Annotation of imach/src/imach.c, revision 1.362
1.362 ! brouard 1: /* $Id: imach.c,v 1.361 2024/05/12 20:29:32 brouard Exp $
1.126 brouard 2: $State: Exp $
1.360 brouard 3: $Log: imach.c,v $
1.362 ! brouard 4: Revision 1.361 2024/05/12 20:29:32 brouard
! 5: Summary: Version 0.99s5
! 6:
! 7: * src/imach.c Version 0.99s5 In fact, the covariance of total life
! 8: expectancy e.. with a partial life expectancy e.j is high,
! 9: therefore the complete matrix of variance covariance has to be
! 10: included in the formula of the standard error of the proportion of
! 11: total life expectancy spent in a specific state:
! 12: var(X/Y)=mu_x^2/mu_y^2*(sigma_x^2/mu_x^2 -2
! 13: sigma_xy/mu_x/mu_y+sigma^2/mu_y^2). Also an error with mle=-3
! 14: made the program core dump. It is fixed in this version.
! 15:
1.361 brouard 16: Revision 1.360 2024/04/30 10:59:22 brouard
17: Summary: Version 0.99s4 and estimation of std of e.j/e..
18:
1.360 brouard 19: Revision 1.359 2024/04/24 21:21:17 brouard
20: Summary: First IMaCh version using Brent Praxis software based on Buckhardt and Gegenfürtner C codes
21:
1.359 brouard 22: Revision 1.6 2024/04/24 21:10:29 brouard
23: Summary: First IMaCh version using Brent Praxis software based on Buckhardt and Gegenfürtner C codes
1.358 brouard 24:
1.359 brouard 25: Revision 1.5 2023/10/09 09:10:01 brouard
26: Summary: trying to reconsider
1.357 brouard 27:
1.359 brouard 28: Revision 1.4 2023/06/22 12:50:51 brouard
29: Summary: stil on going
1.357 brouard 30:
1.359 brouard 31: Revision 1.3 2023/06/22 11:28:07 brouard
32: *** empty log message ***
1.356 brouard 33:
1.359 brouard 34: Revision 1.2 2023/06/22 11:22:40 brouard
35: Summary: with svd but not working yet
1.355 brouard 36:
1.354 brouard 37: Revision 1.353 2023/05/08 18:48:22 brouard
38: *** empty log message ***
39:
1.353 brouard 40: Revision 1.352 2023/04/29 10:46:21 brouard
41: *** empty log message ***
42:
1.352 brouard 43: Revision 1.351 2023/04/29 10:43:47 brouard
44: Summary: 099r45
45:
1.351 brouard 46: Revision 1.350 2023/04/24 11:38:06 brouard
47: *** empty log message ***
48:
1.350 brouard 49: Revision 1.349 2023/01/31 09:19:37 brouard
50: Summary: Improvements in models with age*Vn*Vm
51:
1.348 brouard 52: Revision 1.347 2022/09/18 14:36:44 brouard
53: Summary: version 0.99r42
54:
1.347 brouard 55: Revision 1.346 2022/09/16 13:52:36 brouard
56: * src/imach.c (Module): 0.99r41 Was an error when product of timevarying and fixed. Using FixedV[of name] now. Thank you Feinuo
57:
1.346 brouard 58: Revision 1.345 2022/09/16 13:40:11 brouard
59: Summary: Version 0.99r41
60:
61: * imach.c (Module): 0.99r41 Was an error when product of timevarying and fixed. Using FixedV[of name] now. Thank you Feinuo
62:
1.345 brouard 63: Revision 1.344 2022/09/14 19:33:30 brouard
64: Summary: version 0.99r40
65:
66: * imach.c (Module): Fixing names of variables in T_ (thanks to Feinuo)
67:
1.344 brouard 68: Revision 1.343 2022/09/14 14:22:16 brouard
69: Summary: version 0.99r39
70:
71: * imach.c (Module): Version 0.99r39 with colored dummy covariates
72: (fixed or time varying), using new last columns of
73: ILK_parameter.txt file.
74:
1.343 brouard 75: Revision 1.342 2022/09/11 19:54:09 brouard
76: Summary: 0.99r38
77:
78: * imach.c (Module): Adding timevarying products of any kinds,
79: should work before shifting cotvar from ncovcol+nqv columns in
80: order to have a correspondance between the column of cotvar and
81: the id of column.
82: (Module): Some cleaning and adding covariates in ILK.txt
83:
1.342 brouard 84: Revision 1.341 2022/09/11 07:58:42 brouard
85: Summary: Version 0.99r38
86:
87: After adding change in cotvar.
88:
1.341 brouard 89: Revision 1.340 2022/09/11 07:53:11 brouard
90: Summary: Version imach 0.99r37
91:
92: * imach.c (Module): Adding timevarying products of any kinds,
93: should work before shifting cotvar from ncovcol+nqv columns in
94: order to have a correspondance between the column of cotvar and
95: the id of column.
96:
1.340 brouard 97: Revision 1.339 2022/09/09 17:55:22 brouard
98: Summary: version 0.99r37
99:
100: * imach.c (Module): Many improvements for fixing products of fixed
101: timevarying as well as fixed * fixed, and test with quantitative
102: covariate.
103:
1.339 brouard 104: Revision 1.338 2022/09/04 17:40:33 brouard
105: Summary: 0.99r36
106:
107: * imach.c (Module): Now the easy runs i.e. without result or
108: model=1+age only did not work. The defautl combination should be 1
109: and not 0 because everything hasn't been tranformed yet.
110:
1.338 brouard 111: Revision 1.337 2022/09/02 14:26:02 brouard
112: Summary: version 0.99r35
113:
114: * src/imach.c: Version 0.99r35 because it outputs same results with
115: 1+age+V1+V1*age for females and 1+age for females only
116: (education=1 noweight)
117:
1.337 brouard 118: Revision 1.336 2022/08/31 09:52:36 brouard
119: *** empty log message ***
120:
1.336 brouard 121: Revision 1.335 2022/08/31 08:23:16 brouard
122: Summary: improvements...
123:
1.335 brouard 124: Revision 1.334 2022/08/25 09:08:41 brouard
125: Summary: In progress for quantitative
126:
1.334 brouard 127: Revision 1.333 2022/08/21 09:10:30 brouard
128: * src/imach.c (Module): Version 0.99r33 A lot of changes in
129: reassigning covariates: my first idea was that people will always
130: use the first covariate V1 into the model but in fact they are
131: producing data with many covariates and can use an equation model
132: with some of the covariate; it means that in a model V2+V3 instead
133: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
134: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
135: the equation model is restricted to two variables only (V2, V3)
136: and the combination for V2 should be codtabm(k,1) instead of
137: (codtabm(k,2), and the code should be
138: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
139: made. All of these should be simplified once a day like we did in
140: hpxij() for example by using precov[nres] which is computed in
141: decoderesult for each nres of each resultline. Loop should be done
142: on the equation model globally by distinguishing only product with
143: age (which are changing with age) and no more on type of
144: covariates, single dummies, single covariates.
145:
1.333 brouard 146: Revision 1.332 2022/08/21 09:06:25 brouard
147: Summary: Version 0.99r33
148:
149: * src/imach.c (Module): Version 0.99r33 A lot of changes in
150: reassigning covariates: my first idea was that people will always
151: use the first covariate V1 into the model but in fact they are
152: producing data with many covariates and can use an equation model
153: with some of the covariate; it means that in a model V2+V3 instead
154: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
155: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
156: the equation model is restricted to two variables only (V2, V3)
157: and the combination for V2 should be codtabm(k,1) instead of
158: (codtabm(k,2), and the code should be
159: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
160: made. All of these should be simplified once a day like we did in
161: hpxij() for example by using precov[nres] which is computed in
162: decoderesult for each nres of each resultline. Loop should be done
163: on the equation model globally by distinguishing only product with
164: age (which are changing with age) and no more on type of
165: covariates, single dummies, single covariates.
166:
1.332 brouard 167: Revision 1.331 2022/08/07 05:40:09 brouard
168: *** empty log message ***
169:
1.331 brouard 170: Revision 1.330 2022/08/06 07:18:25 brouard
171: Summary: last 0.99r31
172:
173: * imach.c (Module): Version of imach using partly decoderesult to rebuild xpxij function
174:
1.330 brouard 175: Revision 1.329 2022/08/03 17:29:54 brouard
176: * imach.c (Module): Many errors in graphs fixed with Vn*age covariates.
177:
1.329 brouard 178: Revision 1.328 2022/07/27 17:40:48 brouard
179: Summary: valgrind bug fixed by initializing to zero DummyV as well as Tage
180:
1.328 brouard 181: Revision 1.327 2022/07/27 14:47:35 brouard
182: Summary: Still a problem for one-step probabilities in case of quantitative variables
183:
1.327 brouard 184: Revision 1.326 2022/07/26 17:33:55 brouard
185: Summary: some test with nres=1
186:
1.326 brouard 187: Revision 1.325 2022/07/25 14:27:23 brouard
188: Summary: r30
189:
190: * imach.c (Module): Error cptcovn instead of nsd in bmij (was
191: coredumped, revealed by Feiuno, thank you.
192:
1.325 brouard 193: Revision 1.324 2022/07/23 17:44:26 brouard
194: *** empty log message ***
195:
1.324 brouard 196: Revision 1.323 2022/07/22 12:30:08 brouard
197: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
198:
1.323 brouard 199: Revision 1.322 2022/07/22 12:27:48 brouard
200: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
201:
1.322 brouard 202: Revision 1.321 2022/07/22 12:04:24 brouard
203: Summary: r28
204:
205: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
206:
1.321 brouard 207: Revision 1.320 2022/06/02 05:10:11 brouard
208: *** empty log message ***
209:
1.320 brouard 210: Revision 1.319 2022/06/02 04:45:11 brouard
211: * imach.c (Module): Adding the Wald tests from the log to the main
212: htm for better display of the maximum likelihood estimators.
213:
1.319 brouard 214: Revision 1.318 2022/05/24 08:10:59 brouard
215: * imach.c (Module): Some attempts to find a bug of wrong estimates
216: of confidencce intervals with product in the equation modelC
217:
1.318 brouard 218: Revision 1.317 2022/05/15 15:06:23 brouard
219: * imach.c (Module): Some minor improvements
220:
1.317 brouard 221: Revision 1.316 2022/05/11 15:11:31 brouard
222: Summary: r27
223:
1.316 brouard 224: Revision 1.315 2022/05/11 15:06:32 brouard
225: *** empty log message ***
226:
1.315 brouard 227: Revision 1.314 2022/04/13 17:43:09 brouard
228: * imach.c (Module): Adding link to text data files
229:
1.314 brouard 230: Revision 1.313 2022/04/11 15:57:42 brouard
231: * imach.c (Module): Error in rewriting the 'r' file with yearsfproj or yearsbproj fixed
232:
1.313 brouard 233: Revision 1.312 2022/04/05 21:24:39 brouard
234: *** empty log message ***
235:
1.312 brouard 236: Revision 1.311 2022/04/05 21:03:51 brouard
237: Summary: Fixed quantitative covariates
238:
239: Fixed covariates (dummy or quantitative)
240: with missing values have never been allowed but are ERRORS and
241: program quits. Standard deviations of fixed covariates were
242: wrongly computed. Mean and standard deviations of time varying
243: covariates are still not computed.
244:
1.311 brouard 245: Revision 1.310 2022/03/17 08:45:53 brouard
246: Summary: 99r25
247:
248: Improving detection of errors: result lines should be compatible with
249: the model.
250:
1.310 brouard 251: Revision 1.309 2021/05/20 12:39:14 brouard
252: Summary: Version 0.99r24
253:
1.309 brouard 254: Revision 1.308 2021/03/31 13:11:57 brouard
255: Summary: Version 0.99r23
256:
257:
258: * imach.c (Module): Still bugs in the result loop. Thank to Holly Benett
259:
1.308 brouard 260: Revision 1.307 2021/03/08 18:11:32 brouard
261: Summary: 0.99r22 fixed bug on result:
262:
1.307 brouard 263: Revision 1.306 2021/02/20 15:44:02 brouard
264: Summary: Version 0.99r21
265:
266: * imach.c (Module): Fix bug on quitting after result lines!
267: (Module): Version 0.99r21
268:
1.306 brouard 269: Revision 1.305 2021/02/20 15:28:30 brouard
270: * imach.c (Module): Fix bug on quitting after result lines!
271:
1.305 brouard 272: Revision 1.304 2021/02/12 11:34:20 brouard
273: * imach.c (Module): The use of a Windows BOM (huge) file is now an error
274:
1.304 brouard 275: Revision 1.303 2021/02/11 19:50:15 brouard
276: * (Module): imach.c Someone entered 'results:' instead of 'result:'. Now it is an error which is printed.
277:
1.303 brouard 278: Revision 1.302 2020/02/22 21:00:05 brouard
279: * (Module): imach.c Update mle=-3 (for computing Life expectancy
280: and life table from the data without any state)
281:
1.302 brouard 282: Revision 1.301 2019/06/04 13:51:20 brouard
283: Summary: Error in 'r'parameter file backcast yearsbproj instead of yearsfproj
284:
1.301 brouard 285: Revision 1.300 2019/05/22 19:09:45 brouard
286: Summary: version 0.99r19 of May 2019
287:
1.300 brouard 288: Revision 1.299 2019/05/22 18:37:08 brouard
289: Summary: Cleaned 0.99r19
290:
1.299 brouard 291: Revision 1.298 2019/05/22 18:19:56 brouard
292: *** empty log message ***
293:
1.298 brouard 294: Revision 1.297 2019/05/22 17:56:10 brouard
295: Summary: Fix bug by moving date2dmy and nhstepm which gaefin=-1
296:
1.297 brouard 297: Revision 1.296 2019/05/20 13:03:18 brouard
298: Summary: Projection syntax simplified
299:
300:
301: We can now start projections, forward or backward, from the mean date
302: of inteviews up to or down to a number of years of projection:
303: prevforecast=1 yearsfproj=15.3 mobil_average=0
304: or
305: prevforecast=1 starting-proj-date=1/1/2007 final-proj-date=12/31/2017 mobil_average=0
306: or
307: prevbackcast=1 yearsbproj=12.3 mobil_average=1
308: or
309: prevbackcast=1 starting-back-date=1/10/1999 final-back-date=1/1/1985 mobil_average=1
310:
1.296 brouard 311: Revision 1.295 2019/05/18 09:52:50 brouard
312: Summary: doxygen tex bug
313:
1.295 brouard 314: Revision 1.294 2019/05/16 14:54:33 brouard
315: Summary: There was some wrong lines added
316:
1.294 brouard 317: Revision 1.293 2019/05/09 15:17:34 brouard
318: *** empty log message ***
319:
1.293 brouard 320: Revision 1.292 2019/05/09 14:17:20 brouard
321: Summary: Some updates
322:
1.292 brouard 323: Revision 1.291 2019/05/09 13:44:18 brouard
324: Summary: Before ncovmax
325:
1.291 brouard 326: Revision 1.290 2019/05/09 13:39:37 brouard
327: Summary: 0.99r18 unlimited number of individuals
328:
329: 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.
330:
1.290 brouard 331: Revision 1.289 2018/12/13 09:16:26 brouard
332: Summary: Bug for young ages (<-30) will be in r17
333:
1.289 brouard 334: Revision 1.288 2018/05/02 20:58:27 brouard
335: Summary: Some bugs fixed
336:
1.288 brouard 337: Revision 1.287 2018/05/01 17:57:25 brouard
338: Summary: Bug fixed by providing frequencies only for non missing covariates
339:
1.287 brouard 340: Revision 1.286 2018/04/27 14:27:04 brouard
341: Summary: some minor bugs
342:
1.286 brouard 343: Revision 1.285 2018/04/21 21:02:16 brouard
344: Summary: Some bugs fixed, valgrind tested
345:
1.285 brouard 346: Revision 1.284 2018/04/20 05:22:13 brouard
347: Summary: Computing mean and stdeviation of fixed quantitative variables
348:
1.284 brouard 349: Revision 1.283 2018/04/19 14:49:16 brouard
350: Summary: Some minor bugs fixed
351:
1.283 brouard 352: Revision 1.282 2018/02/27 22:50:02 brouard
353: *** empty log message ***
354:
1.282 brouard 355: Revision 1.281 2018/02/27 19:25:23 brouard
356: Summary: Adding second argument for quitting
357:
1.281 brouard 358: Revision 1.280 2018/02/21 07:58:13 brouard
359: Summary: 0.99r15
360:
361: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
362:
1.280 brouard 363: Revision 1.279 2017/07/20 13:35:01 brouard
364: Summary: temporary working
365:
1.279 brouard 366: Revision 1.278 2017/07/19 14:09:02 brouard
367: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
368:
1.278 brouard 369: Revision 1.277 2017/07/17 08:53:49 brouard
370: Summary: BOM files can be read now
371:
1.277 brouard 372: Revision 1.276 2017/06/30 15:48:31 brouard
373: Summary: Graphs improvements
374:
1.276 brouard 375: Revision 1.275 2017/06/30 13:39:33 brouard
376: Summary: Saito's color
377:
1.275 brouard 378: Revision 1.274 2017/06/29 09:47:08 brouard
379: Summary: Version 0.99r14
380:
1.274 brouard 381: Revision 1.273 2017/06/27 11:06:02 brouard
382: Summary: More documentation on projections
383:
1.273 brouard 384: Revision 1.272 2017/06/27 10:22:40 brouard
385: Summary: Color of backprojection changed from 6 to 5(yellow)
386:
1.272 brouard 387: Revision 1.271 2017/06/27 10:17:50 brouard
388: Summary: Some bug with rint
389:
1.271 brouard 390: Revision 1.270 2017/05/24 05:45:29 brouard
391: *** empty log message ***
392:
1.270 brouard 393: Revision 1.269 2017/05/23 08:39:25 brouard
394: Summary: Code into subroutine, cleanings
395:
1.269 brouard 396: Revision 1.268 2017/05/18 20:09:32 brouard
397: Summary: backprojection and confidence intervals of backprevalence
398:
1.268 brouard 399: Revision 1.267 2017/05/13 10:25:05 brouard
400: Summary: temporary save for backprojection
401:
1.267 brouard 402: Revision 1.266 2017/05/13 07:26:12 brouard
403: Summary: Version 0.99r13 (improvements and bugs fixed)
404:
1.266 brouard 405: Revision 1.265 2017/04/26 16:22:11 brouard
406: Summary: imach 0.99r13 Some bugs fixed
407:
1.265 brouard 408: Revision 1.264 2017/04/26 06:01:29 brouard
409: Summary: Labels in graphs
410:
1.264 brouard 411: Revision 1.263 2017/04/24 15:23:15 brouard
412: Summary: to save
413:
1.263 brouard 414: Revision 1.262 2017/04/18 16:48:12 brouard
415: *** empty log message ***
416:
1.262 brouard 417: Revision 1.261 2017/04/05 10:14:09 brouard
418: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
419:
1.261 brouard 420: Revision 1.260 2017/04/04 17:46:59 brouard
421: Summary: Gnuplot indexations fixed (humm)
422:
1.260 brouard 423: Revision 1.259 2017/04/04 13:01:16 brouard
424: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
425:
1.259 brouard 426: Revision 1.258 2017/04/03 10:17:47 brouard
427: Summary: Version 0.99r12
428:
429: Some cleanings, conformed with updated documentation.
430:
1.258 brouard 431: Revision 1.257 2017/03/29 16:53:30 brouard
432: Summary: Temp
433:
1.257 brouard 434: Revision 1.256 2017/03/27 05:50:23 brouard
435: Summary: Temporary
436:
1.256 brouard 437: Revision 1.255 2017/03/08 16:02:28 brouard
438: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
439:
1.255 brouard 440: Revision 1.254 2017/03/08 07:13:00 brouard
441: Summary: Fixing data parameter line
442:
1.254 brouard 443: Revision 1.253 2016/12/15 11:59:41 brouard
444: Summary: 0.99 in progress
445:
1.253 brouard 446: Revision 1.252 2016/09/15 21:15:37 brouard
447: *** empty log message ***
448:
1.252 brouard 449: Revision 1.251 2016/09/15 15:01:13 brouard
450: Summary: not working
451:
1.251 brouard 452: Revision 1.250 2016/09/08 16:07:27 brouard
453: Summary: continue
454:
1.250 brouard 455: Revision 1.249 2016/09/07 17:14:18 brouard
456: Summary: Starting values from frequencies
457:
1.249 brouard 458: Revision 1.248 2016/09/07 14:10:18 brouard
459: *** empty log message ***
460:
1.248 brouard 461: Revision 1.247 2016/09/02 11:11:21 brouard
462: *** empty log message ***
463:
1.247 brouard 464: Revision 1.246 2016/09/02 08:49:22 brouard
465: *** empty log message ***
466:
1.246 brouard 467: Revision 1.245 2016/09/02 07:25:01 brouard
468: *** empty log message ***
469:
1.245 brouard 470: Revision 1.244 2016/09/02 07:17:34 brouard
471: *** empty log message ***
472:
1.244 brouard 473: Revision 1.243 2016/09/02 06:45:35 brouard
474: *** empty log message ***
475:
1.243 brouard 476: Revision 1.242 2016/08/30 15:01:20 brouard
477: Summary: Fixing a lots
478:
1.242 brouard 479: Revision 1.241 2016/08/29 17:17:25 brouard
480: Summary: gnuplot problem in Back projection to fix
481:
1.241 brouard 482: Revision 1.240 2016/08/29 07:53:18 brouard
483: Summary: Better
484:
1.240 brouard 485: Revision 1.239 2016/08/26 15:51:03 brouard
486: Summary: Improvement in Powell output in order to copy and paste
487:
488: Author:
489:
1.239 brouard 490: Revision 1.238 2016/08/26 14:23:35 brouard
491: Summary: Starting tests of 0.99
492:
1.238 brouard 493: Revision 1.237 2016/08/26 09:20:19 brouard
494: Summary: to valgrind
495:
1.237 brouard 496: Revision 1.236 2016/08/25 10:50:18 brouard
497: *** empty log message ***
498:
1.236 brouard 499: Revision 1.235 2016/08/25 06:59:23 brouard
500: *** empty log message ***
501:
1.235 brouard 502: Revision 1.234 2016/08/23 16:51:20 brouard
503: *** empty log message ***
504:
1.234 brouard 505: Revision 1.233 2016/08/23 07:40:50 brouard
506: Summary: not working
507:
1.233 brouard 508: Revision 1.232 2016/08/22 14:20:21 brouard
509: Summary: not working
510:
1.232 brouard 511: Revision 1.231 2016/08/22 07:17:15 brouard
512: Summary: not working
513:
1.231 brouard 514: Revision 1.230 2016/08/22 06:55:53 brouard
515: Summary: Not working
516:
1.230 brouard 517: Revision 1.229 2016/07/23 09:45:53 brouard
518: Summary: Completing for func too
519:
1.229 brouard 520: Revision 1.228 2016/07/22 17:45:30 brouard
521: Summary: Fixing some arrays, still debugging
522:
1.227 brouard 523: Revision 1.226 2016/07/12 18:42:34 brouard
524: Summary: temp
525:
1.226 brouard 526: Revision 1.225 2016/07/12 08:40:03 brouard
527: Summary: saving but not running
528:
1.225 brouard 529: Revision 1.224 2016/07/01 13:16:01 brouard
530: Summary: Fixes
531:
1.224 brouard 532: Revision 1.223 2016/02/19 09:23:35 brouard
533: Summary: temporary
534:
1.223 brouard 535: Revision 1.222 2016/02/17 08:14:50 brouard
536: Summary: Probably last 0.98 stable version 0.98r6
537:
1.222 brouard 538: Revision 1.221 2016/02/15 23:35:36 brouard
539: Summary: minor bug
540:
1.220 brouard 541: Revision 1.219 2016/02/15 00:48:12 brouard
542: *** empty log message ***
543:
1.219 brouard 544: Revision 1.218 2016/02/12 11:29:23 brouard
545: Summary: 0.99 Back projections
546:
1.218 brouard 547: Revision 1.217 2015/12/23 17:18:31 brouard
548: Summary: Experimental backcast
549:
1.217 brouard 550: Revision 1.216 2015/12/18 17:32:11 brouard
551: Summary: 0.98r4 Warning and status=-2
552:
553: Version 0.98r4 is now:
554: - displaying an error when status is -1, date of interview unknown and date of death known;
555: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
556: Older changes concerning s=-2, dating from 2005 have been supersed.
557:
1.216 brouard 558: Revision 1.215 2015/12/16 08:52:24 brouard
559: Summary: 0.98r4 working
560:
1.215 brouard 561: Revision 1.214 2015/12/16 06:57:54 brouard
562: Summary: temporary not working
563:
1.214 brouard 564: Revision 1.213 2015/12/11 18:22:17 brouard
565: Summary: 0.98r4
566:
1.213 brouard 567: Revision 1.212 2015/11/21 12:47:24 brouard
568: Summary: minor typo
569:
1.212 brouard 570: Revision 1.211 2015/11/21 12:41:11 brouard
571: Summary: 0.98r3 with some graph of projected cross-sectional
572:
573: Author: Nicolas Brouard
574:
1.211 brouard 575: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 576: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 577: Summary: Adding ftolpl parameter
578: Author: N Brouard
579:
580: We had difficulties to get smoothed confidence intervals. It was due
581: to the period prevalence which wasn't computed accurately. The inner
582: parameter ftolpl is now an outer parameter of the .imach parameter
583: file after estepm. If ftolpl is small 1.e-4 and estepm too,
584: computation are long.
585:
1.209 brouard 586: Revision 1.208 2015/11/17 14:31:57 brouard
587: Summary: temporary
588:
1.208 brouard 589: Revision 1.207 2015/10/27 17:36:57 brouard
590: *** empty log message ***
591:
1.207 brouard 592: Revision 1.206 2015/10/24 07:14:11 brouard
593: *** empty log message ***
594:
1.206 brouard 595: Revision 1.205 2015/10/23 15:50:53 brouard
596: Summary: 0.98r3 some clarification for graphs on likelihood contributions
597:
1.205 brouard 598: Revision 1.204 2015/10/01 16:20:26 brouard
599: Summary: Some new graphs of contribution to likelihood
600:
1.204 brouard 601: Revision 1.203 2015/09/30 17:45:14 brouard
602: Summary: looking at better estimation of the hessian
603:
604: Also a better criteria for convergence to the period prevalence And
605: therefore adding the number of years needed to converge. (The
606: prevalence in any alive state shold sum to one
607:
1.203 brouard 608: Revision 1.202 2015/09/22 19:45:16 brouard
609: Summary: Adding some overall graph on contribution to likelihood. Might change
610:
1.202 brouard 611: Revision 1.201 2015/09/15 17:34:58 brouard
612: Summary: 0.98r0
613:
614: - Some new graphs like suvival functions
615: - Some bugs fixed like model=1+age+V2.
616:
1.201 brouard 617: Revision 1.200 2015/09/09 16:53:55 brouard
618: Summary: Big bug thanks to Flavia
619:
620: Even model=1+age+V2. did not work anymore
621:
1.200 brouard 622: Revision 1.199 2015/09/07 14:09:23 brouard
623: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
624:
1.199 brouard 625: Revision 1.198 2015/09/03 07:14:39 brouard
626: Summary: 0.98q5 Flavia
627:
1.198 brouard 628: Revision 1.197 2015/09/01 18:24:39 brouard
629: *** empty log message ***
630:
1.197 brouard 631: Revision 1.196 2015/08/18 23:17:52 brouard
632: Summary: 0.98q5
633:
1.196 brouard 634: Revision 1.195 2015/08/18 16:28:39 brouard
635: Summary: Adding a hack for testing purpose
636:
637: After reading the title, ftol and model lines, if the comment line has
638: a q, starting with #q, the answer at the end of the run is quit. It
639: permits to run test files in batch with ctest. The former workaround was
640: $ echo q | imach foo.imach
641:
1.195 brouard 642: Revision 1.194 2015/08/18 13:32:00 brouard
643: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
644:
1.194 brouard 645: Revision 1.193 2015/08/04 07:17:42 brouard
646: Summary: 0.98q4
647:
1.193 brouard 648: Revision 1.192 2015/07/16 16:49:02 brouard
649: Summary: Fixing some outputs
650:
1.192 brouard 651: Revision 1.191 2015/07/14 10:00:33 brouard
652: Summary: Some fixes
653:
1.191 brouard 654: Revision 1.190 2015/05/05 08:51:13 brouard
655: Summary: Adding digits in output parameters (7 digits instead of 6)
656:
657: Fix 1+age+.
658:
1.190 brouard 659: Revision 1.189 2015/04/30 14:45:16 brouard
660: Summary: 0.98q2
661:
1.189 brouard 662: Revision 1.188 2015/04/30 08:27:53 brouard
663: *** empty log message ***
664:
1.188 brouard 665: Revision 1.187 2015/04/29 09:11:15 brouard
666: *** empty log message ***
667:
1.187 brouard 668: Revision 1.186 2015/04/23 12:01:52 brouard
669: Summary: V1*age is working now, version 0.98q1
670:
671: Some codes had been disabled in order to simplify and Vn*age was
672: working in the optimization phase, ie, giving correct MLE parameters,
673: but, as usual, outputs were not correct and program core dumped.
674:
1.186 brouard 675: Revision 1.185 2015/03/11 13:26:42 brouard
676: Summary: Inclusion of compile and links command line for Intel Compiler
677:
1.185 brouard 678: Revision 1.184 2015/03/11 11:52:39 brouard
679: Summary: Back from Windows 8. Intel Compiler
680:
1.184 brouard 681: Revision 1.183 2015/03/10 20:34:32 brouard
682: Summary: 0.98q0, trying with directest, mnbrak fixed
683:
684: We use directest instead of original Powell test; probably no
685: incidence on the results, but better justifications;
686: We fixed Numerical Recipes mnbrak routine which was wrong and gave
687: wrong results.
688:
1.183 brouard 689: Revision 1.182 2015/02/12 08:19:57 brouard
690: Summary: Trying to keep directest which seems simpler and more general
691: Author: Nicolas Brouard
692:
1.182 brouard 693: Revision 1.181 2015/02/11 23:22:24 brouard
694: Summary: Comments on Powell added
695:
696: Author:
697:
1.181 brouard 698: Revision 1.180 2015/02/11 17:33:45 brouard
699: Summary: Finishing move from main to function (hpijx and prevalence_limit)
700:
1.180 brouard 701: Revision 1.179 2015/01/04 09:57:06 brouard
702: Summary: back to OS/X
703:
1.179 brouard 704: Revision 1.178 2015/01/04 09:35:48 brouard
705: *** empty log message ***
706:
1.178 brouard 707: Revision 1.177 2015/01/03 18:40:56 brouard
708: Summary: Still testing ilc32 on OSX
709:
1.177 brouard 710: Revision 1.176 2015/01/03 16:45:04 brouard
711: *** empty log message ***
712:
1.176 brouard 713: Revision 1.175 2015/01/03 16:33:42 brouard
714: *** empty log message ***
715:
1.175 brouard 716: Revision 1.174 2015/01/03 16:15:49 brouard
717: Summary: Still in cross-compilation
718:
1.174 brouard 719: Revision 1.173 2015/01/03 12:06:26 brouard
720: Summary: trying to detect cross-compilation
721:
1.173 brouard 722: Revision 1.172 2014/12/27 12:07:47 brouard
723: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
724:
1.172 brouard 725: Revision 1.171 2014/12/23 13:26:59 brouard
726: Summary: Back from Visual C
727:
728: Still problem with utsname.h on Windows
729:
1.171 brouard 730: Revision 1.170 2014/12/23 11:17:12 brouard
731: Summary: Cleaning some \%% back to %%
732:
733: The escape was mandatory for a specific compiler (which one?), but too many warnings.
734:
1.170 brouard 735: Revision 1.169 2014/12/22 23:08:31 brouard
736: Summary: 0.98p
737:
738: Outputs some informations on compiler used, OS etc. Testing on different platforms.
739:
1.169 brouard 740: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 741: Summary: update
1.169 brouard 742:
1.168 brouard 743: Revision 1.167 2014/12/22 13:50:56 brouard
744: Summary: Testing uname and compiler version and if compiled 32 or 64
745:
746: Testing on Linux 64
747:
1.167 brouard 748: Revision 1.166 2014/12/22 11:40:47 brouard
749: *** empty log message ***
750:
1.166 brouard 751: Revision 1.165 2014/12/16 11:20:36 brouard
752: Summary: After compiling on Visual C
753:
754: * imach.c (Module): Merging 1.61 to 1.162
755:
1.165 brouard 756: Revision 1.164 2014/12/16 10:52:11 brouard
757: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
758:
759: * imach.c (Module): Merging 1.61 to 1.162
760:
1.164 brouard 761: Revision 1.163 2014/12/16 10:30:11 brouard
762: * imach.c (Module): Merging 1.61 to 1.162
763:
1.163 brouard 764: Revision 1.162 2014/09/25 11:43:39 brouard
765: Summary: temporary backup 0.99!
766:
1.162 brouard 767: Revision 1.1 2014/09/16 11:06:58 brouard
768: Summary: With some code (wrong) for nlopt
769:
770: Author:
771:
772: Revision 1.161 2014/09/15 20:41:41 brouard
773: Summary: Problem with macro SQR on Intel compiler
774:
1.161 brouard 775: Revision 1.160 2014/09/02 09:24:05 brouard
776: *** empty log message ***
777:
1.160 brouard 778: Revision 1.159 2014/09/01 10:34:10 brouard
779: Summary: WIN32
780: Author: Brouard
781:
1.159 brouard 782: Revision 1.158 2014/08/27 17:11:51 brouard
783: *** empty log message ***
784:
1.158 brouard 785: Revision 1.157 2014/08/27 16:26:55 brouard
786: Summary: Preparing windows Visual studio version
787: Author: Brouard
788:
789: In order to compile on Visual studio, time.h is now correct and time_t
790: and tm struct should be used. difftime should be used but sometimes I
791: just make the differences in raw time format (time(&now).
792: Trying to suppress #ifdef LINUX
793: Add xdg-open for __linux in order to open default browser.
794:
1.157 brouard 795: Revision 1.156 2014/08/25 20:10:10 brouard
796: *** empty log message ***
797:
1.156 brouard 798: Revision 1.155 2014/08/25 18:32:34 brouard
799: Summary: New compile, minor changes
800: Author: Brouard
801:
1.155 brouard 802: Revision 1.154 2014/06/20 17:32:08 brouard
803: Summary: Outputs now all graphs of convergence to period prevalence
804:
1.154 brouard 805: Revision 1.153 2014/06/20 16:45:46 brouard
806: Summary: If 3 live state, convergence to period prevalence on same graph
807: Author: Brouard
808:
1.153 brouard 809: Revision 1.152 2014/06/18 17:54:09 brouard
810: Summary: open browser, use gnuplot on same dir than imach if not found in the path
811:
1.152 brouard 812: Revision 1.151 2014/06/18 16:43:30 brouard
813: *** empty log message ***
814:
1.151 brouard 815: Revision 1.150 2014/06/18 16:42:35 brouard
816: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
817: Author: brouard
818:
1.150 brouard 819: Revision 1.149 2014/06/18 15:51:14 brouard
820: Summary: Some fixes in parameter files errors
821: Author: Nicolas Brouard
822:
1.149 brouard 823: Revision 1.148 2014/06/17 17:38:48 brouard
824: Summary: Nothing new
825: Author: Brouard
826:
827: Just a new packaging for OS/X version 0.98nS
828:
1.148 brouard 829: Revision 1.147 2014/06/16 10:33:11 brouard
830: *** empty log message ***
831:
1.147 brouard 832: Revision 1.146 2014/06/16 10:20:28 brouard
833: Summary: Merge
834: Author: Brouard
835:
836: Merge, before building revised version.
837:
1.146 brouard 838: Revision 1.145 2014/06/10 21:23:15 brouard
839: Summary: Debugging with valgrind
840: Author: Nicolas Brouard
841:
842: Lot of changes in order to output the results with some covariates
843: After the Edimburgh REVES conference 2014, it seems mandatory to
844: improve the code.
845: No more memory valgrind error but a lot has to be done in order to
846: continue the work of splitting the code into subroutines.
847: Also, decodemodel has been improved. Tricode is still not
848: optimal. nbcode should be improved. Documentation has been added in
849: the source code.
850:
1.144 brouard 851: Revision 1.143 2014/01/26 09:45:38 brouard
852: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
853:
854: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
855: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
856:
1.143 brouard 857: Revision 1.142 2014/01/26 03:57:36 brouard
858: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
859:
860: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
861:
1.142 brouard 862: Revision 1.141 2014/01/26 02:42:01 brouard
863: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
864:
1.141 brouard 865: Revision 1.140 2011/09/02 10:37:54 brouard
866: Summary: times.h is ok with mingw32 now.
867:
1.140 brouard 868: Revision 1.139 2010/06/14 07:50:17 brouard
869: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
870: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
871:
1.139 brouard 872: Revision 1.138 2010/04/30 18:19:40 brouard
873: *** empty log message ***
874:
1.138 brouard 875: Revision 1.137 2010/04/29 18:11:38 brouard
876: (Module): Checking covariates for more complex models
877: than V1+V2. A lot of change to be done. Unstable.
878:
1.137 brouard 879: Revision 1.136 2010/04/26 20:30:53 brouard
880: (Module): merging some libgsl code. Fixing computation
881: of likelione (using inter/intrapolation if mle = 0) in order to
882: get same likelihood as if mle=1.
883: Some cleaning of code and comments added.
884:
1.136 brouard 885: Revision 1.135 2009/10/29 15:33:14 brouard
886: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
887:
1.135 brouard 888: Revision 1.134 2009/10/29 13:18:53 brouard
889: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
890:
1.134 brouard 891: Revision 1.133 2009/07/06 10:21:25 brouard
892: just nforces
893:
1.133 brouard 894: Revision 1.132 2009/07/06 08:22:05 brouard
895: Many tings
896:
1.132 brouard 897: Revision 1.131 2009/06/20 16:22:47 brouard
898: Some dimensions resccaled
899:
1.131 brouard 900: Revision 1.130 2009/05/26 06:44:34 brouard
901: (Module): Max Covariate is now set to 20 instead of 8. A
902: lot of cleaning with variables initialized to 0. Trying to make
903: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
904:
1.130 brouard 905: Revision 1.129 2007/08/31 13:49:27 lievre
906: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
907:
1.129 lievre 908: Revision 1.128 2006/06/30 13:02:05 brouard
909: (Module): Clarifications on computing e.j
910:
1.128 brouard 911: Revision 1.127 2006/04/28 18:11:50 brouard
912: (Module): Yes the sum of survivors was wrong since
913: imach-114 because nhstepm was no more computed in the age
914: loop. Now we define nhstepma in the age loop.
915: (Module): In order to speed up (in case of numerous covariates) we
916: compute health expectancies (without variances) in a first step
917: and then all the health expectancies with variances or standard
918: deviation (needs data from the Hessian matrices) which slows the
919: computation.
920: In the future we should be able to stop the program is only health
921: expectancies and graph are needed without standard deviations.
922:
1.127 brouard 923: Revision 1.126 2006/04/28 17:23:28 brouard
924: (Module): Yes the sum of survivors was wrong since
925: imach-114 because nhstepm was no more computed in the age
926: loop. Now we define nhstepma in the age loop.
927: Version 0.98h
928:
1.126 brouard 929: Revision 1.125 2006/04/04 15:20:31 lievre
930: Errors in calculation of health expectancies. Age was not initialized.
931: Forecasting file added.
932:
933: Revision 1.124 2006/03/22 17:13:53 lievre
934: Parameters are printed with %lf instead of %f (more numbers after the comma).
935: The log-likelihood is printed in the log file
936:
937: Revision 1.123 2006/03/20 10:52:43 brouard
938: * imach.c (Module): <title> changed, corresponds to .htm file
939: name. <head> headers where missing.
940:
941: * imach.c (Module): Weights can have a decimal point as for
942: English (a comma might work with a correct LC_NUMERIC environment,
943: otherwise the weight is truncated).
944: Modification of warning when the covariates values are not 0 or
945: 1.
946: Version 0.98g
947:
948: Revision 1.122 2006/03/20 09:45:41 brouard
949: (Module): Weights can have a decimal point as for
950: English (a comma might work with a correct LC_NUMERIC environment,
951: otherwise the weight is truncated).
952: Modification of warning when the covariates values are not 0 or
953: 1.
954: Version 0.98g
955:
956: Revision 1.121 2006/03/16 17:45:01 lievre
957: * imach.c (Module): Comments concerning covariates added
958:
959: * imach.c (Module): refinements in the computation of lli if
960: status=-2 in order to have more reliable computation if stepm is
961: not 1 month. Version 0.98f
962:
963: Revision 1.120 2006/03/16 15:10:38 lievre
964: (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 1.119 2006/03/15 17:42:26 brouard
969: (Module): Bug if status = -2, the loglikelihood was
970: computed as likelihood omitting the logarithm. Version O.98e
971:
972: Revision 1.118 2006/03/14 18:20:07 brouard
973: (Module): varevsij Comments added explaining the second
974: table of variances if popbased=1 .
975: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
976: (Module): Function pstamp added
977: (Module): Version 0.98d
978:
979: Revision 1.117 2006/03/14 17:16:22 brouard
980: (Module): varevsij Comments added explaining the second
981: table of variances if popbased=1 .
982: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
983: (Module): Function pstamp added
984: (Module): Version 0.98d
985:
986: Revision 1.116 2006/03/06 10:29:27 brouard
987: (Module): Variance-covariance wrong links and
988: varian-covariance of ej. is needed (Saito).
989:
990: Revision 1.115 2006/02/27 12:17:45 brouard
991: (Module): One freematrix added in mlikeli! 0.98c
992:
993: Revision 1.114 2006/02/26 12:57:58 brouard
994: (Module): Some improvements in processing parameter
995: filename with strsep.
996:
997: Revision 1.113 2006/02/24 14:20:24 brouard
998: (Module): Memory leaks checks with valgrind and:
999: datafile was not closed, some imatrix were not freed and on matrix
1000: allocation too.
1001:
1002: Revision 1.112 2006/01/30 09:55:26 brouard
1003: (Module): Back to gnuplot.exe instead of wgnuplot.exe
1004:
1005: Revision 1.111 2006/01/25 20:38:18 brouard
1006: (Module): Lots of cleaning and bugs added (Gompertz)
1007: (Module): Comments can be added in data file. Missing date values
1008: can be a simple dot '.'.
1009:
1010: Revision 1.110 2006/01/25 00:51:50 brouard
1011: (Module): Lots of cleaning and bugs added (Gompertz)
1012:
1013: Revision 1.109 2006/01/24 19:37:15 brouard
1014: (Module): Comments (lines starting with a #) are allowed in data.
1015:
1016: Revision 1.108 2006/01/19 18:05:42 lievre
1017: Gnuplot problem appeared...
1018: To be fixed
1019:
1020: Revision 1.107 2006/01/19 16:20:37 brouard
1021: Test existence of gnuplot in imach path
1022:
1023: Revision 1.106 2006/01/19 13:24:36 brouard
1024: Some cleaning and links added in html output
1025:
1026: Revision 1.105 2006/01/05 20:23:19 lievre
1027: *** empty log message ***
1028:
1029: Revision 1.104 2005/09/30 16:11:43 lievre
1030: (Module): sump fixed, loop imx fixed, and simplifications.
1031: (Module): If the status is missing at the last wave but we know
1032: that the person is alive, then we can code his/her status as -2
1033: (instead of missing=-1 in earlier versions) and his/her
1034: contributions to the likelihood is 1 - Prob of dying from last
1035: health status (= 1-p13= p11+p12 in the easiest case of somebody in
1036: the healthy state at last known wave). Version is 0.98
1037:
1038: Revision 1.103 2005/09/30 15:54:49 lievre
1039: (Module): sump fixed, loop imx fixed, and simplifications.
1040:
1041: Revision 1.102 2004/09/15 17:31:30 brouard
1042: Add the possibility to read data file including tab characters.
1043:
1044: Revision 1.101 2004/09/15 10:38:38 brouard
1045: Fix on curr_time
1046:
1047: Revision 1.100 2004/07/12 18:29:06 brouard
1048: Add version for Mac OS X. Just define UNIX in Makefile
1049:
1050: Revision 1.99 2004/06/05 08:57:40 brouard
1051: *** empty log message ***
1052:
1053: Revision 1.98 2004/05/16 15:05:56 brouard
1054: New version 0.97 . First attempt to estimate force of mortality
1055: directly from the data i.e. without the need of knowing the health
1056: state at each age, but using a Gompertz model: log u =a + b*age .
1057: This is the basic analysis of mortality and should be done before any
1058: other analysis, in order to test if the mortality estimated from the
1059: cross-longitudinal survey is different from the mortality estimated
1060: from other sources like vital statistic data.
1061:
1062: The same imach parameter file can be used but the option for mle should be -3.
1063:
1.324 brouard 1064: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 1065: former routines in order to include the new code within the former code.
1066:
1067: The output is very simple: only an estimate of the intercept and of
1068: the slope with 95% confident intervals.
1069:
1070: Current limitations:
1071: A) Even if you enter covariates, i.e. with the
1072: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
1073: B) There is no computation of Life Expectancy nor Life Table.
1074:
1075: Revision 1.97 2004/02/20 13:25:42 lievre
1076: Version 0.96d. Population forecasting command line is (temporarily)
1077: suppressed.
1078:
1079: Revision 1.96 2003/07/15 15:38:55 brouard
1080: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
1081: rewritten within the same printf. Workaround: many printfs.
1082:
1083: Revision 1.95 2003/07/08 07:54:34 brouard
1084: * imach.c (Repository):
1085: (Repository): Using imachwizard code to output a more meaningful covariance
1086: matrix (cov(a12,c31) instead of numbers.
1087:
1088: Revision 1.94 2003/06/27 13:00:02 brouard
1089: Just cleaning
1090:
1091: Revision 1.93 2003/06/25 16:33:55 brouard
1092: (Module): On windows (cygwin) function asctime_r doesn't
1093: exist so I changed back to asctime which exists.
1094: (Module): Version 0.96b
1095:
1096: Revision 1.92 2003/06/25 16:30:45 brouard
1097: (Module): On windows (cygwin) function asctime_r doesn't
1098: exist so I changed back to asctime which exists.
1099:
1100: Revision 1.91 2003/06/25 15:30:29 brouard
1101: * imach.c (Repository): Duplicated warning errors corrected.
1102: (Repository): Elapsed time after each iteration is now output. It
1103: helps to forecast when convergence will be reached. Elapsed time
1104: is stamped in powell. We created a new html file for the graphs
1105: concerning matrix of covariance. It has extension -cov.htm.
1106:
1107: Revision 1.90 2003/06/24 12:34:15 brouard
1108: (Module): Some bugs corrected for windows. Also, when
1109: mle=-1 a template is output in file "or"mypar.txt with the design
1110: of the covariance matrix to be input.
1111:
1112: Revision 1.89 2003/06/24 12:30:52 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 1.88 2003/06/23 17:54:56 brouard
1118: * 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.
1119:
1120: Revision 1.87 2003/06/18 12:26:01 brouard
1121: Version 0.96
1122:
1123: Revision 1.86 2003/06/17 20:04:08 brouard
1124: (Module): Change position of html and gnuplot routines and added
1125: routine fileappend.
1126:
1127: Revision 1.85 2003/06/17 13:12:43 brouard
1128: * imach.c (Repository): Check when date of death was earlier that
1129: current date of interview. It may happen when the death was just
1130: prior to the death. In this case, dh was negative and likelihood
1131: was wrong (infinity). We still send an "Error" but patch by
1132: assuming that the date of death was just one stepm after the
1133: interview.
1134: (Repository): Because some people have very long ID (first column)
1135: we changed int to long in num[] and we added a new lvector for
1136: memory allocation. But we also truncated to 8 characters (left
1137: truncation)
1138: (Repository): No more line truncation errors.
1139:
1140: Revision 1.84 2003/06/13 21:44:43 brouard
1141: * imach.c (Repository): Replace "freqsummary" at a correct
1142: place. It differs from routine "prevalence" which may be called
1143: many times. Probs is memory consuming and must be used with
1144: parcimony.
1145: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
1146:
1147: Revision 1.83 2003/06/10 13:39:11 lievre
1148: *** empty log message ***
1149:
1150: Revision 1.82 2003/06/05 15:57:20 brouard
1151: Add log in imach.c and fullversion number is now printed.
1152:
1153: */
1154: /*
1155: Interpolated Markov Chain
1156:
1157: Short summary of the programme:
1158:
1.227 brouard 1159: This program computes Healthy Life Expectancies or State-specific
1160: (if states aren't health statuses) Expectancies from
1161: cross-longitudinal data. Cross-longitudinal data consist in:
1162:
1163: -1- a first survey ("cross") where individuals from different ages
1164: are interviewed on their health status or degree of disability (in
1165: the case of a health survey which is our main interest)
1166:
1167: -2- at least a second wave of interviews ("longitudinal") which
1168: measure each change (if any) in individual health status. Health
1169: expectancies are computed from the time spent in each health state
1170: according to a model. More health states you consider, more time is
1171: necessary to reach the Maximum Likelihood of the parameters involved
1172: in the model. The simplest model is the multinomial logistic model
1173: where pij is the probability to be observed in state j at the second
1174: wave conditional to be observed in state i at the first
1175: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
1176: etc , where 'age' is age and 'sex' is a covariate. If you want to
1177: have a more complex model than "constant and age", you should modify
1178: the program where the markup *Covariates have to be included here
1179: again* invites you to do it. More covariates you add, slower the
1.126 brouard 1180: convergence.
1181:
1182: The advantage of this computer programme, compared to a simple
1183: multinomial logistic model, is clear when the delay between waves is not
1184: identical for each individual. Also, if a individual missed an
1185: intermediate interview, the information is lost, but taken into
1186: account using an interpolation or extrapolation.
1187:
1188: hPijx is the probability to be observed in state i at age x+h
1189: conditional to the observed state i at age x. The delay 'h' can be
1190: split into an exact number (nh*stepm) of unobserved intermediate
1191: states. This elementary transition (by month, quarter,
1192: semester or year) is modelled as a multinomial logistic. The hPx
1193: matrix is simply the matrix product of nh*stepm elementary matrices
1194: and the contribution of each individual to the likelihood is simply
1195: hPijx.
1196:
1197: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 1198: of the life expectancies. It also computes the period (stable) prevalence.
1199:
1200: Back prevalence and projections:
1.227 brouard 1201:
1202: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
1203: double agemaxpar, double ftolpl, int *ncvyearp, double
1204: dateprev1,double dateprev2, int firstpass, int lastpass, int
1205: mobilavproj)
1206:
1207: Computes the back prevalence limit for any combination of
1208: covariate values k at any age between ageminpar and agemaxpar and
1209: returns it in **bprlim. In the loops,
1210:
1211: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
1212: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
1213:
1214: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 1215: Computes for any combination of covariates k and any age between bage and fage
1216: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
1217: oldm=oldms;savm=savms;
1.227 brouard 1218:
1.267 brouard 1219: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 1220: Computes the transition matrix starting at age 'age' over
1221: 'nhstepm*hstepm*stepm' months (i.e. until
1222: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 1223: nhstepm*hstepm matrices.
1224:
1225: Returns p3mat[i][j][h] after calling
1226: p3mat[i][j][h]=matprod2(newm,
1227: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
1228: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
1229: oldm);
1.226 brouard 1230:
1231: Important routines
1232:
1233: - func (or funcone), computes logit (pij) distinguishing
1234: o fixed variables (single or product dummies or quantitative);
1235: o varying variables by:
1236: (1) wave (single, product dummies, quantitative),
1237: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
1238: % fixed dummy (treated) or quantitative (not done because time-consuming);
1239: % varying dummy (not done) or quantitative (not done);
1240: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
1241: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
1242: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
1.325 brouard 1243: o There are 2**cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
1.226 brouard 1244: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 1245:
1.226 brouard 1246:
1247:
1.324 brouard 1248: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
1249: Institut national d'études démographiques, Paris.
1.126 brouard 1250: This software have been partly granted by Euro-REVES, a concerted action
1251: from the European Union.
1252: It is copyrighted identically to a GNU software product, ie programme and
1253: software can be distributed freely for non commercial use. Latest version
1254: can be accessed at http://euroreves.ined.fr/imach .
1255:
1256: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
1257: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
1258:
1259: **********************************************************************/
1260: /*
1261: main
1262: read parameterfile
1263: read datafile
1264: concatwav
1265: freqsummary
1266: if (mle >= 1)
1267: mlikeli
1268: print results files
1269: if mle==1
1270: computes hessian
1271: read end of parameter file: agemin, agemax, bage, fage, estepm
1272: begin-prev-date,...
1273: open gnuplot file
1274: open html file
1.145 brouard 1275: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
1276: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
1277: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
1278: freexexit2 possible for memory heap.
1279:
1280: h Pij x | pij_nom ficrestpij
1281: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
1282: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
1283: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
1284:
1285: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
1286: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
1287: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
1288: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
1289: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
1290:
1.126 brouard 1291: forecasting if prevfcast==1 prevforecast call prevalence()
1292: health expectancies
1293: Variance-covariance of DFLE
1294: prevalence()
1295: movingaverage()
1296: varevsij()
1297: if popbased==1 varevsij(,popbased)
1298: total life expectancies
1299: Variance of period (stable) prevalence
1300: end
1301: */
1302:
1.187 brouard 1303: /* #define DEBUG */
1304: /* #define DEBUGBRENT */
1.203 brouard 1305: /* #define DEBUGLINMIN */
1306: /* #define DEBUGHESS */
1307: #define DEBUGHESSIJ
1.224 brouard 1308: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 1309: #define POWELL /* Instead of NLOPT */
1.224 brouard 1310: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 1311: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
1312: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.319 brouard 1313: /* #define FLATSUP *//* Suppresses directions where likelihood is flat */
1.359 brouard 1314: /* #define POWELLORIGINCONJUGATE /\* Don't use conjugate but biggest decrease if valuable *\/ */
1315: /* #define NOTMINFIT */
1.126 brouard 1316:
1317: #include <math.h>
1318: #include <stdio.h>
1319: #include <stdlib.h>
1320: #include <string.h>
1.226 brouard 1321: #include <ctype.h>
1.159 brouard 1322:
1323: #ifdef _WIN32
1324: #include <io.h>
1.172 brouard 1325: #include <windows.h>
1326: #include <tchar.h>
1.159 brouard 1327: #else
1.126 brouard 1328: #include <unistd.h>
1.159 brouard 1329: #endif
1.126 brouard 1330:
1331: #include <limits.h>
1332: #include <sys/types.h>
1.171 brouard 1333:
1334: #if defined(__GNUC__)
1335: #include <sys/utsname.h> /* Doesn't work on Windows */
1336: #endif
1337:
1.126 brouard 1338: #include <sys/stat.h>
1339: #include <errno.h>
1.159 brouard 1340: /* extern int errno; */
1.126 brouard 1341:
1.157 brouard 1342: /* #ifdef LINUX */
1343: /* #include <time.h> */
1344: /* #include "timeval.h" */
1345: /* #else */
1346: /* #include <sys/time.h> */
1347: /* #endif */
1348:
1.126 brouard 1349: #include <time.h>
1350:
1.136 brouard 1351: #ifdef GSL
1352: #include <gsl/gsl_errno.h>
1353: #include <gsl/gsl_multimin.h>
1354: #endif
1355:
1.167 brouard 1356:
1.162 brouard 1357: #ifdef NLOPT
1358: #include <nlopt.h>
1359: typedef struct {
1360: double (* function)(double [] );
1361: } myfunc_data ;
1362: #endif
1363:
1.126 brouard 1364: /* #include <libintl.h> */
1365: /* #define _(String) gettext (String) */
1366:
1.349 brouard 1367: #define MAXLINE 16384 /* Was 256 and 1024 and 2048. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1368:
1369: #define GNUPLOTPROGRAM "gnuplot"
1.343 brouard 1370: #define GNUPLOTVERSION 5.1
1371: double gnuplotversion=GNUPLOTVERSION;
1.126 brouard 1372: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1.329 brouard 1373: #define FILENAMELENGTH 256
1.126 brouard 1374:
1375: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1376: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1377:
1.349 brouard 1378: #define MAXPARM 216 /**< Maximum number of parameters for the optimization was 128 */
1.144 brouard 1379: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1380:
1381: #define NINTERVMAX 8
1.144 brouard 1382: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1383: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.325 brouard 1384: #define NCOVMAX 30 /**< Maximum number of covariates used in the model, including generated covariates V1*V2 or V1*age */
1.197 brouard 1385: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1386: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1387: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1388: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1389: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1390: /* #define AGESUP 130 */
1.288 brouard 1391: /* #define AGESUP 150 */
1392: #define AGESUP 200
1.268 brouard 1393: #define AGEINF 0
1.218 brouard 1394: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1395: #define AGEBASE 40
1.194 brouard 1396: #define AGEOVERFLOW 1.e20
1.164 brouard 1397: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1398: #ifdef _WIN32
1399: #define DIRSEPARATOR '\\'
1400: #define CHARSEPARATOR "\\"
1401: #define ODIRSEPARATOR '/'
1402: #else
1.126 brouard 1403: #define DIRSEPARATOR '/'
1404: #define CHARSEPARATOR "/"
1405: #define ODIRSEPARATOR '\\'
1406: #endif
1407:
1.362 ! brouard 1408: /* $Id: imach.c,v 1.361 2024/05/12 20:29:32 brouard Exp $ */
1.126 brouard 1409: /* $State: Exp $ */
1.196 brouard 1410: #include "version.h"
1411: char version[]=__IMACH_VERSION__;
1.360 brouard 1412: 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";
1.362 ! brouard 1413: char fullversion[]="$Revision: 1.361 $ $Date: 2024/05/12 20:29:32 $";
1.126 brouard 1414: char strstart[80];
1415: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1416: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.342 brouard 1417: int debugILK=0; /* debugILK is set by a #d in a comment line */
1.187 brouard 1418: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.330 brouard 1419: /* Number of covariates model (1)=V2+V1+ V3*age+V2*V4 */
1420: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
1.335 brouard 1421: 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 1422: 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 1423: int cptcovs=0; /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
1424: int cptcovsnq=0; /**< cptcovsnq number of SIMPLE covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1425: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1.349 brouard 1426: int cptcovprodage=0; /**< Number of fixed covariates with age: V3*age or V2*V3*age 1 */
1427: int cptcovprodvage=0; /**< Number of varying covariates with age: V7*age or V7*V6*age */
1428: int cptcovdageprod=0; /**< Number of doubleproducts with age, since 0.99r44 only: age*Vn*Vm for gnuplot printing*/
1.145 brouard 1429: int cptcovprodnoage=0; /**< Number of covariate products without age */
1.335 brouard 1430: 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 1431: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1432: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.339 brouard 1433: int ncovvt=0; /* Total number of effective (wave) varying covariates (dummy or quantitative or products [without age]) in the model */
1.349 brouard 1434: 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 */
1435: 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 */
1436: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (single or product, dummy or quantitative) in the model */
1437: 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 1438: int nsd=0; /**< Total number of single dummy variables (output) */
1439: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1440: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1441: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1442: int ntveff=0; /**< ntveff number of effective time varying variables */
1443: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1444: int cptcov=0; /* Working variable */
1.334 brouard 1445: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs+1 declared globally ;*/
1.290 brouard 1446: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1447: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.302 brouard 1448: int npar=NPARMAX; /* Number of parameters (nlstate+ndeath-1)*nlstate*ncovmodel; */
1.126 brouard 1449: int nlstate=2; /* Number of live states */
1450: int ndeath=1; /* Number of dead states */
1.130 brouard 1451: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.339 brouard 1452: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable*/
1453: int ncovcolt=0; /* ncovcolt=ncovcol+nqv+ntv+nqtv; total of covariates in the data, not in the model equation*/
1.126 brouard 1454: int popbased=0;
1455:
1456: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1457: int maxwav=0; /* Maxim number of waves */
1458: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1459: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1.359 brouard 1460: int gipmx = 0;
1461: double gsw = 0; /* Global variables on the number of contributions
1.126 brouard 1462: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1463: int mle=1, weightopt=0;
1.126 brouard 1464: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1465: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1466: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1467: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1468: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1469: int selected(int kvar); /* Is covariate kvar selected for printing results */
1470:
1.130 brouard 1471: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1472: double **matprod2(); /* test */
1.126 brouard 1473: double **oldm, **newm, **savm; /* Working pointers to matrices */
1474: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1475: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1476:
1.136 brouard 1477: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1478: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1479: FILE *ficlog, *ficrespow;
1.130 brouard 1480: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1481: double fretone; /* Only one call to likelihood */
1.130 brouard 1482: long ipmx=0; /* Number of contributions */
1.126 brouard 1483: double sw; /* Sum of weights */
1484: char filerespow[FILENAMELENGTH];
1485: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1486: FILE *ficresilk;
1487: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1488: FILE *ficresprobmorprev;
1489: FILE *fichtm, *fichtmcov; /* Html File */
1490: FILE *ficreseij;
1491: char filerese[FILENAMELENGTH];
1492: FILE *ficresstdeij;
1493: char fileresstde[FILENAMELENGTH];
1494: FILE *ficrescveij;
1495: char filerescve[FILENAMELENGTH];
1496: FILE *ficresvij;
1497: char fileresv[FILENAMELENGTH];
1.269 brouard 1498:
1.126 brouard 1499: char title[MAXLINE];
1.234 brouard 1500: char model[MAXLINE]; /**< The model line */
1.217 brouard 1501: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1502: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1503: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1504: char command[FILENAMELENGTH];
1505: int outcmd=0;
1506:
1.217 brouard 1507: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1508: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1509: char filelog[FILENAMELENGTH]; /* Log file */
1510: char filerest[FILENAMELENGTH];
1511: char fileregp[FILENAMELENGTH];
1512: char popfile[FILENAMELENGTH];
1513:
1514: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1515:
1.157 brouard 1516: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1517: /* struct timezone tzp; */
1518: /* extern int gettimeofday(); */
1519: struct tm tml, *gmtime(), *localtime();
1520:
1521: extern time_t time();
1522:
1523: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1524: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1.349 brouard 1525: time_t rlast_btime; /* raw time */
1.157 brouard 1526: struct tm tm;
1527:
1.126 brouard 1528: char strcurr[80], strfor[80];
1529:
1530: char *endptr;
1531: long lval;
1532: double dval;
1533:
1.362 ! brouard 1534: /* This for praxis gegen */
! 1535: /* int prin=1; */
! 1536: double h0=0.25;
! 1537: double macheps;
! 1538: double ffmin;
! 1539:
1.126 brouard 1540: #define NR_END 1
1541: #define FREE_ARG char*
1542: #define FTOL 1.0e-10
1543:
1544: #define NRANSI
1.240 brouard 1545: #define ITMAX 200
1546: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1547:
1548: #define TOL 2.0e-4
1549:
1550: #define CGOLD 0.3819660
1551: #define ZEPS 1.0e-10
1552: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1553:
1554: #define GOLD 1.618034
1555: #define GLIMIT 100.0
1556: #define TINY 1.0e-20
1557:
1558: static double maxarg1,maxarg2;
1559: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1560: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1561:
1562: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1563: #define rint(a) floor(a+0.5)
1.166 brouard 1564: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1565: #define mytinydouble 1.0e-16
1.166 brouard 1566: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1567: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1568: /* static double dsqrarg; */
1569: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1570: static double sqrarg;
1571: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1572: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1573: int agegomp= AGEGOMP;
1574:
1575: int imx;
1576: int stepm=1;
1577: /* Stepm, step in month: minimum step interpolation*/
1578:
1579: int estepm;
1580: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1581:
1582: int m,nb;
1583: long *num;
1.197 brouard 1584: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1585: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1586: covariate for which somebody answered excluding
1587: undefined. Usually 2: 0 and 1. */
1588: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1589: covariate for which somebody answered including
1590: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1591: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1592: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1593: double ***mobaverage, ***mobaverages; /* New global variable */
1.332 brouard 1594: 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 1595: double *ageexmed,*agecens;
1596: double dateintmean=0;
1.296 brouard 1597: double anprojd, mprojd, jprojd; /* For eventual projections */
1598: double anprojf, mprojf, jprojf;
1.126 brouard 1599:
1.296 brouard 1600: double anbackd, mbackd, jbackd; /* For eventual backprojections */
1601: double anbackf, mbackf, jbackf;
1602: double jintmean,mintmean,aintmean;
1.126 brouard 1603: double *weight;
1604: int **s; /* Status */
1.141 brouard 1605: double *agedc;
1.145 brouard 1606: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1607: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1608: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1609: double **coqvar; /* Fixed quantitative covariate nqv */
1.341 brouard 1610: double ***cotvar; /* Time varying covariate start at ncovcol + nqv + (1 to ntv) */
1.225 brouard 1611: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1612: double idx;
1613: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.319 brouard 1614: /* Some documentation */
1615: /* Design original data
1616: * V1 V2 V3 V4 V5 V6 V7 V8 Weight ddb ddth d1st s1 V9 V10 V11 V12 s2 V9 V10 V11 V12
1617: * < ncovcol=6 > nqv=2 (V7 V8) dv dv dv qtv dv dv dvv qtv
1618: * ntv=3 nqtv=1
1.330 brouard 1619: * cptcovn number of covariates (not including constant and age or age*age) = number of plus sign + 1 = 10+1=11
1.319 brouard 1620: * For time varying covariate, quanti or dummies
1621: * cotqvar[wav][iv(1 to nqtv)][i]= [1][12][i]=(V12) quanti
1.341 brouard 1622: * cotvar[wav][ncovcol+nqv+ iv(1 to nqtv)][i]= [(1 to nqtv)][i]=(V12) quanti
1.319 brouard 1623: * cotvar[wav][iv(1 to ntv)][i]= [1][1][i]=(V9) dummies at wav 1
1624: * cotvar[wav][iv(1 to ntv)][i]= [1][2][i]=(V10) dummies at wav 1
1.332 brouard 1625: * covar[Vk,i], value of the Vkth fixed covariate dummy or quanti for individual i:
1.319 brouard 1626: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
1627: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 + V9 + V9*age + V10
1628: * k= 1 2 3 4 5 6 7 8 9 10 11
1629: */
1630: /* According to the model, more columns can be added to covar by the product of covariates */
1.318 brouard 1631: /* 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
1632: # States 1=Coresidence, 2 Living alone, 3 Institution
1633: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1634: */
1.349 brouard 1635: /* V5+V4+ V3+V4*V3 +V5*age+V2 +V1*V2+V1*age+V1+V4*V3*age */
1636: /* kmodel 1 2 3 4 5 6 7 8 9 10 */
1637: /*Typevar[k]= 0 0 0 2 1 0 2 1 0 3 *//*0 for simple covariate (dummy, quantitative,*/
1638: /* fixed or varying), 1 for age product, 2 for*/
1639: /* product without age, 3 for age and double product */
1640: /*Dummy[k]= 1 0 0 1 3 1 1 2 0 3 *//*Dummy[k] 0=dummy (0 1), 1 quantitative */
1641: /*(single or product without age), 2 dummy*/
1642: /* with age product, 3 quant with age product*/
1643: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 6 */
1644: /* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */
1645: /*TnsdVar[Tvar] 1 2 3 */
1646: /*Tvaraff[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1647: /*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1648: /*TvarsDind[nsd] 2 3 9 */ /* position K of single dummy cova */
1649: /* nsq 1 2 */ /* Counting single quantit tv */
1650: /* TvarsQ[k] 5 2 */ /* Number of single quantitative cova */
1651: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1652: /* Tprod[i]=k 1 2 */ /* Position in model of the ith prod without age */
1653: /* cptcovage 1 2 3 */ /* Counting cov*age in the model equation */
1654: /* Tage[cptcovage]=k 5 8 10 */ /* Position in the model of ith cov*age */
1.350 brouard 1655: /* 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"*/
1656: /* 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 1657: /* p Tvard[2][1]@21 = {7, 2, 6, 3, 7, 3, 6, 4, 7, 4, 0 <repeats 11 times>} */
1.350 brouard 1658: /* 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}*/
1659: /* 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 1660: /* Tvard[1][1]@4={4,3,1,2} V4*V3 V1*V2 */ /* Position in model of the ith prod without age */
1.330 brouard 1661: /* 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 1662: /* 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 1663: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.234 brouard 1664: /* Type */
1665: /* V 1 2 3 4 5 */
1666: /* F F V V V */
1667: /* D Q D D Q */
1668: /* */
1669: int *TvarsD;
1.330 brouard 1670: int *TnsdVar;
1.234 brouard 1671: int *TvarsDind;
1672: int *TvarsQ;
1673: int *TvarsQind;
1674:
1.318 brouard 1675: #define MAXRESULTLINESPONE 10+1
1.235 brouard 1676: int nresult=0;
1.258 brouard 1677: int parameterline=0; /* # of the parameter (type) line */
1.334 brouard 1678: int TKresult[MAXRESULTLINESPONE]; /* TKresult[nres]=k for each resultline nres give the corresponding combination of dummies */
1679: int resultmodel[MAXRESULTLINESPONE][NCOVMAX];/* resultmodel[k1]=k3: k1th position in the model corresponds to the k3 position in the resultline */
1680: int modelresult[MAXRESULTLINESPONE][NCOVMAX];/* modelresult[k3]=k1: k1th position in the model corresponds to the k3 position in the resultline */
1681: int Tresult[MAXRESULTLINESPONE][NCOVMAX];/* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1682: int Tinvresult[MAXRESULTLINESPONE][NCOVMAX];/* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1683: double TinvDoQresult[MAXRESULTLINESPONE][NCOVMAX];/* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.334 brouard 1684: int Tvresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1685: double Tqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.318 brouard 1686: double Tqinvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
1.332 brouard 1687: int Tvqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.318 brouard 1688:
1689: /* 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
1690: # States 1=Coresidence, 2 Living alone, 3 Institution
1691: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1692: */
1.234 brouard 1693: /* 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 1694: 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 */
1695: 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 */
1696: 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 */
1697: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1698: 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 */
1699: 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 1700: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1701: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1702: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1703: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1704: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1705: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1706: 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 */
1707: 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 1708: int *TvarVV; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1709: int *TvarVVind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1.349 brouard 1710: int *TvarVVA; /* We count ncovvt time varying covariates (single or products with age) and put their name into TvarVVA */
1711: int *TvarVVAind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1712: int *TvarAVVA; /* We count ALL ncovta time varying covariates (single or products with age) and put their name into TvarVVA */
1713: int *TvarAVVAind; /* We count ALL ncovta time varying covariates (single or products without age) and put their name into TvarVV */
1.339 brouard 1714: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
1.349 brouard 1715: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age */
1716: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
1717: /* TvarVV={3,1,3,1,3}, for V3 and then the product V1*V3 is decomposed into V1 and V3 */
1718: /* 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 1719: int *Tvarsel; /**< Selected covariates for output */
1720: double *Tvalsel; /**< Selected modality value of covariate for output */
1.349 brouard 1721: 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 1722: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1723: 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 1724: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1725: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1726: int *Tage;
1.227 brouard 1727: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1728: 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 1729: 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*/
1730: 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 1731: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1732: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1733: int **Tvard;
1.330 brouard 1734: int **Tvardk;
1.227 brouard 1735: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1736: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1737: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1738: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1739: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1740: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1741: double *lsurv, *lpop, *tpop;
1742:
1.231 brouard 1743: #define FD 1; /* Fixed dummy covariate */
1744: #define FQ 2; /* Fixed quantitative covariate */
1745: #define FP 3; /* Fixed product covariate */
1746: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1747: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1748: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1749: #define VD 10; /* Varying dummy covariate */
1750: #define VQ 11; /* Varying quantitative covariate */
1751: #define VP 12; /* Varying product covariate */
1752: #define VPDD 13; /* Varying product dummy*dummy covariate */
1753: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1754: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1755: #define APFD 16; /* Age product * fixed dummy covariate */
1756: #define APFQ 17; /* Age product * fixed quantitative covariate */
1757: #define APVD 18; /* Age product * varying dummy covariate */
1758: #define APVQ 19; /* Age product * varying quantitative covariate */
1759:
1760: #define FTYPE 1; /* Fixed covariate */
1761: #define VTYPE 2; /* Varying covariate (loop in wave) */
1762: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1763:
1764: struct kmodel{
1765: int maintype; /* main type */
1766: int subtype; /* subtype */
1767: };
1768: struct kmodel modell[NCOVMAX];
1769:
1.143 brouard 1770: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1771: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1772:
1773: /**************** split *************************/
1774: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1775: {
1776: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1777: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1778: */
1779: char *ss; /* pointer */
1.186 brouard 1780: int l1=0, l2=0; /* length counters */
1.126 brouard 1781:
1782: l1 = strlen(path ); /* length of path */
1783: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1784: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1785: if ( ss == NULL ) { /* no directory, so determine current directory */
1786: strcpy( name, path ); /* we got the fullname name because no directory */
1787: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1788: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1789: /* get current working directory */
1790: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1791: #ifdef WIN32
1792: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1793: #else
1794: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1795: #endif
1.126 brouard 1796: return( GLOCK_ERROR_GETCWD );
1797: }
1798: /* got dirc from getcwd*/
1799: printf(" DIRC = %s \n",dirc);
1.205 brouard 1800: } else { /* strip directory from path */
1.126 brouard 1801: ss++; /* after this, the filename */
1802: l2 = strlen( ss ); /* length of filename */
1803: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1804: strcpy( name, ss ); /* save file name */
1805: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1806: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1807: printf(" DIRC2 = %s \n",dirc);
1808: }
1809: /* We add a separator at the end of dirc if not exists */
1810: l1 = strlen( dirc ); /* length of directory */
1811: if( dirc[l1-1] != DIRSEPARATOR ){
1812: dirc[l1] = DIRSEPARATOR;
1813: dirc[l1+1] = 0;
1814: printf(" DIRC3 = %s \n",dirc);
1815: }
1816: ss = strrchr( name, '.' ); /* find last / */
1817: if (ss >0){
1818: ss++;
1819: strcpy(ext,ss); /* save extension */
1820: l1= strlen( name);
1821: l2= strlen(ss)+1;
1822: strncpy( finame, name, l1-l2);
1823: finame[l1-l2]= 0;
1824: }
1825:
1826: return( 0 ); /* we're done */
1827: }
1828:
1829:
1830: /******************************************/
1831:
1832: void replace_back_to_slash(char *s, char*t)
1833: {
1834: int i;
1835: int lg=0;
1836: i=0;
1837: lg=strlen(t);
1838: for(i=0; i<= lg; i++) {
1839: (s[i] = t[i]);
1840: if (t[i]== '\\') s[i]='/';
1841: }
1842: }
1843:
1.132 brouard 1844: char *trimbb(char *out, char *in)
1.137 brouard 1845: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1846: char *s;
1847: s=out;
1848: while (*in != '\0'){
1.137 brouard 1849: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1850: in++;
1851: }
1852: *out++ = *in++;
1853: }
1854: *out='\0';
1855: return s;
1856: }
1857:
1.351 brouard 1858: char *trimbtab(char *out, char *in)
1859: { /* Trim blanks or tabs in line but keeps first blanks if line starts with blanks */
1860: char *s;
1861: s=out;
1862: while (*in != '\0'){
1863: while( (*in == ' ' || *in == '\t')){ /* && *(in+1) != '\0'){*/
1864: in++;
1865: }
1866: *out++ = *in++;
1867: }
1868: *out='\0';
1869: return s;
1870: }
1871:
1.187 brouard 1872: /* char *substrchaine(char *out, char *in, char *chain) */
1873: /* { */
1874: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1875: /* char *s, *t; */
1876: /* t=in;s=out; */
1877: /* while ((*in != *chain) && (*in != '\0')){ */
1878: /* *out++ = *in++; */
1879: /* } */
1880:
1881: /* /\* *in matches *chain *\/ */
1882: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1883: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1884: /* } */
1885: /* in--; chain--; */
1886: /* while ( (*in != '\0')){ */
1887: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1888: /* *out++ = *in++; */
1889: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1890: /* } */
1891: /* *out='\0'; */
1892: /* out=s; */
1893: /* return out; */
1894: /* } */
1895: char *substrchaine(char *out, char *in, char *chain)
1896: {
1897: /* Substract chain 'chain' from 'in', return and output 'out' */
1.349 brouard 1898: /* in="V1+V1*age+age*age+V2", chain="+age*age" out="V1+V1*age+V2" */
1.187 brouard 1899:
1900: char *strloc;
1901:
1.349 brouard 1902: strcpy (out, in); /* out="V1+V1*age+age*age+V2" */
1903: strloc = strstr(out, chain); /* strloc points to out at "+age*age+V2" */
1904: 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 1905: if(strloc != NULL){
1.349 brouard 1906: /* will affect out */ /* strloc+strlen(chain)=|+V2 = "V1+V1*age+age*age|+V2" */ /* Will also work in Unicodek */
1907: 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)*/
1908: /* equivalent to strcpy (strloc, strloc +strlen(chain)) if no overlap; Copies from "+V2" to V1+V1*age+ */
1.187 brouard 1909: }
1.349 brouard 1910: 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 1911: return out;
1912: }
1913:
1914:
1.145 brouard 1915: char *cutl(char *blocc, char *alocc, char *in, char occ)
1916: {
1.187 brouard 1917: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.349 brouard 1918: and alocc starts after first occurence of char 'occ' : ex cutl(blocc,alocc,"abcdef2ghi2j",'2')
1.310 brouard 1919: gives alocc="abcdef" and blocc="ghi2j".
1.145 brouard 1920: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1921: */
1.160 brouard 1922: char *s, *t;
1.145 brouard 1923: t=in;s=in;
1924: while ((*in != occ) && (*in != '\0')){
1925: *alocc++ = *in++;
1926: }
1927: if( *in == occ){
1928: *(alocc)='\0';
1929: s=++in;
1930: }
1931:
1932: if (s == t) {/* occ not found */
1933: *(alocc-(in-s))='\0';
1934: in=s;
1935: }
1936: while ( *in != '\0'){
1937: *blocc++ = *in++;
1938: }
1939:
1940: *blocc='\0';
1941: return t;
1942: }
1.137 brouard 1943: char *cutv(char *blocc, char *alocc, char *in, char occ)
1944: {
1.187 brouard 1945: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1946: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1947: gives blocc="abcdef2ghi" and alocc="j".
1948: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1949: */
1950: char *s, *t;
1951: t=in;s=in;
1952: while (*in != '\0'){
1953: while( *in == occ){
1954: *blocc++ = *in++;
1955: s=in;
1956: }
1957: *blocc++ = *in++;
1958: }
1959: if (s == t) /* occ not found */
1960: *(blocc-(in-s))='\0';
1961: else
1962: *(blocc-(in-s)-1)='\0';
1963: in=s;
1964: while ( *in != '\0'){
1965: *alocc++ = *in++;
1966: }
1967:
1968: *alocc='\0';
1969: return s;
1970: }
1971:
1.126 brouard 1972: int nbocc(char *s, char occ)
1973: {
1974: int i,j=0;
1975: int lg=20;
1976: i=0;
1977: lg=strlen(s);
1978: for(i=0; i<= lg; i++) {
1.234 brouard 1979: if (s[i] == occ ) j++;
1.126 brouard 1980: }
1981: return j;
1982: }
1983:
1.349 brouard 1984: int nboccstr(char *textin, char *chain)
1985: {
1986: /* Counts the number of occurence of "chain" in string textin */
1987: /* in="+V7*V4+age*V2+age*V3+age*V4" chain="age" */
1988: char *strloc;
1989:
1990: int i,j=0;
1991:
1992: i=0;
1993:
1994: strloc=textin; /* strloc points to "^+V7*V4+age+..." in textin */
1995: for(;;) {
1996: strloc= strstr(strloc,chain); /* strloc points to first character of chain in textin if found. Example strloc points^ to "+V7*V4+^age" in textin */
1997: if(strloc != NULL){
1998: strloc = strloc+strlen(chain); /* strloc points to "+V7*V4+age^" in textin */
1999: j++;
2000: }else
2001: break;
2002: }
2003: return j;
2004:
2005: }
1.137 brouard 2006: /* void cutv(char *u,char *v, char*t, char occ) */
2007: /* { */
2008: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
2009: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
2010: /* gives u="abcdef2ghi" and v="j" *\/ */
2011: /* int i,lg,j,p=0; */
2012: /* i=0; */
2013: /* lg=strlen(t); */
2014: /* for(j=0; j<=lg-1; j++) { */
2015: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
2016: /* } */
1.126 brouard 2017:
1.137 brouard 2018: /* for(j=0; j<p; j++) { */
2019: /* (u[j] = t[j]); */
2020: /* } */
2021: /* u[p]='\0'; */
1.126 brouard 2022:
1.137 brouard 2023: /* for(j=0; j<= lg; j++) { */
2024: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
2025: /* } */
2026: /* } */
1.126 brouard 2027:
1.160 brouard 2028: #ifdef _WIN32
2029: char * strsep(char **pp, const char *delim)
2030: {
2031: char *p, *q;
2032:
2033: if ((p = *pp) == NULL)
2034: return 0;
2035: if ((q = strpbrk (p, delim)) != NULL)
2036: {
2037: *pp = q + 1;
2038: *q = '\0';
2039: }
2040: else
2041: *pp = 0;
2042: return p;
2043: }
2044: #endif
2045:
1.126 brouard 2046: /********************** nrerror ********************/
2047:
2048: void nrerror(char error_text[])
2049: {
2050: fprintf(stderr,"ERREUR ...\n");
2051: fprintf(stderr,"%s\n",error_text);
2052: exit(EXIT_FAILURE);
2053: }
2054: /*********************** vector *******************/
2055: double *vector(int nl, int nh)
2056: {
2057: double *v;
2058: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
2059: if (!v) nrerror("allocation failure in vector");
2060: return v-nl+NR_END;
2061: }
2062:
2063: /************************ free vector ******************/
2064: void free_vector(double*v, int nl, int nh)
2065: {
2066: free((FREE_ARG)(v+nl-NR_END));
2067: }
2068:
2069: /************************ivector *******************************/
2070: int *ivector(long nl,long nh)
2071: {
2072: int *v;
2073: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
2074: if (!v) nrerror("allocation failure in ivector");
2075: return v-nl+NR_END;
2076: }
2077:
2078: /******************free ivector **************************/
2079: void free_ivector(int *v, long nl, long nh)
2080: {
2081: free((FREE_ARG)(v+nl-NR_END));
2082: }
2083:
2084: /************************lvector *******************************/
2085: long *lvector(long nl,long nh)
2086: {
2087: long *v;
2088: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
2089: if (!v) nrerror("allocation failure in ivector");
2090: return v-nl+NR_END;
2091: }
2092:
2093: /******************free lvector **************************/
2094: void free_lvector(long *v, long nl, long nh)
2095: {
2096: free((FREE_ARG)(v+nl-NR_END));
2097: }
2098:
2099: /******************* imatrix *******************************/
2100: int **imatrix(long nrl, long nrh, long ncl, long nch)
2101: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
2102: {
2103: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
2104: int **m;
2105:
2106: /* allocate pointers to rows */
2107: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
2108: if (!m) nrerror("allocation failure 1 in matrix()");
2109: m += NR_END;
2110: m -= nrl;
2111:
2112:
2113: /* allocate rows and set pointers to them */
2114: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
2115: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2116: m[nrl] += NR_END;
2117: m[nrl] -= ncl;
2118:
2119: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
2120:
2121: /* return pointer to array of pointers to rows */
2122: return m;
2123: }
2124:
2125: /****************** free_imatrix *************************/
2126: void free_imatrix(m,nrl,nrh,ncl,nch)
2127: int **m;
2128: long nch,ncl,nrh,nrl;
2129: /* free an int matrix allocated by imatrix() */
2130: {
2131: free((FREE_ARG) (m[nrl]+ncl-NR_END));
2132: free((FREE_ARG) (m+nrl-NR_END));
2133: }
2134:
2135: /******************* matrix *******************************/
2136: double **matrix(long nrl, long nrh, long ncl, long nch)
2137: {
2138: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
2139: double **m;
2140:
2141: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
2142: if (!m) nrerror("allocation failure 1 in matrix()");
2143: m += NR_END;
2144: m -= nrl;
2145:
2146: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
2147: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2148: m[nrl] += NR_END;
2149: m[nrl] -= ncl;
2150:
2151: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2152: return m;
1.145 brouard 2153: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
2154: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
2155: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 2156: */
2157: }
2158:
2159: /*************************free matrix ************************/
2160: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
2161: {
2162: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2163: free((FREE_ARG)(m+nrl-NR_END));
2164: }
2165:
2166: /******************* ma3x *******************************/
2167: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
2168: {
2169: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
2170: double ***m;
2171:
2172: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
2173: if (!m) nrerror("allocation failure 1 in matrix()");
2174: m += NR_END;
2175: m -= nrl;
2176:
2177: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
2178: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2179: m[nrl] += NR_END;
2180: m[nrl] -= ncl;
2181:
2182: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2183:
2184: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
2185: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
2186: m[nrl][ncl] += NR_END;
2187: m[nrl][ncl] -= nll;
2188: for (j=ncl+1; j<=nch; j++)
2189: m[nrl][j]=m[nrl][j-1]+nlay;
2190:
2191: for (i=nrl+1; i<=nrh; i++) {
2192: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
2193: for (j=ncl+1; j<=nch; j++)
2194: m[i][j]=m[i][j-1]+nlay;
2195: }
2196: return m;
2197: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
2198: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
2199: */
2200: }
2201:
2202: /*************************free ma3x ************************/
2203: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
2204: {
2205: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
2206: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2207: free((FREE_ARG)(m+nrl-NR_END));
2208: }
2209:
2210: /*************** function subdirf ***********/
2211: char *subdirf(char fileres[])
2212: {
2213: /* Caution optionfilefiname is hidden */
2214: strcpy(tmpout,optionfilefiname);
2215: strcat(tmpout,"/"); /* Add to the right */
2216: strcat(tmpout,fileres);
2217: return tmpout;
2218: }
2219:
2220: /*************** function subdirf2 ***********/
2221: char *subdirf2(char fileres[], char *preop)
2222: {
1.314 brouard 2223: /* Example subdirf2(optionfilefiname,"FB_") with optionfilefiname="texte", result="texte/FB_texte"
2224: Errors in subdirf, 2, 3 while printing tmpout is
1.315 brouard 2225: rewritten within the same printf. Workaround: many printfs */
1.126 brouard 2226: /* Caution optionfilefiname is hidden */
2227: strcpy(tmpout,optionfilefiname);
2228: strcat(tmpout,"/");
2229: strcat(tmpout,preop);
2230: strcat(tmpout,fileres);
2231: return tmpout;
2232: }
2233:
2234: /*************** function subdirf3 ***********/
2235: char *subdirf3(char fileres[], char *preop, char *preop2)
2236: {
2237:
2238: /* Caution optionfilefiname is hidden */
2239: strcpy(tmpout,optionfilefiname);
2240: strcat(tmpout,"/");
2241: strcat(tmpout,preop);
2242: strcat(tmpout,preop2);
2243: strcat(tmpout,fileres);
2244: return tmpout;
2245: }
1.213 brouard 2246:
2247: /*************** function subdirfext ***********/
2248: char *subdirfext(char fileres[], char *preop, char *postop)
2249: {
2250:
2251: strcpy(tmpout,preop);
2252: strcat(tmpout,fileres);
2253: strcat(tmpout,postop);
2254: return tmpout;
2255: }
1.126 brouard 2256:
1.213 brouard 2257: /*************** function subdirfext3 ***********/
2258: char *subdirfext3(char fileres[], char *preop, char *postop)
2259: {
2260:
2261: /* Caution optionfilefiname is hidden */
2262: strcpy(tmpout,optionfilefiname);
2263: strcat(tmpout,"/");
2264: strcat(tmpout,preop);
2265: strcat(tmpout,fileres);
2266: strcat(tmpout,postop);
2267: return tmpout;
2268: }
2269:
1.162 brouard 2270: char *asc_diff_time(long time_sec, char ascdiff[])
2271: {
2272: long sec_left, days, hours, minutes;
2273: days = (time_sec) / (60*60*24);
2274: sec_left = (time_sec) % (60*60*24);
2275: hours = (sec_left) / (60*60) ;
2276: sec_left = (sec_left) %(60*60);
2277: minutes = (sec_left) /60;
2278: sec_left = (sec_left) % (60);
2279: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
2280: return ascdiff;
2281: }
2282:
1.126 brouard 2283: /***************** f1dim *************************/
2284: extern int ncom;
2285: extern double *pcom,*xicom;
2286: extern double (*nrfunc)(double []);
2287:
2288: double f1dim(double x)
2289: {
2290: int j;
2291: double f;
2292: double *xt;
2293:
2294: xt=vector(1,ncom);
2295: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
2296: f=(*nrfunc)(xt);
2297: free_vector(xt,1,ncom);
2298: return f;
2299: }
2300:
2301: /*****************brent *************************/
2302: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 2303: {
2304: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
2305: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
2306: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
2307: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
2308: * returned function value.
2309: */
1.126 brouard 2310: int iter;
2311: double a,b,d,etemp;
1.159 brouard 2312: double fu=0,fv,fw,fx;
1.164 brouard 2313: double ftemp=0.;
1.126 brouard 2314: double p,q,r,tol1,tol2,u,v,w,x,xm;
2315: double e=0.0;
2316:
2317: a=(ax < cx ? ax : cx);
2318: b=(ax > cx ? ax : cx);
2319: x=w=v=bx;
2320: fw=fv=fx=(*f)(x);
2321: for (iter=1;iter<=ITMAX;iter++) {
2322: xm=0.5*(a+b);
2323: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
2324: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
2325: printf(".");fflush(stdout);
2326: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 2327: #ifdef DEBUGBRENT
1.126 brouard 2328: 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);
2329: 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);
2330: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
2331: #endif
2332: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
2333: *xmin=x;
2334: return fx;
2335: }
2336: ftemp=fu;
2337: if (fabs(e) > tol1) {
2338: r=(x-w)*(fx-fv);
2339: q=(x-v)*(fx-fw);
2340: p=(x-v)*q-(x-w)*r;
2341: q=2.0*(q-r);
2342: if (q > 0.0) p = -p;
2343: q=fabs(q);
2344: etemp=e;
2345: e=d;
2346: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 2347: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 2348: else {
1.224 brouard 2349: d=p/q;
2350: u=x+d;
2351: if (u-a < tol2 || b-u < tol2)
2352: d=SIGN(tol1,xm-x);
1.126 brouard 2353: }
2354: } else {
2355: d=CGOLD*(e=(x >= xm ? a-x : b-x));
2356: }
2357: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
2358: fu=(*f)(u);
2359: if (fu <= fx) {
2360: if (u >= x) a=x; else b=x;
2361: SHFT(v,w,x,u)
1.183 brouard 2362: SHFT(fv,fw,fx,fu)
2363: } else {
2364: if (u < x) a=u; else b=u;
2365: if (fu <= fw || w == x) {
1.224 brouard 2366: v=w;
2367: w=u;
2368: fv=fw;
2369: fw=fu;
1.183 brouard 2370: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 2371: v=u;
2372: fv=fu;
1.183 brouard 2373: }
2374: }
1.126 brouard 2375: }
2376: nrerror("Too many iterations in brent");
2377: *xmin=x;
2378: return fx;
2379: }
2380:
2381: /****************** mnbrak ***********************/
2382:
2383: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
2384: double (*func)(double))
1.183 brouard 2385: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
2386: the downhill direction (defined by the function as evaluated at the initial points) and returns
2387: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
2388: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
2389: */
1.126 brouard 2390: double ulim,u,r,q, dum;
2391: double fu;
1.187 brouard 2392:
2393: double scale=10.;
2394: int iterscale=0;
2395:
2396: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
2397: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
2398:
2399:
2400: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
2401: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
2402: /* *bx = *ax - (*ax - *bx)/scale; */
2403: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
2404: /* } */
2405:
1.126 brouard 2406: if (*fb > *fa) {
2407: SHFT(dum,*ax,*bx,dum)
1.183 brouard 2408: SHFT(dum,*fb,*fa,dum)
2409: }
1.126 brouard 2410: *cx=(*bx)+GOLD*(*bx-*ax);
2411: *fc=(*func)(*cx);
1.183 brouard 2412: #ifdef DEBUG
1.224 brouard 2413: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
2414: 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 2415: #endif
1.224 brouard 2416: 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 2417: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 2418: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 2419: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 2420: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
2421: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
2422: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 2423: fu=(*func)(u);
1.163 brouard 2424: #ifdef DEBUG
2425: /* f(x)=A(x-u)**2+f(u) */
2426: double A, fparabu;
2427: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2428: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 2429: 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);
2430: 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 2431: /* And thus,it can be that fu > *fc even if fparabu < *fc */
2432: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
2433: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
2434: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 2435: #endif
1.184 brouard 2436: #ifdef MNBRAKORIGINAL
1.183 brouard 2437: #else
1.191 brouard 2438: /* if (fu > *fc) { */
2439: /* #ifdef DEBUG */
2440: /* printf("mnbrak4 fu > fc \n"); */
2441: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
2442: /* #endif */
2443: /* /\* 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 *\\/ *\/ */
2444: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2445: /* dum=u; /\* Shifting c and u *\/ */
2446: /* u = *cx; */
2447: /* *cx = dum; */
2448: /* dum = fu; */
2449: /* fu = *fc; */
2450: /* *fc =dum; */
2451: /* } else { /\* end *\/ */
2452: /* #ifdef DEBUG */
2453: /* printf("mnbrak3 fu < fc \n"); */
2454: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2455: /* #endif */
2456: /* dum=u; /\* Shifting c and u *\/ */
2457: /* u = *cx; */
2458: /* *cx = dum; */
2459: /* dum = fu; */
2460: /* fu = *fc; */
2461: /* *fc =dum; */
2462: /* } */
1.224 brouard 2463: #ifdef DEBUGMNBRAK
2464: double A, fparabu;
2465: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2466: fparabu= *fa - A*(*ax-u)*(*ax-u);
2467: 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);
2468: 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 2469: #endif
1.191 brouard 2470: dum=u; /* Shifting c and u */
2471: u = *cx;
2472: *cx = dum;
2473: dum = fu;
2474: fu = *fc;
2475: *fc =dum;
1.183 brouard 2476: #endif
1.162 brouard 2477: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2478: #ifdef DEBUG
1.224 brouard 2479: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2480: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2481: #endif
1.126 brouard 2482: fu=(*func)(u);
2483: if (fu < *fc) {
1.183 brouard 2484: #ifdef DEBUG
1.224 brouard 2485: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2486: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2487: #endif
2488: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2489: SHFT(*fb,*fc,fu,(*func)(u))
2490: #ifdef DEBUG
2491: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2492: #endif
2493: }
1.162 brouard 2494: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2495: #ifdef DEBUG
1.224 brouard 2496: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2497: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2498: #endif
1.126 brouard 2499: u=ulim;
2500: fu=(*func)(u);
1.183 brouard 2501: } else { /* u could be left to b (if r > q parabola has a maximum) */
2502: #ifdef DEBUG
1.224 brouard 2503: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2504: 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 2505: #endif
1.126 brouard 2506: u=(*cx)+GOLD*(*cx-*bx);
2507: fu=(*func)(u);
1.224 brouard 2508: #ifdef DEBUG
2509: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2510: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2511: #endif
1.183 brouard 2512: } /* end tests */
1.126 brouard 2513: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2514: SHFT(*fa,*fb,*fc,fu)
2515: #ifdef DEBUG
1.224 brouard 2516: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2517: 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 2518: #endif
2519: } /* 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 2520: }
2521:
2522: /*************** linmin ************************/
1.162 brouard 2523: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2524: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2525: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2526: the value of func at the returned location p . This is actually all accomplished by calling the
2527: routines mnbrak and brent .*/
1.126 brouard 2528: int ncom;
2529: double *pcom,*xicom;
2530: double (*nrfunc)(double []);
2531:
1.224 brouard 2532: #ifdef LINMINORIGINAL
1.126 brouard 2533: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2534: #else
2535: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2536: #endif
1.126 brouard 2537: {
2538: double brent(double ax, double bx, double cx,
2539: double (*f)(double), double tol, double *xmin);
2540: double f1dim(double x);
2541: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2542: double *fc, double (*func)(double));
2543: int j;
2544: double xx,xmin,bx,ax;
2545: double fx,fb,fa;
1.187 brouard 2546:
1.203 brouard 2547: #ifdef LINMINORIGINAL
2548: #else
2549: double scale=10., axs, xxs; /* Scale added for infinity */
2550: #endif
2551:
1.126 brouard 2552: ncom=n;
2553: pcom=vector(1,n);
2554: xicom=vector(1,n);
2555: nrfunc=func;
2556: for (j=1;j<=n;j++) {
2557: pcom[j]=p[j];
1.202 brouard 2558: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2559: }
1.187 brouard 2560:
1.203 brouard 2561: #ifdef LINMINORIGINAL
2562: xx=1.;
2563: #else
2564: axs=0.0;
2565: xxs=1.;
2566: do{
2567: xx= xxs;
2568: #endif
1.187 brouard 2569: ax=0.;
2570: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2571: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2572: /* 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)) */
2573: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2574: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2575: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2576: /* 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 2577: #ifdef LINMINORIGINAL
2578: #else
2579: if (fx != fx){
1.224 brouard 2580: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2581: printf("|");
2582: fprintf(ficlog,"|");
1.203 brouard 2583: #ifdef DEBUGLINMIN
1.224 brouard 2584: 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 2585: #endif
2586: }
1.224 brouard 2587: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2588: #endif
2589:
1.191 brouard 2590: #ifdef DEBUGLINMIN
2591: 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 2592: 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 2593: #endif
1.224 brouard 2594: #ifdef LINMINORIGINAL
2595: #else
1.317 brouard 2596: if(fb == fx){ /* Flat function in the direction */
2597: xmin=xx;
1.224 brouard 2598: *flat=1;
1.317 brouard 2599: }else{
1.224 brouard 2600: *flat=0;
2601: #endif
2602: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2603: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2604: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2605: /* fmin = f(p[j] + xmin * xi[j]) */
2606: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2607: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2608: #ifdef DEBUG
1.224 brouard 2609: 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);
2610: 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);
2611: #endif
2612: #ifdef LINMINORIGINAL
2613: #else
2614: }
1.126 brouard 2615: #endif
1.191 brouard 2616: #ifdef DEBUGLINMIN
2617: printf("linmin end ");
1.202 brouard 2618: fprintf(ficlog,"linmin end ");
1.191 brouard 2619: #endif
1.126 brouard 2620: for (j=1;j<=n;j++) {
1.203 brouard 2621: #ifdef LINMINORIGINAL
2622: xi[j] *= xmin;
2623: #else
2624: #ifdef DEBUGLINMIN
2625: if(xxs <1.0)
2626: printf(" before xi[%d]=%12.8f", j,xi[j]);
2627: #endif
2628: 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) */
2629: #ifdef DEBUGLINMIN
2630: if(xxs <1.0)
2631: 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 );
2632: #endif
2633: #endif
1.187 brouard 2634: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2635: }
1.191 brouard 2636: #ifdef DEBUGLINMIN
1.203 brouard 2637: printf("\n");
1.191 brouard 2638: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2639: 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 2640: for (j=1;j<=n;j++) {
1.202 brouard 2641: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2642: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2643: if(j % ncovmodel == 0){
1.191 brouard 2644: printf("\n");
1.202 brouard 2645: fprintf(ficlog,"\n");
2646: }
1.191 brouard 2647: }
1.203 brouard 2648: #else
1.191 brouard 2649: #endif
1.126 brouard 2650: free_vector(xicom,1,n);
2651: free_vector(pcom,1,n);
2652: }
2653:
1.359 brouard 2654: /**** praxis gegen ****/
2655:
2656: /* This has been tested by Visual C from Microsoft and works */
2657: /* meaning tha valgrind could be wrong */
2658: /*********************************************************************/
2659: /* f u n c t i o n p r a x i s */
2660: /* */
2661: /* praxis is a general purpose routine for the minimization of a */
2662: /* function in several variables. the algorithm used is a modifi- */
2663: /* cation of conjugate gradient search method by powell. the changes */
2664: /* are due to r.p. brent, who gives an algol-w program, which served */
2665: /* as a basis for this function. */
2666: /* */
2667: /* references: */
2668: /* - powell, m.j.d., 1964. an efficient method for finding */
2669: /* the minimum of a function in several variables without */
2670: /* calculating derivatives, computer journal, 7, 155-162 */
2671: /* - brent, r.p., 1973. algorithms for minimization without */
2672: /* derivatives, prentice hall, englewood cliffs. */
2673: /* */
2674: /* problems, suggestions or improvements are always wellcome */
2675: /* karl gegenfurtner 07/08/87 */
2676: /* c - version */
2677: /*********************************************************************/
2678: /* */
2679: /* usage: min = praxis(tol, macheps, h, n, prin, x, func) */
2680: /* macheps has been suppressed because it is replaced by DBL_EPSILON */
2681: /* and if it was an argument of praxis (as it is in original brent) */
2682: /* it should be declared external */
2683: /* usage: min = praxis(tol, h, n, prin, x, func) */
2684: /* was min = praxis(fun, x, n); */
2685: /* */
2686: /* fun the function to be minimized. fun is called from */
2687: /* praxis with x and n as arguments */
2688: /* x a double array containing the initial guesses for */
2689: /* the minimum, which will contain the solution on */
2690: /* return */
2691: /* n an integer specifying the number of unknown */
2692: /* parameters */
2693: /* min praxis returns the least calculated value of fun */
2694: /* */
2695: /* some additional global variables control some more aspects of */
2696: /* the inner workings of praxis. setting them is optional, they */
2697: /* are all set to some reasonable default values given below. */
2698: /* */
2699: /* prin controls the printed output from the routine. */
2700: /* 0 -> no output */
2701: /* 1 -> print only starting and final values */
2702: /* 2 -> detailed map of the minimization process */
2703: /* 3 -> print also eigenvalues and vectors of the */
2704: /* search directions */
2705: /* the default value is 1 */
2706: /* tol is the tolerance allowed for the precision of the */
2707: /* solution. praxis returns if the criterion */
2708: /* 2 * ||x[k]-x[k-1]|| <= sqrt(macheps) * ||x[k]|| + tol */
2709: /* is fulfilled more than ktm times. */
2710: /* the default value depends on the machine precision */
2711: /* ktm see just above. default is 1, and a value of 4 leads */
2712: /* to a very(!) cautious stopping criterion. */
2713: /* h0 or step is a steplength parameter and should be set equal */
2714: /* to the expected distance from the solution. */
2715: /* exceptionally small or large values of step lead to */
2716: /* slower convergence on the first few iterations */
2717: /* the default value for step is 1.0 */
2718: /* scbd is a scaling parameter. 1.0 is the default and */
2719: /* indicates no scaling. if the scales for the different */
2720: /* parameters are very different, scbd should be set to */
2721: /* a value of about 10.0. */
2722: /* illc should be set to true (1) if the problem is known to */
2723: /* be ill-conditioned. the default is false (0). this */
2724: /* variable is automatically set, when praxis finds */
2725: /* the problem to be ill-conditioned during iterations. */
2726: /* maxfun is the maximum number of calls to fun allowed. praxis */
2727: /* will return after maxfun calls to fun even when the */
2728: /* minimum is not yet found. the default value of 0 */
2729: /* indicates no limit on the number of calls. */
2730: /* this return condition is only checked every n */
2731: /* iterations. */
2732: /* */
2733: /*********************************************************************/
2734:
2735: #include <math.h>
2736: #include <stdio.h>
2737: #include <stdlib.h>
2738: #include <float.h> /* for DBL_EPSILON */
2739: /* #include "machine.h" */
2740:
2741:
2742: /* extern void minfit(int n, double eps, double tol, double **ab, double q[]); */
2743: /* extern void minfit(int n, double eps, double tol, double ab[N][N], double q[]); */
2744: /* control parameters */
2745: /* control parameters */
2746: #define SQREPSILON 1.0e-19
2747: /* #define EPSILON 1.0e-8 */ /* in main */
2748:
2749: double tol = SQREPSILON,
2750: scbd = 1.0,
2751: step = 1.0;
2752: int ktm = 1,
2753: /* prin = 2, */
2754: maxfun = 0,
2755: illc = 0;
2756:
2757: /* some global variables */
2758: static int i, j, k, k2, nl, nf, kl, kt;
2759: /* static double s; */
2760: double sl, dn, dmin,
2761: fx, f1, lds, ldt, sf, df,
2762: qf1, qd0, qd1, qa, qb, qc,
2763: m2, m4, small_windows, vsmall, large,
2764: vlarge, ldfac, t2;
2765: /* static double d[N], y[N], z[N], */
2766: /* q0[N], q1[N], v[N][N]; */
2767:
2768: static double *d, *y, *z;
2769: static double *q0, *q1, **v;
2770: double *tflin; /* used in flin: return (*fun)(tflin, n); */
2771: double *e; /* used in minfit, don't konw how to free memory and thus made global */
2772: /* static double s, sl, dn, dmin, */
2773: /* fx, f1, lds, ldt, sf, df, */
2774: /* qf1, qd0, qd1, qa, qb, qc, */
2775: /* m2, m4, small, vsmall, large, */
2776: /* vlarge, ldfac, t2; */
2777: /* static double d[N], y[N], z[N], */
2778: /* q0[N], q1[N], v[N][N]; */
2779:
2780: /* these will be set by praxis to point to it's arguments */
2781: static int prin; /* added */
2782: static int n;
2783: static double *x;
2784: static double (*fun)();
2785: /* static double (*fun)(double *x, int n); */
2786:
2787: /* these will be set by praxis to the global control parameters */
2788: /* static double h, macheps, t; */
2789: extern double macheps;
2790: static double h;
2791: static double t;
2792:
2793: static double
2794: drandom() /* return random no between 0 and 1 */
2795: {
2796: return (double)(rand()%(8192*2))/(double)(8192*2);
2797: }
2798:
2799: static void sort() /* d and v in descending order */
2800: {
2801: int k, i, j;
2802: double s;
2803:
2804: for (i=1; i<=n-1; i++) {
2805: k = i; s = d[i];
2806: for (j=i+1; j<=n; j++) {
2807: if (d[j] > s) {
2808: k = j;
2809: s = d[j];
2810: }
2811: }
2812: if (k > i) {
2813: d[k] = d[i];
2814: d[i] = s;
2815: for (j=1; j<=n; j++) {
2816: s = v[j][i];
2817: v[j][i] = v[j][k];
2818: v[j][k] = s;
2819: }
2820: }
2821: }
2822: }
2823:
2824: double randbrent ( int *naught )
2825: {
2826: double ran1, ran3[127], half;
2827: int ran2, q, r, i, j;
2828: int init=0; /* false */
2829: double rr;
2830: /* REAL*8 RAN1,RAN3(127),HALF */
2831:
2832: /* INTEGER RAN2,Q,R */
2833: /* LOGICAL INIT */
2834: /* DATA INIT/.FALSE./ */
2835: /* IF (INIT) GO TO 3 */
2836: if(!init){
2837: /* R = MOD(NAUGHT,8190) + 1 *//* 1804289383 rand () */
2838: r = *naught % 8190 + 1;/* printf(" naught r %d %d",*naught,r); */
2839: ran2=127;
2840: for(i=ran2; i>0; i--){
2841: /* RAN2 = 128 */
2842: /* DO 2 I=1,127 */
2843: ran2 = ran2-1;
2844: /* RAN2 = RAN2 - 1 */
2845: ran1 = -pow(2.0,55);
2846: /* RAN1 = -2.D0**55 */
2847: /* DO 1 J=1,7 */
2848: for(j=1; j<=7;j++){
2849: /* R = MOD(1756*R,8191) */
2850: r = (1756*r) % 8191;/* printf(" i=%d (1756*r)%8191=%d",j,r); */
2851: q=r/32;
2852: /* Q = R/32 */
2853: /* 1 RAN1 = (RAN1 + Q)*(1.0D0/256) */
2854: ran1 =(ran1+q)*(1.0/256);
2855: }
2856: /* 2 RAN3(RAN2) = RAN1 */
2857: ran3[ran2] = ran1; /* printf(" ran2=%d ran1=%.7g \n",ran2,ran1); */
2858: }
2859: /* INIT = .TRUE. */
2860: init=1;
2861: /* 3 IF (RAN2.EQ.1) RAN2 = 128 */
2862: }
2863: if(ran2 == 0) ran2 = 126;
2864: else ran2 = ran2 -1;
2865: /* RAN2 = RAN2 - 1 */
2866: /* RAN1 = RAN1 + RAN3(RAN2) */
2867: ran1 = ran1 + ran3[ran2];/* printf("BIS ran2=%d ran1=%.7g \n",ran2,ran1); */
2868: half= 0.5;
2869: /* HALF = .5D0 */
2870: /* IF (RAN1.GE.0.D0) HALF = -HALF */
2871: if(ran1 >= 0.) half =-half;
2872: ran1 = ran1 +half;
2873: ran3[ran2] = ran1;
2874: rr= ran1+0.5;
2875: /* RAN1 = RAN1 + HALF */
2876: /* RAN3(RAN2) = RAN1 */
2877: /* RANDOM = RAN1 + .5D0 */
2878: /* r = ( ( double ) ( *seed ) ) * 4.656612875E-10; */
2879: return rr;
2880: }
2881: static void matprint(char *s, double **v, int m, int n)
2882: /* char *s; */
2883: /* double v[N][N]; */
2884: {
2885: #define INCX 8
2886: int i;
2887:
2888: int i2hi;
2889: int ihi;
2890: int ilo;
2891: int i2lo;
2892: int jlo=1;
2893: int j;
2894: int j2hi;
2895: int jhi;
2896: int j2lo;
2897: ilo=1;
2898: ihi=n;
2899: jlo=1;
2900: jhi=n;
2901:
2902: printf ("\n" );
2903: printf ("%s\n", s );
2904: for ( j2lo = jlo; j2lo <= jhi; j2lo = j2lo + INCX )
2905: {
2906: j2hi = j2lo + INCX - 1;
2907: if ( n < j2hi )
2908: {
2909: j2hi = n;
2910: }
2911: if ( jhi < j2hi )
2912: {
2913: j2hi = jhi;
2914: }
2915:
2916: /* fprintf ( ficlog, "\n" ); */
2917: printf ("\n" );
2918: /*
2919: For each column J in the current range...
2920:
2921: Write the header.
2922: */
2923: /* fprintf ( ficlog, " Col: "); */
2924: printf ("Col:");
2925: for ( j = j2lo; j <= j2hi; j++ )
2926: {
2927: /* fprintf ( ficlog, " %7d ", j - 1 ); */
2928: /* printf (" %9d ", j - 1 ); */
2929: printf (" %9d ", j );
2930: }
2931: /* fprintf ( ficlog, "\n" ); */
2932: /* fprintf ( ficlog, " Row\n" ); */
2933: /* fprintf ( ficlog, "\n" ); */
2934: printf ("\n" );
2935: printf (" Row\n" );
2936: printf ("\n" );
2937: /*
2938: Determine the range of the rows in this strip.
2939: */
2940: if ( 1 < ilo ){
2941: i2lo = ilo;
2942: }else{
2943: i2lo = 1;
2944: }
2945: if ( m < ihi ){
2946: i2hi = m;
2947: }else{
2948: i2hi = ihi;
2949: }
2950:
2951: for ( i = i2lo; i <= i2hi; i++ ){
2952: /*
2953: Print out (up to) 5 entries in row I, that lie in the current strip.
2954: */
2955: /* fprintf ( ficlog, "%5d:", i - 1 ); */
2956: /* printf ("%5d:", i - 1 ); */
2957: printf ("%5d:", i );
2958: for ( j = j2lo; j <= j2hi; j++ )
2959: {
2960: /* fprintf ( ficlog, " %14g", a[i-1+(j-1)*m] ); */
2961: /* printf ("%14.7g ", a[i-1+(j-1)*m] ); */
2962: /* printf("%14.7f ", v[i-1][j-1]); */
2963: printf("%14.7f ", v[i][j]);
2964: /* fprintf ( stdout, " %14g", a[i-1+(j-1)*m] ); */
2965: }
2966: /* fprintf ( ficlog, "\n" ); */
2967: printf ("\n" );
2968: }
2969: }
2970:
2971: /* printf("%s\n", s); */
2972: /* for (k=0; k<n; k++) { */
2973: /* for (i=0; i<n; i++) { */
2974: /* /\* printf("%20.10e ", v[k][i]); *\/ */
2975: /* } */
2976: /* printf("\n"); */
2977: /* } */
2978: #undef INCX
2979: }
2980:
2981: void vecprint(char *s, double *x, int n)
2982: /* char *s; */
2983: /* double x[N]; */
2984: {
2985: int i=0;
2986:
2987: printf(" %s", s);
2988: /* for (i=0; i<n; i++) */
2989: for (i=1; i<=n; i++)
2990: printf (" %14.7g", x[i] );
2991: /* printf(" %8d: %14g\n", i, x[i]); */
2992: printf ("\n" );
2993: }
2994:
2995: static void print() /* print a line of traces */
2996: {
2997:
2998:
2999: printf("\n");
3000: /* printf("... chi square reduced to ... %20.10e\n", fx); */
3001: /* printf("... after %u function calls ...\n", nf); */
3002: /* printf("... including %u linear searches ...\n", nl); */
3003: printf("%10d %10d%14.7g",nl, nf, fx);
3004: vecprint("... current values of x ...", x, n);
3005: }
3006: /* static void print2(int n, double *x, int prin, double fx, int nf, int nl) */ /* print a line of traces */
3007: static void print2() /* print a line of traces */
3008: {
3009: int i; double fmin=0.;
3010:
3011: /* printf("\n"); */
3012: /* printf("... chi square reduced to ... %20.10e\n", fx); */
3013: /* printf("... after %u function calls ...\n", nf); */
3014: /* printf("... including %u linear searches ...\n", nl); */
3015: /* printf("%10d %10d%14.7g",nl, nf, fx); */
3016: printf ( "\n" );
3017: printf ( " Linear searches %d", nl );
3018: /* printf ( " Linear searches %d\n", nl ); */
3019: /* printf ( " Function evaluations %d\n", nf ); */
3020: /* printf ( " Function value FX = %g\n", fx ); */
3021: printf ( " Function evaluations %d", nf );
3022: printf ( " Function value FX = %.12lf\n", fx );
3023: #ifdef DEBUGPRAX
3024: printf("n=%d prin=%d\n",n,prin);
3025: #endif
3026: if(fx <= fmin) printf(" UNDEFINED "); else printf("%14.7g",log(fx-fmin));
3027: if ( n <= 4 || 2 < prin )
3028: {
3029: /* for(i=1;i<=n;i++)printf("%14.7g",x[i-1]); */
3030: for(i=1;i<=n;i++)printf("%14.7g",x[i]);
3031: /* r8vec_print ( n, x, " X:" ); */
3032: }
3033: printf("\n");
3034: }
3035:
3036:
3037: /* #ifdef MSDOS */
3038: /* static double tflin[N]; */
3039: /* #endif */
3040:
3041: static double flin(double l, int j)
3042: /* double l; */
3043: {
3044: int i;
3045: /* #ifndef MSDOS */
3046: /* double tflin[N]; */
3047: /* #endif */
3048: /* double *tflin; */ /* Be careful to put tflin on a vector n */
3049:
3050: /* j is used from 0 to n-1 and can be -1 for parabolic search */
3051:
3052: /* if (j != -1) { /\* linear search *\/ */
3053: if (j > 0) { /* linear search */
3054: /* for (i=0; i<n; i++){ */
3055: for (i=1; i<=n; i++){
3056: tflin[i] = x[i] + l *v[i][j];
3057: #ifdef DEBUGPRAX
3058: /* 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); */
3059: 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);
3060: #endif
3061: }
3062: }
3063: else { /* search along parabolic space curve */
3064: qa = l*(l-qd1)/(qd0*(qd0+qd1));
3065: qb = (l+qd0)*(qd1-l)/(qd0*qd1);
3066: qc = l*(l+qd0)/(qd1*(qd0+qd1));
3067: #ifdef DEBUGPRAX
3068: 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);
3069: #endif
3070: /* for (i=0; i<n; i++){ */
3071: for (i=1; i<=n; i++){
3072: tflin[i] = qa*q0[i]+qb*x[i]+qc*q1[i];
3073: #ifdef DEBUGPRAX
3074: /* 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]); */
3075: 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]);
3076: #endif
3077: }
3078: }
3079: nf++;
3080:
3081: #ifdef NR_SHIFT
3082: return (*fun)((tflin-1), n);
3083: #else
3084: /* return (*fun)(tflin, n);*/
3085: return (*fun)(tflin);
3086: #endif
3087: }
3088:
3089: void minny(int j, int nits, double *d2, double *x1, double f1, int fk)
3090: /* double *d2, *x1, f1; */
3091: {
3092: /* here j is from 0 to n-1 and can be -1 for parabolic search */
3093: /* MINIMIZES F FROM X IN THE DIRECTION V(*,J) */
3094: /* UNLESS J<1, WHEN A QUADRATIC SEARCH IS DONE */
3095: /* IN THE PLANE DEFINED BY Q0, Q1 AND X. */
3096: /* D2 AN APPROXIMATION TO HALF F'' (OR ZERO), */
3097: /* X1 AN ESTIMATE OF DISTANCE TO MINIMUM, */
3098: /* RETURNED AS THE DISTANCE FOUND. */
3099: /* IF FK = TRUE THEN F1 IS FLIN(X1), OTHERWISE */
3100: /* X1 AND F1 ARE IGNORED ON ENTRY UNLESS FINAL */
3101: /* FX > F1. NITS CONTROLS THE NUMBER OF TIMES */
3102: /* AN ATTEMPT IS MADE TO HALVE THE INTERVAL. */
3103: /* SIDE EFFECTS: USES AND ALTERS X, FX, NF, NL. */
3104: /* IF J < 1 USES VARIABLES Q... . */
3105: /* USES H, N, T, M2, M4, LDT, DMIN, MACHEPS; */
3106: int k, i, dz;
3107: double x2, xm, f0, f2, fm, d1, t2, sf1, sx1;
3108: double s;
3109: double macheps;
3110: macheps=pow(16.0,-13.0);
3111: sf1 = f1; sx1 = *x1;
3112: k = 0; xm = 0.0; fm = f0 = fx; dz = *d2 < macheps;
3113: /* h=1.0;*/ /* To be revised */
3114: #ifdef DEBUGPRAX
3115: /* printf("min macheps=%14g h=%14g step=%14g t=%14g fx=%14g\n",macheps,h, step,t, fx); */
3116: /* Where is fx coming from */
3117: printf(" min macheps=%14g h=%14g t=%14g fx=%.9lf dirj=%d\n",macheps, h, t, fx, j);
3118: matprint(" min vectors:",v,n,n);
3119: #endif
3120: /* find step size */
3121: s = 0.;
3122: /* for (i=0; i<n; i++) s += x[i]*x[i]; */
3123: for (i=1; i<=n; i++) s += x[i]*x[i];
3124: s = sqrt(s);
3125: if (dz)
3126: t2 = m4*sqrt(fabs(fx)/dmin + s*ldt) + m2*ldt;
3127: else
3128: t2 = m4*sqrt(fabs(fx)/(*d2) + s*ldt) + m2*ldt;
3129: s = s*m4 + t;
3130: if (dz && t2 > s) t2 = s;
3131: if (t2 < small_windows) t2 = small_windows;
3132: if (t2 > 0.01*h) t2 = 0.01 * h;
3133: if (fk && f1 <= fm) {
3134: xm = *x1;
3135: fm = f1;
3136: }
3137: #ifdef DEBUGPRAX
3138: printf(" additional flin X1=%14.7f t2=%14.7f *f1=%14.7f fm=%14.7f fk=%d\n",*x1,t2,f1,fm,fk);
3139: #endif
3140: if (!fk || fabs(*x1) < t2) {
3141: *x1 = (*x1 >= 0 ? t2 : -t2);
3142: /* *x1 = (*x1 > 0 ? t2 : -t2); */ /* kind of error */
3143: #ifdef DEBUGPRAX
3144: printf(" additional flin X1=%16.10e dirj=%d fk=%d\n",*x1, j, fk);
3145: #endif
3146: f1 = flin(*x1, j);
3147: #ifdef DEBUGPRAX
3148: printf(" after flin f1=%18.12e dirj=%d fk=%d\n",f1, j,fk);
3149: #endif
3150: }
3151: if (f1 <= fm) {
3152: xm = *x1;
3153: fm = f1;
3154: }
3155: L0: /*L0 loop or next */
3156: /*
3157: Evaluate FLIN at another point and estimate the second derivative.
3158: */
3159: if (dz) {
3160: x2 = (f0 < f1 ? -(*x1) : 2*(*x1));
3161: #ifdef DEBUGPRAX
3162: printf(" additional second flin x2=%14.8e x1=%14.8e f0=%14.8e f1=%18.12e dirj=%d\n",x2,*x1,f0,f1,j);
3163: #endif
3164: f2 = flin(x2, j);
3165: #ifdef DEBUGPRAX
3166: 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);
3167: #endif
3168: if (f2 <= fm) {
3169: xm = x2;
3170: fm = f2;
3171: }
3172: /* d2 is the curvature or double difference f1 doesn't seem to be accurately computed */
3173: *d2 = (x2*(f1-f0) - (*x1)*(f2-f0))/((*x1)*x2*((*x1)-x2));
3174: #ifdef DEBUGPRAX
3175: double d11,d12;
3176: d11=(f1-f0)/(*x1);d12=(f2-f0)/x2;
3177: 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)));
3178: 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);
3179: double ff1=7.783920622852e+04;
3180: double f1mf0=9.0344736236e-05;
3181: *d2 = (f1mf0)/ (*x1)/((*x1)-x2) - (f2-f0)/x2/((*x1)-x2);
3182: /* *d2 = (ff1-f0)/ (*x1)/((*x1)-x2) - (f2-f0)/x2/((*x1)-x2); */
3183: printf(" simpliff computing *d2=%16.10e f1mf0=%18.12e,f1=f0+f1mf0=%18.12e\n",*d2,f1mf0,f0+f1mf0);
3184: *d2 = ((f1-f0)/ (*x1) - (f2-f0)/x2)/((*x1)-x2);
3185: printf(" overlifi computing *d2=%16.10e\n",*d2);
3186: #endif
3187: *d2 = ((f1-f0)/ (*x1) - (f2-f0)/x2)/((*x1)-x2);
3188: }
3189: #ifdef DEBUGPRAX
3190: printf(" additional second flin xm=%14.8e fm=%14.8e *d2=%14.8e\n",xm, fm,*d2);
3191: #endif
3192: /*
3193: Estimate the first derivative at 0.
3194: */
3195: d1 = (f1-f0)/(*x1) - *x1**d2; dz = 1;
3196: /*
3197: Predict the minimum.
3198: */
3199: if (*d2 <= small_windows) {
3200: x2 = (d1 < 0 ? h : -h);
3201: }
3202: else {
3203: x2 = - 0.5*d1/(*d2);
3204: }
3205: #ifdef DEBUGPRAX
3206: 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);
3207: #endif
3208: if (fabs(x2) > h)
3209: x2 = (x2 > 0 ? h : -h);
3210: L1: /* L1 or try loop */
3211: #ifdef DEBUGPRAX
3212: printf(" AT predicted minimum flin x2=%14.8e x1=%14.8e K=%14d NITS=%14d dirj=%d\n",x2,*x1,k,nits,j);
3213: #endif
3214: f2 = flin(x2, j); /* x[i]+x2*v[i][j] */
3215: #ifdef DEBUGPRAX
3216: printf(" after flin f0=%14.8e f1=%14.8e f2=%14.8e fm=%14.8e\n",f0,f1,f2, fm);
3217: #endif
3218: if ((k < nits) && (f2 > f0)) {
3219: #ifdef DEBUGPRAX
3220: printf(" NO SUCCESS SO TRY AGAIN;\n");
3221: #endif
3222: k++;
3223: if ((f0 < f1) && (*x1*x2 > 0.0))
3224: goto L0; /* or next */
3225: x2 *= 0.5;
3226: goto L1;
3227: }
3228: nl++;
3229: #ifdef DEBUGPRAX
3230: 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);
3231: #endif
3232: if (f2 > fm) x2 = xm; else fm = f2;
3233: if (fabs(x2*(x2-*x1)) > small_windows) {
3234: *d2 = (x2*(f1-f0) - *x1*(fm-f0))/(*x1*x2*(*x1-x2));
3235: }
3236: else {
3237: if (k > 0) *d2 = 0;
3238: }
3239: #ifdef DEBUGPRAX
1.362 ! brouard 3240: 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 3241: #endif
3242: if (*d2 <= small_windows) *d2 = small_windows;
3243: *x1 = x2; fx = fm;
3244: if (sf1 < fx) {
3245: fx = sf1;
3246: *x1 = sx1;
3247: }
3248: /*
3249: Update X for linear search.
3250: */
3251: #ifdef DEBUGPRAX
3252: printf(" end of min x1=%14.8e fx=%14.8e d2=%14.8e\n",*x1, fx, *d2);
3253: #endif
3254:
3255: /* if (j != -1) */
3256: /* for (i=0; i<n; i++) */
3257: /* x[i] += (*x1)*v[i][j]; */
3258: if (j > 0)
3259: for (i=1; i<=n; i++)
3260: x[i] += (*x1)*v[i][j];
3261: }
3262:
3263: void quad() /* look for a minimum along the curve q0, q1, q2 */
3264: {
3265: int i;
3266: double l, s;
3267:
3268: s = fx; fx = qf1; qf1 = s; qd1 = 0.0;
3269: /* for (i=0; i<n; i++) { */
3270: for (i=1; i<=n; i++) {
3271: s = x[i]; l = q1[i]; x[i] = l; q1[i] = s;
3272: qd1 = qd1 + (s-l)*(s-l);
3273: }
3274: s = 0.0; qd1 = sqrt(qd1); l = qd1;
3275: #ifdef DEBUGPRAX
3276: printf(" QUAD after sqrt qd1=%14.8e \n",qd1);
3277: #endif
3278:
3279: if (qd0>0.0 && qd1>0.0 &&nl>=3*n*n) {
3280: #ifdef DEBUGPRAX
3281: printf(" QUAD before min value=%14.8e \n",qf1);
3282: #endif
3283: /* min(-1, 2, &s, &l, qf1, 1); */
3284: minny(0, 2, &s, &l, qf1, 1);
3285: qa = l*(l-qd1)/(qd0*(qd0+qd1));
3286: qb = (l+qd0)*(qd1-l)/(qd0*qd1);
3287: qc = l*(l+qd0)/(qd1*(qd0+qd1));
3288: }
3289: else {
3290: fx = qf1; qa = qb = 0.0; qc = 1.0;
3291: }
3292: #ifdef DEBUGPRAX
3293: printf("after eventual min qd0=%14.8e qd1=%14.8e nl=%d\n",qd0, qd1,nl);
3294: #endif
3295: qd0 = qd1;
3296: /* for (i=0; i<n; i++) { */
3297: for (i=1; i<=n; i++) {
3298: s = q0[i]; q0[i] = x[i];
3299: x[i] = qa*s + qb*x[i] + qc*q1[i];
3300: }
3301: #ifdef DEBUGQUAD
3302: vecprint ( " X after QUAD:" , x, n );
3303: #endif
3304: }
3305:
3306: /* void minfit(int n, double eps, double tol, double ab[N][N], double q[]) */
3307: void minfit(int n, double eps, double tol, double **ab, double q[])
3308: /* int n; */
3309: /* double eps, tol, ab[N][N], q[N]; */
3310: {
3311: int l, kt, l2, i, j, k;
3312: double c, f, g, h, s, x, y, z;
3313: /* double eps; */
3314: /* #ifndef MSDOS */
3315: /* double e[N]; /\* plenty of stack on a vax *\/ */
3316: /* #endif */
3317: /* double *e; */
3318: /* e=vector(0,n-1); /\* should be freed somewhere but gotos *\/ */
3319:
3320: /* householder's reduction to bidiagonal form */
3321:
3322: if(n==1){
3323: /* q[1-1]=ab[1-1][1-1]; */
3324: /* ab[1-1][1-1]=1.0; */
3325: q[1]=ab[1][1];
3326: ab[1][1]=1.0;
3327: return; /* added from hardt */
3328: }
3329: /* eps=macheps; */ /* added */
3330: x = g = 0.0;
3331: #ifdef DEBUGPRAX
3332: matprint (" HOUSE holder:", ab, n, n);
3333: #endif
3334:
3335: /* for (i=0; i<n; i++) { /\* FOR I := 1 UNTIL N DO *\/ */
3336: for (i=1; i<=n; i++) { /* FOR I := 1 UNTIL N DO */
3337: e[i] = g; s = 0.0; l = i+1;
3338: /* for (j=i; j<n; j++) /\* FOR J := I UNTIL N DO S := S*AB(J,I)**2; *\/ /\* not correct *\/ */
3339: for (j=i; j<=n; j++) /* FOR J := I UNTIL N DO S := S*AB(J,I)**2; */ /* not correct */
3340: s += ab[j][i] * ab[j][i];
3341: #ifdef DEBUGPRAXFIN
3342: printf("i=%d s=%d %.7g tol=%.7g",i,s,tol);
3343: #endif
3344: if (s < tol) {
3345: g = 0.0;
3346: }
3347: else {
3348: /* f = ab[i][i]; */
3349: f = ab[i][i];
3350: if (f < 0.0)
3351: g = sqrt(s);
3352: else
3353: g = -sqrt(s);
3354: /* h = f*g - s; ab[i][i] = f - g; */
3355: h = f*g - s; ab[i][i] = f - g;
3356: /* for (j=l; j<n; j++) { */ /* FOR J := L UNTIL N DO */ /* wrong */
3357: for (j=l; j<=n; j++) {
3358: f = 0.0;
3359: /* for (k=i; k<n; k++) /\* FOR K := I UNTIL N DO *\/ /\* wrong *\/ */
3360: for (k=i; k<=n; k++) /* FOR K := I UNTIL N DO */
3361: /* f += ab[k][i] * ab[k][j]; */
3362: f += ab[k][i] * ab[k][j];
3363: f /= h;
3364: for (k=i; k<=n; k++) /* FOR K := I UNTIL N DO */
3365: /* for (k=i; k<n; k++)/\* FOR K := I UNTIL N DO *\/ /\* wrong *\/ */
3366: ab[k][j] += f * ab[k][i];
3367: /* ab[k][j] += f * ab[k][i]; */
3368: #ifdef DEBUGPRAX
3369: printf("Holder J=%d F=%.7g",j,f);
3370: #endif
3371: }
3372: } /* end s */
3373: /* q[i] = g; s = 0.0; */
3374: q[i] = g; s = 0.0;
3375: #ifdef DEBUGPRAX
3376: printf(" I Q=%d %.7g",i,q[i]);
3377: #endif
3378:
3379: /* if (i < n) */
3380: /* if (i <= n) /\* I is always lower or equal to n wasn't in golub reinsch*\/ */
3381: /* for (j=l; j<n; j++) */
3382: for (j=l; j<=n; j++)
3383: s += ab[i][j] * ab[i][j];
3384: /* s += ab[i][j] * ab[i][j]; */
3385: if (s < tol) {
3386: g = 0.0;
3387: }
3388: else {
3389: if(i<n)
3390: /* f = ab[i][i+1]; */ /* Brent golub overflow */
3391: f = ab[i][i+1];
3392: if (f < 0.0)
3393: g = sqrt(s);
3394: else
3395: g = - sqrt(s);
3396: h = f*g - s;
3397: /* h = f*g - s; ab[i][i+1] = f - g; */ /* Overflow for i=n Error in Golub too but not Burkardt*/
3398: /* for (j=l; j<n; j++) */
3399: /* e[j] = ab[i][j]/h; */
3400: if(i<n){
3401: ab[i][i+1] = f - g;
3402: for (j=l; j<=n; j++)
3403: e[j] = ab[i][j]/h;
3404: /* for (j=l; j<n; j++) { */
3405: for (j=l; j<=n; j++) {
3406: s = 0.0;
3407: /* for (k=l; k<n; k++) s += ab[j][k]*ab[i][k]; */
3408: for (k=l; k<=n; k++) s += ab[j][k]*ab[i][k];
3409: /* for (k=l; k<n; k++) ab[j][k] += s * e[k]; */
3410: for (k=l; k<=n; k++) ab[j][k] += s * e[k];
3411: } /* END J */
3412: } /* END i <n */
3413: } /* end s */
3414: /* y = fabs(q[i]) + fabs(e[i]); */
3415: y = fabs(q[i]) + fabs(e[i]);
3416: if (y > x) x = y;
3417: #ifdef DEBUGPRAX
3418: printf(" I Y=%d %.7g",i,y);
3419: #endif
3420: #ifdef DEBUGPRAX
3421: printf(" i=%d e(i) %.7g",i,e[i]);
3422: #endif
3423: } /* end i */
3424: /*
3425: Accumulation of right hand transformations */
3426: /* for (i=n-1; i >= 0; i--) { */ /* FOR I := N STEP -1 UNTIL 1 DO */
3427: /* We should avoid the overflow in Golub */
3428: /* ab[n-1][n-1] = 1.0; */
3429: /* g = e[n-1]; */
3430: ab[n][n] = 1.0;
3431: g = e[n];
3432: l = n;
3433:
3434: /* for (i=n; i >= 1; i--) { */
3435: for (i=n-1; i >= 1; i--) { /* n-1 loops, different from brent and golub*/
3436: if (g != 0.0) {
3437: /* h = ab[i-1][i]*g; */
3438: h = ab[i][i+1]*g;
3439: for (j=l; j<=n; j++) ab[j][i] = ab[i][j] / h;
3440: for (j=l; j<=n; j++) {
3441: /* h = ab[i][i+1]*g; */
3442: /* for (j=l; j<n; j++) ab[j][i] = ab[i][j] / h; */
3443: /* for (j=l; j<n; j++) { */
3444: s = 0.0;
3445: /* for (k=l; k<n; k++) s += ab[i][k] * ab[k][j]; */
3446: /* for (k=l; k<n; k++) ab[k][j] += s * ab[k][i]; */
3447: for (k=l; k<=n; k++) s += ab[i][k] * ab[k][j];
3448: for (k=l; k<=n; k++) ab[k][j] += s * ab[k][i];
3449: }/* END J */
3450: }/* END G */
3451: /* for (j=l; j<n; j++) */
3452: /* ab[i][j] = ab[j][i] = 0.0; */
3453: /* ab[i][i] = 1.0; g = e[i]; l = i; */
3454: for (j=l; j<=n; j++)
3455: ab[i][j] = ab[j][i] = 0.0;
3456: ab[i][i] = 1.0; g = e[i]; l = i;
3457: }/* END I */
3458: #ifdef DEBUGPRAX
3459: matprint (" HOUSE accumulation:",ab,n, n );
3460: #endif
3461:
3462: /* diagonalization to bidiagonal form */
3463: eps *= x;
3464: /* for (k=n-1; k>= 0; k--) { */
3465: for (k=n; k>= 1; k--) {
3466: kt = 0;
3467: TestFsplitting:
3468: #ifdef DEBUGPRAX
3469: printf(" TestFsplitting: k=%d kt=%d\n",k,kt);
3470: /* for(i=1;i<=n;i++)printf(" e(%d)=%.14f",i,e[i]);printf("\n"); */
3471: #endif
3472: kt = kt+1;
3473: /* TestFsplitting: */
3474: /* if (++kt > 30) { */
3475: if (kt > 30) {
3476: e[k] = 0.0;
3477: fprintf(stderr, "\n+++ MINFIT - Fatal error\n");
3478: fprintf ( stderr, " The QR algorithm failed to converge.\n" );
3479: }
3480: /* for (l2=k; l2>=0; l2--) { */
3481: for (l2=k; l2>=1; l2--) {
3482: l = l2;
3483: #ifdef DEBUGPRAX
3484: printf(" l e(l)< eps %d %.7g %.7g ",l,e[l], eps);
3485: #endif
3486: /* if (fabs(e[l]) <= eps) */
3487: if (fabs(e[l]) <= eps)
3488: goto TestFconvergence;
3489: /* if (fabs(q[l-1]) <= eps)*/ /* missing if ( 1 < l ){ *//* printf(" q(l-1)< eps %d %.7g %.7g ",l-1,q[l-2], eps); */
3490: if (fabs(q[l-1]) <= eps)
3491: break; /* goto Cancellation; */
3492: }
3493: Cancellation:
3494: #ifdef DEBUGPRAX
3495: printf(" Cancellation:\n");
3496: #endif
3497: c = 0.0; s = 1.0;
3498: for (i=l; i<=k; i++) {
3499: f = s * e[i]; e[i] *= c;
3500: /* f = s * e[i]; e[i] *= c; */
3501: if (fabs(f) <= eps)
3502: goto TestFconvergence;
3503: /* g = q[i]; */
3504: g = q[i];
3505: if (fabs(f) < fabs(g)) {
3506: double fg = f/g;
3507: h = fabs(g)*sqrt(1.0+fg*fg);
3508: }
3509: else {
3510: double gf = g/f;
3511: h = (f!=0.0 ? fabs(f)*sqrt(1.0+gf*gf) : 0.0);
3512: }
3513: /* COMMENT: THE ABOVE REPLACES Q(I):=H:=LONGSQRT(G*G+F*F) */
3514: /* WHICH MAY GIVE INCORRECT RESULTS IF THE */
3515: /* SQUARES UNDERFLOW OR IF F = G = 0; */
3516:
3517: /* q[i] = h; */
3518: q[i] = h;
3519: if (h == 0.0) { h = 1.0; g = 1.0; }
3520: c = g/h; s = -f/h;
3521: }
3522: TestFconvergence:
3523: #ifdef DEBUGPRAX
3524: printf(" TestFconvergence: l=%d k=%d\n",l,k);
3525: #endif
3526: /* z = q[k]; */
3527: z = q[k];
3528: if (l == k)
3529: goto Convergence;
3530: /* shift from bottom 2x2 minor */
3531: /* x = q[l]; y = q[k-l]; g = e[k-1]; h = e[k]; */ /* Error */
3532: x = q[l]; y = q[k-1]; g = e[k-1]; h = e[k];
3533: f = ((y-z)*(y+z) + (g-h)*(g+h)) / (2.0*h*y);
3534: g = sqrt(f*f+1.0);
3535: if (f <= 0.0)
3536: f = ((x-z)*(x+z) + h*(y/(f-g)-h))/x;
3537: else
3538: f = ((x-z)*(x+z) + h*(y/(f+g)-h))/x;
3539: /* next qr transformation */
3540: s = c = 1.0;
3541: for (i=l+1; i<=k; i++) {
3542: #ifdef DEBUGPRAXQR
3543: 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]);
3544: #endif
3545: /* g = e[i]; y = q[i]; h = s*g; g *= c; */
3546: g = e[i]; y = q[i]; h = s*g; g *= c;
3547: if (fabs(f) < fabs(h)) {
3548: double fh = f/h;
3549: z = fabs(h) * sqrt(1.0 + fh*fh);
3550: }
3551: else {
3552: double hf = h/f;
3553: z = (f!=0.0 ? fabs(f)*sqrt(1.0+hf*hf) : 0.0);
3554: }
3555: /* e[i-1] = z; */
3556: e[i-1] = z;
3557: #ifdef DEBUGPRAXQR
3558: 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]);
3559: #endif
3560: if (z == 0.0)
3561: f = z = 1.0;
3562: c = f/z; s = h/z;
3563: f = x*c + g*s; g = - x*s + g*c; h = y*s;
3564: y *= c;
3565: /* for (j=0; j<n; j++) { */
3566: /* x = ab[j][i-1]; z = ab[j][i]; */
3567: /* ab[j][i-1] = x*c + z*s; */
3568: /* ab[j][i] = - x*s + z*c; */
3569: /* } */
3570: for (j=1; j<=n; j++) {
3571: x = ab[j][i-1]; z = ab[j][i];
3572: ab[j][i-1] = x*c + z*s;
3573: ab[j][i] = - x*s + z*c;
3574: }
3575: if (fabs(f) < fabs(h)) {
3576: double fh = f/h;
3577: z = fabs(h) * sqrt(1.0 + fh*fh);
3578: }
3579: else {
3580: double hf = h/f;
3581: z = (f!=0.0 ? fabs(f)*sqrt(1.0+hf*hf) : 0.0);
3582: }
3583: #ifdef DEBUGPRAXQR
3584: printf(" qr transformation z f h=%.7g %.7g %.7g i=%d k=%d\n",z,f,h, i, k);
3585: #endif
3586: q[i-1] = z;
3587: if (z == 0.0)
3588: z = f = 1.0;
3589: c = f/z; s = h/z;
3590: f = c*g + s*y; /* f can be very small */
3591: x = - s*g + c*y;
3592: }
3593: /* e[l] = 0.0; e[k] = f; q[k] = x; */
3594: e[l] = 0.0; e[k] = f; q[k] = x;
3595: #ifdef DEBUGPRAXQR
3596: 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);
3597: #endif
3598: goto TestFsplitting;
3599: Convergence:
3600: #ifdef DEBUGPRAX
3601: printf(" Convergence:\n");
3602: #endif
3603: if (z < 0.0) {
3604: /* q[k] = - z; */
3605: /* for (j=0; j<n; j++) ab[j][k] = - ab[j][k]; */
3606: q[k] = - z;
3607: for (j=1; j<=n; j++) ab[j][k] = - ab[j][k];
3608: }/* END Z */
3609: }/* END K */
3610: } /* END MINFIT */
3611:
3612:
3613: double praxis(double tol, double macheps, double h0, int _n, int _prin, double *_x, double (*_fun)(double *_x))
3614: /* double praxis(double tol, double macheps, double h0, int _n, int _prin, double *_x, double (*_fun)(double *_x, int _n)) */
3615: /* double praxis(double (*_fun)(), double _x[], int _n) */
3616: /* double (*_fun)(); */
3617: /* double _x[N]; */
3618: /* double (*_fun)(); */
3619: /* double _x[N]; */
3620: {
3621: /* init global extern variables and parameters */
3622: /* double *d, *y, *z, */
3623: /* *q0, *q1, **v; */
3624: /* double *tflin; /\* used in flin: return (*fun)(tflin, n); *\/ */
3625: /* double *e; /\* used in minfit, don't konw how to free memory and thus made global *\/ */
3626:
3627:
3628: int seed; /* added */
3629: int biter=0;
3630: double r;
3631: double randbrent( int (*));
3632: double s, sf;
3633:
3634: h = h0; /* step; */
3635: t = tol;
3636: scbd = 1.0;
3637: illc = 0;
3638: ktm = 1;
3639:
3640: macheps = DBL_EPSILON;
3641: /* prin=4; */
3642: #ifdef DEBUGPRAX
3643: printf("Praxis macheps=%14g h=%14g step=%14g tol=%14g\n",macheps,h, h0,tol);
3644: #endif
3645: n = _n;
3646: x = _x;
3647: prin = _prin;
3648: fun = _fun;
3649: d=vector(1, n);
3650: y=vector(1, n);
3651: z=vector(1, n);
3652: q0=vector(1, n);
3653: q1=vector(1, n);
3654: e=vector(1, n);
3655: tflin=vector(1, n);
3656: v=matrix(1, n, 1, n);
3657: for(i=1;i<=n;i++){d[i]=y[i]=z[i]=q0[0]=e[i]=tflin[i]=0.;}
3658: small_windows = (macheps) * (macheps); vsmall = small_windows*small_windows;
3659: large = 1.0/small_windows; vlarge = 1.0/vsmall;
3660: m2 = sqrt(macheps); m4 = sqrt(m2);
3661: seed = 123456789; /* added */
3662: ldfac = (illc ? 0.1 : 0.01);
3663: for(i=1;i<=n;i++) z[i]=0.; /* Was missing in Gegenfurtner as well as Brent's algol or fortran */
3664: nl = kt = 0; nf = 1;
3665: #ifdef NR_SHIFT
3666: fx = (*fun)((x-1), n);
3667: #else
3668: fx = (*fun)(x);
3669: #endif
3670: qf1 = fx;
3671: t2 = small_windows + fabs(t); t = t2; dmin = small_windows;
3672: #ifdef DEBUGPRAX
3673: printf("praxis2 macheps=%14g h=%14g step=%14g small=%14g t=%14g\n",macheps,h, h0,small_windows, t);
3674: #endif
3675: if (h < 100.0*t) h = 100.0*t;
3676: #ifdef DEBUGPRAX
3677: printf("praxis3 macheps=%14g h=%14g step=%14g small=%14g t=%14g\n",macheps,h, h0,small_windows, t);
3678: #endif
3679: ldt = h;
3680: /* for (i=0; i<n; i++) for (j=0; j<n; j++) */
3681: for (i=1; i<=n; i++) for (j=1; j<=n; j++)
3682: v[i][j] = (i == j ? 1.0 : 0.0);
3683: d[1] = 0.0; qd0 = 0.0;
3684: /* for (i=0; i<n; i++) q1[i] = x[i]; */
3685: for (i=1; i<=n; i++) q1[i] = x[i];
3686: if (prin > 1) {
3687: printf("\n------------- enter function praxis -----------\n");
3688: printf("... current parameter settings ...\n");
3689: printf("... scaling ... %20.10e\n", scbd);
3690: printf("... tol ... %20.10e\n", t);
3691: printf("... maxstep ... %20.10e\n", h);
3692: printf("... illc ... %20u\n", illc);
3693: printf("... ktm ... %20u\n", ktm);
3694: printf("... maxfun ... %20u\n", maxfun);
3695: }
3696: if (prin) print2();
3697:
3698: mloop:
3699: biter++; /* Added to count the loops */
3700: /* sf = d[0]; */
3701: /* s = d[0] = 0.0; */
3702: printf("\n Big iteration %d \n",biter);
3703: fprintf(ficlog,"\n Big iteration %d \n",biter);
3704: sf = d[1];
3705: s = d[1] = 0.0;
3706:
3707: /* minimize along first direction V(*,1) */
3708: #ifdef DEBUGPRAX
3709: printf(" Minimize along the first direction V(*,1). illc=%d\n",illc);
3710: /* fprintf(ficlog," Minimize along the first direction V(*,1).\n"); */
3711: #endif
3712: #ifdef DEBUGPRAX2
3713: printf("praxis4 macheps=%14g h=%14g step=%14g small=%14g t=%14g\n",macheps,h, h0,small_windows, t);
3714: #endif
3715: /* min(0, 2, &d[0], &s, fx, 0); /\* mac heps not global *\/ */
1.362 ! brouard 3716: 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 3717: #ifdef DEBUGPRAX
3718: printf("praxis5 macheps=%14g h=%14g looks at sign of s=%14g fx=%14g\n",macheps,h, s,fx);
3719: #endif
3720: if (s <= 0.0)
3721: /* for (i=0; i < n; i++) */
3722: for (i=1; i <= n; i++)
3723: v[i][1] = -v[i][1];
3724: /* if ((sf <= (0.9 * d[0])) || ((0.9 * sf) >= d[0])) */
3725: if ((sf <= (0.9 * d[1])) || ((0.9 * sf) >= d[1]))
3726: /* for (i=1; i<n; i++) */
3727: for (i=2; i<=n; i++)
3728: d[i] = 0.0;
3729: /* for (k=1; k<n; k++) { */
3730: for (k=2; k<=n; k++) {
3731: /*
3732: The inner loop starts here.
3733: */
3734: #ifdef DEBUGPRAX
3735: printf(" The inner loop here from k=%d to n=%d.\n",k,n);
3736: /* fprintf(ficlog," The inner loop here from k=%d to n=%d.\n",k,n); */
3737: #endif
3738: /* for (i=0; i<n; i++) */
3739: for (i=1; i<=n; i++)
3740: y[i] = x[i];
3741: sf = fx;
3742: #ifdef DEBUGPRAX
3743: printf(" illc=%d and kt=%d and ktm=%d\n", illc, kt, ktm);
3744: #endif
3745: illc = illc || (kt > 0);
3746: next:
3747: kl = k;
3748: df = 0.0;
3749: if (illc) { /* random step to get off resolution valley */
3750: #ifdef DEBUGPRAX
3751: printf(" A random step follows, to avoid resolution valleys.\n");
3752: matprint(" before rand, vectors:",v,n,n);
3753: #endif
3754: for (i=1; i<=n; i++) {
3755: #ifdef NOBRENTRAND
3756: r = drandom();
3757: #else
3758: seed=i;
3759: /* seed=i+1; */
3760: #ifdef DEBUGRAND
3761: printf(" Random seed=%d, brent i=%d",seed,i); /* YYYY i=5 j=1 vji= -0.0001170073 */
3762: #endif
3763: r = randbrent ( &seed );
3764: #endif
3765: #ifdef DEBUGRAND
3766: printf(" Random r=%.7g \n",r);
3767: #endif
3768: z[i] = (0.1 * ldt + t2 * pow(10.0,(double)kt)) * (r - 0.5);
3769: /* z[i] = (0.1 * ldt + t2 * pow(10.0,(double)kt)) * (drandom() - 0.5); */
3770:
3771: s = z[i];
3772: for (j=1; j <= n; j++)
3773: x[j] += s * v[j][i];
3774: }
3775: #ifdef DEBUGRAND
3776: matprint(" after rand, vectors:",v,n,n);
3777: #endif
3778: #ifdef NR_SHIFT
3779: fx = (*fun)((x-1), n);
3780: #else
3781: fx = (*fun)(x, n);
3782: #endif
3783: /* fx = (*func) ( (x-1) ); *//* This for func which is computed from x[1] and not from x[0] xm1=(x-1)*/
3784: nf++;
3785: }
3786: /* minimize along non-conjugate directions */
3787: #ifdef DEBUGPRAX
3788: printf(" Minimize along the 'non-conjugate' directions (dots printed) V(*,%d),...,V(*,%d).\n",k,n);
3789: /* fprintf(ficlog," Minimize along the 'non-conjugate' directions (dots printed) V(*,%d),...,V(*,%d).\n",k,n); */
3790: #endif
3791: /* for (k2=k; k2<n; k2++) { /\* Be careful here k2 <=n ? *\/ */
3792: for (k2=k; k2<=n; k2++) { /* Be careful here k2 <=n ? */
3793: sl = fx;
3794: s = 0.0;
3795: #ifdef DEBUGPRAX
3796: printf(" Minimize along the 'NON-CONJUGATE' true direction k2=%14d fx=%14.7f\n",k2, fx);
3797: matprint(" before min vectors:",v,n,n);
3798: #endif
3799: /* min(k2, 2, &d[k2], &s, fx, 0); */
3800: /* jsearch=k2-1; */
3801: /* min(jsearch, 2, &d[jsearch], &s, fx, 0); */
3802: minny(k2, 2, &d[k2], &s, fx, 0);
3803: #ifdef DEBUGPRAX
3804: 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);
3805: #endif
3806: if (illc) {
3807: /* double szk = s + z[k2]; */
3808: /* s = d[k2] * szk*szk; */
3809: double szk = s + z[k2];
3810: s = d[k2] * szk*szk;
3811: }
3812: else
3813: s = sl - fx;
3814: /* if (df < s) { */
3815: if (df <= s) {
3816: df = s;
3817: kl = k2;
3818: #ifdef DEBUGPRAX
3819: printf(" df=%.7g and choose kl=%d \n",df,kl); /* UUUU */
3820: #endif
3821: }
3822: } /* end loop k2 */
3823: /*
3824: If there was not much improvement on the first try, set
3825: ILLC = true and start the inner loop again.
3826: */
3827: #ifdef DEBUGPRAX
3828: printf(" If there was not much improvement on the first try, set ILLC = true and start the inner loop again. illc=%d\n",illc);
3829: /* fprintf(ficlog," If there was not much improvement on the first try, set ILLC = true and start the inner loop again.\n"); */
3830: #endif
3831: if (!illc && (df < fabs(100.0 * (macheps) * fx))) {
3832: #ifdef DEBUGPRAX
3833: 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);
3834: #endif
3835: illc = 1;
3836: goto next;
3837: }
3838: #ifdef DEBUGPRAX
3839: 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);
3840: #endif
3841:
3842: /* if ((k == 1) && (prin > 1)){ /\* be careful k=2 *\/ */
3843: if ((k == 2) && (prin > 1)){ /* be careful k=2 */
3844: #ifdef DEBUGPRAX
3845: printf(" NEW D The second difference array d:\n" );
3846: /* fprintf(ficlog, " NEW D The second difference array d:\n" ); */
3847: #endif
3848: vecprint(" NEW D The second difference array d:",d,n);
3849: }
3850: /* minimize along conjugate directions */
3851: /*
3852: Minimize along the "conjugate" directions V(*,1),...,V(*,K-1).
3853: */
3854: #ifdef DEBUGPRAX
3855: printf("Minimize along the 'conjugate' directions V(*,1),...,V(*,K-1=%d).\n",k-1);
3856: /* fprintf(ficlog,"Minimize along the 'conjugate' directions V(*,1),...,V(*,K-1=%d).\n",k-1); */
3857: #endif
3858: /* for (k2=0; k2<=k-1; k2++) { */
3859: for (k2=1; k2<=k-1; k2++) {
3860: s = 0.0;
3861: /* min(k2-1, 2, &d[k2-1], &s, fx, 0); */
3862: minny(k2, 2, &d[k2], &s, fx, 0);
3863: }
3864: f1 = fx;
3865: fx = sf;
3866: lds = 0.0;
3867: /* for (i=0; i<n; i++) { */
3868: for (i=1; i<=n; i++) {
3869: sl = x[i];
3870: x[i] = y[i];
3871: y[i] = sl - y[i];
3872: sl = y[i];
3873: lds = lds + sl*sl;
3874: }
3875: lds = sqrt(lds);
3876: #ifdef DEBUGPRAX
3877: printf("Minimization done 'conjugate', shifted all points, computed lds=%.8f\n",lds);
3878: #endif
3879: /*
3880: Discard direction V(*,kl).
3881:
3882: If no random step was taken, V(*,KL) is the "non-conjugate"
3883: direction along which the greatest improvement was made.
3884: */
3885: if (lds > small_windows) {
3886: #ifdef DEBUGPRAX
3887: 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);
3888: matprint(" before shift new conjugate vectors:",v,n,n);
3889: #endif
3890: for (i=kl-1; i>=k; i--) {
3891: /* for (j=0; j < n; j++) */
3892: for (j=1; j <= n; j++)
3893: /* v[j][i+1] = v[j][i]; */ /* This is v[j][i+1]=v[j][i] i=kl-1 to k */
3894: v[j][i+1] = v[j][i]; /* This is v[j][i+1]=v[j][i] i=kl-1 to k */
3895: /* v[j][i+1] = v[j][i]; */
3896: /* d[i+1] = d[i];*/ /* last is d[k+1]= d[k] */
3897: d[i+1] = d[i]; /* last is d[k]= d[k-1] */
3898: }
3899: #ifdef DEBUGPRAX
3900: matprint(" after shift new conjugate vectors:",v,n,n);
3901: #endif /* d[k] = 0.0; */
3902: d[k] = 0.0;
3903: for (i=1; i <= n; i++)
3904: v[i][k] = y[i] / lds;
3905: /* v[i][k] = y[i] / lds; */
3906: #ifdef DEBUGPRAX
3907: 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);
3908: /* fprintf(ficlog,"Minimize along the new 'conjugate' direction V(*,k=%d), which is the normalized vector: (new x) - (old x).\n",k); */
3909: matprint(" before min new conjugate vectors:",v,n,n);
3910: #endif
3911: /* min(k-1, 4, &d[k-1], &lds, f1, 1); */
3912: minny(k, 4, &d[k], &lds, f1, 1);
3913: #ifdef DEBUGPRAX
3914: printf(" after min d(k)=%d %.7g lds=%14f\n",k,d[k],lds);
3915: matprint(" after min vectors:",v,n,n);
3916: #endif
3917: if (lds <= 0.0) {
3918: lds = -lds;
3919: #ifdef DEBUGPRAX
3920: printf(" lds changed sign lds=%.14f k=%d\n",lds,k);
3921: #endif
3922: /* for (i=0; i<n; i++) */
3923: /* v[i][k] = -v[i][k]; */
3924: for (i=1; i<=n; i++)
3925: v[i][k] = -v[i][k];
3926: }
3927: }
3928: ldt = ldfac * ldt;
3929: if (ldt < lds)
3930: ldt = lds;
3931: if (prin > 0){
3932: #ifdef DEBUGPRAX
3933: printf(" k=%d",k);
3934: /* fprintf(ficlog," k=%d",k); */
3935: #endif
3936: print2();/* n, x, prin, fx, nf, nl ); */
3937: }
3938: t2 = 0.0;
3939: /* for (i=0; i<n; i++) */
3940: for (i=1; i<=n; i++)
3941: t2 += x[i]*x[i];
3942: t2 = m2 * sqrt(t2) + t;
3943: /*
3944: See whether the length of the step taken since starting the
3945: inner loop exceeds half the tolerance.
3946: */
3947: #ifdef DEBUGPRAX
3948: printf("See if step length exceeds half the tolerance.\n"); /* ZZZZZ */
3949: /* fprintf(ficlog,"See if step length exceeds half the tolerance.\n"); */
3950: #endif
3951: if (ldt > (0.5 * t2))
3952: kt = 0;
3953: else
3954: kt++;
3955: #ifdef DEBUGPRAX
3956: printf("if kt=%d >? ktm=%d gotoL2 loop\n",kt,ktm);
3957: #endif
3958: if (kt > ktm){
3959: if ( 0 < prin ){
3960: /* printf("\nr8vec_print\n X:\n"); */
3961: /* fprintf(ficlog,"\nr8vec_print\n X:\n"); */
3962: vecprint ("END X:", x, n );
3963: }
3964: goto fret;
3965: }
3966: #ifdef DEBUGPRAX
3967: matprint(" end of L2 loop vectors:",v,n,n);
3968: #endif
3969:
3970: }
3971: /* printf("The inner loop ends here.\n"); */
3972: /* fprintf(ficlog,"The inner loop ends here.\n"); */
3973: /*
3974: The inner loop ends here.
3975:
3976: Try quadratic extrapolation in case we are in a curved valley.
3977: */
3978: #ifdef DEBUGPRAX
3979: printf("Try QUAD ratic extrapolation in case we are in a curved valley.\n");
3980: #endif
3981: /* try quadratic extrapolation in case */
3982: /* we are stuck in a curved valley */
3983: quad();
3984: dn = 0.0;
3985: /* for (i=0; i<n; i++) { */
3986: for (i=1; i<=n; i++) {
3987: d[i] = 1.0 / sqrt(d[i]);
3988: if (dn < d[i])
3989: dn = d[i];
3990: }
3991: if (prin > 2)
3992: matprint(" NEW DIRECTIONS vectors:",v,n,n);
3993: /* for (j=0; j<n; j++) { */
3994: for (j=1; j<=n; j++) {
3995: s = d[j] / dn;
3996: /* for (i=0; i < n; i++) */
3997: for (i=1; i <= n; i++)
3998: v[i][j] *= s;
3999: }
4000:
4001: if (scbd > 1.0) { /* scale axis to reduce condition number */
4002: #ifdef DEBUGPRAX
4003: printf("Scale the axes to try to reduce the condition number.\n");
4004: #endif
4005: /* fprintf(ficlog,"Scale the axes to try to reduce the condition number.\n"); */
4006: s = vlarge;
4007: /* for (i=0; i<n; i++) { */
4008: for (i=1; i<=n; i++) {
4009: sl = 0.0;
4010: /* for (j=0; j < n; j++) */
4011: for (j=1; j <= n; j++)
4012: sl += v[i][j]*v[i][j];
4013: z[i] = sqrt(sl);
4014: if (z[i] < m4)
4015: z[i] = m4;
4016: if (s > z[i])
4017: s = z[i];
4018: }
4019: /* for (i=0; i<n; i++) { */
4020: for (i=1; i<=n; i++) {
4021: sl = s / z[i];
4022: z[i] = 1.0 / sl;
4023: if (z[i] > scbd) {
4024: sl = 1.0 / scbd;
4025: z[i] = scbd;
4026: }
4027: }
4028: }
4029: for (i=1; i<=n; i++)
4030: /* for (j=0; j<=i-1; j++) { */
4031: /* for (j=1; j<=i; j++) { */
4032: for (j=1; j<=i-1; j++) {
4033: s = v[i][j];
4034: v[i][j] = v[j][i];
4035: v[j][i] = s;
4036: }
4037: #ifdef DEBUGPRAX
4038: printf(" Calculate a new set of orthogonal directions before repeating the main loop.\n Transpose V for MINFIT:...\n");
4039: #endif
4040: /*
4041: MINFIT finds the singular value decomposition of V.
4042:
4043: This gives the principal values and principal directions of the
4044: approximating quadratic form without squaring the condition number.
4045: */
4046: #ifdef DEBUGPRAX
4047: 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");
4048: #endif
4049:
4050: minfit(n, macheps, vsmall, v, d);
4051: /* for(i=0; i<n;i++)printf(" %14.7g",d[i]); */
4052: /* v is overwritten with R. */
4053: /*
4054: Unscale the axes.
4055: */
4056: if (scbd > 1.0) {
4057: #ifdef DEBUGPRAX
4058: printf(" Unscale the axes.\n");
4059: #endif
4060: /* for (i=0; i<n; i++) { */
4061: for (i=1; i<=n; i++) {
4062: s = z[i];
4063: /* for (j=0; j<n; j++) */
4064: for (j=1; j<=n; j++)
4065: v[i][j] *= s;
4066: }
4067: /* for (i=0; i<n; i++) { */
4068: for (i=1; i<=n; i++) {
4069: s = 0.0;
4070: /* for (j=0; j<n; j++) */
4071: for (j=1; j<=n; j++)
4072: s += v[j][i]*v[j][i];
4073: s = sqrt(s);
4074: d[i] *= s;
4075: s = 1.0 / s;
4076: /* for (j=0; j<n; j++) */
4077: for (j=1; j<=n; j++)
4078: v[j][i] *= s;
4079: }
4080: }
4081: /* for (i=0; i<n; i++) { */
4082: double dni; /* added for compatibility with buckhardt but not brent */
4083: for (i=1; i<=n; i++) {
4084: dni=dn*d[i]; /* added for compatibility with buckhardt but not brent */
4085: if ((dn * d[i]) > large)
4086: d[i] = vsmall;
4087: else if ((dn * d[i]) < small_windows)
4088: d[i] = vlarge;
4089: else
4090: d[i] = 1.0 / dni / dni; /* added for compatibility with buckhardt but not brent */
4091: /* d[i] = pow(dn * d[i],-2.0); */
4092: }
4093: #ifdef DEBUGPRAX
4094: vecprint ("\n Before sort Eigenvalues of a:",d,n );
4095: #endif
4096:
4097: sort(); /* the new eigenvalues and eigenvectors */
4098: #ifdef DEBUGPRAX
4099: vecprint( " After sort the eigenvalues ....\n", d, n);
4100: matprint( " After sort the eigenvectors....\n", v, n,n);
4101: #endif
4102: #ifdef DEBUGPRAX
4103: printf(" Determine the smallest eigenvalue.\n");
4104: #endif
4105: /* dmin = d[n-1]; */
4106: dmin = d[n];
4107: if (dmin < small_windows)
4108: dmin = small_windows;
4109: /*
4110: The ratio of the smallest to largest eigenvalue determines whether
4111: the system is ill conditioned.
4112: */
4113:
4114: /* illc = (m2 * d[0]) > dmin; */
4115: illc = (m2 * d[1]) > dmin;
4116: #ifdef DEBUGPRAX
4117: 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]);
4118: #endif
4119:
4120: if ((prin > 2) && (scbd > 1.0))
4121: vecprint("\n The scale factors:",z,n);
4122: if (prin > 2)
4123: vecprint(" Principal values (EIGEN VALUES OF A) of the quadratic form:",d,n);
4124: if (prin > 2)
4125: matprint(" The principal axes (EIGEN VECTORS OF A:",v,n, n);
4126:
4127: if ((maxfun > 0) && (nf > maxfun)) {
4128: if (prin)
4129: printf("\n... maximum number of function calls reached ...\n");
4130: goto fret;
4131: }
4132: #ifdef DEBUGPRAX
4133: printf("Goto main loop\n");
4134: #endif
4135: goto mloop; /* back to main loop */
4136:
4137: fret:
4138: if (prin > 0) {
4139: vecprint("\n X:", x, n);
4140: /* printf("\n... ChiSq reduced to %20.10e ...\n", fx); */
4141: /* printf("... after %20u function calls.\n", nf); */
4142: }
4143: free_vector(d, 1, n);
4144: free_vector(y, 1, n);
4145: free_vector(z, 1, n);
4146: free_vector(q0, 1, n);
4147: free_vector(q1, 1, n);
4148: free_matrix(v, 1, n, 1, n);
4149: /* double *d, *y, *z, */
4150: /* *q0, *q1, **v; */
4151: free_vector(tflin, 1, n);
4152: /* double *tflin; /\* used in flin: return (*fun)(tflin, n); *\/ */
4153: free_vector(e, 1, n);
4154: /* double *e; /\* used in minfit, don't konw how to free memory and thus made global *\/ */
4155:
4156: return(fx);
4157: }
4158:
4159: /* end praxis gegen */
1.126 brouard 4160:
4161: /*************** powell ************************/
1.162 brouard 4162: /*
1.317 brouard 4163: Minimization of a function func of n variables. Input consists in an initial starting point
4164: p[1..n] ; an initial matrix xi[1..n][1..n] whose columns contain the initial set of di-
4165: rections (usually the n unit vectors); and ftol, the fractional tolerance in the function value
4166: such that failure to decrease by more than this amount in one iteration signals doneness. On
1.162 brouard 4167: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
4168: function value at p , and iter is the number of iterations taken. The routine linmin is used.
4169: */
1.224 brouard 4170: #ifdef LINMINORIGINAL
4171: #else
4172: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 4173: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 4174: #endif
1.126 brouard 4175: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
4176: double (*func)(double []))
4177: {
1.224 brouard 4178: #ifdef LINMINORIGINAL
4179: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 4180: double (*func)(double []));
1.224 brouard 4181: #else
1.241 brouard 4182: void linmin(double p[], double xi[], int n, double *fret,
4183: double (*func)(double []),int *flat);
1.224 brouard 4184: #endif
1.239 brouard 4185: int i,ibig,j,jk,k;
1.126 brouard 4186: double del,t,*pt,*ptt,*xit;
1.181 brouard 4187: double directest;
1.126 brouard 4188: double fp,fptt;
4189: double *xits;
4190: int niterf, itmp;
1.349 brouard 4191: int Bigter=0, nBigterf=1;
4192:
1.126 brouard 4193: pt=vector(1,n);
4194: ptt=vector(1,n);
4195: xit=vector(1,n);
4196: xits=vector(1,n);
4197: *fret=(*func)(p);
4198: for (j=1;j<=n;j++) pt[j]=p[j];
1.338 brouard 4199: rcurr_time = time(NULL);
4200: fp=(*fret); /* Initialisation */
1.126 brouard 4201: for (*iter=1;;++(*iter)) {
4202: ibig=0;
4203: del=0.0;
1.157 brouard 4204: rlast_time=rcurr_time;
1.349 brouard 4205: rlast_btime=rcurr_time;
1.157 brouard 4206: /* (void) gettimeofday(&curr_time,&tzp); */
4207: rcurr_time = time(NULL);
4208: curr_time = *localtime(&rcurr_time);
1.337 brouard 4209: /* 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); */
4210: /* 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 4211: /* Bigter=(*iter - *iter % ncovmodel)/ncovmodel +1; /\* Big iteration, i.e on ncovmodel cycle *\/ */
4212: Bigter=(*iter - (*iter-1) % n)/n +1; /* Big iteration, i.e on ncovmodel cycle */
1.349 brouard 4213: 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);
4214: 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);
4215: fprintf(ficrespow,"%d %d %.12f %d",*iter,Bigter, *fret,curr_time.tm_sec-start_time.tm_sec);
1.324 brouard 4216: fp=(*fret); /* From former iteration or initial value */
1.192 brouard 4217: for (i=1;i<=n;i++) {
1.126 brouard 4218: fprintf(ficrespow," %.12lf", p[i]);
4219: }
1.239 brouard 4220: fprintf(ficrespow,"\n");fflush(ficrespow);
4221: printf("\n#model= 1 + age ");
4222: fprintf(ficlog,"\n#model= 1 + age ");
4223: if(nagesqr==1){
1.241 brouard 4224: printf(" + age*age ");
4225: fprintf(ficlog," + age*age ");
1.239 brouard 4226: }
1.362 ! brouard 4227: for(j=1;j <=ncovmodel-2-nagesqr;j++){
1.239 brouard 4228: if(Typevar[j]==0) {
4229: printf(" + V%d ",Tvar[j]);
4230: fprintf(ficlog," + V%d ",Tvar[j]);
4231: }else if(Typevar[j]==1) {
4232: printf(" + V%d*age ",Tvar[j]);
4233: fprintf(ficlog," + V%d*age ",Tvar[j]);
4234: }else if(Typevar[j]==2) {
4235: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
4236: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 4237: }else if(Typevar[j]==3) {
4238: printf(" + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
4239: fprintf(ficlog," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.239 brouard 4240: }
4241: }
1.126 brouard 4242: printf("\n");
1.239 brouard 4243: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
4244: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 4245: fprintf(ficlog,"\n");
1.239 brouard 4246: for(i=1,jk=1; i <=nlstate; i++){
4247: for(k=1; k <=(nlstate+ndeath); k++){
4248: if (k != i) {
4249: printf("%d%d ",i,k);
4250: fprintf(ficlog,"%d%d ",i,k);
4251: for(j=1; j <=ncovmodel; j++){
4252: printf("%12.7f ",p[jk]);
4253: fprintf(ficlog,"%12.7f ",p[jk]);
4254: jk++;
4255: }
4256: printf("\n");
4257: fprintf(ficlog,"\n");
4258: }
4259: }
4260: }
1.241 brouard 4261: if(*iter <=3 && *iter >1){
1.157 brouard 4262: tml = *localtime(&rcurr_time);
4263: strcpy(strcurr,asctime(&tml));
4264: rforecast_time=rcurr_time;
1.126 brouard 4265: itmp = strlen(strcurr);
4266: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 4267: strcurr[itmp-1]='\0';
1.162 brouard 4268: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 4269: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.349 brouard 4270: for(nBigterf=1;nBigterf<=31;nBigterf+=10){
4271: niterf=nBigterf*ncovmodel;
4272: /* rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time); */
1.241 brouard 4273: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
4274: forecast_time = *localtime(&rforecast_time);
4275: strcpy(strfor,asctime(&forecast_time));
4276: itmp = strlen(strfor);
4277: if(strfor[itmp-1]=='\n')
4278: strfor[itmp-1]='\0';
1.349 brouard 4279: 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);
4280: 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 4281: }
4282: }
1.359 brouard 4283: for (i=1;i<=n;i++) { /* For each direction i, maximisation after loading directions */
4284: 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 */
4285:
4286: fptt=(*fret); /* Computes likelihood for parameters xit */
1.126 brouard 4287: #ifdef DEBUG
1.203 brouard 4288: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
4289: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 4290: #endif
1.203 brouard 4291: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 4292: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 4293: #ifdef LINMINORIGINAL
1.359 brouard 4294: linmin(p,xit,n,fret,func); /* New point i minimizing in direction xit, i has coordinates p[j].*/
1.357 brouard 4295: /* xit[j] gives the n coordinates of direction i as input.*/
4296: /* *fret gives the maximum value on direction xit */
1.224 brouard 4297: #else
4298: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.359 brouard 4299: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.224 brouard 4300: #endif
1.359 brouard 4301: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 4302: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.359 brouard 4303: /* because that direction will be replaced unless the gain del is small */
4304: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
4305: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
4306: /* with the new direction. */
4307: del=fabs(fptt-(*fret));
4308: ibig=i;
1.126 brouard 4309: }
4310: #ifdef DEBUG
4311: printf("%d %.12e",i,(*fret));
4312: fprintf(ficlog,"%d %.12e",i,(*fret));
4313: for (j=1;j<=n;j++) {
1.359 brouard 4314: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
4315: printf(" x(%d)=%.12e",j,xit[j]);
4316: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 4317: }
4318: for(j=1;j<=n;j++) {
1.359 brouard 4319: printf(" p(%d)=%.12e",j,p[j]);
4320: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 4321: }
4322: printf("\n");
4323: fprintf(ficlog,"\n");
4324: #endif
1.187 brouard 4325: } /* end loop on each direction i */
1.357 brouard 4326: /* Convergence test will use last linmin estimation (fret) and compare to former iteration (fp) */
1.188 brouard 4327: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.359 brouard 4328: /* New value of last point Pn is not computed, P(n-1) */
1.319 brouard 4329: for(j=1;j<=n;j++) {
4330: if(flatdir[j] >0){
4331: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
4332: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
1.302 brouard 4333: }
1.319 brouard 4334: /* printf("\n"); */
4335: /* fprintf(ficlog,"\n"); */
4336: }
1.243 brouard 4337: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
4338: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 4339: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
4340: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
4341: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
4342: /* decreased of more than 3.84 */
4343: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
4344: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
4345: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 4346:
1.188 brouard 4347: /* Starting the program with initial values given by a former maximization will simply change */
4348: /* the scales of the directions and the directions, because the are reset to canonical directions */
4349: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
4350: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 4351: #ifdef DEBUG
4352: int k[2],l;
4353: k[0]=1;
4354: k[1]=-1;
4355: printf("Max: %.12e",(*func)(p));
4356: fprintf(ficlog,"Max: %.12e",(*func)(p));
4357: for (j=1;j<=n;j++) {
4358: printf(" %.12e",p[j]);
4359: fprintf(ficlog," %.12e",p[j]);
4360: }
4361: printf("\n");
4362: fprintf(ficlog,"\n");
4363: for(l=0;l<=1;l++) {
4364: for (j=1;j<=n;j++) {
4365: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
4366: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
4367: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
4368: }
4369: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
4370: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
4371: }
4372: #endif
4373:
4374: free_vector(xit,1,n);
4375: free_vector(xits,1,n);
4376: free_vector(ptt,1,n);
4377: free_vector(pt,1,n);
4378: return;
1.192 brouard 4379: } /* enough precision */
1.240 brouard 4380: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.359 brouard 4381: 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 4382: ptt[j]=2.0*p[j]-pt[j];
1.359 brouard 4383: xit[j]=p[j]-pt[j]; /* Coordinate j of last direction xi_n=P_n-P_0 */
4384: #ifdef DEBUG
4385: printf("\n %d xit=%12.7g p=%12.7g pt=%12.7g ",j,xit[j],p[j],pt[j]);
4386: #endif
4387: pt[j]=p[j]; /* New P0 is Pn */
4388: }
4389: #ifdef DEBUG
4390: printf("\n");
4391: #endif
1.181 brouard 4392: fptt=(*func)(ptt); /* f_3 */
1.359 brouard 4393: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in directions until some iterations are done */
1.224 brouard 4394: if (*iter <=4) {
1.225 brouard 4395: #else
4396: #endif
1.224 brouard 4397: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 4398: #else
1.161 brouard 4399: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 4400: #endif
1.162 brouard 4401: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 4402: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 4403: /* Let f"(x2) be the 2nd derivative equal everywhere. */
4404: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
4405: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 4406: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
4407: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
4408: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 4409: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 4410: /* Even if f3 <f1, directest can be negative and t >0 */
4411: /* mu² and del² are equal when f3=f1 */
1.359 brouard 4412: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
4413: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
4414: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
4415: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 4416: #ifdef NRCORIGINAL
4417: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
4418: #else
4419: 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 4420: t= t- del*SQR(fp-fptt);
1.183 brouard 4421: #endif
1.202 brouard 4422: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 4423: #ifdef DEBUG
1.181 brouard 4424: 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);
4425: 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 4426: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
4427: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
4428: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
4429: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
4430: 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);
4431: 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);
4432: #endif
1.183 brouard 4433: #ifdef POWELLORIGINAL
4434: if (t < 0.0) { /* Then we use it for new direction */
1.361 brouard 4435: #else /* Not POWELLOriginal but Brouard's */
1.182 brouard 4436: if (directest*t < 0.0) { /* Contradiction between both tests */
1.359 brouard 4437: 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 4438: 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 4439: 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 4440: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
4441: }
1.361 brouard 4442: if (directest < 0.0) { /* Then we use (P0, Pn) for new direction Xi_n or Xi_iBig */
1.181 brouard 4443: #endif
1.191 brouard 4444: #ifdef DEBUGLINMIN
1.234 brouard 4445: printf("Before linmin in direction P%d-P0\n",n);
4446: for (j=1;j<=n;j++) {
4447: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
4448: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
4449: if(j % ncovmodel == 0){
4450: printf("\n");
4451: fprintf(ficlog,"\n");
4452: }
4453: }
1.224 brouard 4454: #endif
4455: #ifdef LINMINORIGINAL
1.234 brouard 4456: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 4457: #else
1.234 brouard 4458: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
4459: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 4460: #endif
1.234 brouard 4461:
1.191 brouard 4462: #ifdef DEBUGLINMIN
1.234 brouard 4463: for (j=1;j<=n;j++) {
4464: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
4465: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
4466: if(j % ncovmodel == 0){
4467: printf("\n");
4468: fprintf(ficlog,"\n");
4469: }
4470: }
1.224 brouard 4471: #endif
1.234 brouard 4472: for (j=1;j<=n;j++) {
4473: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
4474: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
4475: }
1.361 brouard 4476:
4477: /* #else */
4478: /* for (i=1;i<=n-1;i++) { */
4479: /* for (j=1;j<=n;j++) { */
4480: /* xi[j][i]=xi[j][i+1]; /\* Standard method of conjugate directions, not Powell who changes the nth direction by p0 pn . *\/ */
4481: /* } */
4482: /* } */
4483: /* for (j=1;j<=n;j++) { */
4484: /* xi[j][n]=xit[j]; /\* and this nth direction by the by the average p_0 p_n *\/ */
4485: /* } */
4486: /* /\* for (j=1;j<=n-1;j++) { *\/ */
4487: /* /\* xi[j][1]=xi[j][j+1]; /\\* Standard method of conjugate directions *\\/ *\/ */
4488: /* /\* xi[j][n]=xit[j]; /\\* and this nth direction by the by the average p_0 p_n *\\/ *\/ */
4489: /* /\* } *\/ */
4490: /* #endif */
1.224 brouard 4491: #ifdef LINMINORIGINAL
4492: #else
1.234 brouard 4493: for (j=1, flatd=0;j<=n;j++) {
4494: if(flatdir[j]>0)
4495: flatd++;
4496: }
4497: if(flatd >0){
1.255 brouard 4498: printf("%d flat directions: ",flatd);
4499: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 4500: for (j=1;j<=n;j++) {
4501: if(flatdir[j]>0){
4502: printf("%d ",j);
4503: fprintf(ficlog,"%d ",j);
4504: }
4505: }
4506: printf("\n");
4507: fprintf(ficlog,"\n");
1.319 brouard 4508: #ifdef FLATSUP
4509: free_vector(xit,1,n);
4510: free_vector(xits,1,n);
4511: free_vector(ptt,1,n);
4512: free_vector(pt,1,n);
4513: return;
4514: #endif
1.361 brouard 4515: } /* endif(flatd >0) */
4516: #endif /* LINMINORIGINAL */
1.234 brouard 4517: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
4518: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
4519:
1.126 brouard 4520: #ifdef DEBUG
1.234 brouard 4521: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
4522: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
4523: for(j=1;j<=n;j++){
4524: printf(" %lf",xit[j]);
4525: fprintf(ficlog," %lf",xit[j]);
4526: }
4527: printf("\n");
4528: fprintf(ficlog,"\n");
1.126 brouard 4529: #endif
1.192 brouard 4530: } /* end of t or directest negative */
1.359 brouard 4531: printf(" Directest is positive, P_n-P_0 does not increase the conjugacy. n=%d\n",n);
4532: fprintf(ficlog," Directest is positive, P_n-P_0 does not increase the conjugacy. n=%d\n",n);
1.224 brouard 4533: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 4534: #else
1.234 brouard 4535: } /* end if (fptt < fp) */
1.192 brouard 4536: #endif
1.225 brouard 4537: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 4538: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 4539: #else
1.224 brouard 4540: #endif
1.234 brouard 4541: } /* loop iteration */
1.126 brouard 4542: }
1.234 brouard 4543:
1.126 brouard 4544: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 4545:
1.235 brouard 4546: 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 4547: {
1.338 brouard 4548: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij . Nicely done
1.279 brouard 4549: * (and selected quantitative values in nres)
4550: * by left multiplying the unit
4551: * matrix by transitions matrix until convergence is reached with precision ftolpl
4552: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
4553: * Wx is row vector: population in state 1, population in state 2, population dead
4554: * or prevalence in state 1, prevalence in state 2, 0
4555: * newm is the matrix after multiplications, its rows are identical at a factor.
4556: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
4557: * Output is prlim.
4558: * Initial matrix pimij
4559: */
1.206 brouard 4560: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
4561: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
4562: /* 0, 0 , 1} */
4563: /*
4564: * and after some iteration: */
4565: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
4566: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
4567: /* 0, 0 , 1} */
4568: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
4569: /* {0.51571254859325999, 0.4842874514067399, */
4570: /* 0.51326036147820708, 0.48673963852179264} */
4571: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 4572:
1.332 brouard 4573: int i, ii,j,k, k1;
1.209 brouard 4574: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 4575: /* double **matprod2(); */ /* test */
1.218 brouard 4576: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 4577: double **newm;
1.209 brouard 4578: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 4579: int ncvloop=0;
1.288 brouard 4580: int first=0;
1.169 brouard 4581:
1.209 brouard 4582: min=vector(1,nlstate);
4583: max=vector(1,nlstate);
4584: meandiff=vector(1,nlstate);
4585:
1.218 brouard 4586: /* Starting with matrix unity */
1.126 brouard 4587: for (ii=1;ii<=nlstate+ndeath;ii++)
4588: for (j=1;j<=nlstate+ndeath;j++){
4589: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4590: }
1.169 brouard 4591:
4592: cov[1]=1.;
4593:
4594: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 4595: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 4596: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 4597: ncvloop++;
1.126 brouard 4598: newm=savm;
4599: /* Covariates have to be included here again */
1.138 brouard 4600: cov[2]=agefin;
1.319 brouard 4601: if(nagesqr==1){
4602: cov[3]= agefin*agefin;
4603: }
1.332 brouard 4604: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
4605: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
4606: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 4607: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 4608: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
4609: }else{
4610: cov[2+nagesqr+k1]=precov[nres][k1];
4611: }
4612: }/* End of loop on model equation */
4613:
4614: /* Start of old code (replaced by a loop on position in the model equation */
4615: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only of the model *\/ */
4616: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
4617: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; *\/ */
4618: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TnsdVar[TvarsD[k]])]; */
4619: /* /\* model = 1 +age + V1*V3 + age*V1 + V2 + V1 + age*V2 + V3 + V3*age + V1*V2 */
4620: /* * k 1 2 3 4 5 6 7 8 */
4621: /* *cov[] 1 2 3 4 5 6 7 8 9 10 */
4622: /* *TypeVar[k] 2 1 0 0 1 0 1 2 */
4623: /* *Dummy[k] 0 2 0 0 2 0 2 0 */
4624: /* *Tvar[k] 4 1 2 1 2 3 3 5 */
4625: /* *nsd=3 (1) (2) (3) */
4626: /* *TvarsD[nsd] [1]=2 1 3 */
4627: /* *TnsdVar [2]=2 [1]=1 [3]=3 */
4628: /* *TvarsDind[nsd](=k) [1]=3 [2]=4 [3]=6 */
4629: /* *Tage[] [1]=1 [2]=2 [3]=3 */
4630: /* *Tvard[] [1][1]=1 [2][1]=1 */
4631: /* * [1][2]=3 [2][2]=2 */
4632: /* *Tprod[](=k) [1]=1 [2]=8 */
4633: /* *TvarsDp(=Tvar) [1]=1 [2]=2 [3]=3 [4]=5 */
4634: /* *TvarD (=k) [1]=1 [2]=3 [3]=4 [3]=6 [4]=6 */
4635: /* *TvarsDpType */
4636: /* *si model= 1 + age + V3 + V2*age + V2 + V3*age */
4637: /* * nsd=1 (1) (2) */
4638: /* *TvarsD[nsd] 3 2 */
4639: /* *TnsdVar (3)=1 (2)=2 */
4640: /* *TvarsDind[nsd](=k) [1]=1 [2]=3 */
4641: /* *Tage[] [1]=2 [2]= 3 */
4642: /* *\/ */
4643: /* /\* cov[++k1]=nbcode[TvarsD[k]][codtabm(ij,k)]; *\/ */
4644: /* /\* 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)); *\/ */
4645: /* } */
4646: /* for (k=1; k<=nsq;k++) { /\* For single quantitative varying covariates only of the model *\/ */
4647: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
4648: /* /\* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline *\/ */
4649: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
4650: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][resultmodel[nres][k1]] */
4651: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
4652: /* /\* 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]); *\/ */
4653: /* } */
4654: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
4655: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
4656: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
4657: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
4658: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
4659: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
4660: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
4661: /* } */
4662: /* /\* 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]); *\/ */
4663: /* } */
4664: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
4665: /* /\* 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]); *\/ */
4666: /* if(Dummy[Tvard[k][1]]==0){ */
4667: /* if(Dummy[Tvard[k][2]]==0){ */
4668: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
4669: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
4670: /* }else{ */
4671: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
4672: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
4673: /* } */
4674: /* }else{ */
4675: /* if(Dummy[Tvard[k][2]]==0){ */
4676: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
4677: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
4678: /* }else{ */
4679: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
4680: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
4681: /* } */
4682: /* } */
4683: /* } /\* End product without age *\/ */
4684: /* ENd of old code */
1.138 brouard 4685: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
4686: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
4687: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 4688: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
4689: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.319 brouard 4690: /* age and covariate values of ij are in 'cov' */
1.142 brouard 4691: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 4692:
1.126 brouard 4693: savm=oldm;
4694: oldm=newm;
1.209 brouard 4695:
4696: for(j=1; j<=nlstate; j++){
4697: max[j]=0.;
4698: min[j]=1.;
4699: }
4700: for(i=1;i<=nlstate;i++){
4701: sumnew=0;
4702: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
4703: for(j=1; j<=nlstate; j++){
4704: prlim[i][j]= newm[i][j]/(1-sumnew);
4705: max[j]=FMAX(max[j],prlim[i][j]);
4706: min[j]=FMIN(min[j],prlim[i][j]);
4707: }
4708: }
4709:
1.126 brouard 4710: maxmax=0.;
1.209 brouard 4711: for(j=1; j<=nlstate; j++){
4712: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
4713: maxmax=FMAX(maxmax,meandiff[j]);
4714: /* 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 4715: } /* j loop */
1.203 brouard 4716: *ncvyear= (int)age- (int)agefin;
1.208 brouard 4717: /* 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 4718: if(maxmax < ftolpl){
1.209 brouard 4719: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
4720: free_vector(min,1,nlstate);
4721: free_vector(max,1,nlstate);
4722: free_vector(meandiff,1,nlstate);
1.126 brouard 4723: return prlim;
4724: }
1.288 brouard 4725: } /* agefin loop */
1.208 brouard 4726: /* After some age loop it doesn't converge */
1.288 brouard 4727: if(!first){
4728: first=1;
4729: 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 4730: 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);
4731: }else if (first >=1 && first <10){
4732: 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);
4733: first++;
4734: }else if (first ==10){
4735: 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);
4736: 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");
4737: fprintf(ficlog,"Warning: the stable prevalence no convergence; too many cases, giving up noticing, even in log file\n");
4738: first++;
1.288 brouard 4739: }
4740:
1.359 brouard 4741: /* Try to lower 'ftol', for example from 1.e-8 to 6.e-9.\n", ftolpl,
4742: * (int)age, (int)delaymax, (int)agefin, ncvloop,
4743: * (int)age-(int)agefin); */
1.209 brouard 4744: free_vector(min,1,nlstate);
4745: free_vector(max,1,nlstate);
4746: free_vector(meandiff,1,nlstate);
1.208 brouard 4747:
1.169 brouard 4748: return prlim; /* should not reach here */
1.126 brouard 4749: }
4750:
1.217 brouard 4751:
4752: /**** Back Prevalence limit (stable or period prevalence) ****************/
4753:
1.218 brouard 4754: /* 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) */
4755: /* 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 4756: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 4757: {
1.264 brouard 4758: /* 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 4759: matrix by transitions matrix until convergence is reached with precision ftolpl */
4760: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
4761: /* Wx is row vector: population in state 1, population in state 2, population dead */
4762: /* or prevalence in state 1, prevalence in state 2, 0 */
4763: /* newm is the matrix after multiplications, its rows are identical at a factor */
4764: /* Initial matrix pimij */
4765: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
4766: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
4767: /* 0, 0 , 1} */
4768: /*
4769: * and after some iteration: */
4770: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
4771: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
4772: /* 0, 0 , 1} */
4773: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
4774: /* {0.51571254859325999, 0.4842874514067399, */
4775: /* 0.51326036147820708, 0.48673963852179264} */
4776: /* If we start from prlim again, prlim tends to a constant matrix */
4777:
1.359 brouard 4778: int i, ii,j, k1;
1.247 brouard 4779: int first=0;
1.217 brouard 4780: double *min, *max, *meandiff, maxmax,sumnew=0.;
4781: /* double **matprod2(); */ /* test */
4782: double **out, cov[NCOVMAX+1], **bmij();
4783: double **newm;
1.218 brouard 4784: double **dnewm, **doldm, **dsavm; /* for use */
4785: double **oldm, **savm; /* for use */
4786:
1.217 brouard 4787: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
4788: int ncvloop=0;
4789:
4790: min=vector(1,nlstate);
4791: max=vector(1,nlstate);
4792: meandiff=vector(1,nlstate);
4793:
1.266 brouard 4794: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
4795: oldm=oldms; savm=savms;
4796:
4797: /* Starting with matrix unity */
4798: for (ii=1;ii<=nlstate+ndeath;ii++)
4799: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 4800: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4801: }
4802:
4803: cov[1]=1.;
4804:
4805: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
4806: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 4807: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 4808: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
4809: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 4810: ncvloop++;
1.218 brouard 4811: newm=savm; /* oldm should be kept from previous iteration or unity at start */
4812: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 4813: /* Covariates have to be included here again */
4814: cov[2]=agefin;
1.319 brouard 4815: if(nagesqr==1){
1.217 brouard 4816: cov[3]= agefin*agefin;;
1.319 brouard 4817: }
1.332 brouard 4818: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 4819: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 4820: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.242 brouard 4821: }else{
1.332 brouard 4822: cov[2+nagesqr+k1]=precov[nres][k1];
1.242 brouard 4823: }
1.332 brouard 4824: }/* End of loop on model equation */
4825:
4826: /* Old code */
4827:
4828: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
4829: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
4830: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; */
4831: /* /\* 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)); *\/ */
4832: /* } */
4833: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
4834: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
4835: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
4836: /* /\* /\\* 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])]); *\\/ *\/ */
4837: /* /\* } *\/ */
4838: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
4839: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
4840: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
4841: /* /\* 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]); *\/ */
4842: /* } */
4843: /* /\* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; *\/ */
4844: /* /\* for (k=1; k<=cptcovprod;k++) /\\* Useless *\\/ *\/ */
4845: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\\/ *\/ */
4846: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
4847: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
4848: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age *\\/ ERROR ???*\/ */
4849: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
4850: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
4851: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
4852: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
4853: /* } */
4854: /* /\* 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]); *\/ */
4855: /* } */
4856: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
4857: /* /\* 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]); *\/ */
4858: /* if(Dummy[Tvard[k][1]]==0){ */
4859: /* if(Dummy[Tvard[k][2]]==0){ */
4860: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
4861: /* }else{ */
4862: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
4863: /* } */
4864: /* }else{ */
4865: /* if(Dummy[Tvard[k][2]]==0){ */
4866: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
4867: /* }else{ */
4868: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
4869: /* } */
4870: /* } */
4871: /* } */
1.217 brouard 4872:
4873: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
4874: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
4875: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
4876: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
4877: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 4878: /* ij should be linked to the correct index of cov */
4879: /* age and covariate values ij are in 'cov', but we need to pass
4880: * ij for the observed prevalence at age and status and covariate
4881: * number: prevacurrent[(int)agefin][ii][ij]
4882: */
4883: /* 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 *\/ */
4884: /* 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 *\/ */
4885: 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 4886: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 4887: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
4888: /* for(i=1; i<=nlstate+ndeath; i++) { */
4889: /* printf("%d newm= ",i); */
4890: /* for(j=1;j<=nlstate+ndeath;j++) { */
4891: /* printf("%f ",newm[i][j]); */
4892: /* } */
4893: /* printf("oldm * "); */
4894: /* for(j=1;j<=nlstate+ndeath;j++) { */
4895: /* printf("%f ",oldm[i][j]); */
4896: /* } */
1.268 brouard 4897: /* printf(" bmmij "); */
1.266 brouard 4898: /* for(j=1;j<=nlstate+ndeath;j++) { */
4899: /* printf("%f ",pmmij[i][j]); */
4900: /* } */
4901: /* printf("\n"); */
4902: /* } */
4903: /* } */
1.217 brouard 4904: savm=oldm;
4905: oldm=newm;
1.266 brouard 4906:
1.217 brouard 4907: for(j=1; j<=nlstate; j++){
4908: max[j]=0.;
4909: min[j]=1.;
4910: }
4911: for(j=1; j<=nlstate; j++){
4912: for(i=1;i<=nlstate;i++){
1.234 brouard 4913: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
4914: bprlim[i][j]= newm[i][j];
4915: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
4916: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 4917: }
4918: }
1.218 brouard 4919:
1.217 brouard 4920: maxmax=0.;
4921: for(i=1; i<=nlstate; i++){
1.318 brouard 4922: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column, could be nan! */
1.217 brouard 4923: maxmax=FMAX(maxmax,meandiff[i]);
4924: /* 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 4925: } /* i loop */
1.217 brouard 4926: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 4927: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 4928: if(maxmax < ftolpl){
1.220 brouard 4929: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 4930: free_vector(min,1,nlstate);
4931: free_vector(max,1,nlstate);
4932: free_vector(meandiff,1,nlstate);
4933: return bprlim;
4934: }
1.288 brouard 4935: } /* agefin loop */
1.217 brouard 4936: /* After some age loop it doesn't converge */
1.288 brouard 4937: if(!first){
1.247 brouard 4938: first=1;
4939: 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\
4940: 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);
4941: }
4942: 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 4943: 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);
4944: /* 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); */
4945: free_vector(min,1,nlstate);
4946: free_vector(max,1,nlstate);
4947: free_vector(meandiff,1,nlstate);
4948:
4949: return bprlim; /* should not reach here */
4950: }
4951:
1.126 brouard 4952: /*************** transition probabilities ***************/
4953:
4954: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
4955: {
1.138 brouard 4956: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 4957: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 4958: model to the ncovmodel covariates (including constant and age).
4959: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
4960: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
4961: ncth covariate in the global vector x is given by the formula:
4962: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
4963: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
4964: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
4965: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 4966: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 4967: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 4968: Sum on j ps[i][j] should equal to 1.
1.138 brouard 4969: */
4970: double s1, lnpijopii;
1.126 brouard 4971: /*double t34;*/
1.164 brouard 4972: int i,j, nc, ii, jj;
1.126 brouard 4973:
1.223 brouard 4974: for(i=1; i<= nlstate; i++){
4975: for(j=1; j<i;j++){
4976: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
4977: /*lnpijopii += param[i][j][nc]*cov[nc];*/
4978: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
4979: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
4980: }
4981: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 4982: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 4983: }
4984: for(j=i+1; j<=nlstate+ndeath;j++){
4985: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
4986: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
4987: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
4988: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
4989: }
4990: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 4991: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 4992: }
4993: }
1.218 brouard 4994:
1.223 brouard 4995: for(i=1; i<= nlstate; i++){
4996: s1=0;
4997: for(j=1; j<i; j++){
1.339 brouard 4998: /* printf("debug1 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 4999: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
5000: }
5001: for(j=i+1; j<=nlstate+ndeath; j++){
1.339 brouard 5002: /* printf("debug2 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 5003: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
5004: }
5005: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
5006: ps[i][i]=1./(s1+1.);
5007: /* Computing other pijs */
5008: for(j=1; j<i; j++)
1.325 brouard 5009: ps[i][j]= exp(ps[i][j])*ps[i][i];/* Bug valgrind */
1.223 brouard 5010: for(j=i+1; j<=nlstate+ndeath; j++)
5011: ps[i][j]= exp(ps[i][j])*ps[i][i];
5012: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
5013: } /* end i */
1.218 brouard 5014:
1.223 brouard 5015: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
5016: for(jj=1; jj<= nlstate+ndeath; jj++){
5017: ps[ii][jj]=0;
5018: ps[ii][ii]=1;
5019: }
5020: }
1.294 brouard 5021:
5022:
1.223 brouard 5023: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
5024: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
5025: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
5026: /* } */
5027: /* printf("\n "); */
5028: /* } */
5029: /* printf("\n ");printf("%lf ",cov[2]);*/
5030: /*
5031: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 5032: goto end;*/
1.266 brouard 5033: return ps; /* Pointer is unchanged since its call */
1.126 brouard 5034: }
5035:
1.218 brouard 5036: /*************** backward transition probabilities ***************/
5037:
5038: /* 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 ) */
5039: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
5040: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
5041: {
1.302 brouard 5042: /* 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 5043: * 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 5044: */
1.359 brouard 5045: int ii, j;
1.222 brouard 5046:
1.359 brouard 5047: double **pmij();
1.222 brouard 5048: double sumnew=0.;
1.218 brouard 5049: double agefin;
1.292 brouard 5050: 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 5051: double **dnewm, **dsavm, **doldm;
5052: double **bbmij;
5053:
1.218 brouard 5054: doldm=ddoldms; /* global pointers */
1.222 brouard 5055: dnewm=ddnewms;
5056: dsavm=ddsavms;
1.318 brouard 5057:
5058: /* Debug */
5059: /* printf("Bmij ij=%d, cov[2}=%f\n", ij, cov[2]); */
1.222 brouard 5060: agefin=cov[2];
1.268 brouard 5061: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 5062: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 5063: the observed prevalence (with this covariate ij) at beginning of transition */
5064: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 5065:
5066: /* P_x */
1.325 brouard 5067: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm *//* Bug valgrind */
1.268 brouard 5068: /* outputs pmmij which is a stochastic matrix in row */
5069:
5070: /* Diag(w_x) */
1.292 brouard 5071: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 5072: sumnew=0.;
1.269 brouard 5073: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 5074: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.297 brouard 5075: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 5076: sumnew+=prevacurrent[(int)agefin][ii][ij];
5077: }
5078: if(sumnew >0.01){ /* At least some value in the prevalence */
5079: for (ii=1;ii<=nlstate+ndeath;ii++){
5080: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 5081: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 5082: }
5083: }else{
5084: for (ii=1;ii<=nlstate+ndeath;ii++){
5085: for (j=1;j<=nlstate+ndeath;j++)
5086: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
5087: }
5088: /* if(sumnew <0.9){ */
5089: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
5090: /* } */
5091: }
5092: k3=0.0; /* We put the last diagonal to 0 */
5093: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
5094: doldm[ii][ii]= k3;
5095: }
5096: /* End doldm, At the end doldm is diag[(w_i)] */
5097:
1.292 brouard 5098: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
5099: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 5100:
1.292 brouard 5101: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 5102: /* 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 5103: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 5104: sumnew=0.;
1.222 brouard 5105: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 5106: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 5107: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 5108: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 5109: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 5110: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 5111: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 5112: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 5113: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 5114: /* }else */
1.268 brouard 5115: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
5116: } /*End ii */
5117: } /* 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 */
5118:
1.292 brouard 5119: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 5120: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 5121: /* end bmij */
1.266 brouard 5122: return ps; /*pointer is unchanged */
1.218 brouard 5123: }
1.217 brouard 5124: /*************** transition probabilities ***************/
5125:
1.218 brouard 5126: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 5127: {
5128: /* According to parameters values stored in x and the covariate's values stored in cov,
5129: computes the probability to be observed in state j being in state i by appying the
5130: model to the ncovmodel covariates (including constant and age).
5131: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
5132: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
5133: ncth covariate in the global vector x is given by the formula:
5134: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
5135: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
5136: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
5137: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
5138: Outputs ps[i][j] the probability to be observed in j being in j according to
5139: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
5140: */
5141: double s1, lnpijopii;
5142: /*double t34;*/
5143: int i,j, nc, ii, jj;
5144:
1.234 brouard 5145: for(i=1; i<= nlstate; i++){
5146: for(j=1; j<i;j++){
5147: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
5148: /*lnpijopii += param[i][j][nc]*cov[nc];*/
5149: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
5150: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
5151: }
5152: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
5153: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
5154: }
5155: for(j=i+1; j<=nlstate+ndeath;j++){
5156: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
5157: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
5158: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
5159: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
5160: }
5161: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
5162: }
5163: }
5164:
5165: for(i=1; i<= nlstate; i++){
5166: s1=0;
5167: for(j=1; j<i; j++){
5168: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
5169: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
5170: }
5171: for(j=i+1; j<=nlstate+ndeath; j++){
5172: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
5173: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
5174: }
5175: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
5176: ps[i][i]=1./(s1+1.);
5177: /* Computing other pijs */
5178: for(j=1; j<i; j++)
5179: ps[i][j]= exp(ps[i][j])*ps[i][i];
5180: for(j=i+1; j<=nlstate+ndeath; j++)
5181: ps[i][j]= exp(ps[i][j])*ps[i][i];
5182: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
5183: } /* end i */
5184:
5185: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
5186: for(jj=1; jj<= nlstate+ndeath; jj++){
5187: ps[ii][jj]=0;
5188: ps[ii][ii]=1;
5189: }
5190: }
1.296 brouard 5191: /* Added for prevbcast */ /* Transposed matrix too */
1.234 brouard 5192: for(jj=1; jj<= nlstate+ndeath; jj++){
5193: s1=0.;
5194: for(ii=1; ii<= nlstate+ndeath; ii++){
5195: s1+=ps[ii][jj];
5196: }
5197: for(ii=1; ii<= nlstate; ii++){
5198: ps[ii][jj]=ps[ii][jj]/s1;
5199: }
5200: }
5201: /* Transposition */
5202: for(jj=1; jj<= nlstate+ndeath; jj++){
5203: for(ii=jj; ii<= nlstate+ndeath; ii++){
5204: s1=ps[ii][jj];
5205: ps[ii][jj]=ps[jj][ii];
5206: ps[jj][ii]=s1;
5207: }
5208: }
5209: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
5210: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
5211: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
5212: /* } */
5213: /* printf("\n "); */
5214: /* } */
5215: /* printf("\n ");printf("%lf ",cov[2]);*/
5216: /*
5217: for(i=1; i<= npar; i++) printf("%f ",x[i]);
5218: goto end;*/
5219: return ps;
1.217 brouard 5220: }
5221:
5222:
1.126 brouard 5223: /**************** Product of 2 matrices ******************/
5224:
1.145 brouard 5225: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 5226: {
5227: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
5228: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
5229: /* in, b, out are matrice of pointers which should have been initialized
5230: before: only the contents of out is modified. The function returns
5231: a pointer to pointers identical to out */
1.145 brouard 5232: int i, j, k;
1.126 brouard 5233: for(i=nrl; i<= nrh; i++)
1.145 brouard 5234: for(k=ncolol; k<=ncoloh; k++){
5235: out[i][k]=0.;
5236: for(j=ncl; j<=nch; j++)
5237: out[i][k] +=in[i][j]*b[j][k];
5238: }
1.126 brouard 5239: return out;
5240: }
5241:
5242:
5243: /************* Higher Matrix Product ***************/
5244:
1.235 brouard 5245: 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 5246: {
1.336 brouard 5247: /* Already optimized with precov.
5248: 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 5249: 'nhstepm*hstepm*stepm' months (i.e. until
5250: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
5251: nhstepm*hstepm matrices.
5252: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
5253: (typically every 2 years instead of every month which is too big
5254: for the memory).
5255: Model is determined by parameters x and covariates have to be
5256: included manually here.
5257:
5258: */
5259:
1.359 brouard 5260: int i, j, d, h, k1;
1.131 brouard 5261: double **out, cov[NCOVMAX+1];
1.126 brouard 5262: double **newm;
1.187 brouard 5263: double agexact;
1.359 brouard 5264: /*double agebegin, ageend;*/
1.126 brouard 5265:
5266: /* Hstepm could be zero and should return the unit matrix */
5267: for (i=1;i<=nlstate+ndeath;i++)
5268: for (j=1;j<=nlstate+ndeath;j++){
5269: oldm[i][j]=(i==j ? 1.0 : 0.0);
5270: po[i][j][0]=(i==j ? 1.0 : 0.0);
5271: }
5272: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
5273: for(h=1; h <=nhstepm; h++){
5274: for(d=1; d <=hstepm; d++){
5275: newm=savm;
5276: /* Covariates have to be included here again */
5277: cov[1]=1.;
1.214 brouard 5278: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 5279: cov[2]=agexact;
1.319 brouard 5280: if(nagesqr==1){
1.227 brouard 5281: cov[3]= agexact*agexact;
1.319 brouard 5282: }
1.330 brouard 5283: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
5284: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
5285: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 5286: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 5287: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
5288: }else{
5289: cov[2+nagesqr+k1]=precov[nres][k1];
5290: }
5291: }/* End of loop on model equation */
5292: /* Old code */
5293: /* if( Dummy[k1]==0 && Typevar[k1]==0 ){ /\* Single dummy *\/ */
5294: /* /\* V(Tvarsel)=Tvalsel=Tresult[nres][pos](value); V(Tvresult[nres][pos] (variable): V(variable)=value) *\/ */
5295: /* /\* for (k=1; k<=nsd;k++) { /\\* For single dummy covariates only *\\/ *\/ */
5296: /* /\* /\\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\\/ *\/ */
5297: /* /\* codtabm(ij,k) (1 & (ij-1) >> (k-1))+1 *\/ */
5298: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
5299: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
5300: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
5301: /* /\* nsd 1 2 3 *\/ /\* Counting single dummies covar fixed or tv *\/ */
5302: /* /\*TvarsD[nsd] 4 3 1 *\/ /\* ID of single dummy cova fixed or timevary*\/ */
5303: /* /\*TvarsDind[k] 2 3 9 *\/ /\* position K of single dummy cova *\/ */
5304: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];or [codtabm(ij,TnsdVar[TvarsD[k]] *\/ */
5305: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
5306: /* /\* 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]])); *\/ */
5307: /* 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); */
5308: /* printf("hpxij new Dummy precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
5309: /* }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /\* Single quantitative variables *\/ */
5310: /* /\* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline *\/ */
5311: /* cov[2+nagesqr+k1]=Tqresult[nres][resultmodel[nres][k1]]; */
5312: /* /\* for (k=1; k<=nsq;k++) { /\\* For single varying covariates only *\\/ *\/ */
5313: /* /\* /\\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\\/ *\/ */
5314: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
5315: /* 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]]); */
5316: /* printf("hpxij new Quanti precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
5317: /* }else if( Dummy[k1]==2 ){ /\* For dummy with age product *\/ */
5318: /* /\* Tvar[k1] Variable in the age product age*V1 is 1 *\/ */
5319: /* /\* [Tinvresult[nres][V1] is its value in the resultline nres *\/ */
5320: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvar[k1]]*cov[2]; */
5321: /* 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]); */
5322: /* printf("hpxij new Dummy with age product precov[nres=%d][k1=%d]=%.4f * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
5323:
5324: /* /\* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; *\/ */
5325: /* /\* for (k=1; k<=cptcovage;k++){ /\\* For product with age V1+V1*age +V4 +age*V3 *\\/ *\/ */
5326: /* /\* 1+2 Tage[1]=2 TVar[2]=1 Dummy[2]=2, Tage[2]=4 TVar[4]=3 Dummy[4]=3 quant*\/ */
5327: /* /\* *\/ */
1.330 brouard 5328: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
5329: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
5330: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
1.332 brouard 5331: /* /\*cptcovage=2 1 2 *\/ */
5332: /* /\*Tage[k]= 5 8 *\/ */
5333: /* }else if( Dummy[k1]==3 ){ /\* For quant with age product *\/ */
5334: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
5335: /* 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]]); */
5336: /* printf("hpxij new Quanti with age product precov[nres=%d][k1=%d] * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
5337: /* /\* if(Dummy[Tage[k]]== 2){ /\\* dummy with age *\\/ *\/ */
5338: /* /\* /\\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\\* dummy with age *\\\/ *\\/ *\/ */
5339: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\\/ *\/ */
5340: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\\/ *\/ */
5341: /* /\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\/ */
5342: /* /\* 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); *\/ */
5343: /* /\* } else if(Dummy[Tage[k]]== 3){ /\\* quantitative with age *\\/ *\/ */
5344: /* /\* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; *\/ */
5345: /* /\* } *\/ */
5346: /* /\* 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]); *\/ */
5347: /* }else if(Typevar[k1]==2 ){ /\* For product (not with age) *\/ */
5348: /* /\* for (k=1; k<=cptcovprod;k++){ /\\* For product without age *\\/ *\/ */
5349: /* /\* /\\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\\/ *\/ */
5350: /* /\* /\\* k 1 2 3 4 5 6 7 8 9 *\\/ *\/ */
5351: /* /\* /\\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\\/ *\/ */
5352: /* /\* /\\*cptcovprod=1 1 2 *\\/ *\/ */
5353: /* /\* /\\*Tprod[]= 4 7 *\\/ *\/ */
5354: /* /\* /\\*Tvard[][1] 4 1 *\\/ *\/ */
5355: /* /\* /\\*Tvard[][2] 3 2 *\\/ *\/ */
1.330 brouard 5356:
1.332 brouard 5357: /* /\* 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])]); *\/ */
5358: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
5359: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]]; */
5360: /* 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]]); */
5361: /* printf("hpxij new Product no age product precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
5362:
5363: /* /\* if(Dummy[Tvardk[k1][1]]==0){ *\/ */
5364: /* /\* if(Dummy[Tvardk[k1][2]]==0){ /\\* Product of dummies *\\/ *\/ */
5365: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
5366: /* /\* cov[2+nagesqr+k1]=Tinvresult[nres][Tvardk[k1][1]] * Tinvresult[nres][Tvardk[k1][2]]; *\/ */
5367: /* /\* 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]])]; *\/ */
5368: /* /\* }else{ /\\* Product of dummy by quantitative *\\/ *\/ */
5369: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,TnsdVar[Tvard[k][1]])] * Tqresult[nres][k]; *\/ */
5370: /* /\* cov[2+nagesqr+k1]=Tresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]]; *\/ */
5371: /* /\* } *\/ */
5372: /* /\* }else{ /\\* Product of quantitative by...*\\/ *\/ */
5373: /* /\* if(Dummy[Tvard[k][2]]==0){ /\\* quant by dummy *\\/ *\/ */
5374: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][Tvard[k][1]]; *\\/ *\/ */
5375: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
5376: /* /\* }else{ /\\* Product of two quant *\\/ *\/ */
5377: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\\/ *\/ */
5378: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
5379: /* /\* } *\/ */
5380: /* /\* }/\\*end of products quantitative *\\/ *\/ */
5381: /* }/\*end of products *\/ */
5382: /* } /\* End of loop on model equation *\/ */
1.235 brouard 5383: /* for (k=1; k<=cptcovn;k++) */
5384: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
5385: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
5386: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
5387: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
5388: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 5389:
5390:
1.126 brouard 5391: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
5392: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.319 brouard 5393: /* right multiplication of oldm by the current matrix */
1.126 brouard 5394: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
5395: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 5396: /* if((int)age == 70){ */
5397: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
5398: /* for(i=1; i<=nlstate+ndeath; i++) { */
5399: /* printf("%d pmmij ",i); */
5400: /* for(j=1;j<=nlstate+ndeath;j++) { */
5401: /* printf("%f ",pmmij[i][j]); */
5402: /* } */
5403: /* printf(" oldm "); */
5404: /* for(j=1;j<=nlstate+ndeath;j++) { */
5405: /* printf("%f ",oldm[i][j]); */
5406: /* } */
5407: /* printf("\n"); */
5408: /* } */
5409: /* } */
1.126 brouard 5410: savm=oldm;
5411: oldm=newm;
5412: }
5413: for(i=1; i<=nlstate+ndeath; i++)
5414: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 5415: po[i][j][h]=newm[i][j];
5416: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 5417: }
1.128 brouard 5418: /*printf("h=%d ",h);*/
1.126 brouard 5419: } /* end h */
1.267 brouard 5420: /* printf("\n H=%d \n",h); */
1.126 brouard 5421: return po;
5422: }
5423:
1.217 brouard 5424: /************* Higher Back Matrix Product ***************/
1.218 brouard 5425: /* 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 5426: 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 5427: {
1.332 brouard 5428: /* For dummy covariates given in each resultline (for historical, computes the corresponding combination ij),
5429: computes the transition matrix starting at age 'age' over
1.217 brouard 5430: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 5431: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
5432: nhstepm*hstepm matrices.
5433: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
5434: (typically every 2 years instead of every month which is too big
1.217 brouard 5435: for the memory).
1.218 brouard 5436: Model is determined by parameters x and covariates have to be
1.266 brouard 5437: included manually here. Then we use a call to bmij(x and cov)
5438: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 5439: */
1.217 brouard 5440:
1.359 brouard 5441: int i, j, d, h, k1;
1.266 brouard 5442: double **out, cov[NCOVMAX+1], **bmij();
5443: double **newm, ***newmm;
1.217 brouard 5444: double agexact;
1.359 brouard 5445: /*double agebegin, ageend;*/
1.222 brouard 5446: double **oldm, **savm;
1.217 brouard 5447:
1.266 brouard 5448: newmm=po; /* To be saved */
5449: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 5450: /* Hstepm could be zero and should return the unit matrix */
5451: for (i=1;i<=nlstate+ndeath;i++)
5452: for (j=1;j<=nlstate+ndeath;j++){
5453: oldm[i][j]=(i==j ? 1.0 : 0.0);
5454: po[i][j][0]=(i==j ? 1.0 : 0.0);
5455: }
5456: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
5457: for(h=1; h <=nhstepm; h++){
5458: for(d=1; d <=hstepm; d++){
5459: newm=savm;
5460: /* Covariates have to be included here again */
5461: cov[1]=1.;
1.271 brouard 5462: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 5463: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
1.318 brouard 5464: /* Debug */
5465: /* printf("hBxij age=%lf, agexact=%lf\n", age, agexact); */
1.217 brouard 5466: cov[2]=agexact;
1.332 brouard 5467: if(nagesqr==1){
1.222 brouard 5468: cov[3]= agexact*agexact;
1.332 brouard 5469: }
5470: /** New code */
5471: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 5472: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 5473: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.325 brouard 5474: }else{
1.332 brouard 5475: cov[2+nagesqr+k1]=precov[nres][k1];
1.325 brouard 5476: }
1.332 brouard 5477: }/* End of loop on model equation */
5478: /** End of new code */
5479: /** This was old code */
5480: /* for (k=1; k<=nsd;k++){ /\* For single dummy covariates only *\//\* cptcovn error *\/ */
5481: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
5482: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
5483: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])];/\* Bug valgrind *\/ */
5484: /* /\* 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)); *\/ */
5485: /* } */
5486: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
5487: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
5488: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
5489: /* /\* 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]); *\/ */
5490: /* } */
5491: /* for (k=1; k<=cptcovage;k++){ /\* Should start at cptcovn+1 *\//\* For product with age *\/ */
5492: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age error!!!*\\/ *\/ */
5493: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
5494: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
5495: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
5496: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
5497: /* } */
5498: /* /\* 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]); *\/ */
5499: /* } */
5500: /* for (k=1; k<=cptcovprod;k++){ /\* Useless because included in cptcovn *\/ */
5501: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])]*nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
5502: /* if(Dummy[Tvard[k][1]]==0){ */
5503: /* if(Dummy[Tvard[k][2]]==0){ */
5504: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][1])]; */
5505: /* }else{ */
5506: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
5507: /* } */
5508: /* }else{ */
5509: /* if(Dummy[Tvard[k][2]]==0){ */
5510: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
5511: /* }else{ */
5512: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
5513: /* } */
5514: /* } */
5515: /* } */
5516: /* /\*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*\/ */
5517: /* /\*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*\/ */
5518: /** End of old code */
5519:
1.218 brouard 5520: /* Careful transposed matrix */
1.266 brouard 5521: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 5522: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 5523: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 5524: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.325 brouard 5525: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);/* Bug valgrind */
1.217 brouard 5526: /* if((int)age == 70){ */
5527: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
5528: /* for(i=1; i<=nlstate+ndeath; i++) { */
5529: /* printf("%d pmmij ",i); */
5530: /* for(j=1;j<=nlstate+ndeath;j++) { */
5531: /* printf("%f ",pmmij[i][j]); */
5532: /* } */
5533: /* printf(" oldm "); */
5534: /* for(j=1;j<=nlstate+ndeath;j++) { */
5535: /* printf("%f ",oldm[i][j]); */
5536: /* } */
5537: /* printf("\n"); */
5538: /* } */
5539: /* } */
5540: savm=oldm;
5541: oldm=newm;
5542: }
5543: for(i=1; i<=nlstate+ndeath; i++)
5544: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 5545: po[i][j][h]=newm[i][j];
1.268 brouard 5546: /* if(h==nhstepm) */
5547: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 5548: }
1.268 brouard 5549: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 5550: } /* end h */
1.268 brouard 5551: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 5552: return po;
5553: }
5554:
5555:
1.162 brouard 5556: #ifdef NLOPT
5557: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
5558: double fret;
5559: double *xt;
5560: int j;
5561: myfunc_data *d2 = (myfunc_data *) pd;
5562: /* xt = (p1-1); */
5563: xt=vector(1,n);
5564: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
5565:
5566: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
5567: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
5568: printf("Function = %.12lf ",fret);
5569: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
5570: printf("\n");
5571: free_vector(xt,1,n);
5572: return fret;
5573: }
5574: #endif
1.126 brouard 5575:
5576: /*************** log-likelihood *************/
5577: double func( double *x)
5578: {
1.336 brouard 5579: int i, ii, j, k, mi, d, kk, kf=0;
1.226 brouard 5580: int ioffset=0;
1.339 brouard 5581: int ipos=0,iposold=0,ncovv=0;
5582:
1.340 brouard 5583: double cotvarv, cotvarvold;
1.226 brouard 5584: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
5585: double **out;
5586: double lli; /* Individual log likelihood */
5587: int s1, s2;
1.228 brouard 5588: 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 5589:
1.226 brouard 5590: double bbh, survp;
5591: double agexact;
1.336 brouard 5592: double agebegin, ageend;
1.226 brouard 5593: /*extern weight */
5594: /* We are differentiating ll according to initial status */
5595: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
5596: /*for(i=1;i<imx;i++)
5597: printf(" %d\n",s[4][i]);
5598: */
1.162 brouard 5599:
1.226 brouard 5600: ++countcallfunc;
1.162 brouard 5601:
1.226 brouard 5602: cov[1]=1.;
1.126 brouard 5603:
1.226 brouard 5604: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 5605: ioffset=0;
1.226 brouard 5606: if(mle==1){
5607: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
5608: /* Computes the values of the ncovmodel covariates of the model
5609: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
5610: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
5611: to be observed in j being in i according to the model.
5612: */
1.243 brouard 5613: ioffset=2+nagesqr ;
1.233 brouard 5614: /* Fixed */
1.345 brouard 5615: for (kf=1; kf<=ncovf;kf++){ /* For each fixed covariate dummy or quant or prod */
1.319 brouard 5616: /* # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi */
5617: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
5618: /* 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 5619: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.336 brouard 5620: 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 5621: /* V1*V2 (7) TvarFind[2]=7, TvarFind[3]=9 */
1.234 brouard 5622: }
1.226 brouard 5623: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
1.319 brouard 5624: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
1.226 brouard 5625: has been calculated etc */
5626: /* For an individual i, wav[i] gives the number of effective waves */
5627: /* We compute the contribution to Likelihood of each effective transition
5628: mw[mi][i] is real wave of the mi th effectve wave */
5629: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
5630: s2=s[mw[mi+1][i]][i];
1.341 brouard 5631: 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 5632: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
5633: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
5634: */
1.336 brouard 5635: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
5636: /* Wave varying (but not age varying) */
1.339 brouard 5637: /* 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*\/ */
5638: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; but where is the crossproduct? *\/ */
5639: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
5640: /* } */
1.340 brouard 5641: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age )*/
5642: itv=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
5643: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
1.345 brouard 5644: if(FixedV[itv]!=0){ /* Not a fixed covariate */
1.341 brouard 5645: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]][i]; /* cotvar[wav][ncovcol+nqv+iv][i] */
1.340 brouard 5646: }else{ /* fixed covariate */
1.345 brouard 5647: 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 5648: }
1.339 brouard 5649: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 brouard 5650: cotvarvold=cotvarv;
5651: }else{ /* A second product */
5652: cotvarv=cotvarv*cotvarvold;
1.339 brouard 5653: }
5654: iposold=ipos;
1.340 brouard 5655: cov[ioffset+ipos]=cotvarv;
1.234 brouard 5656: }
1.339 brouard 5657: /* for products of time varying to be done */
1.234 brouard 5658: for (ii=1;ii<=nlstate+ndeath;ii++)
5659: for (j=1;j<=nlstate+ndeath;j++){
5660: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
5661: savm[ii][j]=(ii==j ? 1.0 : 0.0);
5662: }
1.336 brouard 5663:
5664: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
5665: 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 5666: for(d=0; d<dh[mi][i]; d++){
5667: newm=savm;
5668: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
5669: cov[2]=agexact;
5670: if(nagesqr==1)
5671: cov[3]= agexact*agexact; /* Should be changed here */
1.349 brouard 5672: /* for (kk=1; kk<=cptcovage;kk++) { */
5673: /* if(!FixedV[Tvar[Tage[kk]]]) */
5674: /* cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /\* Tage[kk] gives the data-covariate associated with age *\/ */
5675: /* else */
5676: /* 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) *\/ */
5677: /* } */
5678: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
5679: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
5680: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
5681: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
5682: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
5683: }else{ /* fixed covariate */
5684: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
5685: }
5686: if(ipos!=iposold){ /* Not a product or first of a product */
5687: cotvarvold=cotvarv;
5688: }else{ /* A second product */
5689: cotvarv=cotvarv*cotvarvold;
5690: }
5691: iposold=ipos;
5692: cov[ioffset+ipos]=cotvarv*agexact;
5693: /* For products */
1.234 brouard 5694: }
1.349 brouard 5695:
1.234 brouard 5696: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
5697: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
5698: savm=oldm;
5699: oldm=newm;
5700: } /* end mult */
5701:
5702: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
5703: /* But now since version 0.9 we anticipate for bias at large stepm.
5704: * If stepm is larger than one month (smallest stepm) and if the exact delay
5705: * (in months) between two waves is not a multiple of stepm, we rounded to
5706: * the nearest (and in case of equal distance, to the lowest) interval but now
5707: * we keep into memory the bias bh[mi][i] and also the previous matrix product
5708: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
5709: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 5710: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
5711: * -stepm/2 to stepm/2 .
5712: * For stepm=1 the results are the same as for previous versions of Imach.
5713: * For stepm > 1 the results are less biased than in previous versions.
5714: */
1.234 brouard 5715: s1=s[mw[mi][i]][i];
5716: s2=s[mw[mi+1][i]][i];
5717: bbh=(double)bh[mi][i]/(double)stepm;
5718: /* bias bh is positive if real duration
5719: * is higher than the multiple of stepm and negative otherwise.
5720: */
5721: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
5722: if( s2 > nlstate){
5723: /* i.e. if s2 is a death state and if the date of death is known
5724: then the contribution to the likelihood is the probability to
5725: die between last step unit time and current step unit time,
5726: which is also equal to probability to die before dh
5727: minus probability to die before dh-stepm .
5728: In version up to 0.92 likelihood was computed
5729: as if date of death was unknown. Death was treated as any other
5730: health state: the date of the interview describes the actual state
5731: and not the date of a change in health state. The former idea was
5732: to consider that at each interview the state was recorded
5733: (healthy, disable or death) and IMaCh was corrected; but when we
5734: introduced the exact date of death then we should have modified
5735: the contribution of an exact death to the likelihood. This new
5736: contribution is smaller and very dependent of the step unit
5737: stepm. It is no more the probability to die between last interview
5738: and month of death but the probability to survive from last
5739: interview up to one month before death multiplied by the
5740: probability to die within a month. Thanks to Chris
5741: Jackson for correcting this bug. Former versions increased
5742: mortality artificially. The bad side is that we add another loop
5743: which slows down the processing. The difference can be up to 10%
5744: lower mortality.
5745: */
5746: /* If, at the beginning of the maximization mostly, the
5747: cumulative probability or probability to be dead is
5748: constant (ie = 1) over time d, the difference is equal to
5749: 0. out[s1][3] = savm[s1][3]: probability, being at state
5750: s1 at precedent wave, to be dead a month before current
5751: wave is equal to probability, being at state s1 at
5752: precedent wave, to be dead at mont of the current
5753: wave. Then the observed probability (that this person died)
5754: is null according to current estimated parameter. In fact,
5755: it should be very low but not zero otherwise the log go to
5756: infinity.
5757: */
1.183 brouard 5758: /* #ifdef INFINITYORIGINAL */
5759: /* lli=log(out[s1][s2] - savm[s1][s2]); */
5760: /* #else */
5761: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
5762: /* lli=log(mytinydouble); */
5763: /* else */
5764: /* lli=log(out[s1][s2] - savm[s1][s2]); */
5765: /* #endif */
1.226 brouard 5766: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 5767:
1.226 brouard 5768: } else if ( s2==-1 ) { /* alive */
5769: for (j=1,survp=0. ; j<=nlstate; j++)
5770: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
5771: /*survp += out[s1][j]; */
5772: lli= log(survp);
5773: }
1.336 brouard 5774: /* else if (s2==-4) { */
5775: /* for (j=3,survp=0. ; j<=nlstate; j++) */
5776: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
5777: /* lli= log(survp); */
5778: /* } */
5779: /* else if (s2==-5) { */
5780: /* for (j=1,survp=0. ; j<=2; j++) */
5781: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
5782: /* lli= log(survp); */
5783: /* } */
1.226 brouard 5784: else{
5785: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
5786: /* 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 */
5787: }
5788: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
5789: /*if(lli ==000.0)*/
1.340 brouard 5790: /* 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 5791: ipmx +=1;
5792: sw += weight[i];
5793: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
5794: /* if (lli < log(mytinydouble)){ */
5795: /* 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); */
5796: /* 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]); */
5797: /* } */
5798: } /* end of wave */
5799: } /* end of individual */
5800: } else if(mle==2){
5801: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.319 brouard 5802: ioffset=2+nagesqr ;
5803: for (k=1; k<=ncovf;k++)
5804: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];
1.226 brouard 5805: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 5806: for(k=1; k <= ncovv ; k++){
1.341 brouard 5807: 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 5808: }
1.226 brouard 5809: for (ii=1;ii<=nlstate+ndeath;ii++)
5810: for (j=1;j<=nlstate+ndeath;j++){
5811: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
5812: savm[ii][j]=(ii==j ? 1.0 : 0.0);
5813: }
5814: for(d=0; d<=dh[mi][i]; d++){
5815: newm=savm;
5816: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
5817: cov[2]=agexact;
5818: if(nagesqr==1)
5819: cov[3]= agexact*agexact;
5820: for (kk=1; kk<=cptcovage;kk++) {
5821: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
5822: }
5823: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
5824: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
5825: savm=oldm;
5826: oldm=newm;
5827: } /* end mult */
5828:
5829: s1=s[mw[mi][i]][i];
5830: s2=s[mw[mi+1][i]][i];
5831: bbh=(double)bh[mi][i]/(double)stepm;
5832: 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 */
5833: ipmx +=1;
5834: sw += weight[i];
5835: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
5836: } /* end of wave */
5837: } /* end of individual */
5838: } else if(mle==3){ /* exponential inter-extrapolation */
5839: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
5840: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
5841: for(mi=1; mi<= wav[i]-1; mi++){
5842: for (ii=1;ii<=nlstate+ndeath;ii++)
5843: for (j=1;j<=nlstate+ndeath;j++){
5844: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
5845: savm[ii][j]=(ii==j ? 1.0 : 0.0);
5846: }
5847: for(d=0; d<dh[mi][i]; d++){
5848: newm=savm;
5849: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
5850: cov[2]=agexact;
5851: if(nagesqr==1)
5852: cov[3]= agexact*agexact;
5853: for (kk=1; kk<=cptcovage;kk++) {
1.340 brouard 5854: if(!FixedV[Tvar[Tage[kk]]])
5855: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
5856: else
1.341 brouard 5857: 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 5858: }
5859: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
5860: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
5861: savm=oldm;
5862: oldm=newm;
5863: } /* end mult */
5864:
5865: s1=s[mw[mi][i]][i];
5866: s2=s[mw[mi+1][i]][i];
5867: bbh=(double)bh[mi][i]/(double)stepm;
5868: 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 */
5869: ipmx +=1;
5870: sw += weight[i];
5871: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
5872: } /* end of wave */
5873: } /* end of individual */
5874: }else if (mle==4){ /* ml=4 no inter-extrapolation */
5875: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
5876: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
5877: for(mi=1; mi<= wav[i]-1; mi++){
5878: for (ii=1;ii<=nlstate+ndeath;ii++)
5879: for (j=1;j<=nlstate+ndeath;j++){
5880: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
5881: savm[ii][j]=(ii==j ? 1.0 : 0.0);
5882: }
5883: for(d=0; d<dh[mi][i]; d++){
5884: newm=savm;
5885: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
5886: cov[2]=agexact;
5887: if(nagesqr==1)
5888: cov[3]= agexact*agexact;
5889: for (kk=1; kk<=cptcovage;kk++) {
5890: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
5891: }
1.126 brouard 5892:
1.226 brouard 5893: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
5894: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
5895: savm=oldm;
5896: oldm=newm;
5897: } /* end mult */
5898:
5899: s1=s[mw[mi][i]][i];
5900: s2=s[mw[mi+1][i]][i];
5901: if( s2 > nlstate){
5902: lli=log(out[s1][s2] - savm[s1][s2]);
5903: } else if ( s2==-1 ) { /* alive */
5904: for (j=1,survp=0. ; j<=nlstate; j++)
5905: survp += out[s1][j];
5906: lli= log(survp);
5907: }else{
5908: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
5909: }
5910: ipmx +=1;
5911: sw += weight[i];
5912: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.343 brouard 5913: /* 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 5914: } /* end of wave */
5915: } /* end of individual */
5916: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
5917: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
5918: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
5919: for(mi=1; mi<= wav[i]-1; mi++){
5920: for (ii=1;ii<=nlstate+ndeath;ii++)
5921: for (j=1;j<=nlstate+ndeath;j++){
5922: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
5923: savm[ii][j]=(ii==j ? 1.0 : 0.0);
5924: }
5925: for(d=0; d<dh[mi][i]; d++){
5926: newm=savm;
5927: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
5928: cov[2]=agexact;
5929: if(nagesqr==1)
5930: cov[3]= agexact*agexact;
5931: for (kk=1; kk<=cptcovage;kk++) {
1.340 brouard 5932: if(!FixedV[Tvar[Tage[kk]]])
5933: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
5934: else
1.341 brouard 5935: 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 5936: }
1.126 brouard 5937:
1.226 brouard 5938: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
5939: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
5940: savm=oldm;
5941: oldm=newm;
5942: } /* end mult */
5943:
5944: s1=s[mw[mi][i]][i];
5945: s2=s[mw[mi+1][i]][i];
5946: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
5947: ipmx +=1;
5948: sw += weight[i];
5949: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
5950: /*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]);*/
5951: } /* end of wave */
5952: } /* end of individual */
5953: } /* End of if */
5954: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
5955: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
5956: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
5957: return -l;
1.126 brouard 5958: }
5959:
5960: /*************** log-likelihood *************/
5961: double funcone( double *x)
5962: {
1.228 brouard 5963: /* Same as func but slower because of a lot of printf and if */
1.359 brouard 5964: int i, ii, j, k, mi, d, kv=0, kf=0;
1.228 brouard 5965: int ioffset=0;
1.339 brouard 5966: int ipos=0,iposold=0,ncovv=0;
5967:
1.340 brouard 5968: double cotvarv, cotvarvold;
1.131 brouard 5969: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 5970: double **out;
5971: double lli; /* Individual log likelihood */
5972: double llt;
5973: int s1, s2;
1.228 brouard 5974: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
5975:
1.126 brouard 5976: double bbh, survp;
1.187 brouard 5977: double agexact;
1.214 brouard 5978: double agebegin, ageend;
1.126 brouard 5979: /*extern weight */
5980: /* We are differentiating ll according to initial status */
5981: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
5982: /*for(i=1;i<imx;i++)
5983: printf(" %d\n",s[4][i]);
5984: */
5985: cov[1]=1.;
5986:
5987: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 5988: ioffset=0;
5989: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.336 brouard 5990: /* Computes the values of the ncovmodel covariates of the model
5991: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
5992: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
5993: to be observed in j being in i according to the model.
5994: */
1.243 brouard 5995: /* ioffset=2+nagesqr+cptcovage; */
5996: ioffset=2+nagesqr;
1.232 brouard 5997: /* Fixed */
1.224 brouard 5998: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 5999: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
1.349 brouard 6000: 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 6001: /* printf("Debug3 TvarFind[%d]=%d",kf, TvarFind[kf]); */
6002: /* printf(" Tvar[TvarFind[kf]]=%d", Tvar[TvarFind[kf]]); */
6003: /* printf(" i=%d covar[Tvar[TvarFind[kf]]][i]=%f\n",i,covar[Tvar[TvarFind[kf]]][i]); */
1.335 brouard 6004: 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 6005: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
6006: /* cov[2+6]=covar[Tvar[6]][i]; */
6007: /* cov[2+6]=covar[2][i]; V2 */
6008: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
6009: /* cov[2+7]=covar[Tvar[7]][i]; */
6010: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
6011: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
6012: /* cov[2+9]=covar[Tvar[9]][i]; */
6013: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 6014: }
1.336 brouard 6015: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
6016: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
6017: has been calculated etc */
6018: /* For an individual i, wav[i] gives the number of effective waves */
6019: /* We compute the contribution to Likelihood of each effective transition
6020: mw[mi][i] is real wave of the mi th effectve wave */
6021: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
6022: s2=s[mw[mi+1][i]][i];
1.341 brouard 6023: And the iv th varying covariate in the DATA is the cotvar[mw[mi+1][i]][ncovcol+nqv+iv][i]
1.336 brouard 6024: */
6025: /* This part may be useless now because everythin should be in covar */
1.232 brouard 6026: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
6027: /* 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?)*\/ */
6028: /* } */
1.231 brouard 6029: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
6030: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
6031: /* } */
1.225 brouard 6032:
1.233 brouard 6033:
6034: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.339 brouard 6035: /* 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 */
6036: /* for(k=1; k <= ncovv ; k++){ /\* Varying covariates (single and product but no age )*\/ */
6037: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; *\/ */
6038: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
6039: /* } */
6040:
6041: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
6042: /* model V1+V3+age*V1+age*V3+V1*V3 */
6043: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
6044: /* TvarVV[1]=V3 (first time varying in the model equation, TvarVV[2]=V1 (in V1*V3) TvarVV[3]=3(V3) */
6045: /* We need the position of the time varying or product in the model */
6046: /* 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 */
6047: /* TvarVV gives the variable name */
1.340 brouard 6048: /* Other example V1 + V3 + V5 + age*V1 + age*V3 + age*V5 + V1*V3 + V3*V5 + V1*V5
6049: * k= 1 2 3 4 5 6 7 8 9
6050: * varying 1 2 3 4 5
6051: * ncovv 1 2 3 4 5 6 7 8
1.343 brouard 6052: * TvarVV[ncovv] V3 5 1 3 3 5 1 5
1.340 brouard 6053: * TvarVVind 2 3 7 7 8 8 9 9
6054: * TvarFind[k] 1 0 0 0 0 0 0 0 0
6055: */
1.345 brouard 6056: /* Other model ncovcol=5 nqv=0 ntv=3 nqtv=0 nlstate=3
1.349 brouard 6057: * 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 6058: * FixedV[ncovcol+qv+ntv+nqtv] V5
1.349 brouard 6059: * 3 V1 V2 V3 V4 V5 V6 V7 V8 V3*V2 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
6060: * 0 0 0 0 0 1 1 1 0, 0, 1,1, 1, 0, 1, 0, 1, 0, 1, 0}
6061: * 3 0 0 0 0 0 1 1 1 0, 1 1 1 1 1}
6062: * model= V2 + V3 + V4 + V6 + V7 + V6*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
6063: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
6064: * +age*V6*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
6065: * model2= V2 + V3 + V4 + V6 + V7 + V3*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
6066: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
6067: * +age*V3*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
6068: * model3= V2 + V3 + V4 + V6 + V7 + age*V3*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
6069: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
6070: * +V3*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
6071: * kmodel 1 2 3 4 5 6 7 8 9 10 11
6072: * 12 13 14 15 16
6073: * 17 18 19 20 21
6074: * Tvar[kmodel] 2 3 4 6 7 9 10 11 12 13 14
6075: * 2 3 4 6 7
6076: * 9 11 12 13 14
6077: * cptcovage=5+5 total of covariates with age
6078: * Tage[cptcovage] age*V2=12 13 14 15 16
6079: *1 17 18 19 20 21 gives the position in model of covariates associated with age
6080: *3 Tage[cptcovage] age*V3*V2=6
6081: *3 age*V2=12 13 14 15 16
6082: *3 age*V6*V3=18 19 20 21
6083: * Tvar[Tage[cptcovage]] Tvar[12]=2 3 4 6 Tvar[16]=7(age*V7)
6084: * 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
6085: * 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
6086: * 3 Tvar[Tage[cptcovage]] Tvar[6]=9 Tvar[12]=2 3 4 6 Tvar[16]=7(age*V7)
6087: * 3 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14
6088: * 3 Tage[cptcovage] age*V3*V2=6 age*V2=12 age*V3 13 14 15 16
6089: * age*V6*V3=18 19 20 21 gives the position in model of covariates associated with age
6090: * 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
6091: * Tvar= {2, 3, 4, 6, 7,
6092: * 9, 10, 11, 12, 13, 14,
6093: * Tvar[12]=2, 3, 4, 6, 7,
6094: * Tvar[17]=9, 11, 12, 13, 14}
6095: * Typevar[1]@21 = {0, 0, 0, 0, 0,
6096: * 2, 2, 2, 2, 2, 2,
6097: * 3 3, 2, 2, 2, 2, 2,
6098: * 1, 1, 1, 1, 1,
6099: * 3, 3, 3, 3, 3}
6100: * 3 2, 3, 3, 3, 3}
6101: * 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
6102: * p Tprod[1]@21 {6, 7, 8, 9, 10, 11, 0 <repeats 15 times>}
6103: * 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}
6104: * 3 Tprod[1]@21 {17, 7, 8, 9, 10, 11, 0 <repeats 15 times>}
6105: * cptcovprod=11 (6+5)
6106: * FixedV[Tvar[Tage[cptcovage]]]] FixedV[2]=0 FixedV[3]=0 0 1 (age*V7)Tvar[16]=1 FixedV[absolute] not [kmodel]
6107: * FixedV[Tvar[17]=FixedV[age*V6*V2]=FixedV[9]=1 1 1 1 1
6108: * 3 FixedV[Tvar[17]=FixedV[age*V3*V2]=FixedV[9]=0 [11]=1 1 1 1
6109: * FixedV[] V1=0 V2=0 V3=0 v4=0 V5=0 V6=1 V7=1 v8=1 OK then model dependent
6110: * 9=1 [V7*V2]=[10]=1 11=1 12=1 13=1 14=1
6111: * 3 9=0 [V7*V2]=[10]=1 11=1 12=1 13=1 14=1
6112: * cptcovdageprod=5 for gnuplot printing
6113: * cptcovprodvage=6
6114: * ncova=15 1 2 3 4 5
6115: * 6 7 8 9 10 11 12 13 14 15
6116: * TvarA 2 3 4 6 7
6117: * 6 2 6 7 7 3 6 4 7 4
6118: * TvaAind 12 12 13 13 14 14 15 15 16 16
1.345 brouard 6119: * ncovf 1 2 3
1.349 brouard 6120: * V6 V7 V6*V2 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
6121: * ncovvt=14 1 2 3 4 5 6 7 8 9 10 11 12 13 14
6122: * TvarVV[1]@14 = itv {V6=6, 7, V6*V2=6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
6123: * TvarVVind[1]@14= {4, 5, 6, 6, 7, 7, 8, 8, 9, 9, 10, 10, 11, 11}
6124: * 3 ncovvt=12 V6 V7 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
6125: * 3 TvarVV[1]@12 = itv {6, 7, V7*V2=7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
6126: * 3 1 2 3 4 5 6 7 8 9 10 11 12
6127: * TvarVVind[1]@12= {V6 is in k=4, 5, 7,(4isV2)=7, 8, 8, 9, 9, 10,10, 11,11}TvarVVind[12]=k=11
6128: * TvarV 6, 7, 9, 10, 11, 12, 13, 14
6129: * 3 cptcovprodvage=6
6130: * 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
6131: * 3 TvarAVVA[1]@15= itva 3 2 2 3 4 6 7 6 3 7 3 6 4 7 4
6132: * 3 ncovta 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
1.354 brouard 6133: *?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 6134: * TvarAVVAind[1]@15= V3 is in k=6 6 12 13 14 15 16 18 18 19,19, 20,20 21,21}TvarVVAind[]
6135: * 3 ncovvta=10 +age*V6 + age*V7 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
6136: * 3 we want to compute =cotvar[mw[mi][i]][TvarVVA[ncovva]][i] at position TvarVVAind[ncovva]
6137: * 3 TvarVVA[1]@10= itva 6 7 6 3 7 3 6 4 7 4
6138: * 3 ncovva 1 2 3 4 5 6 7 8 9 10
6139: * TvarVVAind[1]@10= V6 is in k=4 5 8,8 9, 9, 10,10 11 11}TvarVVAind[]
6140: * TvarVVAind[1]@10= 15 16 18,18 19,19, 20,20 21 21}TvarVVAind[]
6141: * TvarVA V3*V2=6 6 , 1, 2, 11, 12, 13, 14
1.345 brouard 6142: * TvarFind[1]@14= {1, 2, 3, 0 <repeats 12 times>}
1.349 brouard 6143: * Tvar[1]@21= {2, 3, 4, 6, 7, 9, 10, 11, 12, 13, 14,
6144: * 2, 3, 4, 6, 7,
6145: * 6, 8, 9, 10, 11}
1.345 brouard 6146: * TvarFind[itv] 0 0 0
6147: * FixedV[itv] 1 1 1 0 1 0 1 0 1 0 0
1.354 brouard 6148: *? FixedV[itv] 1 1 1 0 1 0 1 0 1 0 1 0 1 0
1.345 brouard 6149: * Tvar[TvarFind[ncovf]]=[1]=2 [2]=3 [4]=4
6150: * Tvar[TvarFind[itv]] [0]=? ?ncovv 1 à ncovvt]
6151: * Not a fixed cotvar[mw][itv][i] 6 7 6 2 7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
1.349 brouard 6152: * fixed covar[itv] [6] [7] [6][2]
1.345 brouard 6153: */
6154:
1.349 brouard 6155: 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 */
6156: 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 6157: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
1.345 brouard 6158: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
6159: 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 6160: /* printf("DEBUG ncovv=%d, Varying TvarVV[ncovv]=%d\n",ncovv, TvarVV[ncovv]); */
1.345 brouard 6161: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
1.354 brouard 6162: /* printf("DEBUG Varying cov[ioffset+ipos=%d]=%g \n",ioffset+ipos,cotvarv); */
1.340 brouard 6163: }else{ /* fixed covariate */
1.345 brouard 6164: /* 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 6165: /* printf("DEBUG ncovv=%d, Fixed TvarVV[ncovv]=%d\n",ncovv, TvarVV[ncovv]); */
1.349 brouard 6166: cotvarv=covar[itv][i]; /* Good: In V6*V3, 3 is fixed at position of the data */
1.354 brouard 6167: /* printf("DEBUG Fixed cov[ioffset+ipos=%d]=%g \n",ioffset+ipos,cotvarv); */
1.340 brouard 6168: }
1.339 brouard 6169: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 brouard 6170: cotvarvold=cotvarv;
6171: }else{ /* A second product */
6172: cotvarv=cotvarv*cotvarvold;
1.339 brouard 6173: }
6174: iposold=ipos;
1.340 brouard 6175: cov[ioffset+ipos]=cotvarv;
1.354 brouard 6176: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
1.339 brouard 6177: /* For products */
6178: }
6179: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates single *\/ */
6180: /* iv=TvarVDind[itv]; /\* iv, position in the model equation of time varying covariate itv *\/ */
6181: /* /\* "V1+V3+age*V1+age*V3+V1*V3" with V3 time varying *\/ */
6182: /* /\* 1 2 3 4 5 *\/ */
6183: /* /\*itv 1 *\/ */
6184: /* /\* TvarVInd[1]= 2 *\/ */
6185: /* /\* iv= Tvar[Tmodelind[itv]]-ncovcol-nqv; /\\* Counting the # varying covariate from 1 to ntveff *\\/ *\/ */
6186: /* /\* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; *\/ */
6187: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; *\/ */
6188: /* /\* k=ioffset-2-nagesqr-cptcovage+itv; /\\* position in simple model *\\/ *\/ */
6189: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; *\/ */
6190: /* cov[ioffset+iv]=cotvar[mw[mi][i]][itv][i]; */
6191: /* /\* 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]); *\/ */
6192: /* } */
1.232 brouard 6193: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 6194: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
6195: /* /\* 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]); *\/ */
6196: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 6197: /* } */
1.126 brouard 6198: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 6199: for (j=1;j<=nlstate+ndeath;j++){
6200: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
6201: savm[ii][j]=(ii==j ? 1.0 : 0.0);
6202: }
1.214 brouard 6203:
6204: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
6205: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
6206: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 6207: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 6208: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
6209: and mw[mi+1][i]. dh depends on stepm.*/
6210: newm=savm;
1.247 brouard 6211: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 6212: cov[2]=agexact;
6213: if(nagesqr==1)
6214: cov[3]= agexact*agexact;
1.349 brouard 6215: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
6216: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
6217: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
6218: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
6219: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
6220: /* printf("DEBUG ncovva=%d, Varying TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
6221: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
6222: }else{ /* fixed covariate */
6223: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
6224: /* printf("DEBUG ncovva=%d, Fixed TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
6225: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
6226: }
6227: if(ipos!=iposold){ /* Not a product or first of a product */
6228: cotvarvold=cotvarv;
6229: }else{ /* A second product */
6230: /* printf("DEBUG * \n"); */
6231: cotvarv=cotvarv*cotvarvold;
6232: }
6233: iposold=ipos;
6234: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
6235: cov[ioffset+ipos]=cotvarv*agexact;
6236: /* For products */
1.242 brouard 6237: }
1.349 brouard 6238:
1.242 brouard 6239: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
6240: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
6241: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
6242: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
6243: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
6244: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
6245: savm=oldm;
6246: oldm=newm;
1.126 brouard 6247: } /* end mult */
1.336 brouard 6248: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
6249: /* But now since version 0.9 we anticipate for bias at large stepm.
6250: * If stepm is larger than one month (smallest stepm) and if the exact delay
6251: * (in months) between two waves is not a multiple of stepm, we rounded to
6252: * the nearest (and in case of equal distance, to the lowest) interval but now
6253: * we keep into memory the bias bh[mi][i] and also the previous matrix product
6254: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
6255: * probability in order to take into account the bias as a fraction of the way
6256: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
6257: * -stepm/2 to stepm/2 .
6258: * For stepm=1 the results are the same as for previous versions of Imach.
6259: * For stepm > 1 the results are less biased than in previous versions.
6260: */
1.126 brouard 6261: s1=s[mw[mi][i]][i];
6262: s2=s[mw[mi+1][i]][i];
1.217 brouard 6263: /* if(s2==-1){ */
1.268 brouard 6264: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 6265: /* /\* exit(1); *\/ */
6266: /* } */
1.126 brouard 6267: bbh=(double)bh[mi][i]/(double)stepm;
6268: /* bias is positive if real duration
6269: * is higher than the multiple of stepm and negative otherwise.
6270: */
6271: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 6272: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 6273: } else if ( s2==-1 ) { /* alive */
1.242 brouard 6274: for (j=1,survp=0. ; j<=nlstate; j++)
6275: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
6276: lli= log(survp);
1.126 brouard 6277: }else if (mle==1){
1.242 brouard 6278: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 6279: } else if(mle==2){
1.242 brouard 6280: 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 6281: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 6282: 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 6283: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 6284: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 6285: } else{ /* mle=0 back to 1 */
1.242 brouard 6286: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
6287: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 6288: } /* End of if */
6289: ipmx +=1;
6290: sw += weight[i];
6291: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.342 brouard 6292: /* Printing covariates values for each contribution for checking */
1.343 brouard 6293: /* 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 6294: if(globpr){
1.246 brouard 6295: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 6296: %11.6f %11.6f %11.6f ", \
1.242 brouard 6297: 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 6298: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.343 brouard 6299: /* printf("%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\ */
6300: /* %11.6f %11.6f %11.6f ", \ */
6301: /* num[i], agebegin, ageend, i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],weight[i]*gipmx/gsw, */
6302: /* 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2])); */
1.242 brouard 6303: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
6304: llt +=ll[k]*gipmx/gsw;
6305: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
1.335 brouard 6306: /* printf(" %10.6f",-ll[k]*gipmx/gsw); */
1.242 brouard 6307: }
1.343 brouard 6308: fprintf(ficresilk," %10.6f ", -llt);
1.335 brouard 6309: /* printf(" %10.6f\n", -llt); */
1.342 brouard 6310: /* if(debugILK){ /\* debugILK is set by a #d in a comment line *\/ */
1.343 brouard 6311: /* fprintf(ficresilk,"%09ld ", num[i]); */ /* not necessary */
6312: for (kf=1; kf<=ncovf;kf++){ /* Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */
6313: fprintf(ficresilk," %g",covar[Tvar[TvarFind[kf]]][i]);
6314: }
6315: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age) including individual from products */
6316: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
6317: if(ipos!=iposold){ /* Not a product or first of a product */
6318: fprintf(ficresilk," %g",cov[ioffset+ipos]);
6319: /* printf(" %g",cov[ioffset+ipos]); */
6320: }else{
6321: fprintf(ficresilk,"*");
6322: /* printf("*"); */
1.342 brouard 6323: }
1.343 brouard 6324: iposold=ipos;
6325: }
1.349 brouard 6326: /* for (kk=1; kk<=cptcovage;kk++) { */
6327: /* if(!FixedV[Tvar[Tage[kk]]]){ */
6328: /* fprintf(ficresilk," %g*age",covar[Tvar[Tage[kk]]][i]); */
6329: /* /\* printf(" %g*age",covar[Tvar[Tage[kk]]][i]); *\/ */
6330: /* }else{ */
6331: /* fprintf(ficresilk," %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */
6332: /* /\* printf(" %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/\\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\\/ *\/ */
6333: /* } */
6334: /* } */
6335: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
6336: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
6337: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
6338: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
6339: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
6340: /* printf("DEBUG ncovva=%d, Varying TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
6341: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
6342: }else{ /* fixed covariate */
6343: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
6344: /* printf("DEBUG ncovva=%d, Fixed TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
6345: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
6346: }
6347: if(ipos!=iposold){ /* Not a product or first of a product */
6348: cotvarvold=cotvarv;
6349: }else{ /* A second product */
6350: /* printf("DEBUG * \n"); */
6351: cotvarv=cotvarv*cotvarvold;
1.342 brouard 6352: }
1.349 brouard 6353: cotvarv=cotvarv*agexact;
6354: fprintf(ficresilk," %g*age",cotvarv);
6355: iposold=ipos;
6356: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
6357: cov[ioffset+ipos]=cotvarv;
6358: /* For products */
1.343 brouard 6359: }
6360: /* printf("\n"); */
1.342 brouard 6361: /* } /\* End debugILK *\/ */
6362: fprintf(ficresilk,"\n");
6363: } /* End if globpr */
1.335 brouard 6364: } /* end of wave */
6365: } /* end of individual */
6366: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
1.232 brouard 6367: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
1.335 brouard 6368: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
6369: if(globpr==0){ /* First time we count the contributions and weights */
6370: gipmx=ipmx;
6371: gsw=sw;
6372: }
1.343 brouard 6373: return -l;
1.126 brouard 6374: }
6375:
6376:
6377: /*************** function likelione ***********/
1.292 brouard 6378: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 6379: {
6380: /* This routine should help understanding what is done with
6381: the selection of individuals/waves and
6382: to check the exact contribution to the likelihood.
6383: Plotting could be done.
1.342 brouard 6384: */
6385: void pstamp(FILE *ficres);
1.343 brouard 6386: int k, kf, kk, kvar, ncovv, iposold, ipos;
1.126 brouard 6387:
6388: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 6389: strcpy(fileresilk,"ILK_");
1.202 brouard 6390: strcat(fileresilk,fileresu);
1.126 brouard 6391: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
6392: printf("Problem with resultfile: %s\n", fileresilk);
6393: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
6394: }
1.342 brouard 6395: pstamp(ficresilk);fprintf(ficresilk,"# model=1+age+%s\n",model);
1.214 brouard 6396: 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");
6397: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 6398: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
6399: for(k=1; k<=nlstate; k++)
6400: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
1.342 brouard 6401: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total) ");
6402:
6403: /* if(debugILK){ /\* debugILK is set by a #d in a comment line *\/ */
6404: for(kf=1;kf <= ncovf; kf++){
6405: fprintf(ficresilk,"V%d",Tvar[TvarFind[kf]]);
6406: /* printf("V%d",Tvar[TvarFind[kf]]); */
6407: }
6408: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){
1.343 brouard 6409: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
1.342 brouard 6410: if(ipos!=iposold){ /* Not a product or first of a product */
6411: /* printf(" %d",ipos); */
6412: fprintf(ficresilk," V%d",TvarVV[ncovv]);
6413: }else{
6414: /* printf("*"); */
6415: fprintf(ficresilk,"*");
1.343 brouard 6416: }
1.342 brouard 6417: iposold=ipos;
6418: }
6419: for (kk=1; kk<=cptcovage;kk++) {
6420: if(!FixedV[Tvar[Tage[kk]]]){
6421: /* printf(" %d*age(Fixed)",Tvar[Tage[kk]]); */
6422: fprintf(ficresilk," %d*age(Fixed)",Tvar[Tage[kk]]);
6423: }else{
6424: fprintf(ficresilk," %d*age(Varying)",Tvar[Tage[kk]]);/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
6425: /* printf(" %d*age(Varying)",Tvar[Tage[kk]]);/\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */
6426: }
6427: }
6428: /* } /\* End if debugILK *\/ */
6429: /* printf("\n"); */
6430: fprintf(ficresilk,"\n");
6431: } /* End glogpri */
1.126 brouard 6432:
1.292 brouard 6433: *fretone=(*func)(p);
1.126 brouard 6434: if(*globpri !=0){
6435: fclose(ficresilk);
1.205 brouard 6436: if (mle ==0)
6437: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
6438: else if(mle >=1)
6439: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
6440: 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 6441: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 6442:
1.207 brouard 6443: 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 6444: <img src=\"%s-ori.png\">\n",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 6445: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.343 brouard 6446: <img src=\"%s-dest.png\">\n",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
6447:
6448: for (k=1; k<= nlstate ; k++) {
6449: 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 \
6450: <img src=\"%s-p%dj.png\">\n",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
6451: for(kf=1; kf <= ncovf; kf++){ /* For each simple dummy covariate of the model */
1.350 brouard 6452: kvar=Tvar[TvarFind[kf]]; /* variable */
6453: 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]]);
6454: 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);
6455: fprintf(fichtm,"<img src=\"%s-p%dj-%d.png\">",subdirf2(optionfilefiname,"ILK_"),k,Tvar[TvarFind[kf]]);
1.343 brouard 6456: }
6457: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Loop on the time varying extended covariates (with extension of Vn*Vm */
6458: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
6459: kvar=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
6460: /* 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]); */
6461: if(ipos!=iposold){ /* Not a product or first of a product */
6462: /* fprintf(ficresilk," V%d",TvarVV[ncovv]); */
6463: /* printf(" DebugILK fichtm ipos=%d != iposold=%d\n", ipos, iposold); */
6464: 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) */
6465: 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> \
6466: <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);
6467: } /* End only for dummies time varying (single?) */
6468: }else{ /* Useless product */
6469: /* printf("*"); */
6470: /* fprintf(ficresilk,"*"); */
6471: }
6472: iposold=ipos;
6473: } /* For each time varying covariate */
6474: } /* End loop on states */
6475:
6476: /* if(debugILK){ */
6477: /* for(kf=1; kf <= ncovf; kf++){ /\* For each simple dummy covariate of the model *\/ */
6478: /* /\* kvar=Tvar[TvarFind[kf]]; *\/ /\* variable *\/ */
6479: /* for (k=1; k<= nlstate ; k++) { */
6480: /* 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> \ */
6481: /* <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]]); */
6482: /* } */
6483: /* } */
6484: /* for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /\* Loop on the time varying extended covariates (with extension of Vn*Vm *\/ */
6485: /* ipos=TvarVVind[ncovv]; /\* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate *\/ */
6486: /* kvar=TvarVV[ncovv]; /\* TvarVV={3, 1, 3} gives the name of each varying covariate *\/ */
6487: /* /\* 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]); *\/ */
6488: /* if(ipos!=iposold){ /\* Not a product or first of a product *\/ */
6489: /* /\* fprintf(ficresilk," V%d",TvarVV[ncovv]); *\/ */
6490: /* /\* printf(" DebugILK fichtm ipos=%d != iposold=%d\n", ipos, iposold); *\/ */
6491: /* 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) *\/ */
6492: /* for (k=1; k<= nlstate ; k++) { */
6493: /* 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> \ */
6494: /* <img src=\"%s-p%dj-%d.png\">",k,k,kvar,kvar,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,kvar); */
6495: /* } /\* End state *\/ */
6496: /* } /\* End only for dummies time varying (single?) *\/ */
6497: /* }else{ /\* Useless product *\/ */
6498: /* /\* printf("*"); *\/ */
6499: /* /\* fprintf(ficresilk,"*"); *\/ */
6500: /* } */
6501: /* iposold=ipos; */
6502: /* } /\* For each time varying covariate *\/ */
6503: /* }/\* End debugILK *\/ */
1.207 brouard 6504: fflush(fichtm);
1.343 brouard 6505: }/* End globpri */
1.126 brouard 6506: return;
6507: }
6508:
6509:
6510: /*********** Maximum Likelihood Estimation ***************/
6511:
6512: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
6513: {
1.359 brouard 6514: int i,j, jkk=0, iter=0;
1.126 brouard 6515: double **xi;
1.359 brouard 6516: /*double fret;*/
6517: /*double fretone;*/ /* Only one call to likelihood */
1.126 brouard 6518: /* char filerespow[FILENAMELENGTH];*/
1.354 brouard 6519:
1.359 brouard 6520: /*double * p1;*/ /* Shifted parameters from 0 instead of 1 */
1.162 brouard 6521: #ifdef NLOPT
6522: int creturn;
6523: nlopt_opt opt;
6524: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
6525: double *lb;
6526: double minf; /* the minimum objective value, upon return */
1.354 brouard 6527:
1.162 brouard 6528: myfunc_data dinst, *d = &dinst;
6529: #endif
6530:
6531:
1.126 brouard 6532: xi=matrix(1,npar,1,npar);
1.357 brouard 6533: for (i=1;i<=npar;i++) /* Starting with canonical directions j=1,n xi[i=1,n][j] */
1.126 brouard 6534: for (j=1;j<=npar;j++)
6535: xi[i][j]=(i==j ? 1.0 : 0.0);
1.359 brouard 6536: printf("Powell-prax\n"); fprintf(ficlog,"Powell-prax\n");
1.201 brouard 6537: strcpy(filerespow,"POW_");
1.126 brouard 6538: strcat(filerespow,fileres);
6539: if((ficrespow=fopen(filerespow,"w"))==NULL) {
6540: printf("Problem with resultfile: %s\n", filerespow);
6541: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
6542: }
6543: fprintf(ficrespow,"# Powell\n# iter -2*LL");
6544: for (i=1;i<=nlstate;i++)
6545: for(j=1;j<=nlstate+ndeath;j++)
6546: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
6547: fprintf(ficrespow,"\n");
1.162 brouard 6548: #ifdef POWELL
1.319 brouard 6549: #ifdef LINMINORIGINAL
6550: #else /* LINMINORIGINAL */
6551:
6552: flatdir=ivector(1,npar);
6553: for (j=1;j<=npar;j++) flatdir[j]=0;
6554: #endif /*LINMINORIGINAL */
6555:
6556: #ifdef FLATSUP
6557: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
6558: /* reorganizing p by suppressing flat directions */
6559: for(i=1, jk=1; i <=nlstate; i++){
6560: for(k=1; k <=(nlstate+ndeath); k++){
6561: if (k != i) {
6562: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
6563: if(flatdir[jk]==1){
6564: printf(" To be skipped %d%d flatdir[%d]=%d ",i,k,jk, flatdir[jk]);
6565: }
6566: for(j=1; j <=ncovmodel; j++){
6567: printf("%12.7f ",p[jk]);
6568: jk++;
6569: }
6570: printf("\n");
6571: }
6572: }
6573: }
6574: /* skipping */
6575: /* for(i=1, jk=1, jkk=1;(flatdir[jk]==0)&& (i <=nlstate); i++){ */
6576: for(i=1, jk=1, jkk=1;i <=nlstate; i++){
6577: for(k=1; k <=(nlstate+ndeath); k++){
6578: if (k != i) {
6579: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
6580: if(flatdir[jk]==1){
6581: printf(" To be skipped %d%d flatdir[%d]=%d jk=%d p[%d] ",i,k,jk, flatdir[jk],jk, jk);
6582: for(j=1; j <=ncovmodel; jk++,j++){
6583: printf(" p[%d]=%12.7f",jk, p[jk]);
6584: /*q[jjk]=p[jk];*/
6585: }
6586: }else{
6587: printf(" To be kept %d%d flatdir[%d]=%d jk=%d q[%d]=p[%d] ",i,k,jk, flatdir[jk],jk, jkk, jk);
6588: for(j=1; j <=ncovmodel; jk++,jkk++,j++){
6589: printf(" p[%d]=%12.7f=q[%d]",jk, p[jk],jkk);
6590: /*q[jjk]=p[jk];*/
6591: }
6592: }
6593: printf("\n");
6594: }
6595: fflush(stdout);
6596: }
6597: }
6598: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
6599: #else /* FLATSUP */
1.359 brouard 6600: /* powell(p,xi,npar,ftol,&iter,&fret,func);*/
6601: /* praxis ( t0, h0, n, prin, x, beale_f ); */
1.362 ! brouard 6602: /* int prin=1; */
! 6603: /* double h0=0.25; */
! 6604: /* double macheps; */
! 6605: /* double fmin; */
1.359 brouard 6606: macheps=pow(16.0,-13.0);
6607: /* #include "praxis.h" */
6608: /* Be careful that praxis start at x[0] and powell start at p[1] */
6609: /* praxis ( ftol, h0, npar, prin, p, func ); */
6610: /* p1= (p+1); */ /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
6611: printf("Praxis Gegenfurtner \n");
6612: fprintf(ficlog, "Praxis Gegenfurtner\n");fflush(ficlog);
6613: /* praxis ( ftol, h0, npar, prin, p1, func ); */
6614: /* fmin = praxis(1.e-5,macheps, h, n, prin, x, func); */
1.362 ! brouard 6615: ffmin = praxis(ftol,macheps, h0, npar, prin, p, func);
1.359 brouard 6616: printf("End Praxis\n");
1.319 brouard 6617: #endif /* FLATSUP */
6618:
6619: #ifdef LINMINORIGINAL
6620: #else
6621: free_ivector(flatdir,1,npar);
6622: #endif /* LINMINORIGINAL*/
6623: #endif /* POWELL */
1.126 brouard 6624:
1.162 brouard 6625: #ifdef NLOPT
6626: #ifdef NEWUOA
6627: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
6628: #else
6629: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
6630: #endif
6631: lb=vector(0,npar-1);
6632: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
6633: nlopt_set_lower_bounds(opt, lb);
6634: nlopt_set_initial_step1(opt, 0.1);
6635:
6636: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
6637: d->function = func;
6638: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
6639: nlopt_set_min_objective(opt, myfunc, d);
6640: nlopt_set_xtol_rel(opt, ftol);
6641: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
6642: printf("nlopt failed! %d\n",creturn);
6643: }
6644: else {
6645: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
6646: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
6647: iter=1; /* not equal */
6648: }
6649: nlopt_destroy(opt);
6650: #endif
1.319 brouard 6651: #ifdef FLATSUP
6652: /* npared = npar -flatd/ncovmodel; */
6653: /* xired= matrix(1,npared,1,npared); */
6654: /* paramred= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); */
6655: /* powell(pred,xired,npared,ftol,&iter,&fret,flatdir,func); */
6656: /* free_matrix(xire,1,npared,1,npared); */
6657: #else /* FLATSUP */
6658: #endif /* FLATSUP */
1.126 brouard 6659: free_matrix(xi,1,npar,1,npar);
6660: fclose(ficrespow);
1.203 brouard 6661: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
6662: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 6663: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 6664:
6665: }
6666:
6667: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 6668: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 6669: {
6670: double **a,**y,*x,pd;
1.203 brouard 6671: /* double **hess; */
1.164 brouard 6672: int i, j;
1.126 brouard 6673: int *indx;
6674:
6675: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 6676: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 6677: void lubksb(double **a, int npar, int *indx, double b[]) ;
6678: void ludcmp(double **a, int npar, int *indx, double *d) ;
6679: double gompertz(double p[]);
1.203 brouard 6680: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 6681:
6682: printf("\nCalculation of the hessian matrix. Wait...\n");
6683: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
6684: for (i=1;i<=npar;i++){
1.203 brouard 6685: printf("%d-",i);fflush(stdout);
6686: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 6687:
6688: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
6689:
6690: /* printf(" %f ",p[i]);
6691: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
6692: }
6693:
6694: for (i=1;i<=npar;i++) {
6695: for (j=1;j<=npar;j++) {
6696: if (j>i) {
1.203 brouard 6697: printf(".%d-%d",i,j);fflush(stdout);
6698: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
6699: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 6700:
6701: hess[j][i]=hess[i][j];
6702: /*printf(" %lf ",hess[i][j]);*/
6703: }
6704: }
6705: }
6706: printf("\n");
6707: fprintf(ficlog,"\n");
6708:
6709: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
6710: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
6711:
6712: a=matrix(1,npar,1,npar);
6713: y=matrix(1,npar,1,npar);
6714: x=vector(1,npar);
6715: indx=ivector(1,npar);
6716: for (i=1;i<=npar;i++)
6717: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
6718: ludcmp(a,npar,indx,&pd);
6719:
6720: for (j=1;j<=npar;j++) {
6721: for (i=1;i<=npar;i++) x[i]=0;
6722: x[j]=1;
6723: lubksb(a,npar,indx,x);
6724: for (i=1;i<=npar;i++){
6725: matcov[i][j]=x[i];
6726: }
6727: }
6728:
6729: printf("\n#Hessian matrix#\n");
6730: fprintf(ficlog,"\n#Hessian matrix#\n");
6731: for (i=1;i<=npar;i++) {
6732: for (j=1;j<=npar;j++) {
1.203 brouard 6733: printf("%.6e ",hess[i][j]);
6734: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 6735: }
6736: printf("\n");
6737: fprintf(ficlog,"\n");
6738: }
6739:
1.203 brouard 6740: /* printf("\n#Covariance matrix#\n"); */
6741: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
6742: /* for (i=1;i<=npar;i++) { */
6743: /* for (j=1;j<=npar;j++) { */
6744: /* printf("%.6e ",matcov[i][j]); */
6745: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
6746: /* } */
6747: /* printf("\n"); */
6748: /* fprintf(ficlog,"\n"); */
6749: /* } */
6750:
1.126 brouard 6751: /* Recompute Inverse */
1.203 brouard 6752: /* for (i=1;i<=npar;i++) */
6753: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
6754: /* ludcmp(a,npar,indx,&pd); */
6755:
6756: /* printf("\n#Hessian matrix recomputed#\n"); */
6757:
6758: /* for (j=1;j<=npar;j++) { */
6759: /* for (i=1;i<=npar;i++) x[i]=0; */
6760: /* x[j]=1; */
6761: /* lubksb(a,npar,indx,x); */
6762: /* for (i=1;i<=npar;i++){ */
6763: /* y[i][j]=x[i]; */
6764: /* printf("%.3e ",y[i][j]); */
6765: /* fprintf(ficlog,"%.3e ",y[i][j]); */
6766: /* } */
6767: /* printf("\n"); */
6768: /* fprintf(ficlog,"\n"); */
6769: /* } */
6770:
6771: /* Verifying the inverse matrix */
6772: #ifdef DEBUGHESS
6773: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 6774:
1.203 brouard 6775: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
6776: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 6777:
6778: for (j=1;j<=npar;j++) {
6779: for (i=1;i<=npar;i++){
1.203 brouard 6780: printf("%.2f ",y[i][j]);
6781: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 6782: }
6783: printf("\n");
6784: fprintf(ficlog,"\n");
6785: }
1.203 brouard 6786: #endif
1.126 brouard 6787:
6788: free_matrix(a,1,npar,1,npar);
6789: free_matrix(y,1,npar,1,npar);
6790: free_vector(x,1,npar);
6791: free_ivector(indx,1,npar);
1.203 brouard 6792: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 6793:
6794:
6795: }
6796:
6797: /*************** hessian matrix ****************/
6798: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 6799: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 6800: int i;
6801: int l=1, lmax=20;
1.203 brouard 6802: double k1,k2, res, fx;
1.132 brouard 6803: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 6804: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
6805: int k=0,kmax=10;
6806: double l1;
6807:
6808: fx=func(x);
6809: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 6810: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 6811: l1=pow(10,l);
6812: delts=delt;
6813: for(k=1 ; k <kmax; k=k+1){
6814: delt = delta*(l1*k);
6815: p2[theta]=x[theta] +delt;
1.145 brouard 6816: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 6817: p2[theta]=x[theta]-delt;
6818: k2=func(p2)-fx;
6819: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 6820: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 6821:
1.203 brouard 6822: #ifdef DEBUGHESSII
1.126 brouard 6823: 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);
6824: 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);
6825: #endif
6826: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
6827: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
6828: k=kmax;
6829: }
6830: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 6831: k=kmax; l=lmax*10;
1.126 brouard 6832: }
6833: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
6834: delts=delt;
6835: }
1.203 brouard 6836: } /* End loop k */
1.126 brouard 6837: }
6838: delti[theta]=delts;
6839: return res;
6840:
6841: }
6842:
1.203 brouard 6843: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 6844: {
6845: int i;
1.164 brouard 6846: int l=1, lmax=20;
1.126 brouard 6847: double k1,k2,k3,k4,res,fx;
1.132 brouard 6848: double p2[MAXPARM+1];
1.203 brouard 6849: int k, kmax=1;
6850: double v1, v2, cv12, lc1, lc2;
1.208 brouard 6851:
6852: int firstime=0;
1.203 brouard 6853:
1.126 brouard 6854: fx=func(x);
1.203 brouard 6855: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 6856: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 6857: p2[thetai]=x[thetai]+delti[thetai]*k;
6858: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 6859: k1=func(p2)-fx;
6860:
1.203 brouard 6861: p2[thetai]=x[thetai]+delti[thetai]*k;
6862: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 6863: k2=func(p2)-fx;
6864:
1.203 brouard 6865: p2[thetai]=x[thetai]-delti[thetai]*k;
6866: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 6867: k3=func(p2)-fx;
6868:
1.203 brouard 6869: p2[thetai]=x[thetai]-delti[thetai]*k;
6870: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 6871: k4=func(p2)-fx;
1.203 brouard 6872: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
6873: if(k1*k2*k3*k4 <0.){
1.208 brouard 6874: firstime=1;
1.203 brouard 6875: kmax=kmax+10;
1.208 brouard 6876: }
6877: if(kmax >=10 || firstime ==1){
1.354 brouard 6878: /* What are the thetai and thetaj? thetai/ncovmodel thetai=(thetai-thetai%ncovmodel)/ncovmodel +thetai%ncovmodel=(line,pos) */
1.246 brouard 6879: 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);
6880: 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 6881: 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);
6882: 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);
6883: }
6884: #ifdef DEBUGHESSIJ
6885: v1=hess[thetai][thetai];
6886: v2=hess[thetaj][thetaj];
6887: cv12=res;
6888: /* Computing eigen value of Hessian matrix */
6889: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6890: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6891: if ((lc2 <0) || (lc1 <0) ){
6892: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
6893: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
6894: 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);
6895: 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);
6896: }
1.126 brouard 6897: #endif
6898: }
6899: return res;
6900: }
6901:
1.203 brouard 6902: /* Not done yet: Was supposed to fix if not exactly at the maximum */
6903: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
6904: /* { */
6905: /* int i; */
6906: /* int l=1, lmax=20; */
6907: /* double k1,k2,k3,k4,res,fx; */
6908: /* double p2[MAXPARM+1]; */
6909: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
6910: /* int k=0,kmax=10; */
6911: /* double l1; */
6912:
6913: /* fx=func(x); */
6914: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
6915: /* l1=pow(10,l); */
6916: /* delts=delt; */
6917: /* for(k=1 ; k <kmax; k=k+1){ */
6918: /* delt = delti*(l1*k); */
6919: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
6920: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
6921: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
6922: /* k1=func(p2)-fx; */
6923:
6924: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
6925: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
6926: /* k2=func(p2)-fx; */
6927:
6928: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
6929: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
6930: /* k3=func(p2)-fx; */
6931:
6932: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
6933: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
6934: /* k4=func(p2)-fx; */
6935: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
6936: /* #ifdef DEBUGHESSIJ */
6937: /* 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); */
6938: /* 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); */
6939: /* #endif */
6940: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
6941: /* k=kmax; */
6942: /* } */
6943: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
6944: /* k=kmax; l=lmax*10; */
6945: /* } */
6946: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
6947: /* delts=delt; */
6948: /* } */
6949: /* } /\* End loop k *\/ */
6950: /* } */
6951: /* delti[theta]=delts; */
6952: /* return res; */
6953: /* } */
6954:
6955:
1.126 brouard 6956: /************** Inverse of matrix **************/
6957: void ludcmp(double **a, int n, int *indx, double *d)
6958: {
6959: int i,imax,j,k;
6960: double big,dum,sum,temp;
6961: double *vv;
6962:
6963: vv=vector(1,n);
6964: *d=1.0;
6965: for (i=1;i<=n;i++) {
6966: big=0.0;
6967: for (j=1;j<=n;j++)
6968: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 6969: if (big == 0.0){
6970: printf(" Singular Hessian matrix at row %d:\n",i);
6971: for (j=1;j<=n;j++) {
6972: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
6973: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
6974: }
6975: fflush(ficlog);
6976: fclose(ficlog);
6977: nrerror("Singular matrix in routine ludcmp");
6978: }
1.126 brouard 6979: vv[i]=1.0/big;
6980: }
6981: for (j=1;j<=n;j++) {
6982: for (i=1;i<j;i++) {
6983: sum=a[i][j];
6984: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
6985: a[i][j]=sum;
6986: }
6987: big=0.0;
6988: for (i=j;i<=n;i++) {
6989: sum=a[i][j];
6990: for (k=1;k<j;k++)
6991: sum -= a[i][k]*a[k][j];
6992: a[i][j]=sum;
6993: if ( (dum=vv[i]*fabs(sum)) >= big) {
6994: big=dum;
6995: imax=i;
6996: }
6997: }
6998: if (j != imax) {
6999: for (k=1;k<=n;k++) {
7000: dum=a[imax][k];
7001: a[imax][k]=a[j][k];
7002: a[j][k]=dum;
7003: }
7004: *d = -(*d);
7005: vv[imax]=vv[j];
7006: }
7007: indx[j]=imax;
7008: if (a[j][j] == 0.0) a[j][j]=TINY;
7009: if (j != n) {
7010: dum=1.0/(a[j][j]);
7011: for (i=j+1;i<=n;i++) a[i][j] *= dum;
7012: }
7013: }
7014: free_vector(vv,1,n); /* Doesn't work */
7015: ;
7016: }
7017:
7018: void lubksb(double **a, int n, int *indx, double b[])
7019: {
7020: int i,ii=0,ip,j;
7021: double sum;
7022:
7023: for (i=1;i<=n;i++) {
7024: ip=indx[i];
7025: sum=b[ip];
7026: b[ip]=b[i];
7027: if (ii)
7028: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
7029: else if (sum) ii=i;
7030: b[i]=sum;
7031: }
7032: for (i=n;i>=1;i--) {
7033: sum=b[i];
7034: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
7035: b[i]=sum/a[i][i];
7036: }
7037: }
7038:
7039: void pstamp(FILE *fichier)
7040: {
1.196 brouard 7041: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 7042: }
7043:
1.297 brouard 7044: void date2dmy(double date,double *day, double *month, double *year){
7045: double yp=0., yp1=0., yp2=0.;
7046:
7047: yp1=modf(date,&yp);/* extracts integral of date in yp and
7048: fractional in yp1 */
7049: *year=yp;
7050: yp2=modf((yp1*12),&yp);
7051: *month=yp;
7052: yp1=modf((yp2*30.5),&yp);
7053: *day=yp;
7054: if(*day==0) *day=1;
7055: if(*month==0) *month=1;
7056: }
7057:
1.253 brouard 7058:
7059:
1.126 brouard 7060: /************ Frequencies ********************/
1.251 brouard 7061: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 7062: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
7063: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 7064: { /* Some frequencies as well as proposing some starting values */
1.332 brouard 7065: /* Frequencies of any combination of dummy covariate used in the model equation */
1.265 brouard 7066: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 7067: int iind=0, iage=0;
7068: int mi; /* Effective wave */
7069: int first;
7070: double ***freq; /* Frequencies */
1.268 brouard 7071: 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 */
7072: 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 7073: double *meanq, *stdq, *idq;
1.226 brouard 7074: double **meanqt;
7075: double *pp, **prop, *posprop, *pospropt;
7076: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
7077: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
7078: double agebegin, ageend;
7079:
7080: pp=vector(1,nlstate);
1.251 brouard 7081: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 7082: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
7083: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
7084: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
7085: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 7086: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 7087: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 7088: meanqt=matrix(1,lastpass,1,nqtveff);
7089: strcpy(fileresp,"P_");
7090: strcat(fileresp,fileresu);
7091: /*strcat(fileresphtm,fileresu);*/
7092: if((ficresp=fopen(fileresp,"w"))==NULL) {
7093: printf("Problem with prevalence resultfile: %s\n", fileresp);
7094: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
7095: exit(0);
7096: }
1.240 brouard 7097:
1.226 brouard 7098: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
7099: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
7100: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
7101: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
7102: fflush(ficlog);
7103: exit(70);
7104: }
7105: else{
7106: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 7107: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 7108: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 7109: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
7110: }
1.319 brouard 7111: 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 7112:
1.226 brouard 7113: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
7114: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
7115: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
7116: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
7117: fflush(ficlog);
7118: exit(70);
1.240 brouard 7119: } else{
1.226 brouard 7120: 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 7121: ,<hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 7122: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 7123: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
7124: }
1.319 brouard 7125: 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 7126:
1.253 brouard 7127: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
7128: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 7129: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 7130: j1=0;
1.126 brouard 7131:
1.227 brouard 7132: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
1.335 brouard 7133: j=cptcoveff; /* Only simple dummy covariates used in the model */
1.330 brouard 7134: /* j=cptcovn; /\* Only dummy covariates of the model *\/ */
1.226 brouard 7135: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 7136:
7137:
1.226 brouard 7138: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
7139: reference=low_education V1=0,V2=0
7140: med_educ V1=1 V2=0,
7141: high_educ V1=0 V2=1
1.330 brouard 7142: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcovn
1.226 brouard 7143: */
1.249 brouard 7144: dateintsum=0;
7145: k2cpt=0;
7146:
1.253 brouard 7147: if(cptcoveff == 0 )
1.265 brouard 7148: nl=1; /* Constant and age model only */
1.253 brouard 7149: else
7150: nl=2;
1.265 brouard 7151:
7152: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
7153: /* Loop on nj=1 or 2 if dummy covariates j!=0
1.335 brouard 7154: * Loop on j1(1 to 2**cptcoveff) covariate combination
1.265 brouard 7155: * freq[s1][s2][iage] =0.
7156: * Loop on iind
7157: * ++freq[s1][s2][iage] weighted
7158: * end iind
7159: * if covariate and j!0
7160: * headers Variable on one line
7161: * endif cov j!=0
7162: * header of frequency table by age
7163: * Loop on age
7164: * pp[s1]+=freq[s1][s2][iage] weighted
7165: * pos+=freq[s1][s2][iage] weighted
7166: * Loop on s1 initial state
7167: * fprintf(ficresp
7168: * end s1
7169: * end age
7170: * if j!=0 computes starting values
7171: * end compute starting values
7172: * end j1
7173: * end nl
7174: */
1.253 brouard 7175: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
7176: if(nj==1)
7177: j=0; /* First pass for the constant */
1.265 brouard 7178: else{
1.335 brouard 7179: 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 7180: }
1.251 brouard 7181: first=1;
1.332 brouard 7182: 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 7183: posproptt=0.;
1.330 brouard 7184: /*printf("cptcovn=%d Tvaraff=%d", cptcovn,Tvaraff[1]);
1.251 brouard 7185: scanf("%d", i);*/
7186: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 7187: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 7188: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 7189: freq[i][s2][m]=0;
1.251 brouard 7190:
7191: for (i=1; i<=nlstate; i++) {
1.240 brouard 7192: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 7193: prop[i][m]=0;
7194: posprop[i]=0;
7195: pospropt[i]=0;
7196: }
1.283 brouard 7197: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 7198: idq[z1]=0.;
7199: meanq[z1]=0.;
7200: stdq[z1]=0.;
1.283 brouard 7201: }
7202: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 7203: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 7204: /* meanqt[m][z1]=0.; */
7205: /* } */
7206: /* } */
1.251 brouard 7207: /* dateintsum=0; */
7208: /* k2cpt=0; */
7209:
1.265 brouard 7210: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 7211: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
7212: bool=1;
7213: if(j !=0){
7214: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
1.335 brouard 7215: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
7216: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
1.251 brouard 7217: /* if(Tvaraff[z1] ==-20){ */
7218: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
7219: /* }else if(Tvaraff[z1] ==-10){ */
7220: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
1.330 brouard 7221: /* }else */ /* TODO TODO codtabm(j1,z1) or codtabm(j1,Tvaraff[z1]]z1)*/
1.335 brouard 7222: /* 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); */
7223: if(Tvaraff[z1]<1 || Tvaraff[z1]>=NCOVMAX)
1.338 brouard 7224: printf("Error Tvaraff[z1]=%d<1 or >=%d, cptcoveff=%d model=1+age+%s\n",Tvaraff[z1],NCOVMAX, cptcoveff, model);
1.332 brouard 7225: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]){ /* for combination j1 of covariates */
1.265 brouard 7226: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 7227: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
1.332 brouard 7228: /* 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", */
7229: /* bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),*/
7230: /* j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
1.251 brouard 7231: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
7232: } /* Onlyf fixed */
7233: } /* end z1 */
1.335 brouard 7234: } /* cptcoveff > 0 */
1.251 brouard 7235: } /* end any */
7236: }/* end j==0 */
1.265 brouard 7237: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 7238: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 7239: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 7240: m=mw[mi][iind];
7241: if(j!=0){
7242: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
1.335 brouard 7243: for (z1=1; z1<=cptcoveff; z1++) {
1.251 brouard 7244: if( Fixed[Tmodelind[z1]]==1){
1.341 brouard 7245: /* iv= Tvar[Tmodelind[z1]]-ncovcol-nqv; /\* Good *\/ */
7246: iv= Tvar[Tmodelind[z1]]; /* Good *//* because cotvar starts now at first at ncovcol+nqv+ntv */
1.332 brouard 7247: 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 7248: value is -1, we don't select. It differs from the
7249: constant and age model which counts them. */
7250: bool=0; /* not selected */
7251: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
1.334 brouard 7252: /* i1=Tvaraff[z1]; */
7253: /* i2=TnsdVar[i1]; */
7254: /* i3=nbcode[i1][i2]; */
7255: /* i4=covar[i1][iind]; */
7256: /* if(i4 != i3){ */
7257: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) { /* Bug valgrind */
1.251 brouard 7258: bool=0;
7259: }
7260: }
7261: }
7262: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
7263: } /* end j==0 */
7264: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 7265: if(bool==1){ /*Selected */
1.251 brouard 7266: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
7267: and mw[mi+1][iind]. dh depends on stepm. */
7268: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
7269: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
7270: if(m >=firstpass && m <=lastpass){
7271: k2=anint[m][iind]+(mint[m][iind]/12.);
7272: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
7273: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
7274: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
7275: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
7276: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
7277: if (m<lastpass) {
7278: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
7279: /* 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]); */
7280: if(s[m][iind]==-1)
7281: 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.));
7282: 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 7283: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean on known values only */
7284: if(!isnan(covar[ncovcol+z1][iind])){
1.332 brouard 7285: idq[z1]=idq[z1]+weight[iind];
7286: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
7287: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; *//*error*/
7288: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
1.311 brouard 7289: }
1.284 brouard 7290: }
1.251 brouard 7291: /* if((int)agev[m][iind] == 55) */
7292: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
7293: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
7294: 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 7295: }
1.251 brouard 7296: } /* end if between passes */
7297: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
7298: dateintsum=dateintsum+k2; /* on all covariates ?*/
7299: k2cpt++;
7300: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 7301: }
1.251 brouard 7302: }else{
7303: bool=1;
7304: }/* end bool 2 */
7305: } /* end m */
1.284 brouard 7306: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
7307: /* idq[z1]=idq[z1]+weight[iind]; */
7308: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
7309: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
7310: /* } */
1.251 brouard 7311: } /* end bool */
7312: } /* end iind = 1 to imx */
1.319 brouard 7313: /* prop[s][age] is fed for any initial and valid live state as well as
1.251 brouard 7314: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
7315:
7316:
7317: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.335 brouard 7318: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
1.265 brouard 7319: pstamp(ficresp);
1.335 brouard 7320: if (cptcoveff>0 && j!=0){
1.265 brouard 7321: pstamp(ficresp);
1.251 brouard 7322: printf( "\n#********** Variable ");
7323: fprintf(ficresp, "\n#********** Variable ");
7324: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
7325: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
7326: fprintf(ficlog, "\n#********** Variable ");
1.340 brouard 7327: for (z1=1; z1<=cptcoveff; z1++){
1.251 brouard 7328: if(!FixedV[Tvaraff[z1]]){
1.330 brouard 7329: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7330: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7331: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7332: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7333: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.250 brouard 7334: }else{
1.330 brouard 7335: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7336: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7337: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7338: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7339: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.251 brouard 7340: }
7341: }
7342: printf( "**********\n#");
7343: fprintf(ficresp, "**********\n#");
7344: fprintf(ficresphtm, "**********</h3>\n");
7345: fprintf(ficresphtmfr, "**********</h3>\n");
7346: fprintf(ficlog, "**********\n");
7347: }
1.284 brouard 7348: /*
7349: Printing means of quantitative variables if any
7350: */
7351: for (z1=1; z1<= nqfveff; z1++) {
1.311 brouard 7352: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.3g (weighted) individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.312 brouard 7353: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
1.284 brouard 7354: if(weightopt==1){
7355: printf(" Weighted mean and standard deviation of");
7356: fprintf(ficlog," Weighted mean and standard deviation of");
7357: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
7358: }
1.311 brouard 7359: /* mu = \frac{w x}{\sum w}
7360: var = \frac{\sum w (x-mu)^2}{\sum w} = \frac{w x^2}{\sum w} - mu^2
7361: */
7362: 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]));
7363: 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]));
7364: 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 7365: }
7366: /* for (z1=1; z1<= nqtveff; z1++) { */
7367: /* for(m=1;m<=lastpass;m++){ */
7368: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
7369: /* } */
7370: /* } */
1.283 brouard 7371:
1.251 brouard 7372: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.335 brouard 7373: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
1.265 brouard 7374: fprintf(ficresp, " Age");
1.335 brouard 7375: if(nj==2) for (z1=1; z1<=cptcoveff; z1++) {
7376: 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]]);
7377: fprintf(ficresp, " V%d=%d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
7378: }
1.251 brouard 7379: for(i=1; i<=nlstate;i++) {
1.335 brouard 7380: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 7381: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
7382: }
1.335 brouard 7383: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 7384: fprintf(ficresphtm, "\n");
7385:
7386: /* Header of frequency table by age */
7387: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
7388: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 7389: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 7390: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 7391: if(s2!=0 && m!=0)
7392: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 7393: }
1.226 brouard 7394: }
1.251 brouard 7395: fprintf(ficresphtmfr, "\n");
7396:
7397: /* For each age */
7398: for(iage=iagemin; iage <= iagemax+3; iage++){
7399: fprintf(ficresphtm,"<tr>");
7400: if(iage==iagemax+1){
7401: fprintf(ficlog,"1");
7402: fprintf(ficresphtmfr,"<tr><th>0</th> ");
7403: }else if(iage==iagemax+2){
7404: fprintf(ficlog,"0");
7405: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
7406: }else if(iage==iagemax+3){
7407: fprintf(ficlog,"Total");
7408: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
7409: }else{
1.240 brouard 7410: if(first==1){
1.251 brouard 7411: first=0;
7412: printf("See log file for details...\n");
7413: }
7414: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
7415: fprintf(ficlog,"Age %d", iage);
7416: }
1.265 brouard 7417: for(s1=1; s1 <=nlstate ; s1++){
7418: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
7419: pp[s1] += freq[s1][m][iage];
1.251 brouard 7420: }
1.265 brouard 7421: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 7422: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 7423: pos += freq[s1][m][iage];
7424: if(pp[s1]>=1.e-10){
1.251 brouard 7425: if(first==1){
1.265 brouard 7426: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 7427: }
1.265 brouard 7428: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 7429: }else{
7430: if(first==1)
1.265 brouard 7431: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
7432: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 7433: }
7434: }
7435:
1.265 brouard 7436: for(s1=1; s1 <=nlstate ; s1++){
7437: /* posprop[s1]=0; */
7438: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
7439: pp[s1] += freq[s1][m][iage];
7440: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
7441:
7442: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
7443: pos += pp[s1]; /* pos is the total number of transitions until this age */
7444: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
7445: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
7446: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
7447: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
7448: }
7449:
7450: /* Writing ficresp */
1.335 brouard 7451: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 7452: if( iage <= iagemax){
7453: fprintf(ficresp," %d",iage);
7454: }
7455: }else if( nj==2){
7456: if( iage <= iagemax){
7457: fprintf(ficresp," %d",iage);
1.335 brouard 7458: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.265 brouard 7459: }
1.240 brouard 7460: }
1.265 brouard 7461: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 7462: if(pos>=1.e-5){
1.251 brouard 7463: if(first==1)
1.265 brouard 7464: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
7465: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 7466: }else{
7467: if(first==1)
1.265 brouard 7468: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
7469: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 7470: }
7471: if( iage <= iagemax){
7472: if(pos>=1.e-5){
1.335 brouard 7473: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 7474: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
7475: }else if( nj==2){
7476: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
7477: }
7478: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
7479: /*probs[iage][s1][j1]= pp[s1]/pos;*/
7480: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
7481: } else{
1.335 brouard 7482: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
1.265 brouard 7483: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 7484: }
1.240 brouard 7485: }
1.265 brouard 7486: pospropt[s1] +=posprop[s1];
7487: } /* end loop s1 */
1.251 brouard 7488: /* pospropt=0.; */
1.265 brouard 7489: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 7490: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 7491: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 7492: if(first==1){
1.265 brouard 7493: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 7494: }
1.265 brouard 7495: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
7496: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 7497: }
1.265 brouard 7498: if(s1!=0 && m!=0)
7499: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 7500: }
1.265 brouard 7501: } /* end loop s1 */
1.251 brouard 7502: posproptt=0.;
1.265 brouard 7503: for(s1=1; s1 <=nlstate; s1++){
7504: posproptt += pospropt[s1];
1.251 brouard 7505: }
7506: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 7507: fprintf(ficresphtm,"</tr>\n");
1.335 brouard 7508: if((cptcoveff==0 && nj==1)|| nj==2 ) {
1.265 brouard 7509: if(iage <= iagemax)
7510: fprintf(ficresp,"\n");
1.240 brouard 7511: }
1.251 brouard 7512: if(first==1)
7513: printf("Others in log...\n");
7514: fprintf(ficlog,"\n");
7515: } /* end loop age iage */
1.265 brouard 7516:
1.251 brouard 7517: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 7518: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 7519: if(posproptt < 1.e-5){
1.265 brouard 7520: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 7521: }else{
1.265 brouard 7522: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 7523: }
1.226 brouard 7524: }
1.251 brouard 7525: fprintf(ficresphtm,"</tr>\n");
7526: fprintf(ficresphtm,"</table>\n");
7527: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 7528: if(posproptt < 1.e-5){
1.251 brouard 7529: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
7530: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 7531: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
7532: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 7533: invalidvarcomb[j1]=1;
1.226 brouard 7534: }else{
1.338 brouard 7535: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced (or no resultline).</p>",j1);
1.251 brouard 7536: invalidvarcomb[j1]=0;
1.226 brouard 7537: }
1.251 brouard 7538: fprintf(ficresphtmfr,"</table>\n");
7539: fprintf(ficlog,"\n");
7540: if(j!=0){
7541: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 7542: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 7543: for(k=1; k <=(nlstate+ndeath); k++){
7544: if (k != i) {
1.265 brouard 7545: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 7546: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 7547: if(j1==1){ /* All dummy covariates to zero */
7548: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
7549: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 7550: printf("%d%d ",i,k);
7551: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 7552: 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]));
7553: 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]));
7554: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 7555: }
1.253 brouard 7556: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
7557: for(iage=iagemin; iage <= iagemax+3; iage++){
7558: x[iage]= (double)iage;
7559: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 7560: /* 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 7561: }
1.268 brouard 7562: /* Some are not finite, but linreg will ignore these ages */
7563: no=0;
1.253 brouard 7564: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 7565: pstart[s1]=b;
7566: pstart[s1-1]=a;
1.252 brouard 7567: }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 */
7568: 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]);
7569: 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 7570: 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 7571: printf("%d%d ",i,k);
7572: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 7573: 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 7574: }else{ /* Other cases, like quantitative fixed or varying covariates */
7575: ;
7576: }
7577: /* printf("%12.7f )", param[i][jj][k]); */
7578: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 7579: s1++;
1.251 brouard 7580: } /* end jj */
7581: } /* end k!= i */
7582: } /* end k */
1.265 brouard 7583: } /* end i, s1 */
1.251 brouard 7584: } /* end j !=0 */
7585: } /* end selected combination of covariate j1 */
7586: if(j==0){ /* We can estimate starting values from the occurences in each case */
7587: printf("#Freqsummary: Starting values for the constants:\n");
7588: fprintf(ficlog,"\n");
1.265 brouard 7589: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 7590: for(k=1; k <=(nlstate+ndeath); k++){
7591: if (k != i) {
7592: printf("%d%d ",i,k);
7593: fprintf(ficlog,"%d%d ",i,k);
7594: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 7595: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 7596: if(jj==1){ /* Age has to be done */
1.265 brouard 7597: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
7598: 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]));
7599: 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 7600: }
7601: /* printf("%12.7f )", param[i][jj][k]); */
7602: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 7603: s1++;
1.250 brouard 7604: }
1.251 brouard 7605: printf("\n");
7606: fprintf(ficlog,"\n");
1.250 brouard 7607: }
7608: }
1.284 brouard 7609: } /* end of state i */
1.251 brouard 7610: printf("#Freqsummary\n");
7611: fprintf(ficlog,"\n");
1.265 brouard 7612: for(s1=-1; s1 <=nlstate+ndeath; s1++){
7613: for(s2=-1; s2 <=nlstate+ndeath; s2++){
7614: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
7615: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
7616: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
7617: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
7618: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
7619: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 7620: /* } */
7621: }
1.265 brouard 7622: } /* end loop s1 */
1.251 brouard 7623:
7624: printf("\n");
7625: fprintf(ficlog,"\n");
7626: } /* end j=0 */
1.249 brouard 7627: } /* end j */
1.252 brouard 7628:
1.253 brouard 7629: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 7630: for(i=1, jk=1; i <=nlstate; i++){
7631: for(j=1; j <=nlstate+ndeath; j++){
7632: if(j!=i){
7633: /*ca[0]= k+'a'-1;ca[1]='\0';*/
7634: printf("%1d%1d",i,j);
7635: fprintf(ficparo,"%1d%1d",i,j);
7636: for(k=1; k<=ncovmodel;k++){
7637: /* printf(" %lf",param[i][j][k]); */
7638: /* fprintf(ficparo," %lf",param[i][j][k]); */
7639: p[jk]=pstart[jk];
7640: printf(" %f ",pstart[jk]);
7641: fprintf(ficparo," %f ",pstart[jk]);
7642: jk++;
7643: }
7644: printf("\n");
7645: fprintf(ficparo,"\n");
7646: }
7647: }
7648: }
7649: } /* end mle=-2 */
1.226 brouard 7650: dateintmean=dateintsum/k2cpt;
1.296 brouard 7651: date2dmy(dateintmean,&jintmean,&mintmean,&aintmean);
1.240 brouard 7652:
1.226 brouard 7653: fclose(ficresp);
7654: fclose(ficresphtm);
7655: fclose(ficresphtmfr);
1.283 brouard 7656: free_vector(idq,1,nqfveff);
1.226 brouard 7657: free_vector(meanq,1,nqfveff);
1.284 brouard 7658: free_vector(stdq,1,nqfveff);
1.226 brouard 7659: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 7660: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
7661: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 7662: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 7663: free_vector(pospropt,1,nlstate);
7664: free_vector(posprop,1,nlstate);
1.251 brouard 7665: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 7666: free_vector(pp,1,nlstate);
7667: /* End of freqsummary */
7668: }
1.126 brouard 7669:
1.268 brouard 7670: /* Simple linear regression */
7671: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
7672:
7673: /* y=a+bx regression */
7674: double sumx = 0.0; /* sum of x */
7675: double sumx2 = 0.0; /* sum of x**2 */
7676: double sumxy = 0.0; /* sum of x * y */
7677: double sumy = 0.0; /* sum of y */
7678: double sumy2 = 0.0; /* sum of y**2 */
7679: double sume2 = 0.0; /* sum of square or residuals */
7680: double yhat;
7681:
7682: double denom=0;
7683: int i;
7684: int ne=*no;
7685:
7686: for ( i=ifi, ne=0;i<=ila;i++) {
7687: if(!isfinite(x[i]) || !isfinite(y[i])){
7688: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
7689: continue;
7690: }
7691: ne=ne+1;
7692: sumx += x[i];
7693: sumx2 += x[i]*x[i];
7694: sumxy += x[i] * y[i];
7695: sumy += y[i];
7696: sumy2 += y[i]*y[i];
7697: denom = (ne * sumx2 - sumx*sumx);
7698: /* 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); */
7699: }
7700:
7701: denom = (ne * sumx2 - sumx*sumx);
7702: if (denom == 0) {
7703: // vertical, slope m is infinity
7704: *b = INFINITY;
7705: *a = 0;
7706: if (r) *r = 0;
7707: return 1;
7708: }
7709:
7710: *b = (ne * sumxy - sumx * sumy) / denom;
7711: *a = (sumy * sumx2 - sumx * sumxy) / denom;
7712: if (r!=NULL) {
7713: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
7714: sqrt((sumx2 - sumx*sumx/ne) *
7715: (sumy2 - sumy*sumy/ne));
7716: }
7717: *no=ne;
7718: for ( i=ifi, ne=0;i<=ila;i++) {
7719: if(!isfinite(x[i]) || !isfinite(y[i])){
7720: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
7721: continue;
7722: }
7723: ne=ne+1;
7724: yhat = y[i] - *a -*b* x[i];
7725: sume2 += yhat * yhat ;
7726:
7727: denom = (ne * sumx2 - sumx*sumx);
7728: /* 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); */
7729: }
7730: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
7731: *sa= *sb * sqrt(sumx2/ne);
7732:
7733: return 0;
7734: }
7735:
1.126 brouard 7736: /************ Prevalence ********************/
1.227 brouard 7737: 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)
7738: {
7739: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
7740: in each health status at the date of interview (if between dateprev1 and dateprev2).
7741: We still use firstpass and lastpass as another selection.
7742: */
1.126 brouard 7743:
1.227 brouard 7744: int i, m, jk, j1, bool, z1,j, iv;
7745: int mi; /* Effective wave */
7746: int iage;
1.359 brouard 7747: double agebegin; /*, ageend;*/
1.227 brouard 7748:
7749: double **prop;
7750: double posprop;
7751: double y2; /* in fractional years */
7752: int iagemin, iagemax;
7753: int first; /** to stop verbosity which is redirected to log file */
7754:
7755: iagemin= (int) agemin;
7756: iagemax= (int) agemax;
7757: /*pp=vector(1,nlstate);*/
1.251 brouard 7758: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 7759: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
7760: j1=0;
1.222 brouard 7761:
1.227 brouard 7762: /*j=cptcoveff;*/
7763: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 7764:
1.288 brouard 7765: first=0;
1.335 brouard 7766: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of simple dummy covariates */
1.227 brouard 7767: for (i=1; i<=nlstate; i++)
1.251 brouard 7768: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 7769: prop[i][iage]=0.0;
7770: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
7771: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
7772: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
7773:
7774: for (i=1; i<=imx; i++) { /* Each individual */
7775: bool=1;
7776: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
7777: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
7778: m=mw[mi][i];
7779: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
7780: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
7781: for (z1=1; z1<=cptcoveff; z1++){
7782: if( Fixed[Tmodelind[z1]]==1){
1.341 brouard 7783: iv= Tvar[Tmodelind[z1]];/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
1.332 brouard 7784: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) /* iv=1 to ntv, right modality */
1.227 brouard 7785: bool=0;
7786: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
1.332 brouard 7787: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) {
1.227 brouard 7788: bool=0;
7789: }
7790: }
7791: if(bool==1){ /* Otherwise we skip that wave/person */
7792: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
7793: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
7794: if(m >=firstpass && m <=lastpass){
7795: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
7796: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
7797: if(agev[m][i]==0) agev[m][i]=iagemax+1;
7798: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 7799: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 7800: 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);
7801: exit(1);
7802: }
7803: if (s[m][i]>0 && s[m][i]<=nlstate) {
7804: /*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]]);*/
7805: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
7806: prop[s[m][i]][iagemax+3] += weight[i];
7807: } /* end valid statuses */
7808: } /* end selection of dates */
7809: } /* end selection of waves */
7810: } /* end bool */
7811: } /* end wave */
7812: } /* end individual */
7813: for(i=iagemin; i <= iagemax+3; i++){
7814: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
7815: posprop += prop[jk][i];
7816: }
7817:
7818: for(jk=1; jk <=nlstate ; jk++){
7819: if( i <= iagemax){
7820: if(posprop>=1.e-5){
7821: probs[i][jk][j1]= prop[jk][i]/posprop;
7822: } else{
1.288 brouard 7823: if(!first){
7824: first=1;
1.266 brouard 7825: 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]);
7826: }else{
1.288 brouard 7827: 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 7828: }
7829: }
7830: }
7831: }/* end jk */
7832: }/* end i */
1.222 brouard 7833: /*} *//* end i1 */
1.227 brouard 7834: } /* end j1 */
1.222 brouard 7835:
1.227 brouard 7836: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
7837: /*free_vector(pp,1,nlstate);*/
1.251 brouard 7838: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 7839: } /* End of prevalence */
1.126 brouard 7840:
7841: /************* Waves Concatenation ***************/
7842:
7843: 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)
7844: {
1.298 brouard 7845: /* 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 7846: Death is a valid wave (if date is known).
7847: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
7848: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
1.298 brouard 7849: and mw[mi+1][i]. dh depends on stepm. s[m][i] exists for any wave from firstpass to lastpass
1.227 brouard 7850: */
1.126 brouard 7851:
1.224 brouard 7852: int i=0, mi=0, m=0, mli=0;
1.126 brouard 7853: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
7854: double sum=0., jmean=0.;*/
1.224 brouard 7855: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 7856: int j, k=0,jk, ju, jl;
7857: double sum=0.;
7858: first=0;
1.214 brouard 7859: firstwo=0;
1.217 brouard 7860: firsthree=0;
1.218 brouard 7861: firstfour=0;
1.164 brouard 7862: jmin=100000;
1.126 brouard 7863: jmax=-1;
7864: jmean=0.;
1.224 brouard 7865:
7866: /* Treating live states */
1.214 brouard 7867: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 7868: mi=0; /* First valid wave */
1.227 brouard 7869: mli=0; /* Last valid wave */
1.309 brouard 7870: m=firstpass; /* Loop on waves */
7871: while(s[m][i] <= nlstate){ /* a live state or unknown state */
1.227 brouard 7872: 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 */
7873: mli=m-1;/* mw[++mi][i]=m-1; */
7874: }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 7875: 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 7876: mli=m;
1.224 brouard 7877: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
7878: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 7879: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 7880: }
1.309 brouard 7881: else{ /* m = lastpass, eventual special issue with warning */
1.224 brouard 7882: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 7883: break;
1.224 brouard 7884: #else
1.317 brouard 7885: 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 7886: if(firsthree == 0){
1.302 brouard 7887: 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 7888: firsthree=1;
1.317 brouard 7889: }else if(firsthree >=1 && firsthree < 10){
7890: 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);
7891: firsthree++;
7892: }else if(firsthree == 10){
7893: printf("Information, too many Information flags: no more reported to log either\n");
7894: fprintf(ficlog,"Information, too many Information flags: no more reported to log either\n");
7895: firsthree++;
7896: }else{
7897: firsthree++;
1.227 brouard 7898: }
1.309 brouard 7899: mw[++mi][i]=m; /* Valid transition with unknown status */
1.227 brouard 7900: mli=m;
7901: }
7902: if(s[m][i]==-2){ /* Vital status is really unknown */
7903: nbwarn++;
1.309 brouard 7904: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified?not a transition */
1.227 brouard 7905: 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);
7906: 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);
7907: }
7908: break;
7909: }
7910: break;
1.224 brouard 7911: #endif
1.227 brouard 7912: }/* End m >= lastpass */
1.126 brouard 7913: }/* end while */
1.224 brouard 7914:
1.227 brouard 7915: /* 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 7916: /* After last pass */
1.224 brouard 7917: /* Treating death states */
1.214 brouard 7918: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 7919: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
7920: /* } */
1.126 brouard 7921: mi++; /* Death is another wave */
7922: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 7923: /* Only death is a correct wave */
1.126 brouard 7924: mw[mi][i]=m;
1.257 brouard 7925: } /* else not in a death state */
1.224 brouard 7926: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 7927: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 7928: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.309 brouard 7929: 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 7930: nbwarn++;
7931: if(firstfiv==0){
1.309 brouard 7932: 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 7933: firstfiv=1;
7934: }else{
1.309 brouard 7935: 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 7936: }
1.309 brouard 7937: s[m][i]=nlstate+1; /* Fixing the status as death. Be careful if multiple death states */
7938: }else{ /* Month of Death occured afer last wave month, potential bias */
1.227 brouard 7939: nberr++;
7940: if(firstwo==0){
1.309 brouard 7941: 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 7942: firstwo=1;
7943: }
1.309 brouard 7944: 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 7945: }
1.257 brouard 7946: }else{ /* if date of interview is unknown */
1.227 brouard 7947: /* death is known but not confirmed by death status at any wave */
7948: if(firstfour==0){
1.309 brouard 7949: 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 7950: firstfour=1;
7951: }
1.309 brouard 7952: 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 7953: }
1.224 brouard 7954: } /* end if date of death is known */
7955: #endif
1.309 brouard 7956: wav[i]=mi; /* mi should be the last effective wave (or mli), */
7957: /* wav[i]=mw[mi][i]; */
1.126 brouard 7958: if(mi==0){
7959: nbwarn++;
7960: if(first==0){
1.227 brouard 7961: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
7962: first=1;
1.126 brouard 7963: }
7964: if(first==1){
1.227 brouard 7965: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 7966: }
7967: } /* end mi==0 */
7968: } /* End individuals */
1.214 brouard 7969: /* wav and mw are no more changed */
1.223 brouard 7970:
1.317 brouard 7971: printf("Information, you have to check %d informations which haven't been logged!\n",firsthree);
7972: fprintf(ficlog,"Information, you have to check %d informations which haven't been logged!\n",firsthree);
7973:
7974:
1.126 brouard 7975: for(i=1; i<=imx; i++){
7976: for(mi=1; mi<wav[i];mi++){
7977: if (stepm <=0)
1.227 brouard 7978: dh[mi][i]=1;
1.126 brouard 7979: else{
1.260 brouard 7980: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 7981: if (agedc[i] < 2*AGESUP) {
7982: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
7983: if(j==0) j=1; /* Survives at least one month after exam */
7984: else if(j<0){
7985: nberr++;
1.359 brouard 7986: 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 7987: j=1; /* Temporary Dangerous patch */
7988: 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 7989: 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 7990: 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);
7991: }
7992: k=k+1;
7993: if (j >= jmax){
7994: jmax=j;
7995: ijmax=i;
7996: }
7997: if (j <= jmin){
7998: jmin=j;
7999: ijmin=i;
8000: }
8001: sum=sum+j;
8002: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
8003: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
8004: }
8005: }
8006: else{
8007: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 8008: /* 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 8009:
1.227 brouard 8010: k=k+1;
8011: if (j >= jmax) {
8012: jmax=j;
8013: ijmax=i;
8014: }
8015: else if (j <= jmin){
8016: jmin=j;
8017: ijmin=i;
8018: }
8019: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
8020: /*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]);*/
8021: if(j<0){
8022: nberr++;
1.359 brouard 8023: 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]);
8024: 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 8025: }
8026: sum=sum+j;
8027: }
8028: jk= j/stepm;
8029: jl= j -jk*stepm;
8030: ju= j -(jk+1)*stepm;
8031: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
8032: if(jl==0){
8033: dh[mi][i]=jk;
8034: bh[mi][i]=0;
8035: }else{ /* We want a negative bias in order to only have interpolation ie
8036: * to avoid the price of an extra matrix product in likelihood */
8037: dh[mi][i]=jk+1;
8038: bh[mi][i]=ju;
8039: }
8040: }else{
8041: if(jl <= -ju){
8042: dh[mi][i]=jk;
8043: bh[mi][i]=jl; /* bias is positive if real duration
8044: * is higher than the multiple of stepm and negative otherwise.
8045: */
8046: }
8047: else{
8048: dh[mi][i]=jk+1;
8049: bh[mi][i]=ju;
8050: }
8051: if(dh[mi][i]==0){
8052: dh[mi][i]=1; /* At least one step */
8053: bh[mi][i]=ju; /* At least one step */
8054: /* 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);*/
8055: }
8056: } /* end if mle */
1.126 brouard 8057: }
8058: } /* end wave */
8059: }
8060: jmean=sum/k;
8061: 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 8062: 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 8063: }
1.126 brouard 8064:
8065: /*********** Tricode ****************************/
1.220 brouard 8066: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 8067: {
8068: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
8069: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
8070: * Boring subroutine which should only output nbcode[Tvar[j]][k]
8071: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
8072: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
8073: */
1.130 brouard 8074:
1.242 brouard 8075: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
8076: int modmaxcovj=0; /* Modality max of covariates j */
8077: int cptcode=0; /* Modality max of covariates j */
8078: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 8079:
8080:
1.242 brouard 8081: /* cptcoveff=0; */
8082: /* *cptcov=0; */
1.126 brouard 8083:
1.242 brouard 8084: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 8085: for (k=1; k <= maxncov; k++)
8086: for(j=1; j<=2; j++)
8087: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 8088:
1.242 brouard 8089: /* Loop on covariates without age and products and no quantitative variable */
1.335 brouard 8090: 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 8091: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
1.343 brouard 8092: /* printf("Testing k=%d, cptcovt=%d\n",k, cptcovt); */
1.349 brouard 8093: 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 8094: switch(Fixed[k]) {
8095: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
1.311 brouard 8096: modmaxcovj=0;
8097: modmincovj=0;
1.242 brouard 8098: 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 8099: /* 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 8100: ij=(int)(covar[Tvar[k]][i]);
8101: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
8102: * If product of Vn*Vm, still boolean *:
8103: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
8104: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
8105: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
8106: modality of the nth covariate of individual i. */
8107: if (ij > modmaxcovj)
8108: modmaxcovj=ij;
8109: else if (ij < modmincovj)
8110: modmincovj=ij;
1.287 brouard 8111: if (ij <0 || ij >1 ){
1.311 brouard 8112: printf("ERROR, IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
8113: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
8114: fflush(ficlog);
8115: exit(1);
1.287 brouard 8116: }
8117: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 8118: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
8119: exit(1);
8120: }else
8121: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
8122: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
8123: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
8124: /* getting the maximum value of the modality of the covariate
8125: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
8126: female ies 1, then modmaxcovj=1.
8127: */
8128: } /* end for loop on individuals i */
8129: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
8130: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
8131: cptcode=modmaxcovj;
8132: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
8133: /*for (i=0; i<=cptcode; i++) {*/
8134: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
8135: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
8136: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
8137: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
8138: if( j != -1){
8139: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
8140: covariate for which somebody answered excluding
8141: undefined. Usually 2: 0 and 1. */
8142: }
8143: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
8144: covariate for which somebody answered including
8145: undefined. Usually 3: -1, 0 and 1. */
8146: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
8147: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
8148: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 8149:
1.242 brouard 8150: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
8151: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
8152: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
8153: /* modmincovj=3; modmaxcovj = 7; */
8154: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
8155: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
8156: /* defining two dummy variables: variables V1_1 and V1_2.*/
8157: /* nbcode[Tvar[j]][ij]=k; */
8158: /* nbcode[Tvar[j]][1]=0; */
8159: /* nbcode[Tvar[j]][2]=1; */
8160: /* nbcode[Tvar[j]][3]=2; */
8161: /* To be continued (not working yet). */
8162: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 8163:
8164: /* 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*/
8165: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
8166: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
8167: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
8168: /*, could be restored in the future */
8169: 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 8170: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
8171: break;
8172: }
8173: ij++;
1.287 brouard 8174: 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 8175: cptcode = ij; /* New max modality for covar j */
8176: } /* end of loop on modality i=-1 to 1 or more */
8177: break;
8178: case 1: /* Testing on varying covariate, could be simple and
8179: * should look at waves or product of fixed *
8180: * varying. No time to test -1, assuming 0 and 1 only */
8181: ij=0;
8182: for(i=0; i<=1;i++){
8183: nbcode[Tvar[k]][++ij]=i;
8184: }
8185: break;
8186: default:
8187: break;
8188: } /* end switch */
8189: } /* end dummy test */
1.349 brouard 8190: if(Dummy[k]==1 && Typevar[k] !=1 && Typevar[k] !=3 && Fixed ==0){ /* Fixed Quantitative covariate and not age product */
1.311 brouard 8191: 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 8192: if(Tvar[k]<=0 || Tvar[k]>=NCOVMAX){
8193: printf("Error k=%d \n",k);
8194: exit(1);
8195: }
1.311 brouard 8196: if(isnan(covar[Tvar[k]][i])){
8197: printf("ERROR, IMaCh doesn't treat fixed quantitative covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
8198: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
8199: fflush(ficlog);
8200: exit(1);
8201: }
8202: }
1.335 brouard 8203: } /* end Quanti */
1.287 brouard 8204: } /* 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 8205:
8206: for (k=-1; k< maxncov; k++) Ndum[k]=0;
8207: /* Look at fixed dummy (single or product) covariates to check empty modalities */
8208: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
8209: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
8210: 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 */
8211: 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 */
8212: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
8213: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
8214:
8215: ij=0;
8216: /* 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 8217: 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 */
8218: /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
1.242 brouard 8219: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
8220: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
1.335 brouard 8221: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy simple and non empty in the model */
8222: /* Typevar[k] =0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
8223: /* 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 8224: /* If product not in single variable we don't print results */
8225: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
1.335 brouard 8226: ++ij;/* V5 + V4 + V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V1, *//* V5 quanti, V2 quanti, V4, V3, V1 dummies */
8227: /* k= 1 2 3 4 5 6 7 8 9 */
8228: /* Tvar[k]= 5 4 3 6 5 2 7 1 1 */
8229: /* ij 1 2 3 */
8230: /* Tvaraff[ij]= 4 3 1 */
8231: /* Tmodelind[ij]=2 3 9 */
8232: /* TmodelInvind[ij]=2 1 1 */
1.242 brouard 8233: 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*/
8234: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
8235: 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 */
8236: if(Fixed[k]!=0)
8237: anyvaryingduminmodel=1;
8238: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
8239: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
8240: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
8241: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
8242: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
8243: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
8244: }
8245: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
8246: /* ij--; */
8247: /* cptcoveff=ij; /\*Number of total covariates*\/ */
1.335 brouard 8248: *cptcov=ij; /* cptcov= Number of total real effective simple dummies (fixed or time arying) effective (used as cptcoveff in other functions)
1.242 brouard 8249: * because they can be excluded from the model and real
8250: * if in the model but excluded because missing values, but how to get k from ij?*/
8251: for(j=ij+1; j<= cptcovt; j++){
8252: Tvaraff[j]=0;
8253: Tmodelind[j]=0;
8254: }
8255: for(j=ntveff+1; j<= cptcovt; j++){
8256: TmodelInvind[j]=0;
8257: }
8258: /* To be sorted */
8259: ;
8260: }
1.126 brouard 8261:
1.145 brouard 8262:
1.126 brouard 8263: /*********** Health Expectancies ****************/
8264:
1.235 brouard 8265: 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 8266:
8267: {
8268: /* Health expectancies, no variances */
1.329 brouard 8269: /* cij is the combination in the list of combination of dummy covariates */
8270: /* strstart is a string of time at start of computing */
1.164 brouard 8271: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 8272: int nhstepma, nstepma; /* Decreasing with age */
8273: double age, agelim, hf;
8274: double ***p3mat;
8275: double eip;
8276:
1.238 brouard 8277: /* pstamp(ficreseij); */
1.126 brouard 8278: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
8279: fprintf(ficreseij,"# Age");
8280: for(i=1; i<=nlstate;i++){
8281: for(j=1; j<=nlstate;j++){
8282: fprintf(ficreseij," e%1d%1d ",i,j);
8283: }
8284: fprintf(ficreseij," e%1d. ",i);
8285: }
8286: fprintf(ficreseij,"\n");
8287:
8288:
8289: if(estepm < stepm){
8290: printf ("Problem %d lower than %d\n",estepm, stepm);
8291: }
8292: else hstepm=estepm;
8293: /* We compute the life expectancy from trapezoids spaced every estepm months
8294: * This is mainly to measure the difference between two models: for example
8295: * if stepm=24 months pijx are given only every 2 years and by summing them
8296: * we are calculating an estimate of the Life Expectancy assuming a linear
8297: * progression in between and thus overestimating or underestimating according
8298: * to the curvature of the survival function. If, for the same date, we
8299: * estimate the model with stepm=1 month, we can keep estepm to 24 months
8300: * to compare the new estimate of Life expectancy with the same linear
8301: * hypothesis. A more precise result, taking into account a more precise
8302: * curvature will be obtained if estepm is as small as stepm. */
8303:
8304: /* For example we decided to compute the life expectancy with the smallest unit */
8305: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
8306: nhstepm is the number of hstepm from age to agelim
8307: nstepm is the number of stepm from age to agelin.
1.270 brouard 8308: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 8309: and note for a fixed period like estepm months */
8310: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
8311: survival function given by stepm (the optimization length). Unfortunately it
8312: means that if the survival funtion is printed only each two years of age and if
8313: you sum them up and add 1 year (area under the trapezoids) you won't get the same
8314: results. So we changed our mind and took the option of the best precision.
8315: */
8316: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
8317:
8318: agelim=AGESUP;
8319: /* If stepm=6 months */
8320: /* Computed by stepm unit matrices, product of hstepm matrices, stored
8321: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
8322:
8323: /* nhstepm age range expressed in number of stepm */
8324: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
8325: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
8326: /* if (stepm >= YEARM) hstepm=1;*/
8327: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
8328: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8329:
8330: for (age=bage; age<=fage; age ++){
8331: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
8332: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
8333: /* if (stepm >= YEARM) hstepm=1;*/
8334: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
8335:
8336: /* If stepm=6 months */
8337: /* Computed by stepm unit matrices, product of hstepma matrices, stored
8338: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
1.330 brouard 8339: /* 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 8340: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 8341:
8342: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
8343:
8344: printf("%d|",(int)age);fflush(stdout);
8345: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
8346:
8347: /* Computing expectancies */
8348: for(i=1; i<=nlstate;i++)
8349: for(j=1; j<=nlstate;j++)
8350: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
8351: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
8352:
8353: /* 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]);*/
8354:
8355: }
8356:
8357: fprintf(ficreseij,"%3.0f",age );
8358: for(i=1; i<=nlstate;i++){
8359: eip=0;
8360: for(j=1; j<=nlstate;j++){
8361: eip +=eij[i][j][(int)age];
8362: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
8363: }
8364: fprintf(ficreseij,"%9.4f", eip );
8365: }
8366: fprintf(ficreseij,"\n");
8367:
8368: }
8369: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8370: printf("\n");
8371: fprintf(ficlog,"\n");
8372:
8373: }
8374:
1.235 brouard 8375: 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 8376:
8377: {
8378: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 8379: to initial status i, ei. .
1.126 brouard 8380: */
1.336 brouard 8381: /* Very time consuming function, but already optimized with precov */
1.126 brouard 8382: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
8383: int nhstepma, nstepma; /* Decreasing with age */
8384: double age, agelim, hf;
8385: double ***p3matp, ***p3matm, ***varhe;
8386: double **dnewm,**doldm;
8387: double *xp, *xm;
8388: double **gp, **gm;
8389: double ***gradg, ***trgradg;
8390: int theta;
8391:
8392: double eip, vip;
8393:
8394: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
8395: xp=vector(1,npar);
8396: xm=vector(1,npar);
8397: dnewm=matrix(1,nlstate*nlstate,1,npar);
8398: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
8399:
8400: pstamp(ficresstdeij);
8401: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
8402: fprintf(ficresstdeij,"# Age");
8403: for(i=1; i<=nlstate;i++){
8404: for(j=1; j<=nlstate;j++)
8405: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
8406: fprintf(ficresstdeij," e%1d. ",i);
8407: }
8408: fprintf(ficresstdeij,"\n");
8409:
8410: pstamp(ficrescveij);
8411: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
8412: fprintf(ficrescveij,"# Age");
8413: for(i=1; i<=nlstate;i++)
8414: for(j=1; j<=nlstate;j++){
8415: cptj= (j-1)*nlstate+i;
8416: for(i2=1; i2<=nlstate;i2++)
8417: for(j2=1; j2<=nlstate;j2++){
8418: cptj2= (j2-1)*nlstate+i2;
8419: if(cptj2 <= cptj)
8420: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
8421: }
8422: }
8423: fprintf(ficrescveij,"\n");
8424:
8425: if(estepm < stepm){
8426: printf ("Problem %d lower than %d\n",estepm, stepm);
8427: }
8428: else hstepm=estepm;
8429: /* We compute the life expectancy from trapezoids spaced every estepm months
8430: * This is mainly to measure the difference between two models: for example
8431: * if stepm=24 months pijx are given only every 2 years and by summing them
8432: * we are calculating an estimate of the Life Expectancy assuming a linear
8433: * progression in between and thus overestimating or underestimating according
8434: * to the curvature of the survival function. If, for the same date, we
8435: * estimate the model with stepm=1 month, we can keep estepm to 24 months
8436: * to compare the new estimate of Life expectancy with the same linear
8437: * hypothesis. A more precise result, taking into account a more precise
8438: * curvature will be obtained if estepm is as small as stepm. */
8439:
8440: /* For example we decided to compute the life expectancy with the smallest unit */
8441: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
8442: nhstepm is the number of hstepm from age to agelim
8443: nstepm is the number of stepm from age to agelin.
8444: Look at hpijx to understand the reason of that which relies in memory size
8445: and note for a fixed period like estepm months */
8446: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
8447: survival function given by stepm (the optimization length). Unfortunately it
8448: means that if the survival funtion is printed only each two years of age and if
8449: you sum them up and add 1 year (area under the trapezoids) you won't get the same
8450: results. So we changed our mind and took the option of the best precision.
8451: */
8452: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
8453:
8454: /* If stepm=6 months */
8455: /* nhstepm age range expressed in number of stepm */
8456: agelim=AGESUP;
8457: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
8458: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
8459: /* if (stepm >= YEARM) hstepm=1;*/
8460: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
8461:
8462: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8463: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8464: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
8465: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
8466: gp=matrix(0,nhstepm,1,nlstate*nlstate);
8467: gm=matrix(0,nhstepm,1,nlstate*nlstate);
8468:
8469: for (age=bage; age<=fage; age ++){
8470: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
8471: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
8472: /* if (stepm >= YEARM) hstepm=1;*/
8473: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 8474:
1.126 brouard 8475: /* If stepm=6 months */
8476: /* Computed by stepm unit matrices, product of hstepma matrices, stored
8477: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
8478:
8479: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 8480:
1.126 brouard 8481: /* Computing Variances of health expectancies */
8482: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
8483: decrease memory allocation */
8484: for(theta=1; theta <=npar; theta++){
8485: for(i=1; i<=npar; i++){
1.222 brouard 8486: xp[i] = x[i] + (i==theta ?delti[theta]:0);
8487: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 8488: }
1.235 brouard 8489: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
8490: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 8491:
1.126 brouard 8492: for(j=1; j<= nlstate; j++){
1.222 brouard 8493: for(i=1; i<=nlstate; i++){
8494: for(h=0; h<=nhstepm-1; h++){
8495: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
8496: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
8497: }
8498: }
1.126 brouard 8499: }
1.218 brouard 8500:
1.126 brouard 8501: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 8502: for(h=0; h<=nhstepm-1; h++){
8503: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
8504: }
1.126 brouard 8505: }/* End theta */
8506:
8507:
8508: for(h=0; h<=nhstepm-1; h++)
8509: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 8510: for(theta=1; theta <=npar; theta++)
8511: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 8512:
1.218 brouard 8513:
1.222 brouard 8514: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 8515: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 8516: varhe[ij][ji][(int)age] =0.;
1.218 brouard 8517:
1.222 brouard 8518: printf("%d|",(int)age);fflush(stdout);
8519: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
8520: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 8521: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 8522: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
8523: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
8524: for(ij=1;ij<=nlstate*nlstate;ij++)
8525: for(ji=1;ji<=nlstate*nlstate;ji++)
8526: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 8527: }
8528: }
1.320 brouard 8529: /* if((int)age ==50){ */
8530: /* printf(" age=%d cij=%d nres=%d varhe[%d][%d]=%f ",(int)age, cij, nres, 1,2,varhe[1][2]); */
8531: /* } */
1.126 brouard 8532: /* Computing expectancies */
1.235 brouard 8533: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 8534: for(i=1; i<=nlstate;i++)
8535: for(j=1; j<=nlstate;j++)
1.222 brouard 8536: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
8537: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 8538:
1.222 brouard 8539: /* 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 8540:
1.222 brouard 8541: }
1.269 brouard 8542:
8543: /* Standard deviation of expectancies ij */
1.126 brouard 8544: fprintf(ficresstdeij,"%3.0f",age );
8545: for(i=1; i<=nlstate;i++){
8546: eip=0.;
8547: vip=0.;
8548: for(j=1; j<=nlstate;j++){
1.222 brouard 8549: eip += eij[i][j][(int)age];
8550: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
8551: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
8552: 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 8553: }
8554: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
8555: }
8556: fprintf(ficresstdeij,"\n");
1.218 brouard 8557:
1.269 brouard 8558: /* Variance of expectancies ij */
1.126 brouard 8559: fprintf(ficrescveij,"%3.0f",age );
8560: for(i=1; i<=nlstate;i++)
8561: for(j=1; j<=nlstate;j++){
1.222 brouard 8562: cptj= (j-1)*nlstate+i;
8563: for(i2=1; i2<=nlstate;i2++)
8564: for(j2=1; j2<=nlstate;j2++){
8565: cptj2= (j2-1)*nlstate+i2;
8566: if(cptj2 <= cptj)
8567: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
8568: }
1.126 brouard 8569: }
8570: fprintf(ficrescveij,"\n");
1.218 brouard 8571:
1.126 brouard 8572: }
8573: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
8574: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
8575: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
8576: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
8577: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8578: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8579: printf("\n");
8580: fprintf(ficlog,"\n");
1.218 brouard 8581:
1.126 brouard 8582: free_vector(xm,1,npar);
8583: free_vector(xp,1,npar);
8584: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
8585: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
8586: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
8587: }
1.218 brouard 8588:
1.126 brouard 8589: /************ Variance ******************/
1.235 brouard 8590: 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 8591: {
1.361 brouard 8592: /** Computes the matrix of variance covariance of health expectancies e.j= sum_i w_i e_ij where w_i depends of popbased,
8593: * either cross-sectional or implied.
8594: * 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 8595: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
8596: * double **newm;
8597: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
8598: */
1.218 brouard 8599:
8600: /* int movingaverage(); */
8601: double **dnewm,**doldm;
8602: double **dnewmp,**doldmp;
8603: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 8604: int first=0;
1.218 brouard 8605: int k;
8606: double *xp;
1.279 brouard 8607: double **gp, **gm; /**< for var eij */
8608: double ***gradg, ***trgradg; /**< for var eij */
8609: double **gradgp, **trgradgp; /**< for var p point j */
8610: double *gpp, *gmp; /**< for var p point j */
1.362 ! brouard 8611: double **varppt; /**< for var p.3 p.death nlstate+1 to nlstate+ndeath */
1.218 brouard 8612: double ***p3mat;
8613: double age,agelim, hf;
8614: /* double ***mobaverage; */
8615: int theta;
8616: char digit[4];
8617: char digitp[25];
8618:
8619: char fileresprobmorprev[FILENAMELENGTH];
8620:
8621: if(popbased==1){
8622: if(mobilav!=0)
8623: strcpy(digitp,"-POPULBASED-MOBILAV_");
8624: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
8625: }
8626: else
8627: strcpy(digitp,"-STABLBASED_");
1.126 brouard 8628:
1.218 brouard 8629: /* if (mobilav!=0) { */
8630: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8631: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
8632: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
8633: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
8634: /* } */
8635: /* } */
8636:
8637: strcpy(fileresprobmorprev,"PRMORPREV-");
8638: sprintf(digit,"%-d",ij);
8639: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
8640: strcat(fileresprobmorprev,digit); /* Tvar to be done */
8641: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
8642: strcat(fileresprobmorprev,fileresu);
8643: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
8644: printf("Problem with resultfile: %s\n", fileresprobmorprev);
8645: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
8646: }
8647: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
8648: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
8649: pstamp(ficresprobmorprev);
8650: 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 8651: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
1.337 brouard 8652:
8653: /* We use TinvDoQresult[nres][resultmodel[nres][j] we sort according to the equation model and the resultline: it is a choice */
8654: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ /\* To be done*\/ */
8655: /* fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
8656: /* } */
8657: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */ /* To be done*/
1.344 brouard 8658: /* fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); */
1.337 brouard 8659: fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 8660: }
1.337 brouard 8661: /* for(j=1;j<=cptcoveff;j++) */
8662: /* fprintf(ficresprobmorprev," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,TnsdVar[Tvaraff[j]])]); */
1.238 brouard 8663: fprintf(ficresprobmorprev,"\n");
8664:
1.218 brouard 8665: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
8666: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
8667: fprintf(ficresprobmorprev," p.%-d SE",j);
8668: for(i=1; i<=nlstate;i++)
8669: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
8670: }
8671: fprintf(ficresprobmorprev,"\n");
8672:
8673: fprintf(ficgp,"\n# Routine varevsij");
8674: fprintf(ficgp,"\nunset title \n");
8675: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
8676: 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");
8677: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 8678:
1.361 brouard 8679: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath); /* In fact, currently a double */
1.218 brouard 8680: pstamp(ficresvij);
8681: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
8682: if(popbased==1)
8683: 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);
8684: else
8685: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
8686: fprintf(ficresvij,"# Age");
8687: for(i=1; i<=nlstate;i++)
8688: for(j=1; j<=nlstate;j++)
8689: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
8690: fprintf(ficresvij,"\n");
8691:
8692: xp=vector(1,npar);
8693: dnewm=matrix(1,nlstate,1,npar);
8694: doldm=matrix(1,nlstate,1,nlstate);
8695: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
8696: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
8697:
8698: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
8699: gpp=vector(nlstate+1,nlstate+ndeath);
8700: gmp=vector(nlstate+1,nlstate+ndeath);
8701: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 8702:
1.218 brouard 8703: if(estepm < stepm){
8704: printf ("Problem %d lower than %d\n",estepm, stepm);
8705: }
8706: else hstepm=estepm;
8707: /* For example we decided to compute the life expectancy with the smallest unit */
8708: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
8709: nhstepm is the number of hstepm from age to agelim
8710: nstepm is the number of stepm from age to agelim.
8711: Look at function hpijx to understand why because of memory size limitations,
8712: we decided (b) to get a life expectancy respecting the most precise curvature of the
8713: survival function given by stepm (the optimization length). Unfortunately it
8714: means that if the survival funtion is printed every two years of age and if
8715: you sum them up and add 1 year (area under the trapezoids) you won't get the same
8716: results. So we changed our mind and took the option of the best precision.
8717: */
8718: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
8719: agelim = AGESUP;
8720: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
8721: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
8722: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
8723: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8724: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
8725: gp=matrix(0,nhstepm,1,nlstate);
8726: gm=matrix(0,nhstepm,1,nlstate);
8727:
8728:
8729: for(theta=1; theta <=npar; theta++){
8730: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
8731: xp[i] = x[i] + (i==theta ?delti[theta]:0);
8732: }
1.279 brouard 8733: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
8734: * returns into prlim .
1.288 brouard 8735: */
1.242 brouard 8736: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 8737:
8738: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 8739: if (popbased==1) {
8740: if(mobilav ==0){
8741: for(i=1; i<=nlstate;i++)
8742: prlim[i][i]=probs[(int)age][i][ij];
8743: }else{ /* mobilav */
8744: for(i=1; i<=nlstate;i++)
8745: prlim[i][i]=mobaverage[(int)age][i][ij];
8746: }
8747: }
1.361 brouard 8748: /**< Computes the shifted plus (gp) transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h.
1.279 brouard 8749: */
8750: 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 8751: /**< 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 8752: * at horizon h in state j including mortality.
8753: */
1.218 brouard 8754: for(j=1; j<= nlstate; j++){
8755: for(h=0; h<=nhstepm; h++){
8756: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
1.361 brouard 8757: gp[h][j] += prlim[i][i]*p3mat[i][j][h]; /* gp[h][j]= w_i h_pij */
1.218 brouard 8758: }
8759: }
1.279 brouard 8760: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 8761: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 8762: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 8763: */
1.361 brouard 8764: for(j=nlstate+1;j<=nlstate+ndeath;j++){ /* Currently only once for theta plus p.3(age) Sum_i wi pi3*/
1.218 brouard 8765: for(i=1,gpp[j]=0.; i<= nlstate; i++)
8766: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 8767: }
8768:
8769: /* Again with minus shift */
1.218 brouard 8770:
8771: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
8772: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 8773:
1.242 brouard 8774: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 8775:
8776: if (popbased==1) {
8777: if(mobilav ==0){
8778: for(i=1; i<=nlstate;i++)
8779: prlim[i][i]=probs[(int)age][i][ij];
8780: }else{ /* mobilav */
8781: for(i=1; i<=nlstate;i++)
8782: prlim[i][i]=mobaverage[(int)age][i][ij];
8783: }
8784: }
8785:
1.361 brouard 8786: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres); /* Still minus */
1.218 brouard 8787:
1.361 brouard 8788: for(j=1; j<= nlstate; j++){ /* gm[h][j]= Sum_i of wi * pij = h_p.j */
1.218 brouard 8789: for(h=0; h<=nhstepm; h++){
8790: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
8791: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
8792: }
8793: }
8794: /* This for computing probability of death (h=1 means
8795: computed over hstepm matrices product = hstepm*stepm months)
1.361 brouard 8796: as a weighted average of prlim. j is death. gmp[3]=sum_i w_i*p_i3=p.3 minus theta
1.218 brouard 8797: */
1.361 brouard 8798: for(j=nlstate+1;j<=nlstate+ndeath;j++){ /* Currently only once theta_minus p.3=Sum_i wi pi3*/
1.218 brouard 8799: for(i=1,gmp[j]=0.; i<= nlstate; i++)
8800: gmp[j] += prlim[i][i]*p3mat[i][j][1];
8801: }
1.279 brouard 8802: /* end shifting computations */
8803:
1.361 brouard 8804: /**< Computing gradient of p.j matrix at horizon h and still for one parameter of vector theta
8805: * equation 31 and 32
1.279 brouard 8806: */
1.361 brouard 8807: 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)
8808: * equation 24 */
1.218 brouard 8809: for(h=0; h<=nhstepm; h++){
8810: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
8811: }
1.361 brouard 8812: /**< Gradient of overall mortality p.3 (or p.death)
1.279 brouard 8813: */
1.361 brouard 8814: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* computes grad of p.3 from wi+pi3 grad p.3 (theta) */
1.218 brouard 8815: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
8816: }
8817:
8818: } /* End theta */
1.279 brouard 8819:
1.361 brouard 8820: /* We got the gradient matrix for each theta and each state j of gradg(h]theta][j)=grad(_hp.j(theta) */
8821: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar);
1.218 brouard 8822:
1.361 brouard 8823: for(h=0; h<=nhstepm; h++) /* veij */ /* computes the transposed of grad (_hp.j(theta)*/
1.218 brouard 8824: for(j=1; j<=nlstate;j++)
8825: for(theta=1; theta <=npar; theta++)
8826: trgradg[h][j][theta]=gradg[h][theta][j];
8827:
1.361 brouard 8828: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* computes transposed of grad p.3 (theta)*/
1.218 brouard 8829: for(theta=1; theta <=npar; theta++)
8830: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 8831: /**< as well as its transposed matrix
8832: */
1.218 brouard 8833:
8834: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
8835: for(i=1;i<=nlstate;i++)
8836: for(j=1;j<=nlstate;j++)
8837: vareij[i][j][(int)age] =0.;
1.279 brouard 8838:
8839: /* Computing trgradg by matcov by gradg at age and summing over h
1.361 brouard 8840: * and k (nhstepm) formula 32 of article
8841: * Lievre-Brouard-Heathcote so that for each j, computes the cov(e.j,e.k) (formula 31).
8842: * for given h and k computes trgradg[h](i,j) matcov (theta) gradg(k)(i,j) into vareij[i][j] which is
8843: cov(e.i,e.j) and sums on h and k
8844: * including the covariances.
1.279 brouard 8845: */
8846:
1.218 brouard 8847: for(h=0;h<=nhstepm;h++){
8848: for(k=0;k<=nhstepm;k++){
8849: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
8850: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
8851: for(i=1;i<=nlstate;i++)
8852: for(j=1;j<=nlstate;j++)
1.361 brouard 8853: 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)
8854: including the covariances of e.j */
1.218 brouard 8855: }
8856: }
8857:
1.361 brouard 8858: /* Mortality: pptj is p.3 or p.death = trgradgp by cov by gradgp, variance of
8859: * p.3=1-p..=1-sum i p.i overall mortality computed directly because
1.279 brouard 8860: * we compute the grad (wix pijx) instead of grad (pijx),even if
1.361 brouard 8861: * wix is independent of theta.
1.279 brouard 8862: */
1.218 brouard 8863: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
8864: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
8865: for(j=nlstate+1;j<=nlstate+ndeath;j++)
8866: for(i=nlstate+1;i<=nlstate+ndeath;i++)
1.361 brouard 8867: varppt[j][i]=doldmp[j][i]; /* This is the variance of p.3 */
1.218 brouard 8868: /* end ppptj */
8869: /* x centered again */
8870:
1.242 brouard 8871: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 8872:
8873: if (popbased==1) {
8874: if(mobilav ==0){
8875: for(i=1; i<=nlstate;i++)
8876: prlim[i][i]=probs[(int)age][i][ij];
8877: }else{ /* mobilav */
8878: for(i=1; i<=nlstate;i++)
8879: prlim[i][i]=mobaverage[(int)age][i][ij];
8880: }
8881: }
8882:
8883: /* This for computing probability of death (h=1 means
8884: computed over hstepm (estepm) matrices product = hstepm*stepm months)
8885: as a weighted average of prlim.
8886: */
1.235 brouard 8887: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 8888: for(j=nlstate+1;j<=nlstate+ndeath;j++){
8889: for(i=1,gmp[j]=0.;i<= nlstate; i++)
1.361 brouard 8890: gmp[j] += prlim[i][i]*p3mat[i][j][1]; /* gmp[j] is p.3 */
1.218 brouard 8891: }
8892: /* end probability of death */
8893:
8894: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
8895: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
1.361 brouard 8896: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));/* p.3 (STD p.3) */
1.218 brouard 8897: for(i=1; i<=nlstate;i++){
1.361 brouard 8898: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]); /* wi, pi3 */
1.218 brouard 8899: }
8900: }
8901: fprintf(ficresprobmorprev,"\n");
8902:
8903: fprintf(ficresvij,"%.0f ",age );
8904: for(i=1; i<=nlstate;i++)
8905: for(j=1; j<=nlstate;j++){
8906: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
8907: }
8908: fprintf(ficresvij,"\n");
8909: free_matrix(gp,0,nhstepm,1,nlstate);
8910: free_matrix(gm,0,nhstepm,1,nlstate);
8911: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
8912: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
8913: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8914: } /* End age */
8915: free_vector(gpp,nlstate+1,nlstate+ndeath);
8916: free_vector(gmp,nlstate+1,nlstate+ndeath);
8917: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
8918: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
8919: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
8920: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
8921: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
8922: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
8923: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
8924: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
8925: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
8926: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
8927: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
8928: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
8929: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
8930: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
8931: 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);
8932: /* 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 8933: */
1.218 brouard 8934: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
8935: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 8936:
1.218 brouard 8937: free_vector(xp,1,npar);
8938: free_matrix(doldm,1,nlstate,1,nlstate);
8939: free_matrix(dnewm,1,nlstate,1,npar);
8940: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
8941: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
8942: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
8943: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8944: fclose(ficresprobmorprev);
8945: fflush(ficgp);
8946: fflush(fichtm);
8947: } /* end varevsij */
1.126 brouard 8948:
8949: /************ Variance of prevlim ******************/
1.269 brouard 8950: 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 8951: {
1.205 brouard 8952: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 8953: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 8954:
1.268 brouard 8955: double **dnewmpar,**doldm;
1.126 brouard 8956: int i, j, nhstepm, hstepm;
8957: double *xp;
8958: double *gp, *gm;
8959: double **gradg, **trgradg;
1.208 brouard 8960: double **mgm, **mgp;
1.126 brouard 8961: double age,agelim;
8962: int theta;
8963:
8964: pstamp(ficresvpl);
1.288 brouard 8965: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 8966: fprintf(ficresvpl,"# Age ");
8967: if(nresult >=1)
8968: fprintf(ficresvpl," Result# ");
1.126 brouard 8969: for(i=1; i<=nlstate;i++)
8970: fprintf(ficresvpl," %1d-%1d",i,i);
8971: fprintf(ficresvpl,"\n");
8972:
8973: xp=vector(1,npar);
1.268 brouard 8974: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 8975: doldm=matrix(1,nlstate,1,nlstate);
8976:
8977: hstepm=1*YEARM; /* Every year of age */
8978: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
8979: agelim = AGESUP;
8980: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
8981: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
8982: if (stepm >= YEARM) hstepm=1;
8983: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
8984: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 8985: mgp=matrix(1,npar,1,nlstate);
8986: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 8987: gp=vector(1,nlstate);
8988: gm=vector(1,nlstate);
8989:
8990: for(theta=1; theta <=npar; theta++){
8991: for(i=1; i<=npar; i++){ /* Computes gradient */
8992: xp[i] = x[i] + (i==theta ?delti[theta]:0);
8993: }
1.288 brouard 8994: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
8995: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
8996: /* else */
8997: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 8998: for(i=1;i<=nlstate;i++){
1.126 brouard 8999: gp[i] = prlim[i][i];
1.208 brouard 9000: mgp[theta][i] = prlim[i][i];
9001: }
1.126 brouard 9002: for(i=1; i<=npar; i++) /* Computes gradient */
9003: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 9004: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
9005: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
9006: /* else */
9007: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 9008: for(i=1;i<=nlstate;i++){
1.126 brouard 9009: gm[i] = prlim[i][i];
1.208 brouard 9010: mgm[theta][i] = prlim[i][i];
9011: }
1.126 brouard 9012: for(i=1;i<=nlstate;i++)
9013: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 9014: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 9015: } /* End theta */
9016:
9017: trgradg =matrix(1,nlstate,1,npar);
9018:
9019: for(j=1; j<=nlstate;j++)
9020: for(theta=1; theta <=npar; theta++)
9021: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 9022: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
9023: /* printf("\nmgm mgp %d ",(int)age); */
9024: /* for(j=1; j<=nlstate;j++){ */
9025: /* printf(" %d ",j); */
9026: /* for(theta=1; theta <=npar; theta++) */
9027: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
9028: /* printf("\n "); */
9029: /* } */
9030: /* } */
9031: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
9032: /* printf("\n gradg %d ",(int)age); */
9033: /* for(j=1; j<=nlstate;j++){ */
9034: /* printf("%d ",j); */
9035: /* for(theta=1; theta <=npar; theta++) */
9036: /* printf("%d %lf ",theta,gradg[theta][j]); */
9037: /* printf("\n "); */
9038: /* } */
9039: /* } */
1.126 brouard 9040:
9041: for(i=1;i<=nlstate;i++)
9042: varpl[i][(int)age] =0.;
1.209 brouard 9043: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 9044: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
9045: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 9046: }else{
1.268 brouard 9047: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
9048: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 9049: }
1.126 brouard 9050: for(i=1;i<=nlstate;i++)
9051: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
9052:
9053: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 9054: if(nresult >=1)
9055: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 9056: for(i=1; i<=nlstate;i++){
1.126 brouard 9057: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 9058: /* for(j=1;j<=nlstate;j++) */
9059: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
9060: }
1.126 brouard 9061: fprintf(ficresvpl,"\n");
9062: free_vector(gp,1,nlstate);
9063: free_vector(gm,1,nlstate);
1.208 brouard 9064: free_matrix(mgm,1,npar,1,nlstate);
9065: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 9066: free_matrix(gradg,1,npar,1,nlstate);
9067: free_matrix(trgradg,1,nlstate,1,npar);
9068: } /* End age */
9069:
9070: free_vector(xp,1,npar);
9071: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 9072: free_matrix(dnewmpar,1,nlstate,1,nlstate);
9073:
9074: }
9075:
9076:
9077: /************ Variance of backprevalence limit ******************/
1.269 brouard 9078: 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 9079: {
9080: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
9081: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
9082:
9083: double **dnewmpar,**doldm;
9084: int i, j, nhstepm, hstepm;
9085: double *xp;
9086: double *gp, *gm;
9087: double **gradg, **trgradg;
9088: double **mgm, **mgp;
9089: double age,agelim;
9090: int theta;
9091:
9092: pstamp(ficresvbl);
9093: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
9094: fprintf(ficresvbl,"# Age ");
9095: if(nresult >=1)
9096: fprintf(ficresvbl," Result# ");
9097: for(i=1; i<=nlstate;i++)
9098: fprintf(ficresvbl," %1d-%1d",i,i);
9099: fprintf(ficresvbl,"\n");
9100:
9101: xp=vector(1,npar);
9102: dnewmpar=matrix(1,nlstate,1,npar);
9103: doldm=matrix(1,nlstate,1,nlstate);
9104:
9105: hstepm=1*YEARM; /* Every year of age */
9106: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
9107: agelim = AGEINF;
9108: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
9109: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
9110: if (stepm >= YEARM) hstepm=1;
9111: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
9112: gradg=matrix(1,npar,1,nlstate);
9113: mgp=matrix(1,npar,1,nlstate);
9114: mgm=matrix(1,npar,1,nlstate);
9115: gp=vector(1,nlstate);
9116: gm=vector(1,nlstate);
9117:
9118: for(theta=1; theta <=npar; theta++){
9119: for(i=1; i<=npar; i++){ /* Computes gradient */
9120: xp[i] = x[i] + (i==theta ?delti[theta]:0);
9121: }
9122: if(mobilavproj > 0 )
9123: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
9124: else
9125: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
9126: for(i=1;i<=nlstate;i++){
9127: gp[i] = bprlim[i][i];
9128: mgp[theta][i] = bprlim[i][i];
9129: }
9130: for(i=1; i<=npar; i++) /* Computes gradient */
9131: xp[i] = x[i] - (i==theta ?delti[theta]:0);
9132: if(mobilavproj > 0 )
9133: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
9134: else
9135: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
9136: for(i=1;i<=nlstate;i++){
9137: gm[i] = bprlim[i][i];
9138: mgm[theta][i] = bprlim[i][i];
9139: }
9140: for(i=1;i<=nlstate;i++)
9141: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
9142: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
9143: } /* End theta */
9144:
9145: trgradg =matrix(1,nlstate,1,npar);
9146:
9147: for(j=1; j<=nlstate;j++)
9148: for(theta=1; theta <=npar; theta++)
9149: trgradg[j][theta]=gradg[theta][j];
9150: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
9151: /* printf("\nmgm mgp %d ",(int)age); */
9152: /* for(j=1; j<=nlstate;j++){ */
9153: /* printf(" %d ",j); */
9154: /* for(theta=1; theta <=npar; theta++) */
9155: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
9156: /* printf("\n "); */
9157: /* } */
9158: /* } */
9159: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
9160: /* printf("\n gradg %d ",(int)age); */
9161: /* for(j=1; j<=nlstate;j++){ */
9162: /* printf("%d ",j); */
9163: /* for(theta=1; theta <=npar; theta++) */
9164: /* printf("%d %lf ",theta,gradg[theta][j]); */
9165: /* printf("\n "); */
9166: /* } */
9167: /* } */
9168:
9169: for(i=1;i<=nlstate;i++)
9170: varbpl[i][(int)age] =0.;
9171: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
9172: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
9173: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
9174: }else{
9175: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
9176: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
9177: }
9178: for(i=1;i<=nlstate;i++)
9179: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
9180:
9181: fprintf(ficresvbl,"%.0f ",age );
9182: if(nresult >=1)
9183: fprintf(ficresvbl,"%d ",nres );
9184: for(i=1; i<=nlstate;i++)
9185: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
9186: fprintf(ficresvbl,"\n");
9187: free_vector(gp,1,nlstate);
9188: free_vector(gm,1,nlstate);
9189: free_matrix(mgm,1,npar,1,nlstate);
9190: free_matrix(mgp,1,npar,1,nlstate);
9191: free_matrix(gradg,1,npar,1,nlstate);
9192: free_matrix(trgradg,1,nlstate,1,npar);
9193: } /* End age */
9194:
9195: free_vector(xp,1,npar);
9196: free_matrix(doldm,1,nlstate,1,npar);
9197: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 9198:
9199: }
9200:
9201: /************ Variance of one-step probabilities ******************/
9202: 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 9203: {
9204: int i, j=0, k1, l1, tj;
9205: int k2, l2, j1, z1;
9206: int k=0, l;
9207: int first=1, first1, first2;
1.326 brouard 9208: int nres=0; /* New */
1.222 brouard 9209: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
9210: double **dnewm,**doldm;
9211: double *xp;
9212: double *gp, *gm;
9213: double **gradg, **trgradg;
9214: double **mu;
9215: double age, cov[NCOVMAX+1];
9216: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
9217: int theta;
9218: char fileresprob[FILENAMELENGTH];
9219: char fileresprobcov[FILENAMELENGTH];
9220: char fileresprobcor[FILENAMELENGTH];
9221: double ***varpij;
9222:
9223: strcpy(fileresprob,"PROB_");
1.356 brouard 9224: strcat(fileresprob,fileresu);
1.222 brouard 9225: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
9226: printf("Problem with resultfile: %s\n", fileresprob);
9227: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
9228: }
9229: strcpy(fileresprobcov,"PROBCOV_");
9230: strcat(fileresprobcov,fileresu);
9231: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
9232: printf("Problem with resultfile: %s\n", fileresprobcov);
9233: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
9234: }
9235: strcpy(fileresprobcor,"PROBCOR_");
9236: strcat(fileresprobcor,fileresu);
9237: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
9238: printf("Problem with resultfile: %s\n", fileresprobcor);
9239: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
9240: }
9241: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
9242: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
9243: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
9244: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
9245: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
9246: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
9247: pstamp(ficresprob);
9248: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
9249: fprintf(ficresprob,"# Age");
9250: pstamp(ficresprobcov);
9251: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
9252: fprintf(ficresprobcov,"# Age");
9253: pstamp(ficresprobcor);
9254: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
9255: fprintf(ficresprobcor,"# Age");
1.126 brouard 9256:
9257:
1.222 brouard 9258: for(i=1; i<=nlstate;i++)
9259: for(j=1; j<=(nlstate+ndeath);j++){
9260: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
9261: fprintf(ficresprobcov," p%1d-%1d ",i,j);
9262: fprintf(ficresprobcor," p%1d-%1d ",i,j);
9263: }
9264: /* fprintf(ficresprob,"\n");
9265: fprintf(ficresprobcov,"\n");
9266: fprintf(ficresprobcor,"\n");
9267: */
9268: xp=vector(1,npar);
9269: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
9270: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
9271: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
9272: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
9273: first=1;
9274: fprintf(ficgp,"\n# Routine varprob");
9275: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
9276: fprintf(fichtm,"\n");
9277:
1.288 brouard 9278: 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 9279: 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);
9280: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 9281: and drawn. It helps understanding how is the covariance between two incidences.\
9282: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 9283: 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 9284: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
9285: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
9286: standard deviations wide on each axis. <br>\
9287: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
9288: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
9289: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
9290:
1.222 brouard 9291: cov[1]=1;
9292: /* tj=cptcoveff; */
1.225 brouard 9293: tj = (int) pow(2,cptcoveff);
1.222 brouard 9294: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
9295: j1=0;
1.332 brouard 9296:
9297: for(nres=1;nres <=nresult; nres++){ /* For each resultline */
9298: for(j1=1; j1<=tj;j1++){ /* For any combination of dummy covariates, fixed and varying */
1.342 brouard 9299: /* 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 9300: if(tj != 1 && TKresult[nres]!= j1)
9301: continue;
9302:
9303: /* for(j1=1; j1<=tj;j1++){ /\* For each valid combination of covariates or only once*\/ */
9304: /* for(nres=1;nres <=1; nres++){ /\* For each resultline *\/ */
9305: /* /\* for(nres=1;nres <=nresult; nres++){ /\\* For each resultline *\\/ *\/ */
1.222 brouard 9306: if (cptcovn>0) {
1.334 brouard 9307: fprintf(ficresprob, "\n#********** Variable ");
9308: fprintf(ficresprobcov, "\n#********** Variable ");
9309: fprintf(ficgp, "\n#********** Variable ");
9310: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
9311: fprintf(ficresprobcor, "\n#********** Variable ");
9312:
9313: /* Including quantitative variables of the resultline to be done */
9314: for (z1=1; z1<=cptcovs; z1++){ /* Loop on each variable of this resultline */
1.343 brouard 9315: /* printf("Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model); */
1.338 brouard 9316: fprintf(ficlog,"Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model);
9317: /* 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 9318: if(Dummy[modelresult[nres][z1]]==0){/* Dummy variable of the variable in position modelresult in the model corresponding to z1 in resultline */
9319: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed referenced to model equation */
9320: 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 */
9321: 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 */
9322: 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 */
9323: 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 */
9324: 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 */
9325: fprintf(ficresprob,"fixed ");
9326: fprintf(ficresprobcov,"fixed ");
9327: fprintf(ficgp,"fixed ");
9328: fprintf(fichtmcov,"fixed ");
9329: fprintf(ficresprobcor,"fixed ");
9330: }else{
9331: fprintf(ficresprob,"varyi ");
9332: fprintf(ficresprobcov,"varyi ");
9333: fprintf(ficgp,"varyi ");
9334: fprintf(fichtmcov,"varyi ");
9335: fprintf(ficresprobcor,"varyi ");
9336: }
9337: }else if(Dummy[modelresult[nres][z1]]==1){ /* Quanti variable */
9338: /* For each selected (single) quantitative value */
1.337 brouard 9339: fprintf(ficresprob," V%d=%lg ",Tvqresult[nres][z1],Tqresult[nres][z1]);
1.334 brouard 9340: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed */
9341: fprintf(ficresprob,"fixed ");
9342: fprintf(ficresprobcov,"fixed ");
9343: fprintf(ficgp,"fixed ");
9344: fprintf(fichtmcov,"fixed ");
9345: fprintf(ficresprobcor,"fixed ");
9346: }else{
9347: fprintf(ficresprob,"varyi ");
9348: fprintf(ficresprobcov,"varyi ");
9349: fprintf(ficgp,"varyi ");
9350: fprintf(fichtmcov,"varyi ");
9351: fprintf(ficresprobcor,"varyi ");
9352: }
9353: }else{
9354: 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 */
9355: 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 */
9356: exit(1);
9357: }
9358: } /* End loop on variable of this resultline */
9359: /* for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]); */
1.222 brouard 9360: fprintf(ficresprob, "**********\n#\n");
9361: fprintf(ficresprobcov, "**********\n#\n");
9362: fprintf(ficgp, "**********\n#\n");
9363: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
9364: fprintf(ficresprobcor, "**********\n#");
9365: if(invalidvarcomb[j1]){
9366: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
9367: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
9368: continue;
9369: }
9370: }
9371: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
9372: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
9373: gp=vector(1,(nlstate)*(nlstate+ndeath));
9374: gm=vector(1,(nlstate)*(nlstate+ndeath));
1.334 brouard 9375: for (age=bage; age<=fage; age ++){ /* Fo each age we feed the model equation with covariates, using precov as in hpxij() ? */
1.222 brouard 9376: cov[2]=age;
9377: if(nagesqr==1)
9378: cov[3]= age*age;
1.334 brouard 9379: /* New code end of combination but for each resultline */
9380: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 9381: if(Typevar[k1]==1 || Typevar[k1] ==3){ /* A product with age */
1.334 brouard 9382: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.326 brouard 9383: }else{
1.334 brouard 9384: cov[2+nagesqr+k1]=precov[nres][k1];
1.326 brouard 9385: }
1.334 brouard 9386: }/* End of loop on model equation */
9387: /* Old code */
9388: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
9389: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)]; *\/ */
9390: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
9391: /* /\* Here comes the value of the covariate 'j1' after renumbering k with single dummy covariates *\/ */
9392: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(j1,TnsdVar[TvarsD[k]])]; */
9393: /* /\*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*\//\* j1 1 2 3 4 */
9394: /* * 1 1 1 1 1 */
9395: /* * 2 2 1 1 1 */
9396: /* * 3 1 2 1 1 */
9397: /* *\/ */
9398: /* /\* nbcode[1][1]=0 nbcode[1][2]=1;*\/ */
9399: /* } */
9400: /* /\* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
9401: /* /\* ) p nbcode[Tvar[Tage[k]]][(1 & (ij-1) >> (k-1))+1] *\/ */
9402: /* /\*for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; *\/ */
9403: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
9404: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
9405: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(j1,TnsdVar[Tvar[Tage[k]]])]*cov[2]; */
9406: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
9407: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
9408: /* 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]); */
9409: /* /\* cov[2+nagesqr+Tage[k]]=meanq[k]/idq[k]*cov[2];/\\* Using the mean of quantitative variable Tvar[Tage[k]] /\\* Tqresult[nres][k]; *\\/ *\/ */
9410: /* /\* exit(1); *\/ */
9411: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
9412: /* } */
9413: /* /\* cov[2+Tage[k]+nagesqr]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
9414: /* } */
9415: /* for (k=1; k<=cptcovprod;k++){/\* For product without age *\/ */
9416: /* if(Dummy[Tvard[k][1]]==0){ */
9417: /* if(Dummy[Tvard[k][2]]==0){ */
9418: /* 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]])]; */
9419: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
9420: /* }else{ /\* Should we use the mean of the quantitative variables? *\/ */
9421: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(j1,TnsdVar[Tvard[k][1]])] * Tqresult[nres][resultmodel[nres][k]]; */
9422: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
9423: /* } */
9424: /* }else{ */
9425: /* if(Dummy[Tvard[k][2]]==0){ */
9426: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(j1,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][TnsdVar[Tvard[k][1]]]; */
9427: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
9428: /* }else{ */
9429: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][TnsdVar[Tvard[k][1]]]* Tqinvresult[nres][TnsdVar[Tvard[k][2]]]; */
9430: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
9431: /* } */
9432: /* } */
9433: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
9434: /* } */
1.326 brouard 9435: /* For each age and combination of dummy covariates we slightly move the parameters of delti in order to get the gradient*/
1.222 brouard 9436: for(theta=1; theta <=npar; theta++){
9437: for(i=1; i<=npar; i++)
9438: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 9439:
1.222 brouard 9440: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 9441:
1.222 brouard 9442: k=0;
9443: for(i=1; i<= (nlstate); i++){
9444: for(j=1; j<=(nlstate+ndeath);j++){
9445: k=k+1;
9446: gp[k]=pmmij[i][j];
9447: }
9448: }
1.220 brouard 9449:
1.222 brouard 9450: for(i=1; i<=npar; i++)
9451: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 9452:
1.222 brouard 9453: pmij(pmmij,cov,ncovmodel,xp,nlstate);
9454: k=0;
9455: for(i=1; i<=(nlstate); i++){
9456: for(j=1; j<=(nlstate+ndeath);j++){
9457: k=k+1;
9458: gm[k]=pmmij[i][j];
9459: }
9460: }
1.220 brouard 9461:
1.222 brouard 9462: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
9463: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
9464: }
1.126 brouard 9465:
1.222 brouard 9466: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
9467: for(theta=1; theta <=npar; theta++)
9468: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 9469:
1.222 brouard 9470: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
9471: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 9472:
1.222 brouard 9473: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 9474:
1.222 brouard 9475: k=0;
9476: for(i=1; i<=(nlstate); i++){
9477: for(j=1; j<=(nlstate+ndeath);j++){
9478: k=k+1;
9479: mu[k][(int) age]=pmmij[i][j];
9480: }
9481: }
9482: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
9483: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
9484: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 9485:
1.222 brouard 9486: /*printf("\n%d ",(int)age);
9487: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
9488: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
9489: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
9490: }*/
1.220 brouard 9491:
1.222 brouard 9492: fprintf(ficresprob,"\n%d ",(int)age);
9493: fprintf(ficresprobcov,"\n%d ",(int)age);
9494: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 9495:
1.222 brouard 9496: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
9497: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
9498: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
9499: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
9500: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
9501: }
9502: i=0;
9503: for (k=1; k<=(nlstate);k++){
9504: for (l=1; l<=(nlstate+ndeath);l++){
9505: i++;
9506: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
9507: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
9508: for (j=1; j<=i;j++){
9509: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
9510: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
9511: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
9512: }
9513: }
9514: }/* end of loop for state */
9515: } /* end of loop for age */
9516: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
9517: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
9518: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
9519: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
9520:
9521: /* Confidence intervalle of pij */
9522: /*
9523: fprintf(ficgp,"\nunset parametric;unset label");
9524: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
9525: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
9526: 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);
9527: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
9528: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
9529: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
9530: */
9531:
9532: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
9533: first1=1;first2=2;
9534: for (k2=1; k2<=(nlstate);k2++){
9535: for (l2=1; l2<=(nlstate+ndeath);l2++){
9536: if(l2==k2) continue;
9537: j=(k2-1)*(nlstate+ndeath)+l2;
9538: for (k1=1; k1<=(nlstate);k1++){
9539: for (l1=1; l1<=(nlstate+ndeath);l1++){
9540: if(l1==k1) continue;
9541: i=(k1-1)*(nlstate+ndeath)+l1;
9542: if(i<=j) continue;
9543: for (age=bage; age<=fage; age ++){
9544: if ((int)age %5==0){
9545: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
9546: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
9547: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
9548: mu1=mu[i][(int) age]/stepm*YEARM ;
9549: mu2=mu[j][(int) age]/stepm*YEARM;
9550: c12=cv12/sqrt(v1*v2);
9551: /* Computing eigen value of matrix of covariance */
9552: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
9553: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
9554: if ((lc2 <0) || (lc1 <0) ){
9555: if(first2==1){
9556: first1=0;
9557: 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);
9558: }
9559: 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);
9560: /* lc1=fabs(lc1); */ /* If we want to have them positive */
9561: /* lc2=fabs(lc2); */
9562: }
1.220 brouard 9563:
1.222 brouard 9564: /* Eigen vectors */
1.280 brouard 9565: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
9566: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
9567: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
9568: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
9569: }else
9570: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 9571: /*v21=sqrt(1.-v11*v11); *//* error */
9572: v21=(lc1-v1)/cv12*v11;
9573: v12=-v21;
9574: v22=v11;
9575: tnalp=v21/v11;
9576: if(first1==1){
9577: first1=0;
9578: 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);
9579: }
9580: 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);
9581: /*printf(fignu*/
9582: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
9583: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
9584: if(first==1){
9585: first=0;
9586: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
9587: fprintf(ficgp,"\nset parametric;unset label");
9588: 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);
9589: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 9590: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 9591: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 9592: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 9593: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
9594: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
9595: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
9596: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
9597: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
9598: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
9599: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
9600: 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 9601: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
9602: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 9603: }else{
9604: first=0;
9605: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
9606: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
9607: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
9608: 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 9609: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
9610: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 9611: }/* if first */
9612: } /* age mod 5 */
9613: } /* end loop age */
9614: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
9615: first=1;
9616: } /*l12 */
9617: } /* k12 */
9618: } /*l1 */
9619: }/* k1 */
1.332 brouard 9620: } /* loop on combination of covariates j1 */
1.326 brouard 9621: } /* loop on nres */
1.222 brouard 9622: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
9623: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
9624: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
9625: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
9626: free_vector(xp,1,npar);
9627: fclose(ficresprob);
9628: fclose(ficresprobcov);
9629: fclose(ficresprobcor);
9630: fflush(ficgp);
9631: fflush(fichtmcov);
9632: }
1.126 brouard 9633:
9634:
9635: /******************* Printing html file ***********/
1.201 brouard 9636: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 9637: int lastpass, int stepm, int weightopt, char model[],\
9638: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.296 brouard 9639: int popforecast, int mobilav, int prevfcast, int mobilavproj, int prevbcast, int estepm , \
9640: double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \
9641: double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){
1.359 brouard 9642: int jj1, k1, cpt, nres;
1.319 brouard 9643: /* In fact some results are already printed in fichtm which is open */
1.126 brouard 9644: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
9645: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
9646: </ul>");
1.319 brouard 9647: /* fprintf(fichtm,"<ul><li> model=1+age+%s\n \ */
9648: /* </ul>", model); */
1.214 brouard 9649: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
9650: 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",
9651: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
1.332 brouard 9652: 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 9653: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
9654: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 9655: fprintf(fichtm,"\
9656: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 9657: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 9658: fprintf(fichtm,"\
1.217 brouard 9659: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
9660: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
9661: fprintf(fichtm,"\
1.288 brouard 9662: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 9663: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 9664: fprintf(fichtm,"\
1.288 brouard 9665: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 9666: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
9667: fprintf(fichtm,"\
1.211 brouard 9668: - (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 9669: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 9670: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 9671: if(prevfcast==1){
9672: fprintf(fichtm,"\
9673: - Prevalence projections by age and states: \
1.201 brouard 9674: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 9675: }
1.126 brouard 9676:
9677:
1.225 brouard 9678: m=pow(2,cptcoveff);
1.222 brouard 9679: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 9680:
1.317 brouard 9681: fprintf(fichtm," \n<ul><li><b>Graphs (first order)</b></li><p>");
1.264 brouard 9682:
9683: jj1=0;
9684:
9685: fprintf(fichtm," \n<ul>");
1.337 brouard 9686: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
9687: /* k1=nres; */
1.338 brouard 9688: k1=TKresult[nres];
9689: if(TKresult[nres]==0)k1=1; /* To be checked for no result */
1.337 brouard 9690: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
9691: /* if(m != 1 && TKresult[nres]!= k1) */
9692: /* continue; */
1.264 brouard 9693: jj1++;
9694: if (cptcovn > 0) {
9695: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
1.337 brouard 9696: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
9697: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 9698: }
1.337 brouard 9699: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
9700: /* fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
9701: /* } */
9702: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9703: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
9704: /* } */
1.264 brouard 9705: fprintf(fichtm,"\">");
9706:
9707: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
9708: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 9709: for (cpt=1; cpt<=cptcovs;cpt++){
9710: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 9711: }
1.337 brouard 9712: /* fprintf(fichtm,"************ Results for covariates"); */
9713: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
9714: /* fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
9715: /* } */
9716: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9717: /* fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
9718: /* } */
1.264 brouard 9719: if(invalidvarcomb[k1]){
9720: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
9721: continue;
9722: }
9723: fprintf(fichtm,"</a></li>");
9724: } /* cptcovn >0 */
9725: }
1.317 brouard 9726: fprintf(fichtm," \n</ul>");
1.264 brouard 9727:
1.222 brouard 9728: jj1=0;
1.237 brouard 9729:
1.337 brouard 9730: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
9731: /* k1=nres; */
1.338 brouard 9732: k1=TKresult[nres];
9733: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9734: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
9735: /* if(m != 1 && TKresult[nres]!= k1) */
9736: /* continue; */
1.220 brouard 9737:
1.222 brouard 9738: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
9739: jj1++;
9740: if (cptcovn > 0) {
1.264 brouard 9741: fprintf(fichtm,"\n<p><a name=\"rescov");
1.337 brouard 9742: for (cpt=1; cpt<=cptcovs;cpt++){
9743: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 9744: }
1.337 brouard 9745: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9746: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
9747: /* } */
1.264 brouard 9748: fprintf(fichtm,"\"</a>");
9749:
1.222 brouard 9750: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 9751: for (cpt=1; cpt<=cptcovs;cpt++){
9752: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
9753: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 9754: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
9755: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 9756: }
1.230 brouard 9757: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.338 brouard 9758: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.222 brouard 9759: if(invalidvarcomb[k1]){
9760: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
9761: printf("\nCombination (%d) ignored because no cases \n",k1);
9762: continue;
9763: }
9764: }
9765: /* aij, bij */
1.259 brouard 9766: 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 9767: <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 9768: /* Pij */
1.241 brouard 9769: 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> \
9770: <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 9771: /* Quasi-incidences */
9772: 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 9773: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 9774: 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 9775: 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> \
9776: <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 9777: /* Survival functions (period) in state j */
9778: for(cpt=1; cpt<=nlstate;cpt++){
1.359 brouard 9779: 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 9780: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
9781: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.222 brouard 9782: }
9783: /* State specific survival functions (period) */
9784: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 9785: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
1.359 brouard 9786: 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 9787: <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);
9788: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
9789: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.222 brouard 9790: }
1.288 brouard 9791: /* Period (forward stable) prevalence in each health state */
1.222 brouard 9792: for(cpt=1; cpt<=nlstate;cpt++){
1.359 brouard 9793: 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 9794: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
1.329 brouard 9795: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.222 brouard 9796: }
1.296 brouard 9797: if(prevbcast==1){
1.288 brouard 9798: /* Backward prevalence in each health state */
1.222 brouard 9799: for(cpt=1; cpt<=nlstate;cpt++){
1.338 brouard 9800: 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);
9801: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJB_"),subdirf2(optionfilefiname,"PIJB_"));
9802: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.222 brouard 9803: }
1.217 brouard 9804: }
1.222 brouard 9805: if(prevfcast==1){
1.288 brouard 9806: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 9807: for(cpt=1; cpt<=nlstate;cpt++){
1.314 brouard 9808: 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);
9809: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"F_"),subdirf2(optionfilefiname,"F_"));
9810: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",
9811: subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 9812: }
9813: }
1.296 brouard 9814: if(prevbcast==1){
1.268 brouard 9815: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
9816: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 9817: 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 9818: 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 \
9819: 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 9820: 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);
9821: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"FB_"),subdirf2(optionfilefiname,"FB_"));
9822: fprintf(fichtm," <img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
1.268 brouard 9823: }
9824: }
1.220 brouard 9825:
1.222 brouard 9826: for(cpt=1; cpt<=nlstate;cpt++) {
1.314 brouard 9827: 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);
9828: fprintf(fichtm," (data from text file <a href=\"%s.txt\"> %s.txt</a>)\n<br>",subdirf2(optionfilefiname,"E_"),subdirf2(optionfilefiname,"E_"));
9829: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres );
1.222 brouard 9830: }
9831: /* } /\* end i1 *\/ */
1.337 brouard 9832: }/* End k1=nres */
1.222 brouard 9833: fprintf(fichtm,"</ul>");
1.126 brouard 9834:
1.222 brouard 9835: fprintf(fichtm,"\
1.126 brouard 9836: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 9837: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 9838: - 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 9839: But because parameters are usually highly correlated (a higher incidence of disability \
9840: and a higher incidence of recovery can give very close observed transition) it might \
9841: be very useful to look not only at linear confidence intervals estimated from the \
9842: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
9843: (parameters) of the logistic regression, it might be more meaningful to visualize the \
9844: covariance matrix of the one-step probabilities. \
9845: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 9846:
1.222 brouard 9847: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
9848: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
9849: fprintf(fichtm,"\
1.126 brouard 9850: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 9851: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 9852:
1.222 brouard 9853: fprintf(fichtm,"\
1.126 brouard 9854: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 9855: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
9856: fprintf(fichtm,"\
1.126 brouard 9857: - 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): \
9858: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 9859: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 9860: fprintf(fichtm,"\
1.126 brouard 9861: - (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): \
9862: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 9863: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 9864: fprintf(fichtm,"\
1.288 brouard 9865: - 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 9866: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
9867: fprintf(fichtm,"\
1.128 brouard 9868: - 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 9869: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
9870: fprintf(fichtm,"\
1.288 brouard 9871: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 9872: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 9873:
9874: /* if(popforecast==1) fprintf(fichtm,"\n */
9875: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
9876: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
9877: /* <br>",fileres,fileres,fileres,fileres); */
9878: /* else */
1.338 brouard 9879: /* 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 9880: fflush(fichtm);
1.126 brouard 9881:
1.225 brouard 9882: m=pow(2,cptcoveff);
1.222 brouard 9883: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 9884:
1.317 brouard 9885: fprintf(fichtm," <ul><li><b>Graphs (second order)</b></li><p>");
9886:
9887: jj1=0;
9888:
9889: fprintf(fichtm," \n<ul>");
1.337 brouard 9890: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
9891: /* k1=nres; */
1.338 brouard 9892: k1=TKresult[nres];
1.337 brouard 9893: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
9894: /* if(m != 1 && TKresult[nres]!= k1) */
9895: /* continue; */
1.317 brouard 9896: jj1++;
9897: if (cptcovn > 0) {
9898: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescovsecond");
1.337 brouard 9899: for (cpt=1; cpt<=cptcovs;cpt++){
9900: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 9901: }
9902: fprintf(fichtm,"\">");
9903:
9904: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
9905: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 9906: for (cpt=1; cpt<=cptcovs;cpt++){
9907: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 9908: }
9909: if(invalidvarcomb[k1]){
9910: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
9911: continue;
9912: }
9913: fprintf(fichtm,"</a></li>");
9914: } /* cptcovn >0 */
1.337 brouard 9915: } /* End nres */
1.317 brouard 9916: fprintf(fichtm," \n</ul>");
9917:
1.222 brouard 9918: jj1=0;
1.237 brouard 9919:
1.241 brouard 9920: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9921: /* k1=nres; */
1.338 brouard 9922: k1=TKresult[nres];
9923: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9924: /* for(k1=1; k1<=m;k1++){ */
9925: /* if(m != 1 && TKresult[nres]!= k1) */
9926: /* continue; */
1.222 brouard 9927: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
9928: jj1++;
1.126 brouard 9929: if (cptcovn > 0) {
1.317 brouard 9930: fprintf(fichtm,"\n<p><a name=\"rescovsecond");
1.337 brouard 9931: for (cpt=1; cpt<=cptcovs;cpt++){
9932: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 9933: }
9934: fprintf(fichtm,"\"</a>");
9935:
1.126 brouard 9936: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 9937: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcoveff number of variables */
9938: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
9939: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 9940: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
1.317 brouard 9941: }
1.237 brouard 9942:
1.338 brouard 9943: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.220 brouard 9944:
1.222 brouard 9945: if(invalidvarcomb[k1]){
9946: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
9947: continue;
9948: }
1.337 brouard 9949: } /* If cptcovn >0 */
1.126 brouard 9950: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 9951: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.314 brouard 9952: 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);
9953: fprintf(fichtm," (data from text file <a href=\"%s\">%s</a>)\n <br>",subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
9954: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"V_"), cpt,k1,nres);
1.126 brouard 9955: }
9956: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.360 brouard 9957: health expectancies in each live state (1 to %d) with confidence intervals \
9958: on left y-scale as well as proportions of time spent in each live state \
9959: (with confidence intervals) on right y-scale 0 to 100%%.\
9960: If popbased=1 the smooth (due to the model) \
1.128 brouard 9961: true period expectancies (those weighted with period prevalences are also\
9962: drawn in addition to the population based expectancies computed using\
1.314 brouard 9963: 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);
9964: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>) \n<br>",subdirf2(optionfilefiname,"T_"),subdirf2(optionfilefiname,"T_"));
9965: fprintf(fichtm,"<img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 9966: /* } /\* end i1 *\/ */
1.241 brouard 9967: }/* End nres */
1.222 brouard 9968: fprintf(fichtm,"</ul>");
9969: fflush(fichtm);
1.126 brouard 9970: }
9971:
9972: /******************* Gnuplot file **************/
1.296 brouard 9973: 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 9974:
1.354 brouard 9975: char dirfileres[256],optfileres[256];
9976: char gplotcondition[256], gplotlabel[256];
1.343 brouard 9977: 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 9978: int lv=0, vlv=0, kl=0;
1.130 brouard 9979: int ng=0;
1.201 brouard 9980: int vpopbased;
1.223 brouard 9981: int ioffset; /* variable offset for columns */
1.270 brouard 9982: int iyearc=1; /* variable column for year of projection */
9983: int iagec=1; /* variable column for age of projection */
1.235 brouard 9984: int nres=0; /* Index of resultline */
1.266 brouard 9985: int istart=1; /* For starting graphs in projections */
1.219 brouard 9986:
1.126 brouard 9987: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
9988: /* printf("Problem with file %s",optionfilegnuplot); */
9989: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
9990: /* } */
9991:
9992: /*#ifdef windows */
9993: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 9994: /*#endif */
1.225 brouard 9995: m=pow(2,cptcoveff);
1.126 brouard 9996:
1.274 brouard 9997: /* diagram of the model */
9998: fprintf(ficgp,"\n#Diagram of the model \n");
9999: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
10000: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
10001: 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);
10002:
1.343 brouard 10003: 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 10004: fprintf(ficgp,"\n#show arrow\nunset label\n");
10005: 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);
10006: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
10007: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
10008: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
10009: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
10010:
1.202 brouard 10011: /* Contribution to likelihood */
10012: /* Plot the probability implied in the likelihood */
1.223 brouard 10013: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
10014: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
10015: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
10016: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 10017: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 10018: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
10019: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 10020: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
10021: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
10022: 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));
10023: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
10024: 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));
10025: for (i=1; i<= nlstate ; i ++) {
10026: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
10027: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
10028: 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);
10029: for (j=2; j<= nlstate+ndeath ; j ++) {
10030: 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);
10031: }
10032: fprintf(ficgp,";\nset out; unset ylabel;\n");
10033: }
10034: /* 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 */
10035: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
10036: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
10037: fprintf(ficgp,"\nset out;unset log\n");
10038: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 10039:
1.343 brouard 10040: /* Plot the probability implied in the likelihood by covariate value */
10041: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
10042: /* if(debugILK==1){ */
10043: for(kf=1; kf <= ncovf; kf++){ /* For each simple dummy covariate of the model */
1.347 brouard 10044: kvar=Tvar[TvarFind[kf]]; /* variable name */
10045: /* k=18+Tvar[TvarFind[kf]];/\*offset because there are 18 columns in the ILK_ file but could be placed else where *\/ */
1.350 brouard 10046: /* k=18+kf;/\*offset because there are 18 columns in the ILK_ file *\/ */
1.356 brouard 10047: /* k=19+kf;/\*offset because there are 19 columns in the ILK_ file *\/ */
1.355 brouard 10048: 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 10049: for (i=1; i<= nlstate ; i ++) {
10050: fprintf(ficgp,"\nset out \"%s-p%dj-%d.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i,kvar);
10051: fprintf(ficgp,"unset log;\n# For each simple dummy covariate of the model \n plot \"%s\"",subdirf(fileresilk));
1.348 brouard 10052: if(gnuplotversion >=5.2){ /* Former gnuplot versions do not have variable pointsize!! */
10053: 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);
10054: for (j=2; j<= nlstate+ndeath ; j ++) {
10055: 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);
10056: }
10057: }else{
10058: 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);
10059: for (j=2; j<= nlstate+ndeath ; j ++) {
10060: 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);
10061: }
1.343 brouard 10062: }
10063: fprintf(ficgp,";\nset out; unset ylabel;\n");
10064: }
10065: } /* End of each covariate dummy */
10066: for(ncovv=1, iposold=0, kk=0; ncovv <= ncovvt ; ncovv++){
10067: /* Other example V1 + V3 + V5 + age*V1 + age*V3 + age*V5 + V1*V3 + V3*V5 + V1*V5
10068: * kmodel = 1 2 3 4 5 6 7 8 9
10069: * varying 1 2 3 4 5
10070: * ncovv 1 2 3 4 5 6 7 8
10071: * TvarVV[ncovv] V3 5 1 3 3 5 1 5
10072: * TvarVVind[ncovv]=kmodel 2 3 7 7 8 8 9 9
10073: * TvarFind[kmodel] 1 0 0 0 0 0 0 0 0
10074: * kdata ncovcol=[V1 V2] nqv=0 ntv=[V3 V4] nqtv=V5
10075: * Dummy[kmodel] 0 0 1 2 2 3 1 1 1
10076: */
10077: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
10078: kvar=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
10079: /* 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]); */
10080: if(ipos!=iposold){ /* Not a product or first of a product */
10081: /* printf(" %d",ipos); */
10082: /* fprintf(ficresilk," V%d",TvarVV[ncovv]); */
10083: /* printf(" DebugILK ficgp suite ipos=%d != iposold=%d\n", ipos, iposold); */
10084: kk++; /* Position of the ncovv column in ILK_ */
10085: k=18+ncovf+kk; /*offset because there are 18 columns in the ILK_ file plus ncovf fixed covariate */
10086: 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) */
10087: for (i=1; i<= nlstate ; i ++) {
10088: fprintf(ficgp,"\nset out \"%s-p%dj-%d.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i,kvar);
10089: fprintf(ficgp,"unset log;\n# For each simple dummy covariate of the model \n plot \"%s\"",subdirf(fileresilk));
10090:
1.348 brouard 10091: /* printf("Before DebugILK gnuplotversion=%g >=5.2\n",gnuplotversion); */
1.343 brouard 10092: if(gnuplotversion >=5.2){ /* Former gnuplot versions do not have variable pointsize!! */
10093: /* printf("DebugILK gnuplotversion=%g >=5.2\n",gnuplotversion); */
10094: 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);
10095: for (j=2; j<= nlstate+ndeath ; j ++) {
10096: 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);
10097: }
10098: }else{
10099: /* printf("DebugILK gnuplotversion=%g <5.2\n",gnuplotversion); */
10100: 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);
10101: for (j=2; j<= nlstate+ndeath ; j ++) {
10102: 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);
10103: }
10104: }
10105: fprintf(ficgp,";\nset out; unset ylabel;\n");
10106: }
10107: }/* End if dummy varying */
10108: }else{ /*Product */
10109: /* printf("*"); */
10110: /* fprintf(ficresilk,"*"); */
10111: }
10112: iposold=ipos;
10113: } /* For each time varying covariate */
10114: /* } /\* debugILK==1 *\/ */
10115: /* 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 */
10116: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
10117: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
10118: fprintf(ficgp,"\nset out;unset log\n");
10119: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
10120:
10121:
10122:
1.126 brouard 10123: strcpy(dirfileres,optionfilefiname);
10124: strcpy(optfileres,"vpl");
1.223 brouard 10125: /* 1eme*/
1.238 brouard 10126: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
1.337 brouard 10127: /* for (k1=1; k1<= m ; k1 ++){ /\* For each valid combination of covariate *\/ */
1.236 brouard 10128: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10129: k1=TKresult[nres];
1.338 brouard 10130: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.238 brouard 10131: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.337 brouard 10132: /* if(m != 1 && TKresult[nres]!= k1) */
10133: /* continue; */
1.238 brouard 10134: /* We are interested in selected combination by the resultline */
1.246 brouard 10135: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 10136: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 10137: strcpy(gplotlabel,"(");
1.337 brouard 10138: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10139: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10140: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10141:
10142: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate k get corresponding value lv for combination k1 *\/ */
10143: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the value of the covariate corresponding to k1 combination *\\/ *\/ */
10144: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
10145: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10146: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10147: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10148: /* vlv= nbcode[Tvaraff[k]][lv]; /\* vlv is the value of the covariate lv, 0 or 1 *\/ */
10149: /* /\* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv *\/ */
10150: /* /\* printf(" V%d=%d ",Tvaraff[k],vlv); *\/ */
10151: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10152: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10153: /* } */
10154: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10155: /* /\* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); *\/ */
10156: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
10157: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.264 brouard 10158: }
10159: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 10160: /* printf("\n#\n"); */
1.238 brouard 10161: fprintf(ficgp,"\n#\n");
10162: if(invalidvarcomb[k1]){
1.260 brouard 10163: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 10164: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10165: continue;
10166: }
1.235 brouard 10167:
1.241 brouard 10168: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
10169: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 10170: /* 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 10171: fprintf(ficgp,"set title \"Alive state %d %s model=1+age+%s\" font \"Helvetica,12\"\n",cpt,gplotlabel,model);
1.260 brouard 10172: 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);
10173: /* 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); */
10174: /* k1-1 error should be nres-1*/
1.238 brouard 10175: for (i=1; i<= nlstate ; i ++) {
10176: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
10177: else fprintf(ficgp," %%*lf (%%*lf)");
10178: }
1.288 brouard 10179: 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 10180: for (i=1; i<= nlstate ; i ++) {
10181: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
10182: else fprintf(ficgp," %%*lf (%%*lf)");
10183: }
1.260 brouard 10184: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 10185: for (i=1; i<= nlstate ; i ++) {
10186: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
10187: else fprintf(ficgp," %%*lf (%%*lf)");
10188: }
1.265 brouard 10189: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
10190:
10191: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
10192: if(cptcoveff ==0){
1.271 brouard 10193: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 10194: }else{
10195: kl=0;
10196: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 10197: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
10198: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.265 brouard 10199: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
10200: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
10201: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
10202: vlv= nbcode[Tvaraff[k]][lv];
10203: kl++;
10204: /* 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 *\/ */
10205: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
10206: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
10207: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
10208: if(k==cptcoveff){
10209: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
10210: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
10211: }else{
10212: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
10213: kl++;
10214: }
10215: } /* end covariate */
10216: } /* end if no covariate */
10217:
1.296 brouard 10218: if(prevbcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
1.238 brouard 10219: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 10220: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 10221: if(cptcoveff ==0){
1.245 brouard 10222: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 10223: }else{
10224: kl=0;
10225: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 10226: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
10227: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.238 brouard 10228: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
10229: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
10230: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 10231: /* vlv= nbcode[Tvaraff[k]][lv]; */
10232: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.223 brouard 10233: kl++;
1.238 brouard 10234: /* 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 *\/ */
10235: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
10236: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
10237: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
10238: if(k==cptcoveff){
1.245 brouard 10239: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 10240: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 10241: }else{
1.332 brouard 10242: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]);
1.238 brouard 10243: kl++;
10244: }
10245: } /* end covariate */
10246: } /* end if no covariate */
1.296 brouard 10247: if(prevbcast == 1){
1.268 brouard 10248: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
10249: /* k1-1 error should be nres-1*/
10250: for (i=1; i<= nlstate ; i ++) {
10251: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
10252: else fprintf(ficgp," %%*lf (%%*lf)");
10253: }
1.271 brouard 10254: 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 10255: for (i=1; i<= nlstate ; i ++) {
10256: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
10257: else fprintf(ficgp," %%*lf (%%*lf)");
10258: }
1.276 brouard 10259: 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 10260: for (i=1; i<= nlstate ; i ++) {
10261: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
10262: else fprintf(ficgp," %%*lf (%%*lf)");
10263: }
1.274 brouard 10264: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 10265: } /* end if backprojcast */
1.296 brouard 10266: } /* end if prevbcast */
1.276 brouard 10267: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
10268: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 10269: } /* nres */
1.337 brouard 10270: /* } /\* k1 *\/ */
1.201 brouard 10271: } /* cpt */
1.235 brouard 10272:
10273:
1.126 brouard 10274: /*2 eme*/
1.337 brouard 10275: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 10276: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10277: k1=TKresult[nres];
1.338 brouard 10278: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 10279: /* if(m != 1 && TKresult[nres]!= k1) */
10280: /* continue; */
1.238 brouard 10281: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 10282: strcpy(gplotlabel,"(");
1.337 brouard 10283: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10284: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10285: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10286: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
10287: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
10288: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
10289: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10290: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10291: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10292: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
10293: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10294: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10295: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10296: /* } */
10297: /* /\* for(k=1; k <= ncovds; k++){ *\/ */
10298: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10299: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
10300: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
10301: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 10302: }
1.264 brouard 10303: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 10304: fprintf(ficgp,"\n#\n");
1.223 brouard 10305: if(invalidvarcomb[k1]){
10306: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10307: continue;
10308: }
1.219 brouard 10309:
1.241 brouard 10310: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 10311: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 10312: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
10313: if(vpopbased==0){
1.360 brouard 10314: 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 10315: }else
1.238 brouard 10316: fprintf(ficgp,"\nreplot ");
1.360 brouard 10317: 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 10318: k=2*i;
1.360 brouard 10319: 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 */
10320: for (j=1; j<= nlstate+1 ; j ++) { /* e.. e.1 e.2 again j-1 is the state of end, wlim_i eij*/
10321: 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 */
10322: else fprintf(ficgp," %%*lf (%%*lf)"); /* skipping that field with a star */
1.238 brouard 10323: }
10324: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
1.360 brouard 10325: 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 10326: 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 10327: for (j=1; j<= nlstate+1 ; j ++) {
10328: if (j==i) fprintf(ficgp," %%lf (%%lf)");
10329: else fprintf(ficgp," %%*lf (%%*lf)");
10330: }
10331: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 10332: 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 10333: for (j=1; j<= nlstate+1 ; j ++) {
10334: if (j==i) fprintf(ficgp," %%lf (%%lf)");
10335: else fprintf(ficgp," %%*lf (%%*lf)");
10336: }
1.360 brouard 10337: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0,\\\n"); /* ,\\\n added for th percentage graphs */
1.238 brouard 10338: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
10339: } /* state */
1.360 brouard 10340: /* again for the percentag spent in state i-1=1 to i-1=nlstate */
10341: for (i=2; i<= nlstate+1 ; i ++) { /* For state i-1=0 is LE, while i-1=1 to nlstate are origin state */
10342: k=2*i;
10343: 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 */
10344: for (j=1; j<= nlstate ; j ++)
10345: fprintf(ficgp," %%*lf (%%*lf)"); /* Skipping TLE and LE to read %LE only */
10346: for (j=1; j<= nlstate+1 ; j ++) { /* e.. e.1 e.2 again j-1 is the state of end, wlim_i eij*/
10347: 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 */
10348: else fprintf(ficgp," %%*lf (%%*lf)"); /* skipping that field with a star */
10349: }
10350: if (i== 1) fprintf(ficgp,"\" t\"%%TLE\" w l lt %d axis x1y2, \\\n",i); /* Not used */
10351: 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 */
10352: 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);
10353: for (j=1; j<= nlstate ; j ++)
10354: fprintf(ficgp," %%*lf (%%*lf)"); /* Skipping TLE and LE to read %LE only */
10355: for (j=1; j<= nlstate+1 ; j ++) {
10356: if (j==i) fprintf(ficgp," %%lf (%%lf)");
10357: else fprintf(ficgp," %%*lf (%%*lf)");
10358: }
10359: fprintf(ficgp,"\" t\"\" w l lt 0 axis x1y2,");
10360: 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);
10361: for (j=1; j<= nlstate ; j ++)
10362: fprintf(ficgp," %%*lf (%%*lf)"); /* Skipping TLE and LE to read %LE only */
10363: for (j=1; j<= nlstate+1 ; j ++) {
10364: if (j==i) fprintf(ficgp," %%lf (%%lf)");
10365: else fprintf(ficgp," %%*lf (%%*lf)");
10366: }
10367: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0 axis x1y2");
10368: else fprintf(ficgp,"\" t\"\" w l lt 0 axis x1y2,\\\n");
10369: } /* state for percent */
1.238 brouard 10370: } /* vpopbased */
1.264 brouard 10371: 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 10372: } /* end nres */
1.337 brouard 10373: /* } /\* k1 end 2 eme*\/ */
1.238 brouard 10374:
10375:
10376: /*3eme*/
1.337 brouard 10377: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 10378: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10379: k1=TKresult[nres];
1.338 brouard 10380: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 10381: /* if(m != 1 && TKresult[nres]!= k1) */
10382: /* continue; */
1.238 brouard 10383:
1.332 brouard 10384: for (cpt=1; cpt<= nlstate ; cpt ++) { /* Fragile no verification of covariate values */
1.261 brouard 10385: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 10386: strcpy(gplotlabel,"(");
1.337 brouard 10387: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10388: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10389: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10390: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
10391: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
10392: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
10393: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10394: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10395: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10396: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
10397: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10398: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10399: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10400: /* } */
10401: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10402: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
10403: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
10404: }
1.264 brouard 10405: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 10406: fprintf(ficgp,"\n#\n");
10407: if(invalidvarcomb[k1]){
10408: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10409: continue;
10410: }
10411:
10412: /* k=2+nlstate*(2*cpt-2); */
10413: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 10414: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 10415: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 10416: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 10417: 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 10418: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
10419: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
10420: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
10421: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
10422: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
10423: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 10424:
1.238 brouard 10425: */
10426: for (i=1; i< nlstate ; i ++) {
1.261 brouard 10427: 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 10428: /* 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 10429:
1.238 brouard 10430: }
1.261 brouard 10431: 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 10432: }
1.264 brouard 10433: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 10434: } /* end nres */
1.337 brouard 10435: /* } /\* end kl 3eme *\/ */
1.126 brouard 10436:
1.223 brouard 10437: /* 4eme */
1.201 brouard 10438: /* Survival functions (period) from state i in state j by initial state i */
1.337 brouard 10439: /* for (k1=1; k1<=m; k1++){ /\* For each covariate and each value *\/ */
1.238 brouard 10440: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10441: k1=TKresult[nres];
1.338 brouard 10442: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 10443: /* if(m != 1 && TKresult[nres]!= k1) */
10444: /* continue; */
1.238 brouard 10445: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 10446: strcpy(gplotlabel,"(");
1.337 brouard 10447: fprintf(ficgp,"\n#\n#\n# Survival functions in state %d : 'LIJ_' files, cov=%d state=%d", cpt, k1, cpt);
10448: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10449: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10450: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10451: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
10452: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
10453: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
10454: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10455: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10456: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10457: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
10458: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10459: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10460: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10461: /* } */
10462: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10463: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
10464: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 10465: }
1.264 brouard 10466: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 10467: fprintf(ficgp,"\n#\n");
10468: if(invalidvarcomb[k1]){
10469: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10470: continue;
1.223 brouard 10471: }
1.238 brouard 10472:
1.241 brouard 10473: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 10474: 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 10475: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
10476: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
10477: k=3;
10478: for (i=1; i<= nlstate ; i ++){
10479: if(i==1){
10480: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
10481: }else{
10482: fprintf(ficgp,", '' ");
10483: }
10484: l=(nlstate+ndeath)*(i-1)+1;
10485: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
10486: for (j=2; j<= nlstate+ndeath ; j ++)
10487: fprintf(ficgp,"+$%d",k+l+j-1);
10488: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
10489: } /* nlstate */
1.264 brouard 10490: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 10491: } /* end cpt state*/
10492: } /* end nres */
1.337 brouard 10493: /* } /\* end covariate k1 *\/ */
1.238 brouard 10494:
1.220 brouard 10495: /* 5eme */
1.201 brouard 10496: /* Survival functions (period) from state i in state j by final state j */
1.337 brouard 10497: /* for (k1=1; k1<= m ; k1++){ /\* For each covariate combination if any *\/ */
1.238 brouard 10498: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10499: k1=TKresult[nres];
1.338 brouard 10500: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 10501: /* if(m != 1 && TKresult[nres]!= k1) */
10502: /* continue; */
1.238 brouard 10503: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 10504: strcpy(gplotlabel,"(");
1.238 brouard 10505: 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 10506: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10507: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10508: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10509: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
10510: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
10511: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
10512: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10513: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10514: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10515: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
10516: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10517: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10518: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10519: /* } */
10520: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10521: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
10522: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 10523: }
1.264 brouard 10524: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 10525: fprintf(ficgp,"\n#\n");
10526: if(invalidvarcomb[k1]){
10527: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10528: continue;
10529: }
1.227 brouard 10530:
1.241 brouard 10531: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 10532: 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 10533: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
10534: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
10535: k=3;
10536: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
10537: if(j==1)
10538: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
10539: else
10540: fprintf(ficgp,", '' ");
10541: l=(nlstate+ndeath)*(cpt-1) +j;
10542: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
10543: /* for (i=2; i<= nlstate+ndeath ; i ++) */
10544: /* fprintf(ficgp,"+$%d",k+l+i-1); */
10545: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
10546: } /* nlstate */
10547: fprintf(ficgp,", '' ");
10548: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
10549: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
10550: l=(nlstate+ndeath)*(cpt-1) +j;
10551: if(j < nlstate)
10552: fprintf(ficgp,"$%d +",k+l);
10553: else
10554: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
10555: }
1.264 brouard 10556: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 10557: } /* end cpt state*/
1.337 brouard 10558: /* } /\* end covariate *\/ */
1.238 brouard 10559: } /* end nres */
1.227 brouard 10560:
1.220 brouard 10561: /* 6eme */
1.202 brouard 10562: /* CV preval stable (period) for each covariate */
1.337 brouard 10563: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 10564: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10565: k1=TKresult[nres];
1.338 brouard 10566: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 10567: /* if(m != 1 && TKresult[nres]!= k1) */
10568: /* continue; */
1.255 brouard 10569: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 10570: strcpy(gplotlabel,"(");
1.288 brouard 10571: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 10572: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10573: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10574: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10575: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
10576: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
10577: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
10578: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10579: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10580: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10581: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
10582: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10583: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10584: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10585: /* } */
10586: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10587: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
10588: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 10589: }
1.264 brouard 10590: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 10591: fprintf(ficgp,"\n#\n");
1.223 brouard 10592: if(invalidvarcomb[k1]){
1.227 brouard 10593: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10594: continue;
1.223 brouard 10595: }
1.227 brouard 10596:
1.241 brouard 10597: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 10598: 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 10599: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 10600: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 10601: k=3; /* Offset */
1.255 brouard 10602: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 10603: if(i==1)
10604: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
10605: else
10606: fprintf(ficgp,", '' ");
1.255 brouard 10607: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 10608: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
10609: for (j=2; j<= nlstate ; j ++)
10610: fprintf(ficgp,"+$%d",k+l+j-1);
10611: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 10612: } /* nlstate */
1.264 brouard 10613: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 10614: } /* end cpt state*/
10615: } /* end covariate */
1.227 brouard 10616:
10617:
1.220 brouard 10618: /* 7eme */
1.296 brouard 10619: if(prevbcast == 1){
1.288 brouard 10620: /* CV backward prevalence for each covariate */
1.337 brouard 10621: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 10622: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10623: k1=TKresult[nres];
1.338 brouard 10624: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 10625: /* if(m != 1 && TKresult[nres]!= k1) */
10626: /* continue; */
1.268 brouard 10627: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 10628: strcpy(gplotlabel,"(");
1.288 brouard 10629: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 10630: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10631: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10632: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10633: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
10634: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
10635: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
10636: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10637: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10638: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10639: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
10640: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10641: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10642: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10643: /* } */
10644: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10645: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
10646: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 10647: }
1.264 brouard 10648: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 10649: fprintf(ficgp,"\n#\n");
10650: if(invalidvarcomb[k1]){
10651: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10652: continue;
10653: }
10654:
1.241 brouard 10655: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 10656: 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 10657: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 10658: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 10659: k=3; /* Offset */
1.268 brouard 10660: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 10661: if(i==1)
10662: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
10663: else
10664: fprintf(ficgp,", '' ");
10665: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 10666: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.324 brouard 10667: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
10668: /* 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 10669: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 10670: /* for (j=2; j<= nlstate ; j ++) */
10671: /* fprintf(ficgp,"+$%d",k+l+j-1); */
10672: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 10673: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 10674: } /* nlstate */
1.264 brouard 10675: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 10676: } /* end cpt state*/
10677: } /* end covariate */
1.296 brouard 10678: } /* End if prevbcast */
1.218 brouard 10679:
1.223 brouard 10680: /* 8eme */
1.218 brouard 10681: if(prevfcast==1){
1.288 brouard 10682: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 10683:
1.337 brouard 10684: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 10685: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10686: k1=TKresult[nres];
1.338 brouard 10687: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 10688: /* if(m != 1 && TKresult[nres]!= k1) */
10689: /* continue; */
1.211 brouard 10690: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 10691: strcpy(gplotlabel,"(");
1.288 brouard 10692: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 10693: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10694: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10695: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10696: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
10697: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
10698: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
10699: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10700: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10701: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10702: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
10703: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10704: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10705: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10706: /* } */
10707: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10708: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
10709: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 10710: }
1.264 brouard 10711: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 10712: fprintf(ficgp,"\n#\n");
10713: if(invalidvarcomb[k1]){
10714: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10715: continue;
10716: }
10717:
10718: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 10719: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 10720: 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 10721: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 10722: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 10723:
10724: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
10725: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
10726: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
10727: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 10728: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
10729: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
10730: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
10731: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 10732: if(i==istart){
1.227 brouard 10733: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
10734: }else{
10735: fprintf(ficgp,",\\\n '' ");
10736: }
10737: if(cptcoveff ==0){ /* No covariate */
10738: ioffset=2; /* Age is in 2 */
10739: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
10740: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
10741: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
10742: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
10743: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 10744: if(i==nlstate+1){
1.270 brouard 10745: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 10746: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
10747: fprintf(ficgp,",\\\n '' ");
10748: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 10749: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 10750: offyear, \
1.268 brouard 10751: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 10752: }else
1.227 brouard 10753: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
10754: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
10755: }else{ /* more than 2 covariates */
1.270 brouard 10756: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
10757: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
10758: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
10759: iyearc=ioffset-1;
10760: iagec=ioffset;
1.227 brouard 10761: fprintf(ficgp," u %d:(",ioffset);
10762: kl=0;
10763: strcpy(gplotcondition,"(");
1.351 brouard 10764: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate writing the chain of conditions *\/ */
1.332 brouard 10765: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
1.351 brouard 10766: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10767: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
10768: lv=Tvresult[nres][k];
10769: vlv=TinvDoQresult[nres][Tvresult[nres][k]];
1.227 brouard 10770: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
10771: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
10772: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 10773: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
1.351 brouard 10774: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
1.227 brouard 10775: kl++;
1.351 brouard 10776: /* sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); */
10777: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,lv, kl+1, vlv );
1.227 brouard 10778: kl++;
1.351 brouard 10779: if(k <cptcovs && cptcovs>1)
1.227 brouard 10780: sprintf(gplotcondition+strlen(gplotcondition)," && ");
10781: }
10782: strcpy(gplotcondition+strlen(gplotcondition),")");
10783: /* 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 *\/ */
10784: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
10785: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
10786: /* '' 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*/
10787: if(i==nlstate+1){
1.270 brouard 10788: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
10789: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 10790: fprintf(ficgp,",\\\n '' ");
1.270 brouard 10791: fprintf(ficgp," u %d:(",iagec);
10792: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
10793: iyearc, iagec, offyear, \
10794: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 10795: /* '' 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 10796: }else{
10797: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
10798: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
10799: }
10800: } /* end if covariate */
10801: } /* nlstate */
1.264 brouard 10802: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 10803: } /* end cpt state*/
10804: } /* end covariate */
10805: } /* End if prevfcast */
1.227 brouard 10806:
1.296 brouard 10807: if(prevbcast==1){
1.268 brouard 10808: /* Back projection from cross-sectional to stable (mixed) for each covariate */
10809:
1.337 brouard 10810: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.268 brouard 10811: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10812: k1=TKresult[nres];
1.338 brouard 10813: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 10814: /* if(m != 1 && TKresult[nres]!= k1) */
10815: /* continue; */
1.268 brouard 10816: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
10817: strcpy(gplotlabel,"(");
10818: 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 10819: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
10820: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10821: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10822: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
10823: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
10824: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
10825: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
10826: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
10827: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
10828: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
10829: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10830: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
10831: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
10832: /* } */
10833: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10834: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
10835: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.268 brouard 10836: }
10837: strcpy(gplotlabel+strlen(gplotlabel),")");
10838: fprintf(ficgp,"\n#\n");
10839: if(invalidvarcomb[k1]){
10840: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
10841: continue;
10842: }
10843:
10844: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
10845: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
10846: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
10847: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
10848: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
10849:
10850: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
10851: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
10852: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
10853: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
10854: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
10855: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
10856: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
10857: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
10858: if(i==istart){
10859: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
10860: }else{
10861: fprintf(ficgp,",\\\n '' ");
10862: }
1.351 brouard 10863: /* if(cptcoveff ==0){ /\* No covariate *\/ */
10864: if(cptcovs ==0){ /* No covariate */
1.268 brouard 10865: ioffset=2; /* Age is in 2 */
10866: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
10867: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
10868: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
10869: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
10870: fprintf(ficgp," u %d:(", ioffset);
10871: if(i==nlstate+1){
1.270 brouard 10872: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 10873: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
10874: fprintf(ficgp,",\\\n '' ");
10875: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 10876: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 10877: offbyear, \
10878: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
10879: }else
10880: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
10881: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
10882: }else{ /* more than 2 covariates */
1.270 brouard 10883: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
10884: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
10885: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
10886: iyearc=ioffset-1;
10887: iagec=ioffset;
1.268 brouard 10888: fprintf(ficgp," u %d:(",ioffset);
10889: kl=0;
10890: strcpy(gplotcondition,"(");
1.337 brouard 10891: for (k=1; k<=cptcovs; k++){ /* For each covariate k of the resultline, get corresponding value lv for combination k1 */
1.338 brouard 10892: if(Dummy[modelresult[nres][k]]==0){ /* To be verified */
1.337 brouard 10893: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate writing the chain of conditions *\/ */
10894: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
10895: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
10896: lv=Tvresult[nres][k];
10897: vlv=TinvDoQresult[nres][Tvresult[nres][k]];
10898: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
10899: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
10900: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
10901: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
10902: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
10903: kl++;
10904: /* sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); */
10905: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%lg " ,kl,Tvresult[nres][k], kl+1,TinvDoQresult[nres][Tvresult[nres][k]]);
10906: kl++;
1.338 brouard 10907: if(k <cptcovs && cptcovs>1)
1.337 brouard 10908: sprintf(gplotcondition+strlen(gplotcondition)," && ");
10909: }
1.268 brouard 10910: }
10911: strcpy(gplotcondition+strlen(gplotcondition),")");
10912: /* 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 *\/ */
10913: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
10914: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
10915: /* '' 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*/
10916: if(i==nlstate+1){
1.270 brouard 10917: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
10918: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 10919: fprintf(ficgp,",\\\n '' ");
1.270 brouard 10920: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 10921: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 10922: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
10923: iyearc,iagec,offbyear, \
10924: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 10925: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
10926: }else{
10927: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
10928: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
10929: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
10930: }
10931: } /* end if covariate */
10932: } /* nlstate */
10933: fprintf(ficgp,"\nset out; unset label;\n");
10934: } /* end cpt state*/
10935: } /* end covariate */
1.296 brouard 10936: } /* End if prevbcast */
1.268 brouard 10937:
1.227 brouard 10938:
1.238 brouard 10939: /* 9eme writing MLE parameters */
10940: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 10941: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 10942: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 10943: for(k=1; k <=(nlstate+ndeath); k++){
10944: if (k != i) {
1.227 brouard 10945: fprintf(ficgp,"# current state %d\n",k);
10946: for(j=1; j <=ncovmodel; j++){
10947: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
10948: jk++;
10949: }
10950: fprintf(ficgp,"\n");
1.126 brouard 10951: }
10952: }
1.223 brouard 10953: }
1.187 brouard 10954: fprintf(ficgp,"##############\n#\n");
1.227 brouard 10955:
1.145 brouard 10956: /*goto avoid;*/
1.238 brouard 10957: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
10958: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 10959: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
10960: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
10961: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
10962: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
10963: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
10964: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
10965: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
10966: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
10967: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
10968: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
10969: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
10970: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
10971: fprintf(ficgp,"#\n");
1.223 brouard 10972: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 10973: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.338 brouard 10974: fprintf(ficgp,"#model=1+age+%s \n",model);
1.238 brouard 10975: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.351 brouard 10976: /* fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/\* to be checked *\/ */
10977: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcovs,m);/* to be checked */
1.337 brouard 10978: /* for(k1=1; k1 <=m; k1++) /\* For each combination of covariate *\/ */
1.237 brouard 10979: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 10980: /* k1=nres; */
1.338 brouard 10981: k1=TKresult[nres];
10982: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 10983: fprintf(ficgp,"\n\n# Resultline k1=%d ",k1);
1.264 brouard 10984: strcpy(gplotlabel,"(");
1.276 brouard 10985: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.337 brouard 10986: for (k=1; k<=cptcovs; k++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
10987: /* for each resultline nres, and position k, Tvresult[nres][k] gives the name of the variable and
10988: TinvDoQresult[nres][Tvresult[nres][k]] gives its value double or integer) */
10989: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10990: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
10991: }
10992: /* if(m != 1 && TKresult[nres]!= k1) */
10993: /* continue; */
10994: /* fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1); */
10995: /* strcpy(gplotlabel,"("); */
10996: /* /\*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*\/ */
10997: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
10998: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
10999: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
11000: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
11001: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
11002: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
11003: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
11004: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
11005: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
11006: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
11007: /* } */
11008: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
11009: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
11010: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
11011: /* } */
1.264 brouard 11012: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 11013: fprintf(ficgp,"\n#\n");
1.264 brouard 11014: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 11015: fprintf(ficgp,"\nset key outside ");
11016: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
11017: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 11018: fprintf(ficgp,"\nset ter svg size 640, 480 ");
11019: if (ng==1){
11020: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
11021: fprintf(ficgp,"\nunset log y");
11022: }else if (ng==2){
11023: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
11024: fprintf(ficgp,"\nset log y");
11025: }else if (ng==3){
11026: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
11027: fprintf(ficgp,"\nset log y");
11028: }else
11029: fprintf(ficgp,"\nunset title ");
11030: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
11031: i=1;
11032: for(k2=1; k2<=nlstate; k2++) {
11033: k3=i;
11034: for(k=1; k<=(nlstate+ndeath); k++) {
11035: if (k != k2){
11036: switch( ng) {
11037: case 1:
11038: if(nagesqr==0)
11039: fprintf(ficgp," p%d+p%d*x",i,i+1);
11040: else /* nagesqr =1 */
11041: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
11042: break;
11043: case 2: /* ng=2 */
11044: if(nagesqr==0)
11045: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
11046: else /* nagesqr =1 */
11047: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
11048: break;
11049: case 3:
11050: if(nagesqr==0)
11051: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
11052: else /* nagesqr =1 */
11053: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
11054: break;
11055: }
11056: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 11057: ijp=1; /* product no age */
11058: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
11059: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 11060: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.329 brouard 11061: switch(Typevar[j]){
11062: case 1:
11063: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
11064: if(j==Tage[ij]) { /* Product by age To be looked at!!*//* Bug valgrind */
11065: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
11066: if(DummyV[j]==0){/* Bug valgrind */
11067: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
11068: }else{ /* quantitative */
11069: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
11070: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
11071: }
11072: ij++;
1.268 brouard 11073: }
1.237 brouard 11074: }
1.329 brouard 11075: }
11076: break;
11077: case 2:
11078: if(cptcovprod >0){
11079: if(j==Tprod[ijp]) { /* */
11080: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
11081: if(ijp <=cptcovprod) { /* Product */
11082: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
11083: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
11084: /* 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)]); */
11085: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
11086: }else{ /* Vn is dummy and Vm is quanti */
11087: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
11088: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
11089: }
11090: }else{ /* Vn*Vm Vn is quanti */
11091: if(DummyV[Tvard[ijp][2]]==0){
11092: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
11093: }else{ /* Both quanti */
11094: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
11095: }
1.268 brouard 11096: }
1.329 brouard 11097: ijp++;
1.237 brouard 11098: }
1.329 brouard 11099: } /* end Tprod */
11100: }
11101: break;
1.349 brouard 11102: case 3:
11103: if(cptcovdageprod >0){
11104: /* if(j==Tprod[ijp]) { */ /* not necessary */
11105: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
1.350 brouard 11106: if(ijp <=cptcovprod) { /* Product Vn*Vm and age*VN*Vm*/
11107: if(DummyV[Tvardk[ijp][1]]==0){/* Vn is dummy */
11108: if(DummyV[Tvardk[ijp][2]]==0){/* Vn and Vm are dummy */
1.349 brouard 11109: /* 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)]); */
11110: fprintf(ficgp,"+p%d*%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
11111: }else{ /* Vn is dummy and Vm is quanti */
11112: /* 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 11113: 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 11114: }
1.350 brouard 11115: }else{ /* age* Vn*Vm Vn is quanti HERE */
1.349 brouard 11116: if(DummyV[Tvard[ijp][2]]==0){
1.350 brouard 11117: 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 11118: }else{ /* Both quanti */
1.350 brouard 11119: 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 11120: }
11121: }
11122: ijp++;
11123: }
11124: /* } */ /* end Tprod */
11125: }
11126: break;
1.329 brouard 11127: case 0:
11128: /* simple covariate */
1.264 brouard 11129: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 11130: if(Dummy[j]==0){
11131: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
11132: }else{ /* quantitative */
11133: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 11134: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 11135: }
1.329 brouard 11136: /* end simple */
11137: break;
11138: default:
11139: break;
11140: } /* end switch */
1.237 brouard 11141: } /* end j */
1.329 brouard 11142: }else{ /* k=k2 */
11143: if(ng !=1 ){ /* For logit formula of log p11 is more difficult to get */
11144: fprintf(ficgp," (1.");i=i-ncovmodel;
11145: }else
11146: i=i-ncovmodel;
1.223 brouard 11147: }
1.227 brouard 11148:
1.223 brouard 11149: if(ng != 1){
11150: fprintf(ficgp,")/(1");
1.227 brouard 11151:
1.264 brouard 11152: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 11153: if(nagesqr==0)
1.264 brouard 11154: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 11155: else /* nagesqr =1 */
1.264 brouard 11156: 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 11157:
1.223 brouard 11158: ij=1;
1.329 brouard 11159: ijp=1;
11160: /* for(j=3; j <=ncovmodel-nagesqr; j++){ */
11161: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
11162: switch(Typevar[j]){
11163: case 1:
11164: if(cptcovage >0){
11165: if(j==Tage[ij]) { /* Bug valgrind */
11166: if(ij <=cptcovage) { /* Bug valgrind */
11167: if(DummyV[j]==0){/* Bug valgrind */
11168: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]); */
11169: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,nbcode[Tvar[j]][codtabm(k1,j)]); */
11170: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]);
11171: /* fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);; */
11172: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
11173: }else{ /* quantitative */
11174: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
11175: fprintf(ficgp,"+p%d*%f*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
11176: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
11177: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
11178: }
11179: ij++;
11180: }
11181: }
11182: }
11183: break;
11184: case 2:
11185: if(cptcovprod >0){
11186: if(j==Tprod[ijp]) { /* */
11187: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
11188: if(ijp <=cptcovprod) { /* Product */
11189: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
11190: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
11191: /* 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)]); */
11192: fprintf(ficgp,"+p%d*%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
11193: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
11194: }else{ /* Vn is dummy and Vm is quanti */
11195: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
11196: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
11197: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
11198: }
11199: }else{ /* Vn*Vm Vn is quanti */
11200: if(DummyV[Tvard[ijp][2]]==0){
11201: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
11202: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
11203: }else{ /* Both quanti */
11204: fprintf(ficgp,"+p%d*%f*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
11205: /* fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
11206: }
11207: }
11208: ijp++;
11209: }
11210: } /* end Tprod */
11211: } /* end if */
11212: break;
1.349 brouard 11213: case 3:
11214: if(cptcovdageprod >0){
11215: /* if(j==Tprod[ijp]) { /\* *\/ */
11216: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
11217: if(ijp <=cptcovprod) { /* Product */
1.350 brouard 11218: if(DummyV[Tvardk[ijp][1]]==0){/* Vn is dummy */
11219: if(DummyV[Tvardk[ijp][2]]==0){/* Vn and Vm are dummy */
1.349 brouard 11220: /* 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 11221: 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 11222: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
11223: }else{ /* Vn is dummy and Vm is quanti */
11224: /* 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 11225: 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 11226: /* fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
11227: }
11228: }else{ /* Vn*Vm Vn is quanti */
1.350 brouard 11229: if(DummyV[Tvardk[ijp][2]]==0){
11230: 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 11231: /* fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
11232: }else{ /* Both quanti */
1.350 brouard 11233: 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 11234: /* fprintf(ficgp,"+p%d*%f*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
11235: }
11236: }
11237: ijp++;
11238: }
11239: /* } /\* end Tprod *\/ */
11240: } /* end if */
11241: break;
1.329 brouard 11242: case 0:
11243: /* simple covariate */
11244: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
11245: if(Dummy[j]==0){
11246: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
11247: fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]); /* */
11248: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
11249: }else{ /* quantitative */
11250: fprintf(ficgp,"+p%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* */
11251: /* fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* *\/ */
11252: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
11253: }
11254: /* end simple */
11255: /* fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);/\* Valgrind bug nbcode *\/ */
11256: break;
11257: default:
11258: break;
11259: } /* end switch */
1.223 brouard 11260: }
11261: fprintf(ficgp,")");
11262: }
11263: fprintf(ficgp,")");
11264: if(ng ==2)
1.276 brouard 11265: 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 11266: else /* ng= 3 */
1.276 brouard 11267: 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 11268: }else{ /* end ng <> 1 */
1.223 brouard 11269: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 11270: 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 11271: }
11272: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
11273: fprintf(ficgp,",");
11274: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
11275: fprintf(ficgp,",");
11276: i=i+ncovmodel;
11277: } /* end k */
11278: } /* end k2 */
1.276 brouard 11279: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
11280: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.337 brouard 11281: } /* end resultline */
1.223 brouard 11282: } /* end ng */
11283: /* avoid: */
11284: fflush(ficgp);
1.126 brouard 11285: } /* end gnuplot */
11286:
11287:
11288: /*************** Moving average **************/
1.219 brouard 11289: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 11290: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 11291:
1.222 brouard 11292: int i, cpt, cptcod;
11293: int modcovmax =1;
11294: int mobilavrange, mob;
11295: int iage=0;
1.288 brouard 11296: int firstA1=0, firstA2=0;
1.222 brouard 11297:
1.266 brouard 11298: double sum=0., sumr=0.;
1.222 brouard 11299: double age;
1.266 brouard 11300: double *sumnewp, *sumnewm, *sumnewmr;
11301: double *agemingood, *agemaxgood;
11302: double *agemingoodr, *agemaxgoodr;
1.222 brouard 11303:
11304:
1.278 brouard 11305: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
11306: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 11307:
11308: sumnewp = vector(1,ncovcombmax);
11309: sumnewm = vector(1,ncovcombmax);
1.266 brouard 11310: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 11311: agemingood = vector(1,ncovcombmax);
1.266 brouard 11312: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 11313: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 11314: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 11315:
11316: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 11317: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 11318: sumnewp[cptcod]=0.;
1.266 brouard 11319: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
11320: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 11321: }
11322: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
11323:
1.266 brouard 11324: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
11325: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 11326: else mobilavrange=mobilav;
11327: for (age=bage; age<=fage; age++)
11328: for (i=1; i<=nlstate;i++)
11329: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
11330: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
11331: /* We keep the original values on the extreme ages bage, fage and for
11332: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
11333: we use a 5 terms etc. until the borders are no more concerned.
11334: */
11335: for (mob=3;mob <=mobilavrange;mob=mob+2){
11336: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 11337: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
11338: sumnewm[cptcod]=0.;
11339: for (i=1; i<=nlstate;i++){
1.222 brouard 11340: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
11341: for (cpt=1;cpt<=(mob-1)/2;cpt++){
11342: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
11343: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
11344: }
11345: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 11346: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
11347: } /* end i */
11348: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
11349: } /* end cptcod */
1.222 brouard 11350: }/* end age */
11351: }/* end mob */
1.266 brouard 11352: }else{
11353: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 11354: return -1;
1.266 brouard 11355: }
11356:
11357: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 11358: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
11359: if(invalidvarcomb[cptcod]){
11360: printf("\nCombination (%d) ignored because no cases \n",cptcod);
11361: continue;
11362: }
1.219 brouard 11363:
1.266 brouard 11364: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
11365: sumnewm[cptcod]=0.;
11366: sumnewmr[cptcod]=0.;
11367: for (i=1; i<=nlstate;i++){
11368: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
11369: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
11370: }
11371: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
11372: agemingoodr[cptcod]=age;
11373: }
11374: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
11375: agemingood[cptcod]=age;
11376: }
11377: } /* age */
11378: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 11379: sumnewm[cptcod]=0.;
1.266 brouard 11380: sumnewmr[cptcod]=0.;
1.222 brouard 11381: for (i=1; i<=nlstate;i++){
11382: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 11383: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
11384: }
11385: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
11386: agemaxgoodr[cptcod]=age;
1.222 brouard 11387: }
11388: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 11389: agemaxgood[cptcod]=age;
11390: }
11391: } /* age */
11392: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
11393: /* but they will change */
1.288 brouard 11394: firstA1=0;firstA2=0;
1.266 brouard 11395: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
11396: sumnewm[cptcod]=0.;
11397: sumnewmr[cptcod]=0.;
11398: for (i=1; i<=nlstate;i++){
11399: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
11400: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
11401: }
11402: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
11403: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
11404: agemaxgoodr[cptcod]=age; /* age min */
11405: for (i=1; i<=nlstate;i++)
11406: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
11407: }else{ /* bad we change the value with the values of good ages */
11408: for (i=1; i<=nlstate;i++){
11409: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
11410: } /* i */
11411: } /* end bad */
11412: }else{
11413: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
11414: agemaxgood[cptcod]=age;
11415: }else{ /* bad we change the value with the values of good ages */
11416: for (i=1; i<=nlstate;i++){
11417: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
11418: } /* i */
11419: } /* end bad */
11420: }/* end else */
11421: sum=0.;sumr=0.;
11422: for (i=1; i<=nlstate;i++){
11423: sum+=mobaverage[(int)age][i][cptcod];
11424: sumr+=probs[(int)age][i][cptcod];
11425: }
11426: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 11427: if(!firstA1){
11428: firstA1=1;
11429: 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);
11430: }
11431: 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 11432: } /* end bad */
11433: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
11434: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 11435: if(!firstA2){
11436: firstA2=1;
11437: 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);
11438: }
11439: 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 11440: } /* end bad */
11441: }/* age */
1.266 brouard 11442:
11443: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 11444: sumnewm[cptcod]=0.;
1.266 brouard 11445: sumnewmr[cptcod]=0.;
1.222 brouard 11446: for (i=1; i<=nlstate;i++){
11447: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 11448: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
11449: }
11450: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
11451: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
11452: agemingoodr[cptcod]=age;
11453: for (i=1; i<=nlstate;i++)
11454: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
11455: }else{ /* bad we change the value with the values of good ages */
11456: for (i=1; i<=nlstate;i++){
11457: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
11458: } /* i */
11459: } /* end bad */
11460: }else{
11461: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
11462: agemingood[cptcod]=age;
11463: }else{ /* bad */
11464: for (i=1; i<=nlstate;i++){
11465: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
11466: } /* i */
11467: } /* end bad */
11468: }/* end else */
11469: sum=0.;sumr=0.;
11470: for (i=1; i<=nlstate;i++){
11471: sum+=mobaverage[(int)age][i][cptcod];
11472: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 11473: }
1.266 brouard 11474: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 11475: 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 11476: } /* end bad */
11477: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
11478: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 11479: 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 11480: } /* end bad */
11481: }/* age */
1.266 brouard 11482:
1.222 brouard 11483:
11484: for (age=bage; age<=fage; age++){
1.235 brouard 11485: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 11486: sumnewp[cptcod]=0.;
11487: sumnewm[cptcod]=0.;
11488: for (i=1; i<=nlstate;i++){
11489: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
11490: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
11491: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
11492: }
11493: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
11494: }
11495: /* printf("\n"); */
11496: /* } */
1.266 brouard 11497:
1.222 brouard 11498: /* brutal averaging */
1.266 brouard 11499: /* for (i=1; i<=nlstate;i++){ */
11500: /* for (age=1; age<=bage; age++){ */
11501: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
11502: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
11503: /* } */
11504: /* for (age=fage; age<=AGESUP; age++){ */
11505: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
11506: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
11507: /* } */
11508: /* } /\* end i status *\/ */
11509: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
11510: /* for (age=1; age<=AGESUP; age++){ */
11511: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
11512: /* mobaverage[(int)age][i][cptcod]=0.; */
11513: /* } */
11514: /* } */
1.222 brouard 11515: }/* end cptcod */
1.266 brouard 11516: free_vector(agemaxgoodr,1, ncovcombmax);
11517: free_vector(agemaxgood,1, ncovcombmax);
11518: free_vector(agemingood,1, ncovcombmax);
11519: free_vector(agemingoodr,1, ncovcombmax);
11520: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 11521: free_vector(sumnewm,1, ncovcombmax);
11522: free_vector(sumnewp,1, ncovcombmax);
11523: return 0;
11524: }/* End movingaverage */
1.218 brouard 11525:
1.126 brouard 11526:
1.296 brouard 11527:
1.126 brouard 11528: /************** Forecasting ******************/
1.296 brouard 11529: /* 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)*/
11530: 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){
11531: /* dateintemean, mean date of interviews
11532: dateprojd, year, month, day of starting projection
11533: dateprojf date of end of projection;year of end of projection (same day and month as proj1).
1.126 brouard 11534: agemin, agemax range of age
11535: dateprev1 dateprev2 range of dates during which prevalence is computed
11536: */
1.296 brouard 11537: /* double anprojd, mprojd, jprojd; */
11538: /* double anprojf, mprojf, jprojf; */
1.359 brouard 11539: int yearp, stepsize, hstepm, nhstepm, j, k, i, h, nres=0;
1.126 brouard 11540: double agec; /* generic age */
1.359 brouard 11541: double agelim, ppij;
11542: /*double *popcount;*/
1.126 brouard 11543: double ***p3mat;
1.218 brouard 11544: /* double ***mobaverage; */
1.126 brouard 11545: char fileresf[FILENAMELENGTH];
11546:
11547: agelim=AGESUP;
1.211 brouard 11548: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
11549: in each health status at the date of interview (if between dateprev1 and dateprev2).
11550: We still use firstpass and lastpass as another selection.
11551: */
1.214 brouard 11552: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
11553: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 11554:
1.201 brouard 11555: strcpy(fileresf,"F_");
11556: strcat(fileresf,fileresu);
1.126 brouard 11557: if((ficresf=fopen(fileresf,"w"))==NULL) {
11558: printf("Problem with forecast resultfile: %s\n", fileresf);
11559: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
11560: }
1.235 brouard 11561: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
11562: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 11563:
1.225 brouard 11564: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 11565:
11566:
11567: stepsize=(int) (stepm+YEARM-1)/YEARM;
11568: if (stepm<=12) stepsize=1;
11569: if(estepm < stepm){
11570: printf ("Problem %d lower than %d\n",estepm, stepm);
11571: }
1.270 brouard 11572: else{
11573: hstepm=estepm;
11574: }
11575: if(estepm > stepm){ /* Yes every two year */
11576: stepsize=2;
11577: }
1.296 brouard 11578: hstepm=hstepm/stepm;
1.126 brouard 11579:
1.296 brouard 11580:
11581: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
11582: /* fractional in yp1 *\/ */
11583: /* aintmean=yp; */
11584: /* yp2=modf((yp1*12),&yp); */
11585: /* mintmean=yp; */
11586: /* yp1=modf((yp2*30.5),&yp); */
11587: /* jintmean=yp; */
11588: /* if(jintmean==0) jintmean=1; */
11589: /* if(mintmean==0) mintmean=1; */
1.126 brouard 11590:
1.296 brouard 11591:
11592: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */
11593: /* date2dmy(dateprojd,&jprojd, &mprojd, &anprojd); */
11594: /* date2dmy(dateprojf,&jprojf, &mprojf, &anprojf); */
1.351 brouard 11595: /* i1=pow(2,cptcoveff); */
11596: /* if (cptcovn < 1){i1=1;} */
1.126 brouard 11597:
1.296 brouard 11598: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.126 brouard 11599:
11600: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 11601:
1.126 brouard 11602: /* if (h==(int)(YEARM*yearp)){ */
1.351 brouard 11603: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
11604: k=TKresult[nres];
11605: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
11606: /* 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) *\/ */
11607: /* if(i1 != 1 && TKresult[nres]!= k) */
11608: /* continue; */
11609: /* if(invalidvarcomb[k]){ */
11610: /* printf("\nCombination (%d) projection ignored because no cases \n",k); */
11611: /* continue; */
11612: /* } */
1.227 brouard 11613: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
1.351 brouard 11614: for(j=1;j<=cptcovs;j++){
11615: /* for(j=1;j<=cptcoveff;j++) { */
11616: /* /\* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); *\/ */
11617: /* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11618: /* } */
11619: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
11620: /* fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
11621: /* } */
11622: fprintf(ficresf," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.235 brouard 11623: }
1.351 brouard 11624:
1.227 brouard 11625: fprintf(ficresf," yearproj age");
11626: for(j=1; j<=nlstate+ndeath;j++){
11627: for(i=1; i<=nlstate;i++)
11628: fprintf(ficresf," p%d%d",i,j);
11629: fprintf(ficresf," wp.%d",j);
11630: }
1.296 brouard 11631: for (yearp=0; yearp<=(anprojf-anprojd);yearp +=stepsize) {
1.227 brouard 11632: fprintf(ficresf,"\n");
1.296 brouard 11633: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jprojd,mprojd,anprojd+yearp);
1.270 brouard 11634: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
11635: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 11636: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
11637: nhstepm = nhstepm/hstepm;
11638: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11639: oldm=oldms;savm=savms;
1.268 brouard 11640: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 11641: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 11642: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 11643: for (h=0; h<=nhstepm; h++){
11644: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 11645: break;
11646: }
11647: }
11648: fprintf(ficresf,"\n");
1.351 brouard 11649: /* for(j=1;j<=cptcoveff;j++) */
11650: for(j=1;j<=cptcovs;j++)
11651: fprintf(ficresf,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.332 brouard 11652: /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Tvaraff not correct *\/ */
1.351 brouard 11653: /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /\* TnsdVar[Tvaraff] correct *\/ */
1.296 brouard 11654: fprintf(ficresf,"%.f %.f ",anprojd+yearp,agec+h*hstepm/YEARM*stepm);
1.268 brouard 11655:
11656: for(j=1; j<=nlstate+ndeath;j++) {
11657: ppij=0.;
11658: for(i=1; i<=nlstate;i++) {
1.278 brouard 11659: if (mobilav>=1)
11660: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
11661: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
11662: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
11663: }
1.268 brouard 11664: fprintf(ficresf," %.3f", p3mat[i][j][h]);
11665: } /* end i */
11666: fprintf(ficresf," %.3f", ppij);
11667: }/* end j */
1.227 brouard 11668: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11669: } /* end agec */
1.266 brouard 11670: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
11671: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 11672: } /* end yearp */
11673: } /* end k */
1.219 brouard 11674:
1.126 brouard 11675: fclose(ficresf);
1.215 brouard 11676: printf("End of Computing forecasting \n");
11677: fprintf(ficlog,"End of Computing forecasting\n");
11678:
1.126 brouard 11679: }
11680:
1.269 brouard 11681: /************** Back Forecasting ******************/
1.296 brouard 11682: /* 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){ */
11683: 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){
11684: /* back1, year, month, day of starting backprojection
1.267 brouard 11685: agemin, agemax range of age
11686: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 11687: anback2 year of end of backprojection (same day and month as back1).
11688: prevacurrent and prev are prevalences.
1.267 brouard 11689: */
1.359 brouard 11690: int yearp, stepsize, hstepm, nhstepm, j, k, i, h, nres=0;
1.267 brouard 11691: double agec; /* generic age */
1.359 brouard 11692: double agelim, ppij, ppi; /* ,jintmean,mintmean,aintmean;*/
11693: /*double *popcount;*/
1.267 brouard 11694: double ***p3mat;
11695: /* double ***mobaverage; */
11696: char fileresfb[FILENAMELENGTH];
11697:
1.268 brouard 11698: agelim=AGEINF;
1.267 brouard 11699: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
11700: in each health status at the date of interview (if between dateprev1 and dateprev2).
11701: We still use firstpass and lastpass as another selection.
11702: */
11703: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
11704: /* firstpass, lastpass, stepm, weightopt, model); */
11705:
11706: /*Do we need to compute prevalence again?*/
11707:
11708: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
11709:
11710: strcpy(fileresfb,"FB_");
11711: strcat(fileresfb,fileresu);
11712: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
11713: printf("Problem with back forecast resultfile: %s\n", fileresfb);
11714: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
11715: }
11716: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
11717: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
11718:
11719: if (cptcoveff==0) ncodemax[cptcoveff]=1;
11720:
11721:
11722: stepsize=(int) (stepm+YEARM-1)/YEARM;
11723: if (stepm<=12) stepsize=1;
11724: if(estepm < stepm){
11725: printf ("Problem %d lower than %d\n",estepm, stepm);
11726: }
1.270 brouard 11727: else{
11728: hstepm=estepm;
11729: }
11730: if(estepm >= stepm){ /* Yes every two year */
11731: stepsize=2;
11732: }
1.267 brouard 11733:
11734: hstepm=hstepm/stepm;
1.296 brouard 11735: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
11736: /* fractional in yp1 *\/ */
11737: /* aintmean=yp; */
11738: /* yp2=modf((yp1*12),&yp); */
11739: /* mintmean=yp; */
11740: /* yp1=modf((yp2*30.5),&yp); */
11741: /* jintmean=yp; */
11742: /* if(jintmean==0) jintmean=1; */
11743: /* if(mintmean==0) jintmean=1; */
1.267 brouard 11744:
1.351 brouard 11745: /* i1=pow(2,cptcoveff); */
11746: /* if (cptcovn < 1){i1=1;} */
1.267 brouard 11747:
1.296 brouard 11748: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
11749: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 11750:
11751: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
11752:
1.351 brouard 11753: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
11754: k=TKresult[nres];
11755: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
11756: /* for(k=1; k<=i1;k++){ */
11757: /* if(i1 != 1 && TKresult[nres]!= k) */
11758: /* continue; */
11759: /* if(invalidvarcomb[k]){ */
11760: /* printf("\nCombination (%d) projection ignored because no cases \n",k); */
11761: /* continue; */
11762: /* } */
1.268 brouard 11763: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.351 brouard 11764: for(j=1;j<=cptcovs;j++){
11765: /* for(j=1;j<=cptcoveff;j++) { */
11766: /* fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11767: /* } */
11768: fprintf(ficresfb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.267 brouard 11769: }
1.351 brouard 11770: /* fprintf(ficrespij,"******\n"); */
11771: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
11772: /* fprintf(ficresfb," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
11773: /* } */
1.267 brouard 11774: fprintf(ficresfb," yearbproj age");
11775: for(j=1; j<=nlstate+ndeath;j++){
11776: for(i=1; i<=nlstate;i++)
1.268 brouard 11777: fprintf(ficresfb," b%d%d",i,j);
11778: fprintf(ficresfb," b.%d",j);
1.267 brouard 11779: }
1.296 brouard 11780: for (yearp=0; yearp>=(anbackf-anbackd);yearp -=stepsize) {
1.267 brouard 11781: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
11782: fprintf(ficresfb,"\n");
1.296 brouard 11783: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jbackd,mbackd,anbackd+yearp);
1.273 brouard 11784: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 11785: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
11786: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 11787: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 11788: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 11789: nhstepm = nhstepm/hstepm;
11790: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11791: oldm=oldms;savm=savms;
1.268 brouard 11792: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 11793: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 11794: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 11795: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
11796: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
11797: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 11798: for (h=0; h<=nhstepm; h++){
1.268 brouard 11799: if (h*hstepm/YEARM*stepm ==-yearp) {
11800: break;
11801: }
11802: }
11803: fprintf(ficresfb,"\n");
1.351 brouard 11804: /* for(j=1;j<=cptcoveff;j++) */
11805: for(j=1;j<=cptcovs;j++)
11806: fprintf(ficresfb,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11807: /* fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.296 brouard 11808: fprintf(ficresfb,"%.f %.f ",anbackd+yearp,agec-h*hstepm/YEARM*stepm);
1.268 brouard 11809: for(i=1; i<=nlstate+ndeath;i++) {
11810: ppij=0.;ppi=0.;
11811: for(j=1; j<=nlstate;j++) {
11812: /* if (mobilav==1) */
1.269 brouard 11813: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
11814: ppi=ppi+prevacurrent[(int)agec][j][k];
11815: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
11816: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 11817: /* else { */
11818: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
11819: /* } */
1.268 brouard 11820: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
11821: } /* end j */
11822: if(ppi <0.99){
11823: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
11824: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
11825: }
11826: fprintf(ficresfb," %.3f", ppij);
11827: }/* end j */
1.267 brouard 11828: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11829: } /* end agec */
11830: } /* end yearp */
11831: } /* end k */
1.217 brouard 11832:
1.267 brouard 11833: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 11834:
1.267 brouard 11835: fclose(ficresfb);
11836: printf("End of Computing Back forecasting \n");
11837: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 11838:
1.267 brouard 11839: }
1.217 brouard 11840:
1.269 brouard 11841: /* Variance of prevalence limit: varprlim */
11842: 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 11843: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 11844:
11845: char fileresvpl[FILENAMELENGTH];
11846: FILE *ficresvpl;
11847: double **oldm, **savm;
11848: double **varpl; /* Variances of prevalence limits by age */
11849: int i1, k, nres, j ;
11850:
11851: strcpy(fileresvpl,"VPL_");
11852: strcat(fileresvpl,fileresu);
11853: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 11854: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 11855: exit(0);
11856: }
1.288 brouard 11857: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
11858: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 11859:
11860: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
11861: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
11862:
11863: i1=pow(2,cptcoveff);
11864: if (cptcovn < 1){i1=1;}
11865:
1.337 brouard 11866: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
11867: k=TKresult[nres];
1.338 brouard 11868: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 11869: /* for(k=1; k<=i1;k++){ /\* We find the combination equivalent to result line values of dummies *\/ */
1.269 brouard 11870: if(i1 != 1 && TKresult[nres]!= k)
11871: continue;
11872: fprintf(ficresvpl,"\n#****** ");
11873: printf("\n#****** ");
11874: fprintf(ficlog,"\n#****** ");
1.337 brouard 11875: for(j=1;j<=cptcovs;j++) {
11876: fprintf(ficresvpl,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11877: fprintf(ficlog,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11878: printf("V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11879: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11880: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.269 brouard 11881: }
1.337 brouard 11882: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
11883: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
11884: /* fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
11885: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
11886: /* } */
1.269 brouard 11887: fprintf(ficresvpl,"******\n");
11888: printf("******\n");
11889: fprintf(ficlog,"******\n");
11890:
11891: varpl=matrix(1,nlstate,(int) bage, (int) fage);
11892: oldm=oldms;savm=savms;
11893: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
11894: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
11895: /*}*/
11896: }
11897:
11898: fclose(ficresvpl);
1.288 brouard 11899: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
11900: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 11901:
11902: }
11903: /* Variance of back prevalence: varbprlim */
11904: 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){
11905: /*------- Variance of back (stable) prevalence------*/
11906:
11907: char fileresvbl[FILENAMELENGTH];
11908: FILE *ficresvbl;
11909:
11910: double **oldm, **savm;
11911: double **varbpl; /* Variances of back prevalence limits by age */
11912: int i1, k, nres, j ;
11913:
11914: strcpy(fileresvbl,"VBL_");
11915: strcat(fileresvbl,fileresu);
11916: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
11917: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
11918: exit(0);
11919: }
11920: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
11921: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
11922:
11923:
11924: i1=pow(2,cptcoveff);
11925: if (cptcovn < 1){i1=1;}
11926:
1.337 brouard 11927: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
11928: k=TKresult[nres];
1.338 brouard 11929: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 11930: /* for(k=1; k<=i1;k++){ */
11931: /* if(i1 != 1 && TKresult[nres]!= k) */
11932: /* continue; */
1.269 brouard 11933: fprintf(ficresvbl,"\n#****** ");
11934: printf("\n#****** ");
11935: fprintf(ficlog,"\n#****** ");
1.337 brouard 11936: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */
1.338 brouard 11937: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
11938: fprintf(ficresvbl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
11939: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
1.337 brouard 11940: /* for(j=1;j<=cptcoveff;j++) { */
11941: /* fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11942: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11943: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11944: /* } */
11945: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
11946: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
11947: /* fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
11948: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
1.269 brouard 11949: }
11950: fprintf(ficresvbl,"******\n");
11951: printf("******\n");
11952: fprintf(ficlog,"******\n");
11953:
11954: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
11955: oldm=oldms;savm=savms;
11956:
11957: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
11958: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
11959: /*}*/
11960: }
11961:
11962: fclose(ficresvbl);
11963: printf("done variance-covariance of back prevalence\n");fflush(stdout);
11964: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
11965:
11966: } /* End of varbprlim */
11967:
1.126 brouard 11968: /************** Forecasting *****not tested NB*************/
1.227 brouard 11969: /* 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 11970:
1.227 brouard 11971: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
11972: /* int *popage; */
11973: /* double calagedatem, agelim, kk1, kk2; */
11974: /* double *popeffectif,*popcount; */
11975: /* double ***p3mat,***tabpop,***tabpopprev; */
11976: /* /\* double ***mobaverage; *\/ */
11977: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 11978:
1.227 brouard 11979: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
11980: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
11981: /* agelim=AGESUP; */
11982: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 11983:
1.227 brouard 11984: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 11985:
11986:
1.227 brouard 11987: /* strcpy(filerespop,"POP_"); */
11988: /* strcat(filerespop,fileresu); */
11989: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
11990: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
11991: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
11992: /* } */
11993: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
11994: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 11995:
1.227 brouard 11996: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 11997:
1.227 brouard 11998: /* /\* if (mobilav!=0) { *\/ */
11999: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
12000: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
12001: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
12002: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
12003: /* /\* } *\/ */
12004: /* /\* } *\/ */
1.126 brouard 12005:
1.227 brouard 12006: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
12007: /* if (stepm<=12) stepsize=1; */
1.126 brouard 12008:
1.227 brouard 12009: /* agelim=AGESUP; */
1.126 brouard 12010:
1.227 brouard 12011: /* hstepm=1; */
12012: /* hstepm=hstepm/stepm; */
1.218 brouard 12013:
1.227 brouard 12014: /* if (popforecast==1) { */
12015: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
12016: /* printf("Problem with population file : %s\n",popfile);exit(0); */
12017: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
12018: /* } */
12019: /* popage=ivector(0,AGESUP); */
12020: /* popeffectif=vector(0,AGESUP); */
12021: /* popcount=vector(0,AGESUP); */
1.126 brouard 12022:
1.227 brouard 12023: /* i=1; */
12024: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 12025:
1.227 brouard 12026: /* imx=i; */
12027: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
12028: /* } */
1.218 brouard 12029:
1.227 brouard 12030: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
12031: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
12032: /* k=k+1; */
12033: /* fprintf(ficrespop,"\n#******"); */
12034: /* for(j=1;j<=cptcoveff;j++) { */
12035: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
12036: /* } */
12037: /* fprintf(ficrespop,"******\n"); */
12038: /* fprintf(ficrespop,"# Age"); */
12039: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
12040: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 12041:
1.227 brouard 12042: /* for (cpt=0; cpt<=0;cpt++) { */
12043: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 12044:
1.227 brouard 12045: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
12046: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
12047: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 12048:
1.227 brouard 12049: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
12050: /* oldm=oldms;savm=savms; */
12051: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 12052:
1.227 brouard 12053: /* for (h=0; h<=nhstepm; h++){ */
12054: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
12055: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
12056: /* } */
12057: /* for(j=1; j<=nlstate+ndeath;j++) { */
12058: /* kk1=0.;kk2=0; */
12059: /* for(i=1; i<=nlstate;i++) { */
12060: /* if (mobilav==1) */
12061: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
12062: /* else { */
12063: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
12064: /* } */
12065: /* } */
12066: /* if (h==(int)(calagedatem+12*cpt)){ */
12067: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
12068: /* /\*fprintf(ficrespop," %.3f", kk1); */
12069: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
12070: /* } */
12071: /* } */
12072: /* for(i=1; i<=nlstate;i++){ */
12073: /* kk1=0.; */
12074: /* for(j=1; j<=nlstate;j++){ */
12075: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
12076: /* } */
12077: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
12078: /* } */
1.218 brouard 12079:
1.227 brouard 12080: /* if (h==(int)(calagedatem+12*cpt)) */
12081: /* for(j=1; j<=nlstate;j++) */
12082: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
12083: /* } */
12084: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
12085: /* } */
12086: /* } */
1.218 brouard 12087:
1.227 brouard 12088: /* /\******\/ */
1.218 brouard 12089:
1.227 brouard 12090: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
12091: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
12092: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
12093: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
12094: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 12095:
1.227 brouard 12096: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
12097: /* oldm=oldms;savm=savms; */
12098: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
12099: /* for (h=0; h<=nhstepm; h++){ */
12100: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
12101: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
12102: /* } */
12103: /* for(j=1; j<=nlstate+ndeath;j++) { */
12104: /* kk1=0.;kk2=0; */
12105: /* for(i=1; i<=nlstate;i++) { */
12106: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
12107: /* } */
12108: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
12109: /* } */
12110: /* } */
12111: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
12112: /* } */
12113: /* } */
12114: /* } */
12115: /* } */
1.218 brouard 12116:
1.227 brouard 12117: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 12118:
1.227 brouard 12119: /* if (popforecast==1) { */
12120: /* free_ivector(popage,0,AGESUP); */
12121: /* free_vector(popeffectif,0,AGESUP); */
12122: /* free_vector(popcount,0,AGESUP); */
12123: /* } */
12124: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
12125: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
12126: /* fclose(ficrespop); */
12127: /* } /\* End of popforecast *\/ */
1.218 brouard 12128:
1.126 brouard 12129: int fileappend(FILE *fichier, char *optionfich)
12130: {
12131: if((fichier=fopen(optionfich,"a"))==NULL) {
12132: printf("Problem with file: %s\n", optionfich);
12133: fprintf(ficlog,"Problem with file: %s\n", optionfich);
12134: return (0);
12135: }
12136: fflush(fichier);
12137: return (1);
12138: }
12139:
12140:
12141: /**************** function prwizard **********************/
12142: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
12143: {
12144:
12145: /* Wizard to print covariance matrix template */
12146:
1.164 brouard 12147: char ca[32], cb[32];
12148: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 12149: int numlinepar;
12150:
12151: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
12152: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
12153: for(i=1; i <=nlstate; i++){
12154: jj=0;
12155: for(j=1; j <=nlstate+ndeath; j++){
12156: if(j==i) continue;
12157: jj++;
12158: /*ca[0]= k+'a'-1;ca[1]='\0';*/
12159: printf("%1d%1d",i,j);
12160: fprintf(ficparo,"%1d%1d",i,j);
12161: for(k=1; k<=ncovmodel;k++){
12162: /* printf(" %lf",param[i][j][k]); */
12163: /* fprintf(ficparo," %lf",param[i][j][k]); */
12164: printf(" 0.");
12165: fprintf(ficparo," 0.");
12166: }
12167: printf("\n");
12168: fprintf(ficparo,"\n");
12169: }
12170: }
12171: printf("# Scales (for hessian or gradient estimation)\n");
12172: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
12173: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
12174: for(i=1; i <=nlstate; i++){
12175: jj=0;
12176: for(j=1; j <=nlstate+ndeath; j++){
12177: if(j==i) continue;
12178: jj++;
12179: fprintf(ficparo,"%1d%1d",i,j);
12180: printf("%1d%1d",i,j);
12181: fflush(stdout);
12182: for(k=1; k<=ncovmodel;k++){
12183: /* printf(" %le",delti3[i][j][k]); */
12184: /* fprintf(ficparo," %le",delti3[i][j][k]); */
12185: printf(" 0.");
12186: fprintf(ficparo," 0.");
12187: }
12188: numlinepar++;
12189: printf("\n");
12190: fprintf(ficparo,"\n");
12191: }
12192: }
12193: printf("# Covariance matrix\n");
12194: /* # 121 Var(a12)\n\ */
12195: /* # 122 Cov(b12,a12) Var(b12)\n\ */
12196: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
12197: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
12198: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
12199: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
12200: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
12201: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
12202: fflush(stdout);
12203: fprintf(ficparo,"# Covariance matrix\n");
12204: /* # 121 Var(a12)\n\ */
12205: /* # 122 Cov(b12,a12) Var(b12)\n\ */
12206: /* # ...\n\ */
12207: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
12208:
12209: for(itimes=1;itimes<=2;itimes++){
12210: jj=0;
12211: for(i=1; i <=nlstate; i++){
12212: for(j=1; j <=nlstate+ndeath; j++){
12213: if(j==i) continue;
12214: for(k=1; k<=ncovmodel;k++){
12215: jj++;
12216: ca[0]= k+'a'-1;ca[1]='\0';
12217: if(itimes==1){
12218: printf("#%1d%1d%d",i,j,k);
12219: fprintf(ficparo,"#%1d%1d%d",i,j,k);
12220: }else{
12221: printf("%1d%1d%d",i,j,k);
12222: fprintf(ficparo,"%1d%1d%d",i,j,k);
12223: /* printf(" %.5le",matcov[i][j]); */
12224: }
12225: ll=0;
12226: for(li=1;li <=nlstate; li++){
12227: for(lj=1;lj <=nlstate+ndeath; lj++){
12228: if(lj==li) continue;
12229: for(lk=1;lk<=ncovmodel;lk++){
12230: ll++;
12231: if(ll<=jj){
12232: cb[0]= lk +'a'-1;cb[1]='\0';
12233: if(ll<jj){
12234: if(itimes==1){
12235: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12236: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12237: }else{
12238: printf(" 0.");
12239: fprintf(ficparo," 0.");
12240: }
12241: }else{
12242: if(itimes==1){
12243: printf(" Var(%s%1d%1d)",ca,i,j);
12244: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
12245: }else{
12246: printf(" 0.");
12247: fprintf(ficparo," 0.");
12248: }
12249: }
12250: }
12251: } /* end lk */
12252: } /* end lj */
12253: } /* end li */
12254: printf("\n");
12255: fprintf(ficparo,"\n");
12256: numlinepar++;
12257: } /* end k*/
12258: } /*end j */
12259: } /* end i */
12260: } /* end itimes */
12261:
12262: } /* end of prwizard */
12263: /******************* Gompertz Likelihood ******************************/
12264: double gompertz(double x[])
12265: {
1.302 brouard 12266: double A=0.0,B=0.,L=0.0,sump=0.,num=0.;
1.126 brouard 12267: int i,n=0; /* n is the size of the sample */
12268:
1.220 brouard 12269: for (i=1;i<=imx ; i++) {
1.126 brouard 12270: sump=sump+weight[i];
12271: /* sump=sump+1;*/
12272: num=num+1;
12273: }
1.302 brouard 12274: L=0.0;
12275: /* agegomp=AGEGOMP; */
1.126 brouard 12276: /* for (i=0; i<=imx; i++)
12277: 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]);*/
12278:
1.302 brouard 12279: for (i=1;i<=imx ; i++) {
12280: /* mu(a)=mu(agecomp)*exp(teta*(age-agegomp))
12281: mu(a)=x[1]*exp(x[2]*(age-agegomp)); x[1] and x[2] are per year.
12282: * L= Product mu(agedeces)exp(-\int_ageexam^agedc mu(u) du ) for a death between agedc (in month)
12283: * and agedc +1 month, cens[i]=0: log(x[1]/YEARM)
12284: * +
12285: * exp(-\int_ageexam^agecens mu(u) du ) when censored, cens[i]=1
12286: */
12287: if (wav[i] > 1 || agedc[i] < AGESUP) {
12288: if (cens[i] == 1){
12289: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
12290: } else if (cens[i] == 0){
1.126 brouard 12291: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
1.362 ! brouard 12292: +log(fabs(x[1])/YEARM) +x[2]*(agedc[i]-agegomp)+log(YEARM);
! 12293: /* +log(x[1]/YEARM) +x[2]*(agedc[i]-agegomp)+log(YEARM); */ /* To be seen */
1.302 brouard 12294: } else
12295: printf("Gompertz cens[%d] neither 1 nor 0\n",i);
1.126 brouard 12296: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
1.302 brouard 12297: L=L+A*weight[i];
1.126 brouard 12298: /* 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 12299: }
12300: }
1.126 brouard 12301:
1.302 brouard 12302: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
1.126 brouard 12303:
12304: return -2*L*num/sump;
12305: }
12306:
1.136 brouard 12307: #ifdef GSL
12308: /******************* Gompertz_f Likelihood ******************************/
12309: double gompertz_f(const gsl_vector *v, void *params)
12310: {
1.302 brouard 12311: double A=0.,B=0.,LL=0.0,sump=0.,num=0.;
1.136 brouard 12312: double *x= (double *) v->data;
12313: int i,n=0; /* n is the size of the sample */
12314:
12315: for (i=0;i<=imx-1 ; i++) {
12316: sump=sump+weight[i];
12317: /* sump=sump+1;*/
12318: num=num+1;
12319: }
12320:
12321:
12322: /* for (i=0; i<=imx; i++)
12323: 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]);*/
12324: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
12325: for (i=1;i<=imx ; i++)
12326: {
12327: if (cens[i] == 1 && wav[i]>1)
12328: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
12329:
12330: if (cens[i] == 0 && wav[i]>1)
12331: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
12332: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
12333:
12334: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
12335: if (wav[i] > 1 ) { /* ??? */
12336: LL=LL+A*weight[i];
12337: /* 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]);*/
12338: }
12339: }
12340:
12341: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
12342: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
12343:
12344: return -2*LL*num/sump;
12345: }
12346: #endif
12347:
1.126 brouard 12348: /******************* Printing html file ***********/
1.201 brouard 12349: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 12350: int lastpass, int stepm, int weightopt, char model[],\
12351: int imx, double p[],double **matcov,double agemortsup){
12352: int i,k;
12353:
12354: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
12355: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
12356: for (i=1;i<=2;i++)
12357: 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 12358: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 12359: fprintf(fichtm,"</ul>");
12360:
12361: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
12362:
12363: 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>");
12364:
12365: for (k=agegomp;k<(agemortsup-2);k++)
12366: 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]);
12367:
12368:
12369: fflush(fichtm);
12370: }
12371:
12372: /******************* Gnuplot file **************/
1.201 brouard 12373: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 12374:
12375: char dirfileres[132],optfileres[132];
1.164 brouard 12376:
1.359 brouard 12377: /*int ng;*/
1.126 brouard 12378:
12379:
12380: /*#ifdef windows */
12381: fprintf(ficgp,"cd \"%s\" \n",pathc);
12382: /*#endif */
12383:
12384:
12385: strcpy(dirfileres,optionfilefiname);
12386: strcpy(optfileres,"vpl");
1.199 brouard 12387: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 12388: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 12389: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 12390: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 12391: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
12392:
12393: }
12394:
1.136 brouard 12395: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
12396: {
1.126 brouard 12397:
1.136 brouard 12398: /*-------- data file ----------*/
12399: FILE *fic;
12400: char dummy[]=" ";
1.359 brouard 12401: int i = 0, j = 0, n = 0, iv = 0;/* , v;*/
1.223 brouard 12402: int lstra;
1.136 brouard 12403: int linei, month, year,iout;
1.302 brouard 12404: int noffset=0; /* This is the offset if BOM data file */
1.136 brouard 12405: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 12406: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 12407: char *stratrunc;
1.223 brouard 12408:
1.349 brouard 12409: /* DummyV=ivector(-1,NCOVMAX); /\* 1 to 3 *\/ */
12410: /* FixedV=ivector(-1,NCOVMAX); /\* 1 to 3 *\/ */
1.339 brouard 12411:
12412: ncovcolt=ncovcol+nqv+ntv+nqtv; /* total of covariates in the data, not in the model equation */
12413:
1.136 brouard 12414: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 12415: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
12416: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 12417: }
1.126 brouard 12418:
1.302 brouard 12419: /* Is it a BOM UTF-8 Windows file? */
12420: /* First data line */
12421: linei=0;
12422: while(fgets(line, MAXLINE, fic)) {
12423: noffset=0;
12424: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
12425: {
12426: noffset=noffset+3;
12427: printf("# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);fflush(stdout);
12428: fprintf(ficlog,"# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);
12429: fflush(ficlog); return 1;
12430: }
12431: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
12432: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
12433: {
12434: noffset=noffset+2;
1.304 brouard 12435: 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);
12436: 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 12437: fflush(ficlog); return 1;
12438: }
12439: else if( line[0] == 0 && line[1] == 0)
12440: {
12441: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
12442: noffset=noffset+4;
1.304 brouard 12443: 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);
12444: 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 12445: fflush(ficlog); return 1;
12446: }
12447: } else{
12448: ;/*printf(" Not a BOM file\n");*/
12449: }
12450: /* If line starts with a # it is a comment */
12451: if (line[noffset] == '#') {
12452: linei=linei+1;
12453: break;
12454: }else{
12455: break;
12456: }
12457: }
12458: fclose(fic);
12459: if((fic=fopen(datafile,"r"))==NULL) {
12460: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
12461: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
12462: }
12463: /* Not a Bom file */
12464:
1.136 brouard 12465: i=1;
12466: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
12467: linei=linei+1;
12468: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
12469: if(line[j] == '\t')
12470: line[j] = ' ';
12471: }
12472: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
12473: ;
12474: };
12475: line[j+1]=0; /* Trims blanks at end of line */
12476: if(line[0]=='#'){
12477: fprintf(ficlog,"Comment line\n%s\n",line);
12478: printf("Comment line\n%s\n",line);
12479: continue;
12480: }
12481: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 12482: strcpy(line, linetmp);
1.223 brouard 12483:
12484: /* Loops on waves */
12485: for (j=maxwav;j>=1;j--){
12486: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 12487: cutv(stra, strb, line, ' ');
12488: if(strb[0]=='.') { /* Missing value */
12489: lval=-1;
12490: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
1.341 brouard 12491: cotvar[j][ncovcol+nqv+ntv+iv][i]=-1; /* For performance reasons */
1.238 brouard 12492: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
12493: 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);
12494: 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);
12495: return 1;
12496: }
12497: }else{
12498: errno=0;
12499: /* what_kind_of_number(strb); */
12500: dval=strtod(strb,&endptr);
12501: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
12502: /* if(strb != endptr && *endptr == '\0') */
12503: /* dval=dlval; */
12504: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
12505: if( strb[0]=='\0' || (*endptr != '\0')){
12506: 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);
12507: 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);
12508: return 1;
12509: }
12510: cotqvar[j][iv][i]=dval;
1.341 brouard 12511: cotvar[j][ncovcol+nqv+ntv+iv][i]=dval; /* because cotvar starts now at first ntv */
1.238 brouard 12512: }
12513: strcpy(line,stra);
1.223 brouard 12514: }/* end loop ntqv */
1.225 brouard 12515:
1.223 brouard 12516: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 12517: cutv(stra, strb, line, ' ');
12518: if(strb[0]=='.') { /* Missing value */
12519: lval=-1;
12520: }else{
12521: errno=0;
12522: lval=strtol(strb,&endptr,10);
12523: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
12524: if( strb[0]=='\0' || (*endptr != '\0')){
12525: 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);
12526: 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);
12527: return 1;
12528: }
12529: }
12530: if(lval <-1 || lval >1){
12531: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 12532: 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 12533: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 12534: For example, for multinomial values like 1, 2 and 3,\n \
12535: build V1=0 V2=0 for the reference value (1),\n \
12536: V1=1 V2=0 for (2) \n \
1.223 brouard 12537: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 12538: output of IMaCh is often meaningless.\n \
1.319 brouard 12539: Exiting.\n",lval,linei, i,line,iv,j);
1.238 brouard 12540: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 12541: 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 12542: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 12543: For example, for multinomial values like 1, 2 and 3,\n \
12544: build V1=0 V2=0 for the reference value (1),\n \
12545: V1=1 V2=0 for (2) \n \
1.223 brouard 12546: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 12547: output of IMaCh is often meaningless.\n \
1.319 brouard 12548: Exiting.\n",lval,linei, i,line,iv,j);fflush(ficlog);
1.238 brouard 12549: return 1;
12550: }
1.341 brouard 12551: cotvar[j][ncovcol+nqv+iv][i]=(double)(lval);
1.238 brouard 12552: strcpy(line,stra);
1.223 brouard 12553: }/* end loop ntv */
1.225 brouard 12554:
1.223 brouard 12555: /* Statuses at wave */
1.137 brouard 12556: cutv(stra, strb, line, ' ');
1.223 brouard 12557: if(strb[0]=='.') { /* Missing value */
1.238 brouard 12558: lval=-1;
1.136 brouard 12559: }else{
1.238 brouard 12560: errno=0;
12561: lval=strtol(strb,&endptr,10);
12562: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
1.347 brouard 12563: if( strb[0]=='\0' || (*endptr != '\0' )){
12564: 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);
12565: 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);
12566: return 1;
12567: }else if( lval==0 || lval > nlstate+ndeath){
1.348 brouard 12568: 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);
12569: 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 12570: return 1;
12571: }
1.136 brouard 12572: }
1.225 brouard 12573:
1.136 brouard 12574: s[j][i]=lval;
1.225 brouard 12575:
1.223 brouard 12576: /* Date of Interview */
1.136 brouard 12577: strcpy(line,stra);
12578: cutv(stra, strb,line,' ');
1.169 brouard 12579: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 12580: }
1.169 brouard 12581: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 12582: month=99;
12583: year=9999;
1.136 brouard 12584: }else{
1.225 brouard 12585: 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);
12586: 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);
12587: return 1;
1.136 brouard 12588: }
12589: anint[j][i]= (double) year;
1.302 brouard 12590: mint[j][i]= (double)month;
12591: /* if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){ */
12592: /* 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]); */
12593: /* 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]); */
12594: /* } */
1.136 brouard 12595: strcpy(line,stra);
1.223 brouard 12596: } /* End loop on waves */
1.225 brouard 12597:
1.223 brouard 12598: /* Date of death */
1.136 brouard 12599: cutv(stra, strb,line,' ');
1.169 brouard 12600: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 12601: }
1.169 brouard 12602: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 12603: month=99;
12604: year=9999;
12605: }else{
1.141 brouard 12606: 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 12607: 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);
12608: return 1;
1.136 brouard 12609: }
12610: andc[i]=(double) year;
12611: moisdc[i]=(double) month;
12612: strcpy(line,stra);
12613:
1.223 brouard 12614: /* Date of birth */
1.136 brouard 12615: cutv(stra, strb,line,' ');
1.169 brouard 12616: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 12617: }
1.169 brouard 12618: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 12619: month=99;
12620: year=9999;
12621: }else{
1.141 brouard 12622: 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);
12623: 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 12624: return 1;
1.136 brouard 12625: }
12626: if (year==9999) {
1.141 brouard 12627: 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);
12628: 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 12629: return 1;
12630:
1.136 brouard 12631: }
12632: annais[i]=(double)(year);
1.302 brouard 12633: moisnais[i]=(double)(month);
12634: for (j=1;j<=maxwav;j++){
12635: if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){
12636: 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]);
12637: 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]);
12638: }
12639: }
12640:
1.136 brouard 12641: strcpy(line,stra);
1.225 brouard 12642:
1.223 brouard 12643: /* Sample weight */
1.136 brouard 12644: cutv(stra, strb,line,' ');
12645: errno=0;
12646: dval=strtod(strb,&endptr);
12647: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 12648: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
12649: 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 12650: fflush(ficlog);
12651: return 1;
12652: }
12653: weight[i]=dval;
12654: strcpy(line,stra);
1.225 brouard 12655:
1.223 brouard 12656: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
12657: cutv(stra, strb, line, ' ');
12658: if(strb[0]=='.') { /* Missing value */
1.225 brouard 12659: lval=-1;
1.311 brouard 12660: coqvar[iv][i]=NAN;
12661: covar[ncovcol+iv][i]=NAN; /* including qvar in standard covar for performance reasons */
1.223 brouard 12662: }else{
1.225 brouard 12663: errno=0;
12664: /* what_kind_of_number(strb); */
12665: dval=strtod(strb,&endptr);
12666: /* if(strb != endptr && *endptr == '\0') */
12667: /* dval=dlval; */
12668: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
12669: if( strb[0]=='\0' || (*endptr != '\0')){
12670: 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);
12671: 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);
12672: return 1;
12673: }
12674: coqvar[iv][i]=dval;
1.226 brouard 12675: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 12676: }
12677: strcpy(line,stra);
12678: }/* end loop nqv */
1.136 brouard 12679:
1.223 brouard 12680: /* Covariate values */
1.136 brouard 12681: for (j=ncovcol;j>=1;j--){
12682: cutv(stra, strb,line,' ');
1.223 brouard 12683: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 12684: lval=-1;
1.136 brouard 12685: }else{
1.225 brouard 12686: errno=0;
12687: lval=strtol(strb,&endptr,10);
12688: if( strb[0]=='\0' || (*endptr != '\0')){
12689: 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);
12690: 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);
12691: return 1;
12692: }
1.136 brouard 12693: }
12694: if(lval <-1 || lval >1){
1.225 brouard 12695: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 12696: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
12697: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 12698: For example, for multinomial values like 1, 2 and 3,\n \
12699: build V1=0 V2=0 for the reference value (1),\n \
12700: V1=1 V2=0 for (2) \n \
1.136 brouard 12701: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 12702: output of IMaCh is often meaningless.\n \
1.136 brouard 12703: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 12704: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 12705: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
12706: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 12707: For example, for multinomial values like 1, 2 and 3,\n \
12708: build V1=0 V2=0 for the reference value (1),\n \
12709: V1=1 V2=0 for (2) \n \
1.136 brouard 12710: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 12711: output of IMaCh is often meaningless.\n \
1.136 brouard 12712: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 12713: return 1;
1.136 brouard 12714: }
12715: covar[j][i]=(double)(lval);
12716: strcpy(line,stra);
12717: }
12718: lstra=strlen(stra);
1.225 brouard 12719:
1.136 brouard 12720: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
12721: stratrunc = &(stra[lstra-9]);
12722: num[i]=atol(stratrunc);
12723: }
12724: else
12725: num[i]=atol(stra);
12726: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
12727: 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;}*/
12728:
12729: i=i+1;
12730: } /* End loop reading data */
1.225 brouard 12731:
1.136 brouard 12732: *imax=i-1; /* Number of individuals */
12733: fclose(fic);
1.225 brouard 12734:
1.136 brouard 12735: return (0);
1.164 brouard 12736: /* endread: */
1.225 brouard 12737: printf("Exiting readdata: ");
12738: fclose(fic);
12739: return (1);
1.223 brouard 12740: }
1.126 brouard 12741:
1.234 brouard 12742: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 12743: char *p1 = *stri, *p2 = *stri;
1.235 brouard 12744: while (*p2 == ' ')
1.234 brouard 12745: p2++;
12746: /* while ((*p1++ = *p2++) !=0) */
12747: /* ; */
12748: /* do */
12749: /* while (*p2 == ' ') */
12750: /* p2++; */
12751: /* while (*p1++ == *p2++); */
12752: *stri=p2;
1.145 brouard 12753: }
12754:
1.330 brouard 12755: int decoderesult( char resultline[], int nres)
1.230 brouard 12756: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
12757: {
1.235 brouard 12758: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 12759: char resultsav[MAXLINE];
1.330 brouard 12760: /* int resultmodel[MAXLINE]; */
1.334 brouard 12761: /* int modelresult[MAXLINE]; */
1.230 brouard 12762: char stra[80], strb[80], strc[80], strd[80],stre[80];
12763:
1.234 brouard 12764: removefirstspace(&resultline);
1.332 brouard 12765: printf("decoderesult:%s\n",resultline);
1.230 brouard 12766:
1.332 brouard 12767: strcpy(resultsav,resultline);
1.342 brouard 12768: /* printf("Decoderesult resultsav=\"%s\" resultline=\"%s\"\n", resultsav, resultline); */
1.230 brouard 12769: if (strlen(resultsav) >1){
1.334 brouard 12770: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' in this resultline */
1.230 brouard 12771: }
1.353 brouard 12772: if(j == 0 && cptcovs== 0){ /* Resultline but no = and no covariate in the model */
1.253 brouard 12773: TKresult[nres]=0; /* Combination for the nresult and the model */
12774: return (0);
12775: }
1.234 brouard 12776: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
1.353 brouard 12777: 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);
12778: 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);
12779: if(j==0)
12780: return 1;
1.234 brouard 12781: }
1.334 brouard 12782: for(k=1; k<=j;k++){ /* Loop on any covariate of the RESULT LINE */
1.234 brouard 12783: if(nbocc(resultsav,'=') >1){
1.318 brouard 12784: 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 12785: /* 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 12786: cutl(strc,strd,strb,'='); /* strb:"V4=1" strc="1" strd="V4" */
1.332 brouard 12787: /* If a blank, then strc="V4=" and strd='\0' */
12788: if(strc[0]=='\0'){
12789: printf("Error in resultline, probably a blank after the \"%s\", \"result:%s\", stra=\"%s\" resultsav=\"%s\"\n",strb,resultline, stra, resultsav);
12790: fprintf(ficlog,"Error in resultline, probably a blank after the \"V%s=\", resultline=%s\n",strb,resultline);
12791: return 1;
12792: }
1.234 brouard 12793: }else
12794: cutl(strc,strd,resultsav,'=');
1.318 brouard 12795: Tvalsel[k]=atof(strc); /* 1 */ /* Tvalsel of k is the float value of the kth covariate appearing in this result line */
1.234 brouard 12796:
1.230 brouard 12797: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
1.318 brouard 12798: 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 12799: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
12800: /* cptcovsel++; */
12801: if (nbocc(stra,'=') >0)
12802: strcpy(resultsav,stra); /* and analyzes it */
12803: }
1.235 brouard 12804: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 12805: /* 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 12806: 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 12807: if(Typevar[k1]==0){ /* Single covariate in model */
12808: /* 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.234 brouard 12809: match=0;
1.318 brouard 12810: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
12811: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 12812: modelresult[nres][k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.318 brouard 12813: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
1.234 brouard 12814: break;
12815: }
12816: }
12817: if(match == 0){
1.338 brouard 12818: 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]);
12819: 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 12820: return 1;
1.234 brouard 12821: }
1.332 brouard 12822: }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*/
12823: /* We feed resultmodel[k1]=k2; */
12824: match=0;
12825: 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 */
12826: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 12827: 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 12828: resultmodel[nres][k1]=k2; /* Added here */
1.342 brouard 12829: /* printf("Decoderesult first modelresult[k2=%d]=%d (k1) V%d*AGE\n",k2,k1,Tvar[k1]); */
1.332 brouard 12830: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
12831: break;
12832: }
12833: }
12834: if(match == 0){
1.338 brouard 12835: 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]);
12836: 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 12837: return 1;
12838: }
1.349 brouard 12839: }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 12840: /* resultmodel[nres][of such a Vn * Vm product k1] is not unique, so can't exist, we feed Tvard[k1][1] and [2] */
12841: match=0;
1.342 brouard 12842: /* 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 12843: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
12844: if(Tvardk[k1][1]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
12845: /* modelresult[k2]=k1; */
1.342 brouard 12846: /* printf("Decoderesult first Product modelresult[k2=%d]=%d (k1) V%d * \n",k2,k1,Tvarsel[k2]); */
1.332 brouard 12847: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
12848: }
12849: }
12850: if(match == 0){
1.349 brouard 12851: 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);
12852: 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 12853: return 1;
12854: }
12855: match=0;
12856: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
12857: if(Tvardk[k1][2]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
12858: /* modelresult[k2]=k1;*/
1.342 brouard 12859: /* printf("Decoderesult second Product modelresult[k2=%d]=%d (k1) * V%d \n ",k2,k1,Tvarsel[k2]); */
1.332 brouard 12860: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
12861: break;
12862: }
12863: }
12864: if(match == 0){
1.349 brouard 12865: 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);
12866: 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 12867: return 1;
12868: }
12869: }/* End of testing */
1.333 brouard 12870: }/* End loop cptcovt */
1.235 brouard 12871: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 12872: /* Feeds resultmodel[nres][k1]=k2 for single covariate (k1) in the model equation */
1.334 brouard 12873: 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)
12874: * Loop on resultline variables: result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 12875: match=0;
1.318 brouard 12876: 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 12877: if(Typevar[k1]==0){ /* Single only */
1.349 brouard 12878: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 What if a product? */
1.330 brouard 12879: 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 12880: 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 12881: ++match;
12882: }
12883: }
12884: }
12885: if(match == 0){
1.338 brouard 12886: printf("Error in result line: variable V%d is missing in model; result: %s, model=1+age+%s\n",Tvarsel[k2], resultline, model);
12887: 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 12888: return 1;
1.234 brouard 12889: }else if(match > 1){
1.338 brouard 12890: printf("Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
12891: fprintf(ficlog,"Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
1.310 brouard 12892: return 1;
1.234 brouard 12893: }
12894: }
1.334 brouard 12895: /* cptcovres=j /\* Number of variables in the resultline is equal to cptcovs and thus useless *\/ */
1.234 brouard 12896: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 12897: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.330 brouard 12898: /* nres=1st result line: V4=1 V5=25.1 V3=0 V2=8 V1=1 */
12899: /* 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*/
12900: /* nres=2nd result line: V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.235 brouard 12901: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
12902: /* 1 0 0 0 */
12903: /* 2 1 0 0 */
12904: /* 3 0 1 0 */
1.330 brouard 12905: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 (nres=2)*/
1.235 brouard 12906: /* 5 0 0 1 */
1.330 brouard 12907: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 (nres=1)*/
1.235 brouard 12908: /* 7 0 1 1 */
12909: /* 8 1 1 1 */
1.237 brouard 12910: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
12911: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
12912: /* V5*age V5 known which value for nres? */
12913: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.334 brouard 12914: 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.
12915: * loop on position k1 in the MODEL LINE */
1.331 brouard 12916: /* k counting number of combination of single dummies in the equation model */
12917: /* k4 counting single dummies in the equation model */
12918: /* k4q counting single quantitatives in the equation model */
1.344 brouard 12919: 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 12920: /* 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 12921: /* 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 12922: /* Value in the (current nres) resultline of the variable at the k1th position in the model equation resultmodel[nres][k1]= k3 */
1.332 brouard 12923: /* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline */
12924: /* k3 is the position in the nres result line of the k1th variable of the model equation */
12925: /* Tvarsel[k3]: Name of the variable at the k3th position in the result line. */
12926: /* Tvalsel[k3]: Value of the variable at the k3th position in the result line. */
12927: /* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.334 brouard 12928: /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 12929: /* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1.330 brouard 12930: /* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.332 brouard 12931: k3= resultmodel[nres][k1]; /* From position k1 in model get position k3 in result line */
12932: /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
12933: 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 12934: 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 12935: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][Name]=Value; stores the value into the name of the variable. */
1.332 brouard 12936: /* Tinvresult[nres][4]=1 */
1.334 brouard 12937: /* Tresult[nres][k4+1]=Tvalsel[k3];/\* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) *\/ */
12938: Tresult[nres][k3]=Tvalsel[k3];/* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) */
12939: /* Tvresult[nres][k4+1]=(int)Tvarsel[k3];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
12940: Tvresult[nres][k3]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
1.237 brouard 12941: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.334 brouard 12942: precov[nres][k1]=Tvalsel[k3]; /* Value from resultline of the variable at the k1 position in the model */
1.342 brouard 12943: /* 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 12944: k4++;;
1.331 brouard 12945: }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Quantitative and single */
1.330 brouard 12946: /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.332 brouard 12947: /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.330 brouard 12948: /* Tqinvresult[nres][Name of a quantitative variable]= value of the variable in the result line */
1.332 brouard 12949: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 5 =k3q */
12950: k2q=(int)Tvarsel[k3q]; /* Name of variable at k3q th position in the resultline */
12951: /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.334 brouard 12952: /* Tqresult[nres][k4q+1]=Tvalsel[k3q]; /\* Tqresult[nres][1]=25.1 *\/ */
12953: /* Tvresult[nres][k4q+1]=(int)Tvarsel[k3q];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
12954: /* Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /\* Tvqresult[nres][1]=5 *\/ */
12955: Tqresult[nres][k3q]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
12956: Tvresult[nres][k3q]=(int)Tvarsel[k3q];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
12957: Tvqresult[nres][k3q]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
1.237 brouard 12958: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.330 brouard 12959: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.332 brouard 12960: precov[nres][k1]=Tvalsel[k3q];
1.342 brouard 12961: /* 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 12962: k4q++;;
1.350 brouard 12963: }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"*/
12964: /* Tvar[k1]; */ /* Age variable */ /* 17 age*V6*V2 ?*/
1.332 brouard 12965: /* Wrong we want the value of variable name Tvar[k1] */
1.350 brouard 12966: if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
12967: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
12968: /* 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]]); */
12969: }else{
12970: k3= resultmodel[nres][k1]; /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
12971: 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)*/
12972: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][4]=1 */
12973: precov[nres][k1]=Tvalsel[k3];
12974: }
1.342 brouard 12975: /* 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 12976: }else if( Dummy[k1]==3 ){ /* For quant with age product */
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: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 25.1=k3q */
12982: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
12983: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* TinvDoQresult[nres][5]=25.1 */
12984: precov[nres][k1]=Tvalsel[k3q];
12985: }
1.342 brouard 12986: /* 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 12987: }else if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
1.332 brouard 12988: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
1.342 brouard 12989: /* 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 12990: }else{
1.332 brouard 12991: printf("Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
12992: fprintf(ficlog,"Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
1.235 brouard 12993: }
12994: }
1.234 brouard 12995:
1.334 brouard 12996: TKresult[nres]=++k; /* Number of combinations of dummies for the nresult and the model =Tvalsel[k3]*pow(2,k4) + 1*/
1.230 brouard 12997: return (0);
12998: }
1.235 brouard 12999:
1.230 brouard 13000: int decodemodel( char model[], int lastobs)
13001: /**< This routine decodes the model and returns:
1.224 brouard 13002: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
13003: * - nagesqr = 1 if age*age in the model, otherwise 0.
13004: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
13005: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
13006: * - cptcovage number of covariates with age*products =2
13007: * - cptcovs number of simple covariates
1.339 brouard 13008: * ncovcolt=ncovcol+nqv+ntv+nqtv total of covariates in the data, not in the model equation
1.224 brouard 13009: * - 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 13010: * which is a new column after the 9 (ncovcol+nqv+ntv+nqtv) variables.
1.319 brouard 13011: * - if k is a product Vn*Vm, covar[k][i] is filled with correct values for each individual
1.224 brouard 13012: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
13013: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
13014: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
13015: */
1.319 brouard 13016: /* 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 13017: {
1.359 brouard 13018: int i, j, k, ks;/* , v;*/
1.349 brouard 13019: int n,m;
13020: int j1, k1, k11, k12, k2, k3, k4;
13021: char modelsav[300];
13022: char stra[300], strb[300], strc[300], strd[300],stre[300],strf[300];
1.187 brouard 13023: char *strpt;
1.349 brouard 13024: int **existcomb;
13025:
13026: existcomb=imatrix(1,NCOVMAX,1,NCOVMAX);
13027: for(i=1;i<=NCOVMAX;i++)
13028: for(j=1;j<=NCOVMAX;j++)
13029: existcomb[i][j]=0;
13030:
1.145 brouard 13031: /*removespace(model);*/
1.136 brouard 13032: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.349 brouard 13033: j=0, j1=0, k1=0, k12=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 13034: if (strstr(model,"AGE") !=0){
1.192 brouard 13035: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
13036: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 13037: return 1;
13038: }
1.141 brouard 13039: if (strstr(model,"v") !=0){
1.338 brouard 13040: printf("Error. 'v' must be in upper case 'V' model=1+age+%s ",model);
13041: fprintf(ficlog,"Error. 'v' must be in upper case model=1+age+%s ",model);fflush(ficlog);
1.141 brouard 13042: return 1;
13043: }
1.187 brouard 13044: strcpy(modelsav,model);
13045: if ((strpt=strstr(model,"age*age")) !=0){
1.338 brouard 13046: printf(" strpt=%s, model=1+age+%s\n",strpt, model);
1.187 brouard 13047: if(strpt != model){
1.338 brouard 13048: printf("Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 13049: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 13050: corresponding column of parameters.\n",model);
1.338 brouard 13051: fprintf(ficlog,"Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 13052: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 13053: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 13054: return 1;
1.225 brouard 13055: }
1.187 brouard 13056: nagesqr=1;
13057: if (strstr(model,"+age*age") !=0)
1.234 brouard 13058: substrchaine(modelsav, model, "+age*age");
1.187 brouard 13059: else if (strstr(model,"age*age+") !=0)
1.234 brouard 13060: substrchaine(modelsav, model, "age*age+");
1.187 brouard 13061: else
1.234 brouard 13062: substrchaine(modelsav, model, "age*age");
1.187 brouard 13063: }else
13064: nagesqr=0;
1.349 brouard 13065: 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 13066: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
13067: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.351 brouard 13068: cptcovs=0; /**< Number of simple covariates V1 +V1*age +V3 +V3*V4 +age*age => V1 + V3 =4+1-3=2 Wrong */
1.187 brouard 13069: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 13070: * cst, age and age*age
13071: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
13072: /* including age products which are counted in cptcovage.
13073: * but the covariates which are products must be treated
13074: * separately: ncovn=4- 2=2 (V1+V3). */
1.349 brouard 13075: cptcovprod=0; /**< Number of products V1*V2 +v3*age = 2 */
13076: cptcovdageprod=0; /* Number of doouble products with age age*Vn*VM or Vn*age*Vm or Vn*Vm*age */
1.187 brouard 13077: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.349 brouard 13078: cptcovprodage=0;
13079: /* cptcovprodage=nboccstr(modelsav,"age");*/
1.225 brouard 13080:
1.187 brouard 13081: /* Design
13082: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
13083: * < ncovcol=8 >
13084: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
13085: * k= 1 2 3 4 5 6 7 8
13086: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
1.345 brouard 13087: * covar[k,i], are for fixed covariates, value of kth covariate if not including age for individual i:
1.224 brouard 13088: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
13089: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 13090: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
13091: * Tage[++cptcovage]=k
1.345 brouard 13092: * if products, new covar are created after ncovcol + nqv (quanti fixed) with k1
1.187 brouard 13093: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
13094: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
13095: * 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
13096: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
13097: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
13098: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
1.345 brouard 13099: * < ncovcol=8 8 fixed covariate. Additional starts at 9 (V5*V6) and 10(V7*V8) >
1.187 brouard 13100: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
13101: * k= 1 2 3 4 5 6 7 8 9 10 11 12
1.345 brouard 13102: * Tvard[k]= 2 1 3 3 10 11 8 8 5 6 7 8
13103: * p Tvar[1]@12={2, 1, 3, 3, 9, 10, 8, 8}
1.187 brouard 13104: * p Tprod[1]@2={ 6, 5}
13105: *p Tvard[1][1]@4= {7, 8, 5, 6}
13106: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
13107: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
1.319 brouard 13108: *How to reorganize? Tvars(orted)
1.187 brouard 13109: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
13110: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
13111: * {2, 1, 4, 8, 5, 6, 3, 7}
13112: * Struct []
13113: */
1.225 brouard 13114:
1.187 brouard 13115: /* This loop fills the array Tvar from the string 'model'.*/
13116: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
13117: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
13118: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
13119: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
13120: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
13121: /* k=1 Tvar[1]=2 (from V2) */
13122: /* k=5 Tvar[5] */
13123: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 13124: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 13125: /* } */
1.198 brouard 13126: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 13127: /*
13128: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 13129: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
13130: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
13131: }
1.187 brouard 13132: cptcovage=0;
1.351 brouard 13133:
13134: /* First loop in order to calculate */
13135: /* for age*VN*Vm
13136: * Provides, Typevar[k], Tage[cptcovage], existcomb[n][m], FixedV[ncovcolt+k12]
13137: * Tprod[k1]=k Tposprod[k]=k1; Tvard[k1][1] =m;
13138: */
13139: /* Needs FixedV[Tvardk[k][1]] */
13140: /* For others:
13141: * Sets Typevar[k];
13142: * Tvar[k]=ncovcol+nqv+ntv+nqtv+k11;
13143: * Tposprod[k]=k11;
13144: * Tprod[k11]=k;
13145: * Tvardk[k][1] =m;
13146: * Needs FixedV[Tvardk[k][1]] == 0
13147: */
13148:
1.319 brouard 13149: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model line */
13150: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+' cutl from left to right
13151: 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" */
13152: if (nbocc(modelsav,'+')==0)
13153: strcpy(strb,modelsav); /* and analyzes it */
1.234 brouard 13154: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
13155: /*scanf("%d",i);*/
1.349 brouard 13156: 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 */
13157: 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 */
13158: 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 */
13159: Typevar[k]=3; /* 3 for age and double product age*Vn*Vm varying of fixed */
13160: if(strstr(strc,"age")!=0) { /* It means that strc=V2*age or age*V2 and thus that strd=Vn */
13161: cutl(stre,strf,strc,'*') ; /* strf=age or Vm, stre=Vm or age. If strc=V6*V2 then strf=V6 and stre=V2 */
13162: strcpy(strc,strb); /* save strb(=age*Vn*Vm) into strc */
13163: /* We want strb=Vn*Vm */
13164: if(strcmp(strf,"age")==0){ /* strf is "age" so that stre=Vm =V2 . */
13165: strcpy(strb,strd);
13166: strcat(strb,"*");
13167: strcat(strb,stre);
13168: }else{ /* strf=Vm If strf=V6 then stre=V2 */
13169: strcpy(strb,strf);
13170: strcat(strb,"*");
13171: strcat(strb,stre);
13172: strcpy(strd,strb); /* in order for strd to not be "age" for next test (will be Vn*Vm */
13173: }
1.351 brouard 13174: /* 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]]]); */
13175: /* FixedV[Tvar[Tage[k]]]=0; /\* HERY not sure if V7*V4*age Fixed might not exist yet*\/ */
1.349 brouard 13176: }else{ /* strc=Vn*Vm (and strd=age) and should be strb=Vn*Vm but want to keep original strb double product */
13177: strcpy(stre,strb); /* save full b in stre */
13178: strcpy(strb,strc); /* save short c in new short b for next block strb=Vn*Vm*/
13179: strcpy(strf,strc); /* save short c in new short f */
13180: cutl(strc,strd,strf,'*'); /* We get strd=Vn and strc=Vm for next block (strb=Vn*Vm)*/
13181: /* strcpy(strc,stre);*/ /* save full e in c for future */
13182: }
13183: cptcovdageprod++; /* double product with age Which product is it? */
13184: /* 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 *\/ */
13185: /* cutl(strc,strd,strb,'*'); /\* strd= V6 or V2 or age and strc= V2 or age or V2 *\/ */
1.234 brouard 13186: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
1.349 brouard 13187: n=atoi(stre);
1.234 brouard 13188: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
1.349 brouard 13189: m=atoi(strc);
13190: cptcovage++; /* Counts the number of covariates which include age as a product */
13191: Tage[cptcovage]=k; /* For age*V3*V2 gives the position in model of covariates associated with age Tage[1]=6 HERY too*/
13192: if(existcomb[n][m] == 0){
13193: /* r /home/brouard/Documents/Recherches/REVES/Zachary/Zach-2022/Feinuo_Sun/Feinuo-threeway/femV12V15_3wayintNBe.imach */
13194: 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);
13195: 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);
13196: fflush(ficlog);
13197: k1++; /* The combination Vn*Vm will be in the model so we create it at k1 */
13198: k12++;
13199: existcomb[n][m]=k1;
13200: existcomb[m][n]=k1;
13201: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1;
13202: 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*/
13203: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 Gives the k1 double product Vn*Vm or age*Vn*Vm at the k position */
13204: Tvard[k1][1] =m; /* m 1 for V1*/
13205: Tvardk[k][1] =m; /* m 1 for V1*/
13206: Tvard[k1][2] =n; /* n 4 for V4*/
13207: Tvardk[k][2] =n; /* n 4 for V4*/
1.351 brouard 13208: /* Tvar[Tage[cptcovage]]=k1;*/ /* Tvar[6=age*V3*V2]=9 (new fixed covariate) */ /* We don't know about Fixed yet HERE */
1.349 brouard 13209: 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 */
13210: for (i=1; i<=lastobs;i++){/* For fixed product */
13211: /* Computes the new covariate which is a product of
13212: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
13213: covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
13214: }
13215: cptcovprodage++; /* Counting the number of fixed covariate with age */
13216: FixedV[ncovcolt+k12]=0; /* We expand Vn*Vm */
13217: k12++;
13218: FixedV[ncovcolt+k12]=0;
13219: }else{ /*End of FixedV */
13220: cptcovprodvage++; /* Counting the number of varying covariate with age */
13221: FixedV[ncovcolt+k12]=1; /* We expand Vn*Vm */
13222: k12++;
13223: FixedV[ncovcolt+k12]=1;
13224: }
13225: }else{ /* k1 Vn*Vm already exists */
13226: k11=existcomb[n][m];
13227: Tposprod[k]=k11; /* OK */
13228: Tvar[k]=Tvar[Tprod[k11]]; /* HERY */
13229: Tvardk[k][1]=m;
13230: Tvardk[k][2]=n;
13231: 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 */
13232: /*cptcovage++;*/ /* Counts the number of covariates which include age as a product */
13233: cptcovprodage++; /* Counting the number of fixed covariate with age */
13234: /*Tage[cptcovage]=k;*/ /* For age*V3*V2 Tage[1]=V3*V3=9 HERY too*/
13235: Tvar[Tage[cptcovage]]=k1;
13236: FixedV[ncovcolt+k12]=0; /* We expand Vn*Vm */
13237: k12++;
13238: FixedV[ncovcolt+k12]=0;
13239: }else{ /* Already exists but time varying (and age) */
13240: /*cptcovage++;*/ /* Counts the number of covariates which include age as a product */
13241: /*Tage[cptcovage]=k;*/ /* For age*V3*V2 Tage[1]=V3*V3=9 HERY too*/
13242: /* Tvar[Tage[cptcovage]]=k1; */
13243: cptcovprodvage++;
13244: FixedV[ncovcolt+k12]=1; /* We expand Vn*Vm */
13245: k12++;
13246: FixedV[ncovcolt+k12]=1;
13247: }
13248: }
13249: /* Tage[cptcovage]=k; /\* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
13250: /* Tvar[k]=k11; /\* HERY *\/ */
13251: } 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 */
13252: cptcovprod++;
13253: if (strcmp(strc,"age")==0) { /**< Model includes age: strb= Vn*age c=age d=Vn*/
13254: /* covar is not filled and then is empty */
13255: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
13256: 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 */
13257: Typevar[k]=1; /* 1 for age product */
13258: cptcovage++; /* Counts the number of covariates which include age as a product */
13259: Tage[cptcovage]=k; /* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
13260: if( FixedV[Tvar[k]] == 0){
13261: cptcovprodage++; /* Counting the number of fixed covariate with age */
13262: }else{
13263: cptcovprodvage++; /* Counting the number of fixedvarying covariate with age */
13264: }
13265: /*printf("stre=%s ", stre);*/
13266: } else if (strcmp(strd,"age")==0) { /* strb= age*Vn c=Vn */
13267: cutl(stre,strb,strc,'V');
13268: Tvar[k]=atoi(stre);
13269: Typevar[k]=1; /* 1 for age product */
13270: cptcovage++;
13271: Tage[cptcovage]=k;
13272: if( FixedV[Tvar[k]] == 0){
13273: cptcovprodage++; /* Counting the number of fixed covariate with age */
13274: }else{
13275: cptcovprodvage++; /* Counting the number of fixedvarying covariate with age */
1.339 brouard 13276: }
1.349 brouard 13277: }else{ /* for product Vn*Vm */
13278: Typevar[k]=2; /* 2 for product Vn*Vm */
13279: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
13280: n=atoi(stre);
13281: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
13282: m=atoi(strc);
13283: k1++;
13284: cptcovprodnoage++;
13285: if(existcomb[n][m] != 0 || existcomb[m][n] != 0){
13286: printf("Warning in model combination V%d*V%d already exists in the model in position k1=%d!\n",n,m,existcomb[n][m]);
13287: 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]);
13288: fflush(ficlog);
13289: k11=existcomb[n][m];
13290: Tvar[k]=ncovcol+nqv+ntv+nqtv+k11;
13291: Tposprod[k]=k11;
13292: Tprod[k11]=k;
13293: Tvardk[k][1] =m; /* m 1 for V1*/
13294: /* Tvard[k11][1] =m; /\* n 4 for V4*\/ */
13295: Tvardk[k][2] =n; /* n 4 for V4*/
13296: /* Tvard[k11][2] =n; /\* n 4 for V4*\/ */
13297: }else{ /* combination Vn*Vm doesn't exist we create it (no age)*/
13298: existcomb[n][m]=k1;
13299: existcomb[m][n]=k1;
13300: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* ncovcolt+k1; For model-covariate k tells which data-covariate to use but
13301: because this model-covariate is a construction we invent a new column
13302: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
13303: If already ncovcol=4 and model= V2 + V1 + V1*V4 + age*V3 + V3*V2
13304: thus after V4 we invent V5 and V6 because age*V3 will be computed in 4
13305: Tvar[3=V1*V4]=4+1=5 Tvar[5=V3*V2]=4 + 2= 6, Tvar[4=age*V3]=3 etc */
13306: /* Please remark that the new variables are model dependent */
13307: /* If we have 4 variable but the model uses only 3, like in
13308: * model= V1 + age*V1 + V2 + V3 + age*V2 + age*V3 + V1*V2 + V1*V3
13309: * k= 1 2 3 4 5 6 7 8
13310: * Tvar[k]=1 1 2 3 2 3 (5 6) (and not 4 5 because of V4 missing)
13311: * Tage[kk] [1]= 2 [2]=5 [3]=6 kk=1 to cptcovage=3
13312: * Tvar[Tage[kk]][1]=2 [2]=2 [3]=3
13313: */
13314: /* We need to feed some variables like TvarVV, but later on next loop because of ncovv (k2) is not correct */
13315: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 +V6*V2*age */
13316: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 */
13317: Tvard[k1][1] =m; /* m 1 for V1*/
13318: Tvardk[k][1] =m; /* m 1 for V1*/
13319: Tvard[k1][2] =n; /* n 4 for V4*/
13320: Tvardk[k][2] =n; /* n 4 for V4*/
13321: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
13322: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
13323: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
13324: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
13325: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
13326: 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 */
13327: for (i=1; i<=lastobs;i++){/* For fixed product */
13328: /* Computes the new covariate which is a product of
13329: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
13330: covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
13331: }
13332: /* TvarVV[k2]=n; */
13333: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
13334: /* TvarVV[k2+1]=m; */
13335: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
13336: }else{ /* not FixedV */
13337: /* TvarVV[k2]=n; */
13338: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
13339: /* TvarVV[k2+1]=m; */
13340: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
13341: }
13342: } /* End of creation of Vn*Vm if not created by age*Vn*Vm earlier */
13343: } /* End of product Vn*Vm */
13344: } /* End of age*double product or simple product */
13345: }else { /* not a product */
1.234 brouard 13346: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
13347: /* scanf("%d",i);*/
13348: cutl(strd,strc,strb,'V');
13349: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
13350: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
13351: Tvar[k]=atoi(strd);
13352: Typevar[k]=0; /* 0 for simple covariates */
13353: }
13354: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 13355: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 13356: scanf("%d",i);*/
1.187 brouard 13357: } /* end of loop + on total covariates */
1.351 brouard 13358:
13359:
1.187 brouard 13360: } /* end if strlen(modelsave == 0) age*age might exist */
13361: } /* end if strlen(model == 0) */
1.349 brouard 13362: 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 */
13363:
1.136 brouard 13364: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
13365: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 13366:
1.136 brouard 13367: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 13368: printf("cptcovprod=%d ", cptcovprod);
13369: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
13370: scanf("%d ",i);*/
13371:
13372:
1.230 brouard 13373: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
13374: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 13375: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
13376: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
13377: k = 1 2 3 4 5 6 7 8 9
13378: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
1.319 brouard 13379: Typevar[k]= 0 0 0 2 1 0 2 1 0
1.227 brouard 13380: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
13381: Dummy[k] 1 0 0 0 3 1 1 2 3
13382: Tmodelind[combination of covar]=k;
1.225 brouard 13383: */
13384: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 13385: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 13386: /* 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 13387: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.318 brouard 13388: printf("Model=1+age+%s\n\
1.349 brouard 13389: 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 13390: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
13391: 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 13392: fprintf(ficlog,"Model=1+age+%s\n\
1.349 brouard 13393: 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 13394: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
13395: 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 13396: for(k=-1;k<=NCOVMAX; k++){ Fixed[k]=0; Dummy[k]=0;}
13397: for(k=1;k<=NCOVMAX; k++){TvarFind[k]=0; TvarVind[k]=0;}
1.351 brouard 13398:
13399:
13400: /* Second loop for calculating Fixed[k], Dummy[k]*/
13401:
13402:
1.349 brouard 13403: 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 13404: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 13405: Fixed[k]= 0;
13406: Dummy[k]= 0;
1.225 brouard 13407: ncoveff++;
1.232 brouard 13408: ncovf++;
1.234 brouard 13409: nsd++;
13410: modell[k].maintype= FTYPE;
13411: TvarsD[nsd]=Tvar[k];
13412: TvarsDind[nsd]=k;
1.330 brouard 13413: TnsdVar[Tvar[k]]=nsd;
1.234 brouard 13414: TvarF[ncovf]=Tvar[k];
13415: TvarFind[ncovf]=k;
13416: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
13417: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.339 brouard 13418: /* }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 13419: }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 13420: Fixed[k]= 0;
13421: Dummy[k]= 1;
1.230 brouard 13422: nqfveff++;
1.234 brouard 13423: modell[k].maintype= FTYPE;
13424: modell[k].subtype= FQ;
13425: nsq++;
1.334 brouard 13426: TvarsQ[nsq]=Tvar[k]; /* Gives the variable name (extended to products) of first nsq simple quantitative covariates (fixed or time vary see below */
13427: TvarsQind[nsq]=k; /* Gives the position in the model equation of the first nsq simple quantitative covariates (fixed or time vary) */
1.232 brouard 13428: ncovf++;
1.234 brouard 13429: TvarF[ncovf]=Tvar[k];
13430: TvarFind[ncovf]=k;
1.231 brouard 13431: 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 13432: 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 13433: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.339 brouard 13434: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
13435: /* model V1+V3+age*V1+age*V3+V1*V3 */
13436: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
13437: ncovvt++;
13438: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
13439: TvarVVind[ncovvt]=k; /* TvarVVind[1]=2 (second position in the model equation */
13440:
1.227 brouard 13441: Fixed[k]= 1;
13442: Dummy[k]= 0;
1.225 brouard 13443: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 13444: modell[k].maintype= VTYPE;
13445: modell[k].subtype= VD;
13446: nsd++;
13447: TvarsD[nsd]=Tvar[k];
13448: TvarsDind[nsd]=k;
1.330 brouard 13449: TnsdVar[Tvar[k]]=nsd; /* To be verified */
1.234 brouard 13450: ncovv++; /* Only simple time varying variables */
13451: TvarV[ncovv]=Tvar[k];
1.242 brouard 13452: 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 13453: 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 */
13454: 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 13455: 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);
13456: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 13457: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.339 brouard 13458: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
13459: /* model V1+V3+age*V1+age*V3+V1*V3 */
13460: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
13461: ncovvt++;
13462: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
13463: TvarVVind[ncovvt]=k; /* TvarVV[1]=V3 (first time varying in the model equation */
13464:
1.234 brouard 13465: Fixed[k]= 1;
13466: Dummy[k]= 1;
13467: nqtveff++;
13468: modell[k].maintype= VTYPE;
13469: modell[k].subtype= VQ;
13470: ncovv++; /* Only simple time varying variables */
13471: nsq++;
1.334 brouard 13472: 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) */
13473: 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 13474: TvarV[ncovv]=Tvar[k];
1.242 brouard 13475: 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 13476: 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 */
13477: 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 13478: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
13479: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
1.349 brouard 13480: /* 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 13481: /* printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv); */
1.227 brouard 13482: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 13483: ncova++;
13484: TvarA[ncova]=Tvar[k];
13485: TvarAind[ncova]=k;
1.349 brouard 13486: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
13487: /** 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 13488: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 13489: Fixed[k]= 2;
13490: Dummy[k]= 2;
13491: modell[k].maintype= ATYPE;
13492: modell[k].subtype= APFD;
1.349 brouard 13493: ncovta++;
13494: TvarAVVA[ncovta]=Tvar[k]; /* (2)age*V3 */
13495: TvarAVVAind[ncovta]=k;
1.240 brouard 13496: /* ncoveff++; */
1.227 brouard 13497: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 13498: Fixed[k]= 2;
13499: Dummy[k]= 3;
13500: modell[k].maintype= ATYPE;
13501: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
1.349 brouard 13502: ncovta++;
13503: TvarAVVA[ncovta]=Tvar[k]; /* */
13504: TvarAVVAind[ncovta]=k;
1.240 brouard 13505: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 13506: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 13507: Fixed[k]= 3;
13508: Dummy[k]= 2;
13509: modell[k].maintype= ATYPE;
13510: modell[k].subtype= APVD; /* Product age * varying dummy */
1.349 brouard 13511: ncovva++;
13512: TvarVVA[ncovva]=Tvar[k]; /* (1)+age*V6 + (2)age*V7 */
13513: TvarVVAind[ncovva]=k;
13514: ncovta++;
13515: TvarAVVA[ncovta]=Tvar[k]; /* */
13516: TvarAVVAind[ncovta]=k;
1.240 brouard 13517: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 13518: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 13519: Fixed[k]= 3;
13520: Dummy[k]= 3;
13521: modell[k].maintype= ATYPE;
13522: modell[k].subtype= APVQ; /* Product age * varying quantitative */
1.349 brouard 13523: ncovva++;
13524: TvarVVA[ncovva]=Tvar[k]; /* */
13525: TvarVVAind[ncovva]=k;
13526: ncovta++;
13527: TvarAVVA[ncovta]=Tvar[k]; /* (1)+age*V6 + (2)age*V7 */
13528: TvarAVVAind[ncovta]=k;
1.240 brouard 13529: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 13530: }
1.349 brouard 13531: }else if( Tposprod[k]>0 && Typevar[k]==2){ /* Detects if fixed product no age Vm*Vn */
13532: printf("MEMORY ERRORR k=%d Tposprod[k]=%d, Typevar[k]=%d\n ",k, Tposprod[k], Typevar[k]);
13533: 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 */
13534: 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]]);
13535: Fixed[k]= 0;
13536: Dummy[k]= 0;
13537: ncoveff++;
13538: ncovf++;
13539: /* ncovv++; */
13540: /* TvarVV[ncovv]=Tvardk[k][1]; */
13541: /* FixedV[ncovcolt+ncovv]=0; /\* or FixedV[TvarVV[ncovv]]=0 HERE *\/ */
13542: /* ncovv++; */
13543: /* TvarVV[ncovv]=Tvardk[k][2]; */
13544: /* FixedV[ncovcolt+ncovv]=0; /\* or FixedV[TvarVV[ncovv]]=0 HERE *\/ */
13545: modell[k].maintype= FTYPE;
13546: TvarF[ncovf]=Tvar[k];
13547: /* TnsdVar[Tvar[k]]=nsd; */ /* To be done */
13548: TvarFind[ncovf]=k;
13549: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
13550: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
13551: }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 */
13552: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
13553: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age*/
13554: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
13555: 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 */
13556: ncovvt++;
13557: TvarVV[ncovvt]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */
13558: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
13559: ncovvt++;
13560: TvarVV[ncovvt]=Tvard[k1][2]; /* TvarVV[3]=V3 */
13561: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
13562:
13563: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
13564: /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
13565:
13566: if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */
13567: if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */
13568: Fixed[k]= 1;
13569: Dummy[k]= 0;
13570: modell[k].maintype= FTYPE;
13571: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
13572: ncovf++; /* Fixed variables without age */
13573: TvarF[ncovf]=Tvar[k];
13574: TvarFind[ncovf]=k;
13575: }else if(Tvard[k1][2] <=ncovcol+nqv){ /* Vm is quanti fixed */
13576: Fixed[k]= 0; /* Fixed product */
13577: Dummy[k]= 1;
13578: modell[k].maintype= FTYPE;
13579: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
13580: ncovf++; /* Varying variables without age */
13581: TvarF[ncovf]=Tvar[k];
13582: TvarFind[ncovf]=k;
13583: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is a time varying dummy covariate */
13584: Fixed[k]= 1;
13585: Dummy[k]= 0;
13586: modell[k].maintype= VTYPE;
13587: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
13588: ncovv++; /* Varying variables without age */
13589: TvarV[ncovv]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */
13590: TvarVind[ncovv]=k;/* TvarVind[1]=5 */
13591: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */
13592: Fixed[k]= 1;
13593: Dummy[k]= 1;
13594: modell[k].maintype= VTYPE;
13595: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
13596: ncovv++; /* Varying variables without age */
13597: TvarV[ncovv]=Tvar[k];
13598: TvarVind[ncovv]=k;
13599: }
13600: }else if(Tvard[k1][1] <=ncovcol+nqv){ /* Vn is fixed quanti */
13601: if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */
13602: Fixed[k]= 0; /* Fixed product */
13603: Dummy[k]= 1;
13604: modell[k].maintype= FTYPE;
13605: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
13606: ncovf++; /* Fixed variables without age */
13607: TvarF[ncovf]=Tvar[k];
13608: TvarFind[ncovf]=k;
13609: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is time varying */
13610: Fixed[k]= 1;
13611: Dummy[k]= 1;
13612: modell[k].maintype= VTYPE;
13613: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
13614: ncovv++; /* Varying variables without age */
13615: TvarV[ncovv]=Tvar[k];
13616: TvarVind[ncovv]=k;
13617: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is time varying quanti */
13618: Fixed[k]= 1;
13619: Dummy[k]= 1;
13620: modell[k].maintype= VTYPE;
13621: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
13622: ncovv++; /* Varying variables without age */
13623: TvarV[ncovv]=Tvar[k];
13624: TvarVind[ncovv]=k;
13625: ncovv++; /* Varying variables without age */
13626: TvarV[ncovv]=Tvar[k];
13627: TvarVind[ncovv]=k;
13628: }
13629: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ /* Vn is time varying dummy */
13630: if(Tvard[k1][2] <=ncovcol){
13631: Fixed[k]= 1;
13632: Dummy[k]= 1;
13633: modell[k].maintype= VTYPE;
13634: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
13635: ncovv++; /* Varying variables without age */
13636: TvarV[ncovv]=Tvar[k];
13637: TvarVind[ncovv]=k;
13638: }else if(Tvard[k1][2] <=ncovcol+nqv){
13639: Fixed[k]= 1;
13640: Dummy[k]= 1;
13641: modell[k].maintype= VTYPE;
13642: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
13643: ncovv++; /* Varying variables without age */
13644: TvarV[ncovv]=Tvar[k];
13645: TvarVind[ncovv]=k;
13646: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
13647: Fixed[k]= 1;
13648: Dummy[k]= 0;
13649: modell[k].maintype= VTYPE;
13650: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
13651: ncovv++; /* Varying variables without age */
13652: TvarV[ncovv]=Tvar[k];
13653: TvarVind[ncovv]=k;
13654: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
13655: Fixed[k]= 1;
13656: Dummy[k]= 1;
13657: modell[k].maintype= VTYPE;
13658: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
13659: ncovv++; /* Varying variables without age */
13660: TvarV[ncovv]=Tvar[k];
13661: TvarVind[ncovv]=k;
13662: }
13663: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ /* Vn is time varying quanti */
13664: if(Tvard[k1][2] <=ncovcol){
13665: Fixed[k]= 1;
13666: Dummy[k]= 1;
13667: modell[k].maintype= VTYPE;
13668: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
13669: ncovv++; /* Varying variables without age */
13670: TvarV[ncovv]=Tvar[k];
13671: TvarVind[ncovv]=k;
13672: }else if(Tvard[k1][2] <=ncovcol+nqv){
13673: Fixed[k]= 1;
13674: Dummy[k]= 1;
13675: modell[k].maintype= VTYPE;
13676: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
13677: ncovv++; /* Varying variables without age */
13678: TvarV[ncovv]=Tvar[k];
13679: TvarVind[ncovv]=k;
13680: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
13681: Fixed[k]= 1;
13682: Dummy[k]= 1;
13683: modell[k].maintype= VTYPE;
13684: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
13685: ncovv++; /* Varying variables without age */
13686: TvarV[ncovv]=Tvar[k];
13687: TvarVind[ncovv]=k;
13688: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
13689: Fixed[k]= 1;
13690: Dummy[k]= 1;
13691: modell[k].maintype= VTYPE;
13692: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
13693: ncovv++; /* Varying variables without age */
13694: TvarV[ncovv]=Tvar[k];
13695: TvarVind[ncovv]=k;
13696: }
13697: }else{
13698: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
13699: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
13700: } /*end k1*/
13701: }
13702: }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 13703: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
1.349 brouard 13704: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age*/
13705: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
13706: 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 */
13707: ncova++;
13708: TvarA[ncova]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */
13709: TvarAind[ncova]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
13710: ncova++;
13711: TvarA[ncova]=Tvard[k1][2]; /* TvarVV[3]=V3 */
13712: TvarAind[ncova]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
1.339 brouard 13713:
1.349 brouard 13714: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
13715: /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
13716: if( FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){
13717: ncovta++;
13718: TvarAVVA[ncovta]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
13719: TvarAVVAind[ncovta]=k;
13720: ncovta++;
13721: TvarAVVA[ncovta]=Tvard[k1][2]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
13722: TvarAVVAind[ncovta]=k;
13723: }else{
13724: ncovva++; /* HERY reached */
13725: TvarVVA[ncovva]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
13726: TvarVVAind[ncovva]=k;
13727: ncovva++;
13728: TvarVVA[ncovva]=Tvard[k1][2]; /* */
13729: TvarVVAind[ncovva]=k;
13730: ncovta++;
13731: TvarAVVA[ncovta]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
13732: TvarAVVAind[ncovta]=k;
13733: ncovta++;
13734: TvarAVVA[ncovta]=Tvard[k1][2]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
13735: TvarAVVAind[ncovta]=k;
13736: }
1.339 brouard 13737: if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */
13738: if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */
1.349 brouard 13739: Fixed[k]= 2;
13740: Dummy[k]= 2;
1.240 brouard 13741: modell[k].maintype= FTYPE;
13742: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
1.349 brouard 13743: /* TvarF[ncova]=Tvar[k]; /\* Problem to solve *\/ */
13744: /* TvarFind[ncova]=k; */
1.339 brouard 13745: }else if(Tvard[k1][2] <=ncovcol+nqv){ /* Vm is quanti fixed */
1.349 brouard 13746: Fixed[k]= 2; /* Fixed product */
13747: Dummy[k]= 3;
1.240 brouard 13748: modell[k].maintype= FTYPE;
13749: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
1.349 brouard 13750: /* TvarF[ncova]=Tvar[k]; */
13751: /* TvarFind[ncova]=k; */
1.339 brouard 13752: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is a time varying dummy covariate */
1.349 brouard 13753: Fixed[k]= 3;
13754: Dummy[k]= 2;
1.240 brouard 13755: modell[k].maintype= VTYPE;
13756: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
1.349 brouard 13757: TvarV[ncova]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */
13758: TvarVind[ncova]=k;/* TvarVind[1]=5 */
1.339 brouard 13759: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */
1.349 brouard 13760: Fixed[k]= 3;
13761: Dummy[k]= 3;
1.240 brouard 13762: modell[k].maintype= VTYPE;
13763: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
1.349 brouard 13764: /* ncovv++; /\* Varying variables without age *\/ */
13765: /* TvarV[ncovv]=Tvar[k]; */
13766: /* TvarVind[ncovv]=k; */
1.240 brouard 13767: }
1.339 brouard 13768: }else if(Tvard[k1][1] <=ncovcol+nqv){ /* Vn is fixed quanti */
13769: if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */
1.349 brouard 13770: Fixed[k]= 2; /* Fixed product */
13771: Dummy[k]= 2;
1.240 brouard 13772: modell[k].maintype= FTYPE;
13773: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
1.349 brouard 13774: /* ncova++; /\* Fixed variables with age *\/ */
13775: /* TvarF[ncovf]=Tvar[k]; */
13776: /* TvarFind[ncovf]=k; */
1.339 brouard 13777: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is time varying */
1.349 brouard 13778: Fixed[k]= 2;
13779: Dummy[k]= 3;
1.240 brouard 13780: modell[k].maintype= VTYPE;
13781: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
1.349 brouard 13782: /* ncova++; /\* Varying variables with age *\/ */
13783: /* TvarV[ncova]=Tvar[k]; */
13784: /* TvarVind[ncova]=k; */
1.339 brouard 13785: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is time varying quanti */
1.349 brouard 13786: Fixed[k]= 3;
13787: Dummy[k]= 2;
1.240 brouard 13788: modell[k].maintype= VTYPE;
13789: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
1.349 brouard 13790: ncova++; /* Varying variables without age */
13791: TvarV[ncova]=Tvar[k];
13792: TvarVind[ncova]=k;
13793: /* ncova++; /\* Varying variables without age *\/ */
13794: /* TvarV[ncova]=Tvar[k]; */
13795: /* TvarVind[ncova]=k; */
1.240 brouard 13796: }
1.339 brouard 13797: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ /* Vn is time varying dummy */
1.240 brouard 13798: if(Tvard[k1][2] <=ncovcol){
1.349 brouard 13799: Fixed[k]= 2;
13800: Dummy[k]= 2;
1.240 brouard 13801: modell[k].maintype= VTYPE;
13802: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
1.349 brouard 13803: /* ncova++; /\* Varying variables with age *\/ */
13804: /* TvarV[ncova]=Tvar[k]; */
13805: /* TvarVind[ncova]=k; */
1.240 brouard 13806: }else if(Tvard[k1][2] <=ncovcol+nqv){
1.349 brouard 13807: Fixed[k]= 2;
13808: Dummy[k]= 3;
1.240 brouard 13809: modell[k].maintype= VTYPE;
13810: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
1.349 brouard 13811: /* ncova++; /\* Varying variables with age *\/ */
13812: /* TvarV[ncova]=Tvar[k]; */
13813: /* TvarVind[ncova]=k; */
1.240 brouard 13814: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
1.349 brouard 13815: Fixed[k]= 3;
13816: Dummy[k]= 2;
1.240 brouard 13817: modell[k].maintype= VTYPE;
13818: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
1.349 brouard 13819: /* ncova++; /\* Varying variables with age *\/ */
13820: /* TvarV[ncova]=Tvar[k]; */
13821: /* TvarVind[ncova]=k; */
1.240 brouard 13822: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
1.349 brouard 13823: Fixed[k]= 3;
13824: Dummy[k]= 3;
1.240 brouard 13825: modell[k].maintype= VTYPE;
13826: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
1.349 brouard 13827: /* ncova++; /\* Varying variables with age *\/ */
13828: /* TvarV[ncova]=Tvar[k]; */
13829: /* TvarVind[ncova]=k; */
1.240 brouard 13830: }
1.339 brouard 13831: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ /* Vn is time varying quanti */
1.240 brouard 13832: if(Tvard[k1][2] <=ncovcol){
1.349 brouard 13833: Fixed[k]= 2;
13834: Dummy[k]= 2;
1.240 brouard 13835: modell[k].maintype= VTYPE;
13836: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
1.349 brouard 13837: /* ncova++; /\* Varying variables with age *\/ */
13838: /* TvarV[ncova]=Tvar[k]; */
13839: /* TvarVind[ncova]=k; */
1.240 brouard 13840: }else if(Tvard[k1][2] <=ncovcol+nqv){
1.349 brouard 13841: Fixed[k]= 2;
13842: Dummy[k]= 3;
1.240 brouard 13843: modell[k].maintype= VTYPE;
13844: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
1.349 brouard 13845: /* ncova++; /\* Varying variables with age *\/ */
13846: /* TvarV[ncova]=Tvar[k]; */
13847: /* TvarVind[ncova]=k; */
1.240 brouard 13848: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
1.349 brouard 13849: Fixed[k]= 3;
13850: Dummy[k]= 2;
1.240 brouard 13851: modell[k].maintype= VTYPE;
13852: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
1.349 brouard 13853: /* ncova++; /\* Varying variables with age *\/ */
13854: /* TvarV[ncova]=Tvar[k]; */
13855: /* TvarVind[ncova]=k; */
1.240 brouard 13856: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
1.349 brouard 13857: Fixed[k]= 3;
13858: Dummy[k]= 3;
1.240 brouard 13859: modell[k].maintype= VTYPE;
13860: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
1.349 brouard 13861: /* ncova++; /\* Varying variables with age *\/ */
13862: /* TvarV[ncova]=Tvar[k]; */
13863: /* TvarVind[ncova]=k; */
1.240 brouard 13864: }
1.227 brouard 13865: }else{
1.240 brouard 13866: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
13867: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
13868: } /*end k1*/
1.349 brouard 13869: } else{
1.226 brouard 13870: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
13871: 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 13872: }
1.342 brouard 13873: /* 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]); */
13874: /* printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype); */
1.227 brouard 13875: 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]);
13876: }
1.349 brouard 13877: ncovvta=ncovva;
1.227 brouard 13878: /* Searching for doublons in the model */
13879: for(k1=1; k1<= cptcovt;k1++){
13880: for(k2=1; k2 <k1;k2++){
1.285 brouard 13881: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
13882: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 13883: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
13884: if(Tvar[k1]==Tvar[k2]){
1.338 brouard 13885: 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]);
13886: 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 13887: return(1);
13888: }
13889: }else if (Typevar[k1] ==2){
13890: k3=Tposprod[k1];
13891: k4=Tposprod[k2];
13892: 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 13893: 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]]);
13894: 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 13895: return(1);
13896: }
13897: }
1.227 brouard 13898: }
13899: }
1.225 brouard 13900: }
13901: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
13902: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 13903: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
13904: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.349 brouard 13905:
13906: free_imatrix(existcomb,1,NCOVMAX,1,NCOVMAX);
1.137 brouard 13907: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 13908: /*endread:*/
1.225 brouard 13909: printf("Exiting decodemodel: ");
13910: return (1);
1.136 brouard 13911: }
13912:
1.169 brouard 13913: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 13914: {/* Check ages at death */
1.136 brouard 13915: int i, m;
1.218 brouard 13916: int firstone=0;
13917:
1.136 brouard 13918: for (i=1; i<=imx; i++) {
13919: for(m=2; (m<= maxwav); m++) {
13920: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
13921: anint[m][i]=9999;
1.216 brouard 13922: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
13923: s[m][i]=-1;
1.136 brouard 13924: }
13925: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 13926: *nberr = *nberr + 1;
1.218 brouard 13927: if(firstone == 0){
13928: firstone=1;
1.260 brouard 13929: 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 13930: }
1.262 brouard 13931: 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 13932: s[m][i]=-1; /* Droping the death status */
1.136 brouard 13933: }
13934: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 13935: (*nberr)++;
1.259 brouard 13936: 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 13937: 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 13938: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 13939: }
13940: }
13941: }
13942:
13943: for (i=1; i<=imx; i++) {
13944: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
13945: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 13946: 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 13947: if (s[m][i] >= nlstate+1) {
1.169 brouard 13948: if(agedc[i]>0){
13949: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 13950: agev[m][i]=agedc[i];
1.214 brouard 13951: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 13952: }else {
1.136 brouard 13953: if ((int)andc[i]!=9999){
13954: nbwarn++;
13955: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
13956: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
13957: agev[m][i]=-1;
13958: }
13959: }
1.169 brouard 13960: } /* agedc > 0 */
1.214 brouard 13961: } /* end if */
1.136 brouard 13962: else if(s[m][i] !=9){ /* Standard case, age in fractional
13963: years but with the precision of a month */
13964: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
13965: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
13966: agev[m][i]=1;
13967: else if(agev[m][i] < *agemin){
13968: *agemin=agev[m][i];
13969: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
13970: }
13971: else if(agev[m][i] >*agemax){
13972: *agemax=agev[m][i];
1.156 brouard 13973: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 13974: }
13975: /*agev[m][i]=anint[m][i]-annais[i];*/
13976: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 13977: } /* en if 9*/
1.136 brouard 13978: else { /* =9 */
1.214 brouard 13979: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 13980: agev[m][i]=1;
13981: s[m][i]=-1;
13982: }
13983: }
1.214 brouard 13984: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 13985: agev[m][i]=1;
1.214 brouard 13986: else{
13987: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
13988: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
13989: agev[m][i]=0;
13990: }
13991: } /* End for lastpass */
13992: }
1.136 brouard 13993:
13994: for (i=1; i<=imx; i++) {
13995: for(m=firstpass; (m<=lastpass); m++){
13996: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 13997: (*nberr)++;
1.136 brouard 13998: 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);
13999: 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);
14000: return 1;
14001: }
14002: }
14003: }
14004:
14005: /*for (i=1; i<=imx; i++){
14006: for (m=firstpass; (m<lastpass); m++){
14007: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
14008: }
14009:
14010: }*/
14011:
14012:
1.139 brouard 14013: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
14014: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 14015:
14016: return (0);
1.164 brouard 14017: /* endread:*/
1.136 brouard 14018: printf("Exiting calandcheckages: ");
14019: return (1);
14020: }
14021:
1.172 brouard 14022: #if defined(_MSC_VER)
14023: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
14024: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
14025: //#include "stdafx.h"
14026: //#include <stdio.h>
14027: //#include <tchar.h>
14028: //#include <windows.h>
14029: //#include <iostream>
14030: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
14031:
14032: LPFN_ISWOW64PROCESS fnIsWow64Process;
14033:
14034: BOOL IsWow64()
14035: {
14036: BOOL bIsWow64 = FALSE;
14037:
14038: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
14039: // (HANDLE, PBOOL);
14040:
14041: //LPFN_ISWOW64PROCESS fnIsWow64Process;
14042:
14043: HMODULE module = GetModuleHandle(_T("kernel32"));
14044: const char funcName[] = "IsWow64Process";
14045: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
14046: GetProcAddress(module, funcName);
14047:
14048: if (NULL != fnIsWow64Process)
14049: {
14050: if (!fnIsWow64Process(GetCurrentProcess(),
14051: &bIsWow64))
14052: //throw std::exception("Unknown error");
14053: printf("Unknown error\n");
14054: }
14055: return bIsWow64 != FALSE;
14056: }
14057: #endif
1.177 brouard 14058:
1.191 brouard 14059: void syscompilerinfo(int logged)
1.292 brouard 14060: {
14061: #include <stdint.h>
14062:
14063: /* #include "syscompilerinfo.h"*/
1.185 brouard 14064: /* command line Intel compiler 32bit windows, XP compatible:*/
14065: /* /GS /W3 /Gy
14066: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
14067: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
14068: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 14069: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
14070: */
14071: /* 64 bits */
1.185 brouard 14072: /*
14073: /GS /W3 /Gy
14074: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
14075: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
14076: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
14077: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
14078: /* Optimization are useless and O3 is slower than O2 */
14079: /*
14080: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
14081: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
14082: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
14083: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
14084: */
1.186 brouard 14085: /* Link is */ /* /OUT:"visual studio
1.185 brouard 14086: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
14087: /PDB:"visual studio
14088: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
14089: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
14090: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
14091: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
14092: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
14093: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
14094: uiAccess='false'"
14095: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
14096: /NOLOGO /TLBID:1
14097: */
1.292 brouard 14098:
14099:
1.177 brouard 14100: #if defined __INTEL_COMPILER
1.178 brouard 14101: #if defined(__GNUC__)
14102: struct utsname sysInfo; /* For Intel on Linux and OS/X */
14103: #endif
1.177 brouard 14104: #elif defined(__GNUC__)
1.179 brouard 14105: #ifndef __APPLE__
1.174 brouard 14106: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 14107: #endif
1.177 brouard 14108: struct utsname sysInfo;
1.178 brouard 14109: int cross = CROSS;
14110: if (cross){
14111: printf("Cross-");
1.191 brouard 14112: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 14113: }
1.174 brouard 14114: #endif
14115:
1.191 brouard 14116: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 14117: #if defined(__clang__)
1.191 brouard 14118: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 14119: #endif
14120: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 14121: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 14122: #endif
14123: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 14124: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 14125: #endif
14126: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 14127: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 14128: #endif
14129: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 14130: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 14131: #endif
14132: #if defined(_MSC_VER)
1.191 brouard 14133: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 14134: #endif
14135: #if defined(__PGI)
1.191 brouard 14136: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 14137: #endif
14138: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 14139: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 14140: #endif
1.191 brouard 14141: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 14142:
1.167 brouard 14143: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
14144: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
14145: // Windows (x64 and x86)
1.191 brouard 14146: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 14147: #elif __unix__ // all unices, not all compilers
14148: // Unix
1.191 brouard 14149: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 14150: #elif __linux__
14151: // linux
1.191 brouard 14152: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 14153: #elif __APPLE__
1.174 brouard 14154: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 14155: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 14156: #endif
14157:
14158: /* __MINGW32__ */
14159: /* __CYGWIN__ */
14160: /* __MINGW64__ */
14161: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
14162: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
14163: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
14164: /* _WIN64 // Defined for applications for Win64. */
14165: /* _M_X64 // Defined for compilations that target x64 processors. */
14166: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 14167:
1.167 brouard 14168: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 14169: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 14170: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 14171: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 14172: #else
1.191 brouard 14173: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 14174: #endif
14175:
1.169 brouard 14176: #if defined(__GNUC__)
14177: # if defined(__GNUC_PATCHLEVEL__)
14178: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
14179: + __GNUC_MINOR__ * 100 \
14180: + __GNUC_PATCHLEVEL__)
14181: # else
14182: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
14183: + __GNUC_MINOR__ * 100)
14184: # endif
1.174 brouard 14185: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 14186: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 14187:
14188: if (uname(&sysInfo) != -1) {
14189: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 14190: 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 14191: }
14192: else
14193: perror("uname() error");
1.179 brouard 14194: //#ifndef __INTEL_COMPILER
14195: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 14196: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 14197: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 14198: #endif
1.169 brouard 14199: #endif
1.172 brouard 14200:
1.286 brouard 14201: // void main ()
1.172 brouard 14202: // {
1.169 brouard 14203: #if defined(_MSC_VER)
1.174 brouard 14204: if (IsWow64()){
1.191 brouard 14205: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
14206: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 14207: }
14208: else{
1.191 brouard 14209: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
14210: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 14211: }
1.172 brouard 14212: // printf("\nPress Enter to continue...");
14213: // getchar();
14214: // }
14215:
1.169 brouard 14216: #endif
14217:
1.167 brouard 14218:
1.219 brouard 14219: }
1.136 brouard 14220:
1.219 brouard 14221: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 14222: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.332 brouard 14223: /* Computes the prevalence limit for each combination of the dummy covariates */
1.235 brouard 14224: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 14225: /* double ftolpl = 1.e-10; */
1.180 brouard 14226: double age, agebase, agelim;
1.203 brouard 14227: double tot;
1.180 brouard 14228:
1.202 brouard 14229: strcpy(filerespl,"PL_");
14230: strcat(filerespl,fileresu);
14231: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 14232: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
14233: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 14234: }
1.288 brouard 14235: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
14236: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 14237: pstamp(ficrespl);
1.288 brouard 14238: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 14239: fprintf(ficrespl,"#Age ");
14240: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
14241: fprintf(ficrespl,"\n");
1.180 brouard 14242:
1.219 brouard 14243: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 14244:
1.219 brouard 14245: agebase=ageminpar;
14246: agelim=agemaxpar;
1.180 brouard 14247:
1.227 brouard 14248: /* i1=pow(2,ncoveff); */
1.234 brouard 14249: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 14250: if (cptcovn < 1){i1=1;}
1.180 brouard 14251:
1.337 brouard 14252: /* for(k=1; k<=i1;k++){ /\* For each combination k of dummy covariates in the model *\/ */
1.238 brouard 14253: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 14254: k=TKresult[nres];
1.338 brouard 14255: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 14256: /* if(i1 != 1 && TKresult[nres]!= k) /\* We found the combination k corresponding to the resultline value of dummies *\/ */
14257: /* continue; */
1.235 brouard 14258:
1.238 brouard 14259: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
14260: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
14261: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
14262: /* k=k+1; */
14263: /* to clean */
1.332 brouard 14264: /*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*/
1.238 brouard 14265: fprintf(ficrespl,"#******");
14266: printf("#******");
14267: fprintf(ficlog,"#******");
1.337 brouard 14268: 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 14269: /* fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Here problem for varying dummy*\/ */
1.337 brouard 14270: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14271: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14272: fprintf(ficrespl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
14273: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
14274: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
14275: }
14276: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
14277: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
14278: /* fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
14279: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
14280: /* } */
1.238 brouard 14281: fprintf(ficrespl,"******\n");
14282: printf("******\n");
14283: fprintf(ficlog,"******\n");
14284: if(invalidvarcomb[k]){
14285: printf("\nCombination (%d) ignored because no case \n",k);
14286: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
14287: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
14288: continue;
14289: }
1.219 brouard 14290:
1.238 brouard 14291: fprintf(ficrespl,"#Age ");
1.337 brouard 14292: /* for(j=1;j<=cptcoveff;j++) { */
14293: /* fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14294: /* } */
14295: for(j=1;j<=cptcovs;j++) { /* New the quanti variable is added */
14296: fprintf(ficrespl,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 14297: }
14298: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
14299: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 14300:
1.238 brouard 14301: for (age=agebase; age<=agelim; age++){
14302: /* for (age=agebase; age<=agebase; age++){ */
1.337 brouard 14303: /**< Computes the prevalence limit in each live state at age x and for covariate combination (k and) nres */
14304: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres); /* Nicely done */
1.238 brouard 14305: fprintf(ficrespl,"%.0f ",age );
1.337 brouard 14306: /* for(j=1;j<=cptcoveff;j++) */
14307: /* fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14308: for(j=1;j<=cptcovs;j++)
14309: fprintf(ficrespl,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 14310: tot=0.;
14311: for(i=1; i<=nlstate;i++){
14312: tot += prlim[i][i];
14313: fprintf(ficrespl," %.5f", prlim[i][i]);
14314: }
14315: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
14316: } /* Age */
14317: /* was end of cptcod */
1.337 brouard 14318: } /* nres */
14319: /* } /\* for each combination *\/ */
1.219 brouard 14320: return 0;
1.180 brouard 14321: }
14322:
1.218 brouard 14323: 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 14324: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 14325:
14326: /* Computes the back prevalence limit for any combination of covariate values
14327: * at any age between ageminpar and agemaxpar
14328: */
1.235 brouard 14329: int i, j, k, i1, nres=0 ;
1.217 brouard 14330: /* double ftolpl = 1.e-10; */
14331: double age, agebase, agelim;
14332: double tot;
1.218 brouard 14333: /* double ***mobaverage; */
14334: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 14335:
14336: strcpy(fileresplb,"PLB_");
14337: strcat(fileresplb,fileresu);
14338: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 14339: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
14340: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 14341: }
1.288 brouard 14342: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
14343: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 14344: pstamp(ficresplb);
1.288 brouard 14345: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 14346: fprintf(ficresplb,"#Age ");
14347: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
14348: fprintf(ficresplb,"\n");
14349:
1.218 brouard 14350:
14351: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
14352:
14353: agebase=ageminpar;
14354: agelim=agemaxpar;
14355:
14356:
1.227 brouard 14357: i1=pow(2,cptcoveff);
1.218 brouard 14358: if (cptcovn < 1){i1=1;}
1.227 brouard 14359:
1.238 brouard 14360: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.338 brouard 14361: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
14362: k=TKresult[nres];
14363: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
14364: /* if(i1 != 1 && TKresult[nres]!= k) */
14365: /* continue; */
14366: /* /\*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*\/ */
1.238 brouard 14367: fprintf(ficresplb,"#******");
14368: printf("#******");
14369: fprintf(ficlog,"#******");
1.338 brouard 14370: 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) */
14371: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
14372: fprintf(ficresplb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
14373: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 14374: }
1.338 brouard 14375: /* for(j=1;j<=cptcoveff ;j++) {/\* all covariates *\/ */
14376: /* fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14377: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14378: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14379: /* } */
14380: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
14381: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
14382: /* fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
14383: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
14384: /* } */
1.238 brouard 14385: fprintf(ficresplb,"******\n");
14386: printf("******\n");
14387: fprintf(ficlog,"******\n");
14388: if(invalidvarcomb[k]){
14389: printf("\nCombination (%d) ignored because no cases \n",k);
14390: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
14391: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
14392: continue;
14393: }
1.218 brouard 14394:
1.238 brouard 14395: fprintf(ficresplb,"#Age ");
1.338 brouard 14396: for(j=1;j<=cptcovs;j++) {
14397: fprintf(ficresplb,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 14398: }
14399: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
14400: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 14401:
14402:
1.238 brouard 14403: for (age=agebase; age<=agelim; age++){
14404: /* for (age=agebase; age<=agebase; age++){ */
14405: if(mobilavproj > 0){
14406: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
14407: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 14408: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 14409: }else if (mobilavproj == 0){
14410: 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);
14411: 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);
14412: exit(1);
14413: }else{
14414: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 14415: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 14416: /* printf("TOTOT\n"); */
14417: /* exit(1); */
1.238 brouard 14418: }
14419: fprintf(ficresplb,"%.0f ",age );
1.338 brouard 14420: for(j=1;j<=cptcovs;j++)
14421: fprintf(ficresplb,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 14422: tot=0.;
14423: for(i=1; i<=nlstate;i++){
14424: tot += bprlim[i][i];
14425: fprintf(ficresplb," %.5f", bprlim[i][i]);
14426: }
14427: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
14428: } /* Age */
14429: /* was end of cptcod */
1.255 brouard 14430: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.338 brouard 14431: /* } /\* end of any combination *\/ */
1.238 brouard 14432: } /* end of nres */
1.218 brouard 14433: /* hBijx(p, bage, fage); */
14434: /* fclose(ficrespijb); */
14435:
14436: return 0;
1.217 brouard 14437: }
1.218 brouard 14438:
1.180 brouard 14439: int hPijx(double *p, int bage, int fage){
14440: /*------------- h Pij x at various ages ------------*/
1.336 brouard 14441: /* to be optimized with precov */
1.180 brouard 14442: int stepsize;
14443: int agelim;
14444: int hstepm;
14445: int nhstepm;
1.359 brouard 14446: int h, i, i1, j, k, nres=0;
1.180 brouard 14447:
14448: double agedeb;
14449: double ***p3mat;
14450:
1.337 brouard 14451: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
14452: if((ficrespij=fopen(filerespij,"w"))==NULL) {
14453: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
14454: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
14455: }
14456: printf("Computing pij: result on file '%s' \n", filerespij);
14457: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
14458:
14459: stepsize=(int) (stepm+YEARM-1)/YEARM;
14460: /*if (stepm<=24) stepsize=2;*/
14461:
14462: agelim=AGESUP;
14463: hstepm=stepsize*YEARM; /* Every year of age */
14464: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
14465:
14466: /* hstepm=1; aff par mois*/
14467: pstamp(ficrespij);
14468: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
14469: i1= pow(2,cptcoveff);
14470: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
14471: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
14472: /* k=k+1; */
14473: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
14474: k=TKresult[nres];
1.338 brouard 14475: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 14476: /* for(k=1; k<=i1;k++){ */
14477: /* if(i1 != 1 && TKresult[nres]!= k) */
14478: /* continue; */
14479: fprintf(ficrespij,"\n#****** ");
14480: for(j=1;j<=cptcovs;j++){
14481: fprintf(ficrespij," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
14482: /* fprintf(ficrespij,"@wV%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14483: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
14484: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
14485: /* fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
14486: }
14487: fprintf(ficrespij,"******\n");
14488:
14489: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
14490: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
14491: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
14492:
14493: /* nhstepm=nhstepm*YEARM; aff par mois*/
14494:
14495: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
14496: oldm=oldms;savm=savms;
14497: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
14498: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
14499: for(i=1; i<=nlstate;i++)
14500: for(j=1; j<=nlstate+ndeath;j++)
14501: fprintf(ficrespij," %1d-%1d",i,j);
14502: fprintf(ficrespij,"\n");
14503: for (h=0; h<=nhstepm; h++){
14504: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
14505: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.183 brouard 14506: for(i=1; i<=nlstate;i++)
14507: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 14508: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.183 brouard 14509: fprintf(ficrespij,"\n");
14510: }
1.337 brouard 14511: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
14512: fprintf(ficrespij,"\n");
1.180 brouard 14513: }
1.337 brouard 14514: }
14515: /*}*/
14516: return 0;
1.180 brouard 14517: }
1.218 brouard 14518:
14519: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 14520: /*------------- h Bij x at various ages ------------*/
1.336 brouard 14521: /* To be optimized with precov */
1.217 brouard 14522: int stepsize;
1.218 brouard 14523: /* int agelim; */
14524: int ageminl;
1.217 brouard 14525: int hstepm;
14526: int nhstepm;
1.238 brouard 14527: int h, i, i1, j, k, nres;
1.218 brouard 14528:
1.217 brouard 14529: double agedeb;
14530: double ***p3mat;
1.218 brouard 14531:
14532: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
14533: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
14534: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
14535: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
14536: }
14537: printf("Computing pij back: result on file '%s' \n", filerespijb);
14538: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
14539:
14540: stepsize=(int) (stepm+YEARM-1)/YEARM;
14541: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 14542:
1.218 brouard 14543: /* agelim=AGESUP; */
1.289 brouard 14544: ageminl=AGEINF; /* was 30 */
1.218 brouard 14545: hstepm=stepsize*YEARM; /* Every year of age */
14546: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
14547:
14548: /* hstepm=1; aff par mois*/
14549: pstamp(ficrespijb);
1.255 brouard 14550: 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 14551: i1= pow(2,cptcoveff);
1.218 brouard 14552: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
14553: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
14554: /* k=k+1; */
1.238 brouard 14555: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 14556: k=TKresult[nres];
1.338 brouard 14557: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 14558: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
14559: /* if(i1 != 1 && TKresult[nres]!= k) */
14560: /* continue; */
14561: fprintf(ficrespijb,"\n#****** ");
14562: for(j=1;j<=cptcovs;j++){
1.338 brouard 14563: fprintf(ficrespijb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.337 brouard 14564: /* for(j=1;j<=cptcoveff;j++) */
14565: /* fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14566: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
14567: /* fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
14568: }
14569: fprintf(ficrespijb,"******\n");
14570: if(invalidvarcomb[k]){ /* Is it necessary here? */
14571: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
14572: continue;
14573: }
14574:
14575: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
14576: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
14577: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
14578: 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 */
14579: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 or 28*/
14580:
14581: /* nhstepm=nhstepm*YEARM; aff par mois*/
14582:
14583: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
14584: /* and memory limitations if stepm is small */
14585:
14586: /* oldm=oldms;savm=savms; */
14587: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
14588: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);/* Bug valgrind */
14589: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
14590: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
14591: for(i=1; i<=nlstate;i++)
14592: for(j=1; j<=nlstate+ndeath;j++)
14593: fprintf(ficrespijb," %1d-%1d",i,j);
14594: fprintf(ficrespijb,"\n");
14595: for (h=0; h<=nhstepm; h++){
14596: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
14597: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
14598: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
1.217 brouard 14599: for(i=1; i<=nlstate;i++)
14600: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 14601: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);/* Bug valgrind */
1.217 brouard 14602: fprintf(ficrespijb,"\n");
1.337 brouard 14603: }
14604: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
14605: fprintf(ficrespijb,"\n");
14606: } /* end age deb */
14607: /* } /\* end combination *\/ */
1.238 brouard 14608: } /* end nres */
1.218 brouard 14609: return 0;
14610: } /* hBijx */
1.217 brouard 14611:
1.180 brouard 14612:
1.136 brouard 14613: /***********************************************/
14614: /**************** Main Program *****************/
14615: /***********************************************/
14616:
14617: int main(int argc, char *argv[])
14618: {
14619: #ifdef GSL
14620: const gsl_multimin_fminimizer_type *T;
14621: size_t iteri = 0, it;
14622: int rval = GSL_CONTINUE;
14623: int status = GSL_SUCCESS;
14624: double ssval;
14625: #endif
14626: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 14627: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
14628: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 14629: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 14630: int jj, ll, li, lj, lk;
1.136 brouard 14631: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 14632: int num_filled;
1.136 brouard 14633: int itimes;
14634: int NDIM=2;
14635: int vpopbased=0;
1.235 brouard 14636: int nres=0;
1.258 brouard 14637: int endishere=0;
1.277 brouard 14638: int noffset=0;
1.274 brouard 14639: int ncurrv=0; /* Temporary variable */
14640:
1.164 brouard 14641: char ca[32], cb[32];
1.136 brouard 14642: /* FILE *fichtm; *//* Html File */
14643: /* FILE *ficgp;*/ /*Gnuplot File */
14644: struct stat info;
1.191 brouard 14645: double agedeb=0.;
1.194 brouard 14646:
14647: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 14648: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 14649:
1.361 brouard 14650: double stdpercent; /* for computing the std error of percent e.i: e.i/e.. */
1.165 brouard 14651: double fret;
1.191 brouard 14652: double dum=0.; /* Dummy variable */
1.359 brouard 14653: /* double*** p3mat;*/
1.218 brouard 14654: /* double ***mobaverage; */
1.319 brouard 14655: double wald;
1.164 brouard 14656:
1.351 brouard 14657: char line[MAXLINE], linetmp[MAXLINE];
1.197 brouard 14658: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
14659:
1.234 brouard 14660: char modeltemp[MAXLINE];
1.332 brouard 14661: char resultline[MAXLINE], resultlineori[MAXLINE];
1.230 brouard 14662:
1.136 brouard 14663: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 14664: char *tok, *val; /* pathtot */
1.334 brouard 14665: /* int firstobs=1, lastobs=10; /\* nobs = lastobs-firstobs declared globally ;*\/ */
1.359 brouard 14666: int c, h; /* c2; */
1.191 brouard 14667: int jl=0;
14668: int i1, j1, jk, stepsize=0;
1.194 brouard 14669: int count=0;
14670:
1.164 brouard 14671: int *tab;
1.136 brouard 14672: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.296 brouard 14673: /* double anprojd, mprojd, jprojd; /\* For eventual projections *\/ */
14674: /* double anprojf, mprojf, jprojf; */
14675: /* double jintmean,mintmean,aintmean; */
14676: int prvforecast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
14677: int prvbackcast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
14678: double yrfproj= 10.0; /* Number of years of forward projections */
14679: double yrbproj= 10.0; /* Number of years of backward projections */
14680: int prevbcast=0; /* defined as global for mlikeli and mle, replacing backcast */
1.136 brouard 14681: int mobilav=0,popforecast=0;
1.191 brouard 14682: int hstepm=0, nhstepm=0;
1.136 brouard 14683: int agemortsup;
14684: float sumlpop=0.;
14685: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
14686: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
14687:
1.191 brouard 14688: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 14689: double ftolpl=FTOL;
14690: double **prlim;
1.217 brouard 14691: double **bprlim;
1.317 brouard 14692: double ***param; /* Matrix of parameters, param[i][j][k] param=ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel)
14693: state of origin, state of destination including death, for each covariate: constante, age, and V1 V2 etc. */
1.251 brouard 14694: double ***paramstart; /* Matrix of starting parameter values */
14695: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 14696: double **matcov; /* Matrix of covariance */
1.203 brouard 14697: double **hess; /* Hessian matrix */
1.136 brouard 14698: double ***delti3; /* Scale */
14699: double *delti; /* Scale */
14700: double ***eij, ***vareij;
1.359 brouard 14701: //double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 14702:
1.136 brouard 14703: double *epj, vepp;
1.164 brouard 14704:
1.273 brouard 14705: double dateprev1, dateprev2;
1.296 brouard 14706: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0, dateprojd=0, dateprojf=0;
14707: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0, datebackd=0, datebackf=0;
14708:
1.217 brouard 14709:
1.136 brouard 14710: double **ximort;
1.145 brouard 14711: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 14712: int *dcwave;
14713:
1.164 brouard 14714: char z[1]="c";
1.136 brouard 14715:
14716: /*char *strt;*/
14717: char strtend[80];
1.126 brouard 14718:
1.164 brouard 14719:
1.126 brouard 14720: /* setlocale (LC_ALL, ""); */
14721: /* bindtextdomain (PACKAGE, LOCALEDIR); */
14722: /* textdomain (PACKAGE); */
14723: /* setlocale (LC_CTYPE, ""); */
14724: /* setlocale (LC_MESSAGES, ""); */
14725:
14726: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 14727: rstart_time = time(NULL);
14728: /* (void) gettimeofday(&start_time,&tzp);*/
14729: start_time = *localtime(&rstart_time);
1.126 brouard 14730: curr_time=start_time;
1.157 brouard 14731: /*tml = *localtime(&start_time.tm_sec);*/
14732: /* strcpy(strstart,asctime(&tml)); */
14733: strcpy(strstart,asctime(&start_time));
1.126 brouard 14734:
14735: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 14736: /* tp.tm_sec = tp.tm_sec +86400; */
14737: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 14738: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
14739: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
14740: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 14741: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 14742: /* strt=asctime(&tmg); */
14743: /* printf("Time(after) =%s",strstart); */
14744: /* (void) time (&time_value);
14745: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
14746: * tm = *localtime(&time_value);
14747: * strstart=asctime(&tm);
14748: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
14749: */
14750:
14751: nberr=0; /* Number of errors and warnings */
14752: nbwarn=0;
1.184 brouard 14753: #ifdef WIN32
14754: _getcwd(pathcd, size);
14755: #else
1.126 brouard 14756: getcwd(pathcd, size);
1.184 brouard 14757: #endif
1.191 brouard 14758: syscompilerinfo(0);
1.359 brouard 14759: printf("\nIMaCh prax version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 14760: if(argc <=1){
14761: printf("\nEnter the parameter file name: ");
1.205 brouard 14762: if(!fgets(pathr,FILENAMELENGTH,stdin)){
14763: printf("ERROR Empty parameter file name\n");
14764: goto end;
14765: }
1.126 brouard 14766: i=strlen(pathr);
14767: if(pathr[i-1]=='\n')
14768: pathr[i-1]='\0';
1.156 brouard 14769: i=strlen(pathr);
1.205 brouard 14770: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 14771: pathr[i-1]='\0';
1.205 brouard 14772: }
14773: i=strlen(pathr);
14774: if( i==0 ){
14775: printf("ERROR Empty parameter file name\n");
14776: goto end;
14777: }
14778: for (tok = pathr; tok != NULL; ){
1.126 brouard 14779: printf("Pathr |%s|\n",pathr);
14780: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
14781: printf("val= |%s| pathr=%s\n",val,pathr);
14782: strcpy (pathtot, val);
14783: if(pathr[0] == '\0') break; /* Dirty */
14784: }
14785: }
1.281 brouard 14786: else if (argc<=2){
14787: strcpy(pathtot,argv[1]);
14788: }
1.126 brouard 14789: else{
14790: strcpy(pathtot,argv[1]);
1.281 brouard 14791: strcpy(z,argv[2]);
14792: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 14793: }
14794: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
14795: /*cygwin_split_path(pathtot,path,optionfile);
14796: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
14797: /* cutv(path,optionfile,pathtot,'\\');*/
14798:
14799: /* Split argv[0], imach program to get pathimach */
14800: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
14801: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
14802: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
14803: /* strcpy(pathimach,argv[0]); */
14804: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
14805: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
14806: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 14807: #ifdef WIN32
14808: _chdir(path); /* Can be a relative path */
14809: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
14810: #else
1.126 brouard 14811: chdir(path); /* Can be a relative path */
1.184 brouard 14812: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
14813: #endif
14814: printf("Current directory %s!\n",pathcd);
1.126 brouard 14815: strcpy(command,"mkdir ");
14816: strcat(command,optionfilefiname);
14817: if((outcmd=system(command)) != 0){
1.169 brouard 14818: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 14819: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
14820: /* fclose(ficlog); */
14821: /* exit(1); */
14822: }
14823: /* if((imk=mkdir(optionfilefiname))<0){ */
14824: /* perror("mkdir"); */
14825: /* } */
14826:
14827: /*-------- arguments in the command line --------*/
14828:
1.186 brouard 14829: /* Main Log file */
1.126 brouard 14830: strcat(filelog, optionfilefiname);
14831: strcat(filelog,".log"); /* */
14832: if((ficlog=fopen(filelog,"w"))==NULL) {
14833: printf("Problem with logfile %s\n",filelog);
14834: goto end;
14835: }
14836: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 14837: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 14838: fprintf(ficlog,"\nEnter the parameter file name: \n");
14839: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
14840: path=%s \n\
14841: optionfile=%s\n\
14842: optionfilext=%s\n\
1.156 brouard 14843: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 14844:
1.197 brouard 14845: syscompilerinfo(1);
1.167 brouard 14846:
1.126 brouard 14847: printf("Local time (at start):%s",strstart);
14848: fprintf(ficlog,"Local time (at start): %s",strstart);
14849: fflush(ficlog);
14850: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 14851: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 14852:
14853: /* */
14854: strcpy(fileres,"r");
14855: strcat(fileres, optionfilefiname);
1.201 brouard 14856: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 14857: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 14858: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 14859:
1.186 brouard 14860: /* Main ---------arguments file --------*/
1.126 brouard 14861:
14862: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 14863: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
14864: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 14865: fflush(ficlog);
1.149 brouard 14866: /* goto end; */
14867: exit(70);
1.126 brouard 14868: }
14869:
14870: strcpy(filereso,"o");
1.201 brouard 14871: strcat(filereso,fileresu);
1.126 brouard 14872: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
14873: printf("Problem with Output resultfile: %s\n", filereso);
14874: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
14875: fflush(ficlog);
14876: goto end;
14877: }
1.278 brouard 14878: /*-------- Rewriting parameter file ----------*/
14879: strcpy(rfileres,"r"); /* "Rparameterfile */
14880: strcat(rfileres,optionfilefiname); /* Parameter file first name */
14881: strcat(rfileres,"."); /* */
14882: strcat(rfileres,optionfilext); /* Other files have txt extension */
14883: if((ficres =fopen(rfileres,"w"))==NULL) {
14884: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
14885: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
14886: fflush(ficlog);
14887: goto end;
14888: }
14889: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 14890:
1.278 brouard 14891:
1.126 brouard 14892: /* Reads comments: lines beginning with '#' */
14893: numlinepar=0;
1.277 brouard 14894: /* Is it a BOM UTF-8 Windows file? */
14895: /* First parameter line */
1.197 brouard 14896: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 14897: noffset=0;
14898: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
14899: {
14900: noffset=noffset+3;
14901: printf("# File is an UTF8 Bom.\n"); // 0xBF
14902: }
1.302 brouard 14903: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
14904: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
1.277 brouard 14905: {
14906: noffset=noffset+2;
14907: printf("# File is an UTF16BE BOM file\n");
14908: }
14909: else if( line[0] == 0 && line[1] == 0)
14910: {
14911: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
14912: noffset=noffset+4;
14913: printf("# File is an UTF16BE BOM file\n");
14914: }
14915: } else{
14916: ;/*printf(" Not a BOM file\n");*/
14917: }
14918:
1.197 brouard 14919: /* If line starts with a # it is a comment */
1.277 brouard 14920: if (line[noffset] == '#') {
1.197 brouard 14921: numlinepar++;
14922: fputs(line,stdout);
14923: fputs(line,ficparo);
1.278 brouard 14924: fputs(line,ficres);
1.197 brouard 14925: fputs(line,ficlog);
14926: continue;
14927: }else
14928: break;
14929: }
14930: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
14931: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
14932: if (num_filled != 5) {
14933: printf("Should be 5 parameters\n");
1.283 brouard 14934: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 14935: }
1.126 brouard 14936: numlinepar++;
1.197 brouard 14937: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 14938: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
14939: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
14940: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 14941: }
14942: /* Second parameter line */
14943: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 14944: /* while(fscanf(ficpar,"%[^\n]", line)) { */
14945: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 14946: if (line[0] == '#') {
14947: numlinepar++;
1.283 brouard 14948: printf("%s",line);
14949: fprintf(ficres,"%s",line);
14950: fprintf(ficparo,"%s",line);
14951: fprintf(ficlog,"%s",line);
1.197 brouard 14952: continue;
14953: }else
14954: break;
14955: }
1.223 brouard 14956: 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", \
14957: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
14958: if (num_filled != 11) {
14959: 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 14960: printf("but line=%s\n",line);
1.283 brouard 14961: 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");
14962: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 14963: }
1.286 brouard 14964: if( lastpass > maxwav){
14965: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
14966: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
14967: fflush(ficlog);
14968: goto end;
14969: }
14970: 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 14971: 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 14972: 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 14973: 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 14974: }
1.203 brouard 14975: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 14976: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 14977: /* Third parameter line */
14978: while(fgets(line, MAXLINE, ficpar)) {
14979: /* If line starts with a # it is a comment */
14980: if (line[0] == '#') {
14981: numlinepar++;
1.283 brouard 14982: printf("%s",line);
14983: fprintf(ficres,"%s",line);
14984: fprintf(ficparo,"%s",line);
14985: fprintf(ficlog,"%s",line);
1.197 brouard 14986: continue;
14987: }else
14988: break;
14989: }
1.351 brouard 14990: if((num_filled=sscanf(line,"model=%[^.\n]", model)) !=EOF){ /* Every character after model but dot and return */
14991: if (num_filled != 1){
14992: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
14993: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
14994: model[0]='\0';
14995: goto end;
14996: }else{
14997: trimbtab(linetmp,line); /* Trims multiple blanks in line */
14998: strcpy(line, linetmp);
14999: }
15000: }
15001: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){ /* Every character after 1+age but dot and return */
1.279 brouard 15002: if (num_filled != 1){
1.302 brouard 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);
1.197 brouard 15005: model[0]='\0';
15006: goto end;
15007: }
15008: else{
15009: if (model[0]=='+'){
15010: for(i=1; i<=strlen(model);i++)
15011: modeltemp[i-1]=model[i];
1.201 brouard 15012: strcpy(model,modeltemp);
1.197 brouard 15013: }
15014: }
1.338 brouard 15015: /* printf(" model=1+age%s modeltemp= %s, model=1+age+%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 15016: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 15017: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
15018: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
15019: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 15020: }
15021: /* 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); */
15022: /* numlinepar=numlinepar+3; /\* In general *\/ */
15023: /* 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 15024: /* 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); */
15025: /* 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 15026: fflush(ficlog);
1.190 brouard 15027: /* if(model[0]=='#'|| model[0]== '\0'){ */
15028: if(model[0]=='#'){
1.279 brouard 15029: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
15030: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
15031: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 15032: if(mle != -1){
1.279 brouard 15033: 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 15034: exit(1);
15035: }
15036: }
1.126 brouard 15037: while((c=getc(ficpar))=='#' && c!= EOF){
15038: ungetc(c,ficpar);
15039: fgets(line, MAXLINE, ficpar);
15040: numlinepar++;
1.195 brouard 15041: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
15042: z[0]=line[1];
1.342 brouard 15043: }else if(line[1]=='d'){ /* For debugging individual values of covariates in ficresilk */
1.343 brouard 15044: debugILK=1;printf("DebugILK\n");
1.195 brouard 15045: }
15046: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 15047: fputs(line, stdout);
15048: //puts(line);
1.126 brouard 15049: fputs(line,ficparo);
15050: fputs(line,ficlog);
15051: }
15052: ungetc(c,ficpar);
15053:
15054:
1.290 brouard 15055: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
15056: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
15057: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
1.341 brouard 15058: /* if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /\**< Time varying covariate (dummy and quantitative)*\/ */
15059: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs); /**< Might be better */
1.136 brouard 15060: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
15061: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
15062: v1+v2*age+v2*v3 makes cptcovn = 3
15063: */
15064: if (strlen(model)>1)
1.187 brouard 15065: 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 15066: else
1.187 brouard 15067: ncovmodel=2; /* Constant and age */
1.133 brouard 15068: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
15069: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 15070: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
15071: 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);
15072: 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);
15073: fflush(stdout);
15074: fclose (ficlog);
15075: goto end;
15076: }
1.126 brouard 15077: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
15078: delti=delti3[1][1];
15079: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
15080: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 15081: /* We could also provide initial parameters values giving by simple logistic regression
15082: * only one way, that is without matrix product. We will have nlstate maximizations */
15083: /* for(i=1;i<nlstate;i++){ */
15084: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
15085: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
15086: /* } */
1.126 brouard 15087: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 15088: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
15089: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 15090: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
15091: fclose (ficparo);
15092: fclose (ficlog);
15093: goto end;
15094: exit(0);
1.220 brouard 15095: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 15096: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 15097: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
15098: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 15099: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
15100: matcov=matrix(1,npar,1,npar);
1.203 brouard 15101: hess=matrix(1,npar,1,npar);
1.220 brouard 15102: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 15103: /* Read guessed parameters */
1.126 brouard 15104: /* Reads comments: lines beginning with '#' */
15105: while((c=getc(ficpar))=='#' && c!= EOF){
15106: ungetc(c,ficpar);
15107: fgets(line, MAXLINE, ficpar);
15108: numlinepar++;
1.141 brouard 15109: fputs(line,stdout);
1.126 brouard 15110: fputs(line,ficparo);
15111: fputs(line,ficlog);
15112: }
15113: ungetc(c,ficpar);
15114:
15115: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 15116: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 15117: for(i=1; i <=nlstate; i++){
1.234 brouard 15118: j=0;
1.126 brouard 15119: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 15120: if(jj==i) continue;
15121: j++;
1.292 brouard 15122: while((c=getc(ficpar))=='#' && c!= EOF){
15123: ungetc(c,ficpar);
15124: fgets(line, MAXLINE, ficpar);
15125: numlinepar++;
15126: fputs(line,stdout);
15127: fputs(line,ficparo);
15128: fputs(line,ficlog);
15129: }
15130: ungetc(c,ficpar);
1.234 brouard 15131: fscanf(ficpar,"%1d%1d",&i1,&j1);
15132: if ((i1 != i) || (j1 != jj)){
15133: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 15134: It might be a problem of design; if ncovcol and the model are correct\n \
15135: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 15136: exit(1);
15137: }
15138: fprintf(ficparo,"%1d%1d",i1,j1);
15139: if(mle==1)
15140: printf("%1d%1d",i,jj);
15141: fprintf(ficlog,"%1d%1d",i,jj);
15142: for(k=1; k<=ncovmodel;k++){
15143: fscanf(ficpar," %lf",¶m[i][j][k]);
15144: if(mle==1){
15145: printf(" %lf",param[i][j][k]);
15146: fprintf(ficlog," %lf",param[i][j][k]);
15147: }
15148: else
15149: fprintf(ficlog," %lf",param[i][j][k]);
15150: fprintf(ficparo," %lf",param[i][j][k]);
15151: }
15152: fscanf(ficpar,"\n");
15153: numlinepar++;
15154: if(mle==1)
15155: printf("\n");
15156: fprintf(ficlog,"\n");
15157: fprintf(ficparo,"\n");
1.126 brouard 15158: }
15159: }
15160: fflush(ficlog);
1.234 brouard 15161:
1.251 brouard 15162: /* Reads parameters values */
1.126 brouard 15163: p=param[1][1];
1.251 brouard 15164: pstart=paramstart[1][1];
1.126 brouard 15165:
15166: /* Reads comments: lines beginning with '#' */
15167: while((c=getc(ficpar))=='#' && c!= EOF){
15168: ungetc(c,ficpar);
15169: fgets(line, MAXLINE, ficpar);
15170: numlinepar++;
1.141 brouard 15171: fputs(line,stdout);
1.126 brouard 15172: fputs(line,ficparo);
15173: fputs(line,ficlog);
15174: }
15175: ungetc(c,ficpar);
15176:
15177: for(i=1; i <=nlstate; i++){
15178: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 15179: fscanf(ficpar,"%1d%1d",&i1,&j1);
15180: if ( (i1-i) * (j1-j) != 0){
15181: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
15182: exit(1);
15183: }
15184: printf("%1d%1d",i,j);
15185: fprintf(ficparo,"%1d%1d",i1,j1);
15186: fprintf(ficlog,"%1d%1d",i1,j1);
15187: for(k=1; k<=ncovmodel;k++){
15188: fscanf(ficpar,"%le",&delti3[i][j][k]);
15189: printf(" %le",delti3[i][j][k]);
15190: fprintf(ficparo," %le",delti3[i][j][k]);
15191: fprintf(ficlog," %le",delti3[i][j][k]);
15192: }
15193: fscanf(ficpar,"\n");
15194: numlinepar++;
15195: printf("\n");
15196: fprintf(ficparo,"\n");
15197: fprintf(ficlog,"\n");
1.126 brouard 15198: }
15199: }
15200: fflush(ficlog);
1.234 brouard 15201:
1.145 brouard 15202: /* Reads covariance matrix */
1.126 brouard 15203: delti=delti3[1][1];
1.220 brouard 15204:
15205:
1.126 brouard 15206: /* 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 15207:
1.126 brouard 15208: /* Reads comments: lines beginning with '#' */
15209: while((c=getc(ficpar))=='#' && c!= EOF){
15210: ungetc(c,ficpar);
15211: fgets(line, MAXLINE, ficpar);
15212: numlinepar++;
1.141 brouard 15213: fputs(line,stdout);
1.126 brouard 15214: fputs(line,ficparo);
15215: fputs(line,ficlog);
15216: }
15217: ungetc(c,ficpar);
1.220 brouard 15218:
1.126 brouard 15219: matcov=matrix(1,npar,1,npar);
1.203 brouard 15220: hess=matrix(1,npar,1,npar);
1.131 brouard 15221: for(i=1; i <=npar; i++)
15222: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 15223:
1.194 brouard 15224: /* Scans npar lines */
1.126 brouard 15225: for(i=1; i <=npar; i++){
1.226 brouard 15226: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 15227: if(count != 3){
1.226 brouard 15228: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 15229: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
15230: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 15231: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 15232: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
15233: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 15234: exit(1);
1.220 brouard 15235: }else{
1.226 brouard 15236: if(mle==1)
15237: printf("%1d%1d%d",i1,j1,jk);
15238: }
15239: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
15240: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 15241: for(j=1; j <=i; j++){
1.226 brouard 15242: fscanf(ficpar," %le",&matcov[i][j]);
15243: if(mle==1){
15244: printf(" %.5le",matcov[i][j]);
15245: }
15246: fprintf(ficlog," %.5le",matcov[i][j]);
15247: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 15248: }
15249: fscanf(ficpar,"\n");
15250: numlinepar++;
15251: if(mle==1)
1.220 brouard 15252: printf("\n");
1.126 brouard 15253: fprintf(ficlog,"\n");
15254: fprintf(ficparo,"\n");
15255: }
1.194 brouard 15256: /* End of read covariance matrix npar lines */
1.126 brouard 15257: for(i=1; i <=npar; i++)
15258: for(j=i+1;j<=npar;j++)
1.226 brouard 15259: matcov[i][j]=matcov[j][i];
1.126 brouard 15260:
15261: if(mle==1)
15262: printf("\n");
15263: fprintf(ficlog,"\n");
15264:
15265: fflush(ficlog);
15266:
15267: } /* End of mle != -3 */
1.218 brouard 15268:
1.186 brouard 15269: /* Main data
15270: */
1.290 brouard 15271: nobs=lastobs-firstobs+1; /* was = lastobs;*/
15272: /* num=lvector(1,n); */
15273: /* moisnais=vector(1,n); */
15274: /* annais=vector(1,n); */
15275: /* moisdc=vector(1,n); */
15276: /* andc=vector(1,n); */
15277: /* weight=vector(1,n); */
15278: /* agedc=vector(1,n); */
15279: /* cod=ivector(1,n); */
15280: /* for(i=1;i<=n;i++){ */
15281: num=lvector(firstobs,lastobs);
15282: moisnais=vector(firstobs,lastobs);
15283: annais=vector(firstobs,lastobs);
15284: moisdc=vector(firstobs,lastobs);
15285: andc=vector(firstobs,lastobs);
15286: weight=vector(firstobs,lastobs);
15287: agedc=vector(firstobs,lastobs);
15288: cod=ivector(firstobs,lastobs);
15289: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 15290: num[i]=0;
15291: moisnais[i]=0;
15292: annais[i]=0;
15293: moisdc[i]=0;
15294: andc[i]=0;
15295: agedc[i]=0;
15296: cod[i]=0;
15297: weight[i]=1.0; /* Equal weights, 1 by default */
15298: }
1.290 brouard 15299: mint=matrix(1,maxwav,firstobs,lastobs);
15300: anint=matrix(1,maxwav,firstobs,lastobs);
1.325 brouard 15301: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
1.336 brouard 15302: /* printf("BUG ncovmodel=%d NCOVMAX=%d 2**ncovmodel=%f BUG\n",ncovmodel,NCOVMAX,pow(2,ncovmodel)); */
1.126 brouard 15303: tab=ivector(1,NCOVMAX);
1.144 brouard 15304: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 15305: 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 15306:
1.136 brouard 15307: /* Reads data from file datafile */
15308: if (readdata(datafile, firstobs, lastobs, &imx)==1)
15309: goto end;
15310:
15311: /* Calculation of the number of parameters from char model */
1.234 brouard 15312: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 15313: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
15314: k=3 V4 Tvar[k=3]= 4 (from V4)
15315: k=2 V1 Tvar[k=2]= 1 (from V1)
15316: k=1 Tvar[1]=2 (from V2)
1.234 brouard 15317: */
15318:
15319: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
15320: TvarsDind=ivector(1,NCOVMAX); /* */
1.330 brouard 15321: TnsdVar=ivector(1,NCOVMAX); /* */
1.335 brouard 15322: /* for(i=1; i<=NCOVMAX;i++) TnsdVar[i]=3; */
1.234 brouard 15323: TvarsD=ivector(1,NCOVMAX); /* */
15324: TvarsQind=ivector(1,NCOVMAX); /* */
15325: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 15326: TvarF=ivector(1,NCOVMAX); /* */
15327: TvarFind=ivector(1,NCOVMAX); /* */
15328: TvarV=ivector(1,NCOVMAX); /* */
15329: TvarVind=ivector(1,NCOVMAX); /* */
15330: TvarA=ivector(1,NCOVMAX); /* */
15331: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 15332: TvarFD=ivector(1,NCOVMAX); /* */
15333: TvarFDind=ivector(1,NCOVMAX); /* */
15334: TvarFQ=ivector(1,NCOVMAX); /* */
15335: TvarFQind=ivector(1,NCOVMAX); /* */
15336: TvarVD=ivector(1,NCOVMAX); /* */
15337: TvarVDind=ivector(1,NCOVMAX); /* */
15338: TvarVQ=ivector(1,NCOVMAX); /* */
15339: TvarVQind=ivector(1,NCOVMAX); /* */
1.339 brouard 15340: TvarVV=ivector(1,NCOVMAX); /* */
15341: TvarVVind=ivector(1,NCOVMAX); /* */
1.349 brouard 15342: TvarVVA=ivector(1,NCOVMAX); /* */
15343: TvarVVAind=ivector(1,NCOVMAX); /* */
15344: TvarAVVA=ivector(1,NCOVMAX); /* */
15345: TvarAVVAind=ivector(1,NCOVMAX); /* */
1.231 brouard 15346:
1.230 brouard 15347: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 15348: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 15349: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
15350: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
15351: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.349 brouard 15352: DummyV=ivector(-1,NCOVMAX); /* 1 to 3 */
15353: FixedV=ivector(-1,NCOVMAX); /* 1 to 3 */
15354:
1.137 brouard 15355: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
15356: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
15357: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
15358: */
15359: /* For model-covariate k tells which data-covariate to use but
15360: because this model-covariate is a construction we invent a new column
15361: ncovcol + k1
15362: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
15363: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 15364: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
15365: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 15366: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
15367: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 15368: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 15369: */
1.145 brouard 15370: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
15371: 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 15372: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
15373: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.351 brouard 15374: Tvardk=imatrix(0,NCOVMAX,1,2);
1.145 brouard 15375: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 15376: 4 covariates (3 plus signs)
15377: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
1.328 brouard 15378: */
15379: for(i=1;i<NCOVMAX;i++)
15380: Tage[i]=0;
1.230 brouard 15381: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 15382: * individual dummy, fixed or varying:
15383: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
15384: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 15385: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
15386: * V1 df, V2 qf, V3 & V4 dv, V5 qv
15387: * Tmodelind[1]@9={9,0,3,2,}*/
15388: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
15389: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 15390: * individual quantitative, fixed or varying:
15391: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
15392: * 3, 1, 0, 0, 0, 0, 0, 0},
15393: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.349 brouard 15394:
15395: /* Probably useless zeroes */
15396: for(i=1;i<NCOVMAX;i++){
15397: DummyV[i]=0;
15398: FixedV[i]=0;
15399: }
15400:
15401: for(i=1; i <=ncovcol;i++){
15402: DummyV[i]=0;
15403: FixedV[i]=0;
15404: }
15405: for(i=ncovcol+1; i <=ncovcol+nqv;i++){
15406: DummyV[i]=1;
15407: FixedV[i]=0;
15408: }
15409: for(i=ncovcol+nqv+1; i <=ncovcol+nqv+ntv;i++){
15410: DummyV[i]=0;
15411: FixedV[i]=1;
15412: }
15413: for(i=ncovcol+nqv+ntv+1; i <=ncovcol+nqv+ntv+nqtv;i++){
15414: DummyV[i]=1;
15415: FixedV[i]=1;
15416: }
15417: for(i=1; i <=ncovcol+nqv+ntv+nqtv;i++){
15418: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",i,i,DummyV[i],i,FixedV[i]);
15419: 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]);
15420: }
15421:
15422:
15423:
1.186 brouard 15424: /* Main decodemodel */
15425:
1.187 brouard 15426:
1.223 brouard 15427: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 15428: goto end;
15429:
1.137 brouard 15430: if((double)(lastobs-imx)/(double)imx > 1.10){
15431: nbwarn++;
15432: 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);
15433: 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);
15434: }
1.136 brouard 15435: /* if(mle==1){*/
1.137 brouard 15436: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
15437: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 15438: }
15439:
15440: /*-calculation of age at interview from date of interview and age at death -*/
15441: agev=matrix(1,maxwav,1,imx);
15442:
15443: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
15444: goto end;
15445:
1.126 brouard 15446:
1.136 brouard 15447: agegomp=(int)agemin;
1.290 brouard 15448: free_vector(moisnais,firstobs,lastobs);
15449: free_vector(annais,firstobs,lastobs);
1.126 brouard 15450: /* free_matrix(mint,1,maxwav,1,n);
15451: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 15452: /* free_vector(moisdc,1,n); */
15453: /* free_vector(andc,1,n); */
1.145 brouard 15454: /* */
15455:
1.126 brouard 15456: wav=ivector(1,imx);
1.214 brouard 15457: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
15458: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
15459: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
15460: 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.*/
15461: bh=imatrix(1,lastpass-firstpass+2,1,imx);
15462: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 15463:
15464: /* Concatenates waves */
1.214 brouard 15465: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
15466: Death is a valid wave (if date is known).
15467: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
15468: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
15469: and mw[mi+1][i]. dh depends on stepm.
15470: */
15471:
1.126 brouard 15472: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 15473: /* Concatenates waves */
1.145 brouard 15474:
1.290 brouard 15475: free_vector(moisdc,firstobs,lastobs);
15476: free_vector(andc,firstobs,lastobs);
1.215 brouard 15477:
1.126 brouard 15478: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
15479: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
15480: ncodemax[1]=1;
1.145 brouard 15481: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 15482: cptcoveff=0;
1.220 brouard 15483: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
1.335 brouard 15484: 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 15485: }
15486:
15487: ncovcombmax=pow(2,cptcoveff);
1.338 brouard 15488: invalidvarcomb=ivector(0, ncovcombmax);
15489: for(i=0;i<ncovcombmax;i++)
1.227 brouard 15490: invalidvarcomb[i]=0;
15491:
1.211 brouard 15492: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 15493: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 15494: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 15495:
1.200 brouard 15496: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 15497: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 15498: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 15499: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
15500: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
15501: * (currently 0 or 1) in the data.
15502: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
15503: * corresponding modality (h,j).
15504: */
15505:
1.145 brouard 15506: h=0;
15507: /*if (cptcovn > 0) */
1.126 brouard 15508: m=pow(2,cptcoveff);
15509:
1.144 brouard 15510: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 15511: * For k=4 covariates, h goes from 1 to m=2**k
15512: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
15513: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.329 brouard 15514: * h\k 1 2 3 4 * h-1\k-1 4 3 2 1
15515: *______________________________ *______________________
15516: * 1 i=1 1 i=1 1 i=1 1 i=1 1 * 0 0 0 0 0
15517: * 2 2 1 1 1 * 1 0 0 0 1
15518: * 3 i=2 1 2 1 1 * 2 0 0 1 0
15519: * 4 2 2 1 1 * 3 0 0 1 1
15520: * 5 i=3 1 i=2 1 2 1 * 4 0 1 0 0
15521: * 6 2 1 2 1 * 5 0 1 0 1
15522: * 7 i=4 1 2 2 1 * 6 0 1 1 0
15523: * 8 2 2 2 1 * 7 0 1 1 1
15524: * 9 i=5 1 i=3 1 i=2 1 2 * 8 1 0 0 0
15525: * 10 2 1 1 2 * 9 1 0 0 1
15526: * 11 i=6 1 2 1 2 * 10 1 0 1 0
15527: * 12 2 2 1 2 * 11 1 0 1 1
15528: * 13 i=7 1 i=4 1 2 2 * 12 1 1 0 0
15529: * 14 2 1 2 2 * 13 1 1 0 1
15530: * 15 i=8 1 2 2 2 * 14 1 1 1 0
15531: * 16 2 2 2 2 * 15 1 1 1 1
15532: */
1.212 brouard 15533: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 15534: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
15535: * and the value of each covariate?
15536: * V1=1, V2=1, V3=2, V4=1 ?
15537: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
15538: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
15539: * In order to get the real value in the data, we use nbcode
15540: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
15541: * We are keeping this crazy system in order to be able (in the future?)
15542: * to have more than 2 values (0 or 1) for a covariate.
15543: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
15544: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
15545: * bbbbbbbb
15546: * 76543210
15547: * h-1 00000101 (6-1=5)
1.219 brouard 15548: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 15549: * &
15550: * 1 00000001 (1)
1.219 brouard 15551: * 00000000 = 1 & ((h-1) >> (k-1))
15552: * +1= 00000001 =1
1.211 brouard 15553: *
15554: * h=14, k=3 => h'=h-1=13, k'=k-1=2
15555: * h' 1101 =2^3+2^2+0x2^1+2^0
15556: * >>k' 11
15557: * & 00000001
15558: * = 00000001
15559: * +1 = 00000010=2 = codtabm(14,3)
15560: * Reverse h=6 and m=16?
15561: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
15562: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
15563: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
15564: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
15565: * V3=decodtabm(14,3,2**4)=2
15566: * h'=13 1101 =2^3+2^2+0x2^1+2^0
15567: *(h-1) >> (j-1) 0011 =13 >> 2
15568: * &1 000000001
15569: * = 000000001
15570: * +1= 000000010 =2
15571: * 2211
15572: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
15573: * V3=2
1.220 brouard 15574: * codtabm and decodtabm are identical
1.211 brouard 15575: */
15576:
1.145 brouard 15577:
15578: free_ivector(Ndum,-1,NCOVMAX);
15579:
15580:
1.126 brouard 15581:
1.186 brouard 15582: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 15583: strcpy(optionfilegnuplot,optionfilefiname);
15584: if(mle==-3)
1.201 brouard 15585: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 15586: strcat(optionfilegnuplot,".gp");
15587:
15588: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
15589: printf("Problem with file %s",optionfilegnuplot);
15590: }
15591: else{
1.204 brouard 15592: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 15593: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 15594: //fprintf(ficgp,"set missing 'NaNq'\n");
15595: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 15596: }
15597: /* fclose(ficgp);*/
1.186 brouard 15598:
15599:
15600: /* Initialisation of --------- index.htm --------*/
1.126 brouard 15601:
15602: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
15603: if(mle==-3)
1.201 brouard 15604: strcat(optionfilehtm,"-MORT_");
1.126 brouard 15605: strcat(optionfilehtm,".htm");
15606: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 15607: printf("Problem with %s \n",optionfilehtm);
15608: exit(0);
1.126 brouard 15609: }
15610:
15611: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
15612: strcat(optionfilehtmcov,"-cov.htm");
15613: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
15614: printf("Problem with %s \n",optionfilehtmcov), exit(0);
15615: }
15616: else{
15617: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
15618: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 15619: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 15620: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
15621: }
15622:
1.335 brouard 15623: fprintf(fichtm,"<html><head>\n<meta charset=\"utf-8\"/><meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n\
15624: <title>IMaCh %s</title></head>\n\
15625: <body><font size=\"7\"><a href=http:/euroreves.ined.fr/imach>IMaCh for Interpolated Markov Chain</a> </font><br>\n\
15626: <font size=\"3\">Sponsored by Copyright (C) 2002-2015 <a href=http://www.ined.fr>INED</a>\
15627: -EUROREVES-Institut de longévité-2013-2022-Japan Society for the Promotion of Sciences 日本学術振興会 \
15628: (<a href=https://www.jsps.go.jp/english/e-grants/>Grant-in-Aid for Scientific Research 25293121</a>) - \
15629: <a href=https://software.intel.com/en-us>Intel Software 2015-2018</a></font><br> \n", optionfilehtm);
15630:
15631: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 15632: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 15633: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.337 brouard 15634: 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 15635: \n\
15636: <hr size=\"2\" color=\"#EC5E5E\">\
15637: <ul><li><h4>Parameter files</h4>\n\
15638: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
15639: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
15640: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
15641: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
15642: - Date and time at start: %s</ul>\n",\
1.335 brouard 15643: version,fullversion,optionfilehtm,optionfilehtm,title,datafile,datafile,firstpass,lastpass,stepm, weightopt, model, \
1.126 brouard 15644: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
15645: fileres,fileres,\
15646: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
15647: fflush(fichtm);
15648:
15649: strcpy(pathr,path);
15650: strcat(pathr,optionfilefiname);
1.184 brouard 15651: #ifdef WIN32
15652: _chdir(optionfilefiname); /* Move to directory named optionfile */
15653: #else
1.126 brouard 15654: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 15655: #endif
15656:
1.126 brouard 15657:
1.220 brouard 15658: /* Calculates basic frequencies. Computes observed prevalence at single age
15659: and for any valid combination of covariates
1.126 brouard 15660: and prints on file fileres'p'. */
1.359 brouard 15661: freqsummary(fileres, p, pstart, (double)agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 15662: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 15663:
15664: fprintf(fichtm,"\n");
1.286 brouard 15665: 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 15666: ftol, stepm);
15667: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
15668: ncurrv=1;
15669: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
15670: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
15671: ncurrv=i;
15672: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 15673: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 15674: ncurrv=i;
15675: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 15676: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 15677: ncurrv=i;
15678: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
15679: 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", \
15680: nlstate, ndeath, maxwav, mle, weightopt);
15681:
15682: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
15683: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
15684:
15685:
1.317 brouard 15686: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Number of (used) observations=%d <br>\n\
1.126 brouard 15687: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
15688: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 15689: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 15690: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 15691: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
15692: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
15693: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
15694: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 15695:
1.126 brouard 15696: /* For Powell, parameters are in a vector p[] starting at p[1]
15697: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
15698: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
15699:
15700: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 15701: /* For mortality only */
1.126 brouard 15702: if (mle==-3){
1.136 brouard 15703: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 15704: for(i=1;i<=NDIM;i++)
15705: for(j=1;j<=NDIM;j++)
15706: ximort[i][j]=0.;
1.186 brouard 15707: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 15708: cens=ivector(firstobs,lastobs);
15709: ageexmed=vector(firstobs,lastobs);
15710: agecens=vector(firstobs,lastobs);
15711: dcwave=ivector(firstobs,lastobs);
1.223 brouard 15712:
1.126 brouard 15713: for (i=1; i<=imx; i++){
15714: dcwave[i]=-1;
15715: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 15716: if (s[m][i]>nlstate) {
15717: dcwave[i]=m;
15718: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
15719: break;
15720: }
1.126 brouard 15721: }
1.226 brouard 15722:
1.126 brouard 15723: for (i=1; i<=imx; i++) {
15724: if (wav[i]>0){
1.226 brouard 15725: ageexmed[i]=agev[mw[1][i]][i];
15726: j=wav[i];
15727: agecens[i]=1.;
15728:
15729: if (ageexmed[i]> 1 && wav[i] > 0){
15730: agecens[i]=agev[mw[j][i]][i];
15731: cens[i]= 1;
15732: }else if (ageexmed[i]< 1)
15733: cens[i]= -1;
15734: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
15735: cens[i]=0 ;
1.126 brouard 15736: }
15737: else cens[i]=-1;
15738: }
15739:
15740: for (i=1;i<=NDIM;i++) {
15741: for (j=1;j<=NDIM;j++)
1.226 brouard 15742: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 15743: }
15744:
1.302 brouard 15745: p[1]=0.0268; p[NDIM]=0.083;
15746: /* printf("%lf %lf", p[1], p[2]); */
1.126 brouard 15747:
15748:
1.136 brouard 15749: #ifdef GSL
15750: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 15751: #else
1.359 brouard 15752: printf("Powell-mort\n"); fprintf(ficlog,"Powell-mort\n");
1.136 brouard 15753: #endif
1.201 brouard 15754: strcpy(filerespow,"POW-MORT_");
15755: strcat(filerespow,fileresu);
1.126 brouard 15756: if((ficrespow=fopen(filerespow,"w"))==NULL) {
15757: printf("Problem with resultfile: %s\n", filerespow);
15758: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
15759: }
1.136 brouard 15760: #ifdef GSL
15761: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 15762: #else
1.126 brouard 15763: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 15764: #endif
1.126 brouard 15765: /* for (i=1;i<=nlstate;i++)
15766: for(j=1;j<=nlstate+ndeath;j++)
15767: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
15768: */
15769: fprintf(ficrespow,"\n");
1.136 brouard 15770: #ifdef GSL
15771: /* gsl starts here */
15772: T = gsl_multimin_fminimizer_nmsimplex;
15773: gsl_multimin_fminimizer *sfm = NULL;
15774: gsl_vector *ss, *x;
15775: gsl_multimin_function minex_func;
15776:
15777: /* Initial vertex size vector */
15778: ss = gsl_vector_alloc (NDIM);
15779:
15780: if (ss == NULL){
15781: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
15782: }
15783: /* Set all step sizes to 1 */
15784: gsl_vector_set_all (ss, 0.001);
15785:
15786: /* Starting point */
1.126 brouard 15787:
1.136 brouard 15788: x = gsl_vector_alloc (NDIM);
15789:
15790: if (x == NULL){
15791: gsl_vector_free(ss);
15792: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
15793: }
15794:
15795: /* Initialize method and iterate */
15796: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 15797: /* gsl_vector_set(x, 0, 0.0268); */
15798: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 15799: gsl_vector_set(x, 0, p[1]);
15800: gsl_vector_set(x, 1, p[2]);
15801:
15802: minex_func.f = &gompertz_f;
15803: minex_func.n = NDIM;
15804: minex_func.params = (void *)&p; /* ??? */
15805:
15806: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
15807: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
15808:
15809: printf("Iterations beginning .....\n\n");
15810: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
15811:
15812: iteri=0;
15813: while (rval == GSL_CONTINUE){
15814: iteri++;
15815: status = gsl_multimin_fminimizer_iterate(sfm);
15816:
15817: if (status) printf("error: %s\n", gsl_strerror (status));
15818: fflush(0);
15819:
15820: if (status)
15821: break;
15822:
15823: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
15824: ssval = gsl_multimin_fminimizer_size (sfm);
15825:
15826: if (rval == GSL_SUCCESS)
15827: printf ("converged to a local maximum at\n");
15828:
15829: printf("%5d ", iteri);
15830: for (it = 0; it < NDIM; it++){
15831: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
15832: }
15833: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
15834: }
15835:
15836: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
15837:
15838: gsl_vector_free(x); /* initial values */
15839: gsl_vector_free(ss); /* inital step size */
15840: for (it=0; it<NDIM; it++){
15841: p[it+1]=gsl_vector_get(sfm->x,it);
15842: fprintf(ficrespow," %.12lf", p[it]);
15843: }
15844: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
15845: #endif
15846: #ifdef POWELL
1.361 brouard 15847: #ifdef LINMINORIGINAL
15848: #else /* LINMINORIGINAL */
15849:
15850: flatdir=ivector(1,npar);
15851: for (j=1;j<=npar;j++) flatdir[j]=0;
15852: #endif /*LINMINORIGINAL */
1.362 ! brouard 15853: /* powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz); */
! 15854: /* double h0=0.25; */
! 15855: macheps=pow(16.0,-13.0);
! 15856: printf("Praxis Gegenfurtner mle=%d\n",mle);
! 15857: fprintf(ficlog, "Praxis Gegenfurtner mle=%d\n", mle);fflush(ficlog);
! 15858: /* ffmin = praxis(ftol,macheps, h0, npar, prin, p, gompertz); */
! 15859: /* For the Gompertz we use only two parameters */
! 15860: int _npar=2;
! 15861: ffmin = praxis(ftol,macheps, h0, _npar, 4, p, gompertz);
! 15862: printf("End Praxis\n");
1.126 brouard 15863: fclose(ficrespow);
1.361 brouard 15864: #ifdef LINMINORIGINAL
15865: #else
15866: free_ivector(flatdir,1,npar);
15867: #endif /* LINMINORIGINAL*/
1.126 brouard 15868:
1.203 brouard 15869: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 15870:
15871: for(i=1; i <=NDIM; i++)
15872: for(j=i+1;j<=NDIM;j++)
1.359 brouard 15873: matcov[i][j]=matcov[j][i];
1.126 brouard 15874:
15875: printf("\nCovariance matrix\n ");
1.203 brouard 15876: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 15877: for(i=1; i <=NDIM; i++) {
15878: for(j=1;j<=NDIM;j++){
1.220 brouard 15879: printf("%f ",matcov[i][j]);
15880: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 15881: }
1.203 brouard 15882: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 15883: }
15884:
15885: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 15886: for (i=1;i<=NDIM;i++) {
1.126 brouard 15887: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 15888: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
15889: }
1.302 brouard 15890: lsurv=vector(agegomp,AGESUP);
15891: lpop=vector(agegomp,AGESUP);
15892: tpop=vector(agegomp,AGESUP);
1.126 brouard 15893: lsurv[agegomp]=100000;
15894:
15895: for (k=agegomp;k<=AGESUP;k++) {
15896: agemortsup=k;
15897: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
15898: }
15899:
15900: for (k=agegomp;k<agemortsup;k++)
15901: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
15902:
15903: for (k=agegomp;k<agemortsup;k++){
15904: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
15905: sumlpop=sumlpop+lpop[k];
15906: }
15907:
15908: tpop[agegomp]=sumlpop;
15909: for (k=agegomp;k<(agemortsup-3);k++){
15910: /* tpop[k+1]=2;*/
15911: tpop[k+1]=tpop[k]-lpop[k];
15912: }
15913:
15914:
15915: printf("\nAge lx qx dx Lx Tx e(x)\n");
15916: for (k=agegomp;k<(agemortsup-2);k++)
15917: 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]);
15918:
15919:
15920: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 15921: ageminpar=50;
15922: agemaxpar=100;
1.194 brouard 15923: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
15924: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
15925: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
15926: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
15927: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
15928: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
15929: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 15930: }else{
15931: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
15932: 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 15933: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 15934: }
1.201 brouard 15935: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 15936: stepm, weightopt,\
15937: model,imx,p,matcov,agemortsup);
15938:
1.302 brouard 15939: free_vector(lsurv,agegomp,AGESUP);
15940: free_vector(lpop,agegomp,AGESUP);
15941: free_vector(tpop,agegomp,AGESUP);
1.220 brouard 15942: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 15943: free_ivector(dcwave,firstobs,lastobs);
15944: free_vector(agecens,firstobs,lastobs);
15945: free_vector(ageexmed,firstobs,lastobs);
15946: free_ivector(cens,firstobs,lastobs);
1.220 brouard 15947: #ifdef GSL
1.136 brouard 15948: #endif
1.186 brouard 15949: } /* Endof if mle==-3 mortality only */
1.205 brouard 15950: /* Standard */
15951: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
15952: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
15953: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 15954: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 15955: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
15956: for (k=1; k<=npar;k++)
15957: printf(" %d %8.5f",k,p[k]);
15958: printf("\n");
1.205 brouard 15959: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
15960: /* mlikeli uses func not funcone */
1.247 brouard 15961: /* for(i=1;i<nlstate;i++){ */
15962: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
15963: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
15964: /* } */
1.205 brouard 15965: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
15966: }
15967: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
15968: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
15969: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
15970: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
15971: }
15972: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 15973: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
15974: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
1.335 brouard 15975: /* exit(0); */
1.126 brouard 15976: for (k=1; k<=npar;k++)
15977: printf(" %d %8.5f",k,p[k]);
15978: printf("\n");
15979:
15980: /*--------- results files --------------*/
1.283 brouard 15981: /* 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 15982:
15983:
15984: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 15985: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); /* Printing model equation */
1.126 brouard 15986: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 15987:
15988: printf("#model= 1 + age ");
15989: fprintf(ficres,"#model= 1 + age ");
15990: fprintf(ficlog,"#model= 1 + age ");
15991: fprintf(fichtm,"\n<ul><li> model=1+age+%s\n \
15992: </ul>", model);
15993:
15994: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">\n");
15995: fprintf(fichtm, "<tr><th>Model=</th><th>1</th><th>+ age</th>");
15996: if(nagesqr==1){
15997: printf(" + age*age ");
15998: fprintf(ficres," + age*age ");
15999: fprintf(ficlog," + age*age ");
16000: fprintf(fichtm, "<th>+ age*age</th>");
16001: }
1.362 ! brouard 16002: for(j=1;j <=ncovmodel-2-nagesqr;j++){
1.319 brouard 16003: if(Typevar[j]==0) {
16004: printf(" + V%d ",Tvar[j]);
16005: fprintf(ficres," + V%d ",Tvar[j]);
16006: fprintf(ficlog," + V%d ",Tvar[j]);
16007: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
16008: }else if(Typevar[j]==1) {
16009: printf(" + V%d*age ",Tvar[j]);
16010: fprintf(ficres," + V%d*age ",Tvar[j]);
16011: fprintf(ficlog," + V%d*age ",Tvar[j]);
16012: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
16013: }else if(Typevar[j]==2) {
16014: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
16015: fprintf(ficres," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
16016: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
16017: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 16018: }else if(Typevar[j]==3) { /* TO VERIFY */
16019: printf(" + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
16020: fprintf(ficres," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
16021: fprintf(ficlog," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
16022: fprintf(fichtm, "<th>+ V%d*V%d*age</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.319 brouard 16023: }
16024: }
16025: printf("\n");
16026: fprintf(ficres,"\n");
16027: fprintf(ficlog,"\n");
16028: fprintf(fichtm, "</tr>");
16029: fprintf(fichtm, "\n");
16030:
16031:
1.126 brouard 16032: for(i=1,jk=1; i <=nlstate; i++){
16033: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 16034: if (k != i) {
1.319 brouard 16035: fprintf(fichtm, "<tr>");
1.225 brouard 16036: printf("%d%d ",i,k);
16037: fprintf(ficlog,"%d%d ",i,k);
16038: fprintf(ficres,"%1d%1d ",i,k);
1.319 brouard 16039: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 16040: for(j=1; j <=ncovmodel; j++){
16041: printf("%12.7f ",p[jk]);
16042: fprintf(ficlog,"%12.7f ",p[jk]);
16043: fprintf(ficres,"%12.7f ",p[jk]);
1.319 brouard 16044: fprintf(fichtm, "<td>%12.7f</td>",p[jk]);
1.225 brouard 16045: jk++;
16046: }
16047: printf("\n");
16048: fprintf(ficlog,"\n");
16049: fprintf(ficres,"\n");
1.319 brouard 16050: fprintf(fichtm, "</tr>\n");
1.225 brouard 16051: }
1.126 brouard 16052: }
16053: }
1.319 brouard 16054: /* fprintf(fichtm,"</tr>\n"); */
16055: fprintf(fichtm,"</table>\n");
16056: fprintf(fichtm, "\n");
16057:
1.203 brouard 16058: if(mle != 0){
16059: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 16060: ftolhess=ftol; /* Usually correct */
1.203 brouard 16061: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
16062: 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");
16063: 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 16064: 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 16065: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">");
16066: fprintf(fichtm, "\n<tr><th>Model=</th><th>1</th><th>+ age</th>");
16067: if(nagesqr==1){
16068: printf(" + age*age ");
16069: fprintf(ficres," + age*age ");
16070: fprintf(ficlog," + age*age ");
16071: fprintf(fichtm, "<th>+ age*age</th>");
16072: }
1.362 ! brouard 16073: for(j=1;j <=ncovmodel-2-nagesqr;j++){
1.319 brouard 16074: if(Typevar[j]==0) {
16075: printf(" + V%d ",Tvar[j]);
16076: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
16077: }else if(Typevar[j]==1) {
16078: printf(" + V%d*age ",Tvar[j]);
16079: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
16080: }else if(Typevar[j]==2) {
16081: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 16082: }else if(Typevar[j]==3) { /* TO VERIFY */
16083: fprintf(fichtm, "<th>+ V%d*V%d*age</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.319 brouard 16084: }
16085: }
16086: fprintf(fichtm, "</tr>\n");
16087:
1.203 brouard 16088: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 16089: for(k=1; k <=(nlstate+ndeath); k++){
16090: if (k != i) {
1.319 brouard 16091: fprintf(fichtm, "<tr valign=top>");
1.225 brouard 16092: printf("%d%d ",i,k);
16093: fprintf(ficlog,"%d%d ",i,k);
1.319 brouard 16094: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 16095: for(j=1; j <=ncovmodel; j++){
1.319 brouard 16096: wald=p[jk]/sqrt(matcov[jk][jk]);
1.324 brouard 16097: 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]));
16098: 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 16099: if(fabs(wald) > 1.96){
1.321 brouard 16100: fprintf(fichtm, "<td><b>%12.7f</b></br> (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
1.319 brouard 16101: }else{
16102: fprintf(fichtm, "<td>%12.7f (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
16103: }
1.324 brouard 16104: fprintf(fichtm,"W=%8.3f</br>",wald);
1.319 brouard 16105: 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 16106: jk++;
16107: }
16108: printf("\n");
16109: fprintf(ficlog,"\n");
1.319 brouard 16110: fprintf(fichtm, "</tr>\n");
1.225 brouard 16111: }
16112: }
1.193 brouard 16113: }
1.203 brouard 16114: } /* end of hesscov and Wald tests */
1.319 brouard 16115: fprintf(fichtm,"</table>\n");
1.225 brouard 16116:
1.203 brouard 16117: /* */
1.126 brouard 16118: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
16119: printf("# Scales (for hessian or gradient estimation)\n");
16120: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
16121: for(i=1,jk=1; i <=nlstate; i++){
16122: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 16123: if (j!=i) {
16124: fprintf(ficres,"%1d%1d",i,j);
16125: printf("%1d%1d",i,j);
16126: fprintf(ficlog,"%1d%1d",i,j);
16127: for(k=1; k<=ncovmodel;k++){
16128: printf(" %.5e",delti[jk]);
16129: fprintf(ficlog," %.5e",delti[jk]);
16130: fprintf(ficres," %.5e",delti[jk]);
16131: jk++;
16132: }
16133: printf("\n");
16134: fprintf(ficlog,"\n");
16135: fprintf(ficres,"\n");
16136: }
1.126 brouard 16137: }
16138: }
16139:
16140: 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 16141: if(mle >= 1) /* Too big for the screen */
1.126 brouard 16142: 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");
16143: 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");
16144: /* # 121 Var(a12)\n\ */
16145: /* # 122 Cov(b12,a12) Var(b12)\n\ */
16146: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
16147: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
16148: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
16149: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
16150: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
16151: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
16152:
16153:
16154: /* Just to have a covariance matrix which will be more understandable
16155: even is we still don't want to manage dictionary of variables
16156: */
16157: for(itimes=1;itimes<=2;itimes++){
16158: jj=0;
16159: for(i=1; i <=nlstate; i++){
1.225 brouard 16160: for(j=1; j <=nlstate+ndeath; j++){
16161: if(j==i) continue;
16162: for(k=1; k<=ncovmodel;k++){
16163: jj++;
16164: ca[0]= k+'a'-1;ca[1]='\0';
16165: if(itimes==1){
16166: if(mle>=1)
16167: printf("#%1d%1d%d",i,j,k);
16168: fprintf(ficlog,"#%1d%1d%d",i,j,k);
16169: fprintf(ficres,"#%1d%1d%d",i,j,k);
16170: }else{
16171: if(mle>=1)
16172: printf("%1d%1d%d",i,j,k);
16173: fprintf(ficlog,"%1d%1d%d",i,j,k);
16174: fprintf(ficres,"%1d%1d%d",i,j,k);
16175: }
16176: ll=0;
16177: for(li=1;li <=nlstate; li++){
16178: for(lj=1;lj <=nlstate+ndeath; lj++){
16179: if(lj==li) continue;
16180: for(lk=1;lk<=ncovmodel;lk++){
16181: ll++;
16182: if(ll<=jj){
16183: cb[0]= lk +'a'-1;cb[1]='\0';
16184: if(ll<jj){
16185: if(itimes==1){
16186: if(mle>=1)
16187: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
16188: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
16189: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
16190: }else{
16191: if(mle>=1)
16192: printf(" %.5e",matcov[jj][ll]);
16193: fprintf(ficlog," %.5e",matcov[jj][ll]);
16194: fprintf(ficres," %.5e",matcov[jj][ll]);
16195: }
16196: }else{
16197: if(itimes==1){
16198: if(mle>=1)
16199: printf(" Var(%s%1d%1d)",ca,i,j);
16200: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
16201: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
16202: }else{
16203: if(mle>=1)
16204: printf(" %.7e",matcov[jj][ll]);
16205: fprintf(ficlog," %.7e",matcov[jj][ll]);
16206: fprintf(ficres," %.7e",matcov[jj][ll]);
16207: }
16208: }
16209: }
16210: } /* end lk */
16211: } /* end lj */
16212: } /* end li */
16213: if(mle>=1)
16214: printf("\n");
16215: fprintf(ficlog,"\n");
16216: fprintf(ficres,"\n");
16217: numlinepar++;
16218: } /* end k*/
16219: } /*end j */
1.126 brouard 16220: } /* end i */
16221: } /* end itimes */
16222:
16223: fflush(ficlog);
16224: fflush(ficres);
1.225 brouard 16225: while(fgets(line, MAXLINE, ficpar)) {
16226: /* If line starts with a # it is a comment */
16227: if (line[0] == '#') {
16228: numlinepar++;
16229: fputs(line,stdout);
16230: fputs(line,ficparo);
16231: fputs(line,ficlog);
1.299 brouard 16232: fputs(line,ficres);
1.225 brouard 16233: continue;
16234: }else
16235: break;
16236: }
16237:
1.209 brouard 16238: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
16239: /* ungetc(c,ficpar); */
16240: /* fgets(line, MAXLINE, ficpar); */
16241: /* fputs(line,stdout); */
16242: /* fputs(line,ficparo); */
16243: /* } */
16244: /* ungetc(c,ficpar); */
1.126 brouard 16245:
16246: estepm=0;
1.209 brouard 16247: 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 16248:
16249: if (num_filled != 6) {
16250: 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);
16251: 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);
16252: goto end;
16253: }
16254: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
16255: }
16256: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
16257: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
16258:
1.209 brouard 16259: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 16260: if (estepm==0 || estepm < stepm) estepm=stepm;
16261: if (fage <= 2) {
16262: bage = ageminpar;
16263: fage = agemaxpar;
16264: }
16265:
16266: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 16267: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
16268: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 16269:
1.186 brouard 16270: /* Other stuffs, more or less useful */
1.254 brouard 16271: while(fgets(line, MAXLINE, ficpar)) {
16272: /* If line starts with a # it is a comment */
16273: if (line[0] == '#') {
16274: numlinepar++;
16275: fputs(line,stdout);
16276: fputs(line,ficparo);
16277: fputs(line,ficlog);
1.299 brouard 16278: fputs(line,ficres);
1.254 brouard 16279: continue;
16280: }else
16281: break;
16282: }
16283:
16284: 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){
16285:
16286: if (num_filled != 7) {
16287: 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);
16288: 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);
16289: goto end;
16290: }
16291: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
16292: 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);
16293: 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);
16294: 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 16295: }
1.254 brouard 16296:
16297: while(fgets(line, MAXLINE, ficpar)) {
16298: /* If line starts with a # it is a comment */
16299: if (line[0] == '#') {
16300: numlinepar++;
16301: fputs(line,stdout);
16302: fputs(line,ficparo);
16303: fputs(line,ficlog);
1.299 brouard 16304: fputs(line,ficres);
1.254 brouard 16305: continue;
16306: }else
16307: break;
1.126 brouard 16308: }
16309:
16310:
16311: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
16312: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
16313:
1.254 brouard 16314: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
16315: if (num_filled != 1) {
16316: 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);
16317: 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);
16318: goto end;
16319: }
16320: printf("pop_based=%d\n",popbased);
16321: fprintf(ficlog,"pop_based=%d\n",popbased);
16322: fprintf(ficparo,"pop_based=%d\n",popbased);
16323: fprintf(ficres,"pop_based=%d\n",popbased);
16324: }
16325:
1.258 brouard 16326: /* Results */
1.359 brouard 16327: /* Value of covariate in each resultine will be computed (if product) and sorted according to model rank */
1.332 brouard 16328: /* It is precov[] because we need the varying age in order to compute the real cov[] of the model equation */
16329: precov=matrix(1,MAXRESULTLINESPONE,1,NCOVMAX+1);
1.307 brouard 16330: endishere=0;
1.258 brouard 16331: nresult=0;
1.308 brouard 16332: parameterline=0;
1.258 brouard 16333: do{
16334: if(!fgets(line, MAXLINE, ficpar)){
16335: endishere=1;
1.308 brouard 16336: parameterline=15;
1.258 brouard 16337: }else if (line[0] == '#') {
16338: /* If line starts with a # it is a comment */
1.254 brouard 16339: numlinepar++;
16340: fputs(line,stdout);
16341: fputs(line,ficparo);
16342: fputs(line,ficlog);
1.299 brouard 16343: fputs(line,ficres);
1.254 brouard 16344: continue;
1.258 brouard 16345: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
16346: parameterline=11;
1.296 brouard 16347: else if(sscanf(line,"prevbackcast=%[^\n]\n",modeltemp))
1.258 brouard 16348: parameterline=12;
1.307 brouard 16349: else if(sscanf(line,"result:%[^\n]\n",modeltemp)){
1.258 brouard 16350: parameterline=13;
1.307 brouard 16351: }
1.258 brouard 16352: else{
16353: parameterline=14;
1.254 brouard 16354: }
1.308 brouard 16355: switch (parameterline){ /* =0 only if only comments */
1.258 brouard 16356: case 11:
1.296 brouard 16357: 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)){
16358: 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 16359: 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);
16360: 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);
16361: 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);
16362: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 16363: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
16364: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
1.296 brouard 16365: prvforecast = 1;
16366: }
16367: else if((num_filled=sscanf(line,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",&prevfcast,&yrfproj,&mobilavproj)) !=EOF){/* && (num_filled == 3))*/
1.313 brouard 16368: printf("prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
16369: fprintf(ficlog,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
16370: fprintf(ficres,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
1.296 brouard 16371: prvforecast = 2;
16372: }
16373: else {
16374: 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);
16375: 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);
16376: goto end;
1.258 brouard 16377: }
1.254 brouard 16378: break;
1.258 brouard 16379: case 12:
1.296 brouard 16380: 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)){
16381: 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);
16382: 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);
16383: 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);
16384: 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);
16385: /* day and month of back2 are not used but only year anback2.*/
1.273 brouard 16386: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
16387: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.296 brouard 16388: prvbackcast = 1;
16389: }
16390: else if((num_filled=sscanf(line,"prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",&prevbcast,&yrbproj,&mobilavproj)) ==3){/* && (num_filled == 3))*/
1.313 brouard 16391: printf("prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
16392: fprintf(ficlog,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
16393: fprintf(ficres,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
1.296 brouard 16394: prvbackcast = 2;
16395: }
16396: else {
16397: 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);
16398: 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);
16399: goto end;
1.258 brouard 16400: }
1.230 brouard 16401: break;
1.258 brouard 16402: case 13:
1.332 brouard 16403: num_filled=sscanf(line,"result:%[^\n]\n",resultlineori);
1.307 brouard 16404: nresult++; /* Sum of resultlines */
1.342 brouard 16405: /* printf("Result %d: result:%s\n",nresult, resultlineori); */
1.332 brouard 16406: /* removefirstspace(&resultlineori); */
16407:
16408: if(strstr(resultlineori,"v") !=0){
16409: printf("Error. 'v' must be in upper case 'V' result: %s ",resultlineori);
16410: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultlineori);fflush(ficlog);
16411: return 1;
16412: }
16413: trimbb(resultline, resultlineori); /* Suppressing double blank in the resultline */
1.342 brouard 16414: /* printf("Decoderesult resultline=\"%s\" resultlineori=\"%s\"\n", resultline, resultlineori); */
1.318 brouard 16415: if(nresult > MAXRESULTLINESPONE-1){
16416: 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);
16417: 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 16418: goto end;
16419: }
1.332 brouard 16420:
1.310 brouard 16421: if(!decoderesult(resultline, nresult)){ /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
1.314 brouard 16422: fprintf(ficparo,"result: %s\n",resultline);
16423: fprintf(ficres,"result: %s\n",resultline);
16424: fprintf(ficlog,"result: %s\n",resultline);
1.310 brouard 16425: } else
16426: goto end;
1.307 brouard 16427: break;
16428: case 14:
16429: printf("Error: Unknown command '%s'\n",line);
16430: fprintf(ficlog,"Error: Unknown command '%s'\n",line);
1.314 brouard 16431: if(line[0] == ' ' || line[0] == '\n'){
16432: printf("It should not be an empty line '%s'\n",line);
16433: fprintf(ficlog,"It should not be an empty line '%s'\n",line);
16434: }
1.307 brouard 16435: if(ncovmodel >=2 && nresult==0 ){
16436: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
16437: fprintf(ficlog,"ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 16438: }
1.307 brouard 16439: /* goto end; */
16440: break;
1.308 brouard 16441: case 15:
16442: printf("End of resultlines.\n");
16443: fprintf(ficlog,"End of resultlines.\n");
16444: break;
16445: default: /* parameterline =0 */
1.307 brouard 16446: nresult=1;
16447: decoderesult(".",nresult ); /* No covariate */
1.258 brouard 16448: } /* End switch parameterline */
16449: }while(endishere==0); /* End do */
1.126 brouard 16450:
1.230 brouard 16451: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 16452: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 16453:
16454: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 16455: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 16456: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 16457: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
16458: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 16459: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 16460: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
16461: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 16462: }else{
1.270 brouard 16463: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
1.296 brouard 16464: /* It seems that anprojd which is computed from the mean year at interview which is known yet because of freqsummary */
16465: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */ /* Done in freqsummary */
16466: if(prvforecast==1){
16467: dateprojd=(jproj1+12*mproj1+365*anproj1)/365;
16468: jprojd=jproj1;
16469: mprojd=mproj1;
16470: anprojd=anproj1;
16471: dateprojf=(jproj2+12*mproj2+365*anproj2)/365;
16472: jprojf=jproj2;
16473: mprojf=mproj2;
16474: anprojf=anproj2;
16475: } else if(prvforecast == 2){
16476: dateprojd=dateintmean;
16477: date2dmy(dateprojd,&jprojd, &mprojd, &anprojd);
16478: dateprojf=dateintmean+yrfproj;
16479: date2dmy(dateprojf,&jprojf, &mprojf, &anprojf);
16480: }
16481: if(prvbackcast==1){
16482: datebackd=(jback1+12*mback1+365*anback1)/365;
16483: jbackd=jback1;
16484: mbackd=mback1;
16485: anbackd=anback1;
16486: datebackf=(jback2+12*mback2+365*anback2)/365;
16487: jbackf=jback2;
16488: mbackf=mback2;
16489: anbackf=anback2;
16490: } else if(prvbackcast == 2){
16491: datebackd=dateintmean;
16492: date2dmy(datebackd,&jbackd, &mbackd, &anbackd);
16493: datebackf=dateintmean-yrbproj;
16494: date2dmy(datebackf,&jbackf, &mbackf, &anbackf);
16495: }
16496:
1.350 brouard 16497: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage);/* HERE valgrind Tvard*/
1.220 brouard 16498: }
16499: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.296 brouard 16500: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,prevbcast, estepm, \
16501: jprev1,mprev1,anprev1,dateprev1, dateprojd, datebackd,jprev2,mprev2,anprev2,dateprev2,dateprojf, datebackf);
1.220 brouard 16502:
1.225 brouard 16503: /*------------ free_vector -------------*/
16504: /* chdir(path); */
1.220 brouard 16505:
1.215 brouard 16506: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
16507: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
16508: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
16509: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 16510: free_lvector(num,firstobs,lastobs);
16511: free_vector(agedc,firstobs,lastobs);
1.126 brouard 16512: /*free_matrix(covar,0,NCOVMAX,1,n);*/
16513: /*free_matrix(covar,1,NCOVMAX,1,n);*/
16514: fclose(ficparo);
16515: fclose(ficres);
1.220 brouard 16516:
16517:
1.186 brouard 16518: /* Other results (useful)*/
1.220 brouard 16519:
16520:
1.126 brouard 16521: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 16522: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
16523: prlim=matrix(1,nlstate,1,nlstate);
1.332 brouard 16524: /* Computes the prevalence limit for each combination k of the dummy covariates by calling prevalim(k) */
1.209 brouard 16525: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 16526: fclose(ficrespl);
16527:
16528: /*------------- h Pij x at various ages ------------*/
1.180 brouard 16529: /*#include "hpijx.h"*/
1.332 brouard 16530: /** 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?*/
16531: /* calls hpxij with combination k */
1.180 brouard 16532: hPijx(p, bage, fage);
1.145 brouard 16533: fclose(ficrespij);
1.227 brouard 16534:
1.220 brouard 16535: /* ncovcombmax= pow(2,cptcoveff); */
1.332 brouard 16536: /*-------------- Variance of one-step probabilities for a combination ij or for nres ?---*/
1.145 brouard 16537: k=1;
1.126 brouard 16538: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 16539:
1.269 brouard 16540: /* Prevalence for each covariate combination in probs[age][status][cov] */
16541: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
16542: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 16543: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 16544: for(k=1;k<=ncovcombmax;k++)
16545: probs[i][j][k]=0.;
1.269 brouard 16546: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
16547: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 16548: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 16549: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
16550: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 16551: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 16552: for(k=1;k<=ncovcombmax;k++)
16553: mobaverages[i][j][k]=0.;
1.219 brouard 16554: mobaverage=mobaverages;
16555: if (mobilav!=0) {
1.235 brouard 16556: printf("Movingaveraging observed prevalence\n");
1.258 brouard 16557: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 16558: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
16559: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
16560: printf(" Error in movingaverage mobilav=%d\n",mobilav);
16561: }
1.269 brouard 16562: } else if (mobilavproj !=0) {
1.235 brouard 16563: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 16564: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 16565: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
16566: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
16567: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
16568: }
1.269 brouard 16569: }else{
16570: printf("Internal error moving average\n");
16571: fflush(stdout);
16572: exit(1);
1.219 brouard 16573: }
16574: }/* end if moving average */
1.227 brouard 16575:
1.126 brouard 16576: /*---------- Forecasting ------------------*/
1.296 brouard 16577: if(prevfcast==1){
16578: /* /\* if(stepm ==1){*\/ */
16579: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
16580: /*This done previously after freqsummary.*/
16581: /* dateprojd=(jproj1+12*mproj1+365*anproj1)/365; */
16582: /* dateprojf=(jproj2+12*mproj2+365*anproj2)/365; */
16583:
16584: /* } else if (prvforecast==2){ */
16585: /* /\* if(stepm ==1){*\/ */
16586: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
16587: /* } */
16588: /*prevforecast(fileresu, dateintmean, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);*/
16589: prevforecast(fileresu,dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, p, cptcoveff);
1.126 brouard 16590: }
1.269 brouard 16591:
1.296 brouard 16592: /* Prevbcasting */
16593: if(prevbcast==1){
1.219 brouard 16594: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
16595: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
16596: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
16597:
16598: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
16599:
16600: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 16601:
1.219 brouard 16602: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
16603: fclose(ficresplb);
16604:
1.222 brouard 16605: hBijx(p, bage, fage, mobaverage);
16606: fclose(ficrespijb);
1.219 brouard 16607:
1.296 brouard 16608: /* /\* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, *\/ */
16609: /* /\* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); *\/ */
16610: /* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, */
16611: /* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
16612: prevbackforecast(fileresu, mobaverage, dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2,
16613: mobilavproj, bage, fage, firstpass, lastpass, p, cptcoveff);
16614:
16615:
1.269 brouard 16616: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 16617:
16618:
1.269 brouard 16619: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 16620: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
16621: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
16622: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.296 brouard 16623: } /* end Prevbcasting */
1.268 brouard 16624:
1.186 brouard 16625:
16626: /* ------ Other prevalence ratios------------ */
1.126 brouard 16627:
1.215 brouard 16628: free_ivector(wav,1,imx);
16629: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
16630: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
16631: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 16632:
16633:
1.127 brouard 16634: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 16635:
1.201 brouard 16636: strcpy(filerese,"E_");
16637: strcat(filerese,fileresu);
1.126 brouard 16638: if((ficreseij=fopen(filerese,"w"))==NULL) {
16639: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
16640: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
16641: }
1.208 brouard 16642: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
16643: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 16644:
16645: pstamp(ficreseij);
1.219 brouard 16646:
1.351 brouard 16647: /* i1=pow(2,cptcoveff); /\* Number of combination of dummy covariates *\/ */
16648: /* if (cptcovn < 1){i1=1;} */
1.235 brouard 16649:
1.351 brouard 16650: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
16651: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
16652: /* if(i1 != 1 && TKresult[nres]!= k) */
16653: /* continue; */
1.219 brouard 16654: fprintf(ficreseij,"\n#****** ");
1.235 brouard 16655: printf("\n#****** ");
1.351 brouard 16656: for(j=1;j<=cptcovs;j++){
16657: /* for(j=1;j<=cptcoveff;j++) { */
16658: /* fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
16659: fprintf(ficreseij," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
16660: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
16661: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.235 brouard 16662: }
16663: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.337 brouard 16664: printf(" V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]); /* TvarsQ[j] gives the name of the jth quantitative (fixed or time v) */
16665: fprintf(ficreseij,"V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]);
1.219 brouard 16666: }
16667: fprintf(ficreseij,"******\n");
1.235 brouard 16668: printf("******\n");
1.219 brouard 16669:
16670: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
16671: oldm=oldms;savm=savms;
1.330 brouard 16672: /* 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 16673: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 16674:
1.219 brouard 16675: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 16676: }
16677: fclose(ficreseij);
1.208 brouard 16678: printf("done evsij\n");fflush(stdout);
16679: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 16680:
1.218 brouard 16681:
1.227 brouard 16682: /*---------- State-specific expectancies and variances ------------*/
1.336 brouard 16683: /* Should be moved in a function */
1.201 brouard 16684: strcpy(filerest,"T_");
16685: strcat(filerest,fileresu);
1.127 brouard 16686: if((ficrest=fopen(filerest,"w"))==NULL) {
16687: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
16688: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
16689: }
1.208 brouard 16690: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
16691: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 16692: strcpy(fileresstde,"STDE_");
16693: strcat(fileresstde,fileresu);
1.126 brouard 16694: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 16695: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
16696: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 16697: }
1.227 brouard 16698: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
16699: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 16700:
1.201 brouard 16701: strcpy(filerescve,"CVE_");
16702: strcat(filerescve,fileresu);
1.126 brouard 16703: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 16704: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
16705: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 16706: }
1.227 brouard 16707: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
16708: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 16709:
1.201 brouard 16710: strcpy(fileresv,"V_");
16711: strcat(fileresv,fileresu);
1.126 brouard 16712: if((ficresvij=fopen(fileresv,"w"))==NULL) {
16713: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
16714: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
16715: }
1.227 brouard 16716: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
16717: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 16718:
1.235 brouard 16719: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
16720: if (cptcovn < 1){i1=1;}
16721:
1.334 brouard 16722: for(nres=1; nres <= nresult; nres++) /* For each resultline, find the combination and output results according to the values of dummies and then quanti. */
16723: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying. For each nres and each value at position k
16724: * we know Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline
16725: * Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline
16726: * and Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
16727: /* */
16728: 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 16729: continue;
1.359 brouard 16730: printf("\n# model=1+age+%s \n#****** Result for:", model); /* HERE model is empty */
16731: fprintf(ficrest,"\n# model=1+age+%s \n#****** Result for:", model);
16732: fprintf(ficlog,"\n# model=1+age+%s \n#****** Result for:", model);
1.334 brouard 16733: /* It might not be a good idea to mix dummies and quantitative */
16734: /* 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 *\/ */
16735: 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 */
16736: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /\* Output by variables in the resultline *\/ */
16737: /* Tvaraff[j] is the name of the dummy variable in position j in the equation model:
16738: * Tvaraff[1]@9={4, 3, 0, 0, 0, 0, 0, 0, 0}, in model=V5+V4+V3+V4*V3+V5*age
16739: * (V5 is quanti) V4 and V3 are dummies
16740: * TnsdVar[4] is the position 1 and TnsdVar[3]=2 in codtabm(k,l)(V4 V3)=V4 V3
16741: * l=1 l=2
16742: * k=1 1 1 0 0
16743: * k=2 2 1 1 0
16744: * k=3 [1] [2] 0 1
16745: * k=4 2 2 1 1
16746: * If nres=1 result: V3=1 V4=0 then k=3 and outputs
16747: * If nres=2 result: V4=1 V3=0 then k=2 and outputs
16748: * nres=1 =>k=3 j=1 V4= nbcode[4][codtabm(3,1)=1)=0; j=2 V3= nbcode[3][codtabm(3,2)=2]=1
16749: * nres=2 =>k=2 j=1 V4= nbcode[4][codtabm(2,1)=2)=1; j=2 V3= nbcode[3][codtabm(2,2)=1]=0
16750: */
16751: /* Tvresult[nres][j] Name of the variable at position j in this resultline */
16752: /* Tresult[nres][j] Value of this variable at position j could be a float if quantitative */
16753: /* We give up with the combinations!! */
1.342 brouard 16754: /* if(debugILK) */
16755: /* 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 16756:
16757: 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 16758: /* 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] */
16759: 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 */
16760: 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 */
16761: 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 16762: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
16763: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
16764: }else{
16765: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
16766: }
16767: /* fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
16768: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
16769: }else if(Dummy[modelresult[nres][j]]==1){ /* Quanti variable */
16770: /* For each selected (single) quantitative value */
1.337 brouard 16771: printf(" V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
16772: fprintf(ficlog," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
16773: fprintf(ficrest," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
1.334 brouard 16774: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
16775: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
16776: }else{
16777: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
16778: }
16779: }else{
16780: 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 */
16781: 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 */
16782: exit(1);
16783: }
1.335 brouard 16784: } /* End loop for each variable in the resultline */
1.334 brouard 16785: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
16786: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /\* Wrong j is not in the equation model *\/ */
16787: /* fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
16788: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
16789: /* } */
1.208 brouard 16790: fprintf(ficrest,"******\n");
1.227 brouard 16791: fprintf(ficlog,"******\n");
16792: printf("******\n");
1.208 brouard 16793:
16794: fprintf(ficresstdeij,"\n#****** ");
16795: fprintf(ficrescveij,"\n#****** ");
1.337 brouard 16796: /* It could have been: for(j=1;j<=cptcoveff;j++) {printf("V=%d=%lg",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);} */
16797: /* But it won't be sorted and depends on how the resultline is ordered */
1.225 brouard 16798: for(j=1;j<=cptcoveff;j++) {
1.334 brouard 16799: fprintf(ficresstdeij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
16800: /* fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
16801: /* fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
16802: }
16803: 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 16804: fprintf(ficresstdeij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
16805: fprintf(ficrescveij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
1.235 brouard 16806: }
1.208 brouard 16807: fprintf(ficresstdeij,"******\n");
16808: fprintf(ficrescveij,"******\n");
16809:
16810: fprintf(ficresvij,"\n#****** ");
1.238 brouard 16811: /* pstamp(ficresvij); */
1.225 brouard 16812: for(j=1;j<=cptcoveff;j++)
1.335 brouard 16813: fprintf(ficresvij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
16814: /* fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[TnsdVar[Tvaraff[j]]])]); */
1.235 brouard 16815: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.332 brouard 16816: /* fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); /\* To solve *\/ */
1.337 brouard 16817: fprintf(ficresvij," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /* Solved */
1.235 brouard 16818: }
1.208 brouard 16819: fprintf(ficresvij,"******\n");
16820:
16821: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
16822: oldm=oldms;savm=savms;
1.235 brouard 16823: printf(" cvevsij ");
16824: fprintf(ficlog, " cvevsij ");
16825: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 16826: printf(" end cvevsij \n ");
16827: fprintf(ficlog, " end cvevsij \n ");
16828:
16829: /*
16830: */
16831: /* goto endfree; */
16832:
16833: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
16834: pstamp(ficrest);
16835:
1.269 brouard 16836: epj=vector(1,nlstate+1);
1.208 brouard 16837: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 16838: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
16839: cptcod= 0; /* To be deleted */
1.360 brouard 16840: printf("varevsij vpopbased=%d popbased=%d \n",vpopbased,popbased);
16841: fprintf(ficlog, "varevsij vpopbased=%d popbased=%d \n",vpopbased,popbased);
1.361 brouard 16842: /* 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 */
16843: /* Depending of popbased which changes the prevalences, either cross-sectional or period */
1.235 brouard 16844: 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 16845: fprintf(ficrest,"# Total life expectancy with std error and decomposition into time to be expected in each state\n\
16846: # (these are weighted average of eij where weights are ");
1.227 brouard 16847: if(vpopbased==1)
1.360 brouard 16848: 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 16849: else
1.360 brouard 16850: fprintf(ficrest,"the age specific forward period (stable) prevalences in each state) \n");
16851: fprintf(ficrest,"# with proportions of time spent in each state with standard error (on the right of the table.\n ");
1.335 brouard 16852: fprintf(ficrest,"# Age popbased mobilav e.. (std) "); /* Adding covariate values? */
1.227 brouard 16853: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
1.360 brouard 16854: for (i=1;i<=nlstate;i++) fprintf(ficrest," %% e.%d/e.. (std) ",i);
1.227 brouard 16855: fprintf(ficrest,"\n");
16856: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 16857: printf("Computing age specific forward period (stable) prevalences in each health state \n");
16858: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 16859: for(age=bage; age <=fage ;age++){
1.235 brouard 16860: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 16861: if (vpopbased==1) {
16862: if(mobilav ==0){
16863: for(i=1; i<=nlstate;i++)
16864: prlim[i][i]=probs[(int)age][i][k];
16865: }else{ /* mobilav */
16866: for(i=1; i<=nlstate;i++)
16867: prlim[i][i]=mobaverage[(int)age][i][k];
16868: }
16869: }
1.219 brouard 16870:
1.227 brouard 16871: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
16872: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
16873: /* printf(" age %4.0f ",age); */
16874: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
16875: for(i=1, epj[j]=0.;i <=nlstate;i++) {
16876: epj[j] += prlim[i][i]*eij[i][j][(int)age];
16877: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
16878: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
16879: }
1.361 brouard 16880: epj[nlstate+1] +=epj[j]; /* epp=sum_j epj = sum_j sum_i w_i e_ij */
1.227 brouard 16881: }
16882: /* printf(" age %4.0f \n",age); */
1.219 brouard 16883:
1.361 brouard 16884: for(i=1, vepp=0.;i <=nlstate;i++) /* Variance of total life expectancy e.. */
1.227 brouard 16885: for(j=1;j <=nlstate;j++)
1.361 brouard 16886: vepp += vareij[i][j][(int)age]; /* sum_i sum_j cov(e.i, e.j) = var(e..) */
1.227 brouard 16887: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
1.361 brouard 16888: /* vareij[i][j] is the covariance cov(e.i, e.j) and vareij[j][j] is the variance of e.j */
1.227 brouard 16889: for(j=1;j <=nlstate;j++){
16890: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
16891: }
1.360 brouard 16892: /* And proportion of time spent in state j */
16893: /* $$ E[r(X,Y)-E(r(X,Y))]^2=[\frac{1}{\mu_y} -\frac{\mu_x}{{\mu_y}^2}]' Var(X,Y)[\frac{1}{\mu_y} -\frac{\mu_x}{{\mu_y}^2}]$$ */
1.361 brouard 16894: /* \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}) */
16895: /* \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})*/
16896: /*\mu_x = epj[j], \sigma^2_x = vareij[j][j][(int)age] and \mu_y=epj[nlstate+1], \sigma^2_y=vepp \sigmaxy= */
16897: /* vareij[j][j][(int)age]/epj[nlstate+1]^2 + vepp/epj[nlstate+1]^4 */
1.360 brouard 16898: for(j=1;j <=nlstate;j++){
16899: /* 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 16900: /* 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] )); */
16901:
16902: 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) */
16903: stdpercent += vareij[i][j][(int)age];
16904: }
16905: 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]);
16906: /* 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 */
16907: /* 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] )); */
16908: fprintf(ficrest," %7.3f (%7.3f)", epj[j]/epj[nlstate+1], sqrt(stdpercent));
1.360 brouard 16909: }
1.227 brouard 16910: fprintf(ficrest,"\n");
16911: }
1.208 brouard 16912: } /* End vpopbased */
1.269 brouard 16913: free_vector(epj,1,nlstate+1);
1.208 brouard 16914: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
16915: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 16916: printf("done selection\n");fflush(stdout);
16917: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 16918:
1.335 brouard 16919: } /* End k selection or end covariate selection for nres */
1.227 brouard 16920:
16921: printf("done State-specific expectancies\n");fflush(stdout);
16922: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
16923:
1.335 brouard 16924: /* variance-covariance of forward period prevalence */
1.269 brouard 16925: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 16926:
1.227 brouard 16927:
1.290 brouard 16928: free_vector(weight,firstobs,lastobs);
1.351 brouard 16929: free_imatrix(Tvardk,0,NCOVMAX,1,2);
1.227 brouard 16930: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 16931: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
16932: free_matrix(anint,1,maxwav,firstobs,lastobs);
16933: free_matrix(mint,1,maxwav,firstobs,lastobs);
16934: free_ivector(cod,firstobs,lastobs);
1.227 brouard 16935: free_ivector(tab,1,NCOVMAX);
16936: fclose(ficresstdeij);
16937: fclose(ficrescveij);
16938: fclose(ficresvij);
16939: fclose(ficrest);
16940: fclose(ficpar);
16941:
16942:
1.126 brouard 16943: /*---------- End : free ----------------*/
1.219 brouard 16944: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 16945: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
16946: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 16947: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
16948: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 16949: } /* mle==-3 arrives here for freeing */
1.227 brouard 16950: /* endfree:*/
1.359 brouard 16951: if(mle!=-3) free_matrix(precov, 1,MAXRESULTLINESPONE,1,NCOVMAX+1); /* Could be elsewhere ?*/
1.227 brouard 16952: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
16953: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
16954: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.341 brouard 16955: /* if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs); */
16956: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs);
1.290 brouard 16957: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
16958: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
16959: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 16960: free_matrix(matcov,1,npar,1,npar);
16961: free_matrix(hess,1,npar,1,npar);
16962: /*free_vector(delti,1,npar);*/
16963: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
16964: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 16965: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 16966: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
16967:
16968: free_ivector(ncodemax,1,NCOVMAX);
16969: free_ivector(ncodemaxwundef,1,NCOVMAX);
16970: free_ivector(Dummy,-1,NCOVMAX);
16971: free_ivector(Fixed,-1,NCOVMAX);
1.349 brouard 16972: free_ivector(DummyV,-1,NCOVMAX);
16973: free_ivector(FixedV,-1,NCOVMAX);
1.227 brouard 16974: free_ivector(Typevar,-1,NCOVMAX);
16975: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 16976: free_ivector(TvarsQ,1,NCOVMAX);
16977: free_ivector(TvarsQind,1,NCOVMAX);
16978: free_ivector(TvarsD,1,NCOVMAX);
1.330 brouard 16979: free_ivector(TnsdVar,1,NCOVMAX);
1.234 brouard 16980: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 16981: free_ivector(TvarFD,1,NCOVMAX);
16982: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 16983: free_ivector(TvarF,1,NCOVMAX);
16984: free_ivector(TvarFind,1,NCOVMAX);
16985: free_ivector(TvarV,1,NCOVMAX);
16986: free_ivector(TvarVind,1,NCOVMAX);
16987: free_ivector(TvarA,1,NCOVMAX);
16988: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 16989: free_ivector(TvarFQ,1,NCOVMAX);
16990: free_ivector(TvarFQind,1,NCOVMAX);
16991: free_ivector(TvarVD,1,NCOVMAX);
16992: free_ivector(TvarVDind,1,NCOVMAX);
16993: free_ivector(TvarVQ,1,NCOVMAX);
16994: free_ivector(TvarVQind,1,NCOVMAX);
1.349 brouard 16995: free_ivector(TvarAVVA,1,NCOVMAX);
16996: free_ivector(TvarAVVAind,1,NCOVMAX);
16997: free_ivector(TvarVVA,1,NCOVMAX);
16998: free_ivector(TvarVVAind,1,NCOVMAX);
1.339 brouard 16999: free_ivector(TvarVV,1,NCOVMAX);
17000: free_ivector(TvarVVind,1,NCOVMAX);
17001:
1.230 brouard 17002: free_ivector(Tvarsel,1,NCOVMAX);
17003: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 17004: free_ivector(Tposprod,1,NCOVMAX);
17005: free_ivector(Tprod,1,NCOVMAX);
17006: free_ivector(Tvaraff,1,NCOVMAX);
1.338 brouard 17007: free_ivector(invalidvarcomb,0,ncovcombmax);
1.227 brouard 17008: free_ivector(Tage,1,NCOVMAX);
17009: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 17010: free_ivector(TmodelInvind,1,NCOVMAX);
17011: free_ivector(TmodelInvQind,1,NCOVMAX);
1.332 brouard 17012:
1.359 brouard 17013: /* free_matrix(precov, 1,MAXRESULTLINESPONE,1,NCOVMAX+1); /\* Could be elsewhere ?*\/ */
1.332 brouard 17014:
1.227 brouard 17015: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
17016: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 17017: fflush(fichtm);
17018: fflush(ficgp);
17019:
1.227 brouard 17020:
1.126 brouard 17021: if((nberr >0) || (nbwarn>0)){
1.216 brouard 17022: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
17023: 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 17024: }else{
17025: printf("End of Imach\n");
17026: fprintf(ficlog,"End of Imach\n");
17027: }
17028: printf("See log file on %s\n",filelog);
17029: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 17030: /*(void) gettimeofday(&end_time,&tzp);*/
17031: rend_time = time(NULL);
17032: end_time = *localtime(&rend_time);
17033: /* tml = *localtime(&end_time.tm_sec); */
17034: strcpy(strtend,asctime(&end_time));
1.126 brouard 17035: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
17036: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 17037: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 17038:
1.157 brouard 17039: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
17040: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
17041: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 17042: /* printf("Total time was %d uSec.\n", total_usecs);*/
17043: /* if(fileappend(fichtm,optionfilehtm)){ */
17044: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
17045: fclose(fichtm);
17046: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
17047: fclose(fichtmcov);
17048: fclose(ficgp);
17049: fclose(ficlog);
17050: /*------ End -----------*/
1.227 brouard 17051:
1.281 brouard 17052:
17053: /* Executes gnuplot */
1.227 brouard 17054:
17055: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 17056: #ifdef WIN32
1.227 brouard 17057: if (_chdir(pathcd) != 0)
17058: printf("Can't move to directory %s!\n",path);
17059: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 17060: #else
1.227 brouard 17061: if(chdir(pathcd) != 0)
17062: printf("Can't move to directory %s!\n", path);
17063: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 17064: #endif
1.126 brouard 17065: printf("Current directory %s!\n",pathcd);
17066: /*strcat(plotcmd,CHARSEPARATOR);*/
17067: sprintf(plotcmd,"gnuplot");
1.157 brouard 17068: #ifdef _WIN32
1.126 brouard 17069: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
17070: #endif
17071: if(!stat(plotcmd,&info)){
1.158 brouard 17072: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 17073: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 17074: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 17075: }else
17076: strcpy(pplotcmd,plotcmd);
1.157 brouard 17077: #ifdef __unix
1.126 brouard 17078: strcpy(plotcmd,GNUPLOTPROGRAM);
17079: if(!stat(plotcmd,&info)){
1.158 brouard 17080: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 17081: }else
17082: strcpy(pplotcmd,plotcmd);
17083: #endif
17084: }else
17085: strcpy(pplotcmd,plotcmd);
17086:
17087: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 17088: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 brouard 17089: strcpy(pplotcmd,plotcmd);
1.227 brouard 17090:
1.126 brouard 17091: if((outcmd=system(plotcmd)) != 0){
1.292 brouard 17092: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 17093: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 17094: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 brouard 17095: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 17096: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 brouard 17097: strcpy(plotcmd,pplotcmd);
17098: }
1.126 brouard 17099: }
1.158 brouard 17100: printf(" Successful, please wait...");
1.126 brouard 17101: while (z[0] != 'q') {
17102: /* chdir(path); */
1.154 brouard 17103: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 17104: scanf("%s",z);
17105: /* if (z[0] == 'c') system("./imach"); */
17106: if (z[0] == 'e') {
1.158 brouard 17107: #ifdef __APPLE__
1.152 brouard 17108: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 17109: #elif __linux
17110: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 17111: #else
1.152 brouard 17112: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 17113: #endif
17114: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
17115: system(pplotcmd);
1.126 brouard 17116: }
17117: else if (z[0] == 'g') system(plotcmd);
17118: else if (z[0] == 'q') exit(0);
17119: }
1.227 brouard 17120: end:
1.126 brouard 17121: while (z[0] != 'q') {
1.195 brouard 17122: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 17123: scanf("%s",z);
17124: }
1.283 brouard 17125: printf("End\n");
1.282 brouard 17126: exit(0);
1.126 brouard 17127: }
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