4747: 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");
4748: fprintf(ficlog,"Warning: the stable prevalence no convergence; too many cases, giving up noticing, even in log file\n");
4749: first++;
1.288 brouard 4750: }
4751:
1.359 brouard 4752: /* Try to lower 'ftol', for example from 1.e-8 to 6.e-9.\n", ftolpl,
4753: * (int)age, (int)delaymax, (int)agefin, ncvloop,
4754: * (int)age-(int)agefin); */
1.209 brouard 4755: free_vector(min,1,nlstate);
4756: free_vector(max,1,nlstate);
4757: free_vector(meandiff,1,nlstate);
1.208 brouard 4758:
1.169 brouard 4759: return prlim; /* should not reach here */
1.126 brouard 4760: }
4761:
1.217 brouard 4762:
4763: /**** Back Prevalence limit (stable or period prevalence) ****************/
4764:
1.218 brouard 4765: /* 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) */
4766: /* 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 4767: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 4768: {
1.264 brouard 4769: /* 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 4770: matrix by transitions matrix until convergence is reached with precision ftolpl */
4771: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
4772: /* Wx is row vector: population in state 1, population in state 2, population dead */
4773: /* or prevalence in state 1, prevalence in state 2, 0 */
4774: /* newm is the matrix after multiplications, its rows are identical at a factor */
4775: /* Initial matrix pimij */
4776: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
4777: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
4778: /* 0, 0 , 1} */
4779: /*
4780: * and after some iteration: */
4781: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
4782: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
4783: /* 0, 0 , 1} */
4784: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
4785: /* {0.51571254859325999, 0.4842874514067399, */
4786: /* 0.51326036147820708, 0.48673963852179264} */
4787: /* If we start from prlim again, prlim tends to a constant matrix */
4788:
1.359 brouard 4789: int i, ii,j, k1;
1.247 brouard 4790: int first=0;
1.217 brouard 4791: double *min, *max, *meandiff, maxmax,sumnew=0.;
4792: /* double **matprod2(); */ /* test */
4793: double **out, cov[NCOVMAX+1], **bmij();
4794: double **newm;
1.218 brouard 4795: double **dnewm, **doldm, **dsavm; /* for use */
4796: double **oldm, **savm; /* for use */
4797:
1.217 brouard 4798: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
4799: int ncvloop=0;
4800:
4801: min=vector(1,nlstate);
4802: max=vector(1,nlstate);
4803: meandiff=vector(1,nlstate);
4804:
1.266 brouard 4805: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
4806: oldm=oldms; savm=savms;
4807:
4808: /* Starting with matrix unity */
4809: for (ii=1;ii<=nlstate+ndeath;ii++)
4810: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 4811: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4812: }
4813:
4814: cov[1]=1.;
4815:
4816: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
4817: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 4818: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 4819: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
4820: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 4821: ncvloop++;
1.218 brouard 4822: newm=savm; /* oldm should be kept from previous iteration or unity at start */
4823: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 4824: /* Covariates have to be included here again */
4825: cov[2]=agefin;
1.319 brouard 4826: if(nagesqr==1){
1.217 brouard 4827: cov[3]= agefin*agefin;;
1.319 brouard 4828: }
1.332 brouard 4829: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 4830: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 4831: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.242 brouard 4832: }else{
1.332 brouard 4833: cov[2+nagesqr+k1]=precov[nres][k1];
1.242 brouard 4834: }
1.332 brouard 4835: }/* End of loop on model equation */
4836:
4837: /* Old code */
4838:
4839: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
4840: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
4841: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; */
4842: /* /\* 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)); *\/ */
4843: /* } */
4844: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
4845: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
4846: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
4847: /* /\* /\\* 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])]); *\\/ *\/ */
4848: /* /\* } *\/ */
4849: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
4850: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
4851: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
4852: /* /\* 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]); *\/ */
4853: /* } */
4854: /* /\* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; *\/ */
4855: /* /\* for (k=1; k<=cptcovprod;k++) /\\* Useless *\\/ *\/ */
4856: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\\/ *\/ */
4857: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
4858: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
4859: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age *\\/ ERROR ???*\/ */
4860: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
4861: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
4862: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
4863: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
4864: /* } */
4865: /* /\* 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]); *\/ */
4866: /* } */
4867: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
4868: /* /\* 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]); *\/ */
4869: /* if(Dummy[Tvard[k][1]]==0){ */
4870: /* if(Dummy[Tvard[k][2]]==0){ */
4871: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
4872: /* }else{ */
4873: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
4874: /* } */
4875: /* }else{ */
4876: /* if(Dummy[Tvard[k][2]]==0){ */
4877: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
4878: /* }else{ */
4879: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
4880: /* } */
4881: /* } */
4882: /* } */
1.217 brouard 4883:
4884: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
4885: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
4886: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
4887: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
4888: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 4889: /* ij should be linked to the correct index of cov */
4890: /* age and covariate values ij are in 'cov', but we need to pass
4891: * ij for the observed prevalence at age and status and covariate
4892: * number: prevacurrent[(int)agefin][ii][ij]
4893: */
4894: /* 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 *\/ */
4895: /* 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 *\/ */
4896: 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 4897: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 4898: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
4899: /* for(i=1; i<=nlstate+ndeath; i++) { */
4900: /* printf("%d newm= ",i); */
4901: /* for(j=1;j<=nlstate+ndeath;j++) { */
4902: /* printf("%f ",newm[i][j]); */
4903: /* } */
4904: /* printf("oldm * "); */
4905: /* for(j=1;j<=nlstate+ndeath;j++) { */
4906: /* printf("%f ",oldm[i][j]); */
4907: /* } */
1.268 brouard 4908: /* printf(" bmmij "); */
1.266 brouard 4909: /* for(j=1;j<=nlstate+ndeath;j++) { */
4910: /* printf("%f ",pmmij[i][j]); */
4911: /* } */
4912: /* printf("\n"); */
4913: /* } */
4914: /* } */
1.217 brouard 4915: savm=oldm;
4916: oldm=newm;
1.266 brouard 4917:
1.217 brouard 4918: for(j=1; j<=nlstate; j++){
4919: max[j]=0.;
4920: min[j]=1.;
4921: }
4922: for(j=1; j<=nlstate; j++){
4923: for(i=1;i<=nlstate;i++){
1.234 brouard 4924: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
4925: bprlim[i][j]= newm[i][j];
4926: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
4927: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 4928: }
4929: }
1.218 brouard 4930:
1.217 brouard 4931: maxmax=0.;
4932: for(i=1; i<=nlstate; i++){
1.318 brouard 4933: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column, could be nan! */
1.217 brouard 4934: maxmax=FMAX(maxmax,meandiff[i]);
4935: /* 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 4936: } /* i loop */
1.217 brouard 4937: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 4938: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 4939: if(maxmax < ftolpl){
1.220 brouard 4940: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 4941: free_vector(min,1,nlstate);
4942: free_vector(max,1,nlstate);
4943: free_vector(meandiff,1,nlstate);
4944: return bprlim;
4945: }
1.288 brouard 4946: } /* agefin loop */
1.217 brouard 4947: /* After some age loop it doesn't converge */
1.288 brouard 4948: if(!first){
1.247 brouard 4949: first=1;
4950: 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\
4951: 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);
4952: }
4953: 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 4954: 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);
4955: /* 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); */
4956: free_vector(min,1,nlstate);
4957: free_vector(max,1,nlstate);
4958: free_vector(meandiff,1,nlstate);
4959:
4960: return bprlim; /* should not reach here */
4961: }
4962:
1.126 brouard 4963: /*************** transition probabilities ***************/
4964:
4965: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
4966: {
1.138 brouard 4967: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 4968: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 4969: model to the ncovmodel covariates (including constant and age).
4970: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
4971: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
4972: ncth covariate in the global vector x is given by the formula:
4973: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
4974: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
4975: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
4976: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 4977: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 4978: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 4979: Sum on j ps[i][j] should equal to 1.
1.138 brouard 4980: */
4981: double s1, lnpijopii;
1.126 brouard 4982: /*double t34;*/
1.164 brouard 4983: int i,j, nc, ii, jj;
1.126 brouard 4984:
1.223 brouard 4985: for(i=1; i<= nlstate; i++){
4986: for(j=1; j<i;j++){
4987: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
4988: /*lnpijopii += param[i][j][nc]*cov[nc];*/
4989: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
4990: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
4991: }
4992: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 4993: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 4994: }
4995: for(j=i+1; j<=nlstate+ndeath;j++){
4996: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
4997: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
4998: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
4999: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
5000: }
5001: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 5002: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 5003: }
5004: }
1.218 brouard 5005:
1.223 brouard 5006: for(i=1; i<= nlstate; i++){
5007: s1=0;
5008: for(j=1; j<i; j++){
1.339 brouard 5009: /* printf("debug1 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 5010: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
5011: }
5012: for(j=i+1; j<=nlstate+ndeath; j++){
1.339 brouard 5013: /* printf("debug2 %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: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
5017: ps[i][i]=1./(s1+1.);
5018: /* Computing other pijs */
5019: for(j=1; j<i; j++)
1.325 brouard 5020: ps[i][j]= exp(ps[i][j])*ps[i][i];/* Bug valgrind */
1.223 brouard 5021: for(j=i+1; j<=nlstate+ndeath; j++)
5022: ps[i][j]= exp(ps[i][j])*ps[i][i];
5023: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
5024: } /* end i */
1.218 brouard 5025:
1.223 brouard 5026: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
5027: for(jj=1; jj<= nlstate+ndeath; jj++){
5028: ps[ii][jj]=0;
5029: ps[ii][ii]=1;
5030: }
5031: }
1.294 brouard 5032:
5033:
1.223 brouard 5034: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
5035: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
5036: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
5037: /* } */
5038: /* printf("\n "); */
5039: /* } */
5040: /* printf("\n ");printf("%lf ",cov[2]);*/
5041: /*
5042: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 5043: goto end;*/
1.266 brouard 5044: return ps; /* Pointer is unchanged since its call */
1.126 brouard 5045: }
5046:
1.218 brouard 5047: /*************** backward transition probabilities ***************/
5048:
5049: /* 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 ) */
5050: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
5051: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
5052: {
1.302 brouard 5053: /* 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 5054: * 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 5055: */
1.359 brouard 5056: int ii, j;
1.222 brouard 5057:
1.359 brouard 5058: double **pmij();
1.222 brouard 5059: double sumnew=0.;
1.218 brouard 5060: double agefin;
1.292 brouard 5061: 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 5062: double **dnewm, **dsavm, **doldm;
5063: double **bbmij;
5064:
1.218 brouard 5065: doldm=ddoldms; /* global pointers */
1.222 brouard 5066: dnewm=ddnewms;
5067: dsavm=ddsavms;
1.318 brouard 5068:
5069: /* Debug */
5070: /* printf("Bmij ij=%d, cov[2}=%f\n", ij, cov[2]); */
1.222 brouard 5071: agefin=cov[2];
1.268 brouard 5072: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 5073: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 5074: the observed prevalence (with this covariate ij) at beginning of transition */
5075: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 5076:
5077: /* P_x */
1.325 brouard 5078: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm *//* Bug valgrind */
1.268 brouard 5079: /* outputs pmmij which is a stochastic matrix in row */
5080:
5081: /* Diag(w_x) */
1.292 brouard 5082: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 5083: sumnew=0.;
1.269 brouard 5084: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 5085: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.297 brouard 5086: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 5087: sumnew+=prevacurrent[(int)agefin][ii][ij];
5088: }
5089: if(sumnew >0.01){ /* At least some value in the prevalence */
5090: for (ii=1;ii<=nlstate+ndeath;ii++){
5091: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 5092: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 5093: }
5094: }else{
5095: for (ii=1;ii<=nlstate+ndeath;ii++){
5096: for (j=1;j<=nlstate+ndeath;j++)
5097: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
5098: }
5099: /* if(sumnew <0.9){ */
5100: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
5101: /* } */
5102: }
5103: k3=0.0; /* We put the last diagonal to 0 */
5104: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
5105: doldm[ii][ii]= k3;
5106: }
5107: /* End doldm, At the end doldm is diag[(w_i)] */
5108:
1.292 brouard 5109: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
5110: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 5111:
1.292 brouard 5112: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 5113: /* 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 5114: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 5115: sumnew=0.;
1.222 brouard 5116: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 5117: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 5118: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 5119: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 5120: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 5121: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 5122: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 5123: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 5124: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 5125: /* }else */
1.268 brouard 5126: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
5127: } /*End ii */
5128: } /* 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 */
5129:
1.292 brouard 5130: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 5131: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 5132: /* end bmij */
1.266 brouard 5133: return ps; /*pointer is unchanged */
1.218 brouard 5134: }
1.217 brouard 5135: /*************** transition probabilities ***************/
5136:
1.218 brouard 5137: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 5138: {
5139: /* According to parameters values stored in x and the covariate's values stored in cov,
5140: computes the probability to be observed in state j being in state i by appying the
5141: model to the ncovmodel covariates (including constant and age).
5142: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
5143: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
5144: ncth covariate in the global vector x is given by the formula:
5145: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
5146: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
5147: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
5148: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
5149: Outputs ps[i][j] the probability to be observed in j being in j according to
5150: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
5151: */
5152: double s1, lnpijopii;
5153: /*double t34;*/
5154: int i,j, nc, ii, jj;
5155:
1.234 brouard 5156: for(i=1; i<= nlstate; i++){
5157: for(j=1; j<i;j++){
5158: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
5159: /*lnpijopii += param[i][j][nc]*cov[nc];*/
5160: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
5161: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
5162: }
5163: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
5164: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
5165: }
5166: for(j=i+1; j<=nlstate+ndeath;j++){
5167: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
5168: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
5169: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
5170: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
5171: }
5172: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
5173: }
5174: }
5175:
5176: for(i=1; i<= nlstate; i++){
5177: s1=0;
5178: for(j=1; j<i; j++){
5179: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
5180: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
5181: }
5182: for(j=i+1; j<=nlstate+ndeath; j++){
5183: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
5184: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
5185: }
5186: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
5187: ps[i][i]=1./(s1+1.);
5188: /* Computing other pijs */
5189: for(j=1; j<i; j++)
5190: ps[i][j]= exp(ps[i][j])*ps[i][i];
5191: for(j=i+1; j<=nlstate+ndeath; j++)
5192: ps[i][j]= exp(ps[i][j])*ps[i][i];
5193: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
5194: } /* end i */
5195:
5196: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
5197: for(jj=1; jj<= nlstate+ndeath; jj++){
5198: ps[ii][jj]=0;
5199: ps[ii][ii]=1;
5200: }
5201: }
1.296 brouard 5202: /* Added for prevbcast */ /* Transposed matrix too */
1.234 brouard 5203: for(jj=1; jj<= nlstate+ndeath; jj++){
5204: s1=0.;
5205: for(ii=1; ii<= nlstate+ndeath; ii++){
5206: s1+=ps[ii][jj];
5207: }
5208: for(ii=1; ii<= nlstate; ii++){
5209: ps[ii][jj]=ps[ii][jj]/s1;
5210: }
5211: }
5212: /* Transposition */
5213: for(jj=1; jj<= nlstate+ndeath; jj++){
5214: for(ii=jj; ii<= nlstate+ndeath; ii++){
5215: s1=ps[ii][jj];
5216: ps[ii][jj]=ps[jj][ii];
5217: ps[jj][ii]=s1;
5218: }
5219: }
5220: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
5221: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
5222: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
5223: /* } */
5224: /* printf("\n "); */
5225: /* } */
5226: /* printf("\n ");printf("%lf ",cov[2]);*/
5227: /*
5228: for(i=1; i<= npar; i++) printf("%f ",x[i]);
5229: goto end;*/
5230: return ps;
1.217 brouard 5231: }
5232:
5233:
1.126 brouard 5234: /**************** Product of 2 matrices ******************/
5235:
1.145 brouard 5236: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 5237: {
5238: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
5239: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
5240: /* in, b, out are matrice of pointers which should have been initialized
5241: before: only the contents of out is modified. The function returns
5242: a pointer to pointers identical to out */
1.145 brouard 5243: int i, j, k;
1.126 brouard 5244: for(i=nrl; i<= nrh; i++)
1.145 brouard 5245: for(k=ncolol; k<=ncoloh; k++){
5246: out[i][k]=0.;
5247: for(j=ncl; j<=nch; j++)
5248: out[i][k] +=in[i][j]*b[j][k];
5249: }
1.126 brouard 5250: return out;
5251: }
5252:
5253:
5254: /************* Higher Matrix Product ***************/
5255:
1.235 brouard 5256: 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 5257: {
1.336 brouard 5258: /* Already optimized with precov.
5259: 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 5260: 'nhstepm*hstepm*stepm' months (i.e. until
5261: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
5262: nhstepm*hstepm matrices.
5263: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
5264: (typically every 2 years instead of every month which is too big
5265: for the memory).
5266: Model is determined by parameters x and covariates have to be
5267: included manually here.
5268:
5269: */
5270:
1.359 brouard 5271: int i, j, d, h, k1;
1.131 brouard 5272: double **out, cov[NCOVMAX+1];
1.126 brouard 5273: double **newm;
1.187 brouard 5274: double agexact;
1.359 brouard 5275: /*double agebegin, ageend;*/
1.126 brouard 5276:
5277: /* Hstepm could be zero and should return the unit matrix */
5278: for (i=1;i<=nlstate+ndeath;i++)
5279: for (j=1;j<=nlstate+ndeath;j++){
5280: oldm[i][j]=(i==j ? 1.0 : 0.0);
5281: po[i][j][0]=(i==j ? 1.0 : 0.0);
5282: }
5283: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
5284: for(h=1; h <=nhstepm; h++){
5285: for(d=1; d <=hstepm; d++){
5286: newm=savm;
5287: /* Covariates have to be included here again */
5288: cov[1]=1.;
1.214 brouard 5289: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 5290: cov[2]=agexact;
1.319 brouard 5291: if(nagesqr==1){
1.227 brouard 5292: cov[3]= agexact*agexact;
1.319 brouard 5293: }
1.330 brouard 5294: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
5295: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
5296: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 5297: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 5298: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
5299: }else{
5300: cov[2+nagesqr+k1]=precov[nres][k1];
5301: }
5302: }/* End of loop on model equation */
5303: /* Old code */
5304: /* if( Dummy[k1]==0 && Typevar[k1]==0 ){ /\* Single dummy *\/ */
5305: /* /\* V(Tvarsel)=Tvalsel=Tresult[nres][pos](value); V(Tvresult[nres][pos] (variable): V(variable)=value) *\/ */
5306: /* /\* for (k=1; k<=nsd;k++) { /\\* For single dummy covariates only *\\/ *\/ */
5307: /* /\* /\\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\\/ *\/ */
5308: /* /\* codtabm(ij,k) (1 & (ij-1) >> (k-1))+1 *\/ */
5309: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
5310: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
5311: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
5312: /* /\* nsd 1 2 3 *\/ /\* Counting single dummies covar fixed or tv *\/ */
5313: /* /\*TvarsD[nsd] 4 3 1 *\/ /\* ID of single dummy cova fixed or timevary*\/ */
5314: /* /\*TvarsDind[k] 2 3 9 *\/ /\* position K of single dummy cova *\/ */
5315: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];or [codtabm(ij,TnsdVar[TvarsD[k]] *\/ */
5316: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
5317: /* /\* 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]])); *\/ */
5318: /* 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); */
5319: /* printf("hpxij new Dummy precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
5320: /* }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /\* Single quantitative variables *\/ */
5321: /* /\* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline *\/ */
5322: /* cov[2+nagesqr+k1]=Tqresult[nres][resultmodel[nres][k1]]; */
5323: /* /\* for (k=1; k<=nsq;k++) { /\\* For single varying covariates only *\\/ *\/ */
5324: /* /\* /\\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\\/ *\/ */
5325: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
5326: /* 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]]); */
5327: /* printf("hpxij new Quanti precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
5328: /* }else if( Dummy[k1]==2 ){ /\* For dummy with age product *\/ */
5329: /* /\* Tvar[k1] Variable in the age product age*V1 is 1 *\/ */
5330: /* /\* [Tinvresult[nres][V1] is its value in the resultline nres *\/ */
5331: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvar[k1]]*cov[2]; */
5332: /* 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]); */
5333: /* printf("hpxij new Dummy with age product precov[nres=%d][k1=%d]=%.4f * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
5334:
5335: /* /\* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; *\/ */
5336: /* /\* for (k=1; k<=cptcovage;k++){ /\\* For product with age V1+V1*age +V4 +age*V3 *\\/ *\/ */
5337: /* /\* 1+2 Tage[1]=2 TVar[2]=1 Dummy[2]=2, Tage[2]=4 TVar[4]=3 Dummy[4]=3 quant*\/ */
5338: /* /\* *\/ */
1.330 brouard 5339: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
5340: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
5341: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
1.332 brouard 5342: /* /\*cptcovage=2 1 2 *\/ */
5343: /* /\*Tage[k]= 5 8 *\/ */
5344: /* }else if( Dummy[k1]==3 ){ /\* For quant with age product *\/ */
5345: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
5346: /* 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]]); */
5347: /* printf("hpxij new Quanti with age product precov[nres=%d][k1=%d] * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
5348: /* /\* if(Dummy[Tage[k]]== 2){ /\\* dummy with age *\\/ *\/ */
5349: /* /\* /\\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\\* dummy with age *\\\/ *\\/ *\/ */
5350: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\\/ *\/ */
5351: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\\/ *\/ */
5352: /* /\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\/ */
5353: /* /\* 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); *\/ */
5354: /* /\* } else if(Dummy[Tage[k]]== 3){ /\\* quantitative with age *\\/ *\/ */
5355: /* /\* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; *\/ */
5356: /* /\* } *\/ */
5357: /* /\* 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]); *\/ */
5358: /* }else if(Typevar[k1]==2 ){ /\* For product (not with age) *\/ */
5359: /* /\* for (k=1; k<=cptcovprod;k++){ /\\* For product without age *\\/ *\/ */
5360: /* /\* /\\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\\/ *\/ */
5361: /* /\* /\\* k 1 2 3 4 5 6 7 8 9 *\\/ *\/ */
5362: /* /\* /\\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\\/ *\/ */
5363: /* /\* /\\*cptcovprod=1 1 2 *\\/ *\/ */
5364: /* /\* /\\*Tprod[]= 4 7 *\\/ *\/ */
5365: /* /\* /\\*Tvard[][1] 4 1 *\\/ *\/ */
5366: /* /\* /\\*Tvard[][2] 3 2 *\\/ *\/ */
1.330 brouard 5367:
1.332 brouard 5368: /* /\* 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])]); *\/ */
5369: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
5370: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]]; */
5371: /* 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]]); */
5372: /* printf("hpxij new Product no age product precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
5373:
5374: /* /\* if(Dummy[Tvardk[k1][1]]==0){ *\/ */
5375: /* /\* if(Dummy[Tvardk[k1][2]]==0){ /\\* Product of dummies *\\/ *\/ */
5376: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
5377: /* /\* cov[2+nagesqr+k1]=Tinvresult[nres][Tvardk[k1][1]] * Tinvresult[nres][Tvardk[k1][2]]; *\/ */
5378: /* /\* 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]])]; *\/ */
5379: /* /\* }else{ /\\* Product of dummy by quantitative *\\/ *\/ */
5380: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,TnsdVar[Tvard[k][1]])] * Tqresult[nres][k]; *\/ */
5381: /* /\* cov[2+nagesqr+k1]=Tresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]]; *\/ */
5382: /* /\* } *\/ */
5383: /* /\* }else{ /\\* Product of quantitative by...*\\/ *\/ */
5384: /* /\* if(Dummy[Tvard[k][2]]==0){ /\\* quant by dummy *\\/ *\/ */
5385: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][Tvard[k][1]]; *\\/ *\/ */
5386: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
5387: /* /\* }else{ /\\* Product of two quant *\\/ *\/ */
5388: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\\/ *\/ */
5389: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
5390: /* /\* } *\/ */
5391: /* /\* }/\\*end of products quantitative *\\/ *\/ */
5392: /* }/\*end of products *\/ */
5393: /* } /\* End of loop on model equation *\/ */
1.235 brouard 5394: /* for (k=1; k<=cptcovn;k++) */
5395: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
5396: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
5397: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
5398: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
5399: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 5400:
5401:
1.126 brouard 5402: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
5403: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.319 brouard 5404: /* right multiplication of oldm by the current matrix */
1.126 brouard 5405: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
5406: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 5407: /* if((int)age == 70){ */
5408: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
5409: /* for(i=1; i<=nlstate+ndeath; i++) { */
5410: /* printf("%d pmmij ",i); */
5411: /* for(j=1;j<=nlstate+ndeath;j++) { */
5412: /* printf("%f ",pmmij[i][j]); */
5413: /* } */
5414: /* printf(" oldm "); */
5415: /* for(j=1;j<=nlstate+ndeath;j++) { */
5416: /* printf("%f ",oldm[i][j]); */
5417: /* } */
5418: /* printf("\n"); */
5419: /* } */
5420: /* } */
1.126 brouard 5421: savm=oldm;
5422: oldm=newm;
5423: }
5424: for(i=1; i<=nlstate+ndeath; i++)
5425: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 5426: po[i][j][h]=newm[i][j];
5427: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 5428: }
1.128 brouard 5429: /*printf("h=%d ",h);*/
1.126 brouard 5430: } /* end h */
1.267 brouard 5431: /* printf("\n H=%d \n",h); */
1.126 brouard 5432: return po;
5433: }
5434:
1.217 brouard 5435: /************* Higher Back Matrix Product ***************/
1.218 brouard 5436: /* 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 5437: 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 5438: {
1.332 brouard 5439: /* For dummy covariates given in each resultline (for historical, computes the corresponding combination ij),
5440: computes the transition matrix starting at age 'age' over
1.217 brouard 5441: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 5442: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
5443: nhstepm*hstepm matrices.
5444: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
5445: (typically every 2 years instead of every month which is too big
1.217 brouard 5446: for the memory).
1.218 brouard 5447: Model is determined by parameters x and covariates have to be
1.266 brouard 5448: included manually here. Then we use a call to bmij(x and cov)
5449: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 5450: */
1.217 brouard 5451:
1.359 brouard 5452: int i, j, d, h, k1;
1.266 brouard 5453: double **out, cov[NCOVMAX+1], **bmij();
5454: double **newm, ***newmm;
1.217 brouard 5455: double agexact;
1.359 brouard 5456: /*double agebegin, ageend;*/
1.222 brouard 5457: double **oldm, **savm;
1.217 brouard 5458:
1.266 brouard 5459: newmm=po; /* To be saved */
5460: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 5461: /* Hstepm could be zero and should return the unit matrix */
5462: for (i=1;i<=nlstate+ndeath;i++)
5463: for (j=1;j<=nlstate+ndeath;j++){
5464: oldm[i][j]=(i==j ? 1.0 : 0.0);
5465: po[i][j][0]=(i==j ? 1.0 : 0.0);
5466: }
5467: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
5468: for(h=1; h <=nhstepm; h++){
5469: for(d=1; d <=hstepm; d++){
5470: newm=savm;
5471: /* Covariates have to be included here again */
5472: cov[1]=1.;
1.271 brouard 5473: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 5474: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
1.318 brouard 5475: /* Debug */
5476: /* printf("hBxij age=%lf, agexact=%lf\n", age, agexact); */
1.217 brouard 5477: cov[2]=agexact;
1.332 brouard 5478: if(nagesqr==1){
1.222 brouard 5479: cov[3]= agexact*agexact;
1.332 brouard 5480: }
5481: /** New code */
5482: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 5483: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 5484: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.325 brouard 5485: }else{
1.332 brouard 5486: cov[2+nagesqr+k1]=precov[nres][k1];
1.325 brouard 5487: }
1.332 brouard 5488: }/* End of loop on model equation */
5489: /** End of new code */
5490: /** This was old code */
5491: /* for (k=1; k<=nsd;k++){ /\* For single dummy covariates only *\//\* cptcovn error *\/ */
5492: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
5493: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
5494: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])];/\* Bug valgrind *\/ */
5495: /* /\* 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)); *\/ */
5496: /* } */
5497: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
5498: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
5499: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
5500: /* /\* 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]); *\/ */
5501: /* } */
5502: /* for (k=1; k<=cptcovage;k++){ /\* Should start at cptcovn+1 *\//\* For product with age *\/ */
5503: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age error!!!*\\/ *\/ */
5504: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
5505: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
5506: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
5507: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
5508: /* } */
5509: /* /\* 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]); *\/ */
5510: /* } */
5511: /* for (k=1; k<=cptcovprod;k++){ /\* Useless because included in cptcovn *\/ */
5512: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])]*nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
5513: /* if(Dummy[Tvard[k][1]]==0){ */
5514: /* if(Dummy[Tvard[k][2]]==0){ */
5515: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][1])]; */
5516: /* }else{ */
5517: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
5518: /* } */
5519: /* }else{ */
5520: /* if(Dummy[Tvard[k][2]]==0){ */
5521: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
5522: /* }else{ */
5523: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
5524: /* } */
5525: /* } */
5526: /* } */
5527: /* /\*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*\/ */
5528: /* /\*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*\/ */
5529: /** End of old code */
5530:
1.218 brouard 5531: /* Careful transposed matrix */
1.266 brouard 5532: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 5533: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 5534: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 5535: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.325 brouard 5536: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);/* Bug valgrind */
1.217 brouard 5537: /* if((int)age == 70){ */
5538: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
5539: /* for(i=1; i<=nlstate+ndeath; i++) { */
5540: /* printf("%d pmmij ",i); */
5541: /* for(j=1;j<=nlstate+ndeath;j++) { */
5542: /* printf("%f ",pmmij[i][j]); */
5543: /* } */
5544: /* printf(" oldm "); */
5545: /* for(j=1;j<=nlstate+ndeath;j++) { */
5546: /* printf("%f ",oldm[i][j]); */
5547: /* } */
5548: /* printf("\n"); */
5549: /* } */
5550: /* } */
5551: savm=oldm;
5552: oldm=newm;
5553: }
5554: for(i=1; i<=nlstate+ndeath; i++)
5555: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 5556: po[i][j][h]=newm[i][j];
1.268 brouard 5557: /* if(h==nhstepm) */
5558: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 5559: }
1.268 brouard 5560: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 5561: } /* end h */
1.268 brouard 5562: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 5563: return po;
5564: }
5565:
5566:
1.162 brouard 5567: #ifdef NLOPT
5568: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
5569: double fret;
5570: double *xt;
5571: int j;
5572: myfunc_data *d2 = (myfunc_data *) pd;
5573: /* xt = (p1-1); */
5574: xt=vector(1,n);
5575: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
5576:
5577: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
5578: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
5579: printf("Function = %.12lf ",fret);
5580: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
5581: printf("\n");
5582: free_vector(xt,1,n);
5583: return fret;
5584: }
5585: #endif
1.126 brouard 5586:
5587: /*************** log-likelihood *************/
5588: double func( double *x)
5589: {
1.336 brouard 5590: int i, ii, j, k, mi, d, kk, kf=0;
1.226 brouard 5591: int ioffset=0;
1.339 brouard 5592: int ipos=0,iposold=0,ncovv=0;
5593:
1.340 brouard 5594: double cotvarv, cotvarvold;
1.226 brouard 5595: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
5596: double **out;
5597: double lli; /* Individual log likelihood */
5598: int s1, s2;
1.228 brouard 5599: 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 5600:
1.226 brouard 5601: double bbh, survp;
5602: double agexact;
1.336 brouard 5603: double agebegin, ageend;
1.226 brouard 5604: /*extern weight */
5605: /* We are differentiating ll according to initial status */
5606: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
5607: /*for(i=1;i<imx;i++)
5608: printf(" %d\n",s[4][i]);
5609: */
1.162 brouard 5610:
1.226 brouard 5611: ++countcallfunc;
1.162 brouard 5612:
1.226 brouard 5613: cov[1]=1.;
1.126 brouard 5614:
1.226 brouard 5615: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 5616: ioffset=0;
1.226 brouard 5617: if(mle==1){
5618: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
5619: /* Computes the values of the ncovmodel covariates of the model
5620: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
5621: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
5622: to be observed in j being in i according to the model.
5623: */
1.243 brouard 5624: ioffset=2+nagesqr ;
1.233 brouard 5625: /* Fixed */
1.345 brouard 5626: for (kf=1; kf<=ncovf;kf++){ /* For each fixed covariate dummy or quant or prod */
1.319 brouard 5627: /* # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi */
5628: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
5629: /* 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 5630: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.336 brouard 5631: 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 5632: /* V1*V2 (7) TvarFind[2]=7, TvarFind[3]=9 */
1.234 brouard 5633: }
1.226 brouard 5634: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
1.319 brouard 5635: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
1.226 brouard 5636: has been calculated etc */
5637: /* For an individual i, wav[i] gives the number of effective waves */
5638: /* We compute the contribution to Likelihood of each effective transition
5639: mw[mi][i] is real wave of the mi th effectve wave */
5640: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
5641: s2=s[mw[mi+1][i]][i];
1.341 brouard 5642: 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 5643: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
5644: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
5645: */
1.336 brouard 5646: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
5647: /* Wave varying (but not age varying) */
1.339 brouard 5648: /* 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*\/ */
5649: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; but where is the crossproduct? *\/ */
5650: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
5651: /* } */
1.340 brouard 5652: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age )*/
5653: itv=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
5654: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
1.345 brouard 5655: if(FixedV[itv]!=0){ /* Not a fixed covariate */
1.341 brouard 5656: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]][i]; /* cotvar[wav][ncovcol+nqv+iv][i] */
1.340 brouard 5657: }else{ /* fixed covariate */
1.345 brouard 5658: 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 5659: }
1.339 brouard 5660: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 brouard 5661: cotvarvold=cotvarv;
5662: }else{ /* A second product */
5663: cotvarv=cotvarv*cotvarvold;
1.339 brouard 5664: }
5665: iposold=ipos;
1.340 brouard 5666: cov[ioffset+ipos]=cotvarv;
1.234 brouard 5667: }
1.339 brouard 5668: /* for products of time varying to be done */
1.234 brouard 5669: for (ii=1;ii<=nlstate+ndeath;ii++)
5670: for (j=1;j<=nlstate+ndeath;j++){
5671: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
5672: savm[ii][j]=(ii==j ? 1.0 : 0.0);
5673: }
1.336 brouard 5674:
5675: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
5676: 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 5677: for(d=0; d<dh[mi][i]; d++){
5678: newm=savm;
5679: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
5680: cov[2]=agexact;
5681: if(nagesqr==1)
5682: cov[3]= agexact*agexact; /* Should be changed here */
1.349 brouard 5683: /* for (kk=1; kk<=cptcovage;kk++) { */
5684: /* if(!FixedV[Tvar[Tage[kk]]]) */
5685: /* cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /\* Tage[kk] gives the data-covariate associated with age *\/ */
5686: /* else */
5687: /* 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) *\/ */
5688: /* } */
5689: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
5690: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
5691: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
5692: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
5693: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
5694: }else{ /* fixed covariate */
5695: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
5696: }
5697: if(ipos!=iposold){ /* Not a product or first of a product */
5698: cotvarvold=cotvarv;
5699: }else{ /* A second product */
5700: cotvarv=cotvarv*cotvarvold;
5701: }
5702: iposold=ipos;
5703: cov[ioffset+ipos]=cotvarv*agexact;
5704: /* For products */
1.234 brouard 5705: }
1.349 brouard 5706:
1.234 brouard 5707: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
5708: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
5709: savm=oldm;
5710: oldm=newm;
5711: } /* end mult */
5712:
5713: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
5714: /* But now since version 0.9 we anticipate for bias at large stepm.
5715: * If stepm is larger than one month (smallest stepm) and if the exact delay
5716: * (in months) between two waves is not a multiple of stepm, we rounded to
5717: * the nearest (and in case of equal distance, to the lowest) interval but now
5718: * we keep into memory the bias bh[mi][i] and also the previous matrix product
5719: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
5720: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 5721: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
5722: * -stepm/2 to stepm/2 .
5723: * For stepm=1 the results are the same as for previous versions of Imach.
5724: * For stepm > 1 the results are less biased than in previous versions.
5725: */
1.234 brouard 5726: s1=s[mw[mi][i]][i];
5727: s2=s[mw[mi+1][i]][i];
5728: bbh=(double)bh[mi][i]/(double)stepm;
5729: /* bias bh is positive if real duration
5730: * is higher than the multiple of stepm and negative otherwise.
5731: */
5732: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
5733: if( s2 > nlstate){
5734: /* i.e. if s2 is a death state and if the date of death is known
5735: then the contribution to the likelihood is the probability to
5736: die between last step unit time and current step unit time,
5737: which is also equal to probability to die before dh
5738: minus probability to die before dh-stepm .
5739: In version up to 0.92 likelihood was computed
5740: as if date of death was unknown. Death was treated as any other
5741: health state: the date of the interview describes the actual state
5742: and not the date of a change in health state. The former idea was
5743: to consider that at each interview the state was recorded
5744: (healthy, disable or death) and IMaCh was corrected; but when we
5745: introduced the exact date of death then we should have modified
5746: the contribution of an exact death to the likelihood. This new
5747: contribution is smaller and very dependent of the step unit
5748: stepm. It is no more the probability to die between last interview
5749: and month of death but the probability to survive from last
5750: interview up to one month before death multiplied by the
5751: probability to die within a month. Thanks to Chris
5752: Jackson for correcting this bug. Former versions increased
5753: mortality artificially. The bad side is that we add another loop
5754: which slows down the processing. The difference can be up to 10%
5755: lower mortality.
5756: */
5757: /* If, at the beginning of the maximization mostly, the
5758: cumulative probability or probability to be dead is
5759: constant (ie = 1) over time d, the difference is equal to
5760: 0. out[s1][3] = savm[s1][3]: probability, being at state
5761: s1 at precedent wave, to be dead a month before current
5762: wave is equal to probability, being at state s1 at
5763: precedent wave, to be dead at mont of the current
5764: wave. Then the observed probability (that this person died)
5765: is null according to current estimated parameter. In fact,
5766: it should be very low but not zero otherwise the log go to
5767: infinity.
5768: */
1.183 brouard 5769: /* #ifdef INFINITYORIGINAL */
5770: /* lli=log(out[s1][s2] - savm[s1][s2]); */
5771: /* #else */
5772: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
5773: /* lli=log(mytinydouble); */
5774: /* else */
5775: /* lli=log(out[s1][s2] - savm[s1][s2]); */
5776: /* #endif */
1.226 brouard 5777: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 5778:
1.226 brouard 5779: } else if ( s2==-1 ) { /* alive */
5780: for (j=1,survp=0. ; j<=nlstate; j++)
5781: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
5782: /*survp += out[s1][j]; */
5783: lli= log(survp);
5784: }
1.336 brouard 5785: /* else if (s2==-4) { */
5786: /* for (j=3,survp=0. ; j<=nlstate; j++) */
5787: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
5788: /* lli= log(survp); */
5789: /* } */
5790: /* else if (s2==-5) { */
5791: /* for (j=1,survp=0. ; j<=2; j++) */
5792: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
5793: /* lli= log(survp); */
5794: /* } */
1.226 brouard 5795: else{
5796: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
5797: /* 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 */
5798: }
5799: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
5800: /*if(lli ==000.0)*/
1.340 brouard 5801: /* 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 5802: ipmx +=1;
5803: sw += weight[i];
5804: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
5805: /* if (lli < log(mytinydouble)){ */
5806: /* 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); */
5807: /* 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]); */
5808: /* } */
5809: } /* end of wave */
5810: } /* end of individual */
5811: } else if(mle==2){
5812: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.319 brouard 5813: ioffset=2+nagesqr ;
5814: for (k=1; k<=ncovf;k++)
5815: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];
1.226 brouard 5816: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 5817: for(k=1; k <= ncovv ; k++){
1.341 brouard 5818: 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 5819: }
1.226 brouard 5820: for (ii=1;ii<=nlstate+ndeath;ii++)
5821: for (j=1;j<=nlstate+ndeath;j++){
5822: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
5823: savm[ii][j]=(ii==j ? 1.0 : 0.0);
5824: }
5825: for(d=0; d<=dh[mi][i]; d++){
5826: newm=savm;
5827: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
5828: cov[2]=agexact;
5829: if(nagesqr==1)
5830: cov[3]= agexact*agexact;
5831: for (kk=1; kk<=cptcovage;kk++) {
5832: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
5833: }
5834: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
5835: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
5836: savm=oldm;
5837: oldm=newm;
5838: } /* end mult */
5839:
5840: s1=s[mw[mi][i]][i];
5841: s2=s[mw[mi+1][i]][i];
5842: bbh=(double)bh[mi][i]/(double)stepm;
5843: 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 */
5844: ipmx +=1;
5845: sw += weight[i];
5846: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
5847: } /* end of wave */
5848: } /* end of individual */
5849: } else if(mle==3){ /* exponential inter-extrapolation */
5850: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
5851: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
5852: for(mi=1; mi<= wav[i]-1; mi++){
5853: for (ii=1;ii<=nlstate+ndeath;ii++)
5854: for (j=1;j<=nlstate+ndeath;j++){
5855: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
5856: savm[ii][j]=(ii==j ? 1.0 : 0.0);
5857: }
5858: for(d=0; d<dh[mi][i]; d++){
5859: newm=savm;
5860: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
5861: cov[2]=agexact;
5862: if(nagesqr==1)
5863: cov[3]= agexact*agexact;
5864: for (kk=1; kk<=cptcovage;kk++) {
1.340 brouard 5865: if(!FixedV[Tvar[Tage[kk]]])
5866: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
5867: else
1.341 brouard 5868: 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 5869: }
5870: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
5871: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
5872: savm=oldm;
5873: oldm=newm;
5874: } /* end mult */
5875:
5876: s1=s[mw[mi][i]][i];
5877: s2=s[mw[mi+1][i]][i];
5878: bbh=(double)bh[mi][i]/(double)stepm;
5879: 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 */
5880: ipmx +=1;
5881: sw += weight[i];
5882: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
5883: } /* end of wave */
5884: } /* end of individual */
5885: }else if (mle==4){ /* ml=4 no inter-extrapolation */
5886: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
5887: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
5888: for(mi=1; mi<= wav[i]-1; mi++){
5889: for (ii=1;ii<=nlstate+ndeath;ii++)
5890: for (j=1;j<=nlstate+ndeath;j++){
5891: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
5892: savm[ii][j]=(ii==j ? 1.0 : 0.0);
5893: }
5894: for(d=0; d<dh[mi][i]; d++){
5895: newm=savm;
5896: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
5897: cov[2]=agexact;
5898: if(nagesqr==1)
5899: cov[3]= agexact*agexact;
5900: for (kk=1; kk<=cptcovage;kk++) {
5901: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
5902: }
1.126 brouard 5903:
1.226 brouard 5904: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
5905: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
5906: savm=oldm;
5907: oldm=newm;
5908: } /* end mult */
5909:
5910: s1=s[mw[mi][i]][i];
5911: s2=s[mw[mi+1][i]][i];
5912: if( s2 > nlstate){
5913: lli=log(out[s1][s2] - savm[s1][s2]);
5914: } else if ( s2==-1 ) { /* alive */
5915: for (j=1,survp=0. ; j<=nlstate; j++)
5916: survp += out[s1][j];
5917: lli= log(survp);
5918: }else{
5919: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
5920: }
5921: ipmx +=1;
5922: sw += weight[i];
5923: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.343 brouard 5924: /* 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 5925: } /* end of wave */
5926: } /* end of individual */
5927: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
5928: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
5929: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
5930: for(mi=1; mi<= wav[i]-1; mi++){
5931: for (ii=1;ii<=nlstate+ndeath;ii++)
5932: for (j=1;j<=nlstate+ndeath;j++){
5933: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
5934: savm[ii][j]=(ii==j ? 1.0 : 0.0);
5935: }
5936: for(d=0; d<dh[mi][i]; d++){
5937: newm=savm;
5938: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
5939: cov[2]=agexact;
5940: if(nagesqr==1)
5941: cov[3]= agexact*agexact;
5942: for (kk=1; kk<=cptcovage;kk++) {
1.340 brouard 5943: if(!FixedV[Tvar[Tage[kk]]])
5944: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
5945: else
1.341 brouard 5946: 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 5947: }
1.126 brouard 5948:
1.226 brouard 5949: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
5950: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
5951: savm=oldm;
5952: oldm=newm;
5953: } /* end mult */
5954:
5955: s1=s[mw[mi][i]][i];
5956: s2=s[mw[mi+1][i]][i];
5957: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
5958: ipmx +=1;
5959: sw += weight[i];
5960: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
5961: /*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]);*/
5962: } /* end of wave */
5963: } /* end of individual */
5964: } /* End of if */
5965: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
5966: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
5967: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
5968: return -l;
1.126 brouard 5969: }
5970:
5971: /*************** log-likelihood *************/
5972: double funcone( double *x)
5973: {
1.228 brouard 5974: /* Same as func but slower because of a lot of printf and if */
1.359 brouard 5975: int i, ii, j, k, mi, d, kv=0, kf=0;
1.228 brouard 5976: int ioffset=0;
1.339 brouard 5977: int ipos=0,iposold=0,ncovv=0;
5978:
1.340 brouard 5979: double cotvarv, cotvarvold;
1.131 brouard 5980: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 5981: double **out;
5982: double lli; /* Individual log likelihood */
5983: double llt;
5984: int s1, s2;
1.228 brouard 5985: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
5986:
1.126 brouard 5987: double bbh, survp;
1.187 brouard 5988: double agexact;
1.214 brouard 5989: double agebegin, ageend;
1.126 brouard 5990: /*extern weight */
5991: /* We are differentiating ll according to initial status */
5992: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
5993: /*for(i=1;i<imx;i++)
5994: printf(" %d\n",s[4][i]);
5995: */
5996: cov[1]=1.;
5997:
5998: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 5999: ioffset=0;
6000: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.336 brouard 6001: /* Computes the values of the ncovmodel covariates of the model
6002: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
6003: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
6004: to be observed in j being in i according to the model.
6005: */
1.243 brouard 6006: /* ioffset=2+nagesqr+cptcovage; */
6007: ioffset=2+nagesqr;
1.232 brouard 6008: /* Fixed */
1.224 brouard 6009: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 6010: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
1.349 brouard 6011: 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 6012: /* printf("Debug3 TvarFind[%d]=%d",kf, TvarFind[kf]); */
6013: /* printf(" Tvar[TvarFind[kf]]=%d", Tvar[TvarFind[kf]]); */
6014: /* printf(" i=%d covar[Tvar[TvarFind[kf]]][i]=%f\n",i,covar[Tvar[TvarFind[kf]]][i]); */
1.335 brouard 6015: 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 6016: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
6017: /* cov[2+6]=covar[Tvar[6]][i]; */
6018: /* cov[2+6]=covar[2][i]; V2 */
6019: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
6020: /* cov[2+7]=covar[Tvar[7]][i]; */
6021: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
6022: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
6023: /* cov[2+9]=covar[Tvar[9]][i]; */
6024: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 6025: }
1.336 brouard 6026: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
6027: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
6028: has been calculated etc */
6029: /* For an individual i, wav[i] gives the number of effective waves */
6030: /* We compute the contribution to Likelihood of each effective transition
6031: mw[mi][i] is real wave of the mi th effectve wave */
6032: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
6033: s2=s[mw[mi+1][i]][i];
1.341 brouard 6034: And the iv th varying covariate in the DATA is the cotvar[mw[mi+1][i]][ncovcol+nqv+iv][i]
1.336 brouard 6035: */
6036: /* This part may be useless now because everythin should be in covar */
1.232 brouard 6037: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
6038: /* 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?)*\/ */
6039: /* } */
1.231 brouard 6040: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
6041: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
6042: /* } */
1.225 brouard 6043:
1.233 brouard 6044:
6045: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.339 brouard 6046: /* 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 */
6047: /* for(k=1; k <= ncovv ; k++){ /\* Varying covariates (single and product but no age )*\/ */
6048: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; *\/ */
6049: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
6050: /* } */
6051:
6052: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
6053: /* model V1+V3+age*V1+age*V3+V1*V3 */
6054: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
6055: /* TvarVV[1]=V3 (first time varying in the model equation, TvarVV[2]=V1 (in V1*V3) TvarVV[3]=3(V3) */
6056: /* We need the position of the time varying or product in the model */
6057: /* 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 */
6058: /* TvarVV gives the variable name */
1.340 brouard 6059: /* Other example V1 + V3 + V5 + age*V1 + age*V3 + age*V5 + V1*V3 + V3*V5 + V1*V5
6060: * k= 1 2 3 4 5 6 7 8 9
6061: * varying 1 2 3 4 5
6062: * ncovv 1 2 3 4 5 6 7 8
1.343 brouard 6063: * TvarVV[ncovv] V3 5 1 3 3 5 1 5
1.340 brouard 6064: * TvarVVind 2 3 7 7 8 8 9 9
6065: * TvarFind[k] 1 0 0 0 0 0 0 0 0
6066: */
1.345 brouard 6067: /* Other model ncovcol=5 nqv=0 ntv=3 nqtv=0 nlstate=3
1.349 brouard 6068: * 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 6069: * FixedV[ncovcol+qv+ntv+nqtv] V5
1.349 brouard 6070: * 3 V1 V2 V3 V4 V5 V6 V7 V8 V3*V2 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
6071: * 0 0 0 0 0 1 1 1 0, 0, 1,1, 1, 0, 1, 0, 1, 0, 1, 0}
6072: * 3 0 0 0 0 0 1 1 1 0, 1 1 1 1 1}
6073: * model= V2 + V3 + V4 + V6 + V7 + V6*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
6074: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
6075: * +age*V6*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
6076: * model2= V2 + V3 + V4 + V6 + V7 + V3*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
6077: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
6078: * +age*V3*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
6079: * model3= V2 + V3 + V4 + V6 + V7 + age*V3*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
6080: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
6081: * +V3*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
6082: * kmodel 1 2 3 4 5 6 7 8 9 10 11
6083: * 12 13 14 15 16
6084: * 17 18 19 20 21
6085: * Tvar[kmodel] 2 3 4 6 7 9 10 11 12 13 14
6086: * 2 3 4 6 7
6087: * 9 11 12 13 14
6088: * cptcovage=5+5 total of covariates with age
6089: * Tage[cptcovage] age*V2=12 13 14 15 16
6090: *1 17 18 19 20 21 gives the position in model of covariates associated with age
6091: *3 Tage[cptcovage] age*V3*V2=6
6092: *3 age*V2=12 13 14 15 16
6093: *3 age*V6*V3=18 19 20 21
6094: * Tvar[Tage[cptcovage]] Tvar[12]=2 3 4 6 Tvar[16]=7(age*V7)
6095: * 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
6096: * 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
6097: * 3 Tvar[Tage[cptcovage]] Tvar[6]=9 Tvar[12]=2 3 4 6 Tvar[16]=7(age*V7)
6098: * 3 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14
6099: * 3 Tage[cptcovage] age*V3*V2=6 age*V2=12 age*V3 13 14 15 16
6100: * age*V6*V3=18 19 20 21 gives the position in model of covariates associated with age
6101: * 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
6102: * Tvar= {2, 3, 4, 6, 7,
6103: * 9, 10, 11, 12, 13, 14,
6104: * Tvar[12]=2, 3, 4, 6, 7,
6105: * Tvar[17]=9, 11, 12, 13, 14}
6106: * Typevar[1]@21 = {0, 0, 0, 0, 0,
6107: * 2, 2, 2, 2, 2, 2,
6108: * 3 3, 2, 2, 2, 2, 2,
6109: * 1, 1, 1, 1, 1,
6110: * 3, 3, 3, 3, 3}
6111: * 3 2, 3, 3, 3, 3}
6112: * 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
6113: * p Tprod[1]@21 {6, 7, 8, 9, 10, 11, 0 <repeats 15 times>}
6114: * 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}
6115: * 3 Tprod[1]@21 {17, 7, 8, 9, 10, 11, 0 <repeats 15 times>}
6116: * cptcovprod=11 (6+5)
6117: * FixedV[Tvar[Tage[cptcovage]]]] FixedV[2]=0 FixedV[3]=0 0 1 (age*V7)Tvar[16]=1 FixedV[absolute] not [kmodel]
6118: * FixedV[Tvar[17]=FixedV[age*V6*V2]=FixedV[9]=1 1 1 1 1
6119: * 3 FixedV[Tvar[17]=FixedV[age*V3*V2]=FixedV[9]=0 [11]=1 1 1 1
6120: * FixedV[] V1=0 V2=0 V3=0 v4=0 V5=0 V6=1 V7=1 v8=1 OK then model dependent
6121: * 9=1 [V7*V2]=[10]=1 11=1 12=1 13=1 14=1
6122: * 3 9=0 [V7*V2]=[10]=1 11=1 12=1 13=1 14=1
6123: * cptcovdageprod=5 for gnuplot printing
6124: * cptcovprodvage=6
6125: * ncova=15 1 2 3 4 5
6126: * 6 7 8 9 10 11 12 13 14 15
6127: * TvarA 2 3 4 6 7
6128: * 6 2 6 7 7 3 6 4 7 4
6129: * TvaAind 12 12 13 13 14 14 15 15 16 16
1.345 brouard 6130: * ncovf 1 2 3
1.349 brouard 6131: * V6 V7 V6*V2 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
6132: * ncovvt=14 1 2 3 4 5 6 7 8 9 10 11 12 13 14
6133: * TvarVV[1]@14 = itv {V6=6, 7, V6*V2=6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
6134: * TvarVVind[1]@14= {4, 5, 6, 6, 7, 7, 8, 8, 9, 9, 10, 10, 11, 11}
6135: * 3 ncovvt=12 V6 V7 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
6136: * 3 TvarVV[1]@12 = itv {6, 7, V7*V2=7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
6137: * 3 1 2 3 4 5 6 7 8 9 10 11 12
6138: * TvarVVind[1]@12= {V6 is in k=4, 5, 7,(4isV2)=7, 8, 8, 9, 9, 10,10, 11,11}TvarVVind[12]=k=11
6139: * TvarV 6, 7, 9, 10, 11, 12, 13, 14
6140: * 3 cptcovprodvage=6
6141: * 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
6142: * 3 TvarAVVA[1]@15= itva 3 2 2 3 4 6 7 6 3 7 3 6 4 7 4
6143: * 3 ncovta 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
1.354 brouard 6144: *?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 6145: * TvarAVVAind[1]@15= V3 is in k=6 6 12 13 14 15 16 18 18 19,19, 20,20 21,21}TvarVVAind[]
6146: * 3 ncovvta=10 +age*V6 + age*V7 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
6147: * 3 we want to compute =cotvar[mw[mi][i]][TvarVVA[ncovva]][i] at position TvarVVAind[ncovva]
6148: * 3 TvarVVA[1]@10= itva 6 7 6 3 7 3 6 4 7 4
6149: * 3 ncovva 1 2 3 4 5 6 7 8 9 10
6150: * TvarVVAind[1]@10= V6 is in k=4 5 8,8 9, 9, 10,10 11 11}TvarVVAind[]
6151: * TvarVVAind[1]@10= 15 16 18,18 19,19, 20,20 21 21}TvarVVAind[]
6152: * TvarVA V3*V2=6 6 , 1, 2, 11, 12, 13, 14
1.345 brouard 6153: * TvarFind[1]@14= {1, 2, 3, 0 <repeats 12 times>}
1.349 brouard 6154: * Tvar[1]@21= {2, 3, 4, 6, 7, 9, 10, 11, 12, 13, 14,
6155: * 2, 3, 4, 6, 7,
6156: * 6, 8, 9, 10, 11}
1.345 brouard 6157: * TvarFind[itv] 0 0 0
6158: * FixedV[itv] 1 1 1 0 1 0 1 0 1 0 0
1.354 brouard 6159: *? FixedV[itv] 1 1 1 0 1 0 1 0 1 0 1 0 1 0
1.345 brouard 6160: * Tvar[TvarFind[ncovf]]=[1]=2 [2]=3 [4]=4
6161: * Tvar[TvarFind[itv]] [0]=? ?ncovv 1 à ncovvt]
6162: * Not a fixed cotvar[mw][itv][i] 6 7 6 2 7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
1.349 brouard 6163: * fixed covar[itv] [6] [7] [6][2]
1.345 brouard 6164: */
6165:
1.349 brouard 6166: 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 */
6167: 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 6168: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
1.345 brouard 6169: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
6170: 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 6171: /* printf("DEBUG ncovv=%d, Varying TvarVV[ncovv]=%d\n",ncovv, TvarVV[ncovv]); */
1.345 brouard 6172: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
1.354 brouard 6173: /* printf("DEBUG Varying cov[ioffset+ipos=%d]=%g \n",ioffset+ipos,cotvarv); */
1.340 brouard 6174: }else{ /* fixed covariate */
1.345 brouard 6175: /* 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 6176: /* printf("DEBUG ncovv=%d, Fixed TvarVV[ncovv]=%d\n",ncovv, TvarVV[ncovv]); */
1.349 brouard 6177: cotvarv=covar[itv][i]; /* Good: In V6*V3, 3 is fixed at position of the data */
1.354 brouard 6178: /* printf("DEBUG Fixed cov[ioffset+ipos=%d]=%g \n",ioffset+ipos,cotvarv); */
1.340 brouard 6179: }
1.339 brouard 6180: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 brouard 6181: cotvarvold=cotvarv;
6182: }else{ /* A second product */
6183: cotvarv=cotvarv*cotvarvold;
1.339 brouard 6184: }
6185: iposold=ipos;
1.340 brouard 6186: cov[ioffset+ipos]=cotvarv;
1.354 brouard 6187: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
1.339 brouard 6188: /* For products */
6189: }
6190: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates single *\/ */
6191: /* iv=TvarVDind[itv]; /\* iv, position in the model equation of time varying covariate itv *\/ */
6192: /* /\* "V1+V3+age*V1+age*V3+V1*V3" with V3 time varying *\/ */
6193: /* /\* 1 2 3 4 5 *\/ */
6194: /* /\*itv 1 *\/ */
6195: /* /\* TvarVInd[1]= 2 *\/ */
6196: /* /\* iv= Tvar[Tmodelind[itv]]-ncovcol-nqv; /\\* Counting the # varying covariate from 1 to ntveff *\\/ *\/ */
6197: /* /\* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; *\/ */
6198: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; *\/ */
6199: /* /\* k=ioffset-2-nagesqr-cptcovage+itv; /\\* position in simple model *\\/ *\/ */
6200: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; *\/ */
6201: /* cov[ioffset+iv]=cotvar[mw[mi][i]][itv][i]; */
6202: /* /\* 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]); *\/ */
6203: /* } */
1.232 brouard 6204: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 6205: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
6206: /* /\* 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]); *\/ */
6207: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 6208: /* } */
1.126 brouard 6209: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 6210: for (j=1;j<=nlstate+ndeath;j++){
6211: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
6212: savm[ii][j]=(ii==j ? 1.0 : 0.0);
6213: }
1.214 brouard 6214:
6215: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
6216: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
6217: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 6218: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 6219: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
6220: and mw[mi+1][i]. dh depends on stepm.*/
6221: newm=savm;
1.247 brouard 6222: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 6223: cov[2]=agexact;
6224: if(nagesqr==1)
6225: cov[3]= agexact*agexact;
1.349 brouard 6226: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
6227: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
6228: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
6229: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
6230: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
6231: /* printf("DEBUG ncovva=%d, Varying TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
6232: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
6233: }else{ /* fixed covariate */
6234: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
6235: /* printf("DEBUG ncovva=%d, Fixed TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
6236: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
6237: }
6238: if(ipos!=iposold){ /* Not a product or first of a product */
6239: cotvarvold=cotvarv;
6240: }else{ /* A second product */
6241: /* printf("DEBUG * \n"); */
6242: cotvarv=cotvarv*cotvarvold;
6243: }
6244: iposold=ipos;
6245: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
6246: cov[ioffset+ipos]=cotvarv*agexact;
6247: /* For products */
1.242 brouard 6248: }
1.349 brouard 6249:
1.242 brouard 6250: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
6251: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
6252: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
6253: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
6254: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
6255: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
6256: savm=oldm;
6257: oldm=newm;
1.126 brouard 6258: } /* end mult */
1.336 brouard 6259: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
6260: /* But now since version 0.9 we anticipate for bias at large stepm.
6261: * If stepm is larger than one month (smallest stepm) and if the exact delay
6262: * (in months) between two waves is not a multiple of stepm, we rounded to
6263: * the nearest (and in case of equal distance, to the lowest) interval but now
6264: * we keep into memory the bias bh[mi][i] and also the previous matrix product
6265: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
6266: * probability in order to take into account the bias as a fraction of the way
6267: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
6268: * -stepm/2 to stepm/2 .
6269: * For stepm=1 the results are the same as for previous versions of Imach.
6270: * For stepm > 1 the results are less biased than in previous versions.
6271: */
1.126 brouard 6272: s1=s[mw[mi][i]][i];
6273: s2=s[mw[mi+1][i]][i];
1.217 brouard 6274: /* if(s2==-1){ */
1.268 brouard 6275: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 6276: /* /\* exit(1); *\/ */
6277: /* } */
1.126 brouard 6278: bbh=(double)bh[mi][i]/(double)stepm;
6279: /* bias is positive if real duration
6280: * is higher than the multiple of stepm and negative otherwise.
6281: */
6282: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 6283: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 6284: } else if ( s2==-1 ) { /* alive */
1.242 brouard 6285: for (j=1,survp=0. ; j<=nlstate; j++)
6286: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
6287: lli= log(survp);
1.126 brouard 6288: }else if (mle==1){
1.242 brouard 6289: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 6290: } else if(mle==2){
1.242 brouard 6291: 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 6292: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 6293: 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 6294: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 6295: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 6296: } else{ /* mle=0 back to 1 */
1.242 brouard 6297: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
6298: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 6299: } /* End of if */
6300: ipmx +=1;
6301: sw += weight[i];
6302: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.342 brouard 6303: /* Printing covariates values for each contribution for checking */
1.343 brouard 6304: /* 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 6305: if(globpr){
1.246 brouard 6306: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 6307: %11.6f %11.6f %11.6f ", \
1.242 brouard 6308: 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 6309: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.343 brouard 6310: /* printf("%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\ */
6311: /* %11.6f %11.6f %11.6f ", \ */
6312: /* num[i], agebegin, ageend, i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],weight[i]*gipmx/gsw, */
6313: /* 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2])); */
1.242 brouard 6314: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
6315: llt +=ll[k]*gipmx/gsw;
6316: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
1.335 brouard 6317: /* printf(" %10.6f",-ll[k]*gipmx/gsw); */
1.242 brouard 6318: }
1.343 brouard 6319: fprintf(ficresilk," %10.6f ", -llt);
1.335 brouard 6320: /* printf(" %10.6f\n", -llt); */
1.342 brouard 6321: /* if(debugILK){ /\* debugILK is set by a #d in a comment line *\/ */
1.343 brouard 6322: /* fprintf(ficresilk,"%09ld ", num[i]); */ /* not necessary */
6323: for (kf=1; kf<=ncovf;kf++){ /* Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */
6324: fprintf(ficresilk," %g",covar[Tvar[TvarFind[kf]]][i]);
6325: }
6326: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age) including individual from products */
6327: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
6328: if(ipos!=iposold){ /* Not a product or first of a product */
6329: fprintf(ficresilk," %g",cov[ioffset+ipos]);
6330: /* printf(" %g",cov[ioffset+ipos]); */
6331: }else{
6332: fprintf(ficresilk,"*");
6333: /* printf("*"); */
1.342 brouard 6334: }
1.343 brouard 6335: iposold=ipos;
6336: }
1.349 brouard 6337: /* for (kk=1; kk<=cptcovage;kk++) { */
6338: /* if(!FixedV[Tvar[Tage[kk]]]){ */
6339: /* fprintf(ficresilk," %g*age",covar[Tvar[Tage[kk]]][i]); */
6340: /* /\* printf(" %g*age",covar[Tvar[Tage[kk]]][i]); *\/ */
6341: /* }else{ */
6342: /* fprintf(ficresilk," %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */
6343: /* /\* printf(" %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/\\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\\/ *\/ */
6344: /* } */
6345: /* } */
6346: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
6347: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
6348: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
6349: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
6350: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
6351: /* printf("DEBUG ncovva=%d, Varying TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
6352: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
6353: }else{ /* fixed covariate */
6354: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
6355: /* printf("DEBUG ncovva=%d, Fixed TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
6356: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
6357: }
6358: if(ipos!=iposold){ /* Not a product or first of a product */
6359: cotvarvold=cotvarv;
6360: }else{ /* A second product */
6361: /* printf("DEBUG * \n"); */
6362: cotvarv=cotvarv*cotvarvold;
1.342 brouard 6363: }
1.349 brouard 6364: cotvarv=cotvarv*agexact;
6365: fprintf(ficresilk," %g*age",cotvarv);
6366: iposold=ipos;
6367: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
6368: cov[ioffset+ipos]=cotvarv;
6369: /* For products */
1.343 brouard 6370: }
6371: /* printf("\n"); */
1.342 brouard 6372: /* } /\* End debugILK *\/ */
6373: fprintf(ficresilk,"\n");
6374: } /* End if globpr */
1.335 brouard 6375: } /* end of wave */
6376: } /* end of individual */
6377: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
1.232 brouard 6378: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
1.335 brouard 6379: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
6380: if(globpr==0){ /* First time we count the contributions and weights */
6381: gipmx=ipmx;
6382: gsw=sw;
6383: }
1.343 brouard 6384: return -l;
1.126 brouard 6385: }
6386:
6387:
6388: /*************** function likelione ***********/
1.292 brouard 6389: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 6390: {
6391: /* This routine should help understanding what is done with
6392: the selection of individuals/waves and
6393: to check the exact contribution to the likelihood.
6394: Plotting could be done.
1.342 brouard 6395: */
6396: void pstamp(FILE *ficres);
1.343 brouard 6397: int k, kf, kk, kvar, ncovv, iposold, ipos;
1.126 brouard 6398:
6399: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 6400: strcpy(fileresilk,"ILK_");
1.202 brouard 6401: strcat(fileresilk,fileresu);
1.126 brouard 6402: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
6403: printf("Problem with resultfile: %s\n", fileresilk);
6404: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
6405: }
1.342 brouard 6406: pstamp(ficresilk);fprintf(ficresilk,"# model=1+age+%s\n",model);
1.214 brouard 6407: 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");
6408: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 6409: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
6410: for(k=1; k<=nlstate; k++)
6411: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
1.342 brouard 6412: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total) ");
6413:
6414: /* if(debugILK){ /\* debugILK is set by a #d in a comment line *\/ */
6415: for(kf=1;kf <= ncovf; kf++){
6416: fprintf(ficresilk,"V%d",Tvar[TvarFind[kf]]);
6417: /* printf("V%d",Tvar[TvarFind[kf]]); */
6418: }
6419: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){
1.343 brouard 6420: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
1.342 brouard 6421: if(ipos!=iposold){ /* Not a product or first of a product */
6422: /* printf(" %d",ipos); */
6423: fprintf(ficresilk," V%d",TvarVV[ncovv]);
6424: }else{
6425: /* printf("*"); */
6426: fprintf(ficresilk,"*");
1.343 brouard 6427: }
1.342 brouard 6428: iposold=ipos;
6429: }
6430: for (kk=1; kk<=cptcovage;kk++) {
6431: if(!FixedV[Tvar[Tage[kk]]]){
6432: /* printf(" %d*age(Fixed)",Tvar[Tage[kk]]); */
6433: fprintf(ficresilk," %d*age(Fixed)",Tvar[Tage[kk]]);
6434: }else{
6435: fprintf(ficresilk," %d*age(Varying)",Tvar[Tage[kk]]);/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
6436: /* printf(" %d*age(Varying)",Tvar[Tage[kk]]);/\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */
6437: }
6438: }
6439: /* } /\* End if debugILK *\/ */
6440: /* printf("\n"); */
6441: fprintf(ficresilk,"\n");
6442: } /* End glogpri */
1.126 brouard 6443:
1.292 brouard 6444: *fretone=(*func)(p);
1.126 brouard 6445: if(*globpri !=0){
6446: fclose(ficresilk);
1.205 brouard 6447: if (mle ==0)
6448: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
6449: else if(mle >=1)
6450: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
6451: 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 6452: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 6453:
1.207 brouard 6454: 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 6455: <img src=\"%s-ori.png\">\n",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 6456: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.343 brouard 6457: <img src=\"%s-dest.png\">\n",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
6458:
6459: for (k=1; k<= nlstate ; k++) {
6460: 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 \
6461: <img src=\"%s-p%dj.png\">\n",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
6462: for(kf=1; kf <= ncovf; kf++){ /* For each simple dummy covariate of the model */
1.350 brouard 6463: kvar=Tvar[TvarFind[kf]]; /* variable */
6464: 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]]);
6465: 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);
6466: fprintf(fichtm,"<img src=\"%s-p%dj-%d.png\">",subdirf2(optionfilefiname,"ILK_"),k,Tvar[TvarFind[kf]]);
1.343 brouard 6467: }
6468: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Loop on the time varying extended covariates (with extension of Vn*Vm */
6469: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
6470: kvar=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
6471: /* 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]); */
6472: if(ipos!=iposold){ /* Not a product or first of a product */
6473: /* fprintf(ficresilk," V%d",TvarVV[ncovv]); */
6474: /* printf(" DebugILK fichtm ipos=%d != iposold=%d\n", ipos, iposold); */
6475: 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) */
6476: 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> \
6477: <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);
6478: } /* End only for dummies time varying (single?) */
6479: }else{ /* Useless product */
6480: /* printf("*"); */
6481: /* fprintf(ficresilk,"*"); */
6482: }
6483: iposold=ipos;
6484: } /* For each time varying covariate */
6485: } /* End loop on states */
6486:
6487: /* if(debugILK){ */
6488: /* for(kf=1; kf <= ncovf; kf++){ /\* For each simple dummy covariate of the model *\/ */
6489: /* /\* kvar=Tvar[TvarFind[kf]]; *\/ /\* variable *\/ */
6490: /* for (k=1; k<= nlstate ; k++) { */
6491: /* 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> \ */
6492: /* <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]]); */
6493: /* } */
6494: /* } */
6495: /* for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /\* Loop on the time varying extended covariates (with extension of Vn*Vm *\/ */
6496: /* ipos=TvarVVind[ncovv]; /\* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate *\/ */
6497: /* kvar=TvarVV[ncovv]; /\* TvarVV={3, 1, 3} gives the name of each varying covariate *\/ */
6498: /* /\* 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]); *\/ */
6499: /* if(ipos!=iposold){ /\* Not a product or first of a product *\/ */
6500: /* /\* fprintf(ficresilk," V%d",TvarVV[ncovv]); *\/ */
6501: /* /\* printf(" DebugILK fichtm ipos=%d != iposold=%d\n", ipos, iposold); *\/ */
6502: /* 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) *\/ */
6503: /* for (k=1; k<= nlstate ; k++) { */
6504: /* 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> \ */
6505: /* <img src=\"%s-p%dj-%d.png\">",k,k,kvar,kvar,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,kvar); */
6506: /* } /\* End state *\/ */
6507: /* } /\* End only for dummies time varying (single?) *\/ */
6508: /* }else{ /\* Useless product *\/ */
6509: /* /\* printf("*"); *\/ */
6510: /* /\* fprintf(ficresilk,"*"); *\/ */
6511: /* } */
6512: /* iposold=ipos; */
6513: /* } /\* For each time varying covariate *\/ */
6514: /* }/\* End debugILK *\/ */
1.207 brouard 6515: fflush(fichtm);
1.343 brouard 6516: }/* End globpri */
1.126 brouard 6517: return;
6518: }
6519:
6520:
6521: /*********** Maximum Likelihood Estimation ***************/
6522:
6523: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
6524: {
1.359 brouard 6525: int i,j, jkk=0, iter=0;
1.126 brouard 6526: double **xi;
1.359 brouard 6527: /*double fret;*/
6528: /*double fretone;*/ /* Only one call to likelihood */
1.126 brouard 6529: /* char filerespow[FILENAMELENGTH];*/
1.354 brouard 6530:
1.359 brouard 6531: /*double * p1;*/ /* Shifted parameters from 0 instead of 1 */
1.162 brouard 6532: #ifdef NLOPT
6533: int creturn;
6534: nlopt_opt opt;
6535: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
6536: double *lb;
6537: double minf; /* the minimum objective value, upon return */
1.354 brouard 6538:
1.162 brouard 6539: myfunc_data dinst, *d = &dinst;
6540: #endif
6541:
6542:
1.126 brouard 6543: xi=matrix(1,npar,1,npar);
1.357 brouard 6544: for (i=1;i<=npar;i++) /* Starting with canonical directions j=1,n xi[i=1,n][j] */
1.126 brouard 6545: for (j=1;j<=npar;j++)
6546: xi[i][j]=(i==j ? 1.0 : 0.0);
1.359 brouard 6547: printf("Powell-prax\n"); fprintf(ficlog,"Powell-prax\n");
1.201 brouard 6548: strcpy(filerespow,"POW_");
1.126 brouard 6549: strcat(filerespow,fileres);
6550: if((ficrespow=fopen(filerespow,"w"))==NULL) {
6551: printf("Problem with resultfile: %s\n", filerespow);
6552: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
6553: }
6554: fprintf(ficrespow,"# Powell\n# iter -2*LL");
6555: for (i=1;i<=nlstate;i++)
6556: for(j=1;j<=nlstate+ndeath;j++)
6557: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
6558: fprintf(ficrespow,"\n");
1.162 brouard 6559: #ifdef POWELL
1.319 brouard 6560: #ifdef LINMINORIGINAL
6561: #else /* LINMINORIGINAL */
6562:
6563: flatdir=ivector(1,npar);
6564: for (j=1;j<=npar;j++) flatdir[j]=0;
6565: #endif /*LINMINORIGINAL */
6566:
6567: #ifdef FLATSUP
6568: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
6569: /* reorganizing p by suppressing flat directions */
6570: for(i=1, jk=1; i <=nlstate; i++){
6571: for(k=1; k <=(nlstate+ndeath); k++){
6572: if (k != i) {
6573: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
6574: if(flatdir[jk]==1){
6575: printf(" To be skipped %d%d flatdir[%d]=%d ",i,k,jk, flatdir[jk]);
6576: }
6577: for(j=1; j <=ncovmodel; j++){
6578: printf("%12.7f ",p[jk]);
6579: jk++;
6580: }
6581: printf("\n");
6582: }
6583: }
6584: }
6585: /* skipping */
6586: /* for(i=1, jk=1, jkk=1;(flatdir[jk]==0)&& (i <=nlstate); i++){ */
6587: for(i=1, jk=1, jkk=1;i <=nlstate; i++){
6588: for(k=1; k <=(nlstate+ndeath); k++){
6589: if (k != i) {
6590: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
6591: if(flatdir[jk]==1){
6592: printf(" To be skipped %d%d flatdir[%d]=%d jk=%d p[%d] ",i,k,jk, flatdir[jk],jk, jk);
6593: for(j=1; j <=ncovmodel; jk++,j++){
6594: printf(" p[%d]=%12.7f",jk, p[jk]);
6595: /*q[jjk]=p[jk];*/
6596: }
6597: }else{
6598: printf(" To be kept %d%d flatdir[%d]=%d jk=%d q[%d]=p[%d] ",i,k,jk, flatdir[jk],jk, jkk, jk);
6599: for(j=1; j <=ncovmodel; jk++,jkk++,j++){
6600: printf(" p[%d]=%12.7f=q[%d]",jk, p[jk],jkk);
6601: /*q[jjk]=p[jk];*/
6602: }
6603: }
6604: printf("\n");
6605: }
6606: fflush(stdout);
6607: }
6608: }
6609: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
6610: #else /* FLATSUP */
1.359 brouard 6611: /* powell(p,xi,npar,ftol,&iter,&fret,func);*/
6612: /* praxis ( t0, h0, n, prin, x, beale_f ); */
1.362 brouard 6613: /* int prin=1; */
6614: /* double h0=0.25; */
6615: /* double macheps; */
6616: /* double fmin; */
1.359 brouard 6617: macheps=pow(16.0,-13.0);
6618: /* #include "praxis.h" */
6619: /* Be careful that praxis start at x[0] and powell start at p[1] */
6620: /* praxis ( ftol, h0, npar, prin, p, func ); */
6621: /* p1= (p+1); */ /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
6622: printf("Praxis Gegenfurtner \n");
6623: fprintf(ficlog, "Praxis Gegenfurtner\n");fflush(ficlog);
6624: /* praxis ( ftol, h0, npar, prin, p1, func ); */
6625: /* fmin = praxis(1.e-5,macheps, h, n, prin, x, func); */
1.362 brouard 6626: ffmin = praxis(ftol,macheps, h0, npar, prin, p, func);
1.359 brouard 6627: printf("End Praxis\n");
1.319 brouard 6628: #endif /* FLATSUP */
6629:
6630: #ifdef LINMINORIGINAL
6631: #else
6632: free_ivector(flatdir,1,npar);
6633: #endif /* LINMINORIGINAL*/
6634: #endif /* POWELL */
1.126 brouard 6635:
1.162 brouard 6636: #ifdef NLOPT
6637: #ifdef NEWUOA
6638: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
6639: #else
6640: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
6641: #endif
6642: lb=vector(0,npar-1);
6643: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
6644: nlopt_set_lower_bounds(opt, lb);
6645: nlopt_set_initial_step1(opt, 0.1);
6646:
6647: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
6648: d->function = func;
6649: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
6650: nlopt_set_min_objective(opt, myfunc, d);
6651: nlopt_set_xtol_rel(opt, ftol);
6652: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
6653: printf("nlopt failed! %d\n",creturn);
6654: }
6655: else {
6656: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
6657: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
6658: iter=1; /* not equal */
6659: }
6660: nlopt_destroy(opt);
6661: #endif
1.319 brouard 6662: #ifdef FLATSUP
6663: /* npared = npar -flatd/ncovmodel; */
6664: /* xired= matrix(1,npared,1,npared); */
6665: /* paramred= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); */
6666: /* powell(pred,xired,npared,ftol,&iter,&fret,flatdir,func); */
6667: /* free_matrix(xire,1,npared,1,npared); */
6668: #else /* FLATSUP */
6669: #endif /* FLATSUP */
1.126 brouard 6670: free_matrix(xi,1,npar,1,npar);
6671: fclose(ficrespow);
1.203 brouard 6672: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
6673: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 6674: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 6675:
6676: }
6677:
6678: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 6679: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 6680: {
6681: double **a,**y,*x,pd;
1.203 brouard 6682: /* double **hess; */
1.164 brouard 6683: int i, j;
1.126 brouard 6684: int *indx;
6685:
6686: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 6687: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 6688: void lubksb(double **a, int npar, int *indx, double b[]) ;
6689: void ludcmp(double **a, int npar, int *indx, double *d) ;
6690: double gompertz(double p[]);
1.203 brouard 6691: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 6692:
6693: printf("\nCalculation of the hessian matrix. Wait...\n");
6694: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
6695: for (i=1;i<=npar;i++){
1.203 brouard 6696: printf("%d-",i);fflush(stdout);
6697: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 6698:
6699: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
6700:
6701: /* printf(" %f ",p[i]);
6702: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
6703: }
6704:
6705: for (i=1;i<=npar;i++) {
6706: for (j=1;j<=npar;j++) {
6707: if (j>i) {
1.203 brouard 6708: printf(".%d-%d",i,j);fflush(stdout);
6709: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
6710: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 6711:
6712: hess[j][i]=hess[i][j];
6713: /*printf(" %lf ",hess[i][j]);*/
6714: }
6715: }
6716: }
6717: printf("\n");
6718: fprintf(ficlog,"\n");
6719:
6720: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
6721: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
6722:
6723: a=matrix(1,npar,1,npar);
6724: y=matrix(1,npar,1,npar);
6725: x=vector(1,npar);
6726: indx=ivector(1,npar);
6727: for (i=1;i<=npar;i++)
6728: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
6729: ludcmp(a,npar,indx,&pd);
6730:
6731: for (j=1;j<=npar;j++) {
6732: for (i=1;i<=npar;i++) x[i]=0;
6733: x[j]=1;
6734: lubksb(a,npar,indx,x);
6735: for (i=1;i<=npar;i++){
6736: matcov[i][j]=x[i];
6737: }
6738: }
6739:
6740: printf("\n#Hessian matrix#\n");
6741: fprintf(ficlog,"\n#Hessian matrix#\n");
6742: for (i=1;i<=npar;i++) {
6743: for (j=1;j<=npar;j++) {
1.203 brouard 6744: printf("%.6e ",hess[i][j]);
6745: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 6746: }
6747: printf("\n");
6748: fprintf(ficlog,"\n");
6749: }
6750:
1.203 brouard 6751: /* printf("\n#Covariance matrix#\n"); */
6752: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
6753: /* for (i=1;i<=npar;i++) { */
6754: /* for (j=1;j<=npar;j++) { */
6755: /* printf("%.6e ",matcov[i][j]); */
6756: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
6757: /* } */
6758: /* printf("\n"); */
6759: /* fprintf(ficlog,"\n"); */
6760: /* } */
6761:
1.126 brouard 6762: /* Recompute Inverse */
1.203 brouard 6763: /* for (i=1;i<=npar;i++) */
6764: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
6765: /* ludcmp(a,npar,indx,&pd); */
6766:
6767: /* printf("\n#Hessian matrix recomputed#\n"); */
6768:
6769: /* for (j=1;j<=npar;j++) { */
6770: /* for (i=1;i<=npar;i++) x[i]=0; */
6771: /* x[j]=1; */
6772: /* lubksb(a,npar,indx,x); */
6773: /* for (i=1;i<=npar;i++){ */
6774: /* y[i][j]=x[i]; */
6775: /* printf("%.3e ",y[i][j]); */
6776: /* fprintf(ficlog,"%.3e ",y[i][j]); */
6777: /* } */
6778: /* printf("\n"); */
6779: /* fprintf(ficlog,"\n"); */
6780: /* } */
6781:
6782: /* Verifying the inverse matrix */
6783: #ifdef DEBUGHESS
6784: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 6785:
1.203 brouard 6786: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
6787: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 6788:
6789: for (j=1;j<=npar;j++) {
6790: for (i=1;i<=npar;i++){
1.203 brouard 6791: printf("%.2f ",y[i][j]);
6792: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 6793: }
6794: printf("\n");
6795: fprintf(ficlog,"\n");
6796: }
1.203 brouard 6797: #endif
1.126 brouard 6798:
6799: free_matrix(a,1,npar,1,npar);
6800: free_matrix(y,1,npar,1,npar);
6801: free_vector(x,1,npar);
6802: free_ivector(indx,1,npar);
1.203 brouard 6803: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 6804:
6805:
6806: }
6807:
6808: /*************** hessian matrix ****************/
6809: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 6810: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 6811: int i;
6812: int l=1, lmax=20;
1.203 brouard 6813: double k1,k2, res, fx;
1.132 brouard 6814: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 6815: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
6816: int k=0,kmax=10;
6817: double l1;
6818:
6819: fx=func(x);
6820: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 6821: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 6822: l1=pow(10,l);
6823: delts=delt;
6824: for(k=1 ; k <kmax; k=k+1){
6825: delt = delta*(l1*k);
6826: p2[theta]=x[theta] +delt;
1.145 brouard 6827: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 6828: p2[theta]=x[theta]-delt;
6829: k2=func(p2)-fx;
6830: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 6831: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 6832:
1.203 brouard 6833: #ifdef DEBUGHESSII
1.126 brouard 6834: 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);
6835: 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);
6836: #endif
6837: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
6838: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
6839: k=kmax;
6840: }
6841: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 6842: k=kmax; l=lmax*10;
1.126 brouard 6843: }
6844: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
6845: delts=delt;
6846: }
1.203 brouard 6847: } /* End loop k */
1.126 brouard 6848: }
6849: delti[theta]=delts;
6850: return res;
6851:
6852: }
6853:
1.203 brouard 6854: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 6855: {
6856: int i;
1.164 brouard 6857: int l=1, lmax=20;
1.126 brouard 6858: double k1,k2,k3,k4,res,fx;
1.132 brouard 6859: double p2[MAXPARM+1];
1.203 brouard 6860: int k, kmax=1;
6861: double v1, v2, cv12, lc1, lc2;
1.208 brouard 6862:
6863: int firstime=0;
1.203 brouard 6864:
1.126 brouard 6865: fx=func(x);
1.203 brouard 6866: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 6867: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 6868: p2[thetai]=x[thetai]+delti[thetai]*k;
6869: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 6870: k1=func(p2)-fx;
6871:
1.203 brouard 6872: p2[thetai]=x[thetai]+delti[thetai]*k;
6873: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 6874: k2=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: k3=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: k4=func(p2)-fx;
1.203 brouard 6883: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
6884: if(k1*k2*k3*k4 <0.){
1.208 brouard 6885: firstime=1;
1.203 brouard 6886: kmax=kmax+10;
1.208 brouard 6887: }
6888: if(kmax >=10 || firstime ==1){
1.354 brouard 6889: /* What are the thetai and thetaj? thetai/ncovmodel thetai=(thetai-thetai%ncovmodel)/ncovmodel +thetai%ncovmodel=(line,pos) */
1.246 brouard 6890: 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);
6891: 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 6892: 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);
6893: 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);
6894: }
6895: #ifdef DEBUGHESSIJ
6896: v1=hess[thetai][thetai];
6897: v2=hess[thetaj][thetaj];
6898: cv12=res;
6899: /* Computing eigen value of Hessian matrix */
6900: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6901: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6902: if ((lc2 <0) || (lc1 <0) ){
6903: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
6904: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
6905: 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);
6906: 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);
6907: }
1.126 brouard 6908: #endif
6909: }
6910: return res;
6911: }
6912:
1.203 brouard 6913: /* Not done yet: Was supposed to fix if not exactly at the maximum */
6914: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
6915: /* { */
6916: /* int i; */
6917: /* int l=1, lmax=20; */
6918: /* double k1,k2,k3,k4,res,fx; */
6919: /* double p2[MAXPARM+1]; */
6920: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
6921: /* int k=0,kmax=10; */
6922: /* double l1; */
6923:
6924: /* fx=func(x); */
6925: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
6926: /* l1=pow(10,l); */
6927: /* delts=delt; */
6928: /* for(k=1 ; k <kmax; k=k+1){ */
6929: /* delt = delti*(l1*k); */
6930: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
6931: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
6932: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
6933: /* k1=func(p2)-fx; */
6934:
6935: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
6936: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
6937: /* k2=func(p2)-fx; */
6938:
6939: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
6940: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
6941: /* k3=func(p2)-fx; */
6942:
6943: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
6944: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
6945: /* k4=func(p2)-fx; */
6946: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
6947: /* #ifdef DEBUGHESSIJ */
6948: /* 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); */
6949: /* 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); */
6950: /* #endif */
6951: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
6952: /* k=kmax; */
6953: /* } */
6954: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
6955: /* k=kmax; l=lmax*10; */
6956: /* } */
6957: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
6958: /* delts=delt; */
6959: /* } */
6960: /* } /\* End loop k *\/ */
6961: /* } */
6962: /* delti[theta]=delts; */
6963: /* return res; */
6964: /* } */
6965:
6966:
1.126 brouard 6967: /************** Inverse of matrix **************/
6968: void ludcmp(double **a, int n, int *indx, double *d)
6969: {
6970: int i,imax,j,k;
6971: double big,dum,sum,temp;
6972: double *vv;
6973:
6974: vv=vector(1,n);
6975: *d=1.0;
6976: for (i=1;i<=n;i++) {
6977: big=0.0;
6978: for (j=1;j<=n;j++)
6979: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 6980: if (big == 0.0){
6981: printf(" Singular Hessian matrix at row %d:\n",i);
6982: for (j=1;j<=n;j++) {
6983: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
6984: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
6985: }
6986: fflush(ficlog);
6987: fclose(ficlog);
6988: nrerror("Singular matrix in routine ludcmp");
6989: }
1.126 brouard 6990: vv[i]=1.0/big;
6991: }
6992: for (j=1;j<=n;j++) {
6993: for (i=1;i<j;i++) {
6994: sum=a[i][j];
6995: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
6996: a[i][j]=sum;
6997: }
6998: big=0.0;
6999: for (i=j;i<=n;i++) {
7000: sum=a[i][j];
7001: for (k=1;k<j;k++)
7002: sum -= a[i][k]*a[k][j];
7003: a[i][j]=sum;
7004: if ( (dum=vv[i]*fabs(sum)) >= big) {
7005: big=dum;
7006: imax=i;
7007: }
7008: }
7009: if (j != imax) {
7010: for (k=1;k<=n;k++) {
7011: dum=a[imax][k];
7012: a[imax][k]=a[j][k];
7013: a[j][k]=dum;
7014: }
7015: *d = -(*d);
7016: vv[imax]=vv[j];
7017: }
7018: indx[j]=imax;
7019: if (a[j][j] == 0.0) a[j][j]=TINY;
7020: if (j != n) {
7021: dum=1.0/(a[j][j]);
7022: for (i=j+1;i<=n;i++) a[i][j] *= dum;
7023: }
7024: }
7025: free_vector(vv,1,n); /* Doesn't work */
7026: ;
7027: }
7028:
7029: void lubksb(double **a, int n, int *indx, double b[])
7030: {
7031: int i,ii=0,ip,j;
7032: double sum;
7033:
7034: for (i=1;i<=n;i++) {
7035: ip=indx[i];
7036: sum=b[ip];
7037: b[ip]=b[i];
7038: if (ii)
7039: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
7040: else if (sum) ii=i;
7041: b[i]=sum;
7042: }
7043: for (i=n;i>=1;i--) {
7044: sum=b[i];
7045: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
7046: b[i]=sum/a[i][i];
7047: }
7048: }
7049:
7050: void pstamp(FILE *fichier)
7051: {
1.196 brouard 7052: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 7053: }
7054:
1.297 brouard 7055: void date2dmy(double date,double *day, double *month, double *year){
7056: double yp=0., yp1=0., yp2=0.;
7057:
7058: yp1=modf(date,&yp);/* extracts integral of date in yp and
7059: fractional in yp1 */
7060: *year=yp;
7061: yp2=modf((yp1*12),&yp);
7062: *month=yp;
7063: yp1=modf((yp2*30.5),&yp);
7064: *day=yp;
7065: if(*day==0) *day=1;
7066: if(*month==0) *month=1;
7067: }
7068:
1.253 brouard 7069:
7070:
1.126 brouard 7071: /************ Frequencies ********************/
1.251 brouard 7072: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 7073: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
7074: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 7075: { /* Some frequencies as well as proposing some starting values */
1.332 brouard 7076: /* Frequencies of any combination of dummy covariate used in the model equation */
1.265 brouard 7077: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 7078: int iind=0, iage=0;
7079: int mi; /* Effective wave */
7080: int first;
7081: double ***freq; /* Frequencies */
1.268 brouard 7082: 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 */
7083: 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 7084: double *meanq, *stdq, *idq;
1.226 brouard 7085: double **meanqt;
7086: double *pp, **prop, *posprop, *pospropt;
7087: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
7088: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
7089: double agebegin, ageend;
7090:
7091: pp=vector(1,nlstate);
1.251 brouard 7092: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 7093: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
7094: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
7095: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
7096: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 7097: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 7098: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 7099: meanqt=matrix(1,lastpass,1,nqtveff);
7100: strcpy(fileresp,"P_");
7101: strcat(fileresp,fileresu);
7102: /*strcat(fileresphtm,fileresu);*/
7103: if((ficresp=fopen(fileresp,"w"))==NULL) {
7104: printf("Problem with prevalence resultfile: %s\n", fileresp);
7105: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
7106: exit(0);
7107: }
1.240 brouard 7108:
1.226 brouard 7109: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
7110: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
7111: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
7112: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
7113: fflush(ficlog);
7114: exit(70);
7115: }
7116: else{
7117: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 7118: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 7119: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 7120: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
7121: }
1.319 brouard 7122: 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 7123:
1.226 brouard 7124: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
7125: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
7126: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
7127: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
7128: fflush(ficlog);
7129: exit(70);
1.240 brouard 7130: } else{
1.226 brouard 7131: 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 7132: ,<hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 7133: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 7134: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
7135: }
1.319 brouard 7136: 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 7137:
1.253 brouard 7138: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
7139: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 7140: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 7141: j1=0;
1.126 brouard 7142:
1.227 brouard 7143: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
1.335 brouard 7144: j=cptcoveff; /* Only simple dummy covariates used in the model */
1.330 brouard 7145: /* j=cptcovn; /\* Only dummy covariates of the model *\/ */
1.226 brouard 7146: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 7147:
7148:
1.226 brouard 7149: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
7150: reference=low_education V1=0,V2=0
7151: med_educ V1=1 V2=0,
7152: high_educ V1=0 V2=1
1.330 brouard 7153: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcovn
1.226 brouard 7154: */
1.249 brouard 7155: dateintsum=0;
7156: k2cpt=0;
7157:
1.253 brouard 7158: if(cptcoveff == 0 )
1.265 brouard 7159: nl=1; /* Constant and age model only */
1.253 brouard 7160: else
7161: nl=2;
1.265 brouard 7162:
7163: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
7164: /* Loop on nj=1 or 2 if dummy covariates j!=0
1.335 brouard 7165: * Loop on j1(1 to 2**cptcoveff) covariate combination
1.265 brouard 7166: * freq[s1][s2][iage] =0.
7167: * Loop on iind
7168: * ++freq[s1][s2][iage] weighted
7169: * end iind
7170: * if covariate and j!0
7171: * headers Variable on one line
7172: * endif cov j!=0
7173: * header of frequency table by age
7174: * Loop on age
7175: * pp[s1]+=freq[s1][s2][iage] weighted
7176: * pos+=freq[s1][s2][iage] weighted
7177: * Loop on s1 initial state
7178: * fprintf(ficresp
7179: * end s1
7180: * end age
7181: * if j!=0 computes starting values
7182: * end compute starting values
7183: * end j1
7184: * end nl
7185: */
1.253 brouard 7186: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
7187: if(nj==1)
7188: j=0; /* First pass for the constant */
1.265 brouard 7189: else{
1.335 brouard 7190: 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 7191: }
1.251 brouard 7192: first=1;
1.332 brouard 7193: 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 7194: posproptt=0.;
1.330 brouard 7195: /*printf("cptcovn=%d Tvaraff=%d", cptcovn,Tvaraff[1]);
1.251 brouard 7196: scanf("%d", i);*/
7197: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 7198: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 7199: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 7200: freq[i][s2][m]=0;
1.251 brouard 7201:
7202: for (i=1; i<=nlstate; i++) {
1.240 brouard 7203: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 7204: prop[i][m]=0;
7205: posprop[i]=0;
7206: pospropt[i]=0;
7207: }
1.283 brouard 7208: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 7209: idq[z1]=0.;
7210: meanq[z1]=0.;
7211: stdq[z1]=0.;
1.283 brouard 7212: }
7213: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 7214: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 7215: /* meanqt[m][z1]=0.; */
7216: /* } */
7217: /* } */
1.251 brouard 7218: /* dateintsum=0; */
7219: /* k2cpt=0; */
7220:
1.265 brouard 7221: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 7222: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
7223: bool=1;
7224: if(j !=0){
7225: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
1.335 brouard 7226: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
7227: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
1.251 brouard 7228: /* if(Tvaraff[z1] ==-20){ */
7229: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
7230: /* }else if(Tvaraff[z1] ==-10){ */
7231: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
1.330 brouard 7232: /* }else */ /* TODO TODO codtabm(j1,z1) or codtabm(j1,Tvaraff[z1]]z1)*/
1.335 brouard 7233: /* 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); */
7234: if(Tvaraff[z1]<1 || Tvaraff[z1]>=NCOVMAX)
1.338 brouard 7235: printf("Error Tvaraff[z1]=%d<1 or >=%d, cptcoveff=%d model=1+age+%s\n",Tvaraff[z1],NCOVMAX, cptcoveff, model);
1.332 brouard 7236: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]){ /* for combination j1 of covariates */
1.265 brouard 7237: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 7238: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
1.332 brouard 7239: /* 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", */
7240: /* bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),*/
7241: /* j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
1.251 brouard 7242: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
7243: } /* Onlyf fixed */
7244: } /* end z1 */
1.335 brouard 7245: } /* cptcoveff > 0 */
1.251 brouard 7246: } /* end any */
7247: }/* end j==0 */
1.265 brouard 7248: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 7249: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 7250: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 7251: m=mw[mi][iind];
7252: if(j!=0){
7253: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
1.335 brouard 7254: for (z1=1; z1<=cptcoveff; z1++) {
1.251 brouard 7255: if( Fixed[Tmodelind[z1]]==1){
1.341 brouard 7256: /* iv= Tvar[Tmodelind[z1]]-ncovcol-nqv; /\* Good *\/ */
7257: iv= Tvar[Tmodelind[z1]]; /* Good *//* because cotvar starts now at first at ncovcol+nqv+ntv */
1.332 brouard 7258: 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 7259: value is -1, we don't select. It differs from the
7260: constant and age model which counts them. */
7261: bool=0; /* not selected */
7262: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
1.334 brouard 7263: /* i1=Tvaraff[z1]; */
7264: /* i2=TnsdVar[i1]; */
7265: /* i3=nbcode[i1][i2]; */
7266: /* i4=covar[i1][iind]; */
7267: /* if(i4 != i3){ */
7268: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) { /* Bug valgrind */
1.251 brouard 7269: bool=0;
7270: }
7271: }
7272: }
7273: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
7274: } /* end j==0 */
7275: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 7276: if(bool==1){ /*Selected */
1.251 brouard 7277: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
7278: and mw[mi+1][iind]. dh depends on stepm. */
7279: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
7280: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
7281: if(m >=firstpass && m <=lastpass){
7282: k2=anint[m][iind]+(mint[m][iind]/12.);
7283: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
7284: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
7285: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
7286: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
7287: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
7288: if (m<lastpass) {
7289: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
7290: /* 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]); */
7291: if(s[m][iind]==-1)
7292: 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.));
7293: 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 7294: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean on known values only */
7295: if(!isnan(covar[ncovcol+z1][iind])){
1.332 brouard 7296: idq[z1]=idq[z1]+weight[iind];
7297: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
7298: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; *//*error*/
7299: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
1.311 brouard 7300: }
1.284 brouard 7301: }
1.251 brouard 7302: /* if((int)agev[m][iind] == 55) */
7303: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
7304: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
7305: 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 7306: }
1.251 brouard 7307: } /* end if between passes */
7308: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
7309: dateintsum=dateintsum+k2; /* on all covariates ?*/
7310: k2cpt++;
7311: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 7312: }
1.251 brouard 7313: }else{
7314: bool=1;
7315: }/* end bool 2 */
7316: } /* end m */
1.284 brouard 7317: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
7318: /* idq[z1]=idq[z1]+weight[iind]; */
7319: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
7320: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
7321: /* } */
1.251 brouard 7322: } /* end bool */
7323: } /* end iind = 1 to imx */
1.319 brouard 7324: /* prop[s][age] is fed for any initial and valid live state as well as
1.251 brouard 7325: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
7326:
7327:
7328: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.335 brouard 7329: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
1.265 brouard 7330: pstamp(ficresp);
1.335 brouard 7331: if (cptcoveff>0 && j!=0){
1.265 brouard 7332: pstamp(ficresp);
1.251 brouard 7333: printf( "\n#********** Variable ");
7334: fprintf(ficresp, "\n#********** Variable ");
7335: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
7336: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
7337: fprintf(ficlog, "\n#********** Variable ");
1.340 brouard 7338: for (z1=1; z1<=cptcoveff; z1++){
1.251 brouard 7339: if(!FixedV[Tvaraff[z1]]){
1.330 brouard 7340: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7341: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7342: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7343: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7344: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.250 brouard 7345: }else{
1.330 brouard 7346: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7347: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7348: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7349: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7350: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.251 brouard 7351: }
7352: }
7353: printf( "**********\n#");
7354: fprintf(ficresp, "**********\n#");
7355: fprintf(ficresphtm, "**********</h3>\n");
7356: fprintf(ficresphtmfr, "**********</h3>\n");
7357: fprintf(ficlog, "**********\n");
7358: }
1.284 brouard 7359: /*
7360: Printing means of quantitative variables if any
7361: */
7362: for (z1=1; z1<= nqfveff; z1++) {
1.311 brouard 7363: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.3g (weighted) individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.312 brouard 7364: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
1.284 brouard 7365: if(weightopt==1){
7366: printf(" Weighted mean and standard deviation of");
7367: fprintf(ficlog," Weighted mean and standard deviation of");
7368: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
7369: }
1.311 brouard 7370: /* mu = \frac{w x}{\sum w}
7371: var = \frac{\sum w (x-mu)^2}{\sum w} = \frac{w x^2}{\sum w} - mu^2
7372: */
7373: 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]));
7374: 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]));
7375: 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 7376: }
7377: /* for (z1=1; z1<= nqtveff; z1++) { */
7378: /* for(m=1;m<=lastpass;m++){ */
7379: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
7380: /* } */
7381: /* } */
1.283 brouard 7382:
1.251 brouard 7383: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.335 brouard 7384: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
1.265 brouard 7385: fprintf(ficresp, " Age");
1.335 brouard 7386: if(nj==2) for (z1=1; z1<=cptcoveff; z1++) {
7387: 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]]);
7388: fprintf(ficresp, " V%d=%d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7389: }
1.251 brouard 7390: for(i=1; i<=nlstate;i++) {
1.335 brouard 7391: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 7392: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
7393: }
1.335 brouard 7394: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 7395: fprintf(ficresphtm, "\n");
7396:
7397: /* Header of frequency table by age */
7398: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
7399: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 7400: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 7401: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 7402: if(s2!=0 && m!=0)
7403: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 7404: }
1.226 brouard 7405: }
1.251 brouard 7406: fprintf(ficresphtmfr, "\n");
7407:
7408: /* For each age */
7409: for(iage=iagemin; iage <= iagemax+3; iage++){
7410: fprintf(ficresphtm,"<tr>");
7411: if(iage==iagemax+1){
7412: fprintf(ficlog,"1");
7413: fprintf(ficresphtmfr,"<tr><th>0</th> ");
7414: }else if(iage==iagemax+2){
7415: fprintf(ficlog,"0");
7416: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
7417: }else if(iage==iagemax+3){
7418: fprintf(ficlog,"Total");
7419: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
7420: }else{
1.240 brouard 7421: if(first==1){
1.251 brouard 7422: first=0;
7423: printf("See log file for details...\n");
7424: }
7425: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
7426: fprintf(ficlog,"Age %d", iage);
7427: }
1.265 brouard 7428: for(s1=1; s1 <=nlstate ; s1++){
7429: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
7430: pp[s1] += freq[s1][m][iage];
1.251 brouard 7431: }
1.265 brouard 7432: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 7433: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 7434: pos += freq[s1][m][iage];
7435: if(pp[s1]>=1.e-10){
1.251 brouard 7436: if(first==1){
1.265 brouard 7437: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 7438: }
1.265 brouard 7439: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 7440: }else{
7441: if(first==1)
1.265 brouard 7442: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
7443: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 7444: }
7445: }
7446:
1.265 brouard 7447: for(s1=1; s1 <=nlstate ; s1++){
7448: /* posprop[s1]=0; */
7449: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
7450: pp[s1] += freq[s1][m][iage];
7451: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
7452:
7453: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
7454: pos += pp[s1]; /* pos is the total number of transitions until this age */
7455: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
7456: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
7457: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
7458: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
7459: }
7460:
7461: /* Writing ficresp */
1.335 brouard 7462: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 7463: if( iage <= iagemax){
7464: fprintf(ficresp," %d",iage);
7465: }
7466: }else if( nj==2){
7467: if( iage <= iagemax){
7468: fprintf(ficresp," %d",iage);
1.335 brouard 7469: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.265 brouard 7470: }
1.240 brouard 7471: }
1.265 brouard 7472: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 7473: if(pos>=1.e-5){
1.251 brouard 7474: if(first==1)
1.265 brouard 7475: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
7476: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 7477: }else{
7478: if(first==1)
1.265 brouard 7479: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
7480: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 7481: }
7482: if( iage <= iagemax){
7483: if(pos>=1.e-5){
1.335 brouard 7484: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 7485: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
7486: }else if( nj==2){
7487: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
7488: }
7489: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
7490: /*probs[iage][s1][j1]= pp[s1]/pos;*/
7491: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
7492: } else{
1.335 brouard 7493: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
1.265 brouard 7494: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 7495: }
1.240 brouard 7496: }
1.265 brouard 7497: pospropt[s1] +=posprop[s1];
7498: } /* end loop s1 */
1.251 brouard 7499: /* pospropt=0.; */
1.265 brouard 7500: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 7501: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 7502: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 7503: if(first==1){
1.265 brouard 7504: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 7505: }
1.265 brouard 7506: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
7507: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 7508: }
1.265 brouard 7509: if(s1!=0 && m!=0)
7510: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 7511: }
1.265 brouard 7512: } /* end loop s1 */
1.251 brouard 7513: posproptt=0.;
1.265 brouard 7514: for(s1=1; s1 <=nlstate; s1++){
7515: posproptt += pospropt[s1];
1.251 brouard 7516: }
7517: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 7518: fprintf(ficresphtm,"</tr>\n");
1.335 brouard 7519: if((cptcoveff==0 && nj==1)|| nj==2 ) {
1.265 brouard 7520: if(iage <= iagemax)
7521: fprintf(ficresp,"\n");
1.240 brouard 7522: }
1.251 brouard 7523: if(first==1)
7524: printf("Others in log...\n");
7525: fprintf(ficlog,"\n");
7526: } /* end loop age iage */
1.265 brouard 7527:
1.251 brouard 7528: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 7529: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 7530: if(posproptt < 1.e-5){
1.265 brouard 7531: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 7532: }else{
1.265 brouard 7533: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 7534: }
1.226 brouard 7535: }
1.251 brouard 7536: fprintf(ficresphtm,"</tr>\n");
7537: fprintf(ficresphtm,"</table>\n");
7538: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 7539: if(posproptt < 1.e-5){
1.251 brouard 7540: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
7541: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 7542: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
7543: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 7544: invalidvarcomb[j1]=1;
1.226 brouard 7545: }else{
1.338 brouard 7546: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced (or no resultline).</p>",j1);
1.251 brouard 7547: invalidvarcomb[j1]=0;
1.226 brouard 7548: }
1.251 brouard 7549: fprintf(ficresphtmfr,"</table>\n");
7550: fprintf(ficlog,"\n");
7551: if(j!=0){
7552: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 7553: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 7554: for(k=1; k <=(nlstate+ndeath); k++){
7555: if (k != i) {
1.265 brouard 7556: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 7557: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 7558: if(j1==1){ /* All dummy covariates to zero */
7559: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
7560: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 7561: printf("%d%d ",i,k);
7562: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 7563: 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]));
7564: 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]));
7565: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 7566: }
1.253 brouard 7567: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
7568: for(iage=iagemin; iage <= iagemax+3; iage++){
7569: x[iage]= (double)iage;
7570: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 7571: /* 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 7572: }
1.268 brouard 7573: /* Some are not finite, but linreg will ignore these ages */
7574: no=0;
1.253 brouard 7575: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 7576: pstart[s1]=b;
7577: pstart[s1-1]=a;
1.252 brouard 7578: }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 */
7579: 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]);
7580: 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 7581: 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 7582: printf("%d%d ",i,k);
7583: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 7584: 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 7585: }else{ /* Other cases, like quantitative fixed or varying covariates */
7586: ;
7587: }
7588: /* printf("%12.7f )", param[i][jj][k]); */
7589: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 7590: s1++;
1.251 brouard 7591: } /* end jj */
7592: } /* end k!= i */
7593: } /* end k */
1.265 brouard 7594: } /* end i, s1 */
1.251 brouard 7595: } /* end j !=0 */
7596: } /* end selected combination of covariate j1 */
7597: if(j==0){ /* We can estimate starting values from the occurences in each case */
7598: printf("#Freqsummary: Starting values for the constants:\n");
7599: fprintf(ficlog,"\n");
1.265 brouard 7600: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 7601: for(k=1; k <=(nlstate+ndeath); k++){
7602: if (k != i) {
7603: printf("%d%d ",i,k);
7604: fprintf(ficlog,"%d%d ",i,k);
7605: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 7606: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 7607: if(jj==1){ /* Age has to be done */
1.265 brouard 7608: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
7609: 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]));
7610: 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 7611: }
7612: /* printf("%12.7f )", param[i][jj][k]); */
7613: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 7614: s1++;
1.250 brouard 7615: }
1.251 brouard 7616: printf("\n");
7617: fprintf(ficlog,"\n");
1.250 brouard 7618: }
7619: }
1.284 brouard 7620: } /* end of state i */
1.251 brouard 7621: printf("#Freqsummary\n");
7622: fprintf(ficlog,"\n");
1.265 brouard 7623: for(s1=-1; s1 <=nlstate+ndeath; s1++){
7624: for(s2=-1; s2 <=nlstate+ndeath; s2++){
7625: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
7626: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
7627: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
7628: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
7629: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
7630: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 7631: /* } */
7632: }
1.265 brouard 7633: } /* end loop s1 */
1.251 brouard 7634:
7635: printf("\n");
7636: fprintf(ficlog,"\n");
7637: } /* end j=0 */
1.249 brouard 7638: } /* end j */
1.252 brouard 7639:
1.253 brouard 7640: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 7641: for(i=1, jk=1; i <=nlstate; i++){
7642: for(j=1; j <=nlstate+ndeath; j++){
7643: if(j!=i){
7644: /*ca[0]= k+'a'-1;ca[1]='\0';*/
7645: printf("%1d%1d",i,j);
7646: fprintf(ficparo,"%1d%1d",i,j);
7647: for(k=1; k<=ncovmodel;k++){
7648: /* printf(" %lf",param[i][j][k]); */
7649: /* fprintf(ficparo," %lf",param[i][j][k]); */
7650: p[jk]=pstart[jk];
7651: printf(" %f ",pstart[jk]);
7652: fprintf(ficparo," %f ",pstart[jk]);
7653: jk++;
7654: }
7655: printf("\n");
7656: fprintf(ficparo,"\n");
7657: }
7658: }
7659: }
7660: } /* end mle=-2 */
1.226 brouard 7661: dateintmean=dateintsum/k2cpt;
1.296 brouard 7662: date2dmy(dateintmean,&jintmean,&mintmean,&aintmean);
1.240 brouard 7663:
1.226 brouard 7664: fclose(ficresp);
7665: fclose(ficresphtm);
7666: fclose(ficresphtmfr);
1.283 brouard 7667: free_vector(idq,1,nqfveff);
1.226 brouard 7668: free_vector(meanq,1,nqfveff);
1.284 brouard 7669: free_vector(stdq,1,nqfveff);
1.226 brouard 7670: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 7671: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
7672: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 7673: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 7674: free_vector(pospropt,1,nlstate);
7675: free_vector(posprop,1,nlstate);
1.251 brouard 7676: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 7677: free_vector(pp,1,nlstate);
7678: /* End of freqsummary */
7679: }
1.126 brouard 7680:
1.268 brouard 7681: /* Simple linear regression */
7682: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
7683:
7684: /* y=a+bx regression */
7685: double sumx = 0.0; /* sum of x */
7686: double sumx2 = 0.0; /* sum of x**2 */
7687: double sumxy = 0.0; /* sum of x * y */
7688: double sumy = 0.0; /* sum of y */
7689: double sumy2 = 0.0; /* sum of y**2 */
7690: double sume2 = 0.0; /* sum of square or residuals */
7691: double yhat;
7692:
7693: double denom=0;
7694: int i;
7695: int ne=*no;
7696:
7697: for ( i=ifi, ne=0;i<=ila;i++) {
7698: if(!isfinite(x[i]) || !isfinite(y[i])){
7699: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
7700: continue;
7701: }
7702: ne=ne+1;
7703: sumx += x[i];
7704: sumx2 += x[i]*x[i];
7705: sumxy += x[i] * y[i];
7706: sumy += y[i];
7707: sumy2 += y[i]*y[i];
7708: denom = (ne * sumx2 - sumx*sumx);
7709: /* 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); */
7710: }
7711:
7712: denom = (ne * sumx2 - sumx*sumx);
7713: if (denom == 0) {
7714: // vertical, slope m is infinity
7715: *b = INFINITY;
7716: *a = 0;
7717: if (r) *r = 0;
7718: return 1;
7719: }
7720:
7721: *b = (ne * sumxy - sumx * sumy) / denom;
7722: *a = (sumy * sumx2 - sumx * sumxy) / denom;
7723: if (r!=NULL) {
7724: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
7725: sqrt((sumx2 - sumx*sumx/ne) *
7726: (sumy2 - sumy*sumy/ne));
7727: }
7728: *no=ne;
7729: for ( i=ifi, ne=0;i<=ila;i++) {
7730: if(!isfinite(x[i]) || !isfinite(y[i])){
7731: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
7732: continue;
7733: }
7734: ne=ne+1;
7735: yhat = y[i] - *a -*b* x[i];
7736: sume2 += yhat * yhat ;
7737:
7738: denom = (ne * sumx2 - sumx*sumx);
7739: /* 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); */
7740: }
7741: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
7742: *sa= *sb * sqrt(sumx2/ne);
7743:
7744: return 0;
7745: }
7746:
1.126 brouard 7747: /************ Prevalence ********************/
1.227 brouard 7748: 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)
7749: {
7750: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
7751: in each health status at the date of interview (if between dateprev1 and dateprev2).
7752: We still use firstpass and lastpass as another selection.
7753: */
1.126 brouard 7754:
1.227 brouard 7755: int i, m, jk, j1, bool, z1,j, iv;
7756: int mi; /* Effective wave */
7757: int iage;
1.359 brouard 7758: double agebegin; /*, ageend;*/
1.227 brouard 7759:
7760: double **prop;
7761: double posprop;
7762: double y2; /* in fractional years */
7763: int iagemin, iagemax;
7764: int first; /** to stop verbosity which is redirected to log file */
7765:
7766: iagemin= (int) agemin;
7767: iagemax= (int) agemax;
7768: /*pp=vector(1,nlstate);*/
1.251 brouard 7769: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 7770: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
7771: j1=0;
1.222 brouard 7772:
1.227 brouard 7773: /*j=cptcoveff;*/
7774: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 7775:
1.288 brouard 7776: first=0;
1.335 brouard 7777: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of simple dummy covariates */
1.227 brouard 7778: for (i=1; i<=nlstate; i++)
1.251 brouard 7779: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 7780: prop[i][iage]=0.0;
7781: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
7782: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
7783: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
7784:
7785: for (i=1; i<=imx; i++) { /* Each individual */
7786: bool=1;
7787: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
7788: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
7789: m=mw[mi][i];
7790: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
7791: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
7792: for (z1=1; z1<=cptcoveff; z1++){
7793: if( Fixed[Tmodelind[z1]]==1){
1.341 brouard 7794: iv= Tvar[Tmodelind[z1]];/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
1.332 brouard 7795: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) /* iv=1 to ntv, right modality */
1.227 brouard 7796: bool=0;
7797: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
1.332 brouard 7798: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) {
1.227 brouard 7799: bool=0;
7800: }
7801: }
7802: if(bool==1){ /* Otherwise we skip that wave/person */
7803: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
7804: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
7805: if(m >=firstpass && m <=lastpass){
7806: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
7807: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
7808: if(agev[m][i]==0) agev[m][i]=iagemax+1;
7809: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 7810: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 7811: 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);
7812: exit(1);
7813: }
7814: if (s[m][i]>0 && s[m][i]<=nlstate) {
7815: /*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]]);*/
7816: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
7817: prop[s[m][i]][iagemax+3] += weight[i];
7818: } /* end valid statuses */
7819: } /* end selection of dates */
7820: } /* end selection of waves */
7821: } /* end bool */
7822: } /* end wave */
7823: } /* end individual */
7824: for(i=iagemin; i <= iagemax+3; i++){
7825: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
7826: posprop += prop[jk][i];
7827: }
7828:
7829: for(jk=1; jk <=nlstate ; jk++){
7830: if( i <= iagemax){
7831: if(posprop>=1.e-5){
7832: probs[i][jk][j1]= prop[jk][i]/posprop;
7833: } else{
1.288 brouard 7834: if(!first){
7835: first=1;
1.266 brouard 7836: 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]);
7837: }else{
1.288 brouard 7838: 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 7839: }
7840: }
7841: }
7842: }/* end jk */
7843: }/* end i */
1.222 brouard 7844: /*} *//* end i1 */
1.227 brouard 7845: } /* end j1 */
1.222 brouard 7846:
1.227 brouard 7847: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
7848: /*free_vector(pp,1,nlstate);*/
1.251 brouard 7849: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 7850: } /* End of prevalence */
1.126 brouard 7851:
7852: /************* Waves Concatenation ***************/
7853:
7854: 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)
7855: {
1.298 brouard 7856: /* 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 7857: Death is a valid wave (if date is known).
7858: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
7859: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
1.298 brouard 7860: and mw[mi+1][i]. dh depends on stepm. s[m][i] exists for any wave from firstpass to lastpass
1.227 brouard 7861: */
1.126 brouard 7862:
1.224 brouard 7863: int i=0, mi=0, m=0, mli=0;
1.126 brouard 7864: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
7865: double sum=0., jmean=0.;*/
1.224 brouard 7866: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 7867: int j, k=0,jk, ju, jl;
7868: double sum=0.;
7869: first=0;
1.214 brouard 7870: firstwo=0;
1.217 brouard 7871: firsthree=0;
1.218 brouard 7872: firstfour=0;
1.164 brouard 7873: jmin=100000;
1.126 brouard 7874: jmax=-1;
7875: jmean=0.;
1.224 brouard 7876:
7877: /* Treating live states */
1.214 brouard 7878: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 7879: mi=0; /* First valid wave */
1.227 brouard 7880: mli=0; /* Last valid wave */
1.309 brouard 7881: m=firstpass; /* Loop on waves */
7882: while(s[m][i] <= nlstate){ /* a live state or unknown state */
1.227 brouard 7883: 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 */
7884: mli=m-1;/* mw[++mi][i]=m-1; */
7885: }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 7886: 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 7887: mli=m;
1.224 brouard 7888: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
7889: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 7890: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 7891: }
1.309 brouard 7892: else{ /* m = lastpass, eventual special issue with warning */
1.224 brouard 7893: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 7894: break;
1.224 brouard 7895: #else
1.317 brouard 7896: 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 7897: if(firsthree == 0){
1.302 brouard 7898: 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 7899: firsthree=1;
1.317 brouard 7900: }else if(firsthree >=1 && firsthree < 10){
7901: 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);
7902: firsthree++;
7903: }else if(firsthree == 10){
7904: printf("Information, too many Information flags: no more reported to log either\n");
7905: fprintf(ficlog,"Information, too many Information flags: no more reported to log either\n");
7906: firsthree++;
7907: }else{
7908: firsthree++;
1.227 brouard 7909: }
1.309 brouard 7910: mw[++mi][i]=m; /* Valid transition with unknown status */
1.227 brouard 7911: mli=m;
7912: }
7913: if(s[m][i]==-2){ /* Vital status is really unknown */
7914: nbwarn++;
1.309 brouard 7915: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified?not a transition */
1.227 brouard 7916: 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);
7917: 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);
7918: }
7919: break;
7920: }
7921: break;
1.224 brouard 7922: #endif
1.227 brouard 7923: }/* End m >= lastpass */
1.126 brouard 7924: }/* end while */
1.224 brouard 7925:
1.227 brouard 7926: /* 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 7927: /* After last pass */
1.224 brouard 7928: /* Treating death states */
1.214 brouard 7929: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 7930: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
7931: /* } */
1.126 brouard 7932: mi++; /* Death is another wave */
7933: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 7934: /* Only death is a correct wave */
1.126 brouard 7935: mw[mi][i]=m;
1.257 brouard 7936: } /* else not in a death state */
1.224 brouard 7937: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 7938: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 7939: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.309 brouard 7940: 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 7941: nbwarn++;
7942: if(firstfiv==0){
1.309 brouard 7943: 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 7944: firstfiv=1;
7945: }else{
1.309 brouard 7946: 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 7947: }
1.309 brouard 7948: s[m][i]=nlstate+1; /* Fixing the status as death. Be careful if multiple death states */
7949: }else{ /* Month of Death occured afer last wave month, potential bias */
1.227 brouard 7950: nberr++;
7951: if(firstwo==0){
1.309 brouard 7952: 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 7953: firstwo=1;
7954: }
1.309 brouard 7955: 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 7956: }
1.257 brouard 7957: }else{ /* if date of interview is unknown */
1.227 brouard 7958: /* death is known but not confirmed by death status at any wave */
7959: if(firstfour==0){
1.309 brouard 7960: 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 7961: firstfour=1;
7962: }
1.309 brouard 7963: 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 7964: }
1.224 brouard 7965: } /* end if date of death is known */
7966: #endif
1.309 brouard 7967: wav[i]=mi; /* mi should be the last effective wave (or mli), */
7968: /* wav[i]=mw[mi][i]; */
1.126 brouard 7969: if(mi==0){
7970: nbwarn++;
7971: if(first==0){
1.227 brouard 7972: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
7973: first=1;
1.126 brouard 7974: }
7975: if(first==1){
1.227 brouard 7976: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 7977: }
7978: } /* end mi==0 */
7979: } /* End individuals */
1.214 brouard 7980: /* wav and mw are no more changed */
1.223 brouard 7981:
1.317 brouard 7982: printf("Information, you have to check %d informations which haven't been logged!\n",firsthree);
7983: fprintf(ficlog,"Information, you have to check %d informations which haven't been logged!\n",firsthree);
7984:
7985:
1.126 brouard 7986: for(i=1; i<=imx; i++){
7987: for(mi=1; mi<wav[i];mi++){
7988: if (stepm <=0)
1.227 brouard 7989: dh[mi][i]=1;
1.126 brouard 7990: else{
1.260 brouard 7991: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 7992: if (agedc[i] < 2*AGESUP) {
7993: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
7994: if(j==0) j=1; /* Survives at least one month after exam */
7995: else if(j<0){
7996: nberr++;
1.359 brouard 7997: 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 7998: j=1; /* Temporary Dangerous patch */
7999: 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 8000: 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 8001: 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);
8002: }
8003: k=k+1;
8004: if (j >= jmax){
8005: jmax=j;
8006: ijmax=i;
8007: }
8008: if (j <= jmin){
8009: jmin=j;
8010: ijmin=i;
8011: }
8012: sum=sum+j;
8013: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
8014: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
8015: }
8016: }
8017: else{
8018: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 8019: /* 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 8020:
1.227 brouard 8021: k=k+1;
8022: if (j >= jmax) {
8023: jmax=j;
8024: ijmax=i;
8025: }
8026: else if (j <= jmin){
8027: jmin=j;
8028: ijmin=i;
8029: }
8030: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
8031: /*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]);*/
8032: if(j<0){
8033: nberr++;
1.359 brouard 8034: 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]);
8035: 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 8036: }
8037: sum=sum+j;
8038: }
8039: jk= j/stepm;
8040: jl= j -jk*stepm;
8041: ju= j -(jk+1)*stepm;
8042: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
8043: if(jl==0){
8044: dh[mi][i]=jk;
8045: bh[mi][i]=0;
8046: }else{ /* We want a negative bias in order to only have interpolation ie
8047: * to avoid the price of an extra matrix product in likelihood */
8048: dh[mi][i]=jk+1;
8049: bh[mi][i]=ju;
8050: }
8051: }else{
8052: if(jl <= -ju){
8053: dh[mi][i]=jk;
8054: bh[mi][i]=jl; /* bias is positive if real duration
8055: * is higher than the multiple of stepm and negative otherwise.
8056: */
8057: }
8058: else{
8059: dh[mi][i]=jk+1;
8060: bh[mi][i]=ju;
8061: }
8062: if(dh[mi][i]==0){
8063: dh[mi][i]=1; /* At least one step */
8064: bh[mi][i]=ju; /* At least one step */
8065: /* 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);*/
8066: }
8067: } /* end if mle */
1.126 brouard 8068: }
8069: } /* end wave */
8070: }
8071: jmean=sum/k;
8072: 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 8073: 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 8074: }
1.126 brouard 8075:
8076: /*********** Tricode ****************************/
1.220 brouard 8077: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 8078: {
8079: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
8080: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
8081: * Boring subroutine which should only output nbcode[Tvar[j]][k]
8082: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
8083: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
8084: */
1.130 brouard 8085:
1.242 brouard 8086: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
8087: int modmaxcovj=0; /* Modality max of covariates j */
8088: int cptcode=0; /* Modality max of covariates j */
8089: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 8090:
8091:
1.242 brouard 8092: /* cptcoveff=0; */
8093: /* *cptcov=0; */
1.126 brouard 8094:
1.242 brouard 8095: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 8096: for (k=1; k <= maxncov; k++)
8097: for(j=1; j<=2; j++)
8098: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 8099:
1.242 brouard 8100: /* Loop on covariates without age and products and no quantitative variable */
1.335 brouard 8101: 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 8102: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
1.343 brouard 8103: /* printf("Testing k=%d, cptcovt=%d\n",k, cptcovt); */
1.349 brouard 8104: 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 8105: switch(Fixed[k]) {
8106: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
1.311 brouard 8107: modmaxcovj=0;
8108: modmincovj=0;
1.242 brouard 8109: 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 8110: /* 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 8111: ij=(int)(covar[Tvar[k]][i]);
8112: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
8113: * If product of Vn*Vm, still boolean *:
8114: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
8115: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
8116: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
8117: modality of the nth covariate of individual i. */
8118: if (ij > modmaxcovj)
8119: modmaxcovj=ij;
8120: else if (ij < modmincovj)
8121: modmincovj=ij;
1.287 brouard 8122: if (ij <0 || ij >1 ){
1.311 brouard 8123: printf("ERROR, IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
8124: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
8125: fflush(ficlog);
8126: exit(1);
1.287 brouard 8127: }
8128: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 8129: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
8130: exit(1);
8131: }else
8132: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
8133: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
8134: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
8135: /* getting the maximum value of the modality of the covariate
8136: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
8137: female ies 1, then modmaxcovj=1.
8138: */
8139: } /* end for loop on individuals i */
8140: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
8141: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
8142: cptcode=modmaxcovj;
8143: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
8144: /*for (i=0; i<=cptcode; i++) {*/
8145: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
8146: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
8147: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
8148: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
8149: if( j != -1){
8150: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
8151: covariate for which somebody answered excluding
8152: undefined. Usually 2: 0 and 1. */
8153: }
8154: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
8155: covariate for which somebody answered including
8156: undefined. Usually 3: -1, 0 and 1. */
8157: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
8158: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
8159: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 8160:
1.242 brouard 8161: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
8162: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
8163: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
8164: /* modmincovj=3; modmaxcovj = 7; */
8165: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
8166: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
8167: /* defining two dummy variables: variables V1_1 and V1_2.*/
8168: /* nbcode[Tvar[j]][ij]=k; */
8169: /* nbcode[Tvar[j]][1]=0; */
8170: /* nbcode[Tvar[j]][2]=1; */
8171: /* nbcode[Tvar[j]][3]=2; */
8172: /* To be continued (not working yet). */
8173: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 8174:
8175: /* 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*/
8176: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
8177: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
8178: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
8179: /*, could be restored in the future */
8180: 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 8181: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
8182: break;
8183: }
8184: ij++;
1.287 brouard 8185: 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 8186: cptcode = ij; /* New max modality for covar j */
8187: } /* end of loop on modality i=-1 to 1 or more */
8188: break;
8189: case 1: /* Testing on varying covariate, could be simple and
8190: * should look at waves or product of fixed *
8191: * varying. No time to test -1, assuming 0 and 1 only */
8192: ij=0;
8193: for(i=0; i<=1;i++){
8194: nbcode[Tvar[k]][++ij]=i;
8195: }
8196: break;
8197: default:
8198: break;
8199: } /* end switch */
8200: } /* end dummy test */
1.349 brouard 8201: if(Dummy[k]==1 && Typevar[k] !=1 && Typevar[k] !=3 && Fixed ==0){ /* Fixed Quantitative covariate and not age product */
1.311 brouard 8202: 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 8203: if(Tvar[k]<=0 || Tvar[k]>=NCOVMAX){
8204: printf("Error k=%d \n",k);
8205: exit(1);
8206: }
1.311 brouard 8207: if(isnan(covar[Tvar[k]][i])){
8208: printf("ERROR, IMaCh doesn't treat fixed quantitative covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
8209: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
8210: fflush(ficlog);
8211: exit(1);
8212: }
8213: }
1.335 brouard 8214: } /* end Quanti */
1.287 brouard 8215: } /* 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 8216:
8217: for (k=-1; k< maxncov; k++) Ndum[k]=0;
8218: /* Look at fixed dummy (single or product) covariates to check empty modalities */
8219: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
8220: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
8221: 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 */
8222: 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 */
8223: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
8224: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
8225:
8226: ij=0;
8227: /* 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 8228: 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 */
8229: /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
1.242 brouard 8230: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
8231: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
1.335 brouard 8232: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy simple and non empty in the model */
8233: /* Typevar[k] =0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
8234: /* 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 8235: /* If product not in single variable we don't print results */
8236: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
1.335 brouard 8237: ++ij;/* V5 + V4 + V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V1, *//* V5 quanti, V2 quanti, V4, V3, V1 dummies */
8238: /* k= 1 2 3 4 5 6 7 8 9 */
8239: /* Tvar[k]= 5 4 3 6 5 2 7 1 1 */
8240: /* ij 1 2 3 */
8241: /* Tvaraff[ij]= 4 3 1 */
8242: /* Tmodelind[ij]=2 3 9 */
8243: /* TmodelInvind[ij]=2 1 1 */
1.242 brouard 8244: 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*/
8245: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
8246: 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 */
8247: if(Fixed[k]!=0)
8248: anyvaryingduminmodel=1;
8249: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
8250: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
8251: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
8252: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
8253: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
8254: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
8255: }
8256: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
8257: /* ij--; */
8258: /* cptcoveff=ij; /\*Number of total covariates*\/ */
1.335 brouard 8259: *cptcov=ij; /* cptcov= Number of total real effective simple dummies (fixed or time arying) effective (used as cptcoveff in other functions)
1.242 brouard 8260: * because they can be excluded from the model and real
8261: * if in the model but excluded because missing values, but how to get k from ij?*/
8262: for(j=ij+1; j<= cptcovt; j++){
8263: Tvaraff[j]=0;
8264: Tmodelind[j]=0;
8265: }
8266: for(j=ntveff+1; j<= cptcovt; j++){
8267: TmodelInvind[j]=0;
8268: }
8269: /* To be sorted */
8270: ;
8271: }
1.126 brouard 8272:
1.145 brouard 8273:
1.126 brouard 8274: /*********** Health Expectancies ****************/
8275:
1.235 brouard 8276: 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 8277:
8278: {
8279: /* Health expectancies, no variances */
1.329 brouard 8280: /* cij is the combination in the list of combination of dummy covariates */
8281: /* strstart is a string of time at start of computing */
1.164 brouard 8282: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 8283: int nhstepma, nstepma; /* Decreasing with age */
8284: double age, agelim, hf;
8285: double ***p3mat;
8286: double eip;
8287:
1.238 brouard 8288: /* pstamp(ficreseij); */
1.126 brouard 8289: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
8290: fprintf(ficreseij,"# Age");
8291: for(i=1; i<=nlstate;i++){
8292: for(j=1; j<=nlstate;j++){
8293: fprintf(ficreseij," e%1d%1d ",i,j);
8294: }
8295: fprintf(ficreseij," e%1d. ",i);
8296: }
8297: fprintf(ficreseij,"\n");
8298:
8299:
8300: if(estepm < stepm){
8301: printf ("Problem %d lower than %d\n",estepm, stepm);
8302: }
8303: else hstepm=estepm;
8304: /* We compute the life expectancy from trapezoids spaced every estepm months
8305: * This is mainly to measure the difference between two models: for example
8306: * if stepm=24 months pijx are given only every 2 years and by summing them
8307: * we are calculating an estimate of the Life Expectancy assuming a linear
8308: * progression in between and thus overestimating or underestimating according
8309: * to the curvature of the survival function. If, for the same date, we
8310: * estimate the model with stepm=1 month, we can keep estepm to 24 months
8311: * to compare the new estimate of Life expectancy with the same linear
8312: * hypothesis. A more precise result, taking into account a more precise
8313: * curvature will be obtained if estepm is as small as stepm. */
8314:
8315: /* For example we decided to compute the life expectancy with the smallest unit */
8316: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
8317: nhstepm is the number of hstepm from age to agelim
8318: nstepm is the number of stepm from age to agelin.
1.270 brouard 8319: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 8320: and note for a fixed period like estepm months */
8321: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
8322: survival function given by stepm (the optimization length). Unfortunately it
8323: means that if the survival funtion is printed only each two years of age and if
8324: you sum them up and add 1 year (area under the trapezoids) you won't get the same
8325: results. So we changed our mind and took the option of the best precision.
8326: */
8327: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
8328:
8329: agelim=AGESUP;
8330: /* If stepm=6 months */
8331: /* Computed by stepm unit matrices, product of hstepm matrices, stored
8332: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
8333:
8334: /* nhstepm age range expressed in number of stepm */
8335: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
8336: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
8337: /* if (stepm >= YEARM) hstepm=1;*/
8338: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
8339: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8340:
8341: for (age=bage; age<=fage; age ++){
8342: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
8343: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
8344: /* if (stepm >= YEARM) hstepm=1;*/
8345: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
8346:
8347: /* If stepm=6 months */
8348: /* Computed by stepm unit matrices, product of hstepma matrices, stored
8349: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
1.330 brouard 8350: /* 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 8351: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 8352:
8353: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
8354:
8355: printf("%d|",(int)age);fflush(stdout);
8356: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
8357:
8358: /* Computing expectancies */
8359: for(i=1; i<=nlstate;i++)
8360: for(j=1; j<=nlstate;j++)
8361: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
8362: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
8363:
8364: /* 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]);*/
8365:
8366: }
8367:
8368: fprintf(ficreseij,"%3.0f",age );
8369: for(i=1; i<=nlstate;i++){
8370: eip=0;
8371: for(j=1; j<=nlstate;j++){
8372: eip +=eij[i][j][(int)age];
8373: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
8374: }
8375: fprintf(ficreseij,"%9.4f", eip );
8376: }
8377: fprintf(ficreseij,"\n");
8378:
8379: }
8380: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8381: printf("\n");
8382: fprintf(ficlog,"\n");
8383:
8384: }
8385:
1.235 brouard 8386: 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 8387:
8388: {
8389: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 8390: to initial status i, ei. .
1.126 brouard 8391: */
1.336 brouard 8392: /* Very time consuming function, but already optimized with precov */
1.126 brouard 8393: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
8394: int nhstepma, nstepma; /* Decreasing with age */
8395: double age, agelim, hf;
8396: double ***p3matp, ***p3matm, ***varhe;
8397: double **dnewm,**doldm;
8398: double *xp, *xm;
8399: double **gp, **gm;
8400: double ***gradg, ***trgradg;
8401: int theta;
8402:
8403: double eip, vip;
8404:
8405: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
8406: xp=vector(1,npar);
8407: xm=vector(1,npar);
8408: dnewm=matrix(1,nlstate*nlstate,1,npar);
8409: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
8410:
8411: pstamp(ficresstdeij);
8412: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
8413: fprintf(ficresstdeij,"# Age");
8414: for(i=1; i<=nlstate;i++){
8415: for(j=1; j<=nlstate;j++)
8416: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
8417: fprintf(ficresstdeij," e%1d. ",i);
8418: }
8419: fprintf(ficresstdeij,"\n");
8420:
8421: pstamp(ficrescveij);
8422: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
8423: fprintf(ficrescveij,"# Age");
8424: for(i=1; i<=nlstate;i++)
8425: for(j=1; j<=nlstate;j++){
8426: cptj= (j-1)*nlstate+i;
8427: for(i2=1; i2<=nlstate;i2++)
8428: for(j2=1; j2<=nlstate;j2++){
8429: cptj2= (j2-1)*nlstate+i2;
8430: if(cptj2 <= cptj)
8431: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
8432: }
8433: }
8434: fprintf(ficrescveij,"\n");
8435:
8436: if(estepm < stepm){
8437: printf ("Problem %d lower than %d\n",estepm, stepm);
8438: }
8439: else hstepm=estepm;
8440: /* We compute the life expectancy from trapezoids spaced every estepm months
8441: * This is mainly to measure the difference between two models: for example
8442: * if stepm=24 months pijx are given only every 2 years and by summing them
8443: * we are calculating an estimate of the Life Expectancy assuming a linear
8444: * progression in between and thus overestimating or underestimating according
8445: * to the curvature of the survival function. If, for the same date, we
8446: * estimate the model with stepm=1 month, we can keep estepm to 24 months
8447: * to compare the new estimate of Life expectancy with the same linear
8448: * hypothesis. A more precise result, taking into account a more precise
8449: * curvature will be obtained if estepm is as small as stepm. */
8450:
8451: /* For example we decided to compute the life expectancy with the smallest unit */
8452: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
8453: nhstepm is the number of hstepm from age to agelim
8454: nstepm is the number of stepm from age to agelin.
8455: Look at hpijx to understand the reason of that which relies in memory size
8456: and note for a fixed period like estepm months */
8457: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
8458: survival function given by stepm (the optimization length). Unfortunately it
8459: means that if the survival funtion is printed only each two years of age and if
8460: you sum them up and add 1 year (area under the trapezoids) you won't get the same
8461: results. So we changed our mind and took the option of the best precision.
8462: */
8463: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
8464:
8465: /* If stepm=6 months */
8466: /* nhstepm age range expressed in number of stepm */
8467: agelim=AGESUP;
8468: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
8469: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
8470: /* if (stepm >= YEARM) hstepm=1;*/
8471: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
8472:
8473: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8474: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8475: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
8476: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
8477: gp=matrix(0,nhstepm,1,nlstate*nlstate);
8478: gm=matrix(0,nhstepm,1,nlstate*nlstate);
8479:
8480: for (age=bage; age<=fage; age ++){
8481: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
8482: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
8483: /* if (stepm >= YEARM) hstepm=1;*/
8484: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 8485:
1.126 brouard 8486: /* If stepm=6 months */
8487: /* Computed by stepm unit matrices, product of hstepma matrices, stored
8488: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
8489:
8490: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 8491:
1.126 brouard 8492: /* Computing Variances of health expectancies */
8493: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
8494: decrease memory allocation */
8495: for(theta=1; theta <=npar; theta++){
8496: for(i=1; i<=npar; i++){
1.222 brouard 8497: xp[i] = x[i] + (i==theta ?delti[theta]:0);
8498: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 8499: }
1.235 brouard 8500: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
8501: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 8502:
1.126 brouard 8503: for(j=1; j<= nlstate; j++){
1.222 brouard 8504: for(i=1; i<=nlstate; i++){
8505: for(h=0; h<=nhstepm-1; h++){
8506: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
8507: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
8508: }
8509: }
1.126 brouard 8510: }
1.218 brouard 8511:
1.126 brouard 8512: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 8513: for(h=0; h<=nhstepm-1; h++){
8514: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
8515: }
1.126 brouard 8516: }/* End theta */
8517:
8518:
8519: for(h=0; h<=nhstepm-1; h++)
8520: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 8521: for(theta=1; theta <=npar; theta++)
8522: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 8523:
1.218 brouard 8524:
1.222 brouard 8525: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 8526: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 8527: varhe[ij][ji][(int)age] =0.;
1.218 brouard 8528:
1.222 brouard 8529: printf("%d|",(int)age);fflush(stdout);
8530: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
8531: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 8532: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 8533: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
8534: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
8535: for(ij=1;ij<=nlstate*nlstate;ij++)
8536: for(ji=1;ji<=nlstate*nlstate;ji++)
8537: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 8538: }
8539: }
1.320 brouard 8540: /* if((int)age ==50){ */
8541: /* printf(" age=%d cij=%d nres=%d varhe[%d][%d]=%f ",(int)age, cij, nres, 1,2,varhe[1][2]); */
8542: /* } */
1.126 brouard 8543: /* Computing expectancies */
1.235 brouard 8544: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 8545: for(i=1; i<=nlstate;i++)
8546: for(j=1; j<=nlstate;j++)
1.222 brouard 8547: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
8548: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 8549:
1.222 brouard 8550: /* 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 8551:
1.222 brouard 8552: }
1.269 brouard 8553:
8554: /* Standard deviation of expectancies ij */
1.126 brouard 8555: fprintf(ficresstdeij,"%3.0f",age );
8556: for(i=1; i<=nlstate;i++){
8557: eip=0.;
8558: vip=0.;
8559: for(j=1; j<=nlstate;j++){
1.222 brouard 8560: eip += eij[i][j][(int)age];
8561: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
8562: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
8563: 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 8564: }
8565: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
8566: }
8567: fprintf(ficresstdeij,"\n");
1.218 brouard 8568:
1.269 brouard 8569: /* Variance of expectancies ij */
1.126 brouard 8570: fprintf(ficrescveij,"%3.0f",age );
8571: for(i=1; i<=nlstate;i++)
8572: for(j=1; j<=nlstate;j++){
1.222 brouard 8573: cptj= (j-1)*nlstate+i;
8574: for(i2=1; i2<=nlstate;i2++)
8575: for(j2=1; j2<=nlstate;j2++){
8576: cptj2= (j2-1)*nlstate+i2;
8577: if(cptj2 <= cptj)
8578: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
8579: }
1.126 brouard 8580: }
8581: fprintf(ficrescveij,"\n");
1.218 brouard 8582:
1.126 brouard 8583: }
8584: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
8585: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
8586: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
8587: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
8588: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8589: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8590: printf("\n");
8591: fprintf(ficlog,"\n");
1.218 brouard 8592:
1.126 brouard 8593: free_vector(xm,1,npar);
8594: free_vector(xp,1,npar);
8595: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
8596: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
8597: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
8598: }
1.218 brouard 8599:
1.126 brouard 8600: /************ Variance ******************/
1.235 brouard 8601: 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 8602: {
1.361 brouard 8603: /** Computes the matrix of variance covariance of health expectancies e.j= sum_i w_i e_ij where w_i depends of popbased,
8604: * either cross-sectional or implied.
8605: * 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 8606: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
8607: * double **newm;
8608: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
8609: */
1.218 brouard 8610:
8611: /* int movingaverage(); */
8612: double **dnewm,**doldm;
8613: double **dnewmp,**doldmp;
8614: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 8615: int first=0;
1.218 brouard 8616: int k;
8617: double *xp;
1.279 brouard 8618: double **gp, **gm; /**< for var eij */
8619: double ***gradg, ***trgradg; /**< for var eij */
8620: double **gradgp, **trgradgp; /**< for var p point j */
8621: double *gpp, *gmp; /**< for var p point j */
1.362 brouard 8622: double **varppt; /**< for var p.3 p.death nlstate+1 to nlstate+ndeath */
1.218 brouard 8623: double ***p3mat;
8624: double age,agelim, hf;
8625: /* double ***mobaverage; */
8626: int theta;
8627: char digit[4];
8628: char digitp[25];
8629:
8630: char fileresprobmorprev[FILENAMELENGTH];
8631:
8632: if(popbased==1){
8633: if(mobilav!=0)
8634: strcpy(digitp,"-POPULBASED-MOBILAV_");
8635: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
8636: }
8637: else
8638: strcpy(digitp,"-STABLBASED_");
1.126 brouard 8639:
1.218 brouard 8640: /* if (mobilav!=0) { */
8641: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8642: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
8643: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
8644: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
8645: /* } */
8646: /* } */
8647:
8648: strcpy(fileresprobmorprev,"PRMORPREV-");
8649: sprintf(digit,"%-d",ij);
8650: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
8651: strcat(fileresprobmorprev,digit); /* Tvar to be done */
8652: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
8653: strcat(fileresprobmorprev,fileresu);
8654: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
8655: printf("Problem with resultfile: %s\n", fileresprobmorprev);
8656: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
8657: }
8658: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
8659: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
8660: pstamp(ficresprobmorprev);
8661: 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 8662: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
1.337 brouard 8663:
8664: /* We use TinvDoQresult[nres][resultmodel[nres][j] we sort according to the equation model and the resultline: it is a choice */
8665: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ /\* To be done*\/ */
8666: /* fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
8667: /* } */
8668: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */ /* To be done*/
1.344 brouard 8669: /* fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); */
1.337 brouard 8670: fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 8671: }
1.337 brouard 8672: /* for(j=1;j<=cptcoveff;j++) */
8673: /* fprintf(ficresprobmorprev," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,TnsdVar[Tvaraff[j]])]); */
1.238 brouard 8674: fprintf(ficresprobmorprev,"\n");
8675:
1.218 brouard 8676: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
8677: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
8678: fprintf(ficresprobmorprev," p.%-d SE",j);
8679: for(i=1; i<=nlstate;i++)
8680: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
8681: }
8682: fprintf(ficresprobmorprev,"\n");
8683:
8684: fprintf(ficgp,"\n# Routine varevsij");
8685: fprintf(ficgp,"\nunset title \n");
8686: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
8687: 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");
8688: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 8689:
1.361 brouard 8690: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath); /* In fact, currently a double */
1.218 brouard 8691: pstamp(ficresvij);
8692: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
8693: if(popbased==1)
8694: 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);
8695: else
8696: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
8697: fprintf(ficresvij,"# Age");
8698: for(i=1; i<=nlstate;i++)
8699: for(j=1; j<=nlstate;j++)
8700: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
8701: fprintf(ficresvij,"\n");
8702:
8703: xp=vector(1,npar);
8704: dnewm=matrix(1,nlstate,1,npar);
8705: doldm=matrix(1,nlstate,1,nlstate);
8706: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
8707: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
8708:
8709: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
8710: gpp=vector(nlstate+1,nlstate+ndeath);
8711: gmp=vector(nlstate+1,nlstate+ndeath);
8712: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 8713:
1.218 brouard 8714: if(estepm < stepm){
8715: printf ("Problem %d lower than %d\n",estepm, stepm);
8716: }
8717: else hstepm=estepm;
8718: /* For example we decided to compute the life expectancy with the smallest unit */
8719: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
8720: nhstepm is the number of hstepm from age to agelim
8721: nstepm is the number of stepm from age to agelim.
8722: Look at function hpijx to understand why because of memory size limitations,
8723: we decided (b) to get a life expectancy respecting the most precise curvature of the
8724: survival function given by stepm (the optimization length). Unfortunately it
8725: means that if the survival funtion is printed every two years of age and if
8726: you sum them up and add 1 year (area under the trapezoids) you won't get the same
8727: results. So we changed our mind and took the option of the best precision.
8728: */
8729: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
8730: agelim = AGESUP;
8731: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
8732: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
8733: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
8734: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8735: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
8736: gp=matrix(0,nhstepm,1,nlstate);
8737: gm=matrix(0,nhstepm,1,nlstate);
8738:
8739:
8740: for(theta=1; theta <=npar; theta++){
8741: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
8742: xp[i] = x[i] + (i==theta ?delti[theta]:0);
8743: }
1.279 brouard 8744: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
8745: * returns into prlim .
1.288 brouard 8746: */
1.242 brouard 8747: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 8748:
8749: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 8750: if (popbased==1) {
8751: if(mobilav ==0){
8752: for(i=1; i<=nlstate;i++)
8753: prlim[i][i]=probs[(int)age][i][ij];
8754: }else{ /* mobilav */
8755: for(i=1; i<=nlstate;i++)
8756: prlim[i][i]=mobaverage[(int)age][i][ij];
8757: }
8758: }
1.361 brouard 8759: /**< Computes the shifted plus (gp) transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h.
1.279 brouard 8760: */
8761: 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 8762: /**< 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 8763: * at horizon h in state j including mortality.
8764: */
1.218 brouard 8765: for(j=1; j<= nlstate; j++){
8766: for(h=0; h<=nhstepm; h++){
8767: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
1.361 brouard 8768: gp[h][j] += prlim[i][i]*p3mat[i][j][h]; /* gp[h][j]= w_i h_pij */
1.218 brouard 8769: }
8770: }
1.279 brouard 8771: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 8772: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 8773: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 8774: */
1.361 brouard 8775: for(j=nlstate+1;j<=nlstate+ndeath;j++){ /* Currently only once for theta plus p.3(age) Sum_i wi pi3*/
1.218 brouard 8776: for(i=1,gpp[j]=0.; i<= nlstate; i++)
8777: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 8778: }
8779:
8780: /* Again with minus shift */
1.218 brouard 8781:
8782: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
8783: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 8784:
1.242 brouard 8785: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 8786:
8787: if (popbased==1) {
8788: if(mobilav ==0){
8789: for(i=1; i<=nlstate;i++)
8790: prlim[i][i]=probs[(int)age][i][ij];
8791: }else{ /* mobilav */
8792: for(i=1; i<=nlstate;i++)
8793: prlim[i][i]=mobaverage[(int)age][i][ij];
8794: }
8795: }
8796:
1.361 brouard 8797: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres); /* Still minus */
1.218 brouard 8798:
1.361 brouard 8799: for(j=1; j<= nlstate; j++){ /* gm[h][j]= Sum_i of wi * pij = h_p.j */
1.218 brouard 8800: for(h=0; h<=nhstepm; h++){
8801: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
8802: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
8803: }
8804: }
8805: /* This for computing probability of death (h=1 means
8806: computed over hstepm matrices product = hstepm*stepm months)
1.361 brouard 8807: as a weighted average of prlim. j is death. gmp[3]=sum_i w_i*p_i3=p.3 minus theta
1.218 brouard 8808: */
1.361 brouard 8809: for(j=nlstate+1;j<=nlstate+ndeath;j++){ /* Currently only once theta_minus p.3=Sum_i wi pi3*/
1.218 brouard 8810: for(i=1,gmp[j]=0.; i<= nlstate; i++)
8811: gmp[j] += prlim[i][i]*p3mat[i][j][1];
8812: }
1.279 brouard 8813: /* end shifting computations */
8814:
1.361 brouard 8815: /**< Computing gradient of p.j matrix at horizon h and still for one parameter of vector theta
8816: * equation 31 and 32
1.279 brouard 8817: */
1.361 brouard 8818: 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)
8819: * equation 24 */
1.218 brouard 8820: for(h=0; h<=nhstepm; h++){
8821: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
8822: }
1.361 brouard 8823: /**< Gradient of overall mortality p.3 (or p.death)
1.279 brouard 8824: */
1.361 brouard 8825: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* computes grad of p.3 from wi+pi3 grad p.3 (theta) */
1.218 brouard 8826: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
8827: }
8828:
8829: } /* End theta */
1.279 brouard 8830:
1.361 brouard 8831: /* We got the gradient matrix for each theta and each state j of gradg(h]theta][j)=grad(_hp.j(theta) */
8832: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar);
1.218 brouard 8833:
1.361 brouard 8834: for(h=0; h<=nhstepm; h++) /* veij */ /* computes the transposed of grad (_hp.j(theta)*/
1.218 brouard 8835: for(j=1; j<=nlstate;j++)
8836: for(theta=1; theta <=npar; theta++)
8837: trgradg[h][j][theta]=gradg[h][theta][j];
8838:
1.361 brouard 8839: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* computes transposed of grad p.3 (theta)*/
1.218 brouard 8840: for(theta=1; theta <=npar; theta++)
8841: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 8842: /**< as well as its transposed matrix
8843: */
1.218 brouard 8844:
8845: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
8846: for(i=1;i<=nlstate;i++)
8847: for(j=1;j<=nlstate;j++)
8848: vareij[i][j][(int)age] =0.;
1.279 brouard 8849:
8850: /* Computing trgradg by matcov by gradg at age and summing over h
1.361 brouard 8851: * and k (nhstepm) formula 32 of article
8852: * Lievre-Brouard-Heathcote so that for each j, computes the cov(e.j,e.k) (formula 31).
8853: * for given h and k computes trgradg[h](i,j) matcov (theta) gradg(k)(i,j) into vareij[i][j] which is
8854: cov(e.i,e.j) and sums on h and k
8855: * including the covariances.
1.279 brouard 8856: */
8857:
1.218 brouard 8858: for(h=0;h<=nhstepm;h++){
8859: for(k=0;k<=nhstepm;k++){
8860: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
8861: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
8862: for(i=1;i<=nlstate;i++)
8863: for(j=1;j<=nlstate;j++)
1.361 brouard 8864: 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)
8865: including the covariances of e.j */
1.218 brouard 8866: }
8867: }
8868:
1.361 brouard 8869: /* Mortality: pptj is p.3 or p.death = trgradgp by cov by gradgp, variance of
8870: * p.3=1-p..=1-sum i p.i overall mortality computed directly because
1.279 brouard 8871: * we compute the grad (wix pijx) instead of grad (pijx),even if
1.361 brouard 8872: * wix is independent of theta.
1.279 brouard 8873: */
1.218 brouard 8874: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
8875: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
8876: for(j=nlstate+1;j<=nlstate+ndeath;j++)
8877: for(i=nlstate+1;i<=nlstate+ndeath;i++)
1.361 brouard 8878: varppt[j][i]=doldmp[j][i]; /* This is the variance of p.3 */
1.218 brouard 8879: /* end ppptj */
8880: /* x centered again */
8881:
1.242 brouard 8882: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 8883:
8884: if (popbased==1) {
8885: if(mobilav ==0){
8886: for(i=1; i<=nlstate;i++)
8887: prlim[i][i]=probs[(int)age][i][ij];
8888: }else{ /* mobilav */
8889: for(i=1; i<=nlstate;i++)
8890: prlim[i][i]=mobaverage[(int)age][i][ij];
8891: }
8892: }
8893:
8894: /* This for computing probability of death (h=1 means
8895: computed over hstepm (estepm) matrices product = hstepm*stepm months)
8896: as a weighted average of prlim.
8897: */
1.235 brouard 8898: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 8899: for(j=nlstate+1;j<=nlstate+ndeath;j++){
8900: for(i=1,gmp[j]=0.;i<= nlstate; i++)
1.361 brouard 8901: gmp[j] += prlim[i][i]*p3mat[i][j][1]; /* gmp[j] is p.3 */
1.218 brouard 8902: }
8903: /* end probability of death */
8904:
8905: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
8906: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
1.361 brouard 8907: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));/* p.3 (STD p.3) */
1.218 brouard 8908: for(i=1; i<=nlstate;i++){
1.361 brouard 8909: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]); /* wi, pi3 */
1.218 brouard 8910: }
8911: }
8912: fprintf(ficresprobmorprev,"\n");
8913:
8914: fprintf(ficresvij,"%.0f ",age );
8915: for(i=1; i<=nlstate;i++)
8916: for(j=1; j<=nlstate;j++){
8917: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
8918: }
8919: fprintf(ficresvij,"\n");
8920: free_matrix(gp,0,nhstepm,1,nlstate);
8921: free_matrix(gm,0,nhstepm,1,nlstate);
8922: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
8923: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
8924: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8925: } /* End age */
8926: free_vector(gpp,nlstate+1,nlstate+ndeath);
8927: free_vector(gmp,nlstate+1,nlstate+ndeath);
8928: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
8929: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
8930: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
8931: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
8932: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
8933: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
8934: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
8935: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
8936: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
8937: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
8938: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
8939: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
8940: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
8941: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
8942: 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);
8943: /* 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 8944: */
1.218 brouard 8945: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
8946: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 8947:
1.218 brouard 8948: free_vector(xp,1,npar);
8949: free_matrix(doldm,1,nlstate,1,nlstate);
8950: free_matrix(dnewm,1,nlstate,1,npar);
8951: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
8952: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
8953: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
8954: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8955: fclose(ficresprobmorprev);
8956: fflush(ficgp);
8957: fflush(fichtm);
8958: } /* end varevsij */
1.126 brouard 8959:
8960: /************ Variance of prevlim ******************/
1.269 brouard 8961: 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 8962: {
1.205 brouard 8963: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 8964: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 8965:
1.268 brouard 8966: double **dnewmpar,**doldm;
1.126 brouard 8967: int i, j, nhstepm, hstepm;
8968: double *xp;
8969: double *gp, *gm;
8970: double **gradg, **trgradg;
1.208 brouard 8971: double **mgm, **mgp;
1.126 brouard 8972: double age,agelim;
8973: int theta;
8974:
8975: pstamp(ficresvpl);
1.288 brouard 8976: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 8977: fprintf(ficresvpl,"# Age ");
8978: if(nresult >=1)
8979: fprintf(ficresvpl," Result# ");
1.126 brouard 8980: for(i=1; i<=nlstate;i++)
8981: fprintf(ficresvpl," %1d-%1d",i,i);
8982: fprintf(ficresvpl,"\n");
8983:
8984: xp=vector(1,npar);
1.268 brouard 8985: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 8986: doldm=matrix(1,nlstate,1,nlstate);
8987:
8988: hstepm=1*YEARM; /* Every year of age */
8989: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
8990: agelim = AGESUP;
8991: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
8992: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
8993: if (stepm >= YEARM) hstepm=1;
8994: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
8995: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 8996: mgp=matrix(1,npar,1,nlstate);
8997: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 8998: gp=vector(1,nlstate);
8999: gm=vector(1,nlstate);
9000:
9001: for(theta=1; theta <=npar; theta++){
9002: for(i=1; i<=npar; i++){ /* Computes gradient */
9003: xp[i] = x[i] + (i==theta ?delti[theta]:0);
9004: }
1.288 brouard 9005: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
9006: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
9007: /* else */
9008: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 9009: for(i=1;i<=nlstate;i++){
1.126 brouard 9010: gp[i] = prlim[i][i];
1.208 brouard 9011: mgp[theta][i] = prlim[i][i];
9012: }
1.126 brouard 9013: for(i=1; i<=npar; i++) /* Computes gradient */
9014: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 9015: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
9016: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
9017: /* else */
9018: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 9019: for(i=1;i<=nlstate;i++){
1.126 brouard 9020: gm[i] = prlim[i][i];
1.208 brouard 9021: mgm[theta][i] = prlim[i][i];
9022: }
1.126 brouard 9023: for(i=1;i<=nlstate;i++)
9024: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 9025: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 9026: } /* End theta */
9027:
9028: trgradg =matrix(1,nlstate,1,npar);
9029:
9030: for(j=1; j<=nlstate;j++)
9031: for(theta=1; theta <=npar; theta++)
9032: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 9033: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
9034: /* printf("\nmgm mgp %d ",(int)age); */
9035: /* for(j=1; j<=nlstate;j++){ */
9036: /* printf(" %d ",j); */
9037: /* for(theta=1; theta <=npar; theta++) */
9038: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
9039: /* printf("\n "); */
9040: /* } */
9041: /* } */
9042: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
9043: /* printf("\n gradg %d ",(int)age); */
9044: /* for(j=1; j<=nlstate;j++){ */
9045: /* printf("%d ",j); */
9046: /* for(theta=1; theta <=npar; theta++) */
9047: /* printf("%d %lf ",theta,gradg[theta][j]); */
9048: /* printf("\n "); */
9049: /* } */
9050: /* } */
1.126 brouard 9051:
9052: for(i=1;i<=nlstate;i++)
9053: varpl[i][(int)age] =0.;
1.209 brouard 9054: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 9055: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
9056: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 9057: }else{
1.268 brouard 9058: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
9059: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 9060: }
1.126 brouard 9061: for(i=1;i<=nlstate;i++)
9062: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
9063:
9064: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 9065: if(nresult >=1)
9066: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 9067: for(i=1; i<=nlstate;i++){
1.126 brouard 9068: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 9069: /* for(j=1;j<=nlstate;j++) */
9070: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
9071: }
1.126 brouard 9072: fprintf(ficresvpl,"\n");
9073: free_vector(gp,1,nlstate);
9074: free_vector(gm,1,nlstate);
1.208 brouard 9075: free_matrix(mgm,1,npar,1,nlstate);
9076: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 9077: free_matrix(gradg,1,npar,1,nlstate);
9078: free_matrix(trgradg,1,nlstate,1,npar);
9079: } /* End age */
9080:
9081: free_vector(xp,1,npar);
9082: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 9083: free_matrix(dnewmpar,1,nlstate,1,nlstate);
9084:
9085: }
9086:
9087:
9088: /************ Variance of backprevalence limit ******************/
1.269 brouard 9089: 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 9090: {
9091: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
9092: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
9093:
9094: double **dnewmpar,**doldm;
9095: int i, j, nhstepm, hstepm;
9096: double *xp;
9097: double *gp, *gm;
9098: double **gradg, **trgradg;
9099: double **mgm, **mgp;
9100: double age,agelim;
9101: int theta;
9102:
9103: pstamp(ficresvbl);
9104: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
9105: fprintf(ficresvbl,"# Age ");
9106: if(nresult >=1)
9107: fprintf(ficresvbl," Result# ");
9108: for(i=1; i<=nlstate;i++)
9109: fprintf(ficresvbl," %1d-%1d",i,i);
9110: fprintf(ficresvbl,"\n");
9111:
9112: xp=vector(1,npar);
9113: dnewmpar=matrix(1,nlstate,1,npar);
9114: doldm=matrix(1,nlstate,1,nlstate);
9115:
9116: hstepm=1*YEARM; /* Every year of age */
9117: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
9118: agelim = AGEINF;
9119: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
9120: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
9121: if (stepm >= YEARM) hstepm=1;
9122: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
9123: gradg=matrix(1,npar,1,nlstate);
9124: mgp=matrix(1,npar,1,nlstate);
9125: mgm=matrix(1,npar,1,nlstate);
9126: gp=vector(1,nlstate);
9127: gm=vector(1,nlstate);
9128:
9129: for(theta=1; theta <=npar; theta++){
9130: for(i=1; i<=npar; i++){ /* Computes gradient */
9131: xp[i] = x[i] + (i==theta ?delti[theta]:0);
9132: }
9133: if(mobilavproj > 0 )
9134: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
9135: else
9136: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
9137: for(i=1;i<=nlstate;i++){
9138: gp[i] = bprlim[i][i];
9139: mgp[theta][i] = bprlim[i][i];
9140: }
9141: for(i=1; i<=npar; i++) /* Computes gradient */
9142: xp[i] = x[i] - (i==theta ?delti[theta]:0);
9143: if(mobilavproj > 0 )
9144: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
9145: else
9146: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
9147: for(i=1;i<=nlstate;i++){
9148: gm[i] = bprlim[i][i];
9149: mgm[theta][i] = bprlim[i][i];
9150: }
9151: for(i=1;i<=nlstate;i++)
9152: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
9153: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
9154: } /* End theta */
9155:
9156: trgradg =matrix(1,nlstate,1,npar);
9157:
9158: for(j=1; j<=nlstate;j++)
9159: for(theta=1; theta <=npar; theta++)
9160: trgradg[j][theta]=gradg[theta][j];
9161: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
9162: /* printf("\nmgm mgp %d ",(int)age); */
9163: /* for(j=1; j<=nlstate;j++){ */
9164: /* printf(" %d ",j); */
9165: /* for(theta=1; theta <=npar; theta++) */
9166: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
9167: /* printf("\n "); */
9168: /* } */
9169: /* } */
9170: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
9171: /* printf("\n gradg %d ",(int)age); */
9172: /* for(j=1; j<=nlstate;j++){ */
9173: /* printf("%d ",j); */
9174: /* for(theta=1; theta <=npar; theta++) */
9175: /* printf("%d %lf ",theta,gradg[theta][j]); */
9176: /* printf("\n "); */
9177: /* } */
9178: /* } */
9179:
9180: for(i=1;i<=nlstate;i++)
9181: varbpl[i][(int)age] =0.;
9182: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
9183: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
9184: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
9185: }else{
9186: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
9187: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
9188: }
9189: for(i=1;i<=nlstate;i++)
9190: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
9191:
9192: fprintf(ficresvbl,"%.0f ",age );
9193: if(nresult >=1)
9194: fprintf(ficresvbl,"%d ",nres );
9195: for(i=1; i<=nlstate;i++)
9196: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
9197: fprintf(ficresvbl,"\n");
9198: free_vector(gp,1,nlstate);
9199: free_vector(gm,1,nlstate);
9200: free_matrix(mgm,1,npar,1,nlstate);
9201: free_matrix(mgp,1,npar,1,nlstate);
9202: free_matrix(gradg,1,npar,1,nlstate);
9203: free_matrix(trgradg,1,nlstate,1,npar);
9204: } /* End age */
9205:
9206: free_vector(xp,1,npar);
9207: free_matrix(doldm,1,nlstate,1,npar);
9208: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 9209:
9210: }
9211:
9212: /************ Variance of one-step probabilities ******************/
9213: 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 9214: {
9215: int i, j=0, k1, l1, tj;
9216: int k2, l2, j1, z1;
9217: int k=0, l;
9218: int first=1, first1, first2;
1.326 brouard 9219: int nres=0; /* New */
1.222 brouard 9220: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
9221: double **dnewm,**doldm;
9222: double *xp;
9223: double *gp, *gm;
9224: double **gradg, **trgradg;
9225: double **mu;
9226: double age, cov[NCOVMAX+1];
9227: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
9228: int theta;
9229: char fileresprob[FILENAMELENGTH];
9230: char fileresprobcov[FILENAMELENGTH];
9231: char fileresprobcor[FILENAMELENGTH];
9232: double ***varpij;
9233:
9234: strcpy(fileresprob,"PROB_");
1.356 brouard 9235: strcat(fileresprob,fileresu);
1.222 brouard 9236: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
9237: printf("Problem with resultfile: %s\n", fileresprob);
9238: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
9239: }
9240: strcpy(fileresprobcov,"PROBCOV_");
9241: strcat(fileresprobcov,fileresu);
9242: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
9243: printf("Problem with resultfile: %s\n", fileresprobcov);
9244: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
9245: }
9246: strcpy(fileresprobcor,"PROBCOR_");
9247: strcat(fileresprobcor,fileresu);
9248: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
9249: printf("Problem with resultfile: %s\n", fileresprobcor);
9250: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
9251: }
9252: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
9253: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
9254: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
9255: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
9256: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
9257: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
9258: pstamp(ficresprob);
9259: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
9260: fprintf(ficresprob,"# Age");
9261: pstamp(ficresprobcov);
9262: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
9263: fprintf(ficresprobcov,"# Age");
9264: pstamp(ficresprobcor);
9265: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
9266: fprintf(ficresprobcor,"# Age");
1.126 brouard 9267:
9268:
1.222 brouard 9269: for(i=1; i<=nlstate;i++)
9270: for(j=1; j<=(nlstate+ndeath);j++){
9271: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
9272: fprintf(ficresprobcov," p%1d-%1d ",i,j);
9273: fprintf(ficresprobcor," p%1d-%1d ",i,j);
9274: }
9275: /* fprintf(ficresprob,"\n");
9276: fprintf(ficresprobcov,"\n");
9277: fprintf(ficresprobcor,"\n");
9278: */
9279: xp=vector(1,npar);
9280: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
9281: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
9282: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
9283: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
9284: first=1;
9285: fprintf(ficgp,"\n# Routine varprob");
9286: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
9287: fprintf(fichtm,"\n");
9288:
1.288 brouard 9289: 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 9290: 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);
9291: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 9292: and drawn. It helps understanding how is the covariance between two incidences.\
9293: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 9294: 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 9295: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
9296: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
9297: standard deviations wide on each axis. <br>\
9298: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
9299: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
9300: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
9301:
1.222 brouard 9302: cov[1]=1;
9303: /* tj=cptcoveff; */
1.225 brouard 9304: tj = (int) pow(2,cptcoveff);
1.222 brouard 9305: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
9306: j1=0;
1.332 brouard 9307:
9308: for(nres=1;nres <=nresult; nres++){ /* For each resultline */
9309: for(j1=1; j1<=tj;j1++){ /* For any combination of dummy covariates, fixed and varying */
1.342 brouard 9310: /* 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 9311: if(tj != 1 && TKresult[nres]!= j1)
9312: continue;
9313:
9314: /* for(j1=1; j1<=tj;j1++){ /\* For each valid combination of covariates or only once*\/ */
9315: /* for(nres=1;nres <=1; nres++){ /\* For each resultline *\/ */
9316: /* /\* for(nres=1;nres <=nresult; nres++){ /\\* For each resultline *\\/ *\/ */
1.222 brouard 9317: if (cptcovn>0) {
1.334 brouard 9318: fprintf(ficresprob, "\n#********** Variable ");
9319: fprintf(ficresprobcov, "\n#********** Variable ");
9320: fprintf(ficgp, "\n#********** Variable ");
9321: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
9322: fprintf(ficresprobcor, "\n#********** Variable ");
9323:
9324: /* Including quantitative variables of the resultline to be done */
9325: for (z1=1; z1<=cptcovs; z1++){ /* Loop on each variable of this resultline */
1.343 brouard 9326: /* printf("Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model); */
1.338 brouard 9327: fprintf(ficlog,"Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model);
9328: /* 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 9329: if(Dummy[modelresult[nres][z1]]==0){/* Dummy variable of the variable in position modelresult in the model corresponding to z1 in resultline */
9330: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed referenced to model equation */
9331: 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 */
9332: 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 */
9333: 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 */
9334: 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 */
9335: 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 */
9336: fprintf(ficresprob,"fixed ");
9337: fprintf(ficresprobcov,"fixed ");
9338: fprintf(ficgp,"fixed ");
9339: fprintf(fichtmcov,"fixed ");
9340: fprintf(ficresprobcor,"fixed ");
9341: }else{
9342: fprintf(ficresprob,"varyi ");
9343: fprintf(ficresprobcov,"varyi ");
9344: fprintf(ficgp,"varyi ");
9345: fprintf(fichtmcov,"varyi ");
9346: fprintf(ficresprobcor,"varyi ");
9347: }
9348: }else if(Dummy[modelresult[nres][z1]]==1){ /* Quanti variable */
9349: /* For each selected (single) quantitative value */
1.337 brouard 9350: fprintf(ficresprob," V%d=%lg ",Tvqresult[nres][z1],Tqresult[nres][z1]);
1.334 brouard 9351: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed */
9352: fprintf(ficresprob,"fixed ");
9353: fprintf(ficresprobcov,"fixed ");
9354: fprintf(ficgp,"fixed ");
9355: fprintf(fichtmcov,"fixed ");
9356: fprintf(ficresprobcor,"fixed ");
9357: }else{
9358: fprintf(ficresprob,"varyi ");
9359: fprintf(ficresprobcov,"varyi ");
9360: fprintf(ficgp,"varyi ");
9361: fprintf(fichtmcov,"varyi ");
9362: fprintf(ficresprobcor,"varyi ");
9363: }
9364: }else{
9365: 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 */
9366: 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 */
9367: exit(1);
9368: }
9369: } /* End loop on variable of this resultline */
9370: /* for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]); */
1.222 brouard 9371: fprintf(ficresprob, "**********\n#\n");
9372: fprintf(ficresprobcov, "**********\n#\n");
9373: fprintf(ficgp, "**********\n#\n");
9374: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
9375: fprintf(ficresprobcor, "**********\n#");
9376: if(invalidvarcomb[j1]){
9377: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
9378: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
9379: continue;
9380: }
9381: }
9382: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
9383: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
9384: gp=vector(1,(nlstate)*(nlstate+ndeath));
9385: gm=vector(1,(nlstate)*(nlstate+ndeath));
1.334 brouard 9386: for (age=bage; age<=fage; age ++){ /* Fo each age we feed the model equation with covariates, using precov as in hpxij() ? */
1.222 brouard 9387: cov[2]=age;
9388: if(nagesqr==1)
9389: cov[3]= age*age;
1.334 brouard 9390: /* New code end of combination but for each resultline */
9391: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 9392: if(Typevar[k1]==1 || Typevar[k1] ==3){ /* A product with age */
1.334 brouard 9393: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.326 brouard 9394: }else{
1.334 brouard 9395: cov[2+nagesqr+k1]=precov[nres][k1];
1.326 brouard 9396: }
1.334 brouard 9397: }/* End of loop on model equation */
9398: /* Old code */
9399: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
9400: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)]; *\/ */
9401: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
9402: /* /\* Here comes the value of the covariate 'j1' after renumbering k with single dummy covariates *\/ */
9403: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(j1,TnsdVar[TvarsD[k]])]; */
9404: /* /\*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*\//\* j1 1 2 3 4 */
9405: /* * 1 1 1 1 1 */
9406: /* * 2 2 1 1 1 */
9407: /* * 3 1 2 1 1 */
9408: /* *\/ */
9409: /* /\* nbcode[1][1]=0 nbcode[1][2]=1;*\/ */
9410: /* } */
9411: /* /\* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
9412: /* /\* ) p nbcode[Tvar[Tage[k]]][(1 & (ij-1) >> (k-1))+1] *\/ */
9413: /* /\*for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; *\/ */
9414: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
9415: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
9416: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(j1,TnsdVar[Tvar[Tage[k]]])]*cov[2]; */
9417: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
9418: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
9419: /* 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]); */
9420: /* /\* cov[2+nagesqr+Tage[k]]=meanq[k]/idq[k]*cov[2];/\\* Using the mean of quantitative variable Tvar[Tage[k]] /\\* Tqresult[nres][k]; *\\/ *\/ */
9421: /* /\* exit(1); *\/ */
9422: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
9423: /* } */
9424: /* /\* cov[2+Tage[k]+nagesqr]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
9425: /* } */
9426: /* for (k=1; k<=cptcovprod;k++){/\* For product without age *\/ */
9427: /* if(Dummy[Tvard[k][1]]==0){ */
9428: /* if(Dummy[Tvard[k][2]]==0){ */
9429: /* 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]])]; */
9430: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
9431: /* }else{ /\* Should we use the mean of the quantitative variables? *\/ */
9432: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(j1,TnsdVar[Tvard[k][1]])] * Tqresult[nres][resultmodel[nres][k]]; */
9433: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
9434: /* } */
9435: /* }else{ */
9436: /* if(Dummy[Tvard[k][2]]==0){ */
9437: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(j1,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][TnsdVar[Tvard[k][1]]]; */
9438: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
9439: /* }else{ */
9440: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][TnsdVar[Tvard[k][1]]]* Tqinvresult[nres][TnsdVar[Tvard[k][2]]]; */
9441: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
9442: /* } */
9443: /* } */
9444: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
9445: /* } */
1.326 brouard 9446: /* For each age and combination of dummy covariates we slightly move the parameters of delti in order to get the gradient*/
1.222 brouard 9447: for(theta=1; theta <=npar; theta++){
9448: for(i=1; i<=npar; i++)
9449: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 9450:
1.222 brouard 9451: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 9452:
1.222 brouard 9453: k=0;
9454: for(i=1; i<= (nlstate); i++){
9455: for(j=1; j<=(nlstate+ndeath);j++){
9456: k=k+1;
9457: gp[k]=pmmij[i][j];
9458: }
9459: }
1.220 brouard 9460:
1.222 brouard 9461: for(i=1; i<=npar; i++)
9462: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 9463:
1.222 brouard 9464: pmij(pmmij,cov,ncovmodel,xp,nlstate);
9465: k=0;
9466: for(i=1; i<=(nlstate); i++){
9467: for(j=1; j<=(nlstate+ndeath);j++){
9468: k=k+1;
9469: gm[k]=pmmij[i][j];
9470: }
9471: }
1.220 brouard 9472:
1.222 brouard 9473: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
9474: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
9475: }
1.126 brouard 9476:
1.222 brouard 9477: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
9478: for(theta=1; theta <=npar; theta++)
9479: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 9480:
1.222 brouard 9481: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
9482: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 9483:
1.222 brouard 9484: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 9485:
1.222 brouard 9486: k=0;
9487: for(i=1; i<=(nlstate); i++){
9488: for(j=1; j<=(nlstate+ndeath);j++){
9489: k=k+1;
9490: mu[k][(int) age]=pmmij[i][j];
9491: }
9492: }
9493: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
9494: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
9495: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 9496:
1.222 brouard 9497: /*printf("\n%d ",(int)age);
9498: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
9499: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
9500: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
9501: }*/
1.220 brouard 9502:
1.222 brouard 9503: fprintf(ficresprob,"\n%d ",(int)age);
9504: fprintf(ficresprobcov,"\n%d ",(int)age);
9505: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 9506:
1.222 brouard 9507: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
9508: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
9509: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
9510: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
9511: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
9512: }
9513: i=0;
9514: for (k=1; k<=(nlstate);k++){
9515: for (l=1; l<=(nlstate+ndeath);l++){
9516: i++;
9517: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
9518: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
9519: for (j=1; j<=i;j++){
9520: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
9521: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
9522: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
9523: }
9524: }
9525: }/* end of loop for state */
9526: } /* end of loop for age */
9527: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
9528: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
9529: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
9530: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
9531:
9532: /* Confidence intervalle of pij */
9533: /*
9534: fprintf(ficgp,"\nunset parametric;unset label");
9535: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
9536: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
9537: 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);
9538: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
9539: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
9540: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
9541: */
9542:
9543: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
9544: first1=1;first2=2;
9545: for (k2=1; k2<=(nlstate);k2++){
9546: for (l2=1; l2<=(nlstate+ndeath);l2++){
9547: if(l2==k2) continue;
9548: j=(k2-1)*(nlstate+ndeath)+l2;
9549: for (k1=1; k1<=(nlstate);k1++){
9550: for (l1=1; l1<=(nlstate+ndeath);l1++){
9551: if(l1==k1) continue;
9552: i=(k1-1)*(nlstate+ndeath)+l1;
9553: if(i<=j) continue;
9554: for (age=bage; age<=fage; age ++){
9555: if ((int)age %5==0){
9556: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
9557: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
9558: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
9559: mu1=mu[i][(int) age]/stepm*YEARM ;
9560: mu2=mu[j][(int) age]/stepm*YEARM;
9561: c12=cv12/sqrt(v1*v2);
9562: /* Computing eigen value of matrix of covariance */
9563: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
9564: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
9565: if ((lc2 <0) || (lc1 <0) ){
9566: if(first2==1){
9567: first1=0;
9568: 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);
9569: }
9570: 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);
9571: /* lc1=fabs(lc1); */ /* If we want to have them positive */
9572: /* lc2=fabs(lc2); */
9573: }
1.220 brouard 9574:
1.222 brouard 9575: /* Eigen vectors */
1.280 brouard 9576: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
9577: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
9578: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
9579: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
9580: }else
9581: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 9582: /*v21=sqrt(1.-v11*v11); *//* error */
9583: v21=(lc1-v1)/cv12*v11;
9584: v12=-v21;
9585: v22=v11;
9586: tnalp=v21/v11;
9587: if(first1==1){
9588: first1=0;
9589: 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);
9590: }
9591: 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);
9592: /*printf(fignu*/
9593: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
9594: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
9595: if(first==1){
9596: first=0;
9597: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
9598: fprintf(ficgp,"\nset parametric;unset label");
9599: 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);
9600: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 9601: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 9602: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 9603: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 9604: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
9605: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
9606: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
9607: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
9608: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
9609: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
9610: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
9611: 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 9612: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
9613: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 9614: }else{
9615: first=0;
9616: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
9617: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
9618: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
9619: 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 9620: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
9621: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 9622: }/* if first */
9623: } /* age mod 5 */
9624: } /* end loop age */
9625: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
9626: first=1;
9627: } /*l12 */
9628: } /* k12 */
9629: } /*l1 */
9630: }/* k1 */
1.332 brouard 9631: } /* loop on combination of covariates j1 */
1.326 brouard 9632: } /* loop on nres */
1.222 brouard 9633: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
9634: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
9635: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
9636: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
9637: free_vector(xp,1,npar);
9638: fclose(ficresprob);
9639: fclose(ficresprobcov);
9640: fclose(ficresprobcor);
9641: fflush(ficgp);
9642: fflush(fichtmcov);
9643: }
1.126 brouard 9644:
9645:
9646: /******************* Printing html file ***********/
1.201 brouard 9647: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 9648: int lastpass, int stepm, int weightopt, char model[],\
9649: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.296 brouard 9650: int popforecast, int mobilav, int prevfcast, int mobilavproj, int prevbcast, int estepm , \
9651: double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \
9652: double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){
1.359 brouard 9653: int jj1, k1, cpt, nres;
1.319 brouard 9654: /* In fact some results are already printed in fichtm which is open */
1.126 brouard 9655: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
9656: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
9657: </ul>");
1.319 brouard 9658: /* fprintf(fichtm,"<ul><li> model=1+age+%s\n \ */
9659: /* </ul>", model); */
1.214 brouard 9660: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
9661: 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",
9662: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
1.332 brouard 9663: 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 9664: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
9665: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 9666: fprintf(fichtm,"\
9667: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 9668: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 9669: fprintf(fichtm,"\
1.217 brouard 9670: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
9671: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
9672: fprintf(fichtm,"\
1.288 brouard 9673: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 9674: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 9675: fprintf(fichtm,"\
1.288 brouard 9676: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 9677: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
9678: fprintf(fichtm,"\
1.211 brouard 9679: - (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 9680: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 9681: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 9682: if(prevfcast==1){
9683: fprintf(fichtm,"\
9684: - Prevalence projections by age and states: \
1.201 brouard 9685: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 9686: }
1.126 brouard 9687:
9688:
1.225 brouard 9689: m=pow(2,cptcoveff);
1.222 brouard 9690: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 9691:
1.317 brouard 9692: fprintf(fichtm," \n<ul><li><b>Graphs (first order)</b></li><p>");
1.264 brouard 9693:
9694: jj1=0;
9695:
9696: fprintf(fichtm," \n<ul>");
1.337 brouard 9697: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
9698: /* k1=nres; */
1.338 brouard 9699: k1=TKresult[nres];
9700: if(TKresult[nres]==0)k1=1; /* To be checked for no result */
1.337 brouard 9701: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
9702: /* if(m != 1 && TKresult[nres]!= k1) */
9703: /* continue; */
1.264 brouard 9704: jj1++;
9705: if (cptcovn > 0) {
9706: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
1.337 brouard 9707: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
9708: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 9709: }
1.337 brouard 9710: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
9711: /* fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
9712: /* } */
9713: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9714: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
9715: /* } */
1.264 brouard 9716: fprintf(fichtm,"\">");
9717:
9718: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
9719: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 9720: for (cpt=1; cpt<=cptcovs;cpt++){
9721: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 9722: }
1.337 brouard 9723: /* fprintf(fichtm,"************ Results for covariates"); */
9724: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
9725: /* fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
9726: /* } */
9727: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9728: /* fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
9729: /* } */
1.264 brouard 9730: if(invalidvarcomb[k1]){
9731: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
9732: continue;
9733: }
9734: fprintf(fichtm,"</a></li>");
9735: } /* cptcovn >0 */
9736: }
1.317 brouard 9737: fprintf(fichtm," \n</ul>");
1.264 brouard 9738:
1.222 brouard 9739: jj1=0;
1.237 brouard 9740:
1.337 brouard 9741: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
9742: /* k1=nres; */
1.338 brouard 9743: k1=TKresult[nres];
9744: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9745: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
9746: /* if(m != 1 && TKresult[nres]!= k1) */
9747: /* continue; */
1.220 brouard 9748:
1.222 brouard 9749: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
9750: jj1++;
9751: if (cptcovn > 0) {
1.264 brouard 9752: fprintf(fichtm,"\n<p><a name=\"rescov");
1.337 brouard 9753: for (cpt=1; cpt<=cptcovs;cpt++){
9754: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 9755: }
1.337 brouard 9756: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9757: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
9758: /* } */
1.264 brouard 9759: fprintf(fichtm,"\"</a>");
9760:
1.222 brouard 9761: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 9762: for (cpt=1; cpt<=cptcovs;cpt++){
9763: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
9764: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 9765: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
9766: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 9767: }
1.230 brouard 9768: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.338 brouard 9769: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.222 brouard 9770: if(invalidvarcomb[k1]){
9771: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
9772: printf("\nCombination (%d) ignored because no cases \n",k1);
9773: continue;
9774: }
9775: }
9776: /* aij, bij */
1.259 brouard 9777: 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 9778: <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 9779: /* Pij */
1.241 brouard 9780: 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> \
9781: <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 9782: /* Quasi-incidences */
9783: 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 9784: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 9785: 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 9786: 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> \
9787: <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 9788: /* Survival functions (period) in state j */
9789: for(cpt=1; cpt<=nlstate;cpt++){
1.359 brouard 9790: 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 9791: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
9792: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.222 brouard 9793: }
9794: /* State specific survival functions (period) */
9795: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 9796: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
1.359 brouard 9797: 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 9798: <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);
9799: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
9800: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.222 brouard 9801: }
1.288 brouard 9802: /* Period (forward stable) prevalence in each health state */
1.222 brouard 9803: for(cpt=1; cpt<=nlstate;cpt++){
1.359 brouard 9804: 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 9805: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
1.329 brouard 9806: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.222 brouard 9807: }
1.296 brouard 9808: if(prevbcast==1){
1.288 brouard 9809: /* Backward prevalence in each health state */
1.222 brouard 9810: for(cpt=1; cpt<=nlstate;cpt++){
1.338 brouard 9811: 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);
9812: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJB_"),subdirf2(optionfilefiname,"PIJB_"));
9813: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.222 brouard 9814: }
1.217 brouard 9815: }
1.222 brouard 9816: if(prevfcast==1){
1.288 brouard 9817: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 9818: for(cpt=1; cpt<=nlstate;cpt++){
1.314 brouard 9819: 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);
9820: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"F_"),subdirf2(optionfilefiname,"F_"));
9821: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",
9822: subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 9823: }
9824: }
1.296 brouard 9825: if(prevbcast==1){
1.268 brouard 9826: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
9827: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 9828: 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 9829: 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 \
9830: 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 9831: 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);
9832: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"FB_"),subdirf2(optionfilefiname,"FB_"));
9833: fprintf(fichtm," <img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
1.268 brouard 9834: }
9835: }
1.220 brouard 9836:
1.222 brouard 9837: for(cpt=1; cpt<=nlstate;cpt++) {
1.314 brouard 9838: 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);
9839: fprintf(fichtm," (data from text file <a href=\"%s.txt\"> %s.txt</a>)\n<br>",subdirf2(optionfilefiname,"E_"),subdirf2(optionfilefiname,"E_"));
9840: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres );
1.222 brouard 9841: }
9842: /* } /\* end i1 *\/ */
1.337 brouard 9843: }/* End k1=nres */
1.222 brouard 9844: fprintf(fichtm,"</ul>");
1.126 brouard 9845:
1.222 brouard 9846: fprintf(fichtm,"\
1.126 brouard 9847: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 9848: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 9849: - 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 9850: But because parameters are usually highly correlated (a higher incidence of disability \
9851: and a higher incidence of recovery can give very close observed transition) it might \
9852: be very useful to look not only at linear confidence intervals estimated from the \
9853: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
9854: (parameters) of the logistic regression, it might be more meaningful to visualize the \
9855: covariance matrix of the one-step probabilities. \
9856: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 9857:
1.222 brouard 9858: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
9859: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
9860: fprintf(fichtm,"\
1.126 brouard 9861: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 9862: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 9863:
1.222 brouard 9864: fprintf(fichtm,"\
1.126 brouard 9865: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 9866: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
9867: fprintf(fichtm,"\
1.126 brouard 9868: - 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): \
9869: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 9870: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 9871: fprintf(fichtm,"\
1.126 brouard 9872: - (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): \
9873: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 9874: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 9875: fprintf(fichtm,"\
1.288 brouard 9876: - 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 9877: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
9878: fprintf(fichtm,"\
1.128 brouard 9879: - 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 9880: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
9881: fprintf(fichtm,"\
1.288 brouard 9882: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 9883: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 9884:
9885: /* if(popforecast==1) fprintf(fichtm,"\n */
9886: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
9887: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
9888: /* <br>",fileres,fileres,fileres,fileres); */
9889: /* else */
1.338 brouard 9890: /* 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 9891: fflush(fichtm);
1.126 brouard 9892:
1.225 brouard 9893: m=pow(2,cptcoveff);
1.222 brouard 9894: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 9895:
1.317 brouard 9896: fprintf(fichtm," <ul><li><b>Graphs (second order)</b></li><p>");
9897:
9898: jj1=0;
9899:
9900: fprintf(fichtm," \n<ul>");
1.337 brouard 9901: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
9902: /* k1=nres; */
1.338 brouard 9903: k1=TKresult[nres];
1.337 brouard 9904: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
9905: /* if(m != 1 && TKresult[nres]!= k1) */
9906: /* continue; */
1.317 brouard 9907: jj1++;
9908: if (cptcovn > 0) {
9909: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescovsecond");
1.337 brouard 9910: for (cpt=1; cpt<=cptcovs;cpt++){
9911: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 9912: }
9913: fprintf(fichtm,"\">");
9914:
9915: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
9916: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 9917: for (cpt=1; cpt<=cptcovs;cpt++){
9918: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 9919: }
9920: if(invalidvarcomb[k1]){
9921: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
9922: continue;
9923: }
9924: fprintf(fichtm,"</a></li>");
9925: } /* cptcovn >0 */
1.337 brouard 9926: } /* End nres */
1.317 brouard 9927: fprintf(fichtm," \n</ul>");
9928:
1.222 brouard 9929: jj1=0;
1.237 brouard 9930:
1.241 brouard 9931: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9932: /* k1=nres; */
1.338 brouard 9933: k1=TKresult[nres];
9934: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9935: /* for(k1=1; k1<=m;k1++){ */
9936: /* if(m != 1 && TKresult[nres]!= k1) */
9937: /* continue; */
1.222 brouard 9938: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
9939: jj1++;
1.126 brouard 9940: if (cptcovn > 0) {
1.317 brouard 9941: fprintf(fichtm,"\n<p><a name=\"rescovsecond");
1.337 brouard 9942: for (cpt=1; cpt<=cptcovs;cpt++){
9943: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 9944: }
9945: fprintf(fichtm,"\"</a>");
9946:
1.126 brouard 9947: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 9948: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcoveff number of variables */
9949: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
9950: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 9951: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
1.317 brouard 9952: }
1.237 brouard 9953:
1.338 brouard 9954: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.220 brouard 9955:
1.222 brouard 9956: if(invalidvarcomb[k1]){
9957: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
9958: continue;
9959: }
1.337 brouard 9960: } /* If cptcovn >0 */
1.126 brouard 9961: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 9962: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.314 brouard 9963: 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);
9964: fprintf(fichtm," (data from text file <a href=\"%s\">%s</a>)\n <br>",subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
9965: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"V_"), cpt,k1,nres);
1.126 brouard 9966: }
9967: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.360 brouard 9968: health expectancies in each live state (1 to %d) with confidence intervals \
9969: on left y-scale as well as proportions of time spent in each live state \
9970: (with confidence intervals) on right y-scale 0 to 100%%.\
9971: If popbased=1 the smooth (due to the model) \
1.128 brouard 9972: true period expectancies (those weighted with period prevalences are also\
9973: drawn in addition to the population based expectancies computed using\
1.314 brouard 9974: 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);
9975: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>) \n<br>",subdirf2(optionfilefiname,"T_"),subdirf2(optionfilefiname,"T_"));
9976: fprintf(fichtm,"<img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 9977: /* } /\* end i1 *\/ */
1.241 brouard 9978: }/* End nres */
1.222 brouard 9979: fprintf(fichtm,"</ul>");
9980: fflush(fichtm);
1.126 brouard 9981: }
9982:
9983: /******************* Gnuplot file **************/
1.296 brouard 9984: 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 9985:
1.354 brouard 9986: char dirfileres[256],optfileres[256];
9987: char gplotcondition[256], gplotlabel[256];
1.343 brouard 9988: 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 9989: int lv=0, vlv=0, kl=0;
1.130 brouard 9990: int ng=0;
1.201 brouard 9991: int vpopbased;
1.223 brouard 9992: int ioffset; /* variable offset for columns */
1.270 brouard 9993: int iyearc=1; /* variable column for year of projection */
9994: int iagec=1; /* variable column for age of projection */
1.235 brouard 9995: int nres=0; /* Index of resultline */
1.266 brouard 9996: int istart=1; /* For starting graphs in projections */
1.219 brouard 9997:
1.126 brouard 9998: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
9999: /* printf("Problem with file %s",optionfilegnuplot); */
10000: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
10001: /* } */
10002:
10003: /*#ifdef windows */
10004: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 10005: /*#endif */
1.225 brouard 10006: m=pow(2,cptcoveff);
1.126 brouard 10007:
1.274 brouard 10008: /* diagram of the model */
10009: fprintf(ficgp,"\n#Diagram of the model \n");
10010: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
10011: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
10012: 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);
10013:
1.343 brouard 10014: 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 10015: fprintf(ficgp,"\n#show arrow\nunset label\n");
10016: 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);
10017: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
10018: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
10019: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
10020: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
10021:
1.202 brouard 10022: /* Contribution to likelihood */
10023: /* Plot the probability implied in the likelihood */
1.223 brouard 10024: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
10025: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
10026: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
10027: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 10028: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 10029: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
10030: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 10031: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
10032: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
10033: 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));
10034: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
10035: 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));
10036: for (i=1; i<= nlstate ; i ++) {
10037: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
10038: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
10039: 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);
10040: for (j=2; j<= nlstate+ndeath ; j ++) {
10041: 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);
10042: }
10043: fprintf(ficgp,";\nset out; unset ylabel;\n");
10044: }
10045: /* 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 */
10046: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
10047: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
10048: fprintf(ficgp,"\nset out;unset log\n");
10049: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 10050:
1.343 brouard 10051: /* Plot the probability implied in the likelihood by covariate value */
10052: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
10053: /* if(debugILK==1){ */
10054: for(kf=1; kf <= ncovf; kf++){ /* For each simple dummy covariate of the model */
1.347 brouard 10055: kvar=Tvar[TvarFind[kf]]; /* variable name */
10056: /* k=18+Tvar[TvarFind[kf]];/\*offset because there are 18 columns in the ILK_ file but could be placed else where *\/ */
1.350 brouard 10057: /* k=18+kf;/\*offset because there are 18 columns in the ILK_ file *\/ */
1.356 brouard 10058: /* k=19+kf;/\*offset because there are 19 columns in the ILK_ file *\/ */
1.355 brouard 10059: 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 10060: for (i=1; i<= nlstate ; i ++) {
10061: fprintf(ficgp,"\nset out \"%s-p%dj-%d.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i,kvar);
10062: fprintf(ficgp,"unset log;\n# For each simple dummy covariate of the model \n plot \"%s\"",subdirf(fileresilk));
1.348 brouard 10063: if(gnuplotversion >=5.2){ /* Former gnuplot versions do not have variable pointsize!! */
10064: 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);
10065: for (j=2; j<= nlstate+ndeath ; j ++) {
10066: 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);
10067: }
10068: }else{
10069: 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);
10070: for (j=2; j<= nlstate+ndeath ; j ++) {
10071: 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);
10072: }
1.343 brouard 10073: }
10074: fprintf(ficgp,";\nset out; unset ylabel;\n");
10075: }
10076: } /* End of each covariate dummy */
10077: for(ncovv=1, iposold=0, kk=0; ncovv <= ncovvt ; ncovv++){
10078: /* Other example V1 + V3 + V5 + age*V1 + age*V3 + age*V5 + V1*V3 + V3*V5 + V1*V5
10079: * kmodel = 1 2 3 4 5 6 7 8 9
10080: * varying 1 2 3 4 5
10081: * ncovv 1 2 3 4 5 6 7 8
10082: * TvarVV[ncovv] V3 5 1 3 3 5 1 5
10083: * TvarVVind[ncovv]=kmodel 2 3 7 7 8 8 9 9
10084: * TvarFind[kmodel] 1 0 0 0 0 0 0 0 0
10085: * kdata ncovcol=[V1 V2] nqv=0 ntv=[V3 V4] nqtv=V5
10086: * Dummy[kmodel] 0 0 1 2 2 3 1 1 1
10087: */
10088: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
10089: kvar=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
10090: /* 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]); */
10091: if(ipos!=iposold){ /* Not a product or first of a product */
10092: /* printf(" %d",ipos); */
10093: /* fprintf(ficresilk," V%d",TvarVV[ncovv]); */
10094: /* printf(" DebugILK ficgp suite ipos=%d != iposold=%d\n", ipos, iposold); */
10095: kk++; /* Position of the ncovv column in ILK_ */
10096: k=18+ncovf+kk; /*offset because there are 18 columns in the ILK_ file plus ncovf fixed covariate */
10097: 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) */
10098: for (i=1; i<= nlstate ; i ++) {
10099: fprintf(ficgp,"\nset out \"%s-p%dj-%d.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i,kvar);
10100: fprintf(ficgp,"unset log;\n# For each simple dummy covariate of the model \n plot \"%s\"",subdirf(fileresilk));
10101:
1.348 brouard 10102: /* printf("Before DebugILK gnuplotversion=%g >=5.2\n",gnuplotversion); */
1.343 brouard 10103: if(gnuplotversion >=5.2){ /* Former gnuplot versions do not have variable pointsize!! */
10104: /* printf("DebugILK gnuplotversion=%g >=5.2\n",gnuplotversion); */
10105: 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);
10106: for (j=2; j<= nlstate+ndeath ; j ++) {
10107: 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);
10108: }
10109: }else{
10110: /* printf("DebugILK gnuplotversion=%g <5.2\n",gnuplotversion); */
10111: 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);
10112: for (j=2; j<= nlstate+ndeath ; j ++) {
10113: 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);
10114: }
10115: }
10116: fprintf(ficgp,";\nset out; unset ylabel;\n");
10117: }
10118: }/* End if dummy varying */
10119: }else{ /*Product */
10120: /* printf("*"); */
10121: /* fprintf(ficresilk,"*"); */
10122: }
10123: iposold=ipos;
10124: } /* For each time varying covariate */
10125: /* } /\* debugILK==1 *\/ */
10126: /* 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 */
10127: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
10128: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
10129: fprintf(ficgp,"\nset out;unset log\n");
10130: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
10131:
10132:
10133:
1.126 brouard 10134: strcpy(dirfileres,optionfilefiname);
10135: strcpy(optfileres,"vpl");
1.223 brouard 10136: /* 1eme*/
1.238 brouard 10137: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
1.337 brouard 10138: /* for (k1=1; k1<= m ; k1 ++){ /\* For each valid combination of covariate *\/ */
1.236 brouard 10139: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10140: k1=TKresult[nres];
1.338 brouard 10141: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.238 brouard 10142: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.337 brouard 10143: /* if(m != 1 && TKresult[nres]!= k1) */
10144: /* continue; */
1.238 brouard 10145: /* We are interested in selected combination by the resultline */
1.246 brouard 10146: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 10147: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 10148: strcpy(gplotlabel,"(");
1.337 brouard 10149: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10150: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10151: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10152:
10153: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate k get corresponding value lv for combination k1 *\/ */
10154: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the value of the covariate corresponding to k1 combination *\\/ *\/ */
10155: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
10156: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10157: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10158: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10159: /* vlv= nbcode[Tvaraff[k]][lv]; /\* vlv is the value of the covariate lv, 0 or 1 *\/ */
10160: /* /\* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv *\/ */
10161: /* /\* printf(" V%d=%d ",Tvaraff[k],vlv); *\/ */
10162: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10163: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10164: /* } */
10165: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10166: /* /\* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); *\/ */
10167: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
10168: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.264 brouard 10169: }
10170: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 10171: /* printf("\n#\n"); */
1.238 brouard 10172: fprintf(ficgp,"\n#\n");
10173: if(invalidvarcomb[k1]){
1.260 brouard 10174: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 10175: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10176: continue;
10177: }
1.235 brouard 10178:
1.241 brouard 10179: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
10180: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 10181: /* 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 10182: fprintf(ficgp,"set title \"Alive state %d %s model=1+age+%s\" font \"Helvetica,12\"\n",cpt,gplotlabel,model);
1.260 brouard 10183: 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);
10184: /* 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); */
10185: /* k1-1 error should be nres-1*/
1.238 brouard 10186: for (i=1; i<= nlstate ; i ++) {
10187: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
10188: else fprintf(ficgp," %%*lf (%%*lf)");
10189: }
1.288 brouard 10190: 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 10191: for (i=1; i<= nlstate ; i ++) {
10192: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
10193: else fprintf(ficgp," %%*lf (%%*lf)");
10194: }
1.260 brouard 10195: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 10196: for (i=1; i<= nlstate ; i ++) {
10197: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
10198: else fprintf(ficgp," %%*lf (%%*lf)");
10199: }
1.265 brouard 10200: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
10201:
10202: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
10203: if(cptcoveff ==0){
1.271 brouard 10204: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 10205: }else{
10206: kl=0;
10207: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 10208: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
10209: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.265 brouard 10210: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
10211: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
10212: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
10213: vlv= nbcode[Tvaraff[k]][lv];
10214: kl++;
10215: /* 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 *\/ */
10216: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
10217: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
10218: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
10219: if(k==cptcoveff){
10220: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
10221: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
10222: }else{
10223: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
10224: kl++;
10225: }
10226: } /* end covariate */
10227: } /* end if no covariate */
10228:
1.296 brouard 10229: if(prevbcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
1.238 brouard 10230: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 10231: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 10232: if(cptcoveff ==0){
1.245 brouard 10233: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 10234: }else{
10235: kl=0;
10236: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 10237: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
10238: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.238 brouard 10239: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
10240: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
10241: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 10242: /* vlv= nbcode[Tvaraff[k]][lv]; */
10243: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.223 brouard 10244: kl++;
1.238 brouard 10245: /* 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 *\/ */
10246: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
10247: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
10248: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
10249: if(k==cptcoveff){
1.245 brouard 10250: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 10251: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 10252: }else{
1.332 brouard 10253: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]);
1.238 brouard 10254: kl++;
10255: }
10256: } /* end covariate */
10257: } /* end if no covariate */
1.296 brouard 10258: if(prevbcast == 1){
1.268 brouard 10259: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
10260: /* k1-1 error should be nres-1*/
10261: for (i=1; i<= nlstate ; i ++) {
10262: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
10263: else fprintf(ficgp," %%*lf (%%*lf)");
10264: }
1.271 brouard 10265: 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 10266: for (i=1; i<= nlstate ; i ++) {
10267: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
10268: else fprintf(ficgp," %%*lf (%%*lf)");
10269: }
1.276 brouard 10270: 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 10271: for (i=1; i<= nlstate ; i ++) {
10272: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
10273: else fprintf(ficgp," %%*lf (%%*lf)");
10274: }
1.274 brouard 10275: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 10276: } /* end if backprojcast */
1.296 brouard 10277: } /* end if prevbcast */
1.276 brouard 10278: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
10279: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 10280: } /* nres */
1.337 brouard 10281: /* } /\* k1 *\/ */
1.201 brouard 10282: } /* cpt */
1.235 brouard 10283:
10284:
1.126 brouard 10285: /*2 eme*/
1.337 brouard 10286: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 10287: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10288: k1=TKresult[nres];
1.338 brouard 10289: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 10290: /* if(m != 1 && TKresult[nres]!= k1) */
10291: /* continue; */
1.238 brouard 10292: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 10293: strcpy(gplotlabel,"(");
1.337 brouard 10294: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10295: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10296: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10297: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
10298: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
10299: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
10300: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10301: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10302: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10303: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
10304: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10305: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10306: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10307: /* } */
10308: /* /\* for(k=1; k <= ncovds; k++){ *\/ */
10309: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10310: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
10311: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
10312: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 10313: }
1.264 brouard 10314: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 10315: fprintf(ficgp,"\n#\n");
1.223 brouard 10316: if(invalidvarcomb[k1]){
10317: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10318: continue;
10319: }
1.219 brouard 10320:
1.241 brouard 10321: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 10322: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 10323: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
10324: if(vpopbased==0){
1.360 brouard 10325: 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 10326: }else
1.238 brouard 10327: fprintf(ficgp,"\nreplot ");
1.360 brouard 10328: 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 10329: k=2*i;
1.360 brouard 10330: 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 */
10331: for (j=1; j<= nlstate+1 ; j ++) { /* e.. e.1 e.2 again j-1 is the state of end, wlim_i eij*/
10332: 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 */
10333: else fprintf(ficgp," %%*lf (%%*lf)"); /* skipping that field with a star */
1.238 brouard 10334: }
10335: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
1.360 brouard 10336: 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 10337: 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 10338: for (j=1; j<= nlstate+1 ; j ++) {
10339: if (j==i) fprintf(ficgp," %%lf (%%lf)");
10340: else fprintf(ficgp," %%*lf (%%*lf)");
10341: }
10342: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 10343: 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 10344: for (j=1; j<= nlstate+1 ; j ++) {
10345: if (j==i) fprintf(ficgp," %%lf (%%lf)");
10346: else fprintf(ficgp," %%*lf (%%*lf)");
10347: }
1.360 brouard 10348: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0,\\\n"); /* ,\\\n added for th percentage graphs */
1.238 brouard 10349: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
10350: } /* state */
1.360 brouard 10351: /* again for the percentag spent in state i-1=1 to i-1=nlstate */
10352: for (i=2; i<= nlstate+1 ; i ++) { /* For state i-1=0 is LE, while i-1=1 to nlstate are origin state */
10353: k=2*i;
10354: 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 */
10355: for (j=1; j<= nlstate ; j ++)
10356: fprintf(ficgp," %%*lf (%%*lf)"); /* Skipping TLE and LE to read %LE only */
10357: for (j=1; j<= nlstate+1 ; j ++) { /* e.. e.1 e.2 again j-1 is the state of end, wlim_i eij*/
10358: 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 */
10359: else fprintf(ficgp," %%*lf (%%*lf)"); /* skipping that field with a star */
10360: }
10361: if (i== 1) fprintf(ficgp,"\" t\"%%TLE\" w l lt %d axis x1y2, \\\n",i); /* Not used */
10362: 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 */
10363: 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);
10364: for (j=1; j<= nlstate ; j ++)
10365: fprintf(ficgp," %%*lf (%%*lf)"); /* Skipping TLE and LE to read %LE only */
10366: for (j=1; j<= nlstate+1 ; j ++) {
10367: if (j==i) fprintf(ficgp," %%lf (%%lf)");
10368: else fprintf(ficgp," %%*lf (%%*lf)");
10369: }
10370: fprintf(ficgp,"\" t\"\" w l lt 0 axis x1y2,");
10371: 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);
10372: for (j=1; j<= nlstate ; j ++)
10373: fprintf(ficgp," %%*lf (%%*lf)"); /* Skipping TLE and LE to read %LE only */
10374: for (j=1; j<= nlstate+1 ; j ++) {
10375: if (j==i) fprintf(ficgp," %%lf (%%lf)");
10376: else fprintf(ficgp," %%*lf (%%*lf)");
10377: }
10378: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0 axis x1y2");
10379: else fprintf(ficgp,"\" t\"\" w l lt 0 axis x1y2,\\\n");
10380: } /* state for percent */
1.238 brouard 10381: } /* vpopbased */
1.264 brouard 10382: 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 10383: } /* end nres */
1.337 brouard 10384: /* } /\* k1 end 2 eme*\/ */
1.238 brouard 10385:
10386:
10387: /*3eme*/
1.337 brouard 10388: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 10389: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10390: k1=TKresult[nres];
1.338 brouard 10391: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 10392: /* if(m != 1 && TKresult[nres]!= k1) */
10393: /* continue; */
1.238 brouard 10394:
1.332 brouard 10395: for (cpt=1; cpt<= nlstate ; cpt ++) { /* Fragile no verification of covariate values */
1.261 brouard 10396: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 10397: strcpy(gplotlabel,"(");
1.337 brouard 10398: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10399: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10400: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10401: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
10402: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
10403: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
10404: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10405: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10406: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10407: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
10408: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10409: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10410: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10411: /* } */
10412: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10413: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
10414: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
10415: }
1.264 brouard 10416: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 10417: fprintf(ficgp,"\n#\n");
10418: if(invalidvarcomb[k1]){
10419: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10420: continue;
10421: }
10422:
10423: /* k=2+nlstate*(2*cpt-2); */
10424: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 10425: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 10426: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 10427: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 10428: 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 10429: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
10430: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
10431: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
10432: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
10433: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
10434: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 10435:
1.238 brouard 10436: */
10437: for (i=1; i< nlstate ; i ++) {
1.261 brouard 10438: 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 10439: /* 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 10440:
1.238 brouard 10441: }
1.261 brouard 10442: 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 10443: }
1.264 brouard 10444: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 10445: } /* end nres */
1.337 brouard 10446: /* } /\* end kl 3eme *\/ */
1.126 brouard 10447:
1.223 brouard 10448: /* 4eme */
1.201 brouard 10449: /* Survival functions (period) from state i in state j by initial state i */
1.337 brouard 10450: /* for (k1=1; k1<=m; k1++){ /\* For each covariate and each value *\/ */
1.238 brouard 10451: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10452: k1=TKresult[nres];
1.338 brouard 10453: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 10454: /* if(m != 1 && TKresult[nres]!= k1) */
10455: /* continue; */
1.238 brouard 10456: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 10457: strcpy(gplotlabel,"(");
1.337 brouard 10458: fprintf(ficgp,"\n#\n#\n# Survival functions in state %d : 'LIJ_' files, cov=%d state=%d", cpt, k1, cpt);
10459: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10460: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10461: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10462: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
10463: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
10464: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
10465: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10466: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10467: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10468: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
10469: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10470: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10471: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10472: /* } */
10473: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10474: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
10475: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 10476: }
1.264 brouard 10477: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 10478: fprintf(ficgp,"\n#\n");
10479: if(invalidvarcomb[k1]){
10480: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10481: continue;
1.223 brouard 10482: }
1.238 brouard 10483:
1.241 brouard 10484: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 10485: 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 10486: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
10487: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
10488: k=3;
10489: for (i=1; i<= nlstate ; i ++){
10490: if(i==1){
10491: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
10492: }else{
10493: fprintf(ficgp,", '' ");
10494: }
10495: l=(nlstate+ndeath)*(i-1)+1;
10496: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
10497: for (j=2; j<= nlstate+ndeath ; j ++)
10498: fprintf(ficgp,"+$%d",k+l+j-1);
10499: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
10500: } /* nlstate */
1.264 brouard 10501: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 10502: } /* end cpt state*/
10503: } /* end nres */
1.337 brouard 10504: /* } /\* end covariate k1 *\/ */
1.238 brouard 10505:
1.220 brouard 10506: /* 5eme */
1.201 brouard 10507: /* Survival functions (period) from state i in state j by final state j */
1.337 brouard 10508: /* for (k1=1; k1<= m ; k1++){ /\* For each covariate combination if any *\/ */
1.238 brouard 10509: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10510: k1=TKresult[nres];
1.338 brouard 10511: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 10512: /* if(m != 1 && TKresult[nres]!= k1) */
10513: /* continue; */
1.238 brouard 10514: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 10515: strcpy(gplotlabel,"(");
1.238 brouard 10516: 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 10517: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10518: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10519: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10520: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
10521: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
10522: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
10523: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10524: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10525: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10526: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
10527: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10528: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10529: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10530: /* } */
10531: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10532: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
10533: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 10534: }
1.264 brouard 10535: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 10536: fprintf(ficgp,"\n#\n");
10537: if(invalidvarcomb[k1]){
10538: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10539: continue;
10540: }
1.227 brouard 10541:
1.241 brouard 10542: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 10543: 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 10544: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
10545: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
10546: k=3;
10547: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
10548: if(j==1)
10549: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
10550: else
10551: fprintf(ficgp,", '' ");
10552: l=(nlstate+ndeath)*(cpt-1) +j;
10553: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
10554: /* for (i=2; i<= nlstate+ndeath ; i ++) */
10555: /* fprintf(ficgp,"+$%d",k+l+i-1); */
10556: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
10557: } /* nlstate */
10558: fprintf(ficgp,", '' ");
10559: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
10560: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
10561: l=(nlstate+ndeath)*(cpt-1) +j;
10562: if(j < nlstate)
10563: fprintf(ficgp,"$%d +",k+l);
10564: else
10565: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
10566: }
1.264 brouard 10567: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 10568: } /* end cpt state*/
1.337 brouard 10569: /* } /\* end covariate *\/ */
1.238 brouard 10570: } /* end nres */
1.227 brouard 10571:
1.220 brouard 10572: /* 6eme */
1.202 brouard 10573: /* CV preval stable (period) for each covariate */
1.337 brouard 10574: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 10575: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10576: k1=TKresult[nres];
1.338 brouard 10577: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 10578: /* if(m != 1 && TKresult[nres]!= k1) */
10579: /* continue; */
1.255 brouard 10580: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 10581: strcpy(gplotlabel,"(");
1.288 brouard 10582: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 10583: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10584: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10585: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10586: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
10587: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
10588: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
10589: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10590: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10591: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10592: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
10593: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10594: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10595: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10596: /* } */
10597: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10598: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
10599: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 10600: }
1.264 brouard 10601: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 10602: fprintf(ficgp,"\n#\n");
1.223 brouard 10603: if(invalidvarcomb[k1]){
1.227 brouard 10604: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10605: continue;
1.223 brouard 10606: }
1.227 brouard 10607:
1.241 brouard 10608: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 10609: 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 10610: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 10611: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 10612: k=3; /* Offset */
1.255 brouard 10613: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 10614: if(i==1)
10615: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
10616: else
10617: fprintf(ficgp,", '' ");
1.255 brouard 10618: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 10619: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
10620: for (j=2; j<= nlstate ; j ++)
10621: fprintf(ficgp,"+$%d",k+l+j-1);
10622: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 10623: } /* nlstate */
1.264 brouard 10624: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 10625: } /* end cpt state*/
10626: } /* end covariate */
1.227 brouard 10627:
10628:
1.220 brouard 10629: /* 7eme */
1.296 brouard 10630: if(prevbcast == 1){
1.288 brouard 10631: /* CV backward prevalence for each covariate */
1.337 brouard 10632: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 10633: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10634: k1=TKresult[nres];
1.338 brouard 10635: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 10636: /* if(m != 1 && TKresult[nres]!= k1) */
10637: /* continue; */
1.268 brouard 10638: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 10639: strcpy(gplotlabel,"(");
1.288 brouard 10640: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 10641: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10642: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10643: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10644: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
10645: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
10646: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
10647: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10648: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10649: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10650: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
10651: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10652: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10653: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10654: /* } */
10655: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10656: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
10657: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 10658: }
1.264 brouard 10659: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 10660: fprintf(ficgp,"\n#\n");
10661: if(invalidvarcomb[k1]){
10662: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10663: continue;
10664: }
10665:
1.241 brouard 10666: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 10667: 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 10668: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 10669: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 10670: k=3; /* Offset */
1.268 brouard 10671: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 10672: if(i==1)
10673: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
10674: else
10675: fprintf(ficgp,", '' ");
10676: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 10677: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.324 brouard 10678: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
10679: /* 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 10680: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 10681: /* for (j=2; j<= nlstate ; j ++) */
10682: /* fprintf(ficgp,"+$%d",k+l+j-1); */
10683: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 10684: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 10685: } /* nlstate */
1.264 brouard 10686: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 10687: } /* end cpt state*/
10688: } /* end covariate */
1.296 brouard 10689: } /* End if prevbcast */
1.218 brouard 10690:
1.223 brouard 10691: /* 8eme */
1.218 brouard 10692: if(prevfcast==1){
1.288 brouard 10693: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 10694:
1.337 brouard 10695: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 10696: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10697: k1=TKresult[nres];
1.338 brouard 10698: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 10699: /* if(m != 1 && TKresult[nres]!= k1) */
10700: /* continue; */
1.211 brouard 10701: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 10702: strcpy(gplotlabel,"(");
1.288 brouard 10703: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 10704: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10705: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10706: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10707: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
10708: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
10709: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
10710: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10711: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10712: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10713: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
10714: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10715: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10716: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10717: /* } */
10718: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10719: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
10720: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 10721: }
1.264 brouard 10722: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 10723: fprintf(ficgp,"\n#\n");
10724: if(invalidvarcomb[k1]){
10725: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10726: continue;
10727: }
10728:
10729: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 10730: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 10731: 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 10732: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 10733: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 10734:
10735: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
10736: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
10737: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
10738: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 10739: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
10740: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
10741: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
10742: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 10743: if(i==istart){
1.227 brouard 10744: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
10745: }else{
10746: fprintf(ficgp,",\\\n '' ");
10747: }
10748: if(cptcoveff ==0){ /* No covariate */
10749: ioffset=2; /* Age is in 2 */
10750: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
10751: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
10752: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
10753: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
10754: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 10755: if(i==nlstate+1){
1.270 brouard 10756: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 10757: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
10758: fprintf(ficgp,",\\\n '' ");
10759: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 10760: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 10761: offyear, \
1.268 brouard 10762: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 10763: }else
1.227 brouard 10764: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
10765: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
10766: }else{ /* more than 2 covariates */
1.270 brouard 10767: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
10768: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
10769: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
10770: iyearc=ioffset-1;
10771: iagec=ioffset;
1.227 brouard 10772: fprintf(ficgp," u %d:(",ioffset);
10773: kl=0;
10774: strcpy(gplotcondition,"(");
1.351 brouard 10775: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate writing the chain of conditions *\/ */
1.332 brouard 10776: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
1.351 brouard 10777: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10778: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
10779: lv=Tvresult[nres][k];
10780: vlv=TinvDoQresult[nres][Tvresult[nres][k]];
1.227 brouard 10781: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
10782: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
10783: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 10784: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
1.351 brouard 10785: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
1.227 brouard 10786: kl++;
1.351 brouard 10787: /* sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); */
10788: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,lv, kl+1, vlv );
1.227 brouard 10789: kl++;
1.351 brouard 10790: if(k <cptcovs && cptcovs>1)
1.227 brouard 10791: sprintf(gplotcondition+strlen(gplotcondition)," && ");
10792: }
10793: strcpy(gplotcondition+strlen(gplotcondition),")");
10794: /* 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 *\/ */
10795: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
10796: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
10797: /* '' 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*/
10798: if(i==nlstate+1){
1.270 brouard 10799: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
10800: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 10801: fprintf(ficgp,",\\\n '' ");
1.270 brouard 10802: fprintf(ficgp," u %d:(",iagec);
10803: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
10804: iyearc, iagec, offyear, \
10805: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 10806: /* '' 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 10807: }else{
10808: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
10809: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
10810: }
10811: } /* end if covariate */
10812: } /* nlstate */
1.264 brouard 10813: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 10814: } /* end cpt state*/
10815: } /* end covariate */
10816: } /* End if prevfcast */
1.227 brouard 10817:
1.296 brouard 10818: if(prevbcast==1){
1.268 brouard 10819: /* Back projection from cross-sectional to stable (mixed) for each covariate */
10820:
1.337 brouard 10821: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.268 brouard 10822: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10823: k1=TKresult[nres];
1.338 brouard 10824: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 10825: /* if(m != 1 && TKresult[nres]!= k1) */
10826: /* continue; */
1.268 brouard 10827: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
10828: strcpy(gplotlabel,"(");
10829: 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 10830: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10831: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10832: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10833: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
10834: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
10835: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
10836: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10837: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10838: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10839: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
10840: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10841: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10842: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10843: /* } */
10844: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10845: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
10846: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.268 brouard 10847: }
10848: strcpy(gplotlabel+strlen(gplotlabel),")");
10849: fprintf(ficgp,"\n#\n");
10850: if(invalidvarcomb[k1]){
10851: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10852: continue;
10853: }
10854:
10855: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
10856: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
10857: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
10858: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
10859: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
10860:
10861: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
10862: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
10863: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
10864: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
10865: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
10866: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
10867: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
10868: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
10869: if(i==istart){
10870: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
10871: }else{
10872: fprintf(ficgp,",\\\n '' ");
10873: }
1.351 brouard 10874: /* if(cptcoveff ==0){ /\* No covariate *\/ */
10875: if(cptcovs ==0){ /* No covariate */
1.268 brouard 10876: ioffset=2; /* Age is in 2 */
10877: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
10878: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
10879: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
10880: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
10881: fprintf(ficgp," u %d:(", ioffset);
10882: if(i==nlstate+1){
1.270 brouard 10883: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 10884: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
10885: fprintf(ficgp,",\\\n '' ");
10886: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 10887: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 10888: offbyear, \
10889: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
10890: }else
10891: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
10892: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
10893: }else{ /* more than 2 covariates */
1.270 brouard 10894: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
10895: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
10896: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
10897: iyearc=ioffset-1;
10898: iagec=ioffset;
1.268 brouard 10899: fprintf(ficgp," u %d:(",ioffset);
10900: kl=0;
10901: strcpy(gplotcondition,"(");
1.337 brouard 10902: for (k=1; k<=cptcovs; k++){ /* For each covariate k of the resultline, get corresponding value lv for combination k1 */
1.338 brouard 10903: if(Dummy[modelresult[nres][k]]==0){ /* To be verified */
1.337 brouard 10904: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate writing the chain of conditions *\/ */
10905: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
10906: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
10907: lv=Tvresult[nres][k];
10908: vlv=TinvDoQresult[nres][Tvresult[nres][k]];
10909: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
10910: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
10911: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
10912: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
10913: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10914: kl++;
10915: /* sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); */
10916: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%lg " ,kl,Tvresult[nres][k], kl+1,TinvDoQresult[nres][Tvresult[nres][k]]);
10917: kl++;
1.338 brouard 10918: if(k <cptcovs && cptcovs>1)
1.337 brouard 10919: sprintf(gplotcondition+strlen(gplotcondition)," && ");
10920: }
1.268 brouard 10921: }
10922: strcpy(gplotcondition+strlen(gplotcondition),")");
10923: /* 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 *\/ */
10924: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
10925: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
10926: /* '' 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*/
10927: if(i==nlstate+1){
1.270 brouard 10928: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
10929: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 10930: fprintf(ficgp,",\\\n '' ");
1.270 brouard 10931: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 10932: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 10933: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
10934: iyearc,iagec,offbyear, \
10935: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 10936: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
10937: }else{
10938: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
10939: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
10940: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
10941: }
10942: } /* end if covariate */
10943: } /* nlstate */
10944: fprintf(ficgp,"\nset out; unset label;\n");
10945: } /* end cpt state*/
10946: } /* end covariate */
1.296 brouard 10947: } /* End if prevbcast */
1.268 brouard 10948:
1.227 brouard 10949:
1.238 brouard 10950: /* 9eme writing MLE parameters */
10951: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 10952: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 10953: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 10954: for(k=1; k <=(nlstate+ndeath); k++){
10955: if (k != i) {
1.227 brouard 10956: fprintf(ficgp,"# current state %d\n",k);
10957: for(j=1; j <=ncovmodel; j++){
10958: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
10959: jk++;
10960: }
10961: fprintf(ficgp,"\n");
1.126 brouard 10962: }
10963: }
1.223 brouard 10964: }
1.187 brouard 10965: fprintf(ficgp,"##############\n#\n");
1.227 brouard 10966:
1.145 brouard 10967: /*goto avoid;*/
1.238 brouard 10968: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
10969: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 10970: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
10971: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
10972: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
10973: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
10974: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
10975: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
10976: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
10977: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
10978: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
10979: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
10980: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
10981: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
10982: fprintf(ficgp,"#\n");
1.223 brouard 10983: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 10984: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.338 brouard 10985: fprintf(ficgp,"#model=1+age+%s \n",model);
1.238 brouard 10986: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.351 brouard 10987: /* fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/\* to be checked *\/ */
10988: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcovs,m);/* to be checked */
1.337 brouard 10989: /* for(k1=1; k1 <=m; k1++) /\* For each combination of covariate *\/ */
1.237 brouard 10990: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10991: /* k1=nres; */
1.338 brouard 10992: k1=TKresult[nres];
10993: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 10994: fprintf(ficgp,"\n\n# Resultline k1=%d ",k1);
1.264 brouard 10995: strcpy(gplotlabel,"(");
1.276 brouard 10996: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.337 brouard 10997: for (k=1; k<=cptcovs; k++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
10998: /* for each resultline nres, and position k, Tvresult[nres][k] gives the name of the variable and
10999: TinvDoQresult[nres][Tvresult[nres][k]] gives its value double or integer) */
11000: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
11001: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
11002: }
11003: /* if(m != 1 && TKresult[nres]!= k1) */
11004: /* continue; */
11005: /* fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1); */
11006: /* strcpy(gplotlabel,"("); */
11007: /* /\*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*\/ */
11008: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
11009: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
11010: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
11011: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
11012: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
11013: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
11014: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
11015: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
11016: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
11017: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
11018: /* } */
11019: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
11020: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
11021: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
11022: /* } */
1.264 brouard 11023: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 11024: fprintf(ficgp,"\n#\n");
1.264 brouard 11025: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 11026: fprintf(ficgp,"\nset key outside ");
11027: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
11028: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 11029: fprintf(ficgp,"\nset ter svg size 640, 480 ");
11030: if (ng==1){
11031: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
11032: fprintf(ficgp,"\nunset log y");
11033: }else if (ng==2){
11034: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
11035: fprintf(ficgp,"\nset log y");
11036: }else if (ng==3){
11037: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
11038: fprintf(ficgp,"\nset log y");
11039: }else
11040: fprintf(ficgp,"\nunset title ");
11041: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
11042: i=1;
11043: for(k2=1; k2<=nlstate; k2++) {
11044: k3=i;
11045: for(k=1; k<=(nlstate+ndeath); k++) {
11046: if (k != k2){
11047: switch( ng) {
11048: case 1:
11049: if(nagesqr==0)
11050: fprintf(ficgp," p%d+p%d*x",i,i+1);
11051: else /* nagesqr =1 */
11052: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
11053: break;
11054: case 2: /* ng=2 */
11055: if(nagesqr==0)
11056: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
11057: else /* nagesqr =1 */
11058: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
11059: break;
11060: case 3:
11061: if(nagesqr==0)
11062: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
11063: else /* nagesqr =1 */
11064: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
11065: break;
11066: }
11067: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 11068: ijp=1; /* product no age */
11069: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
11070: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 11071: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.329 brouard 11072: switch(Typevar[j]){
11073: case 1:
11074: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
11075: if(j==Tage[ij]) { /* Product by age To be looked at!!*//* Bug valgrind */
11076: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
11077: if(DummyV[j]==0){/* Bug valgrind */
11078: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
11079: }else{ /* quantitative */
11080: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
11081: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
11082: }
11083: ij++;
1.268 brouard 11084: }
1.237 brouard 11085: }
1.329 brouard 11086: }
11087: break;
11088: case 2:
11089: if(cptcovprod >0){
11090: if(j==Tprod[ijp]) { /* */
11091: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
11092: if(ijp <=cptcovprod) { /* Product */
11093: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
11094: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
11095: /* 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)]); */
11096: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
11097: }else{ /* Vn is dummy and Vm is quanti */
11098: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
11099: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
11100: }
11101: }else{ /* Vn*Vm Vn is quanti */
11102: if(DummyV[Tvard[ijp][2]]==0){
11103: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
11104: }else{ /* Both quanti */
11105: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
11106: }
1.268 brouard 11107: }
1.329 brouard 11108: ijp++;
1.237 brouard 11109: }
1.329 brouard 11110: } /* end Tprod */
11111: }
11112: break;
1.349 brouard 11113: case 3:
11114: if(cptcovdageprod >0){
11115: /* if(j==Tprod[ijp]) { */ /* not necessary */
11116: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
1.350 brouard 11117: if(ijp <=cptcovprod) { /* Product Vn*Vm and age*VN*Vm*/
11118: if(DummyV[Tvardk[ijp][1]]==0){/* Vn is dummy */
11119: if(DummyV[Tvardk[ijp][2]]==0){/* Vn and Vm are dummy */
1.349 brouard 11120: /* 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)]); */
11121: fprintf(ficgp,"+p%d*%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
11122: }else{ /* Vn is dummy and Vm is quanti */
11123: /* 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 11124: 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 11125: }
1.350 brouard 11126: }else{ /* age* Vn*Vm Vn is quanti HERE */
1.349 brouard 11127: if(DummyV[Tvard[ijp][2]]==0){
1.350 brouard 11128: 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 11129: }else{ /* Both quanti */
1.350 brouard 11130: 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 11131: }
11132: }
11133: ijp++;
11134: }
11135: /* } */ /* end Tprod */
11136: }
11137: break;
1.329 brouard 11138: case 0:
11139: /* simple covariate */
1.264 brouard 11140: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 11141: if(Dummy[j]==0){
11142: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
11143: }else{ /* quantitative */
11144: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 11145: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 11146: }
1.329 brouard 11147: /* end simple */
11148: break;
11149: default:
11150: break;
11151: } /* end switch */
1.237 brouard 11152: } /* end j */
1.329 brouard 11153: }else{ /* k=k2 */
11154: if(ng !=1 ){ /* For logit formula of log p11 is more difficult to get */
11155: fprintf(ficgp," (1.");i=i-ncovmodel;
11156: }else
11157: i=i-ncovmodel;
1.223 brouard 11158: }
1.227 brouard 11159:
1.223 brouard 11160: if(ng != 1){
11161: fprintf(ficgp,")/(1");
1.227 brouard 11162:
1.264 brouard 11163: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 11164: if(nagesqr==0)
1.264 brouard 11165: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 11166: else /* nagesqr =1 */
1.264 brouard 11167: 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 11168:
1.223 brouard 11169: ij=1;
1.329 brouard 11170: ijp=1;
11171: /* for(j=3; j <=ncovmodel-nagesqr; j++){ */
11172: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
11173: switch(Typevar[j]){
11174: case 1:
11175: if(cptcovage >0){
11176: if(j==Tage[ij]) { /* Bug valgrind */
11177: if(ij <=cptcovage) { /* Bug valgrind */
11178: if(DummyV[j]==0){/* Bug valgrind */
11179: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]); */
11180: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,nbcode[Tvar[j]][codtabm(k1,j)]); */
11181: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]);
11182: /* fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);; */
11183: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
11184: }else{ /* quantitative */
11185: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
11186: fprintf(ficgp,"+p%d*%f*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
11187: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
11188: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
11189: }
11190: ij++;
11191: }
11192: }
11193: }
11194: break;
11195: case 2:
11196: if(cptcovprod >0){
11197: if(j==Tprod[ijp]) { /* */
11198: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
11199: if(ijp <=cptcovprod) { /* Product */
11200: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
11201: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
11202: /* 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)]); */
11203: fprintf(ficgp,"+p%d*%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
11204: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
11205: }else{ /* Vn is dummy and Vm is quanti */
11206: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
11207: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
11208: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
11209: }
11210: }else{ /* Vn*Vm Vn is quanti */
11211: if(DummyV[Tvard[ijp][2]]==0){
11212: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
11213: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
11214: }else{ /* Both quanti */
11215: fprintf(ficgp,"+p%d*%f*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
11216: /* fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
11217: }
11218: }
11219: ijp++;
11220: }
11221: } /* end Tprod */
11222: } /* end if */
11223: break;
1.349 brouard 11224: case 3:
11225: if(cptcovdageprod >0){
11226: /* if(j==Tprod[ijp]) { /\* *\/ */
11227: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
11228: if(ijp <=cptcovprod) { /* Product */
1.350 brouard 11229: if(DummyV[Tvardk[ijp][1]]==0){/* Vn is dummy */
11230: if(DummyV[Tvardk[ijp][2]]==0){/* Vn and Vm are dummy */
1.349 brouard 11231: /* 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 11232: 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 11233: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
11234: }else{ /* Vn is dummy and Vm is quanti */
11235: /* 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 11236: 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 11237: /* fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
11238: }
11239: }else{ /* Vn*Vm Vn is quanti */
1.350 brouard 11240: if(DummyV[Tvardk[ijp][2]]==0){
11241: 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 11242: /* fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
11243: }else{ /* Both quanti */
1.350 brouard 11244: 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 11245: /* fprintf(ficgp,"+p%d*%f*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
11246: }
11247: }
11248: ijp++;
11249: }
11250: /* } /\* end Tprod *\/ */
11251: } /* end if */
11252: break;
1.329 brouard 11253: case 0:
11254: /* simple covariate */
11255: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
11256: if(Dummy[j]==0){
11257: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
11258: fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]); /* */
11259: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
11260: }else{ /* quantitative */
11261: fprintf(ficgp,"+p%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* */
11262: /* fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* *\/ */
11263: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
11264: }
11265: /* end simple */
11266: /* fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);/\* Valgrind bug nbcode *\/ */
11267: break;
11268: default:
11269: break;
11270: } /* end switch */
1.223 brouard 11271: }
11272: fprintf(ficgp,")");
11273: }
11274: fprintf(ficgp,")");
11275: if(ng ==2)
1.276 brouard 11276: 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 11277: else /* ng= 3 */
1.276 brouard 11278: 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 11279: }else{ /* end ng <> 1 */
1.223 brouard 11280: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 11281: 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 11282: }
11283: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
11284: fprintf(ficgp,",");
11285: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
11286: fprintf(ficgp,",");
11287: i=i+ncovmodel;
11288: } /* end k */
11289: } /* end k2 */
1.276 brouard 11290: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
11291: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.337 brouard 11292: } /* end resultline */
1.223 brouard 11293: } /* end ng */
11294: /* avoid: */
11295: fflush(ficgp);
1.126 brouard 11296: } /* end gnuplot */
11297:
11298:
11299: /*************** Moving average **************/
1.219 brouard 11300: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 11301: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 11302:
1.222 brouard 11303: int i, cpt, cptcod;
11304: int modcovmax =1;
11305: int mobilavrange, mob;
11306: int iage=0;
1.288 brouard 11307: int firstA1=0, firstA2=0;
1.222 brouard 11308:
1.266 brouard 11309: double sum=0., sumr=0.;
1.222 brouard 11310: double age;
1.266 brouard 11311: double *sumnewp, *sumnewm, *sumnewmr;
11312: double *agemingood, *agemaxgood;
11313: double *agemingoodr, *agemaxgoodr;
1.222 brouard 11314:
11315:
1.278 brouard 11316: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
11317: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 11318:
11319: sumnewp = vector(1,ncovcombmax);
11320: sumnewm = vector(1,ncovcombmax);
1.266 brouard 11321: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 11322: agemingood = vector(1,ncovcombmax);
1.266 brouard 11323: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 11324: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 11325: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 11326:
11327: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 11328: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 11329: sumnewp[cptcod]=0.;
1.266 brouard 11330: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
11331: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 11332: }
11333: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
11334:
1.266 brouard 11335: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
11336: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 11337: else mobilavrange=mobilav;
11338: for (age=bage; age<=fage; age++)
11339: for (i=1; i<=nlstate;i++)
11340: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
11341: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
11342: /* We keep the original values on the extreme ages bage, fage and for
11343: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
11344: we use a 5 terms etc. until the borders are no more concerned.
11345: */
11346: for (mob=3;mob <=mobilavrange;mob=mob+2){
11347: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 11348: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
11349: sumnewm[cptcod]=0.;
11350: for (i=1; i<=nlstate;i++){
1.222 brouard 11351: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
11352: for (cpt=1;cpt<=(mob-1)/2;cpt++){
11353: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
11354: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
11355: }
11356: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 11357: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
11358: } /* end i */
11359: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
11360: } /* end cptcod */
1.222 brouard 11361: }/* end age */
11362: }/* end mob */
1.266 brouard 11363: }else{
11364: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 11365: return -1;
1.266 brouard 11366: }
11367:
11368: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 11369: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
11370: if(invalidvarcomb[cptcod]){
11371: printf("\nCombination (%d) ignored because no cases \n",cptcod);
11372: continue;
11373: }
1.219 brouard 11374:
1.266 brouard 11375: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
11376: sumnewm[cptcod]=0.;
11377: sumnewmr[cptcod]=0.;
11378: for (i=1; i<=nlstate;i++){
11379: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
11380: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
11381: }
11382: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
11383: agemingoodr[cptcod]=age;
11384: }
11385: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
11386: agemingood[cptcod]=age;
11387: }
11388: } /* age */
11389: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 11390: sumnewm[cptcod]=0.;
1.266 brouard 11391: sumnewmr[cptcod]=0.;
1.222 brouard 11392: for (i=1; i<=nlstate;i++){
11393: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 11394: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
11395: }
11396: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
11397: agemaxgoodr[cptcod]=age;
1.222 brouard 11398: }
11399: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 11400: agemaxgood[cptcod]=age;
11401: }
11402: } /* age */
11403: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
11404: /* but they will change */
1.288 brouard 11405: firstA1=0;firstA2=0;
1.266 brouard 11406: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
11407: sumnewm[cptcod]=0.;
11408: sumnewmr[cptcod]=0.;
11409: for (i=1; i<=nlstate;i++){
11410: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
11411: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
11412: }
11413: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
11414: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
11415: agemaxgoodr[cptcod]=age; /* age min */
11416: for (i=1; i<=nlstate;i++)
11417: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
11418: }else{ /* bad we change the value with the values of good ages */
11419: for (i=1; i<=nlstate;i++){
11420: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
11421: } /* i */
11422: } /* end bad */
11423: }else{
11424: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
11425: agemaxgood[cptcod]=age;
11426: }else{ /* bad we change the value with the values of good ages */
11427: for (i=1; i<=nlstate;i++){
11428: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
11429: } /* i */
11430: } /* end bad */
11431: }/* end else */
11432: sum=0.;sumr=0.;
11433: for (i=1; i<=nlstate;i++){
11434: sum+=mobaverage[(int)age][i][cptcod];
11435: sumr+=probs[(int)age][i][cptcod];
11436: }
11437: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 11438: if(!firstA1){
11439: firstA1=1;
11440: 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);
11441: }
11442: 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 11443: } /* end bad */
11444: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
11445: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 11446: if(!firstA2){
11447: firstA2=1;
11448: 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);
11449: }
11450: 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 11451: } /* end bad */
11452: }/* age */
1.266 brouard 11453:
11454: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 11455: sumnewm[cptcod]=0.;
1.266 brouard 11456: sumnewmr[cptcod]=0.;
1.222 brouard 11457: for (i=1; i<=nlstate;i++){
11458: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 11459: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
11460: }
11461: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
11462: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
11463: agemingoodr[cptcod]=age;
11464: for (i=1; i<=nlstate;i++)
11465: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
11466: }else{ /* bad we change the value with the values of good ages */
11467: for (i=1; i<=nlstate;i++){
11468: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
11469: } /* i */
11470: } /* end bad */
11471: }else{
11472: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
11473: agemingood[cptcod]=age;
11474: }else{ /* bad */
11475: for (i=1; i<=nlstate;i++){
11476: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
11477: } /* i */
11478: } /* end bad */
11479: }/* end else */
11480: sum=0.;sumr=0.;
11481: for (i=1; i<=nlstate;i++){
11482: sum+=mobaverage[(int)age][i][cptcod];
11483: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 11484: }
1.266 brouard 11485: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 11486: 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 11487: } /* end bad */
11488: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
11489: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 11490: 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 11491: } /* end bad */
11492: }/* age */
1.266 brouard 11493:
1.222 brouard 11494:
11495: for (age=bage; age<=fage; age++){
1.235 brouard 11496: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 11497: sumnewp[cptcod]=0.;
11498: sumnewm[cptcod]=0.;
11499: for (i=1; i<=nlstate;i++){
11500: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
11501: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
11502: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
11503: }
11504: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
11505: }
11506: /* printf("\n"); */
11507: /* } */
1.266 brouard 11508:
1.222 brouard 11509: /* brutal averaging */
1.266 brouard 11510: /* for (i=1; i<=nlstate;i++){ */
11511: /* for (age=1; age<=bage; age++){ */
11512: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
11513: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
11514: /* } */
11515: /* for (age=fage; age<=AGESUP; age++){ */
11516: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
11517: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
11518: /* } */
11519: /* } /\* end i status *\/ */
11520: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
11521: /* for (age=1; age<=AGESUP; age++){ */
11522: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
11523: /* mobaverage[(int)age][i][cptcod]=0.; */
11524: /* } */
11525: /* } */
1.222 brouard 11526: }/* end cptcod */
1.266 brouard 11527: free_vector(agemaxgoodr,1, ncovcombmax);
11528: free_vector(agemaxgood,1, ncovcombmax);
11529: free_vector(agemingood,1, ncovcombmax);
11530: free_vector(agemingoodr,1, ncovcombmax);
11531: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 11532: free_vector(sumnewm,1, ncovcombmax);
11533: free_vector(sumnewp,1, ncovcombmax);
11534: return 0;
11535: }/* End movingaverage */
1.218 brouard 11536:
1.126 brouard 11537:
1.296 brouard 11538:
1.126 brouard 11539: /************** Forecasting ******************/
1.296 brouard 11540: /* 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)*/
11541: 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){
11542: /* dateintemean, mean date of interviews
11543: dateprojd, year, month, day of starting projection
11544: dateprojf date of end of projection;year of end of projection (same day and month as proj1).
1.126 brouard 11545: agemin, agemax range of age
11546: dateprev1 dateprev2 range of dates during which prevalence is computed
11547: */
1.296 brouard 11548: /* double anprojd, mprojd, jprojd; */
11549: /* double anprojf, mprojf, jprojf; */
1.359 brouard 11550: int yearp, stepsize, hstepm, nhstepm, j, k, i, h, nres=0;
1.126 brouard 11551: double agec; /* generic age */
1.359 brouard 11552: double agelim, ppij;
11553: /*double *popcount;*/
1.126 brouard 11554: double ***p3mat;
1.218 brouard 11555: /* double ***mobaverage; */
1.126 brouard 11556: char fileresf[FILENAMELENGTH];
11557:
11558: agelim=AGESUP;
1.211 brouard 11559: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
11560: in each health status at the date of interview (if between dateprev1 and dateprev2).
11561: We still use firstpass and lastpass as another selection.
11562: */
1.214 brouard 11563: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
11564: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 11565:
1.201 brouard 11566: strcpy(fileresf,"F_");
11567: strcat(fileresf,fileresu);
1.126 brouard 11568: if((ficresf=fopen(fileresf,"w"))==NULL) {
11569: printf("Problem with forecast resultfile: %s\n", fileresf);
11570: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
11571: }
1.235 brouard 11572: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
11573: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 11574:
1.225 brouard 11575: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 11576:
11577:
11578: stepsize=(int) (stepm+YEARM-1)/YEARM;
11579: if (stepm<=12) stepsize=1;
11580: if(estepm < stepm){
11581: printf ("Problem %d lower than %d\n",estepm, stepm);
11582: }
1.270 brouard 11583: else{
11584: hstepm=estepm;
11585: }
11586: if(estepm > stepm){ /* Yes every two year */
11587: stepsize=2;
11588: }
1.296 brouard 11589: hstepm=hstepm/stepm;
1.126 brouard 11590:
1.296 brouard 11591:
11592: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
11593: /* fractional in yp1 *\/ */
11594: /* aintmean=yp; */
11595: /* yp2=modf((yp1*12),&yp); */
11596: /* mintmean=yp; */
11597: /* yp1=modf((yp2*30.5),&yp); */
11598: /* jintmean=yp; */
11599: /* if(jintmean==0) jintmean=1; */
11600: /* if(mintmean==0) mintmean=1; */
1.126 brouard 11601:
1.296 brouard 11602:
11603: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */
11604: /* date2dmy(dateprojd,&jprojd, &mprojd, &anprojd); */
11605: /* date2dmy(dateprojf,&jprojf, &mprojf, &anprojf); */
1.351 brouard 11606: /* i1=pow(2,cptcoveff); */
11607: /* if (cptcovn < 1){i1=1;} */
1.126 brouard 11608:
1.296 brouard 11609: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.126 brouard 11610:
11611: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 11612:
1.126 brouard 11613: /* if (h==(int)(YEARM*yearp)){ */
1.351 brouard 11614: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
11615: k=TKresult[nres];
11616: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
11617: /* 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) *\/ */
11618: /* if(i1 != 1 && TKresult[nres]!= k) */
11619: /* continue; */
11620: /* if(invalidvarcomb[k]){ */
11621: /* printf("\nCombination (%d) projection ignored because no cases \n",k); */
11622: /* continue; */
11623: /* } */
1.227 brouard 11624: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
1.351 brouard 11625: for(j=1;j<=cptcovs;j++){
11626: /* for(j=1;j<=cptcoveff;j++) { */
11627: /* /\* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); *\/ */
11628: /* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11629: /* } */
11630: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
11631: /* fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
11632: /* } */
11633: fprintf(ficresf," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.235 brouard 11634: }
1.351 brouard 11635:
1.227 brouard 11636: fprintf(ficresf," yearproj age");
11637: for(j=1; j<=nlstate+ndeath;j++){
11638: for(i=1; i<=nlstate;i++)
11639: fprintf(ficresf," p%d%d",i,j);
11640: fprintf(ficresf," wp.%d",j);
11641: }
1.296 brouard 11642: for (yearp=0; yearp<=(anprojf-anprojd);yearp +=stepsize) {
1.227 brouard 11643: fprintf(ficresf,"\n");
1.296 brouard 11644: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jprojd,mprojd,anprojd+yearp);
1.270 brouard 11645: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
11646: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 11647: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
11648: nhstepm = nhstepm/hstepm;
11649: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11650: oldm=oldms;savm=savms;
1.268 brouard 11651: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 11652: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 11653: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 11654: for (h=0; h<=nhstepm; h++){
11655: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 11656: break;
11657: }
11658: }
11659: fprintf(ficresf,"\n");
1.351 brouard 11660: /* for(j=1;j<=cptcoveff;j++) */
11661: for(j=1;j<=cptcovs;j++)
11662: fprintf(ficresf,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.332 brouard 11663: /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Tvaraff not correct *\/ */
1.351 brouard 11664: /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /\* TnsdVar[Tvaraff] correct *\/ */
1.296 brouard 11665: fprintf(ficresf,"%.f %.f ",anprojd+yearp,agec+h*hstepm/YEARM*stepm);
1.268 brouard 11666:
11667: for(j=1; j<=nlstate+ndeath;j++) {
11668: ppij=0.;
11669: for(i=1; i<=nlstate;i++) {
1.278 brouard 11670: if (mobilav>=1)
11671: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
11672: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
11673: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
11674: }
1.268 brouard 11675: fprintf(ficresf," %.3f", p3mat[i][j][h]);
11676: } /* end i */
11677: fprintf(ficresf," %.3f", ppij);
11678: }/* end j */
1.227 brouard 11679: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11680: } /* end agec */
1.266 brouard 11681: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
11682: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 11683: } /* end yearp */
11684: } /* end k */
1.219 brouard 11685:
1.126 brouard 11686: fclose(ficresf);
1.215 brouard 11687: printf("End of Computing forecasting \n");
11688: fprintf(ficlog,"End of Computing forecasting\n");
11689:
1.126 brouard 11690: }
11691:
1.269 brouard 11692: /************** Back Forecasting ******************/
1.296 brouard 11693: /* 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){ */
11694: 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){
11695: /* back1, year, month, day of starting backprojection
1.267 brouard 11696: agemin, agemax range of age
11697: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 11698: anback2 year of end of backprojection (same day and month as back1).
11699: prevacurrent and prev are prevalences.
1.267 brouard 11700: */
1.359 brouard 11701: int yearp, stepsize, hstepm, nhstepm, j, k, i, h, nres=0;
1.267 brouard 11702: double agec; /* generic age */
1.359 brouard 11703: double agelim, ppij, ppi; /* ,jintmean,mintmean,aintmean;*/
11704: /*double *popcount;*/
1.267 brouard 11705: double ***p3mat;
11706: /* double ***mobaverage; */
11707: char fileresfb[FILENAMELENGTH];
11708:
1.268 brouard 11709: agelim=AGEINF;
1.267 brouard 11710: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
11711: in each health status at the date of interview (if between dateprev1 and dateprev2).
11712: We still use firstpass and lastpass as another selection.
11713: */
11714: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
11715: /* firstpass, lastpass, stepm, weightopt, model); */
11716:
11717: /*Do we need to compute prevalence again?*/
11718:
11719: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
11720:
11721: strcpy(fileresfb,"FB_");
11722: strcat(fileresfb,fileresu);
11723: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
11724: printf("Problem with back forecast resultfile: %s\n", fileresfb);
11725: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
11726: }
11727: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
11728: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
11729:
11730: if (cptcoveff==0) ncodemax[cptcoveff]=1;
11731:
11732:
11733: stepsize=(int) (stepm+YEARM-1)/YEARM;
11734: if (stepm<=12) stepsize=1;
11735: if(estepm < stepm){
11736: printf ("Problem %d lower than %d\n",estepm, stepm);
11737: }
1.270 brouard 11738: else{
11739: hstepm=estepm;
11740: }
11741: if(estepm >= stepm){ /* Yes every two year */
11742: stepsize=2;
11743: }
1.267 brouard 11744:
11745: hstepm=hstepm/stepm;
1.296 brouard 11746: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
11747: /* fractional in yp1 *\/ */
11748: /* aintmean=yp; */
11749: /* yp2=modf((yp1*12),&yp); */
11750: /* mintmean=yp; */
11751: /* yp1=modf((yp2*30.5),&yp); */
11752: /* jintmean=yp; */
11753: /* if(jintmean==0) jintmean=1; */
11754: /* if(mintmean==0) jintmean=1; */
1.267 brouard 11755:
1.351 brouard 11756: /* i1=pow(2,cptcoveff); */
11757: /* if (cptcovn < 1){i1=1;} */
1.267 brouard 11758:
1.296 brouard 11759: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
11760: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 11761:
11762: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
11763:
1.351 brouard 11764: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
11765: k=TKresult[nres];
11766: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
11767: /* for(k=1; k<=i1;k++){ */
11768: /* if(i1 != 1 && TKresult[nres]!= k) */
11769: /* continue; */
11770: /* if(invalidvarcomb[k]){ */
11771: /* printf("\nCombination (%d) projection ignored because no cases \n",k); */
11772: /* continue; */
11773: /* } */
1.268 brouard 11774: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.351 brouard 11775: for(j=1;j<=cptcovs;j++){
11776: /* for(j=1;j<=cptcoveff;j++) { */
11777: /* fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11778: /* } */
11779: fprintf(ficresfb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.267 brouard 11780: }
1.351 brouard 11781: /* fprintf(ficrespij,"******\n"); */
11782: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
11783: /* fprintf(ficresfb," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
11784: /* } */
1.267 brouard 11785: fprintf(ficresfb," yearbproj age");
11786: for(j=1; j<=nlstate+ndeath;j++){
11787: for(i=1; i<=nlstate;i++)
1.268 brouard 11788: fprintf(ficresfb," b%d%d",i,j);
11789: fprintf(ficresfb," b.%d",j);
1.267 brouard 11790: }
1.296 brouard 11791: for (yearp=0; yearp>=(anbackf-anbackd);yearp -=stepsize) {
1.267 brouard 11792: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
11793: fprintf(ficresfb,"\n");
1.296 brouard 11794: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jbackd,mbackd,anbackd+yearp);
1.273 brouard 11795: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 11796: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
11797: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 11798: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 11799: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 11800: nhstepm = nhstepm/hstepm;
11801: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11802: oldm=oldms;savm=savms;
1.268 brouard 11803: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 11804: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 11805: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 11806: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
11807: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
11808: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 11809: for (h=0; h<=nhstepm; h++){
1.268 brouard 11810: if (h*hstepm/YEARM*stepm ==-yearp) {
11811: break;
11812: }
11813: }
11814: fprintf(ficresfb,"\n");
1.351 brouard 11815: /* for(j=1;j<=cptcoveff;j++) */
11816: for(j=1;j<=cptcovs;j++)
11817: fprintf(ficresfb,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11818: /* fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.296 brouard 11819: fprintf(ficresfb,"%.f %.f ",anbackd+yearp,agec-h*hstepm/YEARM*stepm);
1.268 brouard 11820: for(i=1; i<=nlstate+ndeath;i++) {
11821: ppij=0.;ppi=0.;
11822: for(j=1; j<=nlstate;j++) {
11823: /* if (mobilav==1) */
1.269 brouard 11824: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
11825: ppi=ppi+prevacurrent[(int)agec][j][k];
11826: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
11827: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 11828: /* else { */
11829: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
11830: /* } */
1.268 brouard 11831: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
11832: } /* end j */
11833: if(ppi <0.99){
11834: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
11835: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
11836: }
11837: fprintf(ficresfb," %.3f", ppij);
11838: }/* end j */
1.267 brouard 11839: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11840: } /* end agec */
11841: } /* end yearp */
11842: } /* end k */
1.217 brouard 11843:
1.267 brouard 11844: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 11845:
1.267 brouard 11846: fclose(ficresfb);
11847: printf("End of Computing Back forecasting \n");
11848: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 11849:
1.267 brouard 11850: }
1.217 brouard 11851:
1.269 brouard 11852: /* Variance of prevalence limit: varprlim */
11853: 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 11854: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 11855:
11856: char fileresvpl[FILENAMELENGTH];
11857: FILE *ficresvpl;
11858: double **oldm, **savm;
11859: double **varpl; /* Variances of prevalence limits by age */
11860: int i1, k, nres, j ;
11861:
11862: strcpy(fileresvpl,"VPL_");
11863: strcat(fileresvpl,fileresu);
11864: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 11865: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 11866: exit(0);
11867: }
1.288 brouard 11868: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
11869: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 11870:
11871: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
11872: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
11873:
11874: i1=pow(2,cptcoveff);
11875: if (cptcovn < 1){i1=1;}
11876:
1.337 brouard 11877: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
11878: k=TKresult[nres];
1.338 brouard 11879: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 11880: /* for(k=1; k<=i1;k++){ /\* We find the combination equivalent to result line values of dummies *\/ */
1.269 brouard 11881: if(i1 != 1 && TKresult[nres]!= k)
11882: continue;
11883: fprintf(ficresvpl,"\n#****** ");
11884: printf("\n#****** ");
11885: fprintf(ficlog,"\n#****** ");
1.337 brouard 11886: for(j=1;j<=cptcovs;j++) {
11887: fprintf(ficresvpl,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11888: fprintf(ficlog,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11889: printf("V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11890: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11891: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.269 brouard 11892: }
1.337 brouard 11893: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
11894: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
11895: /* fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
11896: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
11897: /* } */
1.269 brouard 11898: fprintf(ficresvpl,"******\n");
11899: printf("******\n");
11900: fprintf(ficlog,"******\n");
11901:
11902: varpl=matrix(1,nlstate,(int) bage, (int) fage);
11903: oldm=oldms;savm=savms;
11904: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
11905: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
11906: /*}*/
11907: }
11908:
11909: fclose(ficresvpl);
1.288 brouard 11910: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
11911: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 11912:
11913: }
11914: /* Variance of back prevalence: varbprlim */
11915: 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){
11916: /*------- Variance of back (stable) prevalence------*/
11917:
11918: char fileresvbl[FILENAMELENGTH];
11919: FILE *ficresvbl;
11920:
11921: double **oldm, **savm;
11922: double **varbpl; /* Variances of back prevalence limits by age */
11923: int i1, k, nres, j ;
11924:
11925: strcpy(fileresvbl,"VBL_");
11926: strcat(fileresvbl,fileresu);
11927: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
11928: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
11929: exit(0);
11930: }
11931: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
11932: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
11933:
11934:
11935: i1=pow(2,cptcoveff);
11936: if (cptcovn < 1){i1=1;}
11937:
1.337 brouard 11938: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
11939: k=TKresult[nres];
1.338 brouard 11940: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 11941: /* for(k=1; k<=i1;k++){ */
11942: /* if(i1 != 1 && TKresult[nres]!= k) */
11943: /* continue; */
1.269 brouard 11944: fprintf(ficresvbl,"\n#****** ");
11945: printf("\n#****** ");
11946: fprintf(ficlog,"\n#****** ");
1.337 brouard 11947: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */
1.338 brouard 11948: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
11949: fprintf(ficresvbl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
11950: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
1.337 brouard 11951: /* for(j=1;j<=cptcoveff;j++) { */
11952: /* fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11953: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11954: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11955: /* } */
11956: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
11957: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
11958: /* fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
11959: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
1.269 brouard 11960: }
11961: fprintf(ficresvbl,"******\n");
11962: printf("******\n");
11963: fprintf(ficlog,"******\n");
11964:
11965: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
11966: oldm=oldms;savm=savms;
11967:
11968: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
11969: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
11970: /*}*/
11971: }
11972:
11973: fclose(ficresvbl);
11974: printf("done variance-covariance of back prevalence\n");fflush(stdout);
11975: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
11976:
11977: } /* End of varbprlim */
11978:
1.126 brouard 11979: /************** Forecasting *****not tested NB*************/
1.227 brouard 11980: /* 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 11981:
1.227 brouard 11982: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
11983: /* int *popage; */
11984: /* double calagedatem, agelim, kk1, kk2; */
11985: /* double *popeffectif,*popcount; */
11986: /* double ***p3mat,***tabpop,***tabpopprev; */
11987: /* /\* double ***mobaverage; *\/ */
11988: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 11989:
1.227 brouard 11990: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
11991: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
11992: /* agelim=AGESUP; */
11993: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 11994:
1.227 brouard 11995: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 11996:
11997:
1.227 brouard 11998: /* strcpy(filerespop,"POP_"); */
11999: /* strcat(filerespop,fileresu); */
12000: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
12001: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
12002: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
12003: /* } */
12004: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
12005: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 12006:
1.227 brouard 12007: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 12008:
1.227 brouard 12009: /* /\* if (mobilav!=0) { *\/ */
12010: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
12011: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
12012: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
12013: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
12014: /* /\* } *\/ */
12015: /* /\* } *\/ */
1.126 brouard 12016:
1.227 brouard 12017: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
12018: /* if (stepm<=12) stepsize=1; */
1.126 brouard 12019:
1.227 brouard 12020: /* agelim=AGESUP; */
1.126 brouard 12021:
1.227 brouard 12022: /* hstepm=1; */
12023: /* hstepm=hstepm/stepm; */
1.218 brouard 12024:
1.227 brouard 12025: /* if (popforecast==1) { */
12026: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
12027: /* printf("Problem with population file : %s\n",popfile);exit(0); */
12028: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
12029: /* } */
12030: /* popage=ivector(0,AGESUP); */
12031: /* popeffectif=vector(0,AGESUP); */
12032: /* popcount=vector(0,AGESUP); */
1.126 brouard 12033:
1.227 brouard 12034: /* i=1; */
12035: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 12036:
1.227 brouard 12037: /* imx=i; */
12038: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
12039: /* } */
1.218 brouard 12040:
1.227 brouard 12041: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
12042: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
12043: /* k=k+1; */
12044: /* fprintf(ficrespop,"\n#******"); */
12045: /* for(j=1;j<=cptcoveff;j++) { */
12046: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
12047: /* } */
12048: /* fprintf(ficrespop,"******\n"); */
12049: /* fprintf(ficrespop,"# Age"); */
12050: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
12051: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 12052:
1.227 brouard 12053: /* for (cpt=0; cpt<=0;cpt++) { */
12054: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 12055:
1.227 brouard 12056: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
12057: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
12058: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 12059:
1.227 brouard 12060: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
12061: /* oldm=oldms;savm=savms; */
12062: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 12063:
1.227 brouard 12064: /* for (h=0; h<=nhstepm; h++){ */
12065: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
12066: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
12067: /* } */
12068: /* for(j=1; j<=nlstate+ndeath;j++) { */
12069: /* kk1=0.;kk2=0; */
12070: /* for(i=1; i<=nlstate;i++) { */
12071: /* if (mobilav==1) */
12072: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
12073: /* else { */
12074: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
12075: /* } */
12076: /* } */
12077: /* if (h==(int)(calagedatem+12*cpt)){ */
12078: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
12079: /* /\*fprintf(ficrespop," %.3f", kk1); */
12080: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
12081: /* } */
12082: /* } */
12083: /* for(i=1; i<=nlstate;i++){ */
12084: /* kk1=0.; */
12085: /* for(j=1; j<=nlstate;j++){ */
12086: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
12087: /* } */
12088: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
12089: /* } */
1.218 brouard 12090:
1.227 brouard 12091: /* if (h==(int)(calagedatem+12*cpt)) */
12092: /* for(j=1; j<=nlstate;j++) */
12093: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
12094: /* } */
12095: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
12096: /* } */
12097: /* } */
1.218 brouard 12098:
1.227 brouard 12099: /* /\******\/ */
1.218 brouard 12100:
1.227 brouard 12101: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
12102: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
12103: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
12104: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
12105: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 12106:
1.227 brouard 12107: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
12108: /* oldm=oldms;savm=savms; */
12109: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
12110: /* for (h=0; h<=nhstepm; h++){ */
12111: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
12112: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
12113: /* } */
12114: /* for(j=1; j<=nlstate+ndeath;j++) { */
12115: /* kk1=0.;kk2=0; */
12116: /* for(i=1; i<=nlstate;i++) { */
12117: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
12118: /* } */
12119: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
12120: /* } */
12121: /* } */
12122: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
12123: /* } */
12124: /* } */
12125: /* } */
12126: /* } */
1.218 brouard 12127:
1.227 brouard 12128: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 12129:
1.227 brouard 12130: /* if (popforecast==1) { */
12131: /* free_ivector(popage,0,AGESUP); */
12132: /* free_vector(popeffectif,0,AGESUP); */
12133: /* free_vector(popcount,0,AGESUP); */
12134: /* } */
12135: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
12136: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
12137: /* fclose(ficrespop); */
12138: /* } /\* End of popforecast *\/ */
1.218 brouard 12139:
1.126 brouard 12140: int fileappend(FILE *fichier, char *optionfich)
12141: {
12142: if((fichier=fopen(optionfich,"a"))==NULL) {
12143: printf("Problem with file: %s\n", optionfich);
12144: fprintf(ficlog,"Problem with file: %s\n", optionfich);
12145: return (0);
12146: }
12147: fflush(fichier);
12148: return (1);
12149: }
12150:
12151:
12152: /**************** function prwizard **********************/
12153: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
12154: {
12155:
12156: /* Wizard to print covariance matrix template */
12157:
1.164 brouard 12158: char ca[32], cb[32];
12159: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 12160: int numlinepar;
12161:
12162: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
12163: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
12164: for(i=1; i <=nlstate; i++){
12165: jj=0;
12166: for(j=1; j <=nlstate+ndeath; j++){
12167: if(j==i) continue;
12168: jj++;
12169: /*ca[0]= k+'a'-1;ca[1]='\0';*/
12170: printf("%1d%1d",i,j);
12171: fprintf(ficparo,"%1d%1d",i,j);
12172: for(k=1; k<=ncovmodel;k++){
12173: /* printf(" %lf",param[i][j][k]); */
12174: /* fprintf(ficparo," %lf",param[i][j][k]); */
12175: printf(" 0.");
12176: fprintf(ficparo," 0.");
12177: }
12178: printf("\n");
12179: fprintf(ficparo,"\n");
12180: }
12181: }
12182: printf("# Scales (for hessian or gradient estimation)\n");
12183: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
12184: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
12185: for(i=1; i <=nlstate; i++){
12186: jj=0;
12187: for(j=1; j <=nlstate+ndeath; j++){
12188: if(j==i) continue;
12189: jj++;
12190: fprintf(ficparo,"%1d%1d",i,j);
12191: printf("%1d%1d",i,j);
12192: fflush(stdout);
12193: for(k=1; k<=ncovmodel;k++){
12194: /* printf(" %le",delti3[i][j][k]); */
12195: /* fprintf(ficparo," %le",delti3[i][j][k]); */
12196: printf(" 0.");
12197: fprintf(ficparo," 0.");
12198: }
12199: numlinepar++;
12200: printf("\n");
12201: fprintf(ficparo,"\n");
12202: }
12203: }
12204: printf("# Covariance matrix\n");
12205: /* # 121 Var(a12)\n\ */
12206: /* # 122 Cov(b12,a12) Var(b12)\n\ */
12207: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
12208: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
12209: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
12210: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
12211: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
12212: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
12213: fflush(stdout);
12214: fprintf(ficparo,"# Covariance matrix\n");
12215: /* # 121 Var(a12)\n\ */
12216: /* # 122 Cov(b12,a12) Var(b12)\n\ */
12217: /* # ...\n\ */
12218: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
12219:
12220: for(itimes=1;itimes<=2;itimes++){
12221: jj=0;
12222: for(i=1; i <=nlstate; i++){
12223: for(j=1; j <=nlstate+ndeath; j++){
12224: if(j==i) continue;
12225: for(k=1; k<=ncovmodel;k++){
12226: jj++;
12227: ca[0]= k+'a'-1;ca[1]='\0';
12228: if(itimes==1){
12229: printf("#%1d%1d%d",i,j,k);
12230: fprintf(ficparo,"#%1d%1d%d",i,j,k);
12231: }else{
12232: printf("%1d%1d%d",i,j,k);
12233: fprintf(ficparo,"%1d%1d%d",i,j,k);
12234: /* printf(" %.5le",matcov[i][j]); */
12235: }
12236: ll=0;
12237: for(li=1;li <=nlstate; li++){
12238: for(lj=1;lj <=nlstate+ndeath; lj++){
12239: if(lj==li) continue;
12240: for(lk=1;lk<=ncovmodel;lk++){
12241: ll++;
12242: if(ll<=jj){
12243: cb[0]= lk +'a'-1;cb[1]='\0';
12244: if(ll<jj){
12245: if(itimes==1){
12246: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12247: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12248: }else{
12249: printf(" 0.");
12250: fprintf(ficparo," 0.");
12251: }
12252: }else{
12253: if(itimes==1){
12254: printf(" Var(%s%1d%1d)",ca,i,j);
12255: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
12256: }else{
12257: printf(" 0.");
12258: fprintf(ficparo," 0.");
12259: }
12260: }
12261: }
12262: } /* end lk */
12263: } /* end lj */
12264: } /* end li */
12265: printf("\n");
12266: fprintf(ficparo,"\n");
12267: numlinepar++;
12268: } /* end k*/
12269: } /*end j */
12270: } /* end i */
12271: } /* end itimes */
12272:
12273: } /* end of prwizard */
12274: /******************* Gompertz Likelihood ******************************/
12275: double gompertz(double x[])
12276: {
1.302 brouard 12277: double A=0.0,B=0.,L=0.0,sump=0.,num=0.;
1.126 brouard 12278: int i,n=0; /* n is the size of the sample */
12279:
1.220 brouard 12280: for (i=1;i<=imx ; i++) {
1.126 brouard 12281: sump=sump+weight[i];
12282: /* sump=sump+1;*/
12283: num=num+1;
12284: }
1.302 brouard 12285: L=0.0;
12286: /* agegomp=AGEGOMP; */
1.126 brouard 12287: /* for (i=0; i<=imx; i++)
12288: 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]);*/
12289:
1.302 brouard 12290: for (i=1;i<=imx ; i++) {
12291: /* mu(a)=mu(agecomp)*exp(teta*(age-agegomp))
12292: mu(a)=x[1]*exp(x[2]*(age-agegomp)); x[1] and x[2] are per year.
12293: * L= Product mu(agedeces)exp(-\int_ageexam^agedc mu(u) du ) for a death between agedc (in month)
12294: * and agedc +1 month, cens[i]=0: log(x[1]/YEARM)
12295: * +
12296: * exp(-\int_ageexam^agecens mu(u) du ) when censored, cens[i]=1
12297: */
12298: if (wav[i] > 1 || agedc[i] < AGESUP) {
12299: if (cens[i] == 1){
12300: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
12301: } else if (cens[i] == 0){
1.126 brouard 12302: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
1.362 brouard 12303: +log(fabs(x[1])/YEARM) +x[2]*(agedc[i]-agegomp)+log(YEARM);
12304: /* +log(x[1]/YEARM) +x[2]*(agedc[i]-agegomp)+log(YEARM); */ /* To be seen */
1.302 brouard 12305: } else
12306: printf("Gompertz cens[%d] neither 1 nor 0\n",i);
1.126 brouard 12307: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
1.302 brouard 12308: L=L+A*weight[i];
1.126 brouard 12309: /* 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 12310: }
12311: }
1.126 brouard 12312:
1.302 brouard 12313: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
1.126 brouard 12314:
12315: return -2*L*num/sump;
12316: }
12317:
1.136 brouard 12318: #ifdef GSL
12319: /******************* Gompertz_f Likelihood ******************************/
12320: double gompertz_f(const gsl_vector *v, void *params)
12321: {
1.302 brouard 12322: double A=0.,B=0.,LL=0.0,sump=0.,num=0.;
1.136 brouard 12323: double *x= (double *) v->data;
12324: int i,n=0; /* n is the size of the sample */
12325:
12326: for (i=0;i<=imx-1 ; i++) {
12327: sump=sump+weight[i];
12328: /* sump=sump+1;*/
12329: num=num+1;
12330: }
12331:
12332:
12333: /* for (i=0; i<=imx; i++)
12334: 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]);*/
12335: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
12336: for (i=1;i<=imx ; i++)
12337: {
12338: if (cens[i] == 1 && wav[i]>1)
12339: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
12340:
12341: if (cens[i] == 0 && wav[i]>1)
12342: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
12343: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
12344:
12345: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
12346: if (wav[i] > 1 ) { /* ??? */
12347: LL=LL+A*weight[i];
12348: /* 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]);*/
12349: }
12350: }
12351:
12352: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
12353: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
12354:
12355: return -2*LL*num/sump;
12356: }
12357: #endif
12358:
1.126 brouard 12359: /******************* Printing html file ***********/
1.201 brouard 12360: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 12361: int lastpass, int stepm, int weightopt, char model[],\
12362: int imx, double p[],double **matcov,double agemortsup){
12363: int i,k;
12364:
12365: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
12366: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
12367: for (i=1;i<=2;i++)
12368: 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 12369: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 12370: fprintf(fichtm,"</ul>");
12371:
12372: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
12373:
12374: 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>");
12375:
12376: for (k=agegomp;k<(agemortsup-2);k++)
12377: 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]);
12378:
12379:
12380: fflush(fichtm);
12381: }
12382:
12383: /******************* Gnuplot file **************/
1.201 brouard 12384: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 12385:
12386: char dirfileres[132],optfileres[132];
1.164 brouard 12387:
1.359 brouard 12388: /*int ng;*/
1.126 brouard 12389:
12390:
12391: /*#ifdef windows */
12392: fprintf(ficgp,"cd \"%s\" \n",pathc);
12393: /*#endif */
12394:
12395:
12396: strcpy(dirfileres,optionfilefiname);
12397: strcpy(optfileres,"vpl");
1.199 brouard 12398: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 12399: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 12400: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 12401: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 12402: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
12403:
12404: }
12405:
1.136 brouard 12406: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
12407: {
1.126 brouard 12408:
1.136 brouard 12409: /*-------- data file ----------*/
12410: FILE *fic;
12411: char dummy[]=" ";
1.359 brouard 12412: int i = 0, j = 0, n = 0, iv = 0;/* , v;*/
1.223 brouard 12413: int lstra;
1.136 brouard 12414: int linei, month, year,iout;
1.302 brouard 12415: int noffset=0; /* This is the offset if BOM data file */
1.136 brouard 12416: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 12417: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 12418: char *stratrunc;
1.223 brouard 12419:
1.349 brouard 12420: /* DummyV=ivector(-1,NCOVMAX); /\* 1 to 3 *\/ */
12421: /* FixedV=ivector(-1,NCOVMAX); /\* 1 to 3 *\/ */
1.339 brouard 12422:
12423: ncovcolt=ncovcol+nqv+ntv+nqtv; /* total of covariates in the data, not in the model equation */
12424:
1.136 brouard 12425: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 12426: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
12427: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 12428: }
1.126 brouard 12429:
1.302 brouard 12430: /* Is it a BOM UTF-8 Windows file? */
12431: /* First data line */
12432: linei=0;
12433: while(fgets(line, MAXLINE, fic)) {
12434: noffset=0;
12435: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
12436: {
12437: noffset=noffset+3;
12438: printf("# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);fflush(stdout);
12439: fprintf(ficlog,"# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);
12440: fflush(ficlog); return 1;
12441: }
12442: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
12443: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
12444: {
12445: noffset=noffset+2;
1.304 brouard 12446: 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);
12447: 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 12448: fflush(ficlog); return 1;
12449: }
12450: else if( line[0] == 0 && line[1] == 0)
12451: {
12452: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
12453: noffset=noffset+4;
1.304 brouard 12454: 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);
12455: 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 12456: fflush(ficlog); return 1;
12457: }
12458: } else{
12459: ;/*printf(" Not a BOM file\n");*/
12460: }
12461: /* If line starts with a # it is a comment */
12462: if (line[noffset] == '#') {
12463: linei=linei+1;
12464: break;
12465: }else{
12466: break;
12467: }
12468: }
12469: fclose(fic);
12470: if((fic=fopen(datafile,"r"))==NULL) {
12471: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
12472: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
12473: }
12474: /* Not a Bom file */
12475:
1.136 brouard 12476: i=1;
12477: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
12478: linei=linei+1;
12479: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
12480: if(line[j] == '\t')
12481: line[j] = ' ';
12482: }
12483: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
12484: ;
12485: };
12486: line[j+1]=0; /* Trims blanks at end of line */
12487: if(line[0]=='#'){
12488: fprintf(ficlog,"Comment line\n%s\n",line);
12489: printf("Comment line\n%s\n",line);
12490: continue;
12491: }
12492: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 12493: strcpy(line, linetmp);
1.223 brouard 12494:
12495: /* Loops on waves */
12496: for (j=maxwav;j>=1;j--){
12497: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 12498: cutv(stra, strb, line, ' ');
12499: if(strb[0]=='.') { /* Missing value */
12500: lval=-1;
12501: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
1.341 brouard 12502: cotvar[j][ncovcol+nqv+ntv+iv][i]=-1; /* For performance reasons */
1.238 brouard 12503: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
12504: 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);
12505: 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);
12506: return 1;
12507: }
12508: }else{
12509: errno=0;
12510: /* what_kind_of_number(strb); */
12511: dval=strtod(strb,&endptr);
12512: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
12513: /* if(strb != endptr && *endptr == '\0') */
12514: /* dval=dlval; */
12515: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
12516: if( strb[0]=='\0' || (*endptr != '\0')){
12517: 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);
12518: 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);
12519: return 1;
12520: }
12521: cotqvar[j][iv][i]=dval;
1.341 brouard 12522: cotvar[j][ncovcol+nqv+ntv+iv][i]=dval; /* because cotvar starts now at first ntv */
1.238 brouard 12523: }
12524: strcpy(line,stra);
1.223 brouard 12525: }/* end loop ntqv */
1.225 brouard 12526:
1.223 brouard 12527: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 12528: cutv(stra, strb, line, ' ');
12529: if(strb[0]=='.') { /* Missing value */
12530: lval=-1;
12531: }else{
12532: errno=0;
12533: lval=strtol(strb,&endptr,10);
12534: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
12535: if( strb[0]=='\0' || (*endptr != '\0')){
12536: 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);
12537: 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);
12538: return 1;
12539: }
12540: }
12541: if(lval <-1 || lval >1){
12542: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 12543: 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 12544: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 12545: For example, for multinomial values like 1, 2 and 3,\n \
12546: build V1=0 V2=0 for the reference value (1),\n \
12547: V1=1 V2=0 for (2) \n \
1.223 brouard 12548: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 12549: output of IMaCh is often meaningless.\n \
1.319 brouard 12550: Exiting.\n",lval,linei, i,line,iv,j);
1.238 brouard 12551: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 12552: 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 12553: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 12554: For example, for multinomial values like 1, 2 and 3,\n \
12555: build V1=0 V2=0 for the reference value (1),\n \
12556: V1=1 V2=0 for (2) \n \
1.223 brouard 12557: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 12558: output of IMaCh is often meaningless.\n \
1.319 brouard 12559: Exiting.\n",lval,linei, i,line,iv,j);fflush(ficlog);
1.238 brouard 12560: return 1;
12561: }
1.341 brouard 12562: cotvar[j][ncovcol+nqv+iv][i]=(double)(lval);
1.238 brouard 12563: strcpy(line,stra);
1.223 brouard 12564: }/* end loop ntv */
1.225 brouard 12565:
1.223 brouard 12566: /* Statuses at wave */
1.137 brouard 12567: cutv(stra, strb, line, ' ');
1.223 brouard 12568: if(strb[0]=='.') { /* Missing value */
1.238 brouard 12569: lval=-1;
1.136 brouard 12570: }else{
1.238 brouard 12571: errno=0;
12572: lval=strtol(strb,&endptr,10);
12573: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
1.347 brouard 12574: if( strb[0]=='\0' || (*endptr != '\0' )){
12575: 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);
12576: 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);
12577: return 1;
12578: }else if( lval==0 || lval > nlstate+ndeath){
1.348 brouard 12579: 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);
12580: 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 12581: return 1;
12582: }
1.136 brouard 12583: }
1.225 brouard 12584:
1.136 brouard 12585: s[j][i]=lval;
1.225 brouard 12586:
1.223 brouard 12587: /* Date of Interview */
1.136 brouard 12588: strcpy(line,stra);
12589: cutv(stra, strb,line,' ');
1.169 brouard 12590: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 12591: }
1.169 brouard 12592: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 12593: month=99;
12594: year=9999;
1.136 brouard 12595: }else{
1.225 brouard 12596: 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);
12597: 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);
12598: return 1;
1.136 brouard 12599: }
12600: anint[j][i]= (double) year;
1.302 brouard 12601: mint[j][i]= (double)month;
12602: /* if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){ */
12603: /* 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]); */
12604: /* 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]); */
12605: /* } */
1.136 brouard 12606: strcpy(line,stra);
1.223 brouard 12607: } /* End loop on waves */
1.225 brouard 12608:
1.223 brouard 12609: /* Date of death */
1.136 brouard 12610: cutv(stra, strb,line,' ');
1.169 brouard 12611: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 12612: }
1.169 brouard 12613: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 12614: month=99;
12615: year=9999;
12616: }else{
1.141 brouard 12617: 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 12618: 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);
12619: return 1;
1.136 brouard 12620: }
12621: andc[i]=(double) year;
12622: moisdc[i]=(double) month;
12623: strcpy(line,stra);
12624:
1.223 brouard 12625: /* Date of birth */
1.136 brouard 12626: cutv(stra, strb,line,' ');
1.169 brouard 12627: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 12628: }
1.169 brouard 12629: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 12630: month=99;
12631: year=9999;
12632: }else{
1.141 brouard 12633: 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);
12634: 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 12635: return 1;
1.136 brouard 12636: }
12637: if (year==9999) {
1.141 brouard 12638: 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);
12639: 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 12640: return 1;
12641:
1.136 brouard 12642: }
12643: annais[i]=(double)(year);
1.302 brouard 12644: moisnais[i]=(double)(month);
12645: for (j=1;j<=maxwav;j++){
12646: if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){
12647: 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]);
12648: 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]);
12649: }
12650: }
12651:
1.136 brouard 12652: strcpy(line,stra);
1.225 brouard 12653:
1.223 brouard 12654: /* Sample weight */
1.136 brouard 12655: cutv(stra, strb,line,' ');
12656: errno=0;
12657: dval=strtod(strb,&endptr);
12658: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 12659: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
12660: 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 12661: fflush(ficlog);
12662: return 1;
12663: }
12664: weight[i]=dval;
12665: strcpy(line,stra);
1.225 brouard 12666:
1.223 brouard 12667: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
12668: cutv(stra, strb, line, ' ');
12669: if(strb[0]=='.') { /* Missing value */
1.225 brouard 12670: lval=-1;
1.311 brouard 12671: coqvar[iv][i]=NAN;
12672: covar[ncovcol+iv][i]=NAN; /* including qvar in standard covar for performance reasons */
1.223 brouard 12673: }else{
1.225 brouard 12674: errno=0;
12675: /* what_kind_of_number(strb); */
12676: dval=strtod(strb,&endptr);
12677: /* if(strb != endptr && *endptr == '\0') */
12678: /* dval=dlval; */
12679: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
12680: if( strb[0]=='\0' || (*endptr != '\0')){
12681: 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);
12682: 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);
12683: return 1;
12684: }
12685: coqvar[iv][i]=dval;
1.226 brouard 12686: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 12687: }
12688: strcpy(line,stra);
12689: }/* end loop nqv */
1.136 brouard 12690:
1.223 brouard 12691: /* Covariate values */
1.136 brouard 12692: for (j=ncovcol;j>=1;j--){
12693: cutv(stra, strb,line,' ');
1.223 brouard 12694: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 12695: lval=-1;
1.136 brouard 12696: }else{
1.225 brouard 12697: errno=0;
12698: lval=strtol(strb,&endptr,10);
12699: if( strb[0]=='\0' || (*endptr != '\0')){
12700: 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);
12701: 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);
12702: return 1;
12703: }
1.136 brouard 12704: }
12705: if(lval <-1 || lval >1){
1.225 brouard 12706: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 12707: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
12708: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 12709: For example, for multinomial values like 1, 2 and 3,\n \
12710: build V1=0 V2=0 for the reference value (1),\n \
12711: V1=1 V2=0 for (2) \n \
1.136 brouard 12712: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 12713: output of IMaCh is often meaningless.\n \
1.136 brouard 12714: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 12715: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 12716: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
12717: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 12718: For example, for multinomial values like 1, 2 and 3,\n \
12719: build V1=0 V2=0 for the reference value (1),\n \
12720: V1=1 V2=0 for (2) \n \
1.136 brouard 12721: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 12722: output of IMaCh is often meaningless.\n \
1.136 brouard 12723: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 12724: return 1;
1.136 brouard 12725: }
12726: covar[j][i]=(double)(lval);
12727: strcpy(line,stra);
12728: }
12729: lstra=strlen(stra);
1.225 brouard 12730:
1.136 brouard 12731: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
12732: stratrunc = &(stra[lstra-9]);
12733: num[i]=atol(stratrunc);
12734: }
12735: else
12736: num[i]=atol(stra);
12737: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
12738: 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;}*/
12739:
12740: i=i+1;
12741: } /* End loop reading data */
1.225 brouard 12742:
1.136 brouard 12743: *imax=i-1; /* Number of individuals */
12744: fclose(fic);
1.225 brouard 12745:
1.136 brouard 12746: return (0);
1.164 brouard 12747: /* endread: */
1.225 brouard 12748: printf("Exiting readdata: ");
12749: fclose(fic);
12750: return (1);
1.223 brouard 12751: }
1.126 brouard 12752:
1.234 brouard 12753: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 12754: char *p1 = *stri, *p2 = *stri;
1.235 brouard 12755: while (*p2 == ' ')
1.234 brouard 12756: p2++;
12757: /* while ((*p1++ = *p2++) !=0) */
12758: /* ; */
12759: /* do */
12760: /* while (*p2 == ' ') */
12761: /* p2++; */
12762: /* while (*p1++ == *p2++); */
12763: *stri=p2;
1.145 brouard 12764: }
12765:
1.330 brouard 12766: int decoderesult( char resultline[], int nres)
1.230 brouard 12767: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
12768: {
1.235 brouard 12769: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 12770: char resultsav[MAXLINE];
1.330 brouard 12771: /* int resultmodel[MAXLINE]; */
1.334 brouard 12772: /* int modelresult[MAXLINE]; */
1.230 brouard 12773: char stra[80], strb[80], strc[80], strd[80],stre[80];
12774:
1.234 brouard 12775: removefirstspace(&resultline);
1.332 brouard 12776: printf("decoderesult:%s\n",resultline);
1.230 brouard 12777:
1.332 brouard 12778: strcpy(resultsav,resultline);
1.342 brouard 12779: /* printf("Decoderesult resultsav=\"%s\" resultline=\"%s\"\n", resultsav, resultline); */
1.230 brouard 12780: if (strlen(resultsav) >1){
1.334 brouard 12781: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' in this resultline */
1.230 brouard 12782: }
1.353 brouard 12783: if(j == 0 && cptcovs== 0){ /* Resultline but no = and no covariate in the model */
1.253 brouard 12784: TKresult[nres]=0; /* Combination for the nresult and the model */
12785: return (0);
12786: }
1.234 brouard 12787: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
1.353 brouard 12788: 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);
12789: 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);
12790: if(j==0)
12791: return 1;
1.234 brouard 12792: }
1.334 brouard 12793: for(k=1; k<=j;k++){ /* Loop on any covariate of the RESULT LINE */
1.234 brouard 12794: if(nbocc(resultsav,'=') >1){
1.318 brouard 12795: 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 12796: /* 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 12797: cutl(strc,strd,strb,'='); /* strb:"V4=1" strc="1" strd="V4" */
1.332 brouard 12798: /* If a blank, then strc="V4=" and strd='\0' */
12799: if(strc[0]=='\0'){
12800: printf("Error in resultline, probably a blank after the \"%s\", \"result:%s\", stra=\"%s\" resultsav=\"%s\"\n",strb,resultline, stra, resultsav);
12801: fprintf(ficlog,"Error in resultline, probably a blank after the \"V%s=\", resultline=%s\n",strb,resultline);
12802: return 1;
12803: }
1.234 brouard 12804: }else
12805: cutl(strc,strd,resultsav,'=');
1.318 brouard 12806: Tvalsel[k]=atof(strc); /* 1 */ /* Tvalsel of k is the float value of the kth covariate appearing in this result line */
1.234 brouard 12807:
1.230 brouard 12808: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
1.318 brouard 12809: 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 12810: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
12811: /* cptcovsel++; */
12812: if (nbocc(stra,'=') >0)
12813: strcpy(resultsav,stra); /* and analyzes it */
12814: }
1.235 brouard 12815: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 12816: /* 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 12817: 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 12818: if(Typevar[k1]==0){ /* Single covariate in model */
12819: /* 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.234 brouard 12820: match=0;
1.318 brouard 12821: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
12822: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 12823: modelresult[nres][k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.318 brouard 12824: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
1.234 brouard 12825: break;
12826: }
12827: }
12828: if(match == 0){
1.338 brouard 12829: 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]);
12830: 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 12831: return 1;
1.234 brouard 12832: }
1.332 brouard 12833: }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*/
12834: /* We feed resultmodel[k1]=k2; */
12835: match=0;
12836: 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 */
12837: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 12838: 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 12839: resultmodel[nres][k1]=k2; /* Added here */
1.342 brouard 12840: /* printf("Decoderesult first modelresult[k2=%d]=%d (k1) V%d*AGE\n",k2,k1,Tvar[k1]); */
1.332 brouard 12841: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
12842: break;
12843: }
12844: }
12845: if(match == 0){
1.338 brouard 12846: 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]);
12847: 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 12848: return 1;
12849: }
1.349 brouard 12850: }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 12851: /* resultmodel[nres][of such a Vn * Vm product k1] is not unique, so can't exist, we feed Tvard[k1][1] and [2] */
12852: match=0;
1.342 brouard 12853: /* 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 12854: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
12855: if(Tvardk[k1][1]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
12856: /* modelresult[k2]=k1; */
1.342 brouard 12857: /* printf("Decoderesult first Product modelresult[k2=%d]=%d (k1) V%d * \n",k2,k1,Tvarsel[k2]); */
1.332 brouard 12858: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
12859: }
12860: }
12861: if(match == 0){
1.349 brouard 12862: 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);
12863: 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 12864: return 1;
12865: }
12866: match=0;
12867: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
12868: if(Tvardk[k1][2]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
12869: /* modelresult[k2]=k1;*/
1.342 brouard 12870: /* printf("Decoderesult second Product modelresult[k2=%d]=%d (k1) * V%d \n ",k2,k1,Tvarsel[k2]); */
1.332 brouard 12871: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
12872: break;
12873: }
12874: }
12875: if(match == 0){
1.349 brouard 12876: 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);
12877: 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 12878: return 1;
12879: }
12880: }/* End of testing */
1.333 brouard 12881: }/* End loop cptcovt */
1.235 brouard 12882: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 12883: /* Feeds resultmodel[nres][k1]=k2 for single covariate (k1) in the model equation */
1.334 brouard 12884: 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)
12885: * Loop on resultline variables: result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 12886: match=0;
1.318 brouard 12887: 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 12888: if(Typevar[k1]==0){ /* Single only */
1.349 brouard 12889: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 What if a product? */
1.330 brouard 12890: 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 12891: 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 12892: ++match;
12893: }
12894: }
12895: }
12896: if(match == 0){
1.338 brouard 12897: printf("Error in result line: variable V%d is missing in model; result: %s, model=1+age+%s\n",Tvarsel[k2], resultline, model);
12898: 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 12899: return 1;
1.234 brouard 12900: }else if(match > 1){
1.338 brouard 12901: printf("Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
12902: fprintf(ficlog,"Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
1.310 brouard 12903: return 1;
1.234 brouard 12904: }
12905: }
1.334 brouard 12906: /* cptcovres=j /\* Number of variables in the resultline is equal to cptcovs and thus useless *\/ */
1.234 brouard 12907: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 12908: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.330 brouard 12909: /* nres=1st result line: V4=1 V5=25.1 V3=0 V2=8 V1=1 */
12910: /* 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*/
12911: /* nres=2nd result line: V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.235 brouard 12912: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
12913: /* 1 0 0 0 */
12914: /* 2 1 0 0 */
12915: /* 3 0 1 0 */
1.330 brouard 12916: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 (nres=2)*/
1.235 brouard 12917: /* 5 0 0 1 */
1.330 brouard 12918: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 (nres=1)*/
1.235 brouard 12919: /* 7 0 1 1 */
12920: /* 8 1 1 1 */
1.237 brouard 12921: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
12922: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
12923: /* V5*age V5 known which value for nres? */
12924: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.334 brouard 12925: 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.
12926: * loop on position k1 in the MODEL LINE */
1.331 brouard 12927: /* k counting number of combination of single dummies in the equation model */
12928: /* k4 counting single dummies in the equation model */
12929: /* k4q counting single quantitatives in the equation model */
1.344 brouard 12930: 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 12931: /* 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 12932: /* 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 12933: /* Value in the (current nres) resultline of the variable at the k1th position in the model equation resultmodel[nres][k1]= k3 */
1.332 brouard 12934: /* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline */
12935: /* k3 is the position in the nres result line of the k1th variable of the model equation */
12936: /* Tvarsel[k3]: Name of the variable at the k3th position in the result line. */
12937: /* Tvalsel[k3]: Value of the variable at the k3th position in the result line. */
12938: /* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.334 brouard 12939: /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 12940: /* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1.330 brouard 12941: /* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.332 brouard 12942: k3= resultmodel[nres][k1]; /* From position k1 in model get position k3 in result line */
12943: /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
12944: 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 12945: 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 12946: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][Name]=Value; stores the value into the name of the variable. */
1.332 brouard 12947: /* Tinvresult[nres][4]=1 */
1.334 brouard 12948: /* Tresult[nres][k4+1]=Tvalsel[k3];/\* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) *\/ */
12949: Tresult[nres][k3]=Tvalsel[k3];/* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) */
12950: /* Tvresult[nres][k4+1]=(int)Tvarsel[k3];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
12951: Tvresult[nres][k3]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
1.237 brouard 12952: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.334 brouard 12953: precov[nres][k1]=Tvalsel[k3]; /* Value from resultline of the variable at the k1 position in the model */
1.342 brouard 12954: /* 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 12955: k4++;;
1.331 brouard 12956: }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Quantitative and single */
1.330 brouard 12957: /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.332 brouard 12958: /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.330 brouard 12959: /* Tqinvresult[nres][Name of a quantitative variable]= value of the variable in the result line */
1.332 brouard 12960: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 5 =k3q */
12961: k2q=(int)Tvarsel[k3q]; /* Name of variable at k3q th position in the resultline */
12962: /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.334 brouard 12963: /* Tqresult[nres][k4q+1]=Tvalsel[k3q]; /\* Tqresult[nres][1]=25.1 *\/ */
12964: /* Tvresult[nres][k4q+1]=(int)Tvarsel[k3q];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
12965: /* Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /\* Tvqresult[nres][1]=5 *\/ */
12966: Tqresult[nres][k3q]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
12967: Tvresult[nres][k3q]=(int)Tvarsel[k3q];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
12968: Tvqresult[nres][k3q]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
1.237 brouard 12969: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.330 brouard 12970: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.332 brouard 12971: precov[nres][k1]=Tvalsel[k3q];
1.342 brouard 12972: /* 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 12973: k4q++;;
1.350 brouard 12974: }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"*/
12975: /* Tvar[k1]; */ /* Age variable */ /* 17 age*V6*V2 ?*/
1.332 brouard 12976: /* Wrong we want the value of variable name Tvar[k1] */
1.350 brouard 12977: if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
12978: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
12979: /* 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]]); */
12980: }else{
12981: k3= resultmodel[nres][k1]; /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
12982: 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)*/
12983: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][4]=1 */
12984: precov[nres][k1]=Tvalsel[k3];
12985: }
1.342 brouard 12986: /* 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 12987: }else if( Dummy[k1]==3 ){ /* For quant with age product */
1.350 brouard 12988: if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
12989: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
12990: /* 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]]); */
12991: }else{
12992: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 25.1=k3q */
12993: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
12994: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* TinvDoQresult[nres][5]=25.1 */
12995: precov[nres][k1]=Tvalsel[k3q];
12996: }
1.342 brouard 12997: /* 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 12998: }else if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
1.332 brouard 12999: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
1.342 brouard 13000: /* 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 13001: }else{
1.332 brouard 13002: printf("Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
13003: fprintf(ficlog,"Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
1.235 brouard 13004: }
13005: }
1.234 brouard 13006:
1.334 brouard 13007: TKresult[nres]=++k; /* Number of combinations of dummies for the nresult and the model =Tvalsel[k3]*pow(2,k4) + 1*/
1.230 brouard 13008: return (0);
13009: }
1.235 brouard 13010:
1.230 brouard 13011: int decodemodel( char model[], int lastobs)
13012: /**< This routine decodes the model and returns:
1.224 brouard 13013: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
13014: * - nagesqr = 1 if age*age in the model, otherwise 0.
13015: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
13016: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
13017: * - cptcovage number of covariates with age*products =2
13018: * - cptcovs number of simple covariates
1.339 brouard 13019: * ncovcolt=ncovcol+nqv+ntv+nqtv total of covariates in the data, not in the model equation
1.224 brouard 13020: * - 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 13021: * which is a new column after the 9 (ncovcol+nqv+ntv+nqtv) variables.
1.319 brouard 13022: * - if k is a product Vn*Vm, covar[k][i] is filled with correct values for each individual
1.224 brouard 13023: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
13024: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
13025: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
13026: */
1.319 brouard 13027: /* 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 13028: {
1.359 brouard 13029: int i, j, k, ks;/* , v;*/
1.349 brouard 13030: int n,m;
13031: int j1, k1, k11, k12, k2, k3, k4;
13032: char modelsav[300];
13033: char stra[300], strb[300], strc[300], strd[300],stre[300],strf[300];
1.187 brouard 13034: char *strpt;
1.349 brouard 13035: int **existcomb;
13036:
13037: existcomb=imatrix(1,NCOVMAX,1,NCOVMAX);
13038: for(i=1;i<=NCOVMAX;i++)
13039: for(j=1;j<=NCOVMAX;j++)
13040: existcomb[i][j]=0;
13041:
1.145 brouard 13042: /*removespace(model);*/
1.136 brouard 13043: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.349 brouard 13044: j=0, j1=0, k1=0, k12=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 13045: if (strstr(model,"AGE") !=0){
1.192 brouard 13046: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
13047: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 13048: return 1;
13049: }
1.141 brouard 13050: if (strstr(model,"v") !=0){
1.338 brouard 13051: printf("Error. 'v' must be in upper case 'V' model=1+age+%s ",model);
13052: fprintf(ficlog,"Error. 'v' must be in upper case model=1+age+%s ",model);fflush(ficlog);
1.141 brouard 13053: return 1;
13054: }
1.187 brouard 13055: strcpy(modelsav,model);
13056: if ((strpt=strstr(model,"age*age")) !=0){
1.338 brouard 13057: printf(" strpt=%s, model=1+age+%s\n",strpt, model);
1.187 brouard 13058: if(strpt != model){
1.338 brouard 13059: printf("Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 13060: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 13061: corresponding column of parameters.\n",model);
1.338 brouard 13062: fprintf(ficlog,"Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 13063: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 13064: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 13065: return 1;
1.225 brouard 13066: }
1.187 brouard 13067: nagesqr=1;
13068: if (strstr(model,"+age*age") !=0)
1.234 brouard 13069: substrchaine(modelsav, model, "+age*age");
1.187 brouard 13070: else if (strstr(model,"age*age+") !=0)
1.234 brouard 13071: substrchaine(modelsav, model, "age*age+");
1.187 brouard 13072: else
1.234 brouard 13073: substrchaine(modelsav, model, "age*age");
1.187 brouard 13074: }else
13075: nagesqr=0;
1.349 brouard 13076: 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 13077: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
13078: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.351 brouard 13079: cptcovs=0; /**< Number of simple covariates V1 +V1*age +V3 +V3*V4 +age*age => V1 + V3 =4+1-3=2 Wrong */
1.187 brouard 13080: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 13081: * cst, age and age*age
13082: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
13083: /* including age products which are counted in cptcovage.
13084: * but the covariates which are products must be treated
13085: * separately: ncovn=4- 2=2 (V1+V3). */
1.349 brouard 13086: cptcovprod=0; /**< Number of products V1*V2 +v3*age = 2 */
13087: cptcovdageprod=0; /* Number of doouble products with age age*Vn*VM or Vn*age*Vm or Vn*Vm*age */
1.187 brouard 13088: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.349 brouard 13089: cptcovprodage=0;
13090: /* cptcovprodage=nboccstr(modelsav,"age");*/
1.225 brouard 13091:
1.187 brouard 13092: /* Design
13093: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
13094: * < ncovcol=8 >
13095: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
13096: * k= 1 2 3 4 5 6 7 8
13097: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
1.345 brouard 13098: * covar[k,i], are for fixed covariates, value of kth covariate if not including age for individual i:
1.224 brouard 13099: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
13100: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 13101: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
13102: * Tage[++cptcovage]=k
1.345 brouard 13103: * if products, new covar are created after ncovcol + nqv (quanti fixed) with k1
1.187 brouard 13104: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
13105: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
13106: * 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
13107: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
13108: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
13109: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
1.345 brouard 13110: * < ncovcol=8 8 fixed covariate. Additional starts at 9 (V5*V6) and 10(V7*V8) >
1.187 brouard 13111: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
13112: * k= 1 2 3 4 5 6 7 8 9 10 11 12
1.345 brouard 13113: * Tvard[k]= 2 1 3 3 10 11 8 8 5 6 7 8
13114: * p Tvar[1]@12={2, 1, 3, 3, 9, 10, 8, 8}
1.187 brouard 13115: * p Tprod[1]@2={ 6, 5}
13116: *p Tvard[1][1]@4= {7, 8, 5, 6}
13117: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
13118: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
1.319 brouard 13119: *How to reorganize? Tvars(orted)
1.187 brouard 13120: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
13121: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
13122: * {2, 1, 4, 8, 5, 6, 3, 7}
13123: * Struct []
13124: */
1.225 brouard 13125:
1.187 brouard 13126: /* This loop fills the array Tvar from the string 'model'.*/
13127: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
13128: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
13129: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
13130: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
13131: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
13132: /* k=1 Tvar[1]=2 (from V2) */
13133: /* k=5 Tvar[5] */
13134: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 13135: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 13136: /* } */
1.198 brouard 13137: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 13138: /*
13139: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 13140: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
13141: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
13142: }
1.187 brouard 13143: cptcovage=0;
1.351 brouard 13144:
13145: /* First loop in order to calculate */
13146: /* for age*VN*Vm
13147: * Provides, Typevar[k], Tage[cptcovage], existcomb[n][m], FixedV[ncovcolt+k12]
13148: * Tprod[k1]=k Tposprod[k]=k1; Tvard[k1][1] =m;
13149: */
13150: /* Needs FixedV[Tvardk[k][1]] */
13151: /* For others:
13152: * Sets Typevar[k];
13153: * Tvar[k]=ncovcol+nqv+ntv+nqtv+k11;
13154: * Tposprod[k]=k11;
13155: * Tprod[k11]=k;
13156: * Tvardk[k][1] =m;
13157: * Needs FixedV[Tvardk[k][1]] == 0
13158: */
13159:
1.319 brouard 13160: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model line */
13161: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+' cutl from left to right
13162: 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" */
13163: if (nbocc(modelsav,'+')==0)
13164: strcpy(strb,modelsav); /* and analyzes it */
1.234 brouard 13165: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
13166: /*scanf("%d",i);*/
1.349 brouard 13167: 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 */
13168: 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 */
13169: 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 */
13170: Typevar[k]=3; /* 3 for age and double product age*Vn*Vm varying of fixed */
13171: if(strstr(strc,"age")!=0) { /* It means that strc=V2*age or age*V2 and thus that strd=Vn */
13172: cutl(stre,strf,strc,'*') ; /* strf=age or Vm, stre=Vm or age. If strc=V6*V2 then strf=V6 and stre=V2 */
13173: strcpy(strc,strb); /* save strb(=age*Vn*Vm) into strc */
13174: /* We want strb=Vn*Vm */
13175: if(strcmp(strf,"age")==0){ /* strf is "age" so that stre=Vm =V2 . */
13176: strcpy(strb,strd);
13177: strcat(strb,"*");
13178: strcat(strb,stre);
13179: }else{ /* strf=Vm If strf=V6 then stre=V2 */
13180: strcpy(strb,strf);
13181: strcat(strb,"*");
13182: strcat(strb,stre);
13183: strcpy(strd,strb); /* in order for strd to not be "age" for next test (will be Vn*Vm */
13184: }
1.351 brouard 13185: /* 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]]]); */
13186: /* FixedV[Tvar[Tage[k]]]=0; /\* HERY not sure if V7*V4*age Fixed might not exist yet*\/ */
1.349 brouard 13187: }else{ /* strc=Vn*Vm (and strd=age) and should be strb=Vn*Vm but want to keep original strb double product */
13188: strcpy(stre,strb); /* save full b in stre */
13189: strcpy(strb,strc); /* save short c in new short b for next block strb=Vn*Vm*/
13190: strcpy(strf,strc); /* save short c in new short f */
13191: cutl(strc,strd,strf,'*'); /* We get strd=Vn and strc=Vm for next block (strb=Vn*Vm)*/
13192: /* strcpy(strc,stre);*/ /* save full e in c for future */
13193: }
13194: cptcovdageprod++; /* double product with age Which product is it? */
13195: /* 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 *\/ */
13196: /* cutl(strc,strd,strb,'*'); /\* strd= V6 or V2 or age and strc= V2 or age or V2 *\/ */
1.234 brouard 13197: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
1.349 brouard 13198: n=atoi(stre);
1.234 brouard 13199: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
1.349 brouard 13200: m=atoi(strc);
13201: cptcovage++; /* Counts the number of covariates which include age as a product */
13202: Tage[cptcovage]=k; /* For age*V3*V2 gives the position in model of covariates associated with age Tage[1]=6 HERY too*/
13203: if(existcomb[n][m] == 0){
13204: /* r /home/brouard/Documents/Recherches/REVES/Zachary/Zach-2022/Feinuo_Sun/Feinuo-threeway/femV12V15_3wayintNBe.imach */
13205: 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);
13206: 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);
13207: fflush(ficlog);
13208: k1++; /* The combination Vn*Vm will be in the model so we create it at k1 */
13209: k12++;
13210: existcomb[n][m]=k1;
13211: existcomb[m][n]=k1;
13212: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1;
13213: 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*/
13214: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 Gives the k1 double product Vn*Vm or age*Vn*Vm at the k position */
13215: Tvard[k1][1] =m; /* m 1 for V1*/
13216: Tvardk[k][1] =m; /* m 1 for V1*/
13217: Tvard[k1][2] =n; /* n 4 for V4*/
13218: Tvardk[k][2] =n; /* n 4 for V4*/
1.351 brouard 13219: /* Tvar[Tage[cptcovage]]=k1;*/ /* Tvar[6=age*V3*V2]=9 (new fixed covariate) */ /* We don't know about Fixed yet HERE */
1.349 brouard 13220: 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 */
13221: for (i=1; i<=lastobs;i++){/* For fixed product */
13222: /* Computes the new covariate which is a product of
13223: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
13224: covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
13225: }
13226: cptcovprodage++; /* Counting the number of fixed covariate with age */
13227: FixedV[ncovcolt+k12]=0; /* We expand Vn*Vm */
13228: k12++;
13229: FixedV[ncovcolt+k12]=0;
13230: }else{ /*End of FixedV */
13231: cptcovprodvage++; /* Counting the number of varying covariate with age */
13232: FixedV[ncovcolt+k12]=1; /* We expand Vn*Vm */
13233: k12++;
13234: FixedV[ncovcolt+k12]=1;
13235: }
13236: }else{ /* k1 Vn*Vm already exists */
13237: k11=existcomb[n][m];
13238: Tposprod[k]=k11; /* OK */
13239: Tvar[k]=Tvar[Tprod[k11]]; /* HERY */
13240: Tvardk[k][1]=m;
13241: Tvardk[k][2]=n;
13242: 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 */
13243: /*cptcovage++;*/ /* Counts the number of covariates which include age as a product */
13244: cptcovprodage++; /* Counting the number of fixed covariate with age */
13245: /*Tage[cptcovage]=k;*/ /* For age*V3*V2 Tage[1]=V3*V3=9 HERY too*/
13246: Tvar[Tage[cptcovage]]=k1;
13247: FixedV[ncovcolt+k12]=0; /* We expand Vn*Vm */
13248: k12++;
13249: FixedV[ncovcolt+k12]=0;
13250: }else{ /* Already exists but time varying (and age) */
13251: /*cptcovage++;*/ /* Counts the number of covariates which include age as a product */
13252: /*Tage[cptcovage]=k;*/ /* For age*V3*V2 Tage[1]=V3*V3=9 HERY too*/
13253: /* Tvar[Tage[cptcovage]]=k1; */
13254: cptcovprodvage++;
13255: FixedV[ncovcolt+k12]=1; /* We expand Vn*Vm */
13256: k12++;
13257: FixedV[ncovcolt+k12]=1;
13258: }
13259: }
13260: /* Tage[cptcovage]=k; /\* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
13261: /* Tvar[k]=k11; /\* HERY *\/ */
13262: } 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 */
13263: cptcovprod++;
13264: if (strcmp(strc,"age")==0) { /**< Model includes age: strb= Vn*age c=age d=Vn*/
13265: /* covar is not filled and then is empty */
13266: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
13267: 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 */
13268: Typevar[k]=1; /* 1 for age product */
13269: cptcovage++; /* Counts the number of covariates which include age as a product */
13270: Tage[cptcovage]=k; /* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
13271: if( FixedV[Tvar[k]] == 0){
13272: cptcovprodage++; /* Counting the number of fixed covariate with age */
13273: }else{
13274: cptcovprodvage++; /* Counting the number of fixedvarying covariate with age */
13275: }
13276: /*printf("stre=%s ", stre);*/
13277: } else if (strcmp(strd,"age")==0) { /* strb= age*Vn c=Vn */
13278: cutl(stre,strb,strc,'V');
13279: Tvar[k]=atoi(stre);
13280: Typevar[k]=1; /* 1 for age product */
13281: cptcovage++;
13282: Tage[cptcovage]=k;
13283: if( FixedV[Tvar[k]] == 0){
13284: cptcovprodage++; /* Counting the number of fixed covariate with age */
13285: }else{
13286: cptcovprodvage++; /* Counting the number of fixedvarying covariate with age */
1.339 brouard 13287: }
1.349 brouard 13288: }else{ /* for product Vn*Vm */
13289: Typevar[k]=2; /* 2 for product Vn*Vm */
13290: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
13291: n=atoi(stre);
13292: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
13293: m=atoi(strc);
13294: k1++;
13295: cptcovprodnoage++;
13296: if(existcomb[n][m] != 0 || existcomb[m][n] != 0){
13297: printf("Warning in model combination V%d*V%d already exists in the model in position k1=%d!\n",n,m,existcomb[n][m]);
13298: 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]);
13299: fflush(ficlog);
13300: k11=existcomb[n][m];
13301: Tvar[k]=ncovcol+nqv+ntv+nqtv+k11;
13302: Tposprod[k]=k11;
13303: Tprod[k11]=k;
13304: Tvardk[k][1] =m; /* m 1 for V1*/
13305: /* Tvard[k11][1] =m; /\* n 4 for V4*\/ */
13306: Tvardk[k][2] =n; /* n 4 for V4*/
13307: /* Tvard[k11][2] =n; /\* n 4 for V4*\/ */
13308: }else{ /* combination Vn*Vm doesn't exist we create it (no age)*/
13309: existcomb[n][m]=k1;
13310: existcomb[m][n]=k1;
13311: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* ncovcolt+k1; For model-covariate k tells which data-covariate to use but
13312: because this model-covariate is a construction we invent a new column
13313: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
13314: If already ncovcol=4 and model= V2 + V1 + V1*V4 + age*V3 + V3*V2
13315: thus after V4 we invent V5 and V6 because age*V3 will be computed in 4
13316: Tvar[3=V1*V4]=4+1=5 Tvar[5=V3*V2]=4 + 2= 6, Tvar[4=age*V3]=3 etc */
13317: /* Please remark that the new variables are model dependent */
13318: /* If we have 4 variable but the model uses only 3, like in
13319: * model= V1 + age*V1 + V2 + V3 + age*V2 + age*V3 + V1*V2 + V1*V3
13320: * k= 1 2 3 4 5 6 7 8
13321: * Tvar[k]=1 1 2 3 2 3 (5 6) (and not 4 5 because of V4 missing)
13322: * Tage[kk] [1]= 2 [2]=5 [3]=6 kk=1 to cptcovage=3
13323: * Tvar[Tage[kk]][1]=2 [2]=2 [3]=3
13324: */
13325: /* We need to feed some variables like TvarVV, but later on next loop because of ncovv (k2) is not correct */
13326: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 +V6*V2*age */
13327: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 */
13328: Tvard[k1][1] =m; /* m 1 for V1*/
13329: Tvardk[k][1] =m; /* m 1 for V1*/
13330: Tvard[k1][2] =n; /* n 4 for V4*/
13331: Tvardk[k][2] =n; /* n 4 for V4*/
13332: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
13333: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
13334: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
13335: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
13336: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
13337: 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 */
13338: for (i=1; i<=lastobs;i++){/* For fixed product */
13339: /* Computes the new covariate which is a product of
13340: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
13341: covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
13342: }
13343: /* TvarVV[k2]=n; */
13344: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
13345: /* TvarVV[k2+1]=m; */
13346: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
13347: }else{ /* not FixedV */
13348: /* TvarVV[k2]=n; */
13349: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
13350: /* TvarVV[k2+1]=m; */
13351: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
13352: }
13353: } /* End of creation of Vn*Vm if not created by age*Vn*Vm earlier */
13354: } /* End of product Vn*Vm */
13355: } /* End of age*double product or simple product */
13356: }else { /* not a product */
1.234 brouard 13357: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
13358: /* scanf("%d",i);*/
13359: cutl(strd,strc,strb,'V');
13360: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
13361: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
13362: Tvar[k]=atoi(strd);
13363: Typevar[k]=0; /* 0 for simple covariates */
13364: }
13365: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 13366: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 13367: scanf("%d",i);*/
1.187 brouard 13368: } /* end of loop + on total covariates */
1.351 brouard 13369:
13370:
1.187 brouard 13371: } /* end if strlen(modelsave == 0) age*age might exist */
13372: } /* end if strlen(model == 0) */
1.349 brouard 13373: 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 */
13374:
1.136 brouard 13375: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
13376: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 13377:
1.136 brouard 13378: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 13379: printf("cptcovprod=%d ", cptcovprod);
13380: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
13381: scanf("%d ",i);*/
13382:
13383:
1.230 brouard 13384: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
13385: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 13386: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
13387: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
13388: k = 1 2 3 4 5 6 7 8 9
13389: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
1.319 brouard 13390: Typevar[k]= 0 0 0 2 1 0 2 1 0
1.227 brouard 13391: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
13392: Dummy[k] 1 0 0 0 3 1 1 2 3
13393: Tmodelind[combination of covar]=k;
1.225 brouard 13394: */
13395: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 13396: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 13397: /* 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 13398: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.318 brouard 13399: printf("Model=1+age+%s\n\
1.349 brouard 13400: 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 13401: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
13402: 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 13403: fprintf(ficlog,"Model=1+age+%s\n\
1.349 brouard 13404: 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 13405: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
13406: 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 13407: for(k=-1;k<=NCOVMAX; k++){ Fixed[k]=0; Dummy[k]=0;}
13408: for(k=1;k<=NCOVMAX; k++){TvarFind[k]=0; TvarVind[k]=0;}
1.351 brouard 13409:
13410:
13411: /* Second loop for calculating Fixed[k], Dummy[k]*/
13412:
13413:
1.349 brouard 13414: 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 13415: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 13416: Fixed[k]= 0;
13417: Dummy[k]= 0;
1.225 brouard 13418: ncoveff++;
1.232 brouard 13419: ncovf++;
1.234 brouard 13420: nsd++;
13421: modell[k].maintype= FTYPE;
13422: TvarsD[nsd]=Tvar[k];
13423: TvarsDind[nsd]=k;
1.330 brouard 13424: TnsdVar[Tvar[k]]=nsd;
1.234 brouard 13425: TvarF[ncovf]=Tvar[k];
13426: TvarFind[ncovf]=k;
13427: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
13428: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.339 brouard 13429: /* }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 13430: }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 13431: Fixed[k]= 0;
13432: Dummy[k]= 1;
1.230 brouard 13433: nqfveff++;
1.234 brouard 13434: modell[k].maintype= FTYPE;
13435: modell[k].subtype= FQ;
13436: nsq++;
1.334 brouard 13437: TvarsQ[nsq]=Tvar[k]; /* Gives the variable name (extended to products) of first nsq simple quantitative covariates (fixed or time vary see below */
13438: TvarsQind[nsq]=k; /* Gives the position in the model equation of the first nsq simple quantitative covariates (fixed or time vary) */
1.232 brouard 13439: ncovf++;
1.234 brouard 13440: TvarF[ncovf]=Tvar[k];
13441: TvarFind[ncovf]=k;
1.231 brouard 13442: 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 13443: 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 13444: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.339 brouard 13445: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
13446: /* model V1+V3+age*V1+age*V3+V1*V3 */
13447: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
13448: ncovvt++;
13449: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
13450: TvarVVind[ncovvt]=k; /* TvarVVind[1]=2 (second position in the model equation */
13451:
1.227 brouard 13452: Fixed[k]= 1;
13453: Dummy[k]= 0;
1.225 brouard 13454: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 13455: modell[k].maintype= VTYPE;
13456: modell[k].subtype= VD;
13457: nsd++;
13458: TvarsD[nsd]=Tvar[k];
13459: TvarsDind[nsd]=k;
1.330 brouard 13460: TnsdVar[Tvar[k]]=nsd; /* To be verified */
1.234 brouard 13461: ncovv++; /* Only simple time varying variables */
13462: TvarV[ncovv]=Tvar[k];
1.242 brouard 13463: 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 13464: 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 */
13465: 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 13466: 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);
13467: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 13468: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.339 brouard 13469: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
13470: /* model V1+V3+age*V1+age*V3+V1*V3 */
13471: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
13472: ncovvt++;
13473: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
13474: TvarVVind[ncovvt]=k; /* TvarVV[1]=V3 (first time varying in the model equation */
13475:
1.234 brouard 13476: Fixed[k]= 1;
13477: Dummy[k]= 1;
13478: nqtveff++;
13479: modell[k].maintype= VTYPE;
13480: modell[k].subtype= VQ;
13481: ncovv++; /* Only simple time varying variables */
13482: nsq++;
1.334 brouard 13483: 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) */
13484: 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 13485: TvarV[ncovv]=Tvar[k];
1.242 brouard 13486: 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 13487: 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 */
13488: 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 13489: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
13490: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
1.349 brouard 13491: /* 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 13492: /* printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv); */
1.227 brouard 13493: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 13494: ncova++;
13495: TvarA[ncova]=Tvar[k];
13496: TvarAind[ncova]=k;
1.349 brouard 13497: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
13498: /** 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 13499: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 13500: Fixed[k]= 2;
13501: Dummy[k]= 2;
13502: modell[k].maintype= ATYPE;
13503: modell[k].subtype= APFD;
1.349 brouard 13504: ncovta++;
13505: TvarAVVA[ncovta]=Tvar[k]; /* (2)age*V3 */
13506: TvarAVVAind[ncovta]=k;
1.240 brouard 13507: /* ncoveff++; */
1.227 brouard 13508: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 13509: Fixed[k]= 2;
13510: Dummy[k]= 3;
13511: modell[k].maintype= ATYPE;
13512: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
1.349 brouard 13513: ncovta++;
13514: TvarAVVA[ncovta]=Tvar[k]; /* */
13515: TvarAVVAind[ncovta]=k;
1.240 brouard 13516: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 13517: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 13518: Fixed[k]= 3;
13519: Dummy[k]= 2;
13520: modell[k].maintype= ATYPE;
13521: modell[k].subtype= APVD; /* Product age * varying dummy */
1.349 brouard 13522: ncovva++;
13523: TvarVVA[ncovva]=Tvar[k]; /* (1)+age*V6 + (2)age*V7 */
13524: TvarVVAind[ncovva]=k;
13525: ncovta++;
13526: TvarAVVA[ncovta]=Tvar[k]; /* */
13527: TvarAVVAind[ncovta]=k;
1.240 brouard 13528: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 13529: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 13530: Fixed[k]= 3;
13531: Dummy[k]= 3;
13532: modell[k].maintype= ATYPE;
13533: modell[k].subtype= APVQ; /* Product age * varying quantitative */
1.349 brouard 13534: ncovva++;
13535: TvarVVA[ncovva]=Tvar[k]; /* */
13536: TvarVVAind[ncovva]=k;
13537: ncovta++;
13538: TvarAVVA[ncovta]=Tvar[k]; /* (1)+age*V6 + (2)age*V7 */
13539: TvarAVVAind[ncovta]=k;
1.240 brouard 13540: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 13541: }
1.349 brouard 13542: }else if( Tposprod[k]>0 && Typevar[k]==2){ /* Detects if fixed product no age Vm*Vn */
13543: printf("MEMORY ERRORR k=%d Tposprod[k]=%d, Typevar[k]=%d\n ",k, Tposprod[k], Typevar[k]);
13544: 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 */
13545: 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]]);
13546: Fixed[k]= 0;
13547: Dummy[k]= 0;
13548: ncoveff++;
13549: ncovf++;
13550: /* ncovv++; */
13551: /* TvarVV[ncovv]=Tvardk[k][1]; */
13552: /* FixedV[ncovcolt+ncovv]=0; /\* or FixedV[TvarVV[ncovv]]=0 HERE *\/ */
13553: /* ncovv++; */
13554: /* TvarVV[ncovv]=Tvardk[k][2]; */
13555: /* FixedV[ncovcolt+ncovv]=0; /\* or FixedV[TvarVV[ncovv]]=0 HERE *\/ */
13556: modell[k].maintype= FTYPE;
13557: TvarF[ncovf]=Tvar[k];
13558: /* TnsdVar[Tvar[k]]=nsd; */ /* To be done */
13559: TvarFind[ncovf]=k;
13560: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
13561: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
13562: }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 */
13563: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
13564: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age*/
13565: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
13566: 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 */
13567: ncovvt++;
13568: TvarVV[ncovvt]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */
13569: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
13570: ncovvt++;
13571: TvarVV[ncovvt]=Tvard[k1][2]; /* TvarVV[3]=V3 */
13572: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
13573:
13574: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
13575: /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
13576:
13577: if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */
13578: if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */
13579: Fixed[k]= 1;
13580: Dummy[k]= 0;
13581: modell[k].maintype= FTYPE;
13582: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
13583: ncovf++; /* Fixed variables without age */
13584: TvarF[ncovf]=Tvar[k];
13585: TvarFind[ncovf]=k;
13586: }else if(Tvard[k1][2] <=ncovcol+nqv){ /* Vm is quanti fixed */
13587: Fixed[k]= 0; /* Fixed product */
13588: Dummy[k]= 1;
13589: modell[k].maintype= FTYPE;
13590: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
13591: ncovf++; /* Varying variables without age */
13592: TvarF[ncovf]=Tvar[k];
13593: TvarFind[ncovf]=k;
13594: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is a time varying dummy covariate */
13595: Fixed[k]= 1;
13596: Dummy[k]= 0;
13597: modell[k].maintype= VTYPE;
13598: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
13599: ncovv++; /* Varying variables without age */
13600: TvarV[ncovv]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */
13601: TvarVind[ncovv]=k;/* TvarVind[1]=5 */
13602: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */
13603: Fixed[k]= 1;
13604: Dummy[k]= 1;
13605: modell[k].maintype= VTYPE;
13606: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
13607: ncovv++; /* Varying variables without age */
13608: TvarV[ncovv]=Tvar[k];
13609: TvarVind[ncovv]=k;
13610: }
13611: }else if(Tvard[k1][1] <=ncovcol+nqv){ /* Vn is fixed quanti */
13612: if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */
13613: Fixed[k]= 0; /* Fixed product */
13614: Dummy[k]= 1;
13615: modell[k].maintype= FTYPE;
13616: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
13617: ncovf++; /* Fixed variables without age */
13618: TvarF[ncovf]=Tvar[k];
13619: TvarFind[ncovf]=k;
13620: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is time varying */
13621: Fixed[k]= 1;
13622: Dummy[k]= 1;
13623: modell[k].maintype= VTYPE;
13624: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
13625: ncovv++; /* Varying variables without age */
13626: TvarV[ncovv]=Tvar[k];
13627: TvarVind[ncovv]=k;
13628: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is time varying quanti */
13629: Fixed[k]= 1;
13630: Dummy[k]= 1;
13631: modell[k].maintype= VTYPE;
13632: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
13633: ncovv++; /* Varying variables without age */
13634: TvarV[ncovv]=Tvar[k];
13635: TvarVind[ncovv]=k;
13636: ncovv++; /* Varying variables without age */
13637: TvarV[ncovv]=Tvar[k];
13638: TvarVind[ncovv]=k;
13639: }
13640: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ /* Vn is time varying dummy */
13641: if(Tvard[k1][2] <=ncovcol){
13642: Fixed[k]= 1;
13643: Dummy[k]= 1;
13644: modell[k].maintype= VTYPE;
13645: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
13646: ncovv++; /* Varying variables without age */
13647: TvarV[ncovv]=Tvar[k];
13648: TvarVind[ncovv]=k;
13649: }else if(Tvard[k1][2] <=ncovcol+nqv){
13650: Fixed[k]= 1;
13651: Dummy[k]= 1;
13652: modell[k].maintype= VTYPE;
13653: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
13654: ncovv++; /* Varying variables without age */
13655: TvarV[ncovv]=Tvar[k];
13656: TvarVind[ncovv]=k;
13657: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
13658: Fixed[k]= 1;
13659: Dummy[k]= 0;
13660: modell[k].maintype= VTYPE;
13661: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
13662: ncovv++; /* Varying variables without age */
13663: TvarV[ncovv]=Tvar[k];
13664: TvarVind[ncovv]=k;
13665: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
13666: Fixed[k]= 1;
13667: Dummy[k]= 1;
13668: modell[k].maintype= VTYPE;
13669: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
13670: ncovv++; /* Varying variables without age */
13671: TvarV[ncovv]=Tvar[k];
13672: TvarVind[ncovv]=k;
13673: }
13674: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ /* Vn is time varying quanti */
13675: if(Tvard[k1][2] <=ncovcol){
13676: Fixed[k]= 1;
13677: Dummy[k]= 1;
13678: modell[k].maintype= VTYPE;
13679: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
13680: ncovv++; /* Varying variables without age */
13681: TvarV[ncovv]=Tvar[k];
13682: TvarVind[ncovv]=k;
13683: }else if(Tvard[k1][2] <=ncovcol+nqv){
13684: Fixed[k]= 1;
13685: Dummy[k]= 1;
13686: modell[k].maintype= VTYPE;
13687: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
13688: ncovv++; /* Varying variables without age */
13689: TvarV[ncovv]=Tvar[k];
13690: TvarVind[ncovv]=k;
13691: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
13692: Fixed[k]= 1;
13693: Dummy[k]= 1;
13694: modell[k].maintype= VTYPE;
13695: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
13696: ncovv++; /* Varying variables without age */
13697: TvarV[ncovv]=Tvar[k];
13698: TvarVind[ncovv]=k;
13699: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
13700: Fixed[k]= 1;
13701: Dummy[k]= 1;
13702: modell[k].maintype= VTYPE;
13703: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
13704: ncovv++; /* Varying variables without age */
13705: TvarV[ncovv]=Tvar[k];
13706: TvarVind[ncovv]=k;
13707: }
13708: }else{
13709: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
13710: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
13711: } /*end k1*/
13712: }
13713: }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 13714: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
1.349 brouard 13715: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age*/
13716: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
13717: 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 */
13718: ncova++;
13719: TvarA[ncova]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */
13720: TvarAind[ncova]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
13721: ncova++;
13722: TvarA[ncova]=Tvard[k1][2]; /* TvarVV[3]=V3 */
13723: TvarAind[ncova]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
1.339 brouard 13724:
1.349 brouard 13725: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
13726: /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
13727: if( FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){
13728: ncovta++;
13729: TvarAVVA[ncovta]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
13730: TvarAVVAind[ncovta]=k;
13731: ncovta++;
13732: TvarAVVA[ncovta]=Tvard[k1][2]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
13733: TvarAVVAind[ncovta]=k;
13734: }else{
13735: ncovva++; /* HERY reached */
13736: TvarVVA[ncovva]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
13737: TvarVVAind[ncovva]=k;
13738: ncovva++;
13739: TvarVVA[ncovva]=Tvard[k1][2]; /* */
13740: TvarVVAind[ncovva]=k;
13741: ncovta++;
13742: TvarAVVA[ncovta]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
13743: TvarAVVAind[ncovta]=k;
13744: ncovta++;
13745: TvarAVVA[ncovta]=Tvard[k1][2]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
13746: TvarAVVAind[ncovta]=k;
13747: }
1.339 brouard 13748: if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */
13749: if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */
1.349 brouard 13750: Fixed[k]= 2;
13751: Dummy[k]= 2;
1.240 brouard 13752: modell[k].maintype= FTYPE;
13753: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
1.349 brouard 13754: /* TvarF[ncova]=Tvar[k]; /\* Problem to solve *\/ */
13755: /* TvarFind[ncova]=k; */
1.339 brouard 13756: }else if(Tvard[k1][2] <=ncovcol+nqv){ /* Vm is quanti fixed */
1.349 brouard 13757: Fixed[k]= 2; /* Fixed product */
13758: Dummy[k]= 3;
1.240 brouard 13759: modell[k].maintype= FTYPE;
13760: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
1.349 brouard 13761: /* TvarF[ncova]=Tvar[k]; */
13762: /* TvarFind[ncova]=k; */
1.339 brouard 13763: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is a time varying dummy covariate */
1.349 brouard 13764: Fixed[k]= 3;
13765: Dummy[k]= 2;
1.240 brouard 13766: modell[k].maintype= VTYPE;
13767: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
1.349 brouard 13768: TvarV[ncova]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */
13769: TvarVind[ncova]=k;/* TvarVind[1]=5 */
1.339 brouard 13770: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */
1.349 brouard 13771: Fixed[k]= 3;
13772: Dummy[k]= 3;
1.240 brouard 13773: modell[k].maintype= VTYPE;
13774: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
1.349 brouard 13775: /* ncovv++; /\* Varying variables without age *\/ */
13776: /* TvarV[ncovv]=Tvar[k]; */
13777: /* TvarVind[ncovv]=k; */
1.240 brouard 13778: }
1.339 brouard 13779: }else if(Tvard[k1][1] <=ncovcol+nqv){ /* Vn is fixed quanti */
13780: if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */
1.349 brouard 13781: Fixed[k]= 2; /* Fixed product */
13782: Dummy[k]= 2;
1.240 brouard 13783: modell[k].maintype= FTYPE;
13784: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
1.349 brouard 13785: /* ncova++; /\* Fixed variables with age *\/ */
13786: /* TvarF[ncovf]=Tvar[k]; */
13787: /* TvarFind[ncovf]=k; */
1.339 brouard 13788: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is time varying */
1.349 brouard 13789: Fixed[k]= 2;
13790: Dummy[k]= 3;
1.240 brouard 13791: modell[k].maintype= VTYPE;
13792: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
1.349 brouard 13793: /* ncova++; /\* Varying variables with age *\/ */
13794: /* TvarV[ncova]=Tvar[k]; */
13795: /* TvarVind[ncova]=k; */
1.339 brouard 13796: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is time varying quanti */
1.349 brouard 13797: Fixed[k]= 3;
13798: Dummy[k]= 2;
1.240 brouard 13799: modell[k].maintype= VTYPE;
13800: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
1.349 brouard 13801: ncova++; /* Varying variables without age */
13802: TvarV[ncova]=Tvar[k];
13803: TvarVind[ncova]=k;
13804: /* ncova++; /\* Varying variables without age *\/ */
13805: /* TvarV[ncova]=Tvar[k]; */
13806: /* TvarVind[ncova]=k; */
1.240 brouard 13807: }
1.339 brouard 13808: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ /* Vn is time varying dummy */
1.240 brouard 13809: if(Tvard[k1][2] <=ncovcol){
1.349 brouard 13810: Fixed[k]= 2;
13811: Dummy[k]= 2;
1.240 brouard 13812: modell[k].maintype= VTYPE;
13813: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
1.349 brouard 13814: /* ncova++; /\* Varying variables with age *\/ */
13815: /* TvarV[ncova]=Tvar[k]; */
13816: /* TvarVind[ncova]=k; */
1.240 brouard 13817: }else if(Tvard[k1][2] <=ncovcol+nqv){
1.349 brouard 13818: Fixed[k]= 2;
13819: Dummy[k]= 3;
1.240 brouard 13820: modell[k].maintype= VTYPE;
13821: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
1.349 brouard 13822: /* ncova++; /\* Varying variables with age *\/ */
13823: /* TvarV[ncova]=Tvar[k]; */
13824: /* TvarVind[ncova]=k; */
1.240 brouard 13825: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
1.349 brouard 13826: Fixed[k]= 3;
13827: Dummy[k]= 2;
1.240 brouard 13828: modell[k].maintype= VTYPE;
13829: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
1.349 brouard 13830: /* ncova++; /\* Varying variables with age *\/ */
13831: /* TvarV[ncova]=Tvar[k]; */
13832: /* TvarVind[ncova]=k; */
1.240 brouard 13833: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
1.349 brouard 13834: Fixed[k]= 3;
13835: Dummy[k]= 3;
1.240 brouard 13836: modell[k].maintype= VTYPE;
13837: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
1.349 brouard 13838: /* ncova++; /\* Varying variables with age *\/ */
13839: /* TvarV[ncova]=Tvar[k]; */
13840: /* TvarVind[ncova]=k; */
1.240 brouard 13841: }
1.339 brouard 13842: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ /* Vn is time varying quanti */
1.240 brouard 13843: if(Tvard[k1][2] <=ncovcol){
1.349 brouard 13844: Fixed[k]= 2;
13845: Dummy[k]= 2;
1.240 brouard 13846: modell[k].maintype= VTYPE;
13847: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
1.349 brouard 13848: /* ncova++; /\* Varying variables with age *\/ */
13849: /* TvarV[ncova]=Tvar[k]; */
13850: /* TvarVind[ncova]=k; */
1.240 brouard 13851: }else if(Tvard[k1][2] <=ncovcol+nqv){
1.349 brouard 13852: Fixed[k]= 2;
13853: Dummy[k]= 3;
1.240 brouard 13854: modell[k].maintype= VTYPE;
13855: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
1.349 brouard 13856: /* ncova++; /\* Varying variables with age *\/ */
13857: /* TvarV[ncova]=Tvar[k]; */
13858: /* TvarVind[ncova]=k; */
1.240 brouard 13859: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
1.349 brouard 13860: Fixed[k]= 3;
13861: Dummy[k]= 2;
1.240 brouard 13862: modell[k].maintype= VTYPE;
13863: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
1.349 brouard 13864: /* ncova++; /\* Varying variables with age *\/ */
13865: /* TvarV[ncova]=Tvar[k]; */
13866: /* TvarVind[ncova]=k; */
1.240 brouard 13867: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
1.349 brouard 13868: Fixed[k]= 3;
13869: Dummy[k]= 3;
1.240 brouard 13870: modell[k].maintype= VTYPE;
13871: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
1.349 brouard 13872: /* ncova++; /\* Varying variables with age *\/ */
13873: /* TvarV[ncova]=Tvar[k]; */
13874: /* TvarVind[ncova]=k; */
1.240 brouard 13875: }
1.227 brouard 13876: }else{
1.240 brouard 13877: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
13878: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
13879: } /*end k1*/
1.349 brouard 13880: } else{
1.226 brouard 13881: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
13882: 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 13883: }
1.342 brouard 13884: /* 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]); */
13885: /* printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype); */
1.227 brouard 13886: 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]);
13887: }
1.349 brouard 13888: ncovvta=ncovva;
1.227 brouard 13889: /* Searching for doublons in the model */
13890: for(k1=1; k1<= cptcovt;k1++){
13891: for(k2=1; k2 <k1;k2++){
1.285 brouard 13892: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
13893: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 13894: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
13895: if(Tvar[k1]==Tvar[k2]){
1.338 brouard 13896: 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]);
13897: 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 13898: return(1);
13899: }
13900: }else if (Typevar[k1] ==2){
13901: k3=Tposprod[k1];
13902: k4=Tposprod[k2];
13903: 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 13904: 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]]);
13905: 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 13906: return(1);
13907: }
13908: }
1.227 brouard 13909: }
13910: }
1.225 brouard 13911: }
13912: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
13913: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 13914: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
13915: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.349 brouard 13916:
13917: free_imatrix(existcomb,1,NCOVMAX,1,NCOVMAX);
1.137 brouard 13918: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 13919: /*endread:*/
1.225 brouard 13920: printf("Exiting decodemodel: ");
13921: return (1);
1.136 brouard 13922: }
13923:
1.169 brouard 13924: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 13925: {/* Check ages at death */
1.136 brouard 13926: int i, m;
1.218 brouard 13927: int firstone=0;
13928:
1.136 brouard 13929: for (i=1; i<=imx; i++) {
13930: for(m=2; (m<= maxwav); m++) {
13931: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
13932: anint[m][i]=9999;
1.216 brouard 13933: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
13934: s[m][i]=-1;
1.136 brouard 13935: }
13936: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 13937: *nberr = *nberr + 1;
1.218 brouard 13938: if(firstone == 0){
13939: firstone=1;
1.260 brouard 13940: 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 13941: }
1.262 brouard 13942: 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 13943: s[m][i]=-1; /* Droping the death status */
1.136 brouard 13944: }
13945: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 13946: (*nberr)++;
1.259 brouard 13947: 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 13948: 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 13949: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 13950: }
13951: }
13952: }
13953:
13954: for (i=1; i<=imx; i++) {
13955: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
13956: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 13957: 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 13958: if (s[m][i] >= nlstate+1) {
1.169 brouard 13959: if(agedc[i]>0){
13960: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 13961: agev[m][i]=agedc[i];
1.214 brouard 13962: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 13963: }else {
1.136 brouard 13964: if ((int)andc[i]!=9999){
13965: nbwarn++;
13966: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
13967: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
13968: agev[m][i]=-1;
13969: }
13970: }
1.169 brouard 13971: } /* agedc > 0 */
1.214 brouard 13972: } /* end if */
1.136 brouard 13973: else if(s[m][i] !=9){ /* Standard case, age in fractional
13974: years but with the precision of a month */
13975: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
13976: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
13977: agev[m][i]=1;
13978: else if(agev[m][i] < *agemin){
13979: *agemin=agev[m][i];
13980: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
13981: }
13982: else if(agev[m][i] >*agemax){
13983: *agemax=agev[m][i];
1.156 brouard 13984: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 13985: }
13986: /*agev[m][i]=anint[m][i]-annais[i];*/
13987: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 13988: } /* en if 9*/
1.136 brouard 13989: else { /* =9 */
1.214 brouard 13990: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 13991: agev[m][i]=1;
13992: s[m][i]=-1;
13993: }
13994: }
1.214 brouard 13995: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 13996: agev[m][i]=1;
1.214 brouard 13997: else{
13998: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
13999: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
14000: agev[m][i]=0;
14001: }
14002: } /* End for lastpass */
14003: }
1.136 brouard 14004:
14005: for (i=1; i<=imx; i++) {
14006: for(m=firstpass; (m<=lastpass); m++){
14007: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 14008: (*nberr)++;
1.136 brouard 14009: 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);
14010: 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);
14011: return 1;
14012: }
14013: }
14014: }
14015:
14016: /*for (i=1; i<=imx; i++){
14017: for (m=firstpass; (m<lastpass); m++){
14018: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
14019: }
14020:
14021: }*/
14022:
14023:
1.139 brouard 14024: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
14025: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 14026:
14027: return (0);
1.164 brouard 14028: /* endread:*/
1.136 brouard 14029: printf("Exiting calandcheckages: ");
14030: return (1);
14031: }
14032:
1.172 brouard 14033: #if defined(_MSC_VER)
14034: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
14035: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
14036: //#include "stdafx.h"
14037: //#include <stdio.h>
14038: //#include <tchar.h>
14039: //#include <windows.h>
14040: //#include <iostream>
14041: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
14042:
14043: LPFN_ISWOW64PROCESS fnIsWow64Process;
14044:
14045: BOOL IsWow64()
14046: {
14047: BOOL bIsWow64 = FALSE;
14048:
14049: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
14050: // (HANDLE, PBOOL);
14051:
14052: //LPFN_ISWOW64PROCESS fnIsWow64Process;
14053:
14054: HMODULE module = GetModuleHandle(_T("kernel32"));
14055: const char funcName[] = "IsWow64Process";
14056: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
14057: GetProcAddress(module, funcName);
14058:
14059: if (NULL != fnIsWow64Process)
14060: {
14061: if (!fnIsWow64Process(GetCurrentProcess(),
14062: &bIsWow64))
14063: //throw std::exception("Unknown error");
14064: printf("Unknown error\n");
14065: }
14066: return bIsWow64 != FALSE;
14067: }
14068: #endif
1.177 brouard 14069:
1.191 brouard 14070: void syscompilerinfo(int logged)
1.292 brouard 14071: {
14072: #include <stdint.h>
14073:
14074: /* #include "syscompilerinfo.h"*/
1.185 brouard 14075: /* command line Intel compiler 32bit windows, XP compatible:*/
14076: /* /GS /W3 /Gy
14077: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
14078: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
14079: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 14080: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
14081: */
14082: /* 64 bits */
1.185 brouard 14083: /*
14084: /GS /W3 /Gy
14085: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
14086: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
14087: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
14088: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
14089: /* Optimization are useless and O3 is slower than O2 */
14090: /*
14091: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
14092: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
14093: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
14094: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
14095: */
1.186 brouard 14096: /* Link is */ /* /OUT:"visual studio
1.185 brouard 14097: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
14098: /PDB:"visual studio
14099: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
14100: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
14101: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
14102: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
14103: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
14104: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
14105: uiAccess='false'"
14106: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
14107: /NOLOGO /TLBID:1
14108: */
1.292 brouard 14109:
14110:
1.177 brouard 14111: #if defined __INTEL_COMPILER
1.178 brouard 14112: #if defined(__GNUC__)
14113: struct utsname sysInfo; /* For Intel on Linux and OS/X */
14114: #endif
1.177 brouard 14115: #elif defined(__GNUC__)
1.179 brouard 14116: #ifndef __APPLE__
1.174 brouard 14117: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 14118: #endif
1.177 brouard 14119: struct utsname sysInfo;
1.178 brouard 14120: int cross = CROSS;
14121: if (cross){
14122: printf("Cross-");
1.191 brouard 14123: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 14124: }
1.174 brouard 14125: #endif
14126:
1.191 brouard 14127: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 14128: #if defined(__clang__)
1.191 brouard 14129: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 14130: #endif
14131: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 14132: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 14133: #endif
14134: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 14135: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 14136: #endif
14137: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 14138: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 14139: #endif
14140: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 14141: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 14142: #endif
14143: #if defined(_MSC_VER)
1.191 brouard 14144: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 14145: #endif
14146: #if defined(__PGI)
1.191 brouard 14147: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 14148: #endif
14149: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 14150: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 14151: #endif
1.191 brouard 14152: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 14153:
1.167 brouard 14154: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
14155: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
14156: // Windows (x64 and x86)
1.191 brouard 14157: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 14158: #elif __unix__ // all unices, not all compilers
14159: // Unix
1.191 brouard 14160: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 14161: #elif __linux__
14162: // linux
1.191 brouard 14163: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 14164: #elif __APPLE__
1.174 brouard 14165: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 14166: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 14167: #endif
14168:
14169: /* __MINGW32__ */
14170: /* __CYGWIN__ */
14171: /* __MINGW64__ */
14172: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
14173: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
14174: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
14175: /* _WIN64 // Defined for applications for Win64. */
14176: /* _M_X64 // Defined for compilations that target x64 processors. */
14177: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 14178:
1.167 brouard 14179: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 14180: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 14181: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 14182: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 14183: #else
1.191 brouard 14184: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 14185: #endif
14186:
1.169 brouard 14187: #if defined(__GNUC__)
14188: # if defined(__GNUC_PATCHLEVEL__)
14189: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
14190: + __GNUC_MINOR__ * 100 \
14191: + __GNUC_PATCHLEVEL__)
14192: # else
14193: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
14194: + __GNUC_MINOR__ * 100)
14195: # endif
1.174 brouard 14196: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 14197: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 14198:
14199: if (uname(&sysInfo) != -1) {
14200: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 14201: 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 14202: }
14203: else
14204: perror("uname() error");
1.179 brouard 14205: //#ifndef __INTEL_COMPILER
14206: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 14207: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 14208: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 14209: #endif
1.169 brouard 14210: #endif
1.172 brouard 14211:
1.286 brouard 14212: // void main ()
1.172 brouard 14213: // {
1.169 brouard 14214: #if defined(_MSC_VER)
1.174 brouard 14215: if (IsWow64()){
1.191 brouard 14216: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
14217: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 14218: }
14219: else{
1.191 brouard 14220: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
14221: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 14222: }
1.172 brouard 14223: // printf("\nPress Enter to continue...");
14224: // getchar();
14225: // }
14226:
1.169 brouard 14227: #endif
14228:
1.167 brouard 14229:
1.219 brouard 14230: }
1.136 brouard 14231:
1.219 brouard 14232: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 14233: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.332 brouard 14234: /* Computes the prevalence limit for each combination of the dummy covariates */
1.235 brouard 14235: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 14236: /* double ftolpl = 1.e-10; */
1.180 brouard 14237: double age, agebase, agelim;
1.203 brouard 14238: double tot;
1.180 brouard 14239:
1.202 brouard 14240: strcpy(filerespl,"PL_");
14241: strcat(filerespl,fileresu);
14242: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 14243: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
14244: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 14245: }
1.288 brouard 14246: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
14247: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 14248: pstamp(ficrespl);
1.288 brouard 14249: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 14250: fprintf(ficrespl,"#Age ");
14251: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
14252: fprintf(ficrespl,"\n");
1.180 brouard 14253:
1.219 brouard 14254: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 14255:
1.219 brouard 14256: agebase=ageminpar;
14257: agelim=agemaxpar;
1.180 brouard 14258:
1.227 brouard 14259: /* i1=pow(2,ncoveff); */
1.234 brouard 14260: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 14261: if (cptcovn < 1){i1=1;}
1.180 brouard 14262:
1.337 brouard 14263: /* for(k=1; k<=i1;k++){ /\* For each combination k of dummy covariates in the model *\/ */
1.238 brouard 14264: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 14265: k=TKresult[nres];
1.338 brouard 14266: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 14267: /* if(i1 != 1 && TKresult[nres]!= k) /\* We found the combination k corresponding to the resultline value of dummies *\/ */
14268: /* continue; */
1.235 brouard 14269:
1.238 brouard 14270: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
14271: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
14272: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
14273: /* k=k+1; */
14274: /* to clean */
1.332 brouard 14275: /*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*/
1.238 brouard 14276: fprintf(ficrespl,"#******");
14277: printf("#******");
14278: fprintf(ficlog,"#******");
1.337 brouard 14279: 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 14280: /* fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Here problem for varying dummy*\/ */
1.337 brouard 14281: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14282: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14283: fprintf(ficrespl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
14284: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
14285: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
14286: }
14287: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
14288: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
14289: /* fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
14290: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
14291: /* } */
1.238 brouard 14292: fprintf(ficrespl,"******\n");
14293: printf("******\n");
14294: fprintf(ficlog,"******\n");
14295: if(invalidvarcomb[k]){
14296: printf("\nCombination (%d) ignored because no case \n",k);
14297: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
14298: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
14299: continue;
14300: }
1.219 brouard 14301:
1.238 brouard 14302: fprintf(ficrespl,"#Age ");
1.337 brouard 14303: /* for(j=1;j<=cptcoveff;j++) { */
14304: /* fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14305: /* } */
14306: for(j=1;j<=cptcovs;j++) { /* New the quanti variable is added */
14307: fprintf(ficrespl,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 14308: }
14309: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
14310: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 14311:
1.238 brouard 14312: for (age=agebase; age<=agelim; age++){
14313: /* for (age=agebase; age<=agebase; age++){ */
1.337 brouard 14314: /**< Computes the prevalence limit in each live state at age x and for covariate combination (k and) nres */
14315: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres); /* Nicely done */
1.238 brouard 14316: fprintf(ficrespl,"%.0f ",age );
1.337 brouard 14317: /* for(j=1;j<=cptcoveff;j++) */
14318: /* fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14319: for(j=1;j<=cptcovs;j++)
14320: fprintf(ficrespl,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 14321: tot=0.;
14322: for(i=1; i<=nlstate;i++){
14323: tot += prlim[i][i];
14324: fprintf(ficrespl," %.5f", prlim[i][i]);
14325: }
14326: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
14327: } /* Age */
14328: /* was end of cptcod */
1.337 brouard 14329: } /* nres */
14330: /* } /\* for each combination *\/ */
1.219 brouard 14331: return 0;
1.180 brouard 14332: }
14333:
1.218 brouard 14334: 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 14335: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 14336:
14337: /* Computes the back prevalence limit for any combination of covariate values
14338: * at any age between ageminpar and agemaxpar
14339: */
1.235 brouard 14340: int i, j, k, i1, nres=0 ;
1.217 brouard 14341: /* double ftolpl = 1.e-10; */
14342: double age, agebase, agelim;
14343: double tot;
1.218 brouard 14344: /* double ***mobaverage; */
14345: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 14346:
14347: strcpy(fileresplb,"PLB_");
14348: strcat(fileresplb,fileresu);
14349: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 14350: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
14351: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 14352: }
1.288 brouard 14353: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
14354: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 14355: pstamp(ficresplb);
1.288 brouard 14356: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 14357: fprintf(ficresplb,"#Age ");
14358: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
14359: fprintf(ficresplb,"\n");
14360:
1.218 brouard 14361:
14362: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
14363:
14364: agebase=ageminpar;
14365: agelim=agemaxpar;
14366:
14367:
1.227 brouard 14368: i1=pow(2,cptcoveff);
1.218 brouard 14369: if (cptcovn < 1){i1=1;}
1.227 brouard 14370:
1.238 brouard 14371: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.338 brouard 14372: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
14373: k=TKresult[nres];
14374: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
14375: /* if(i1 != 1 && TKresult[nres]!= k) */
14376: /* continue; */
14377: /* /\*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*\/ */
1.238 brouard 14378: fprintf(ficresplb,"#******");
14379: printf("#******");
14380: fprintf(ficlog,"#******");
1.338 brouard 14381: 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) */
14382: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
14383: fprintf(ficresplb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
14384: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 14385: }
1.338 brouard 14386: /* for(j=1;j<=cptcoveff ;j++) {/\* all covariates *\/ */
14387: /* fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14388: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14389: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14390: /* } */
14391: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
14392: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
14393: /* fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
14394: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
14395: /* } */
1.238 brouard 14396: fprintf(ficresplb,"******\n");
14397: printf("******\n");
14398: fprintf(ficlog,"******\n");
14399: if(invalidvarcomb[k]){
14400: printf("\nCombination (%d) ignored because no cases \n",k);
14401: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
14402: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
14403: continue;
14404: }
1.218 brouard 14405:
1.238 brouard 14406: fprintf(ficresplb,"#Age ");
1.338 brouard 14407: for(j=1;j<=cptcovs;j++) {
14408: fprintf(ficresplb,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 14409: }
14410: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
14411: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 14412:
14413:
1.238 brouard 14414: for (age=agebase; age<=agelim; age++){
14415: /* for (age=agebase; age<=agebase; age++){ */
14416: if(mobilavproj > 0){
14417: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
14418: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 14419: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 14420: }else if (mobilavproj == 0){
14421: 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);
14422: 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);
14423: exit(1);
14424: }else{
14425: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 14426: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 14427: /* printf("TOTOT\n"); */
14428: /* exit(1); */
1.238 brouard 14429: }
14430: fprintf(ficresplb,"%.0f ",age );
1.338 brouard 14431: for(j=1;j<=cptcovs;j++)
14432: fprintf(ficresplb,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 14433: tot=0.;
14434: for(i=1; i<=nlstate;i++){
14435: tot += bprlim[i][i];
14436: fprintf(ficresplb," %.5f", bprlim[i][i]);
14437: }
14438: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
14439: } /* Age */
14440: /* was end of cptcod */
1.255 brouard 14441: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.338 brouard 14442: /* } /\* end of any combination *\/ */
1.238 brouard 14443: } /* end of nres */
1.218 brouard 14444: /* hBijx(p, bage, fage); */
14445: /* fclose(ficrespijb); */
14446:
14447: return 0;
1.217 brouard 14448: }
1.218 brouard 14449:
1.180 brouard 14450: int hPijx(double *p, int bage, int fage){
14451: /*------------- h Pij x at various ages ------------*/
1.336 brouard 14452: /* to be optimized with precov */
1.180 brouard 14453: int stepsize;
14454: int agelim;
14455: int hstepm;
14456: int nhstepm;
1.359 brouard 14457: int h, i, i1, j, k, nres=0;
1.180 brouard 14458:
14459: double agedeb;
14460: double ***p3mat;
14461:
1.337 brouard 14462: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
14463: if((ficrespij=fopen(filerespij,"w"))==NULL) {
14464: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
14465: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
14466: }
14467: printf("Computing pij: result on file '%s' \n", filerespij);
14468: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
14469:
14470: stepsize=(int) (stepm+YEARM-1)/YEARM;
14471: /*if (stepm<=24) stepsize=2;*/
14472:
14473: agelim=AGESUP;
14474: hstepm=stepsize*YEARM; /* Every year of age */
14475: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
14476:
14477: /* hstepm=1; aff par mois*/
14478: pstamp(ficrespij);
14479: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
14480: i1= pow(2,cptcoveff);
14481: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
14482: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
14483: /* k=k+1; */
14484: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
14485: k=TKresult[nres];
1.338 brouard 14486: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 14487: /* for(k=1; k<=i1;k++){ */
14488: /* if(i1 != 1 && TKresult[nres]!= k) */
14489: /* continue; */
14490: fprintf(ficrespij,"\n#****** ");
14491: for(j=1;j<=cptcovs;j++){
14492: fprintf(ficrespij," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
14493: /* fprintf(ficrespij,"@wV%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14494: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
14495: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
14496: /* fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
14497: }
14498: fprintf(ficrespij,"******\n");
14499:
14500: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
14501: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
14502: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
14503:
14504: /* nhstepm=nhstepm*YEARM; aff par mois*/
14505:
14506: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
14507: oldm=oldms;savm=savms;
14508: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
14509: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
14510: for(i=1; i<=nlstate;i++)
14511: for(j=1; j<=nlstate+ndeath;j++)
14512: fprintf(ficrespij," %1d-%1d",i,j);
14513: fprintf(ficrespij,"\n");
14514: for (h=0; h<=nhstepm; h++){
14515: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
14516: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.183 brouard 14517: for(i=1; i<=nlstate;i++)
14518: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 14519: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.183 brouard 14520: fprintf(ficrespij,"\n");
14521: }
1.337 brouard 14522: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
14523: fprintf(ficrespij,"\n");
1.180 brouard 14524: }
1.337 brouard 14525: }
14526: /*}*/
14527: return 0;
1.180 brouard 14528: }
1.218 brouard 14529:
14530: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 14531: /*------------- h Bij x at various ages ------------*/
1.336 brouard 14532: /* To be optimized with precov */
1.217 brouard 14533: int stepsize;
1.218 brouard 14534: /* int agelim; */
14535: int ageminl;
1.217 brouard 14536: int hstepm;
14537: int nhstepm;
1.238 brouard 14538: int h, i, i1, j, k, nres;
1.218 brouard 14539:
1.217 brouard 14540: double agedeb;
14541: double ***p3mat;
1.218 brouard 14542:
14543: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
14544: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
14545: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
14546: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
14547: }
14548: printf("Computing pij back: result on file '%s' \n", filerespijb);
14549: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
14550:
14551: stepsize=(int) (stepm+YEARM-1)/YEARM;
14552: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 14553:
1.218 brouard 14554: /* agelim=AGESUP; */
1.289 brouard 14555: ageminl=AGEINF; /* was 30 */
1.218 brouard 14556: hstepm=stepsize*YEARM; /* Every year of age */
14557: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
14558:
14559: /* hstepm=1; aff par mois*/
14560: pstamp(ficrespijb);
1.255 brouard 14561: 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 14562: i1= pow(2,cptcoveff);
1.218 brouard 14563: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
14564: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
14565: /* k=k+1; */
1.238 brouard 14566: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 14567: k=TKresult[nres];
1.338 brouard 14568: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 14569: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
14570: /* if(i1 != 1 && TKresult[nres]!= k) */
14571: /* continue; */
14572: fprintf(ficrespijb,"\n#****** ");
14573: for(j=1;j<=cptcovs;j++){
1.338 brouard 14574: fprintf(ficrespijb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.337 brouard 14575: /* for(j=1;j<=cptcoveff;j++) */
14576: /* fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14577: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
14578: /* fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
14579: }
14580: fprintf(ficrespijb,"******\n");
14581: if(invalidvarcomb[k]){ /* Is it necessary here? */
14582: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
14583: continue;
14584: }
14585:
14586: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
14587: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
14588: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
14589: 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 */
14590: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 or 28*/
14591:
14592: /* nhstepm=nhstepm*YEARM; aff par mois*/
14593:
14594: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
14595: /* and memory limitations if stepm is small */
14596:
14597: /* oldm=oldms;savm=savms; */
14598: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
14599: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);/* Bug valgrind */
14600: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
14601: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
14602: for(i=1; i<=nlstate;i++)
14603: for(j=1; j<=nlstate+ndeath;j++)
14604: fprintf(ficrespijb," %1d-%1d",i,j);
14605: fprintf(ficrespijb,"\n");
14606: for (h=0; h<=nhstepm; h++){
14607: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
14608: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
14609: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
1.217 brouard 14610: for(i=1; i<=nlstate;i++)
14611: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 14612: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);/* Bug valgrind */
1.217 brouard 14613: fprintf(ficrespijb,"\n");
1.337 brouard 14614: }
14615: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
14616: fprintf(ficrespijb,"\n");
14617: } /* end age deb */
14618: /* } /\* end combination *\/ */
1.238 brouard 14619: } /* end nres */
1.218 brouard 14620: return 0;
14621: } /* hBijx */
1.217 brouard 14622:
1.180 brouard 14623:
1.136 brouard 14624: /***********************************************/
14625: /**************** Main Program *****************/
14626: /***********************************************/
14627:
14628: int main(int argc, char *argv[])
14629: {
14630: #ifdef GSL
14631: const gsl_multimin_fminimizer_type *T;
14632: size_t iteri = 0, it;
14633: int rval = GSL_CONTINUE;
14634: int status = GSL_SUCCESS;
14635: double ssval;
14636: #endif
14637: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 14638: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
14639: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 14640: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 14641: int jj, ll, li, lj, lk;
1.136 brouard 14642: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 14643: int num_filled;
1.136 brouard 14644: int itimes;
14645: int NDIM=2;
14646: int vpopbased=0;
1.235 brouard 14647: int nres=0;
1.258 brouard 14648: int endishere=0;
1.277 brouard 14649: int noffset=0;
1.274 brouard 14650: int ncurrv=0; /* Temporary variable */
14651:
1.164 brouard 14652: char ca[32], cb[32];
1.136 brouard 14653: /* FILE *fichtm; *//* Html File */
14654: /* FILE *ficgp;*/ /*Gnuplot File */
14655: struct stat info;
1.191 brouard 14656: double agedeb=0.;
1.194 brouard 14657:
14658: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 14659: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 14660:
1.361 brouard 14661: double stdpercent; /* for computing the std error of percent e.i: e.i/e.. */
1.165 brouard 14662: double fret;
1.191 brouard 14663: double dum=0.; /* Dummy variable */
1.359 brouard 14664: /* double*** p3mat;*/
1.218 brouard 14665: /* double ***mobaverage; */
1.319 brouard 14666: double wald;
1.164 brouard 14667:
1.351 brouard 14668: char line[MAXLINE], linetmp[MAXLINE];
1.197 brouard 14669: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
14670:
1.234 brouard 14671: char modeltemp[MAXLINE];
1.332 brouard 14672: char resultline[MAXLINE], resultlineori[MAXLINE];
1.230 brouard 14673:
1.136 brouard 14674: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 14675: char *tok, *val; /* pathtot */
1.334 brouard 14676: /* int firstobs=1, lastobs=10; /\* nobs = lastobs-firstobs declared globally ;*\/ */
1.359 brouard 14677: int c, h; /* c2; */
1.191 brouard 14678: int jl=0;
14679: int i1, j1, jk, stepsize=0;
1.194 brouard 14680: int count=0;
14681:
1.164 brouard 14682: int *tab;
1.136 brouard 14683: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.296 brouard 14684: /* double anprojd, mprojd, jprojd; /\* For eventual projections *\/ */
14685: /* double anprojf, mprojf, jprojf; */
14686: /* double jintmean,mintmean,aintmean; */
14687: int prvforecast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
14688: int prvbackcast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
14689: double yrfproj= 10.0; /* Number of years of forward projections */
14690: double yrbproj= 10.0; /* Number of years of backward projections */
14691: int prevbcast=0; /* defined as global for mlikeli and mle, replacing backcast */
1.136 brouard 14692: int mobilav=0,popforecast=0;
1.191 brouard 14693: int hstepm=0, nhstepm=0;
1.136 brouard 14694: int agemortsup;
14695: float sumlpop=0.;
14696: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
14697: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
14698:
1.191 brouard 14699: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 14700: double ftolpl=FTOL;
14701: double **prlim;
1.217 brouard 14702: double **bprlim;
1.317 brouard 14703: double ***param; /* Matrix of parameters, param[i][j][k] param=ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel)
14704: state of origin, state of destination including death, for each covariate: constante, age, and V1 V2 etc. */
1.251 brouard 14705: double ***paramstart; /* Matrix of starting parameter values */
14706: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 14707: double **matcov; /* Matrix of covariance */
1.203 brouard 14708: double **hess; /* Hessian matrix */
1.136 brouard 14709: double ***delti3; /* Scale */
14710: double *delti; /* Scale */
14711: double ***eij, ***vareij;
1.359 brouard 14712: //double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 14713:
1.136 brouard 14714: double *epj, vepp;
1.164 brouard 14715:
1.273 brouard 14716: double dateprev1, dateprev2;
1.296 brouard 14717: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0, dateprojd=0, dateprojf=0;
14718: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0, datebackd=0, datebackf=0;
14719:
1.217 brouard 14720:
1.136 brouard 14721: double **ximort;
1.145 brouard 14722: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 14723: int *dcwave;
14724:
1.164 brouard 14725: char z[1]="c";
1.136 brouard 14726:
14727: /*char *strt;*/
14728: char strtend[80];
1.126 brouard 14729:
1.164 brouard 14730:
1.126 brouard 14731: /* setlocale (LC_ALL, ""); */
14732: /* bindtextdomain (PACKAGE, LOCALEDIR); */
14733: /* textdomain (PACKAGE); */
14734: /* setlocale (LC_CTYPE, ""); */
14735: /* setlocale (LC_MESSAGES, ""); */
14736:
14737: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 14738: rstart_time = time(NULL);
14739: /* (void) gettimeofday(&start_time,&tzp);*/
14740: start_time = *localtime(&rstart_time);
1.126 brouard 14741: curr_time=start_time;
1.157 brouard 14742: /*tml = *localtime(&start_time.tm_sec);*/
14743: /* strcpy(strstart,asctime(&tml)); */
14744: strcpy(strstart,asctime(&start_time));
1.126 brouard 14745:
14746: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 14747: /* tp.tm_sec = tp.tm_sec +86400; */
14748: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 14749: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
14750: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
14751: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 14752: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 14753: /* strt=asctime(&tmg); */
14754: /* printf("Time(after) =%s",strstart); */
14755: /* (void) time (&time_value);
14756: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
14757: * tm = *localtime(&time_value);
14758: * strstart=asctime(&tm);
14759: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
14760: */
14761:
14762: nberr=0; /* Number of errors and warnings */
14763: nbwarn=0;
1.184 brouard 14764: #ifdef WIN32
14765: _getcwd(pathcd, size);
14766: #else
1.126 brouard 14767: getcwd(pathcd, size);
1.184 brouard 14768: #endif
1.191 brouard 14769: syscompilerinfo(0);
1.359 brouard 14770: printf("\nIMaCh prax version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 14771: if(argc <=1){
14772: printf("\nEnter the parameter file name: ");
1.205 brouard 14773: if(!fgets(pathr,FILENAMELENGTH,stdin)){
14774: printf("ERROR Empty parameter file name\n");
14775: goto end;
14776: }
1.126 brouard 14777: i=strlen(pathr);
14778: if(pathr[i-1]=='\n')
14779: pathr[i-1]='\0';
1.156 brouard 14780: i=strlen(pathr);
1.205 brouard 14781: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 14782: pathr[i-1]='\0';
1.205 brouard 14783: }
14784: i=strlen(pathr);
14785: if( i==0 ){
14786: printf("ERROR Empty parameter file name\n");
14787: goto end;
14788: }
14789: for (tok = pathr; tok != NULL; ){
1.126 brouard 14790: printf("Pathr |%s|\n",pathr);
14791: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
14792: printf("val= |%s| pathr=%s\n",val,pathr);
14793: strcpy (pathtot, val);
14794: if(pathr[0] == '\0') break; /* Dirty */
14795: }
14796: }
1.281 brouard 14797: else if (argc<=2){
14798: strcpy(pathtot,argv[1]);
14799: }
1.126 brouard 14800: else{
14801: strcpy(pathtot,argv[1]);
1.281 brouard 14802: strcpy(z,argv[2]);
14803: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 14804: }
14805: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
14806: /*cygwin_split_path(pathtot,path,optionfile);
14807: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
14808: /* cutv(path,optionfile,pathtot,'\\');*/
14809:
14810: /* Split argv[0], imach program to get pathimach */
14811: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
14812: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
14813: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
14814: /* strcpy(pathimach,argv[0]); */
14815: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
14816: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
14817: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 14818: #ifdef WIN32
14819: _chdir(path); /* Can be a relative path */
14820: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
14821: #else
1.126 brouard 14822: chdir(path); /* Can be a relative path */
1.184 brouard 14823: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
14824: #endif
14825: printf("Current directory %s!\n",pathcd);
1.126 brouard 14826: strcpy(command,"mkdir ");
14827: strcat(command,optionfilefiname);
14828: if((outcmd=system(command)) != 0){
1.169 brouard 14829: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 14830: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
14831: /* fclose(ficlog); */
14832: /* exit(1); */
14833: }
14834: /* if((imk=mkdir(optionfilefiname))<0){ */
14835: /* perror("mkdir"); */
14836: /* } */
14837:
14838: /*-------- arguments in the command line --------*/
14839:
1.186 brouard 14840: /* Main Log file */
1.126 brouard 14841: strcat(filelog, optionfilefiname);
14842: strcat(filelog,".log"); /* */
14843: if((ficlog=fopen(filelog,"w"))==NULL) {
14844: printf("Problem with logfile %s\n",filelog);
14845: goto end;
14846: }
14847: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 14848: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 14849: fprintf(ficlog,"\nEnter the parameter file name: \n");
14850: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
14851: path=%s \n\
14852: optionfile=%s\n\
14853: optionfilext=%s\n\
1.156 brouard 14854: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 14855:
1.197 brouard 14856: syscompilerinfo(1);
1.167 brouard 14857:
1.126 brouard 14858: printf("Local time (at start):%s",strstart);
14859: fprintf(ficlog,"Local time (at start): %s",strstart);
14860: fflush(ficlog);
14861: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 14862: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 14863:
14864: /* */
14865: strcpy(fileres,"r");
14866: strcat(fileres, optionfilefiname);
1.201 brouard 14867: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 14868: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 14869: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 14870:
1.186 brouard 14871: /* Main ---------arguments file --------*/
1.126 brouard 14872:
14873: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 14874: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
14875: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 14876: fflush(ficlog);
1.149 brouard 14877: /* goto end; */
14878: exit(70);
1.126 brouard 14879: }
14880:
14881: strcpy(filereso,"o");
1.201 brouard 14882: strcat(filereso,fileresu);
1.126 brouard 14883: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
14884: printf("Problem with Output resultfile: %s\n", filereso);
14885: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
14886: fflush(ficlog);
14887: goto end;
14888: }
1.278 brouard 14889: /*-------- Rewriting parameter file ----------*/
14890: strcpy(rfileres,"r"); /* "Rparameterfile */
14891: strcat(rfileres,optionfilefiname); /* Parameter file first name */
14892: strcat(rfileres,"."); /* */
14893: strcat(rfileres,optionfilext); /* Other files have txt extension */
14894: if((ficres =fopen(rfileres,"w"))==NULL) {
14895: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
14896: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
14897: fflush(ficlog);
14898: goto end;
14899: }
14900: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 14901:
1.278 brouard 14902:
1.126 brouard 14903: /* Reads comments: lines beginning with '#' */
14904: numlinepar=0;
1.277 brouard 14905: /* Is it a BOM UTF-8 Windows file? */
14906: /* First parameter line */
1.197 brouard 14907: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 14908: noffset=0;
14909: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
14910: {
14911: noffset=noffset+3;
14912: printf("# File is an UTF8 Bom.\n"); // 0xBF
14913: }
1.302 brouard 14914: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
14915: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
1.277 brouard 14916: {
14917: noffset=noffset+2;
14918: printf("# File is an UTF16BE BOM file\n");
14919: }
14920: else if( line[0] == 0 && line[1] == 0)
14921: {
14922: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
14923: noffset=noffset+4;
14924: printf("# File is an UTF16BE BOM file\n");
14925: }
14926: } else{
14927: ;/*printf(" Not a BOM file\n");*/
14928: }
14929:
1.197 brouard 14930: /* If line starts with a # it is a comment */
1.277 brouard 14931: if (line[noffset] == '#') {
1.197 brouard 14932: numlinepar++;
14933: fputs(line,stdout);
14934: fputs(line,ficparo);
1.278 brouard 14935: fputs(line,ficres);
1.197 brouard 14936: fputs(line,ficlog);
14937: continue;
14938: }else
14939: break;
14940: }
14941: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
14942: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
14943: if (num_filled != 5) {
14944: printf("Should be 5 parameters\n");
1.283 brouard 14945: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 14946: }
1.126 brouard 14947: numlinepar++;
1.197 brouard 14948: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 14949: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
14950: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
14951: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 14952: }
14953: /* Second parameter line */
14954: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 14955: /* while(fscanf(ficpar,"%[^\n]", line)) { */
14956: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 14957: if (line[0] == '#') {
14958: numlinepar++;
1.283 brouard 14959: printf("%s",line);
14960: fprintf(ficres,"%s",line);
14961: fprintf(ficparo,"%s",line);
14962: fprintf(ficlog,"%s",line);
1.197 brouard 14963: continue;
14964: }else
14965: break;
14966: }
1.223 brouard 14967: 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", \
14968: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
14969: if (num_filled != 11) {
14970: 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 14971: printf("but line=%s\n",line);
1.283 brouard 14972: 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");
14973: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 14974: }
1.286 brouard 14975: if( lastpass > maxwav){
14976: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
14977: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
14978: fflush(ficlog);
14979: goto end;
14980: }
14981: 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 14982: 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 14983: 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 14984: 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 14985: }
1.203 brouard 14986: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 14987: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 14988: /* Third parameter line */
14989: while(fgets(line, MAXLINE, ficpar)) {
14990: /* If line starts with a # it is a comment */
14991: if (line[0] == '#') {
14992: numlinepar++;
1.283 brouard 14993: printf("%s",line);
14994: fprintf(ficres,"%s",line);
14995: fprintf(ficparo,"%s",line);
14996: fprintf(ficlog,"%s",line);
1.197 brouard 14997: continue;
14998: }else
14999: break;
15000: }
1.351 brouard 15001: if((num_filled=sscanf(line,"model=%[^.\n]", model)) !=EOF){ /* Every character after model but dot and return */
15002: if (num_filled != 1){
15003: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
15004: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
15005: model[0]='\0';
15006: goto end;
15007: }else{
15008: trimbtab(linetmp,line); /* Trims multiple blanks in line */
15009: strcpy(line, linetmp);
15010: }
15011: }
15012: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){ /* Every character after 1+age but dot and return */
1.279 brouard 15013: if (num_filled != 1){
1.302 brouard 15014: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
15015: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
1.197 brouard 15016: model[0]='\0';
15017: goto end;
15018: }
15019: else{
15020: if (model[0]=='+'){
15021: for(i=1; i<=strlen(model);i++)
15022: modeltemp[i-1]=model[i];
1.201 brouard 15023: strcpy(model,modeltemp);
1.197 brouard 15024: }
15025: }
1.338 brouard 15026: /* printf(" model=1+age%s modeltemp= %s, model=1+age+%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 15027: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 15028: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
15029: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
15030: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 15031: }
15032: /* 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); */
15033: /* numlinepar=numlinepar+3; /\* In general *\/ */
15034: /* 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 15035: /* 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); */
15036: /* 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 15037: fflush(ficlog);
1.190 brouard 15038: /* if(model[0]=='#'|| model[0]== '\0'){ */
15039: if(model[0]=='#'){
1.279 brouard 15040: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
15041: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
15042: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 15043: if(mle != -1){
1.279 brouard 15044: 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 15045: exit(1);
15046: }
15047: }
1.126 brouard 15048: while((c=getc(ficpar))=='#' && c!= EOF){
15049: ungetc(c,ficpar);
15050: fgets(line, MAXLINE, ficpar);
15051: numlinepar++;
1.195 brouard 15052: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
15053: z[0]=line[1];
1.342 brouard 15054: }else if(line[1]=='d'){ /* For debugging individual values of covariates in ficresilk */
1.343 brouard 15055: debugILK=1;printf("DebugILK\n");
1.195 brouard 15056: }
15057: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 15058: fputs(line, stdout);
15059: //puts(line);
1.126 brouard 15060: fputs(line,ficparo);
15061: fputs(line,ficlog);
15062: }
15063: ungetc(c,ficpar);
15064:
15065:
1.290 brouard 15066: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
15067: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
15068: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
1.341 brouard 15069: /* if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /\**< Time varying covariate (dummy and quantitative)*\/ */
15070: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs); /**< Might be better */
1.136 brouard 15071: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
15072: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
15073: v1+v2*age+v2*v3 makes cptcovn = 3
15074: */
15075: if (strlen(model)>1)
1.187 brouard 15076: 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 15077: else
1.187 brouard 15078: ncovmodel=2; /* Constant and age */
1.133 brouard 15079: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
15080: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 15081: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
15082: 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);
15083: 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);
15084: fflush(stdout);
15085: fclose (ficlog);
15086: goto end;
15087: }
1.126 brouard 15088: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
15089: delti=delti3[1][1];
15090: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
15091: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 15092: /* We could also provide initial parameters values giving by simple logistic regression
15093: * only one way, that is without matrix product. We will have nlstate maximizations */
15094: /* for(i=1;i<nlstate;i++){ */
15095: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
15096: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
15097: /* } */
1.126 brouard 15098: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 15099: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
15100: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 15101: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
15102: fclose (ficparo);
15103: fclose (ficlog);
15104: goto end;
15105: exit(0);
1.220 brouard 15106: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 15107: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 15108: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
15109: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 15110: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
15111: matcov=matrix(1,npar,1,npar);
1.203 brouard 15112: hess=matrix(1,npar,1,npar);
1.220 brouard 15113: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 15114: /* Read guessed parameters */
1.126 brouard 15115: /* Reads comments: lines beginning with '#' */
15116: while((c=getc(ficpar))=='#' && c!= EOF){
15117: ungetc(c,ficpar);
15118: fgets(line, MAXLINE, ficpar);
15119: numlinepar++;
1.141 brouard 15120: fputs(line,stdout);
1.126 brouard 15121: fputs(line,ficparo);
15122: fputs(line,ficlog);
15123: }
15124: ungetc(c,ficpar);
15125:
15126: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 15127: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 15128: for(i=1; i <=nlstate; i++){
1.234 brouard 15129: j=0;
1.126 brouard 15130: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 15131: if(jj==i) continue;
15132: j++;
1.292 brouard 15133: while((c=getc(ficpar))=='#' && c!= EOF){
15134: ungetc(c,ficpar);
15135: fgets(line, MAXLINE, ficpar);
15136: numlinepar++;
15137: fputs(line,stdout);
15138: fputs(line,ficparo);
15139: fputs(line,ficlog);
15140: }
15141: ungetc(c,ficpar);
1.234 brouard 15142: fscanf(ficpar,"%1d%1d",&i1,&j1);
15143: if ((i1 != i) || (j1 != jj)){
15144: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 15145: It might be a problem of design; if ncovcol and the model are correct\n \
15146: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 15147: exit(1);
15148: }
15149: fprintf(ficparo,"%1d%1d",i1,j1);
15150: if(mle==1)
15151: printf("%1d%1d",i,jj);
15152: fprintf(ficlog,"%1d%1d",i,jj);
15153: for(k=1; k<=ncovmodel;k++){
15154: fscanf(ficpar," %lf",¶m[i][j][k]);
15155: if(mle==1){
15156: printf(" %lf",param[i][j][k]);
15157: fprintf(ficlog," %lf",param[i][j][k]);
15158: }
15159: else
15160: fprintf(ficlog," %lf",param[i][j][k]);
15161: fprintf(ficparo," %lf",param[i][j][k]);
15162: }
15163: fscanf(ficpar,"\n");
15164: numlinepar++;
15165: if(mle==1)
15166: printf("\n");
15167: fprintf(ficlog,"\n");
15168: fprintf(ficparo,"\n");
1.126 brouard 15169: }
15170: }
15171: fflush(ficlog);
1.234 brouard 15172:
1.251 brouard 15173: /* Reads parameters values */
1.126 brouard 15174: p=param[1][1];
1.251 brouard 15175: pstart=paramstart[1][1];
1.126 brouard 15176:
15177: /* Reads comments: lines beginning with '#' */
15178: while((c=getc(ficpar))=='#' && c!= EOF){
15179: ungetc(c,ficpar);
15180: fgets(line, MAXLINE, ficpar);
15181: numlinepar++;
1.141 brouard 15182: fputs(line,stdout);
1.126 brouard 15183: fputs(line,ficparo);
15184: fputs(line,ficlog);
15185: }
15186: ungetc(c,ficpar);
15187:
15188: for(i=1; i <=nlstate; i++){
15189: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 15190: fscanf(ficpar,"%1d%1d",&i1,&j1);
15191: if ( (i1-i) * (j1-j) != 0){
15192: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
15193: exit(1);
15194: }
15195: printf("%1d%1d",i,j);
15196: fprintf(ficparo,"%1d%1d",i1,j1);
15197: fprintf(ficlog,"%1d%1d",i1,j1);
15198: for(k=1; k<=ncovmodel;k++){
15199: fscanf(ficpar,"%le",&delti3[i][j][k]);
15200: printf(" %le",delti3[i][j][k]);
15201: fprintf(ficparo," %le",delti3[i][j][k]);
15202: fprintf(ficlog," %le",delti3[i][j][k]);
15203: }
15204: fscanf(ficpar,"\n");
15205: numlinepar++;
15206: printf("\n");
15207: fprintf(ficparo,"\n");
15208: fprintf(ficlog,"\n");
1.126 brouard 15209: }
15210: }
15211: fflush(ficlog);
1.234 brouard 15212:
1.145 brouard 15213: /* Reads covariance matrix */
1.126 brouard 15214: delti=delti3[1][1];
1.220 brouard 15215:
15216:
1.126 brouard 15217: /* 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 15218:
1.126 brouard 15219: /* Reads comments: lines beginning with '#' */
15220: while((c=getc(ficpar))=='#' && c!= EOF){
15221: ungetc(c,ficpar);
15222: fgets(line, MAXLINE, ficpar);
15223: numlinepar++;
1.141 brouard 15224: fputs(line,stdout);
1.126 brouard 15225: fputs(line,ficparo);
15226: fputs(line,ficlog);
15227: }
15228: ungetc(c,ficpar);
1.220 brouard 15229:
1.126 brouard 15230: matcov=matrix(1,npar,1,npar);
1.203 brouard 15231: hess=matrix(1,npar,1,npar);
1.131 brouard 15232: for(i=1; i <=npar; i++)
15233: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 15234:
1.194 brouard 15235: /* Scans npar lines */
1.126 brouard 15236: for(i=1; i <=npar; i++){
1.226 brouard 15237: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 15238: if(count != 3){
1.226 brouard 15239: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 15240: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
15241: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 15242: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 15243: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
15244: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 15245: exit(1);
1.220 brouard 15246: }else{
1.226 brouard 15247: if(mle==1)
15248: printf("%1d%1d%d",i1,j1,jk);
15249: }
15250: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
15251: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 15252: for(j=1; j <=i; j++){
1.226 brouard 15253: fscanf(ficpar," %le",&matcov[i][j]);
15254: if(mle==1){
15255: printf(" %.5le",matcov[i][j]);
15256: }
15257: fprintf(ficlog," %.5le",matcov[i][j]);
15258: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 15259: }
15260: fscanf(ficpar,"\n");
15261: numlinepar++;
15262: if(mle==1)
1.220 brouard 15263: printf("\n");
1.126 brouard 15264: fprintf(ficlog,"\n");
15265: fprintf(ficparo,"\n");
15266: }
1.194 brouard 15267: /* End of read covariance matrix npar lines */
1.126 brouard 15268: for(i=1; i <=npar; i++)
15269: for(j=i+1;j<=npar;j++)
1.226 brouard 15270: matcov[i][j]=matcov[j][i];
1.126 brouard 15271:
15272: if(mle==1)
15273: printf("\n");
15274: fprintf(ficlog,"\n");
15275:
15276: fflush(ficlog);
15277:
15278: } /* End of mle != -3 */
1.218 brouard 15279:
1.186 brouard 15280: /* Main data
15281: */
1.290 brouard 15282: nobs=lastobs-firstobs+1; /* was = lastobs;*/
15283: /* num=lvector(1,n); */
15284: /* moisnais=vector(1,n); */
15285: /* annais=vector(1,n); */
15286: /* moisdc=vector(1,n); */
15287: /* andc=vector(1,n); */
15288: /* weight=vector(1,n); */
15289: /* agedc=vector(1,n); */
15290: /* cod=ivector(1,n); */
15291: /* for(i=1;i<=n;i++){ */
15292: num=lvector(firstobs,lastobs);
15293: moisnais=vector(firstobs,lastobs);
15294: annais=vector(firstobs,lastobs);
15295: moisdc=vector(firstobs,lastobs);
15296: andc=vector(firstobs,lastobs);
15297: weight=vector(firstobs,lastobs);
15298: agedc=vector(firstobs,lastobs);
15299: cod=ivector(firstobs,lastobs);
15300: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 15301: num[i]=0;
15302: moisnais[i]=0;
15303: annais[i]=0;
15304: moisdc[i]=0;
15305: andc[i]=0;
15306: agedc[i]=0;
15307: cod[i]=0;
15308: weight[i]=1.0; /* Equal weights, 1 by default */
15309: }
1.290 brouard 15310: mint=matrix(1,maxwav,firstobs,lastobs);
15311: anint=matrix(1,maxwav,firstobs,lastobs);
1.325 brouard 15312: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
1.336 brouard 15313: /* printf("BUG ncovmodel=%d NCOVMAX=%d 2**ncovmodel=%f BUG\n",ncovmodel,NCOVMAX,pow(2,ncovmodel)); */
1.126 brouard 15314: tab=ivector(1,NCOVMAX);
1.144 brouard 15315: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 15316: 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 15317:
1.136 brouard 15318: /* Reads data from file datafile */
15319: if (readdata(datafile, firstobs, lastobs, &imx)==1)
15320: goto end;
15321:
15322: /* Calculation of the number of parameters from char model */
1.234 brouard 15323: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 15324: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
15325: k=3 V4 Tvar[k=3]= 4 (from V4)
15326: k=2 V1 Tvar[k=2]= 1 (from V1)
15327: k=1 Tvar[1]=2 (from V2)
1.234 brouard 15328: */
15329:
15330: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
15331: TvarsDind=ivector(1,NCOVMAX); /* */
1.330 brouard 15332: TnsdVar=ivector(1,NCOVMAX); /* */
1.335 brouard 15333: /* for(i=1; i<=NCOVMAX;i++) TnsdVar[i]=3; */
1.234 brouard 15334: TvarsD=ivector(1,NCOVMAX); /* */
15335: TvarsQind=ivector(1,NCOVMAX); /* */
15336: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 15337: TvarF=ivector(1,NCOVMAX); /* */
15338: TvarFind=ivector(1,NCOVMAX); /* */
15339: TvarV=ivector(1,NCOVMAX); /* */
15340: TvarVind=ivector(1,NCOVMAX); /* */
15341: TvarA=ivector(1,NCOVMAX); /* */
15342: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 15343: TvarFD=ivector(1,NCOVMAX); /* */
15344: TvarFDind=ivector(1,NCOVMAX); /* */
15345: TvarFQ=ivector(1,NCOVMAX); /* */
15346: TvarFQind=ivector(1,NCOVMAX); /* */
15347: TvarVD=ivector(1,NCOVMAX); /* */
15348: TvarVDind=ivector(1,NCOVMAX); /* */
15349: TvarVQ=ivector(1,NCOVMAX); /* */
15350: TvarVQind=ivector(1,NCOVMAX); /* */
1.339 brouard 15351: TvarVV=ivector(1,NCOVMAX); /* */
15352: TvarVVind=ivector(1,NCOVMAX); /* */
1.349 brouard 15353: TvarVVA=ivector(1,NCOVMAX); /* */
15354: TvarVVAind=ivector(1,NCOVMAX); /* */
15355: TvarAVVA=ivector(1,NCOVMAX); /* */
15356: TvarAVVAind=ivector(1,NCOVMAX); /* */
1.231 brouard 15357:
1.230 brouard 15358: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 15359: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 15360: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
15361: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
15362: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.349 brouard 15363: DummyV=ivector(-1,NCOVMAX); /* 1 to 3 */
15364: FixedV=ivector(-1,NCOVMAX); /* 1 to 3 */
15365:
1.137 brouard 15366: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
15367: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
15368: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
15369: */
15370: /* For model-covariate k tells which data-covariate to use but
15371: because this model-covariate is a construction we invent a new column
15372: ncovcol + k1
15373: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
15374: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 15375: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
15376: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 15377: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
15378: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 15379: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 15380: */
1.145 brouard 15381: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
15382: 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 15383: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
15384: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.351 brouard 15385: Tvardk=imatrix(0,NCOVMAX,1,2);
1.145 brouard 15386: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 15387: 4 covariates (3 plus signs)
15388: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
1.328 brouard 15389: */
15390: for(i=1;i<NCOVMAX;i++)
15391: Tage[i]=0;
1.230 brouard 15392: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 15393: * individual dummy, fixed or varying:
15394: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
15395: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 15396: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
15397: * V1 df, V2 qf, V3 & V4 dv, V5 qv
15398: * Tmodelind[1]@9={9,0,3,2,}*/
15399: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
15400: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 15401: * individual quantitative, fixed or varying:
15402: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
15403: * 3, 1, 0, 0, 0, 0, 0, 0},
15404: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.349 brouard 15405:
15406: /* Probably useless zeroes */
15407: for(i=1;i<NCOVMAX;i++){
15408: DummyV[i]=0;
15409: FixedV[i]=0;
15410: }
15411:
15412: for(i=1; i <=ncovcol;i++){
15413: DummyV[i]=0;
15414: FixedV[i]=0;
15415: }
15416: for(i=ncovcol+1; i <=ncovcol+nqv;i++){
15417: DummyV[i]=1;
15418: FixedV[i]=0;
15419: }
15420: for(i=ncovcol+nqv+1; i <=ncovcol+nqv+ntv;i++){
15421: DummyV[i]=0;
15422: FixedV[i]=1;
15423: }
15424: for(i=ncovcol+nqv+ntv+1; i <=ncovcol+nqv+ntv+nqtv;i++){
15425: DummyV[i]=1;
15426: FixedV[i]=1;
15427: }
15428: for(i=1; i <=ncovcol+nqv+ntv+nqtv;i++){
15429: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",i,i,DummyV[i],i,FixedV[i]);
15430: 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]);
15431: }
15432:
15433:
15434:
1.186 brouard 15435: /* Main decodemodel */
15436:
1.187 brouard 15437:
1.223 brouard 15438: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 15439: goto end;
15440:
1.137 brouard 15441: if((double)(lastobs-imx)/(double)imx > 1.10){
15442: nbwarn++;
15443: 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);
15444: 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);
15445: }
1.136 brouard 15446: /* if(mle==1){*/
1.137 brouard 15447: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
15448: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 15449: }
15450:
15451: /*-calculation of age at interview from date of interview and age at death -*/
15452: agev=matrix(1,maxwav,1,imx);
15453:
15454: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
15455: goto end;
15456:
1.126 brouard 15457:
1.136 brouard 15458: agegomp=(int)agemin;
1.290 brouard 15459: free_vector(moisnais,firstobs,lastobs);
15460: free_vector(annais,firstobs,lastobs);
1.126 brouard 15461: /* free_matrix(mint,1,maxwav,1,n);
15462: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 15463: /* free_vector(moisdc,1,n); */
15464: /* free_vector(andc,1,n); */
1.145 brouard 15465: /* */
15466:
1.126 brouard 15467: wav=ivector(1,imx);
1.214 brouard 15468: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
15469: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
15470: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
15471: 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.*/
15472: bh=imatrix(1,lastpass-firstpass+2,1,imx);
15473: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 15474:
15475: /* Concatenates waves */
1.214 brouard 15476: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
15477: Death is a valid wave (if date is known).
15478: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
15479: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
15480: and mw[mi+1][i]. dh depends on stepm.
15481: */
15482:
1.126 brouard 15483: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 15484: /* Concatenates waves */
1.145 brouard 15485:
1.290 brouard 15486: free_vector(moisdc,firstobs,lastobs);
15487: free_vector(andc,firstobs,lastobs);
1.215 brouard 15488:
1.126 brouard 15489: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
15490: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
15491: ncodemax[1]=1;
1.145 brouard 15492: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 15493: cptcoveff=0;
1.220 brouard 15494: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
1.335 brouard 15495: 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 15496: }
15497:
15498: ncovcombmax=pow(2,cptcoveff);
1.338 brouard 15499: invalidvarcomb=ivector(0, ncovcombmax);
15500: for(i=0;i<ncovcombmax;i++)
1.227 brouard 15501: invalidvarcomb[i]=0;
15502:
1.211 brouard 15503: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 15504: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 15505: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 15506:
1.200 brouard 15507: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 15508: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 15509: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 15510: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
15511: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
15512: * (currently 0 or 1) in the data.
15513: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
15514: * corresponding modality (h,j).
15515: */
15516:
1.145 brouard 15517: h=0;
15518: /*if (cptcovn > 0) */
1.126 brouard 15519: m=pow(2,cptcoveff);
15520:
1.144 brouard 15521: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 15522: * For k=4 covariates, h goes from 1 to m=2**k
15523: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
15524: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.329 brouard 15525: * h\k 1 2 3 4 * h-1\k-1 4 3 2 1
15526: *______________________________ *______________________
15527: * 1 i=1 1 i=1 1 i=1 1 i=1 1 * 0 0 0 0 0
15528: * 2 2 1 1 1 * 1 0 0 0 1
15529: * 3 i=2 1 2 1 1 * 2 0 0 1 0
15530: * 4 2 2 1 1 * 3 0 0 1 1
15531: * 5 i=3 1 i=2 1 2 1 * 4 0 1 0 0
15532: * 6 2 1 2 1 * 5 0 1 0 1
15533: * 7 i=4 1 2 2 1 * 6 0 1 1 0
15534: * 8 2 2 2 1 * 7 0 1 1 1
15535: * 9 i=5 1 i=3 1 i=2 1 2 * 8 1 0 0 0
15536: * 10 2 1 1 2 * 9 1 0 0 1
15537: * 11 i=6 1 2 1 2 * 10 1 0 1 0
15538: * 12 2 2 1 2 * 11 1 0 1 1
15539: * 13 i=7 1 i=4 1 2 2 * 12 1 1 0 0
15540: * 14 2 1 2 2 * 13 1 1 0 1
15541: * 15 i=8 1 2 2 2 * 14 1 1 1 0
15542: * 16 2 2 2 2 * 15 1 1 1 1
15543: */
1.212 brouard 15544: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 15545: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
15546: * and the value of each covariate?
15547: * V1=1, V2=1, V3=2, V4=1 ?
15548: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
15549: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
15550: * In order to get the real value in the data, we use nbcode
15551: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
15552: * We are keeping this crazy system in order to be able (in the future?)
15553: * to have more than 2 values (0 or 1) for a covariate.
15554: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
15555: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
15556: * bbbbbbbb
15557: * 76543210
15558: * h-1 00000101 (6-1=5)
1.219 brouard 15559: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 15560: * &
15561: * 1 00000001 (1)
1.219 brouard 15562: * 00000000 = 1 & ((h-1) >> (k-1))
15563: * +1= 00000001 =1
1.211 brouard 15564: *
15565: * h=14, k=3 => h'=h-1=13, k'=k-1=2
15566: * h' 1101 =2^3+2^2+0x2^1+2^0
15567: * >>k' 11
15568: * & 00000001
15569: * = 00000001
15570: * +1 = 00000010=2 = codtabm(14,3)
15571: * Reverse h=6 and m=16?
15572: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
15573: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
15574: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
15575: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
15576: * V3=decodtabm(14,3,2**4)=2
15577: * h'=13 1101 =2^3+2^2+0x2^1+2^0
15578: *(h-1) >> (j-1) 0011 =13 >> 2
15579: * &1 000000001
15580: * = 000000001
15581: * +1= 000000010 =2
15582: * 2211
15583: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
15584: * V3=2
1.220 brouard 15585: * codtabm and decodtabm are identical
1.211 brouard 15586: */
15587:
1.145 brouard 15588:
15589: free_ivector(Ndum,-1,NCOVMAX);
15590:
15591:
1.126 brouard 15592:
1.186 brouard 15593: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 15594: strcpy(optionfilegnuplot,optionfilefiname);
15595: if(mle==-3)
1.201 brouard 15596: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 15597: strcat(optionfilegnuplot,".gp");
15598:
15599: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
15600: printf("Problem with file %s",optionfilegnuplot);
15601: }
15602: else{
1.204 brouard 15603: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 15604: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 15605: //fprintf(ficgp,"set missing 'NaNq'\n");
15606: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 15607: }
15608: /* fclose(ficgp);*/
1.186 brouard 15609:
15610:
15611: /* Initialisation of --------- index.htm --------*/
1.126 brouard 15612:
15613: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
15614: if(mle==-3)
1.201 brouard 15615: strcat(optionfilehtm,"-MORT_");
1.126 brouard 15616: strcat(optionfilehtm,".htm");
15617: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 15618: printf("Problem with %s \n",optionfilehtm);
15619: exit(0);
1.126 brouard 15620: }
15621:
15622: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
15623: strcat(optionfilehtmcov,"-cov.htm");
15624: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
15625: printf("Problem with %s \n",optionfilehtmcov), exit(0);
15626: }
15627: else{
15628: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
15629: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 15630: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 15631: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
15632: }
15633:
1.335 brouard 15634: fprintf(fichtm,"<html><head>\n<meta charset=\"utf-8\"/><meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n\
15635: <title>IMaCh %s</title></head>\n\
15636: <body><font size=\"7\"><a href=http:/euroreves.ined.fr/imach>IMaCh for Interpolated Markov Chain</a> </font><br>\n\
15637: <font size=\"3\">Sponsored by Copyright (C) 2002-2015 <a href=http://www.ined.fr>INED</a>\
15638: -EUROREVES-Institut de longévité-2013-2022-Japan Society for the Promotion of Sciences 日本学術振興会 \
15639: (<a href=https://www.jsps.go.jp/english/e-grants/>Grant-in-Aid for Scientific Research 25293121</a>) - \
15640: <a href=https://software.intel.com/en-us>Intel Software 2015-2018</a></font><br> \n", optionfilehtm);
15641:
15642: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 15643: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 15644: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.337 brouard 15645: 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 15646: \n\
15647: <hr size=\"2\" color=\"#EC5E5E\">\
15648: <ul><li><h4>Parameter files</h4>\n\
15649: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
15650: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
15651: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
15652: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
15653: - Date and time at start: %s</ul>\n",\
1.335 brouard 15654: version,fullversion,optionfilehtm,optionfilehtm,title,datafile,datafile,firstpass,lastpass,stepm, weightopt, model, \
1.126 brouard 15655: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
15656: fileres,fileres,\
15657: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
15658: fflush(fichtm);
15659:
15660: strcpy(pathr,path);
15661: strcat(pathr,optionfilefiname);
1.184 brouard 15662: #ifdef WIN32
15663: _chdir(optionfilefiname); /* Move to directory named optionfile */
15664: #else
1.126 brouard 15665: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 15666: #endif
15667:
1.126 brouard 15668:
1.220 brouard 15669: /* Calculates basic frequencies. Computes observed prevalence at single age
15670: and for any valid combination of covariates
1.126 brouard 15671: and prints on file fileres'p'. */
1.359 brouard 15672: freqsummary(fileres, p, pstart, (double)agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 15673: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 15674:
15675: fprintf(fichtm,"\n");
1.286 brouard 15676: 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 15677: ftol, stepm);
15678: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
15679: ncurrv=1;
15680: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
15681: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
15682: ncurrv=i;
15683: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 15684: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 15685: ncurrv=i;
15686: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 15687: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 15688: ncurrv=i;
15689: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
15690: 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", \
15691: nlstate, ndeath, maxwav, mle, weightopt);
15692:
15693: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
15694: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
15695:
15696:
1.317 brouard 15697: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Number of (used) observations=%d <br>\n\
1.126 brouard 15698: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
15699: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 15700: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 15701: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 15702: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
15703: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
15704: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
15705: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 15706:
1.126 brouard 15707: /* For Powell, parameters are in a vector p[] starting at p[1]
15708: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
15709: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
15710:
15711: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 15712: /* For mortality only */
1.126 brouard 15713: if (mle==-3){
1.136 brouard 15714: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 15715: for(i=1;i<=NDIM;i++)
15716: for(j=1;j<=NDIM;j++)
15717: ximort[i][j]=0.;
1.186 brouard 15718: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 15719: cens=ivector(firstobs,lastobs);
15720: ageexmed=vector(firstobs,lastobs);
15721: agecens=vector(firstobs,lastobs);
15722: dcwave=ivector(firstobs,lastobs);
1.223 brouard 15723:
1.126 brouard 15724: for (i=1; i<=imx; i++){
15725: dcwave[i]=-1;
15726: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 15727: if (s[m][i]>nlstate) {
15728: dcwave[i]=m;
15729: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
15730: break;
15731: }
1.126 brouard 15732: }
1.226 brouard 15733:
1.126 brouard 15734: for (i=1; i<=imx; i++) {
15735: if (wav[i]>0){
1.226 brouard 15736: ageexmed[i]=agev[mw[1][i]][i];
15737: j=wav[i];
15738: agecens[i]=1.;
15739:
15740: if (ageexmed[i]> 1 && wav[i] > 0){
15741: agecens[i]=agev[mw[j][i]][i];
15742: cens[i]= 1;
15743: }else if (ageexmed[i]< 1)
15744: cens[i]= -1;
15745: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
15746: cens[i]=0 ;
1.126 brouard 15747: }
15748: else cens[i]=-1;
15749: }
15750:
15751: for (i=1;i<=NDIM;i++) {
15752: for (j=1;j<=NDIM;j++)
1.226 brouard 15753: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 15754: }
15755:
1.302 brouard 15756: p[1]=0.0268; p[NDIM]=0.083;
15757: /* printf("%lf %lf", p[1], p[2]); */
1.126 brouard 15758:
15759:
1.136 brouard 15760: #ifdef GSL
15761: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 15762: #else
1.359 brouard 15763: printf("Powell-mort\n"); fprintf(ficlog,"Powell-mort\n");
1.136 brouard 15764: #endif
1.201 brouard 15765: strcpy(filerespow,"POW-MORT_");
15766: strcat(filerespow,fileresu);
1.126 brouard 15767: if((ficrespow=fopen(filerespow,"w"))==NULL) {
15768: printf("Problem with resultfile: %s\n", filerespow);
15769: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
15770: }
1.136 brouard 15771: #ifdef GSL
15772: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 15773: #else
1.126 brouard 15774: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 15775: #endif
1.126 brouard 15776: /* for (i=1;i<=nlstate;i++)
15777: for(j=1;j<=nlstate+ndeath;j++)
15778: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
15779: */
15780: fprintf(ficrespow,"\n");
1.136 brouard 15781: #ifdef GSL
15782: /* gsl starts here */
15783: T = gsl_multimin_fminimizer_nmsimplex;
15784: gsl_multimin_fminimizer *sfm = NULL;
15785: gsl_vector *ss, *x;
15786: gsl_multimin_function minex_func;
15787:
15788: /* Initial vertex size vector */
15789: ss = gsl_vector_alloc (NDIM);
15790:
15791: if (ss == NULL){
15792: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
15793: }
15794: /* Set all step sizes to 1 */
15795: gsl_vector_set_all (ss, 0.001);
15796:
15797: /* Starting point */
1.126 brouard 15798:
1.136 brouard 15799: x = gsl_vector_alloc (NDIM);
15800:
15801: if (x == NULL){
15802: gsl_vector_free(ss);
15803: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
15804: }
15805:
15806: /* Initialize method and iterate */
15807: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 15808: /* gsl_vector_set(x, 0, 0.0268); */
15809: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 15810: gsl_vector_set(x, 0, p[1]);
15811: gsl_vector_set(x, 1, p[2]);
15812:
15813: minex_func.f = &gompertz_f;
15814: minex_func.n = NDIM;
15815: minex_func.params = (void *)&p; /* ??? */
15816:
15817: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
15818: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
15819:
15820: printf("Iterations beginning .....\n\n");
15821: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
15822:
15823: iteri=0;
15824: while (rval == GSL_CONTINUE){
15825: iteri++;
15826: status = gsl_multimin_fminimizer_iterate(sfm);
15827:
15828: if (status) printf("error: %s\n", gsl_strerror (status));
15829: fflush(0);
15830:
15831: if (status)
15832: break;
15833:
15834: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
15835: ssval = gsl_multimin_fminimizer_size (sfm);
15836:
15837: if (rval == GSL_SUCCESS)
15838: printf ("converged to a local maximum at\n");
15839:
15840: printf("%5d ", iteri);
15841: for (it = 0; it < NDIM; it++){
15842: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
15843: }
15844: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
15845: }
15846:
15847: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
15848:
15849: gsl_vector_free(x); /* initial values */
15850: gsl_vector_free(ss); /* inital step size */
15851: for (it=0; it<NDIM; it++){
15852: p[it+1]=gsl_vector_get(sfm->x,it);
15853: fprintf(ficrespow," %.12lf", p[it]);
15854: }
15855: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
15856: #endif
15857: #ifdef POWELL
1.361 brouard 15858: #ifdef LINMINORIGINAL
15859: #else /* LINMINORIGINAL */
15860:
15861: flatdir=ivector(1,npar);
15862: for (j=1;j<=npar;j++) flatdir[j]=0;
15863: #endif /*LINMINORIGINAL */
1.362 brouard 15864: /* powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz); */
15865: /* double h0=0.25; */
15866: macheps=pow(16.0,-13.0);
15867: printf("Praxis Gegenfurtner mle=%d\n",mle);
15868: fprintf(ficlog, "Praxis Gegenfurtner mle=%d\n", mle);fflush(ficlog);
15869: /* ffmin = praxis(ftol,macheps, h0, npar, prin, p, gompertz); */
15870: /* For the Gompertz we use only two parameters */
15871: int _npar=2;
15872: ffmin = praxis(ftol,macheps, h0, _npar, 4, p, gompertz);
15873: printf("End Praxis\n");
1.126 brouard 15874: fclose(ficrespow);
1.361 brouard 15875: #ifdef LINMINORIGINAL
15876: #else
15877: free_ivector(flatdir,1,npar);
15878: #endif /* LINMINORIGINAL*/
1.126 brouard 15879:
1.203 brouard 15880: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 15881:
15882: for(i=1; i <=NDIM; i++)
15883: for(j=i+1;j<=NDIM;j++)
1.359 brouard 15884: matcov[i][j]=matcov[j][i];
1.126 brouard 15885:
15886: printf("\nCovariance matrix\n ");
1.203 brouard 15887: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 15888: for(i=1; i <=NDIM; i++) {
15889: for(j=1;j<=NDIM;j++){
1.220 brouard 15890: printf("%f ",matcov[i][j]);
15891: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 15892: }
1.203 brouard 15893: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 15894: }
15895:
15896: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 15897: for (i=1;i<=NDIM;i++) {
1.126 brouard 15898: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 15899: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
15900: }
1.302 brouard 15901: lsurv=vector(agegomp,AGESUP);
15902: lpop=vector(agegomp,AGESUP);
15903: tpop=vector(agegomp,AGESUP);
1.126 brouard 15904: lsurv[agegomp]=100000;
15905:
15906: for (k=agegomp;k<=AGESUP;k++) {
15907: agemortsup=k;
15908: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
15909: }
15910:
15911: for (k=agegomp;k<agemortsup;k++)
15912: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
15913:
15914: for (k=agegomp;k<agemortsup;k++){
15915: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
15916: sumlpop=sumlpop+lpop[k];
15917: }
15918:
15919: tpop[agegomp]=sumlpop;
15920: for (k=agegomp;k<(agemortsup-3);k++){
15921: /* tpop[k+1]=2;*/
15922: tpop[k+1]=tpop[k]-lpop[k];
15923: }
15924:
15925:
15926: printf("\nAge lx qx dx Lx Tx e(x)\n");
15927: for (k=agegomp;k<(agemortsup-2);k++)
15928: 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]);
15929:
15930:
15931: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 15932: ageminpar=50;
15933: agemaxpar=100;
1.194 brouard 15934: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
15935: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
15936: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
15937: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
15938: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
15939: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
15940: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 15941: }else{
15942: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
15943: 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 15944: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 15945: }
1.201 brouard 15946: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 15947: stepm, weightopt,\
15948: model,imx,p,matcov,agemortsup);
15949:
1.302 brouard 15950: free_vector(lsurv,agegomp,AGESUP);
15951: free_vector(lpop,agegomp,AGESUP);
15952: free_vector(tpop,agegomp,AGESUP);
1.220 brouard 15953: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 15954: free_ivector(dcwave,firstobs,lastobs);
15955: free_vector(agecens,firstobs,lastobs);
15956: free_vector(ageexmed,firstobs,lastobs);
15957: free_ivector(cens,firstobs,lastobs);
1.220 brouard 15958: #ifdef GSL
1.136 brouard 15959: #endif
1.186 brouard 15960: } /* Endof if mle==-3 mortality only */
1.205 brouard 15961: /* Standard */
15962: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
15963: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
15964: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 15965: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 15966: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
15967: for (k=1; k<=npar;k++)
15968: printf(" %d %8.5f",k,p[k]);
15969: printf("\n");
1.205 brouard 15970: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
15971: /* mlikeli uses func not funcone */
1.247 brouard 15972: /* for(i=1;i<nlstate;i++){ */
15973: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
15974: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
15975: /* } */
1.205 brouard 15976: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
15977: }
15978: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
15979: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
15980: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
15981: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
15982: }
15983: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 15984: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
15985: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
1.335 brouard 15986: /* exit(0); */
1.126 brouard 15987: for (k=1; k<=npar;k++)
15988: printf(" %d %8.5f",k,p[k]);
15989: printf("\n");
15990:
15991: /*--------- results files --------------*/
1.283 brouard 15992: /* 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 15993:
15994:
15995: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 15996: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); /* Printing model equation */
1.126 brouard 15997: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 15998:
15999: printf("#model= 1 + age ");
16000: fprintf(ficres,"#model= 1 + age ");
16001: fprintf(ficlog,"#model= 1 + age ");
16002: fprintf(fichtm,"\n<ul><li> model=1+age+%s\n \
16003: </ul>", model);
16004:
16005: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">\n");
16006: fprintf(fichtm, "<tr><th>Model=</th><th>1</th><th>+ age</th>");
16007: if(nagesqr==1){
16008: printf(" + age*age ");
16009: fprintf(ficres," + age*age ");
16010: fprintf(ficlog," + age*age ");
16011: fprintf(fichtm, "<th>+ age*age</th>");
16012: }
1.362 brouard 16013: for(j=1;j <=ncovmodel-2-nagesqr;j++){
1.319 brouard 16014: if(Typevar[j]==0) {
16015: printf(" + V%d ",Tvar[j]);
16016: fprintf(ficres," + V%d ",Tvar[j]);
16017: fprintf(ficlog," + V%d ",Tvar[j]);
16018: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
16019: }else if(Typevar[j]==1) {
16020: printf(" + V%d*age ",Tvar[j]);
16021: fprintf(ficres," + V%d*age ",Tvar[j]);
16022: fprintf(ficlog," + V%d*age ",Tvar[j]);
16023: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
16024: }else if(Typevar[j]==2) {
16025: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
16026: fprintf(ficres," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
16027: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
16028: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 16029: }else if(Typevar[j]==3) { /* TO VERIFY */
16030: printf(" + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
16031: fprintf(ficres," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
16032: fprintf(ficlog," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
16033: fprintf(fichtm, "<th>+ V%d*V%d*age</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.319 brouard 16034: }
16035: }
16036: printf("\n");
16037: fprintf(ficres,"\n");
16038: fprintf(ficlog,"\n");
16039: fprintf(fichtm, "</tr>");
16040: fprintf(fichtm, "\n");
16041:
16042:
1.126 brouard 16043: for(i=1,jk=1; i <=nlstate; i++){
16044: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 16045: if (k != i) {
1.319 brouard 16046: fprintf(fichtm, "<tr>");
1.225 brouard 16047: printf("%d%d ",i,k);
16048: fprintf(ficlog,"%d%d ",i,k);
16049: fprintf(ficres,"%1d%1d ",i,k);
1.319 brouard 16050: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 16051: for(j=1; j <=ncovmodel; j++){
16052: printf("%12.7f ",p[jk]);
16053: fprintf(ficlog,"%12.7f ",p[jk]);
16054: fprintf(ficres,"%12.7f ",p[jk]);
1.319 brouard 16055: fprintf(fichtm, "<td>%12.7f</td>",p[jk]);
1.225 brouard 16056: jk++;
16057: }
16058: printf("\n");
16059: fprintf(ficlog,"\n");
16060: fprintf(ficres,"\n");
1.319 brouard 16061: fprintf(fichtm, "</tr>\n");
1.225 brouard 16062: }
1.126 brouard 16063: }
16064: }
1.319 brouard 16065: /* fprintf(fichtm,"</tr>\n"); */
16066: fprintf(fichtm,"</table>\n");
16067: fprintf(fichtm, "\n");
16068:
1.203 brouard 16069: if(mle != 0){
16070: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 16071: ftolhess=ftol; /* Usually correct */
1.203 brouard 16072: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
16073: 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");
16074: 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 16075: 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 16076: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">");
16077: fprintf(fichtm, "\n<tr><th>Model=</th><th>1</th><th>+ age</th>");
16078: if(nagesqr==1){
16079: printf(" + age*age ");
16080: fprintf(ficres," + age*age ");
16081: fprintf(ficlog," + age*age ");
16082: fprintf(fichtm, "<th>+ age*age</th>");
16083: }
1.362 brouard 16084: for(j=1;j <=ncovmodel-2-nagesqr;j++){
1.319 brouard 16085: if(Typevar[j]==0) {
16086: printf(" + V%d ",Tvar[j]);
16087: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
16088: }else if(Typevar[j]==1) {
16089: printf(" + V%d*age ",Tvar[j]);
16090: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
16091: }else if(Typevar[j]==2) {
16092: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 16093: }else if(Typevar[j]==3) { /* TO VERIFY */
16094: fprintf(fichtm, "<th>+ V%d*V%d*age</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.319 brouard 16095: }
16096: }
16097: fprintf(fichtm, "</tr>\n");
16098:
1.203 brouard 16099: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 16100: for(k=1; k <=(nlstate+ndeath); k++){
16101: if (k != i) {
1.319 brouard 16102: fprintf(fichtm, "<tr valign=top>");
1.225 brouard 16103: printf("%d%d ",i,k);
16104: fprintf(ficlog,"%d%d ",i,k);
1.319 brouard 16105: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 16106: for(j=1; j <=ncovmodel; j++){
1.319 brouard 16107: wald=p[jk]/sqrt(matcov[jk][jk]);
1.324 brouard 16108: 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]));
16109: 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 16110: if(fabs(wald) > 1.96){
1.321 brouard 16111: fprintf(fichtm, "<td><b>%12.7f</b></br> (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
1.319 brouard 16112: }else{
16113: fprintf(fichtm, "<td>%12.7f (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
16114: }
1.324 brouard 16115: fprintf(fichtm,"W=%8.3f</br>",wald);
1.319 brouard 16116: 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 16117: jk++;
16118: }
16119: printf("\n");
16120: fprintf(ficlog,"\n");
1.319 brouard 16121: fprintf(fichtm, "</tr>\n");
1.225 brouard 16122: }
16123: }
1.193 brouard 16124: }
1.203 brouard 16125: } /* end of hesscov and Wald tests */
1.319 brouard 16126: fprintf(fichtm,"</table>\n");
1.225 brouard 16127:
1.203 brouard 16128: /* */
1.126 brouard 16129: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
16130: printf("# Scales (for hessian or gradient estimation)\n");
16131: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
16132: for(i=1,jk=1; i <=nlstate; i++){
16133: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 16134: if (j!=i) {
16135: fprintf(ficres,"%1d%1d",i,j);
16136: printf("%1d%1d",i,j);
16137: fprintf(ficlog,"%1d%1d",i,j);
16138: for(k=1; k<=ncovmodel;k++){
16139: printf(" %.5e",delti[jk]);
16140: fprintf(ficlog," %.5e",delti[jk]);
16141: fprintf(ficres," %.5e",delti[jk]);
16142: jk++;
16143: }
16144: printf("\n");
16145: fprintf(ficlog,"\n");
16146: fprintf(ficres,"\n");
16147: }
1.126 brouard 16148: }
16149: }
16150:
16151: 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 16152: if(mle >= 1) /* Too big for the screen */
1.126 brouard 16153: 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");
16154: 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");
16155: /* # 121 Var(a12)\n\ */
16156: /* # 122 Cov(b12,a12) Var(b12)\n\ */
16157: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
16158: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
16159: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
16160: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
16161: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
16162: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
16163:
16164:
16165: /* Just to have a covariance matrix which will be more understandable
16166: even is we still don't want to manage dictionary of variables
16167: */
16168: for(itimes=1;itimes<=2;itimes++){
16169: jj=0;
16170: for(i=1; i <=nlstate; i++){
1.225 brouard 16171: for(j=1; j <=nlstate+ndeath; j++){
16172: if(j==i) continue;
16173: for(k=1; k<=ncovmodel;k++){
16174: jj++;
16175: ca[0]= k+'a'-1;ca[1]='\0';
16176: if(itimes==1){
16177: if(mle>=1)
16178: printf("#%1d%1d%d",i,j,k);
16179: fprintf(ficlog,"#%1d%1d%d",i,j,k);
16180: fprintf(ficres,"#%1d%1d%d",i,j,k);
16181: }else{
16182: if(mle>=1)
16183: printf("%1d%1d%d",i,j,k);
16184: fprintf(ficlog,"%1d%1d%d",i,j,k);
16185: fprintf(ficres,"%1d%1d%d",i,j,k);
16186: }
16187: ll=0;
16188: for(li=1;li <=nlstate; li++){
16189: for(lj=1;lj <=nlstate+ndeath; lj++){
16190: if(lj==li) continue;
16191: for(lk=1;lk<=ncovmodel;lk++){
16192: ll++;
16193: if(ll<=jj){
16194: cb[0]= lk +'a'-1;cb[1]='\0';
16195: if(ll<jj){
16196: if(itimes==1){
16197: if(mle>=1)
16198: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
16199: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
16200: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
16201: }else{
16202: if(mle>=1)
16203: printf(" %.5e",matcov[jj][ll]);
16204: fprintf(ficlog," %.5e",matcov[jj][ll]);
16205: fprintf(ficres," %.5e",matcov[jj][ll]);
16206: }
16207: }else{
16208: if(itimes==1){
16209: if(mle>=1)
16210: printf(" Var(%s%1d%1d)",ca,i,j);
16211: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
16212: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
16213: }else{
16214: if(mle>=1)
16215: printf(" %.7e",matcov[jj][ll]);
16216: fprintf(ficlog," %.7e",matcov[jj][ll]);
16217: fprintf(ficres," %.7e",matcov[jj][ll]);
16218: }
16219: }
16220: }
16221: } /* end lk */
16222: } /* end lj */
16223: } /* end li */
16224: if(mle>=1)
16225: printf("\n");
16226: fprintf(ficlog,"\n");
16227: fprintf(ficres,"\n");
16228: numlinepar++;
16229: } /* end k*/
16230: } /*end j */
1.126 brouard 16231: } /* end i */
16232: } /* end itimes */
16233:
16234: fflush(ficlog);
16235: fflush(ficres);
1.225 brouard 16236: while(fgets(line, MAXLINE, ficpar)) {
16237: /* If line starts with a # it is a comment */
16238: if (line[0] == '#') {
16239: numlinepar++;
16240: fputs(line,stdout);
16241: fputs(line,ficparo);
16242: fputs(line,ficlog);
1.299 brouard 16243: fputs(line,ficres);
1.225 brouard 16244: continue;
16245: }else
16246: break;
16247: }
16248:
1.209 brouard 16249: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
16250: /* ungetc(c,ficpar); */
16251: /* fgets(line, MAXLINE, ficpar); */
16252: /* fputs(line,stdout); */
16253: /* fputs(line,ficparo); */
16254: /* } */
16255: /* ungetc(c,ficpar); */
1.126 brouard 16256:
16257: estepm=0;
1.209 brouard 16258: 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 16259:
16260: if (num_filled != 6) {
16261: 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);
16262: 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);
16263: goto end;
16264: }
16265: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
16266: }
16267: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
16268: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
16269:
1.209 brouard 16270: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 16271: if (estepm==0 || estepm < stepm) estepm=stepm;
16272: if (fage <= 2) {
16273: bage = ageminpar;
16274: fage = agemaxpar;
16275: }
16276:
16277: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 16278: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
16279: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 16280:
1.186 brouard 16281: /* Other stuffs, more or less useful */
1.254 brouard 16282: while(fgets(line, MAXLINE, ficpar)) {
16283: /* If line starts with a # it is a comment */
16284: if (line[0] == '#') {
16285: numlinepar++;
16286: fputs(line,stdout);
16287: fputs(line,ficparo);
16288: fputs(line,ficlog);
1.299 brouard 16289: fputs(line,ficres);
1.254 brouard 16290: continue;
16291: }else
16292: break;
16293: }
16294:
16295: 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){
16296:
16297: if (num_filled != 7) {
16298: 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);
16299: 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);
16300: goto end;
16301: }
16302: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
16303: 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);
16304: 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);
16305: 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 16306: }
1.254 brouard 16307:
16308: while(fgets(line, MAXLINE, ficpar)) {
16309: /* If line starts with a # it is a comment */
16310: if (line[0] == '#') {
16311: numlinepar++;
16312: fputs(line,stdout);
16313: fputs(line,ficparo);
16314: fputs(line,ficlog);
1.299 brouard 16315: fputs(line,ficres);
1.254 brouard 16316: continue;
16317: }else
16318: break;
1.126 brouard 16319: }
16320:
16321:
16322: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
16323: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
16324:
1.254 brouard 16325: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
16326: if (num_filled != 1) {
16327: 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);
16328: 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);
16329: goto end;
16330: }
16331: printf("pop_based=%d\n",popbased);
16332: fprintf(ficlog,"pop_based=%d\n",popbased);
16333: fprintf(ficparo,"pop_based=%d\n",popbased);
16334: fprintf(ficres,"pop_based=%d\n",popbased);
16335: }
16336:
1.258 brouard 16337: /* Results */
1.359 brouard 16338: /* Value of covariate in each resultine will be computed (if product) and sorted according to model rank */
1.332 brouard 16339: /* It is precov[] because we need the varying age in order to compute the real cov[] of the model equation */
16340: precov=matrix(1,MAXRESULTLINESPONE,1,NCOVMAX+1);
1.307 brouard 16341: endishere=0;
1.258 brouard 16342: nresult=0;
1.308 brouard 16343: parameterline=0;
1.258 brouard 16344: do{
16345: if(!fgets(line, MAXLINE, ficpar)){
16346: endishere=1;
1.308 brouard 16347: parameterline=15;
1.258 brouard 16348: }else if (line[0] == '#') {
16349: /* If line starts with a # it is a comment */
1.254 brouard 16350: numlinepar++;
16351: fputs(line,stdout);
16352: fputs(line,ficparo);
16353: fputs(line,ficlog);
1.299 brouard 16354: fputs(line,ficres);
1.254 brouard 16355: continue;
1.258 brouard 16356: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
16357: parameterline=11;
1.296 brouard 16358: else if(sscanf(line,"prevbackcast=%[^\n]\n",modeltemp))
1.258 brouard 16359: parameterline=12;
1.307 brouard 16360: else if(sscanf(line,"result:%[^\n]\n",modeltemp)){
1.258 brouard 16361: parameterline=13;
1.307 brouard 16362: }
1.258 brouard 16363: else{
16364: parameterline=14;
1.254 brouard 16365: }
1.308 brouard 16366: switch (parameterline){ /* =0 only if only comments */
1.258 brouard 16367: case 11:
1.296 brouard 16368: 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)){
16369: 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 16370: 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);
16371: 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);
16372: 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);
16373: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 16374: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
16375: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
1.296 brouard 16376: prvforecast = 1;
16377: }
16378: else if((num_filled=sscanf(line,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",&prevfcast,&yrfproj,&mobilavproj)) !=EOF){/* && (num_filled == 3))*/
1.313 brouard 16379: printf("prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
16380: fprintf(ficlog,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
16381: fprintf(ficres,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
1.296 brouard 16382: prvforecast = 2;
16383: }
16384: else {
16385: 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);
16386: 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);
16387: goto end;
1.258 brouard 16388: }
1.254 brouard 16389: break;
1.258 brouard 16390: case 12:
1.296 brouard 16391: 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)){
16392: 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);
16393: 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);
16394: 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);
16395: 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);
16396: /* day and month of back2 are not used but only year anback2.*/
1.273 brouard 16397: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
16398: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.296 brouard 16399: prvbackcast = 1;
16400: }
16401: else if((num_filled=sscanf(line,"prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",&prevbcast,&yrbproj,&mobilavproj)) ==3){/* && (num_filled == 3))*/
1.313 brouard 16402: printf("prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
16403: fprintf(ficlog,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
16404: fprintf(ficres,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
1.296 brouard 16405: prvbackcast = 2;
16406: }
16407: else {
16408: 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);
16409: 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);
16410: goto end;
1.258 brouard 16411: }
1.230 brouard 16412: break;
1.258 brouard 16413: case 13:
1.332 brouard 16414: num_filled=sscanf(line,"result:%[^\n]\n",resultlineori);
1.307 brouard 16415: nresult++; /* Sum of resultlines */
1.342 brouard 16416: /* printf("Result %d: result:%s\n",nresult, resultlineori); */
1.332 brouard 16417: /* removefirstspace(&resultlineori); */
16418:
16419: if(strstr(resultlineori,"v") !=0){
16420: printf("Error. 'v' must be in upper case 'V' result: %s ",resultlineori);
16421: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultlineori);fflush(ficlog);
16422: return 1;
16423: }
16424: trimbb(resultline, resultlineori); /* Suppressing double blank in the resultline */
1.342 brouard 16425: /* printf("Decoderesult resultline=\"%s\" resultlineori=\"%s\"\n", resultline, resultlineori); */
1.318 brouard 16426: if(nresult > MAXRESULTLINESPONE-1){
16427: 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);
16428: 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 16429: goto end;
16430: }
1.332 brouard 16431:
1.310 brouard 16432: if(!decoderesult(resultline, nresult)){ /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
1.314 brouard 16433: fprintf(ficparo,"result: %s\n",resultline);
16434: fprintf(ficres,"result: %s\n",resultline);
16435: fprintf(ficlog,"result: %s\n",resultline);
1.310 brouard 16436: } else
16437: goto end;
1.307 brouard 16438: break;
16439: case 14:
16440: printf("Error: Unknown command '%s'\n",line);
16441: fprintf(ficlog,"Error: Unknown command '%s'\n",line);
1.314 brouard 16442: if(line[0] == ' ' || line[0] == '\n'){
16443: printf("It should not be an empty line '%s'\n",line);
16444: fprintf(ficlog,"It should not be an empty line '%s'\n",line);
16445: }
1.307 brouard 16446: if(ncovmodel >=2 && nresult==0 ){
16447: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
16448: fprintf(ficlog,"ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 16449: }
1.307 brouard 16450: /* goto end; */
16451: break;
1.308 brouard 16452: case 15:
16453: printf("End of resultlines.\n");
16454: fprintf(ficlog,"End of resultlines.\n");
16455: break;
16456: default: /* parameterline =0 */
1.307 brouard 16457: nresult=1;
16458: decoderesult(".",nresult ); /* No covariate */
1.258 brouard 16459: } /* End switch parameterline */
16460: }while(endishere==0); /* End do */
1.126 brouard 16461:
1.230 brouard 16462: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 16463: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 16464:
16465: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 16466: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 16467: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 16468: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
16469: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 16470: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 16471: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
16472: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 16473: }else{
1.270 brouard 16474: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
1.296 brouard 16475: /* It seems that anprojd which is computed from the mean year at interview which is known yet because of freqsummary */
16476: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */ /* Done in freqsummary */
16477: if(prvforecast==1){
16478: dateprojd=(jproj1+12*mproj1+365*anproj1)/365;
16479: jprojd=jproj1;
16480: mprojd=mproj1;
16481: anprojd=anproj1;
16482: dateprojf=(jproj2+12*mproj2+365*anproj2)/365;
16483: jprojf=jproj2;
16484: mprojf=mproj2;
16485: anprojf=anproj2;
16486: } else if(prvforecast == 2){
16487: dateprojd=dateintmean;
16488: date2dmy(dateprojd,&jprojd, &mprojd, &anprojd);
16489: dateprojf=dateintmean+yrfproj;
16490: date2dmy(dateprojf,&jprojf, &mprojf, &anprojf);
16491: }
16492: if(prvbackcast==1){
16493: datebackd=(jback1+12*mback1+365*anback1)/365;
16494: jbackd=jback1;
16495: mbackd=mback1;
16496: anbackd=anback1;
16497: datebackf=(jback2+12*mback2+365*anback2)/365;
16498: jbackf=jback2;
16499: mbackf=mback2;
16500: anbackf=anback2;
16501: } else if(prvbackcast == 2){
16502: datebackd=dateintmean;
16503: date2dmy(datebackd,&jbackd, &mbackd, &anbackd);
16504: datebackf=dateintmean-yrbproj;
16505: date2dmy(datebackf,&jbackf, &mbackf, &anbackf);
16506: }
16507:
1.350 brouard 16508: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage);/* HERE valgrind Tvard*/
1.220 brouard 16509: }
16510: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.296 brouard 16511: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,prevbcast, estepm, \
16512: jprev1,mprev1,anprev1,dateprev1, dateprojd, datebackd,jprev2,mprev2,anprev2,dateprev2,dateprojf, datebackf);
1.220 brouard 16513:
1.225 brouard 16514: /*------------ free_vector -------------*/
16515: /* chdir(path); */
1.220 brouard 16516:
1.215 brouard 16517: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
16518: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
16519: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
16520: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 16521: free_lvector(num,firstobs,lastobs);
16522: free_vector(agedc,firstobs,lastobs);
1.126 brouard 16523: /*free_matrix(covar,0,NCOVMAX,1,n);*/
16524: /*free_matrix(covar,1,NCOVMAX,1,n);*/
16525: fclose(ficparo);
16526: fclose(ficres);
1.220 brouard 16527:
16528:
1.186 brouard 16529: /* Other results (useful)*/
1.220 brouard 16530:
16531:
1.126 brouard 16532: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 16533: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
16534: prlim=matrix(1,nlstate,1,nlstate);
1.332 brouard 16535: /* Computes the prevalence limit for each combination k of the dummy covariates by calling prevalim(k) */
1.209 brouard 16536: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 16537: fclose(ficrespl);
16538:
16539: /*------------- h Pij x at various ages ------------*/
1.180 brouard 16540: /*#include "hpijx.h"*/
1.332 brouard 16541: /** 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?*/
16542: /* calls hpxij with combination k */
1.180 brouard 16543: hPijx(p, bage, fage);
1.145 brouard 16544: fclose(ficrespij);
1.227 brouard 16545:
1.220 brouard 16546: /* ncovcombmax= pow(2,cptcoveff); */
1.332 brouard 16547: /*-------------- Variance of one-step probabilities for a combination ij or for nres ?---*/
1.145 brouard 16548: k=1;
1.126 brouard 16549: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 16550:
1.269 brouard 16551: /* Prevalence for each covariate combination in probs[age][status][cov] */
16552: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
16553: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 16554: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 16555: for(k=1;k<=ncovcombmax;k++)
16556: probs[i][j][k]=0.;
1.269 brouard 16557: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
16558: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 16559: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 16560: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
16561: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 16562: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 16563: for(k=1;k<=ncovcombmax;k++)
16564: mobaverages[i][j][k]=0.;
1.219 brouard 16565: mobaverage=mobaverages;
16566: if (mobilav!=0) {
1.235 brouard 16567: printf("Movingaveraging observed prevalence\n");
1.258 brouard 16568: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 16569: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
16570: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
16571: printf(" Error in movingaverage mobilav=%d\n",mobilav);
16572: }
1.269 brouard 16573: } else if (mobilavproj !=0) {
1.235 brouard 16574: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 16575: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 16576: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
16577: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
16578: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
16579: }
1.269 brouard 16580: }else{
16581: printf("Internal error moving average\n");
16582: fflush(stdout);
16583: exit(1);
1.219 brouard 16584: }
16585: }/* end if moving average */
1.227 brouard 16586:
1.126 brouard 16587: /*---------- Forecasting ------------------*/
1.296 brouard 16588: if(prevfcast==1){
16589: /* /\* if(stepm ==1){*\/ */
16590: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
16591: /*This done previously after freqsummary.*/
16592: /* dateprojd=(jproj1+12*mproj1+365*anproj1)/365; */
16593: /* dateprojf=(jproj2+12*mproj2+365*anproj2)/365; */
16594:
16595: /* } else if (prvforecast==2){ */
16596: /* /\* if(stepm ==1){*\/ */
16597: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
16598: /* } */
16599: /*prevforecast(fileresu, dateintmean, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);*/
16600: prevforecast(fileresu,dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, p, cptcoveff);
1.126 brouard 16601: }
1.269 brouard 16602:
1.296 brouard 16603: /* Prevbcasting */
16604: if(prevbcast==1){
1.219 brouard 16605: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
16606: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
16607: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
16608:
16609: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
16610:
16611: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 16612:
1.219 brouard 16613: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
16614: fclose(ficresplb);
16615:
1.222 brouard 16616: hBijx(p, bage, fage, mobaverage);
16617: fclose(ficrespijb);
1.219 brouard 16618:
1.296 brouard 16619: /* /\* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, *\/ */
16620: /* /\* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); *\/ */
16621: /* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, */
16622: /* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
16623: prevbackforecast(fileresu, mobaverage, dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2,
16624: mobilavproj, bage, fage, firstpass, lastpass, p, cptcoveff);
16625:
16626:
1.269 brouard 16627: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 16628:
16629:
1.269 brouard 16630: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 16631: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
16632: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
16633: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.296 brouard 16634: } /* end Prevbcasting */
1.268 brouard 16635:
1.186 brouard 16636:
16637: /* ------ Other prevalence ratios------------ */
1.126 brouard 16638:
1.215 brouard 16639: free_ivector(wav,1,imx);
16640: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
16641: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
16642: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 16643:
16644:
1.127 brouard 16645: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 16646:
1.201 brouard 16647: strcpy(filerese,"E_");
16648: strcat(filerese,fileresu);
1.126 brouard 16649: if((ficreseij=fopen(filerese,"w"))==NULL) {
16650: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
16651: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
16652: }
1.208 brouard 16653: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
16654: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 16655:
16656: pstamp(ficreseij);
1.219 brouard 16657:
1.351 brouard 16658: /* i1=pow(2,cptcoveff); /\* Number of combination of dummy covariates *\/ */
16659: /* if (cptcovn < 1){i1=1;} */
1.235 brouard 16660:
1.351 brouard 16661: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
16662: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
16663: /* if(i1 != 1 && TKresult[nres]!= k) */
16664: /* continue; */
1.219 brouard 16665: fprintf(ficreseij,"\n#****** ");
1.235 brouard 16666: printf("\n#****** ");
1.351 brouard 16667: for(j=1;j<=cptcovs;j++){
16668: /* for(j=1;j<=cptcoveff;j++) { */
16669: /* fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
16670: fprintf(ficreseij," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
16671: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
16672: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.235 brouard 16673: }
16674: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.337 brouard 16675: printf(" V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]); /* TvarsQ[j] gives the name of the jth quantitative (fixed or time v) */
16676: fprintf(ficreseij,"V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]);
1.219 brouard 16677: }
16678: fprintf(ficreseij,"******\n");
1.235 brouard 16679: printf("******\n");
1.219 brouard 16680:
16681: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
16682: oldm=oldms;savm=savms;
1.330 brouard 16683: /* 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 16684: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 16685:
1.219 brouard 16686: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 16687: }
16688: fclose(ficreseij);
1.208 brouard 16689: printf("done evsij\n");fflush(stdout);
16690: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 16691:
1.218 brouard 16692:
1.227 brouard 16693: /*---------- State-specific expectancies and variances ------------*/
1.336 brouard 16694: /* Should be moved in a function */
1.201 brouard 16695: strcpy(filerest,"T_");
16696: strcat(filerest,fileresu);
1.127 brouard 16697: if((ficrest=fopen(filerest,"w"))==NULL) {
16698: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
16699: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
16700: }
1.208 brouard 16701: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
16702: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 16703: strcpy(fileresstde,"STDE_");
16704: strcat(fileresstde,fileresu);
1.126 brouard 16705: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 16706: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
16707: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 16708: }
1.227 brouard 16709: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
16710: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 16711:
1.201 brouard 16712: strcpy(filerescve,"CVE_");
16713: strcat(filerescve,fileresu);
1.126 brouard 16714: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 16715: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
16716: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 16717: }
1.227 brouard 16718: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
16719: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 16720:
1.201 brouard 16721: strcpy(fileresv,"V_");
16722: strcat(fileresv,fileresu);
1.126 brouard 16723: if((ficresvij=fopen(fileresv,"w"))==NULL) {
16724: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
16725: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
16726: }
1.227 brouard 16727: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
16728: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 16729:
1.235 brouard 16730: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
16731: if (cptcovn < 1){i1=1;}
16732:
1.334 brouard 16733: for(nres=1; nres <= nresult; nres++) /* For each resultline, find the combination and output results according to the values of dummies and then quanti. */
16734: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying. For each nres and each value at position k
16735: * we know Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline
16736: * Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline
16737: * and Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
16738: /* */
16739: 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 16740: continue;
1.359 brouard 16741: printf("\n# model=1+age+%s \n#****** Result for:", model); /* HERE model is empty */
16742: fprintf(ficrest,"\n# model=1+age+%s \n#****** Result for:", model);
16743: fprintf(ficlog,"\n# model=1+age+%s \n#****** Result for:", model);
1.334 brouard 16744: /* It might not be a good idea to mix dummies and quantitative */
16745: /* 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 *\/ */
16746: 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 */
16747: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /\* Output by variables in the resultline *\/ */
16748: /* Tvaraff[j] is the name of the dummy variable in position j in the equation model:
16749: * Tvaraff[1]@9={4, 3, 0, 0, 0, 0, 0, 0, 0}, in model=V5+V4+V3+V4*V3+V5*age
16750: * (V5 is quanti) V4 and V3 are dummies
16751: * TnsdVar[4] is the position 1 and TnsdVar[3]=2 in codtabm(k,l)(V4 V3)=V4 V3
16752: * l=1 l=2
16753: * k=1 1 1 0 0
16754: * k=2 2 1 1 0
16755: * k=3 [1] [2] 0 1
16756: * k=4 2 2 1 1
16757: * If nres=1 result: V3=1 V4=0 then k=3 and outputs
16758: * If nres=2 result: V4=1 V3=0 then k=2 and outputs
16759: * nres=1 =>k=3 j=1 V4= nbcode[4][codtabm(3,1)=1)=0; j=2 V3= nbcode[3][codtabm(3,2)=2]=1
16760: * nres=2 =>k=2 j=1 V4= nbcode[4][codtabm(2,1)=2)=1; j=2 V3= nbcode[3][codtabm(2,2)=1]=0
16761: */
16762: /* Tvresult[nres][j] Name of the variable at position j in this resultline */
16763: /* Tresult[nres][j] Value of this variable at position j could be a float if quantitative */
16764: /* We give up with the combinations!! */
1.342 brouard 16765: /* if(debugILK) */
16766: /* 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 16767:
16768: 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 16769: /* 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] */
16770: 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 */
16771: 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 */
16772: 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 16773: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
16774: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
16775: }else{
16776: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
16777: }
16778: /* fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
16779: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
16780: }else if(Dummy[modelresult[nres][j]]==1){ /* Quanti variable */
16781: /* For each selected (single) quantitative value */
1.337 brouard 16782: printf(" V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
16783: fprintf(ficlog," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
16784: fprintf(ficrest," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
1.334 brouard 16785: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
16786: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
16787: }else{
16788: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
16789: }
16790: }else{
16791: 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 */
16792: 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 */
16793: exit(1);
16794: }
1.335 brouard 16795: } /* End loop for each variable in the resultline */
1.334 brouard 16796: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
16797: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /\* Wrong j is not in the equation model *\/ */
16798: /* fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
16799: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
16800: /* } */
1.208 brouard 16801: fprintf(ficrest,"******\n");
1.227 brouard 16802: fprintf(ficlog,"******\n");
16803: printf("******\n");
1.208 brouard 16804:
16805: fprintf(ficresstdeij,"\n#****** ");
16806: fprintf(ficrescveij,"\n#****** ");
1.337 brouard 16807: /* It could have been: for(j=1;j<=cptcoveff;j++) {printf("V=%d=%lg",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);} */
16808: /* But it won't be sorted and depends on how the resultline is ordered */
1.225 brouard 16809: for(j=1;j<=cptcoveff;j++) {
1.334 brouard 16810: fprintf(ficresstdeij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
16811: /* fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
16812: /* fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
16813: }
16814: 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 16815: fprintf(ficresstdeij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
16816: fprintf(ficrescveij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
1.235 brouard 16817: }
1.208 brouard 16818: fprintf(ficresstdeij,"******\n");
16819: fprintf(ficrescveij,"******\n");
16820:
16821: fprintf(ficresvij,"\n#****** ");
1.238 brouard 16822: /* pstamp(ficresvij); */
1.225 brouard 16823: for(j=1;j<=cptcoveff;j++)
1.335 brouard 16824: fprintf(ficresvij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
16825: /* fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[TnsdVar[Tvaraff[j]]])]); */
1.235 brouard 16826: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.332 brouard 16827: /* fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); /\* To solve *\/ */
1.337 brouard 16828: fprintf(ficresvij," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /* Solved */
1.235 brouard 16829: }
1.208 brouard 16830: fprintf(ficresvij,"******\n");
16831:
16832: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
16833: oldm=oldms;savm=savms;
1.235 brouard 16834: printf(" cvevsij ");
16835: fprintf(ficlog, " cvevsij ");
16836: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 16837: printf(" end cvevsij \n ");
16838: fprintf(ficlog, " end cvevsij \n ");
16839:
16840: /*
16841: */
16842: /* goto endfree; */
16843:
16844: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
16845: pstamp(ficrest);
16846:
1.269 brouard 16847: epj=vector(1,nlstate+1);
1.208 brouard 16848: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 16849: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
16850: cptcod= 0; /* To be deleted */
1.360 brouard 16851: printf("varevsij vpopbased=%d popbased=%d \n",vpopbased,popbased);
16852: fprintf(ficlog, "varevsij vpopbased=%d popbased=%d \n",vpopbased,popbased);
1.361 brouard 16853: /* 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 */
16854: /* Depending of popbased which changes the prevalences, either cross-sectional or period */
1.235 brouard 16855: 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 16856: fprintf(ficrest,"# Total life expectancy with std error and decomposition into time to be expected in each state\n\
16857: # (these are weighted average of eij where weights are ");
1.227 brouard 16858: if(vpopbased==1)
1.360 brouard 16859: 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 16860: else
1.360 brouard 16861: fprintf(ficrest,"the age specific forward period (stable) prevalences in each state) \n");
16862: fprintf(ficrest,"# with proportions of time spent in each state with standard error (on the right of the table.\n ");
1.335 brouard 16863: fprintf(ficrest,"# Age popbased mobilav e.. (std) "); /* Adding covariate values? */
1.227 brouard 16864: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
1.360 brouard 16865: for (i=1;i<=nlstate;i++) fprintf(ficrest," %% e.%d/e.. (std) ",i);
1.227 brouard 16866: fprintf(ficrest,"\n");
16867: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 16868: printf("Computing age specific forward period (stable) prevalences in each health state \n");
16869: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 16870: for(age=bage; age <=fage ;age++){
1.235 brouard 16871: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 16872: if (vpopbased==1) {
16873: if(mobilav ==0){
16874: for(i=1; i<=nlstate;i++)
16875: prlim[i][i]=probs[(int)age][i][k];
16876: }else{ /* mobilav */
16877: for(i=1; i<=nlstate;i++)
16878: prlim[i][i]=mobaverage[(int)age][i][k];
16879: }
16880: }
1.219 brouard 16881:
1.227 brouard 16882: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
16883: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
16884: /* printf(" age %4.0f ",age); */
16885: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
16886: for(i=1, epj[j]=0.;i <=nlstate;i++) {
16887: epj[j] += prlim[i][i]*eij[i][j][(int)age];
16888: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
16889: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
16890: }
1.361 brouard 16891: epj[nlstate+1] +=epj[j]; /* epp=sum_j epj = sum_j sum_i w_i e_ij */
1.227 brouard 16892: }
16893: /* printf(" age %4.0f \n",age); */
1.219 brouard 16894:
1.361 brouard 16895: for(i=1, vepp=0.;i <=nlstate;i++) /* Variance of total life expectancy e.. */
1.227 brouard 16896: for(j=1;j <=nlstate;j++)
1.361 brouard 16897: vepp += vareij[i][j][(int)age]; /* sum_i sum_j cov(e.i, e.j) = var(e..) */
1.227 brouard 16898: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
1.361 brouard 16899: /* vareij[i][j] is the covariance cov(e.i, e.j) and vareij[j][j] is the variance of e.j */
1.227 brouard 16900: for(j=1;j <=nlstate;j++){
16901: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
16902: }
1.360 brouard 16903: /* And proportion of time spent in state j */
16904: /* $$ E[r(X,Y)-E(r(X,Y))]^2=[\frac{1}{\mu_y} -\frac{\mu_x}{{\mu_y}^2}]' Var(X,Y)[\frac{1}{\mu_y} -\frac{\mu_x}{{\mu_y}^2}]$$ */
1.361 brouard 16905: /* \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}) */
16906: /* \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})*/
16907: /*\mu_x = epj[j], \sigma^2_x = vareij[j][j][(int)age] and \mu_y=epj[nlstate+1], \sigma^2_y=vepp \sigmaxy= */
16908: /* vareij[j][j][(int)age]/epj[nlstate+1]^2 + vepp/epj[nlstate+1]^4 */
1.360 brouard 16909: for(j=1;j <=nlstate;j++){
16910: /* 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 16911: /* 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] )); */
16912:
16913: 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) */
16914: stdpercent += vareij[i][j][(int)age];
16915: }
16916: 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]);
16917: /* 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 */
16918: /* 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] )); */
16919: fprintf(ficrest," %7.3f (%7.3f)", epj[j]/epj[nlstate+1], sqrt(stdpercent));
1.360 brouard 16920: }
1.227 brouard 16921: fprintf(ficrest,"\n");
16922: }
1.208 brouard 16923: } /* End vpopbased */
1.269 brouard 16924: free_vector(epj,1,nlstate+1);
1.208 brouard 16925: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
16926: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 16927: printf("done selection\n");fflush(stdout);
16928: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 16929:
1.335 brouard 16930: } /* End k selection or end covariate selection for nres */
1.227 brouard 16931:
16932: printf("done State-specific expectancies\n");fflush(stdout);
16933: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
16934:
1.335 brouard 16935: /* variance-covariance of forward period prevalence */
1.269 brouard 16936: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 16937:
1.227 brouard 16938:
1.290 brouard 16939: free_vector(weight,firstobs,lastobs);
1.351 brouard 16940: free_imatrix(Tvardk,0,NCOVMAX,1,2);
1.227 brouard 16941: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 16942: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
16943: free_matrix(anint,1,maxwav,firstobs,lastobs);
16944: free_matrix(mint,1,maxwav,firstobs,lastobs);
16945: free_ivector(cod,firstobs,lastobs);
1.227 brouard 16946: free_ivector(tab,1,NCOVMAX);
16947: fclose(ficresstdeij);
16948: fclose(ficrescveij);
16949: fclose(ficresvij);
16950: fclose(ficrest);
16951: fclose(ficpar);
16952:
16953:
1.126 brouard 16954: /*---------- End : free ----------------*/
1.219 brouard 16955: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 16956: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
16957: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 16958: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
16959: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 16960: } /* mle==-3 arrives here for freeing */
1.227 brouard 16961: /* endfree:*/
1.359 brouard 16962: if(mle!=-3) free_matrix(precov, 1,MAXRESULTLINESPONE,1,NCOVMAX+1); /* Could be elsewhere ?*/
1.227 brouard 16963: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
16964: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
16965: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.341 brouard 16966: /* if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs); */
16967: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs);
1.290 brouard 16968: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
16969: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
16970: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 16971: free_matrix(matcov,1,npar,1,npar);
16972: free_matrix(hess,1,npar,1,npar);
16973: /*free_vector(delti,1,npar);*/
16974: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
16975: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 16976: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 16977: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
16978:
16979: free_ivector(ncodemax,1,NCOVMAX);
16980: free_ivector(ncodemaxwundef,1,NCOVMAX);
16981: free_ivector(Dummy,-1,NCOVMAX);
16982: free_ivector(Fixed,-1,NCOVMAX);
1.349 brouard 16983: free_ivector(DummyV,-1,NCOVMAX);
16984: free_ivector(FixedV,-1,NCOVMAX);
1.227 brouard 16985: free_ivector(Typevar,-1,NCOVMAX);
16986: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 16987: free_ivector(TvarsQ,1,NCOVMAX);
16988: free_ivector(TvarsQind,1,NCOVMAX);
16989: free_ivector(TvarsD,1,NCOVMAX);
1.330 brouard 16990: free_ivector(TnsdVar,1,NCOVMAX);
1.234 brouard 16991: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 16992: free_ivector(TvarFD,1,NCOVMAX);
16993: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 16994: free_ivector(TvarF,1,NCOVMAX);
16995: free_ivector(TvarFind,1,NCOVMAX);
16996: free_ivector(TvarV,1,NCOVMAX);
16997: free_ivector(TvarVind,1,NCOVMAX);
16998: free_ivector(TvarA,1,NCOVMAX);
16999: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 17000: free_ivector(TvarFQ,1,NCOVMAX);
17001: free_ivector(TvarFQind,1,NCOVMAX);
17002: free_ivector(TvarVD,1,NCOVMAX);
17003: free_ivector(TvarVDind,1,NCOVMAX);
17004: free_ivector(TvarVQ,1,NCOVMAX);
17005: free_ivector(TvarVQind,1,NCOVMAX);
1.349 brouard 17006: free_ivector(TvarAVVA,1,NCOVMAX);
17007: free_ivector(TvarAVVAind,1,NCOVMAX);
17008: free_ivector(TvarVVA,1,NCOVMAX);
17009: free_ivector(TvarVVAind,1,NCOVMAX);
1.339 brouard 17010: free_ivector(TvarVV,1,NCOVMAX);
17011: free_ivector(TvarVVind,1,NCOVMAX);
17012:
1.230 brouard 17013: free_ivector(Tvarsel,1,NCOVMAX);
17014: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 17015: free_ivector(Tposprod,1,NCOVMAX);
17016: free_ivector(Tprod,1,NCOVMAX);
17017: free_ivector(Tvaraff,1,NCOVMAX);
1.338 brouard 17018: free_ivector(invalidvarcomb,0,ncovcombmax);
1.227 brouard 17019: free_ivector(Tage,1,NCOVMAX);
17020: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 17021: free_ivector(TmodelInvind,1,NCOVMAX);
17022: free_ivector(TmodelInvQind,1,NCOVMAX);
1.332 brouard 17023:
1.359 brouard 17024: /* free_matrix(precov, 1,MAXRESULTLINESPONE,1,NCOVMAX+1); /\* Could be elsewhere ?*\/ */
1.332 brouard 17025:
1.227 brouard 17026: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
17027: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 17028: fflush(fichtm);
17029: fflush(ficgp);
17030:
1.227 brouard 17031:
1.126 brouard 17032: if((nberr >0) || (nbwarn>0)){
1.216 brouard 17033: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
17034: 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 17035: }else{
17036: printf("End of Imach\n");
17037: fprintf(ficlog,"End of Imach\n");
17038: }
17039: printf("See log file on %s\n",filelog);
17040: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 17041: /*(void) gettimeofday(&end_time,&tzp);*/
17042: rend_time = time(NULL);
17043: end_time = *localtime(&rend_time);
17044: /* tml = *localtime(&end_time.tm_sec); */
17045: strcpy(strtend,asctime(&end_time));
1.126 brouard 17046: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
17047: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 17048: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 17049:
1.157 brouard 17050: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
17051: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
17052: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 17053: /* printf("Total time was %d uSec.\n", total_usecs);*/
17054: /* if(fileappend(fichtm,optionfilehtm)){ */
17055: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
17056: fclose(fichtm);
17057: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
17058: fclose(fichtmcov);
17059: fclose(ficgp);
17060: fclose(ficlog);
17061: /*------ End -----------*/
1.227 brouard 17062:
1.281 brouard 17063:
17064: /* Executes gnuplot */
1.227 brouard 17065:
17066: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 17067: #ifdef WIN32
1.227 brouard 17068: if (_chdir(pathcd) != 0)
17069: printf("Can't move to directory %s!\n",path);
17070: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 17071: #else
1.227 brouard 17072: if(chdir(pathcd) != 0)
17073: printf("Can't move to directory %s!\n", path);
17074: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 17075: #endif
1.126 brouard 17076: printf("Current directory %s!\n",pathcd);
17077: /*strcat(plotcmd,CHARSEPARATOR);*/
17078: sprintf(plotcmd,"gnuplot");
1.157 brouard 17079: #ifdef _WIN32
1.126 brouard 17080: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
17081: #endif
17082: if(!stat(plotcmd,&info)){
1.158 brouard 17083: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 17084: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 17085: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 17086: }else
17087: strcpy(pplotcmd,plotcmd);
1.157 brouard 17088: #ifdef __unix
1.126 brouard 17089: strcpy(plotcmd,GNUPLOTPROGRAM);
17090: if(!stat(plotcmd,&info)){
1.158 brouard 17091: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 17092: }else
17093: strcpy(pplotcmd,plotcmd);
17094: #endif
17095: }else
17096: strcpy(pplotcmd,plotcmd);
17097:
17098: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 17099: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 brouard 17100: strcpy(pplotcmd,plotcmd);
1.227 brouard 17101:
1.126 brouard 17102: if((outcmd=system(plotcmd)) != 0){
1.292 brouard 17103: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 17104: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 17105: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 brouard 17106: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 17107: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 brouard 17108: strcpy(plotcmd,pplotcmd);
17109: }
1.126 brouard 17110: }
1.158 brouard 17111: printf(" Successful, please wait...");
1.126 brouard 17112: while (z[0] != 'q') {
17113: /* chdir(path); */
1.154 brouard 17114: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 17115: scanf("%s",z);
17116: /* if (z[0] == 'c') system("./imach"); */
17117: if (z[0] == 'e') {
1.158 brouard 17118: #ifdef __APPLE__
1.152 brouard 17119: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 17120: #elif __linux
17121: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 17122: #else
1.152 brouard 17123: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 17124: #endif
17125: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
17126: system(pplotcmd);
1.126 brouard 17127: }
17128: else if (z[0] == 'g') system(plotcmd);
17129: else if (z[0] == 'q') exit(0);
17130: }
1.227 brouard 17131: end:
1.126 brouard 17132: while (z[0] != 'q') {
1.195 brouard 17133: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 17134: scanf("%s",z);
17135: }
1.283 brouard 17136: printf("End\n");
1.282 brouard 17137: exit(0);
1.126 brouard 17138: }
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