Annotation of imach/src/imach.c, revision 1.334
1.334 ! brouard 1: /* $Id: imach.c,v 1.333 2022/08/21 09:10:30 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.334 ! brouard 4: Revision 1.333 2022/08/21 09:10:30 brouard
! 5: * src/imach.c (Module): Version 0.99r33 A lot of changes in
! 6: reassigning covariates: my first idea was that people will always
! 7: use the first covariate V1 into the model but in fact they are
! 8: producing data with many covariates and can use an equation model
! 9: with some of the covariate; it means that in a model V2+V3 instead
! 10: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
! 11: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
! 12: the equation model is restricted to two variables only (V2, V3)
! 13: and the combination for V2 should be codtabm(k,1) instead of
! 14: (codtabm(k,2), and the code should be
! 15: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
! 16: made. All of these should be simplified once a day like we did in
! 17: hpxij() for example by using precov[nres] which is computed in
! 18: decoderesult for each nres of each resultline. Loop should be done
! 19: on the equation model globally by distinguishing only product with
! 20: age (which are changing with age) and no more on type of
! 21: covariates, single dummies, single covariates.
! 22:
1.333 brouard 23: Revision 1.332 2022/08/21 09:06:25 brouard
24: Summary: Version 0.99r33
25:
26: * src/imach.c (Module): Version 0.99r33 A lot of changes in
27: reassigning covariates: my first idea was that people will always
28: use the first covariate V1 into the model but in fact they are
29: producing data with many covariates and can use an equation model
30: with some of the covariate; it means that in a model V2+V3 instead
31: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
32: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
33: the equation model is restricted to two variables only (V2, V3)
34: and the combination for V2 should be codtabm(k,1) instead of
35: (codtabm(k,2), and the code should be
36: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
37: made. All of these should be simplified once a day like we did in
38: hpxij() for example by using precov[nres] which is computed in
39: decoderesult for each nres of each resultline. Loop should be done
40: on the equation model globally by distinguishing only product with
41: age (which are changing with age) and no more on type of
42: covariates, single dummies, single covariates.
43:
1.332 brouard 44: Revision 1.331 2022/08/07 05:40:09 brouard
45: *** empty log message ***
46:
1.331 brouard 47: Revision 1.330 2022/08/06 07:18:25 brouard
48: Summary: last 0.99r31
49:
50: * imach.c (Module): Version of imach using partly decoderesult to rebuild xpxij function
51:
1.330 brouard 52: Revision 1.329 2022/08/03 17:29:54 brouard
53: * imach.c (Module): Many errors in graphs fixed with Vn*age covariates.
54:
1.329 brouard 55: Revision 1.328 2022/07/27 17:40:48 brouard
56: Summary: valgrind bug fixed by initializing to zero DummyV as well as Tage
57:
1.328 brouard 58: Revision 1.327 2022/07/27 14:47:35 brouard
59: Summary: Still a problem for one-step probabilities in case of quantitative variables
60:
1.327 brouard 61: Revision 1.326 2022/07/26 17:33:55 brouard
62: Summary: some test with nres=1
63:
1.326 brouard 64: Revision 1.325 2022/07/25 14:27:23 brouard
65: Summary: r30
66:
67: * imach.c (Module): Error cptcovn instead of nsd in bmij (was
68: coredumped, revealed by Feiuno, thank you.
69:
1.325 brouard 70: Revision 1.324 2022/07/23 17:44:26 brouard
71: *** empty log message ***
72:
1.324 brouard 73: Revision 1.323 2022/07/22 12:30:08 brouard
74: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
75:
1.323 brouard 76: Revision 1.322 2022/07/22 12:27:48 brouard
77: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
78:
1.322 brouard 79: Revision 1.321 2022/07/22 12:04:24 brouard
80: Summary: r28
81:
82: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
83:
1.321 brouard 84: Revision 1.320 2022/06/02 05:10:11 brouard
85: *** empty log message ***
86:
1.320 brouard 87: Revision 1.319 2022/06/02 04:45:11 brouard
88: * imach.c (Module): Adding the Wald tests from the log to the main
89: htm for better display of the maximum likelihood estimators.
90:
1.319 brouard 91: Revision 1.318 2022/05/24 08:10:59 brouard
92: * imach.c (Module): Some attempts to find a bug of wrong estimates
93: of confidencce intervals with product in the equation modelC
94:
1.318 brouard 95: Revision 1.317 2022/05/15 15:06:23 brouard
96: * imach.c (Module): Some minor improvements
97:
1.317 brouard 98: Revision 1.316 2022/05/11 15:11:31 brouard
99: Summary: r27
100:
1.316 brouard 101: Revision 1.315 2022/05/11 15:06:32 brouard
102: *** empty log message ***
103:
1.315 brouard 104: Revision 1.314 2022/04/13 17:43:09 brouard
105: * imach.c (Module): Adding link to text data files
106:
1.314 brouard 107: Revision 1.313 2022/04/11 15:57:42 brouard
108: * imach.c (Module): Error in rewriting the 'r' file with yearsfproj or yearsbproj fixed
109:
1.313 brouard 110: Revision 1.312 2022/04/05 21:24:39 brouard
111: *** empty log message ***
112:
1.312 brouard 113: Revision 1.311 2022/04/05 21:03:51 brouard
114: Summary: Fixed quantitative covariates
115:
116: Fixed covariates (dummy or quantitative)
117: with missing values have never been allowed but are ERRORS and
118: program quits. Standard deviations of fixed covariates were
119: wrongly computed. Mean and standard deviations of time varying
120: covariates are still not computed.
121:
1.311 brouard 122: Revision 1.310 2022/03/17 08:45:53 brouard
123: Summary: 99r25
124:
125: Improving detection of errors: result lines should be compatible with
126: the model.
127:
1.310 brouard 128: Revision 1.309 2021/05/20 12:39:14 brouard
129: Summary: Version 0.99r24
130:
1.309 brouard 131: Revision 1.308 2021/03/31 13:11:57 brouard
132: Summary: Version 0.99r23
133:
134:
135: * imach.c (Module): Still bugs in the result loop. Thank to Holly Benett
136:
1.308 brouard 137: Revision 1.307 2021/03/08 18:11:32 brouard
138: Summary: 0.99r22 fixed bug on result:
139:
1.307 brouard 140: Revision 1.306 2021/02/20 15:44:02 brouard
141: Summary: Version 0.99r21
142:
143: * imach.c (Module): Fix bug on quitting after result lines!
144: (Module): Version 0.99r21
145:
1.306 brouard 146: Revision 1.305 2021/02/20 15:28:30 brouard
147: * imach.c (Module): Fix bug on quitting after result lines!
148:
1.305 brouard 149: Revision 1.304 2021/02/12 11:34:20 brouard
150: * imach.c (Module): The use of a Windows BOM (huge) file is now an error
151:
1.304 brouard 152: Revision 1.303 2021/02/11 19:50:15 brouard
153: * (Module): imach.c Someone entered 'results:' instead of 'result:'. Now it is an error which is printed.
154:
1.303 brouard 155: Revision 1.302 2020/02/22 21:00:05 brouard
156: * (Module): imach.c Update mle=-3 (for computing Life expectancy
157: and life table from the data without any state)
158:
1.302 brouard 159: Revision 1.301 2019/06/04 13:51:20 brouard
160: Summary: Error in 'r'parameter file backcast yearsbproj instead of yearsfproj
161:
1.301 brouard 162: Revision 1.300 2019/05/22 19:09:45 brouard
163: Summary: version 0.99r19 of May 2019
164:
1.300 brouard 165: Revision 1.299 2019/05/22 18:37:08 brouard
166: Summary: Cleaned 0.99r19
167:
1.299 brouard 168: Revision 1.298 2019/05/22 18:19:56 brouard
169: *** empty log message ***
170:
1.298 brouard 171: Revision 1.297 2019/05/22 17:56:10 brouard
172: Summary: Fix bug by moving date2dmy and nhstepm which gaefin=-1
173:
1.297 brouard 174: Revision 1.296 2019/05/20 13:03:18 brouard
175: Summary: Projection syntax simplified
176:
177:
178: We can now start projections, forward or backward, from the mean date
179: of inteviews up to or down to a number of years of projection:
180: prevforecast=1 yearsfproj=15.3 mobil_average=0
181: or
182: prevforecast=1 starting-proj-date=1/1/2007 final-proj-date=12/31/2017 mobil_average=0
183: or
184: prevbackcast=1 yearsbproj=12.3 mobil_average=1
185: or
186: prevbackcast=1 starting-back-date=1/10/1999 final-back-date=1/1/1985 mobil_average=1
187:
1.296 brouard 188: Revision 1.295 2019/05/18 09:52:50 brouard
189: Summary: doxygen tex bug
190:
1.295 brouard 191: Revision 1.294 2019/05/16 14:54:33 brouard
192: Summary: There was some wrong lines added
193:
1.294 brouard 194: Revision 1.293 2019/05/09 15:17:34 brouard
195: *** empty log message ***
196:
1.293 brouard 197: Revision 1.292 2019/05/09 14:17:20 brouard
198: Summary: Some updates
199:
1.292 brouard 200: Revision 1.291 2019/05/09 13:44:18 brouard
201: Summary: Before ncovmax
202:
1.291 brouard 203: Revision 1.290 2019/05/09 13:39:37 brouard
204: Summary: 0.99r18 unlimited number of individuals
205:
206: 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.
207:
1.290 brouard 208: Revision 1.289 2018/12/13 09:16:26 brouard
209: Summary: Bug for young ages (<-30) will be in r17
210:
1.289 brouard 211: Revision 1.288 2018/05/02 20:58:27 brouard
212: Summary: Some bugs fixed
213:
1.288 brouard 214: Revision 1.287 2018/05/01 17:57:25 brouard
215: Summary: Bug fixed by providing frequencies only for non missing covariates
216:
1.287 brouard 217: Revision 1.286 2018/04/27 14:27:04 brouard
218: Summary: some minor bugs
219:
1.286 brouard 220: Revision 1.285 2018/04/21 21:02:16 brouard
221: Summary: Some bugs fixed, valgrind tested
222:
1.285 brouard 223: Revision 1.284 2018/04/20 05:22:13 brouard
224: Summary: Computing mean and stdeviation of fixed quantitative variables
225:
1.284 brouard 226: Revision 1.283 2018/04/19 14:49:16 brouard
227: Summary: Some minor bugs fixed
228:
1.283 brouard 229: Revision 1.282 2018/02/27 22:50:02 brouard
230: *** empty log message ***
231:
1.282 brouard 232: Revision 1.281 2018/02/27 19:25:23 brouard
233: Summary: Adding second argument for quitting
234:
1.281 brouard 235: Revision 1.280 2018/02/21 07:58:13 brouard
236: Summary: 0.99r15
237:
238: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
239:
1.280 brouard 240: Revision 1.279 2017/07/20 13:35:01 brouard
241: Summary: temporary working
242:
1.279 brouard 243: Revision 1.278 2017/07/19 14:09:02 brouard
244: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
245:
1.278 brouard 246: Revision 1.277 2017/07/17 08:53:49 brouard
247: Summary: BOM files can be read now
248:
1.277 brouard 249: Revision 1.276 2017/06/30 15:48:31 brouard
250: Summary: Graphs improvements
251:
1.276 brouard 252: Revision 1.275 2017/06/30 13:39:33 brouard
253: Summary: Saito's color
254:
1.275 brouard 255: Revision 1.274 2017/06/29 09:47:08 brouard
256: Summary: Version 0.99r14
257:
1.274 brouard 258: Revision 1.273 2017/06/27 11:06:02 brouard
259: Summary: More documentation on projections
260:
1.273 brouard 261: Revision 1.272 2017/06/27 10:22:40 brouard
262: Summary: Color of backprojection changed from 6 to 5(yellow)
263:
1.272 brouard 264: Revision 1.271 2017/06/27 10:17:50 brouard
265: Summary: Some bug with rint
266:
1.271 brouard 267: Revision 1.270 2017/05/24 05:45:29 brouard
268: *** empty log message ***
269:
1.270 brouard 270: Revision 1.269 2017/05/23 08:39:25 brouard
271: Summary: Code into subroutine, cleanings
272:
1.269 brouard 273: Revision 1.268 2017/05/18 20:09:32 brouard
274: Summary: backprojection and confidence intervals of backprevalence
275:
1.268 brouard 276: Revision 1.267 2017/05/13 10:25:05 brouard
277: Summary: temporary save for backprojection
278:
1.267 brouard 279: Revision 1.266 2017/05/13 07:26:12 brouard
280: Summary: Version 0.99r13 (improvements and bugs fixed)
281:
1.266 brouard 282: Revision 1.265 2017/04/26 16:22:11 brouard
283: Summary: imach 0.99r13 Some bugs fixed
284:
1.265 brouard 285: Revision 1.264 2017/04/26 06:01:29 brouard
286: Summary: Labels in graphs
287:
1.264 brouard 288: Revision 1.263 2017/04/24 15:23:15 brouard
289: Summary: to save
290:
1.263 brouard 291: Revision 1.262 2017/04/18 16:48:12 brouard
292: *** empty log message ***
293:
1.262 brouard 294: Revision 1.261 2017/04/05 10:14:09 brouard
295: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
296:
1.261 brouard 297: Revision 1.260 2017/04/04 17:46:59 brouard
298: Summary: Gnuplot indexations fixed (humm)
299:
1.260 brouard 300: Revision 1.259 2017/04/04 13:01:16 brouard
301: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
302:
1.259 brouard 303: Revision 1.258 2017/04/03 10:17:47 brouard
304: Summary: Version 0.99r12
305:
306: Some cleanings, conformed with updated documentation.
307:
1.258 brouard 308: Revision 1.257 2017/03/29 16:53:30 brouard
309: Summary: Temp
310:
1.257 brouard 311: Revision 1.256 2017/03/27 05:50:23 brouard
312: Summary: Temporary
313:
1.256 brouard 314: Revision 1.255 2017/03/08 16:02:28 brouard
315: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
316:
1.255 brouard 317: Revision 1.254 2017/03/08 07:13:00 brouard
318: Summary: Fixing data parameter line
319:
1.254 brouard 320: Revision 1.253 2016/12/15 11:59:41 brouard
321: Summary: 0.99 in progress
322:
1.253 brouard 323: Revision 1.252 2016/09/15 21:15:37 brouard
324: *** empty log message ***
325:
1.252 brouard 326: Revision 1.251 2016/09/15 15:01:13 brouard
327: Summary: not working
328:
1.251 brouard 329: Revision 1.250 2016/09/08 16:07:27 brouard
330: Summary: continue
331:
1.250 brouard 332: Revision 1.249 2016/09/07 17:14:18 brouard
333: Summary: Starting values from frequencies
334:
1.249 brouard 335: Revision 1.248 2016/09/07 14:10:18 brouard
336: *** empty log message ***
337:
1.248 brouard 338: Revision 1.247 2016/09/02 11:11:21 brouard
339: *** empty log message ***
340:
1.247 brouard 341: Revision 1.246 2016/09/02 08:49:22 brouard
342: *** empty log message ***
343:
1.246 brouard 344: Revision 1.245 2016/09/02 07:25:01 brouard
345: *** empty log message ***
346:
1.245 brouard 347: Revision 1.244 2016/09/02 07:17:34 brouard
348: *** empty log message ***
349:
1.244 brouard 350: Revision 1.243 2016/09/02 06:45:35 brouard
351: *** empty log message ***
352:
1.243 brouard 353: Revision 1.242 2016/08/30 15:01:20 brouard
354: Summary: Fixing a lots
355:
1.242 brouard 356: Revision 1.241 2016/08/29 17:17:25 brouard
357: Summary: gnuplot problem in Back projection to fix
358:
1.241 brouard 359: Revision 1.240 2016/08/29 07:53:18 brouard
360: Summary: Better
361:
1.240 brouard 362: Revision 1.239 2016/08/26 15:51:03 brouard
363: Summary: Improvement in Powell output in order to copy and paste
364:
365: Author:
366:
1.239 brouard 367: Revision 1.238 2016/08/26 14:23:35 brouard
368: Summary: Starting tests of 0.99
369:
1.238 brouard 370: Revision 1.237 2016/08/26 09:20:19 brouard
371: Summary: to valgrind
372:
1.237 brouard 373: Revision 1.236 2016/08/25 10:50:18 brouard
374: *** empty log message ***
375:
1.236 brouard 376: Revision 1.235 2016/08/25 06:59:23 brouard
377: *** empty log message ***
378:
1.235 brouard 379: Revision 1.234 2016/08/23 16:51:20 brouard
380: *** empty log message ***
381:
1.234 brouard 382: Revision 1.233 2016/08/23 07:40:50 brouard
383: Summary: not working
384:
1.233 brouard 385: Revision 1.232 2016/08/22 14:20:21 brouard
386: Summary: not working
387:
1.232 brouard 388: Revision 1.231 2016/08/22 07:17:15 brouard
389: Summary: not working
390:
1.231 brouard 391: Revision 1.230 2016/08/22 06:55:53 brouard
392: Summary: Not working
393:
1.230 brouard 394: Revision 1.229 2016/07/23 09:45:53 brouard
395: Summary: Completing for func too
396:
1.229 brouard 397: Revision 1.228 2016/07/22 17:45:30 brouard
398: Summary: Fixing some arrays, still debugging
399:
1.227 brouard 400: Revision 1.226 2016/07/12 18:42:34 brouard
401: Summary: temp
402:
1.226 brouard 403: Revision 1.225 2016/07/12 08:40:03 brouard
404: Summary: saving but not running
405:
1.225 brouard 406: Revision 1.224 2016/07/01 13:16:01 brouard
407: Summary: Fixes
408:
1.224 brouard 409: Revision 1.223 2016/02/19 09:23:35 brouard
410: Summary: temporary
411:
1.223 brouard 412: Revision 1.222 2016/02/17 08:14:50 brouard
413: Summary: Probably last 0.98 stable version 0.98r6
414:
1.222 brouard 415: Revision 1.221 2016/02/15 23:35:36 brouard
416: Summary: minor bug
417:
1.220 brouard 418: Revision 1.219 2016/02/15 00:48:12 brouard
419: *** empty log message ***
420:
1.219 brouard 421: Revision 1.218 2016/02/12 11:29:23 brouard
422: Summary: 0.99 Back projections
423:
1.218 brouard 424: Revision 1.217 2015/12/23 17:18:31 brouard
425: Summary: Experimental backcast
426:
1.217 brouard 427: Revision 1.216 2015/12/18 17:32:11 brouard
428: Summary: 0.98r4 Warning and status=-2
429:
430: Version 0.98r4 is now:
431: - displaying an error when status is -1, date of interview unknown and date of death known;
432: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
433: Older changes concerning s=-2, dating from 2005 have been supersed.
434:
1.216 brouard 435: Revision 1.215 2015/12/16 08:52:24 brouard
436: Summary: 0.98r4 working
437:
1.215 brouard 438: Revision 1.214 2015/12/16 06:57:54 brouard
439: Summary: temporary not working
440:
1.214 brouard 441: Revision 1.213 2015/12/11 18:22:17 brouard
442: Summary: 0.98r4
443:
1.213 brouard 444: Revision 1.212 2015/11/21 12:47:24 brouard
445: Summary: minor typo
446:
1.212 brouard 447: Revision 1.211 2015/11/21 12:41:11 brouard
448: Summary: 0.98r3 with some graph of projected cross-sectional
449:
450: Author: Nicolas Brouard
451:
1.211 brouard 452: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 453: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 454: Summary: Adding ftolpl parameter
455: Author: N Brouard
456:
457: We had difficulties to get smoothed confidence intervals. It was due
458: to the period prevalence which wasn't computed accurately. The inner
459: parameter ftolpl is now an outer parameter of the .imach parameter
460: file after estepm. If ftolpl is small 1.e-4 and estepm too,
461: computation are long.
462:
1.209 brouard 463: Revision 1.208 2015/11/17 14:31:57 brouard
464: Summary: temporary
465:
1.208 brouard 466: Revision 1.207 2015/10/27 17:36:57 brouard
467: *** empty log message ***
468:
1.207 brouard 469: Revision 1.206 2015/10/24 07:14:11 brouard
470: *** empty log message ***
471:
1.206 brouard 472: Revision 1.205 2015/10/23 15:50:53 brouard
473: Summary: 0.98r3 some clarification for graphs on likelihood contributions
474:
1.205 brouard 475: Revision 1.204 2015/10/01 16:20:26 brouard
476: Summary: Some new graphs of contribution to likelihood
477:
1.204 brouard 478: Revision 1.203 2015/09/30 17:45:14 brouard
479: Summary: looking at better estimation of the hessian
480:
481: Also a better criteria for convergence to the period prevalence And
482: therefore adding the number of years needed to converge. (The
483: prevalence in any alive state shold sum to one
484:
1.203 brouard 485: Revision 1.202 2015/09/22 19:45:16 brouard
486: Summary: Adding some overall graph on contribution to likelihood. Might change
487:
1.202 brouard 488: Revision 1.201 2015/09/15 17:34:58 brouard
489: Summary: 0.98r0
490:
491: - Some new graphs like suvival functions
492: - Some bugs fixed like model=1+age+V2.
493:
1.201 brouard 494: Revision 1.200 2015/09/09 16:53:55 brouard
495: Summary: Big bug thanks to Flavia
496:
497: Even model=1+age+V2. did not work anymore
498:
1.200 brouard 499: Revision 1.199 2015/09/07 14:09:23 brouard
500: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
501:
1.199 brouard 502: Revision 1.198 2015/09/03 07:14:39 brouard
503: Summary: 0.98q5 Flavia
504:
1.198 brouard 505: Revision 1.197 2015/09/01 18:24:39 brouard
506: *** empty log message ***
507:
1.197 brouard 508: Revision 1.196 2015/08/18 23:17:52 brouard
509: Summary: 0.98q5
510:
1.196 brouard 511: Revision 1.195 2015/08/18 16:28:39 brouard
512: Summary: Adding a hack for testing purpose
513:
514: After reading the title, ftol and model lines, if the comment line has
515: a q, starting with #q, the answer at the end of the run is quit. It
516: permits to run test files in batch with ctest. The former workaround was
517: $ echo q | imach foo.imach
518:
1.195 brouard 519: Revision 1.194 2015/08/18 13:32:00 brouard
520: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
521:
1.194 brouard 522: Revision 1.193 2015/08/04 07:17:42 brouard
523: Summary: 0.98q4
524:
1.193 brouard 525: Revision 1.192 2015/07/16 16:49:02 brouard
526: Summary: Fixing some outputs
527:
1.192 brouard 528: Revision 1.191 2015/07/14 10:00:33 brouard
529: Summary: Some fixes
530:
1.191 brouard 531: Revision 1.190 2015/05/05 08:51:13 brouard
532: Summary: Adding digits in output parameters (7 digits instead of 6)
533:
534: Fix 1+age+.
535:
1.190 brouard 536: Revision 1.189 2015/04/30 14:45:16 brouard
537: Summary: 0.98q2
538:
1.189 brouard 539: Revision 1.188 2015/04/30 08:27:53 brouard
540: *** empty log message ***
541:
1.188 brouard 542: Revision 1.187 2015/04/29 09:11:15 brouard
543: *** empty log message ***
544:
1.187 brouard 545: Revision 1.186 2015/04/23 12:01:52 brouard
546: Summary: V1*age is working now, version 0.98q1
547:
548: Some codes had been disabled in order to simplify and Vn*age was
549: working in the optimization phase, ie, giving correct MLE parameters,
550: but, as usual, outputs were not correct and program core dumped.
551:
1.186 brouard 552: Revision 1.185 2015/03/11 13:26:42 brouard
553: Summary: Inclusion of compile and links command line for Intel Compiler
554:
1.185 brouard 555: Revision 1.184 2015/03/11 11:52:39 brouard
556: Summary: Back from Windows 8. Intel Compiler
557:
1.184 brouard 558: Revision 1.183 2015/03/10 20:34:32 brouard
559: Summary: 0.98q0, trying with directest, mnbrak fixed
560:
561: We use directest instead of original Powell test; probably no
562: incidence on the results, but better justifications;
563: We fixed Numerical Recipes mnbrak routine which was wrong and gave
564: wrong results.
565:
1.183 brouard 566: Revision 1.182 2015/02/12 08:19:57 brouard
567: Summary: Trying to keep directest which seems simpler and more general
568: Author: Nicolas Brouard
569:
1.182 brouard 570: Revision 1.181 2015/02/11 23:22:24 brouard
571: Summary: Comments on Powell added
572:
573: Author:
574:
1.181 brouard 575: Revision 1.180 2015/02/11 17:33:45 brouard
576: Summary: Finishing move from main to function (hpijx and prevalence_limit)
577:
1.180 brouard 578: Revision 1.179 2015/01/04 09:57:06 brouard
579: Summary: back to OS/X
580:
1.179 brouard 581: Revision 1.178 2015/01/04 09:35:48 brouard
582: *** empty log message ***
583:
1.178 brouard 584: Revision 1.177 2015/01/03 18:40:56 brouard
585: Summary: Still testing ilc32 on OSX
586:
1.177 brouard 587: Revision 1.176 2015/01/03 16:45:04 brouard
588: *** empty log message ***
589:
1.176 brouard 590: Revision 1.175 2015/01/03 16:33:42 brouard
591: *** empty log message ***
592:
1.175 brouard 593: Revision 1.174 2015/01/03 16:15:49 brouard
594: Summary: Still in cross-compilation
595:
1.174 brouard 596: Revision 1.173 2015/01/03 12:06:26 brouard
597: Summary: trying to detect cross-compilation
598:
1.173 brouard 599: Revision 1.172 2014/12/27 12:07:47 brouard
600: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
601:
1.172 brouard 602: Revision 1.171 2014/12/23 13:26:59 brouard
603: Summary: Back from Visual C
604:
605: Still problem with utsname.h on Windows
606:
1.171 brouard 607: Revision 1.170 2014/12/23 11:17:12 brouard
608: Summary: Cleaning some \%% back to %%
609:
610: The escape was mandatory for a specific compiler (which one?), but too many warnings.
611:
1.170 brouard 612: Revision 1.169 2014/12/22 23:08:31 brouard
613: Summary: 0.98p
614:
615: Outputs some informations on compiler used, OS etc. Testing on different platforms.
616:
1.169 brouard 617: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 618: Summary: update
1.169 brouard 619:
1.168 brouard 620: Revision 1.167 2014/12/22 13:50:56 brouard
621: Summary: Testing uname and compiler version and if compiled 32 or 64
622:
623: Testing on Linux 64
624:
1.167 brouard 625: Revision 1.166 2014/12/22 11:40:47 brouard
626: *** empty log message ***
627:
1.166 brouard 628: Revision 1.165 2014/12/16 11:20:36 brouard
629: Summary: After compiling on Visual C
630:
631: * imach.c (Module): Merging 1.61 to 1.162
632:
1.165 brouard 633: Revision 1.164 2014/12/16 10:52:11 brouard
634: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
635:
636: * imach.c (Module): Merging 1.61 to 1.162
637:
1.164 brouard 638: Revision 1.163 2014/12/16 10:30:11 brouard
639: * imach.c (Module): Merging 1.61 to 1.162
640:
1.163 brouard 641: Revision 1.162 2014/09/25 11:43:39 brouard
642: Summary: temporary backup 0.99!
643:
1.162 brouard 644: Revision 1.1 2014/09/16 11:06:58 brouard
645: Summary: With some code (wrong) for nlopt
646:
647: Author:
648:
649: Revision 1.161 2014/09/15 20:41:41 brouard
650: Summary: Problem with macro SQR on Intel compiler
651:
1.161 brouard 652: Revision 1.160 2014/09/02 09:24:05 brouard
653: *** empty log message ***
654:
1.160 brouard 655: Revision 1.159 2014/09/01 10:34:10 brouard
656: Summary: WIN32
657: Author: Brouard
658:
1.159 brouard 659: Revision 1.158 2014/08/27 17:11:51 brouard
660: *** empty log message ***
661:
1.158 brouard 662: Revision 1.157 2014/08/27 16:26:55 brouard
663: Summary: Preparing windows Visual studio version
664: Author: Brouard
665:
666: In order to compile on Visual studio, time.h is now correct and time_t
667: and tm struct should be used. difftime should be used but sometimes I
668: just make the differences in raw time format (time(&now).
669: Trying to suppress #ifdef LINUX
670: Add xdg-open for __linux in order to open default browser.
671:
1.157 brouard 672: Revision 1.156 2014/08/25 20:10:10 brouard
673: *** empty log message ***
674:
1.156 brouard 675: Revision 1.155 2014/08/25 18:32:34 brouard
676: Summary: New compile, minor changes
677: Author: Brouard
678:
1.155 brouard 679: Revision 1.154 2014/06/20 17:32:08 brouard
680: Summary: Outputs now all graphs of convergence to period prevalence
681:
1.154 brouard 682: Revision 1.153 2014/06/20 16:45:46 brouard
683: Summary: If 3 live state, convergence to period prevalence on same graph
684: Author: Brouard
685:
1.153 brouard 686: Revision 1.152 2014/06/18 17:54:09 brouard
687: Summary: open browser, use gnuplot on same dir than imach if not found in the path
688:
1.152 brouard 689: Revision 1.151 2014/06/18 16:43:30 brouard
690: *** empty log message ***
691:
1.151 brouard 692: Revision 1.150 2014/06/18 16:42:35 brouard
693: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
694: Author: brouard
695:
1.150 brouard 696: Revision 1.149 2014/06/18 15:51:14 brouard
697: Summary: Some fixes in parameter files errors
698: Author: Nicolas Brouard
699:
1.149 brouard 700: Revision 1.148 2014/06/17 17:38:48 brouard
701: Summary: Nothing new
702: Author: Brouard
703:
704: Just a new packaging for OS/X version 0.98nS
705:
1.148 brouard 706: Revision 1.147 2014/06/16 10:33:11 brouard
707: *** empty log message ***
708:
1.147 brouard 709: Revision 1.146 2014/06/16 10:20:28 brouard
710: Summary: Merge
711: Author: Brouard
712:
713: Merge, before building revised version.
714:
1.146 brouard 715: Revision 1.145 2014/06/10 21:23:15 brouard
716: Summary: Debugging with valgrind
717: Author: Nicolas Brouard
718:
719: Lot of changes in order to output the results with some covariates
720: After the Edimburgh REVES conference 2014, it seems mandatory to
721: improve the code.
722: No more memory valgrind error but a lot has to be done in order to
723: continue the work of splitting the code into subroutines.
724: Also, decodemodel has been improved. Tricode is still not
725: optimal. nbcode should be improved. Documentation has been added in
726: the source code.
727:
1.144 brouard 728: Revision 1.143 2014/01/26 09:45:38 brouard
729: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
730:
731: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
732: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
733:
1.143 brouard 734: Revision 1.142 2014/01/26 03:57:36 brouard
735: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
736:
737: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
738:
1.142 brouard 739: Revision 1.141 2014/01/26 02:42:01 brouard
740: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
741:
1.141 brouard 742: Revision 1.140 2011/09/02 10:37:54 brouard
743: Summary: times.h is ok with mingw32 now.
744:
1.140 brouard 745: Revision 1.139 2010/06/14 07:50:17 brouard
746: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
747: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
748:
1.139 brouard 749: Revision 1.138 2010/04/30 18:19:40 brouard
750: *** empty log message ***
751:
1.138 brouard 752: Revision 1.137 2010/04/29 18:11:38 brouard
753: (Module): Checking covariates for more complex models
754: than V1+V2. A lot of change to be done. Unstable.
755:
1.137 brouard 756: Revision 1.136 2010/04/26 20:30:53 brouard
757: (Module): merging some libgsl code. Fixing computation
758: of likelione (using inter/intrapolation if mle = 0) in order to
759: get same likelihood as if mle=1.
760: Some cleaning of code and comments added.
761:
1.136 brouard 762: Revision 1.135 2009/10/29 15:33:14 brouard
763: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
764:
1.135 brouard 765: Revision 1.134 2009/10/29 13:18:53 brouard
766: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
767:
1.134 brouard 768: Revision 1.133 2009/07/06 10:21:25 brouard
769: just nforces
770:
1.133 brouard 771: Revision 1.132 2009/07/06 08:22:05 brouard
772: Many tings
773:
1.132 brouard 774: Revision 1.131 2009/06/20 16:22:47 brouard
775: Some dimensions resccaled
776:
1.131 brouard 777: Revision 1.130 2009/05/26 06:44:34 brouard
778: (Module): Max Covariate is now set to 20 instead of 8. A
779: lot of cleaning with variables initialized to 0. Trying to make
780: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
781:
1.130 brouard 782: Revision 1.129 2007/08/31 13:49:27 lievre
783: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
784:
1.129 lievre 785: Revision 1.128 2006/06/30 13:02:05 brouard
786: (Module): Clarifications on computing e.j
787:
1.128 brouard 788: Revision 1.127 2006/04/28 18:11:50 brouard
789: (Module): Yes the sum of survivors was wrong since
790: imach-114 because nhstepm was no more computed in the age
791: loop. Now we define nhstepma in the age loop.
792: (Module): In order to speed up (in case of numerous covariates) we
793: compute health expectancies (without variances) in a first step
794: and then all the health expectancies with variances or standard
795: deviation (needs data from the Hessian matrices) which slows the
796: computation.
797: In the future we should be able to stop the program is only health
798: expectancies and graph are needed without standard deviations.
799:
1.127 brouard 800: Revision 1.126 2006/04/28 17:23:28 brouard
801: (Module): Yes the sum of survivors was wrong since
802: imach-114 because nhstepm was no more computed in the age
803: loop. Now we define nhstepma in the age loop.
804: Version 0.98h
805:
1.126 brouard 806: Revision 1.125 2006/04/04 15:20:31 lievre
807: Errors in calculation of health expectancies. Age was not initialized.
808: Forecasting file added.
809:
810: Revision 1.124 2006/03/22 17:13:53 lievre
811: Parameters are printed with %lf instead of %f (more numbers after the comma).
812: The log-likelihood is printed in the log file
813:
814: Revision 1.123 2006/03/20 10:52:43 brouard
815: * imach.c (Module): <title> changed, corresponds to .htm file
816: name. <head> headers where missing.
817:
818: * imach.c (Module): Weights can have a decimal point as for
819: English (a comma might work with a correct LC_NUMERIC environment,
820: otherwise the weight is truncated).
821: Modification of warning when the covariates values are not 0 or
822: 1.
823: Version 0.98g
824:
825: Revision 1.122 2006/03/20 09:45:41 brouard
826: (Module): Weights can have a decimal point as for
827: English (a comma might work with a correct LC_NUMERIC environment,
828: otherwise the weight is truncated).
829: Modification of warning when the covariates values are not 0 or
830: 1.
831: Version 0.98g
832:
833: Revision 1.121 2006/03/16 17:45:01 lievre
834: * imach.c (Module): Comments concerning covariates added
835:
836: * imach.c (Module): refinements in the computation of lli if
837: status=-2 in order to have more reliable computation if stepm is
838: not 1 month. Version 0.98f
839:
840: Revision 1.120 2006/03/16 15:10:38 lievre
841: (Module): refinements in the computation of lli if
842: status=-2 in order to have more reliable computation if stepm is
843: not 1 month. Version 0.98f
844:
845: Revision 1.119 2006/03/15 17:42:26 brouard
846: (Module): Bug if status = -2, the loglikelihood was
847: computed as likelihood omitting the logarithm. Version O.98e
848:
849: Revision 1.118 2006/03/14 18:20:07 brouard
850: (Module): varevsij Comments added explaining the second
851: table of variances if popbased=1 .
852: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
853: (Module): Function pstamp added
854: (Module): Version 0.98d
855:
856: Revision 1.117 2006/03/14 17:16:22 brouard
857: (Module): varevsij Comments added explaining the second
858: table of variances if popbased=1 .
859: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
860: (Module): Function pstamp added
861: (Module): Version 0.98d
862:
863: Revision 1.116 2006/03/06 10:29:27 brouard
864: (Module): Variance-covariance wrong links and
865: varian-covariance of ej. is needed (Saito).
866:
867: Revision 1.115 2006/02/27 12:17:45 brouard
868: (Module): One freematrix added in mlikeli! 0.98c
869:
870: Revision 1.114 2006/02/26 12:57:58 brouard
871: (Module): Some improvements in processing parameter
872: filename with strsep.
873:
874: Revision 1.113 2006/02/24 14:20:24 brouard
875: (Module): Memory leaks checks with valgrind and:
876: datafile was not closed, some imatrix were not freed and on matrix
877: allocation too.
878:
879: Revision 1.112 2006/01/30 09:55:26 brouard
880: (Module): Back to gnuplot.exe instead of wgnuplot.exe
881:
882: Revision 1.111 2006/01/25 20:38:18 brouard
883: (Module): Lots of cleaning and bugs added (Gompertz)
884: (Module): Comments can be added in data file. Missing date values
885: can be a simple dot '.'.
886:
887: Revision 1.110 2006/01/25 00:51:50 brouard
888: (Module): Lots of cleaning and bugs added (Gompertz)
889:
890: Revision 1.109 2006/01/24 19:37:15 brouard
891: (Module): Comments (lines starting with a #) are allowed in data.
892:
893: Revision 1.108 2006/01/19 18:05:42 lievre
894: Gnuplot problem appeared...
895: To be fixed
896:
897: Revision 1.107 2006/01/19 16:20:37 brouard
898: Test existence of gnuplot in imach path
899:
900: Revision 1.106 2006/01/19 13:24:36 brouard
901: Some cleaning and links added in html output
902:
903: Revision 1.105 2006/01/05 20:23:19 lievre
904: *** empty log message ***
905:
906: Revision 1.104 2005/09/30 16:11:43 lievre
907: (Module): sump fixed, loop imx fixed, and simplifications.
908: (Module): If the status is missing at the last wave but we know
909: that the person is alive, then we can code his/her status as -2
910: (instead of missing=-1 in earlier versions) and his/her
911: contributions to the likelihood is 1 - Prob of dying from last
912: health status (= 1-p13= p11+p12 in the easiest case of somebody in
913: the healthy state at last known wave). Version is 0.98
914:
915: Revision 1.103 2005/09/30 15:54:49 lievre
916: (Module): sump fixed, loop imx fixed, and simplifications.
917:
918: Revision 1.102 2004/09/15 17:31:30 brouard
919: Add the possibility to read data file including tab characters.
920:
921: Revision 1.101 2004/09/15 10:38:38 brouard
922: Fix on curr_time
923:
924: Revision 1.100 2004/07/12 18:29:06 brouard
925: Add version for Mac OS X. Just define UNIX in Makefile
926:
927: Revision 1.99 2004/06/05 08:57:40 brouard
928: *** empty log message ***
929:
930: Revision 1.98 2004/05/16 15:05:56 brouard
931: New version 0.97 . First attempt to estimate force of mortality
932: directly from the data i.e. without the need of knowing the health
933: state at each age, but using a Gompertz model: log u =a + b*age .
934: This is the basic analysis of mortality and should be done before any
935: other analysis, in order to test if the mortality estimated from the
936: cross-longitudinal survey is different from the mortality estimated
937: from other sources like vital statistic data.
938:
939: The same imach parameter file can be used but the option for mle should be -3.
940:
1.324 brouard 941: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 942: former routines in order to include the new code within the former code.
943:
944: The output is very simple: only an estimate of the intercept and of
945: the slope with 95% confident intervals.
946:
947: Current limitations:
948: A) Even if you enter covariates, i.e. with the
949: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
950: B) There is no computation of Life Expectancy nor Life Table.
951:
952: Revision 1.97 2004/02/20 13:25:42 lievre
953: Version 0.96d. Population forecasting command line is (temporarily)
954: suppressed.
955:
956: Revision 1.96 2003/07/15 15:38:55 brouard
957: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
958: rewritten within the same printf. Workaround: many printfs.
959:
960: Revision 1.95 2003/07/08 07:54:34 brouard
961: * imach.c (Repository):
962: (Repository): Using imachwizard code to output a more meaningful covariance
963: matrix (cov(a12,c31) instead of numbers.
964:
965: Revision 1.94 2003/06/27 13:00:02 brouard
966: Just cleaning
967:
968: Revision 1.93 2003/06/25 16:33:55 brouard
969: (Module): On windows (cygwin) function asctime_r doesn't
970: exist so I changed back to asctime which exists.
971: (Module): Version 0.96b
972:
973: Revision 1.92 2003/06/25 16:30:45 brouard
974: (Module): On windows (cygwin) function asctime_r doesn't
975: exist so I changed back to asctime which exists.
976:
977: Revision 1.91 2003/06/25 15:30:29 brouard
978: * imach.c (Repository): Duplicated warning errors corrected.
979: (Repository): Elapsed time after each iteration is now output. It
980: helps to forecast when convergence will be reached. Elapsed time
981: is stamped in powell. We created a new html file for the graphs
982: concerning matrix of covariance. It has extension -cov.htm.
983:
984: Revision 1.90 2003/06/24 12:34:15 brouard
985: (Module): Some bugs corrected for windows. Also, when
986: mle=-1 a template is output in file "or"mypar.txt with the design
987: of the covariance matrix to be input.
988:
989: Revision 1.89 2003/06/24 12:30:52 brouard
990: (Module): Some bugs corrected for windows. Also, when
991: mle=-1 a template is output in file "or"mypar.txt with the design
992: of the covariance matrix to be input.
993:
994: Revision 1.88 2003/06/23 17:54:56 brouard
995: * 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.
996:
997: Revision 1.87 2003/06/18 12:26:01 brouard
998: Version 0.96
999:
1000: Revision 1.86 2003/06/17 20:04:08 brouard
1001: (Module): Change position of html and gnuplot routines and added
1002: routine fileappend.
1003:
1004: Revision 1.85 2003/06/17 13:12:43 brouard
1005: * imach.c (Repository): Check when date of death was earlier that
1006: current date of interview. It may happen when the death was just
1007: prior to the death. In this case, dh was negative and likelihood
1008: was wrong (infinity). We still send an "Error" but patch by
1009: assuming that the date of death was just one stepm after the
1010: interview.
1011: (Repository): Because some people have very long ID (first column)
1012: we changed int to long in num[] and we added a new lvector for
1013: memory allocation. But we also truncated to 8 characters (left
1014: truncation)
1015: (Repository): No more line truncation errors.
1016:
1017: Revision 1.84 2003/06/13 21:44:43 brouard
1018: * imach.c (Repository): Replace "freqsummary" at a correct
1019: place. It differs from routine "prevalence" which may be called
1020: many times. Probs is memory consuming and must be used with
1021: parcimony.
1022: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
1023:
1024: Revision 1.83 2003/06/10 13:39:11 lievre
1025: *** empty log message ***
1026:
1027: Revision 1.82 2003/06/05 15:57:20 brouard
1028: Add log in imach.c and fullversion number is now printed.
1029:
1030: */
1031: /*
1032: Interpolated Markov Chain
1033:
1034: Short summary of the programme:
1035:
1.227 brouard 1036: This program computes Healthy Life Expectancies or State-specific
1037: (if states aren't health statuses) Expectancies from
1038: cross-longitudinal data. Cross-longitudinal data consist in:
1039:
1040: -1- a first survey ("cross") where individuals from different ages
1041: are interviewed on their health status or degree of disability (in
1042: the case of a health survey which is our main interest)
1043:
1044: -2- at least a second wave of interviews ("longitudinal") which
1045: measure each change (if any) in individual health status. Health
1046: expectancies are computed from the time spent in each health state
1047: according to a model. More health states you consider, more time is
1048: necessary to reach the Maximum Likelihood of the parameters involved
1049: in the model. The simplest model is the multinomial logistic model
1050: where pij is the probability to be observed in state j at the second
1051: wave conditional to be observed in state i at the first
1052: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
1053: etc , where 'age' is age and 'sex' is a covariate. If you want to
1054: have a more complex model than "constant and age", you should modify
1055: the program where the markup *Covariates have to be included here
1056: again* invites you to do it. More covariates you add, slower the
1.126 brouard 1057: convergence.
1058:
1059: The advantage of this computer programme, compared to a simple
1060: multinomial logistic model, is clear when the delay between waves is not
1061: identical for each individual. Also, if a individual missed an
1062: intermediate interview, the information is lost, but taken into
1063: account using an interpolation or extrapolation.
1064:
1065: hPijx is the probability to be observed in state i at age x+h
1066: conditional to the observed state i at age x. The delay 'h' can be
1067: split into an exact number (nh*stepm) of unobserved intermediate
1068: states. This elementary transition (by month, quarter,
1069: semester or year) is modelled as a multinomial logistic. The hPx
1070: matrix is simply the matrix product of nh*stepm elementary matrices
1071: and the contribution of each individual to the likelihood is simply
1072: hPijx.
1073:
1074: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 1075: of the life expectancies. It also computes the period (stable) prevalence.
1076:
1077: Back prevalence and projections:
1.227 brouard 1078:
1079: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
1080: double agemaxpar, double ftolpl, int *ncvyearp, double
1081: dateprev1,double dateprev2, int firstpass, int lastpass, int
1082: mobilavproj)
1083:
1084: Computes the back prevalence limit for any combination of
1085: covariate values k at any age between ageminpar and agemaxpar and
1086: returns it in **bprlim. In the loops,
1087:
1088: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
1089: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
1090:
1091: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 1092: Computes for any combination of covariates k and any age between bage and fage
1093: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
1094: oldm=oldms;savm=savms;
1.227 brouard 1095:
1.267 brouard 1096: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 1097: Computes the transition matrix starting at age 'age' over
1098: 'nhstepm*hstepm*stepm' months (i.e. until
1099: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 1100: nhstepm*hstepm matrices.
1101:
1102: Returns p3mat[i][j][h] after calling
1103: p3mat[i][j][h]=matprod2(newm,
1104: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
1105: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
1106: oldm);
1.226 brouard 1107:
1108: Important routines
1109:
1110: - func (or funcone), computes logit (pij) distinguishing
1111: o fixed variables (single or product dummies or quantitative);
1112: o varying variables by:
1113: (1) wave (single, product dummies, quantitative),
1114: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
1115: % fixed dummy (treated) or quantitative (not done because time-consuming);
1116: % varying dummy (not done) or quantitative (not done);
1117: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
1118: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
1119: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
1.325 brouard 1120: o There are 2**cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
1.226 brouard 1121: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 1122:
1.226 brouard 1123:
1124:
1.324 brouard 1125: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
1126: Institut national d'études démographiques, Paris.
1.126 brouard 1127: This software have been partly granted by Euro-REVES, a concerted action
1128: from the European Union.
1129: It is copyrighted identically to a GNU software product, ie programme and
1130: software can be distributed freely for non commercial use. Latest version
1131: can be accessed at http://euroreves.ined.fr/imach .
1132:
1133: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
1134: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
1135:
1136: **********************************************************************/
1137: /*
1138: main
1139: read parameterfile
1140: read datafile
1141: concatwav
1142: freqsummary
1143: if (mle >= 1)
1144: mlikeli
1145: print results files
1146: if mle==1
1147: computes hessian
1148: read end of parameter file: agemin, agemax, bage, fage, estepm
1149: begin-prev-date,...
1150: open gnuplot file
1151: open html file
1.145 brouard 1152: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
1153: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
1154: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
1155: freexexit2 possible for memory heap.
1156:
1157: h Pij x | pij_nom ficrestpij
1158: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
1159: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
1160: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
1161:
1162: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
1163: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
1164: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
1165: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
1166: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
1167:
1.126 brouard 1168: forecasting if prevfcast==1 prevforecast call prevalence()
1169: health expectancies
1170: Variance-covariance of DFLE
1171: prevalence()
1172: movingaverage()
1173: varevsij()
1174: if popbased==1 varevsij(,popbased)
1175: total life expectancies
1176: Variance of period (stable) prevalence
1177: end
1178: */
1179:
1.187 brouard 1180: /* #define DEBUG */
1181: /* #define DEBUGBRENT */
1.203 brouard 1182: /* #define DEBUGLINMIN */
1183: /* #define DEBUGHESS */
1184: #define DEBUGHESSIJ
1.224 brouard 1185: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 1186: #define POWELL /* Instead of NLOPT */
1.224 brouard 1187: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 1188: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
1189: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.319 brouard 1190: /* #define FLATSUP *//* Suppresses directions where likelihood is flat */
1.126 brouard 1191:
1192: #include <math.h>
1193: #include <stdio.h>
1194: #include <stdlib.h>
1195: #include <string.h>
1.226 brouard 1196: #include <ctype.h>
1.159 brouard 1197:
1198: #ifdef _WIN32
1199: #include <io.h>
1.172 brouard 1200: #include <windows.h>
1201: #include <tchar.h>
1.159 brouard 1202: #else
1.126 brouard 1203: #include <unistd.h>
1.159 brouard 1204: #endif
1.126 brouard 1205:
1206: #include <limits.h>
1207: #include <sys/types.h>
1.171 brouard 1208:
1209: #if defined(__GNUC__)
1210: #include <sys/utsname.h> /* Doesn't work on Windows */
1211: #endif
1212:
1.126 brouard 1213: #include <sys/stat.h>
1214: #include <errno.h>
1.159 brouard 1215: /* extern int errno; */
1.126 brouard 1216:
1.157 brouard 1217: /* #ifdef LINUX */
1218: /* #include <time.h> */
1219: /* #include "timeval.h" */
1220: /* #else */
1221: /* #include <sys/time.h> */
1222: /* #endif */
1223:
1.126 brouard 1224: #include <time.h>
1225:
1.136 brouard 1226: #ifdef GSL
1227: #include <gsl/gsl_errno.h>
1228: #include <gsl/gsl_multimin.h>
1229: #endif
1230:
1.167 brouard 1231:
1.162 brouard 1232: #ifdef NLOPT
1233: #include <nlopt.h>
1234: typedef struct {
1235: double (* function)(double [] );
1236: } myfunc_data ;
1237: #endif
1238:
1.126 brouard 1239: /* #include <libintl.h> */
1240: /* #define _(String) gettext (String) */
1241:
1.251 brouard 1242: #define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1243:
1244: #define GNUPLOTPROGRAM "gnuplot"
1245: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1.329 brouard 1246: #define FILENAMELENGTH 256
1.126 brouard 1247:
1248: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1249: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1250:
1.144 brouard 1251: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
1252: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1253:
1254: #define NINTERVMAX 8
1.144 brouard 1255: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1256: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.325 brouard 1257: #define NCOVMAX 30 /**< Maximum number of covariates used in the model, including generated covariates V1*V2 or V1*age */
1.197 brouard 1258: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1259: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1260: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1261: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1262: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1263: /* #define AGESUP 130 */
1.288 brouard 1264: /* #define AGESUP 150 */
1265: #define AGESUP 200
1.268 brouard 1266: #define AGEINF 0
1.218 brouard 1267: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1268: #define AGEBASE 40
1.194 brouard 1269: #define AGEOVERFLOW 1.e20
1.164 brouard 1270: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1271: #ifdef _WIN32
1272: #define DIRSEPARATOR '\\'
1273: #define CHARSEPARATOR "\\"
1274: #define ODIRSEPARATOR '/'
1275: #else
1.126 brouard 1276: #define DIRSEPARATOR '/'
1277: #define CHARSEPARATOR "/"
1278: #define ODIRSEPARATOR '\\'
1279: #endif
1280:
1.334 ! brouard 1281: /* $Id: imach.c,v 1.333 2022/08/21 09:10:30 brouard Exp $ */
1.126 brouard 1282: /* $State: Exp $ */
1.196 brouard 1283: #include "version.h"
1284: char version[]=__IMACH_VERSION__;
1.332 brouard 1285: char copyright[]="August 2022,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 2000-2022";
1.334 ! brouard 1286: char fullversion[]="$Revision: 1.333 $ $Date: 2022/08/21 09:10:30 $";
1.126 brouard 1287: char strstart[80];
1288: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1289: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.187 brouard 1290: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.330 brouard 1291: /* Number of covariates model (1)=V2+V1+ V3*age+V2*V4 */
1292: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
1293: int cptcovn=0; /**< cptcovn decodemodel: number of covariates k of the models excluding age*products =6 and age*age */
1294: int cptcovt=0; /**< cptcovt: total number of covariates of the model (2) nbocc(+)+1 = 8 excepting constant and age and age*age */
1295: int cptcovs=0; /**< cptcovs number of simple covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
1.225 brouard 1296: int cptcovsnq=0; /**< cptcovsnq number of simple covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1297: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1298: int cptcovprodnoage=0; /**< Number of covariate products without age */
1.334 ! brouard 1299: int cptcoveff=0; /* Total number of single dummy covariates to vary for printing results (2**cptcoveff combinations of dummies)(computed in tricode as cptcov) */
1.233 brouard 1300: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1301: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.232 brouard 1302: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 1303: int nsd=0; /**< Total number of single dummy variables (output) */
1304: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1305: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1306: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1307: int ntveff=0; /**< ntveff number of effective time varying variables */
1308: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1309: int cptcov=0; /* Working variable */
1.334 ! brouard 1310: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs+1 declared globally ;*/
1.290 brouard 1311: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1312: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.302 brouard 1313: int npar=NPARMAX; /* Number of parameters (nlstate+ndeath-1)*nlstate*ncovmodel; */
1.126 brouard 1314: int nlstate=2; /* Number of live states */
1315: int ndeath=1; /* Number of dead states */
1.130 brouard 1316: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.223 brouard 1317: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable */
1.126 brouard 1318: int popbased=0;
1319:
1320: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1321: int maxwav=0; /* Maxim number of waves */
1322: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1323: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1324: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1325: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1326: int mle=1, weightopt=0;
1.126 brouard 1327: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1328: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1329: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1330: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1331: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1332: int selected(int kvar); /* Is covariate kvar selected for printing results */
1333:
1.130 brouard 1334: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1335: double **matprod2(); /* test */
1.126 brouard 1336: double **oldm, **newm, **savm; /* Working pointers to matrices */
1337: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1338: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1339:
1.136 brouard 1340: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1341: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1342: FILE *ficlog, *ficrespow;
1.130 brouard 1343: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1344: double fretone; /* Only one call to likelihood */
1.130 brouard 1345: long ipmx=0; /* Number of contributions */
1.126 brouard 1346: double sw; /* Sum of weights */
1347: char filerespow[FILENAMELENGTH];
1348: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1349: FILE *ficresilk;
1350: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1351: FILE *ficresprobmorprev;
1352: FILE *fichtm, *fichtmcov; /* Html File */
1353: FILE *ficreseij;
1354: char filerese[FILENAMELENGTH];
1355: FILE *ficresstdeij;
1356: char fileresstde[FILENAMELENGTH];
1357: FILE *ficrescveij;
1358: char filerescve[FILENAMELENGTH];
1359: FILE *ficresvij;
1360: char fileresv[FILENAMELENGTH];
1.269 brouard 1361:
1.126 brouard 1362: char title[MAXLINE];
1.234 brouard 1363: char model[MAXLINE]; /**< The model line */
1.217 brouard 1364: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1365: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1366: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1367: char command[FILENAMELENGTH];
1368: int outcmd=0;
1369:
1.217 brouard 1370: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1371: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1372: char filelog[FILENAMELENGTH]; /* Log file */
1373: char filerest[FILENAMELENGTH];
1374: char fileregp[FILENAMELENGTH];
1375: char popfile[FILENAMELENGTH];
1376:
1377: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1378:
1.157 brouard 1379: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1380: /* struct timezone tzp; */
1381: /* extern int gettimeofday(); */
1382: struct tm tml, *gmtime(), *localtime();
1383:
1384: extern time_t time();
1385:
1386: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1387: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1388: struct tm tm;
1389:
1.126 brouard 1390: char strcurr[80], strfor[80];
1391:
1392: char *endptr;
1393: long lval;
1394: double dval;
1395:
1396: #define NR_END 1
1397: #define FREE_ARG char*
1398: #define FTOL 1.0e-10
1399:
1400: #define NRANSI
1.240 brouard 1401: #define ITMAX 200
1402: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1403:
1404: #define TOL 2.0e-4
1405:
1406: #define CGOLD 0.3819660
1407: #define ZEPS 1.0e-10
1408: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1409:
1410: #define GOLD 1.618034
1411: #define GLIMIT 100.0
1412: #define TINY 1.0e-20
1413:
1414: static double maxarg1,maxarg2;
1415: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1416: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1417:
1418: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1419: #define rint(a) floor(a+0.5)
1.166 brouard 1420: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1421: #define mytinydouble 1.0e-16
1.166 brouard 1422: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1423: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1424: /* static double dsqrarg; */
1425: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1426: static double sqrarg;
1427: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1428: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1429: int agegomp= AGEGOMP;
1430:
1431: int imx;
1432: int stepm=1;
1433: /* Stepm, step in month: minimum step interpolation*/
1434:
1435: int estepm;
1436: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1437:
1438: int m,nb;
1439: long *num;
1.197 brouard 1440: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1441: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1442: covariate for which somebody answered excluding
1443: undefined. Usually 2: 0 and 1. */
1444: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1445: covariate for which somebody answered including
1446: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1447: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1448: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1449: double ***mobaverage, ***mobaverages; /* New global variable */
1.332 brouard 1450: 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 1451: double *ageexmed,*agecens;
1452: double dateintmean=0;
1.296 brouard 1453: double anprojd, mprojd, jprojd; /* For eventual projections */
1454: double anprojf, mprojf, jprojf;
1.126 brouard 1455:
1.296 brouard 1456: double anbackd, mbackd, jbackd; /* For eventual backprojections */
1457: double anbackf, mbackf, jbackf;
1458: double jintmean,mintmean,aintmean;
1.126 brouard 1459: double *weight;
1460: int **s; /* Status */
1.141 brouard 1461: double *agedc;
1.145 brouard 1462: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1463: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1464: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1465: double **coqvar; /* Fixed quantitative covariate nqv */
1466: double ***cotvar; /* Time varying covariate ntv */
1.225 brouard 1467: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1468: double idx;
1469: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.319 brouard 1470: /* Some documentation */
1471: /* Design original data
1472: * V1 V2 V3 V4 V5 V6 V7 V8 Weight ddb ddth d1st s1 V9 V10 V11 V12 s2 V9 V10 V11 V12
1473: * < ncovcol=6 > nqv=2 (V7 V8) dv dv dv qtv dv dv dvv qtv
1474: * ntv=3 nqtv=1
1.330 brouard 1475: * cptcovn number of covariates (not including constant and age or age*age) = number of plus sign + 1 = 10+1=11
1.319 brouard 1476: * For time varying covariate, quanti or dummies
1477: * cotqvar[wav][iv(1 to nqtv)][i]= [1][12][i]=(V12) quanti
1478: * cotvar[wav][ntv+iv][i]= [3+(1 to nqtv)][i]=(V12) quanti
1479: * cotvar[wav][iv(1 to ntv)][i]= [1][1][i]=(V9) dummies at wav 1
1480: * cotvar[wav][iv(1 to ntv)][i]= [1][2][i]=(V10) dummies at wav 1
1.332 brouard 1481: * covar[Vk,i], value of the Vkth fixed covariate dummy or quanti for individual i:
1.319 brouard 1482: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
1483: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 + V9 + V9*age + V10
1484: * k= 1 2 3 4 5 6 7 8 9 10 11
1485: */
1486: /* According to the model, more columns can be added to covar by the product of covariates */
1.318 brouard 1487: /* 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
1488: # States 1=Coresidence, 2 Living alone, 3 Institution
1489: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1490: */
1.319 brouard 1491: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1492: /* k 1 2 3 4 5 6 7 8 9 */
1493: /*Typevar[k]= 0 0 0 2 1 0 2 1 0 *//*0 for simple covariate (dummy, quantitative,*/
1494: /* fixed or varying), 1 for age product, 2 for*/
1495: /* product */
1496: /*Dummy[k]= 1 0 0 1 3 1 1 2 0 *//*Dummy[k] 0=dummy (0 1), 1 quantitative */
1497: /*(single or product without age), 2 dummy*/
1498: /* with age product, 3 quant with age product*/
1499: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1500: /* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */
1.330 brouard 1501: /*TnsdVar[Tvar] 1 2 3 */
1.319 brouard 1502: /*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1503: /*TvarsDind[k] 2 3 9 */ /* position K of single dummy cova */
1504: /* nsq 1 2 */ /* Counting single quantit tv */
1505: /* TvarsQ[k] 5 2 */ /* Number of single quantitative cova */
1506: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1507: /* Tprod[i]=k 1 2 */ /* Position in model of the ith prod without age */
1508: /* cptcovage 1 2 */ /* Counting cov*age in the model equation */
1509: /* Tage[cptcovage]=k 5 8 */ /* Position in the model of ith cov*age */
1510: /* Tvard[1][1]@4={4,3,1,2} V4*V3 V1*V2 */ /* Position in model of the ith prod without age */
1.330 brouard 1511: /* 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 1512: /* 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 1513: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.234 brouard 1514: /* Type */
1515: /* V 1 2 3 4 5 */
1516: /* F F V V V */
1517: /* D Q D D Q */
1518: /* */
1519: int *TvarsD;
1.330 brouard 1520: int *TnsdVar;
1.234 brouard 1521: int *TvarsDind;
1522: int *TvarsQ;
1523: int *TvarsQind;
1524:
1.318 brouard 1525: #define MAXRESULTLINESPONE 10+1
1.235 brouard 1526: int nresult=0;
1.258 brouard 1527: int parameterline=0; /* # of the parameter (type) line */
1.334 ! brouard 1528: int TKresult[MAXRESULTLINESPONE]; /* TKresult[nres]=k for each resultline nres give the corresponding combination of dummies */
! 1529: int resultmodel[MAXRESULTLINESPONE][NCOVMAX];/* resultmodel[k1]=k3: k1th position in the model corresponds to the k3 position in the resultline */
! 1530: int modelresult[MAXRESULTLINESPONE][NCOVMAX];/* modelresult[k3]=k1: k1th position in the model corresponds to the k3 position in the resultline */
! 1531: int Tresult[MAXRESULTLINESPONE][NCOVMAX];/* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1532: int Tinvresult[MAXRESULTLINESPONE][NCOVMAX];/* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1533: double TinvDoQresult[MAXRESULTLINESPONE][NCOVMAX];/* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.334 ! brouard 1534: int Tvresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1535: double Tqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.318 brouard 1536: double Tqinvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
1.332 brouard 1537: int Tvqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.318 brouard 1538:
1539: /* 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
1540: # States 1=Coresidence, 2 Living alone, 3 Institution
1541: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1542: */
1.234 brouard 1543: /* 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 1544: 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 */
1545: 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 */
1546: 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 */
1547: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1548: 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 */
1549: 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 1550: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1551: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1552: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1553: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1554: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1555: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1556: 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 */
1557: 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 */
1558:
1.230 brouard 1559: int *Tvarsel; /**< Selected covariates for output */
1560: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1561: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1562: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1563: 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 1564: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1565: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1566: int *Tage;
1.227 brouard 1567: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1568: 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 1569: 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*/
1570: 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 1571: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1572: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1573: int **Tvard;
1.330 brouard 1574: int **Tvardk;
1.227 brouard 1575: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1576: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1577: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1578: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1579: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1580: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1581: double *lsurv, *lpop, *tpop;
1582:
1.231 brouard 1583: #define FD 1; /* Fixed dummy covariate */
1584: #define FQ 2; /* Fixed quantitative covariate */
1585: #define FP 3; /* Fixed product covariate */
1586: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1587: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1588: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1589: #define VD 10; /* Varying dummy covariate */
1590: #define VQ 11; /* Varying quantitative covariate */
1591: #define VP 12; /* Varying product covariate */
1592: #define VPDD 13; /* Varying product dummy*dummy covariate */
1593: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1594: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1595: #define APFD 16; /* Age product * fixed dummy covariate */
1596: #define APFQ 17; /* Age product * fixed quantitative covariate */
1597: #define APVD 18; /* Age product * varying dummy covariate */
1598: #define APVQ 19; /* Age product * varying quantitative covariate */
1599:
1600: #define FTYPE 1; /* Fixed covariate */
1601: #define VTYPE 2; /* Varying covariate (loop in wave) */
1602: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1603:
1604: struct kmodel{
1605: int maintype; /* main type */
1606: int subtype; /* subtype */
1607: };
1608: struct kmodel modell[NCOVMAX];
1609:
1.143 brouard 1610: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1611: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1612:
1613: /**************** split *************************/
1614: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1615: {
1616: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1617: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1618: */
1619: char *ss; /* pointer */
1.186 brouard 1620: int l1=0, l2=0; /* length counters */
1.126 brouard 1621:
1622: l1 = strlen(path ); /* length of path */
1623: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1624: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1625: if ( ss == NULL ) { /* no directory, so determine current directory */
1626: strcpy( name, path ); /* we got the fullname name because no directory */
1627: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1628: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1629: /* get current working directory */
1630: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1631: #ifdef WIN32
1632: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1633: #else
1634: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1635: #endif
1.126 brouard 1636: return( GLOCK_ERROR_GETCWD );
1637: }
1638: /* got dirc from getcwd*/
1639: printf(" DIRC = %s \n",dirc);
1.205 brouard 1640: } else { /* strip directory from path */
1.126 brouard 1641: ss++; /* after this, the filename */
1642: l2 = strlen( ss ); /* length of filename */
1643: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1644: strcpy( name, ss ); /* save file name */
1645: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1646: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1647: printf(" DIRC2 = %s \n",dirc);
1648: }
1649: /* We add a separator at the end of dirc if not exists */
1650: l1 = strlen( dirc ); /* length of directory */
1651: if( dirc[l1-1] != DIRSEPARATOR ){
1652: dirc[l1] = DIRSEPARATOR;
1653: dirc[l1+1] = 0;
1654: printf(" DIRC3 = %s \n",dirc);
1655: }
1656: ss = strrchr( name, '.' ); /* find last / */
1657: if (ss >0){
1658: ss++;
1659: strcpy(ext,ss); /* save extension */
1660: l1= strlen( name);
1661: l2= strlen(ss)+1;
1662: strncpy( finame, name, l1-l2);
1663: finame[l1-l2]= 0;
1664: }
1665:
1666: return( 0 ); /* we're done */
1667: }
1668:
1669:
1670: /******************************************/
1671:
1672: void replace_back_to_slash(char *s, char*t)
1673: {
1674: int i;
1675: int lg=0;
1676: i=0;
1677: lg=strlen(t);
1678: for(i=0; i<= lg; i++) {
1679: (s[i] = t[i]);
1680: if (t[i]== '\\') s[i]='/';
1681: }
1682: }
1683:
1.132 brouard 1684: char *trimbb(char *out, char *in)
1.137 brouard 1685: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1686: char *s;
1687: s=out;
1688: while (*in != '\0'){
1.137 brouard 1689: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1690: in++;
1691: }
1692: *out++ = *in++;
1693: }
1694: *out='\0';
1695: return s;
1696: }
1697:
1.187 brouard 1698: /* char *substrchaine(char *out, char *in, char *chain) */
1699: /* { */
1700: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1701: /* char *s, *t; */
1702: /* t=in;s=out; */
1703: /* while ((*in != *chain) && (*in != '\0')){ */
1704: /* *out++ = *in++; */
1705: /* } */
1706:
1707: /* /\* *in matches *chain *\/ */
1708: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1709: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1710: /* } */
1711: /* in--; chain--; */
1712: /* while ( (*in != '\0')){ */
1713: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1714: /* *out++ = *in++; */
1715: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1716: /* } */
1717: /* *out='\0'; */
1718: /* out=s; */
1719: /* return out; */
1720: /* } */
1721: char *substrchaine(char *out, char *in, char *chain)
1722: {
1723: /* Substract chain 'chain' from 'in', return and output 'out' */
1724: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1725:
1726: char *strloc;
1727:
1728: strcpy (out, in);
1729: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1730: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1731: if(strloc != NULL){
1732: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1733: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1734: /* strcpy (strloc, strloc +strlen(chain));*/
1735: }
1736: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1737: return out;
1738: }
1739:
1740:
1.145 brouard 1741: char *cutl(char *blocc, char *alocc, char *in, char occ)
1742: {
1.187 brouard 1743: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1744: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.310 brouard 1745: gives alocc="abcdef" and blocc="ghi2j".
1.145 brouard 1746: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1747: */
1.160 brouard 1748: char *s, *t;
1.145 brouard 1749: t=in;s=in;
1750: while ((*in != occ) && (*in != '\0')){
1751: *alocc++ = *in++;
1752: }
1753: if( *in == occ){
1754: *(alocc)='\0';
1755: s=++in;
1756: }
1757:
1758: if (s == t) {/* occ not found */
1759: *(alocc-(in-s))='\0';
1760: in=s;
1761: }
1762: while ( *in != '\0'){
1763: *blocc++ = *in++;
1764: }
1765:
1766: *blocc='\0';
1767: return t;
1768: }
1.137 brouard 1769: char *cutv(char *blocc, char *alocc, char *in, char occ)
1770: {
1.187 brouard 1771: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1772: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1773: gives blocc="abcdef2ghi" and alocc="j".
1774: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1775: */
1776: char *s, *t;
1777: t=in;s=in;
1778: while (*in != '\0'){
1779: while( *in == occ){
1780: *blocc++ = *in++;
1781: s=in;
1782: }
1783: *blocc++ = *in++;
1784: }
1785: if (s == t) /* occ not found */
1786: *(blocc-(in-s))='\0';
1787: else
1788: *(blocc-(in-s)-1)='\0';
1789: in=s;
1790: while ( *in != '\0'){
1791: *alocc++ = *in++;
1792: }
1793:
1794: *alocc='\0';
1795: return s;
1796: }
1797:
1.126 brouard 1798: int nbocc(char *s, char occ)
1799: {
1800: int i,j=0;
1801: int lg=20;
1802: i=0;
1803: lg=strlen(s);
1804: for(i=0; i<= lg; i++) {
1.234 brouard 1805: if (s[i] == occ ) j++;
1.126 brouard 1806: }
1807: return j;
1808: }
1809:
1.137 brouard 1810: /* void cutv(char *u,char *v, char*t, char occ) */
1811: /* { */
1812: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1813: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1814: /* gives u="abcdef2ghi" and v="j" *\/ */
1815: /* int i,lg,j,p=0; */
1816: /* i=0; */
1817: /* lg=strlen(t); */
1818: /* for(j=0; j<=lg-1; j++) { */
1819: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1820: /* } */
1.126 brouard 1821:
1.137 brouard 1822: /* for(j=0; j<p; j++) { */
1823: /* (u[j] = t[j]); */
1824: /* } */
1825: /* u[p]='\0'; */
1.126 brouard 1826:
1.137 brouard 1827: /* for(j=0; j<= lg; j++) { */
1828: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1829: /* } */
1830: /* } */
1.126 brouard 1831:
1.160 brouard 1832: #ifdef _WIN32
1833: char * strsep(char **pp, const char *delim)
1834: {
1835: char *p, *q;
1836:
1837: if ((p = *pp) == NULL)
1838: return 0;
1839: if ((q = strpbrk (p, delim)) != NULL)
1840: {
1841: *pp = q + 1;
1842: *q = '\0';
1843: }
1844: else
1845: *pp = 0;
1846: return p;
1847: }
1848: #endif
1849:
1.126 brouard 1850: /********************** nrerror ********************/
1851:
1852: void nrerror(char error_text[])
1853: {
1854: fprintf(stderr,"ERREUR ...\n");
1855: fprintf(stderr,"%s\n",error_text);
1856: exit(EXIT_FAILURE);
1857: }
1858: /*********************** vector *******************/
1859: double *vector(int nl, int nh)
1860: {
1861: double *v;
1862: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1863: if (!v) nrerror("allocation failure in vector");
1864: return v-nl+NR_END;
1865: }
1866:
1867: /************************ free vector ******************/
1868: void free_vector(double*v, int nl, int nh)
1869: {
1870: free((FREE_ARG)(v+nl-NR_END));
1871: }
1872:
1873: /************************ivector *******************************/
1874: int *ivector(long nl,long nh)
1875: {
1876: int *v;
1877: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1878: if (!v) nrerror("allocation failure in ivector");
1879: return v-nl+NR_END;
1880: }
1881:
1882: /******************free ivector **************************/
1883: void free_ivector(int *v, long nl, long nh)
1884: {
1885: free((FREE_ARG)(v+nl-NR_END));
1886: }
1887:
1888: /************************lvector *******************************/
1889: long *lvector(long nl,long nh)
1890: {
1891: long *v;
1892: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1893: if (!v) nrerror("allocation failure in ivector");
1894: return v-nl+NR_END;
1895: }
1896:
1897: /******************free lvector **************************/
1898: void free_lvector(long *v, long nl, long nh)
1899: {
1900: free((FREE_ARG)(v+nl-NR_END));
1901: }
1902:
1903: /******************* imatrix *******************************/
1904: int **imatrix(long nrl, long nrh, long ncl, long nch)
1905: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1906: {
1907: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1908: int **m;
1909:
1910: /* allocate pointers to rows */
1911: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1912: if (!m) nrerror("allocation failure 1 in matrix()");
1913: m += NR_END;
1914: m -= nrl;
1915:
1916:
1917: /* allocate rows and set pointers to them */
1918: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
1919: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1920: m[nrl] += NR_END;
1921: m[nrl] -= ncl;
1922:
1923: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
1924:
1925: /* return pointer to array of pointers to rows */
1926: return m;
1927: }
1928:
1929: /****************** free_imatrix *************************/
1930: void free_imatrix(m,nrl,nrh,ncl,nch)
1931: int **m;
1932: long nch,ncl,nrh,nrl;
1933: /* free an int matrix allocated by imatrix() */
1934: {
1935: free((FREE_ARG) (m[nrl]+ncl-NR_END));
1936: free((FREE_ARG) (m+nrl-NR_END));
1937: }
1938:
1939: /******************* matrix *******************************/
1940: double **matrix(long nrl, long nrh, long ncl, long nch)
1941: {
1942: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
1943: double **m;
1944:
1945: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1946: if (!m) nrerror("allocation failure 1 in matrix()");
1947: m += NR_END;
1948: m -= nrl;
1949:
1950: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1951: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1952: m[nrl] += NR_END;
1953: m[nrl] -= ncl;
1954:
1955: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1956: return m;
1.145 brouard 1957: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
1958: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
1959: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 1960: */
1961: }
1962:
1963: /*************************free matrix ************************/
1964: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
1965: {
1966: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1967: free((FREE_ARG)(m+nrl-NR_END));
1968: }
1969:
1970: /******************* ma3x *******************************/
1971: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
1972: {
1973: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
1974: double ***m;
1975:
1976: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1977: if (!m) nrerror("allocation failure 1 in matrix()");
1978: m += NR_END;
1979: m -= nrl;
1980:
1981: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1982: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1983: m[nrl] += NR_END;
1984: m[nrl] -= ncl;
1985:
1986: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1987:
1988: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
1989: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
1990: m[nrl][ncl] += NR_END;
1991: m[nrl][ncl] -= nll;
1992: for (j=ncl+1; j<=nch; j++)
1993: m[nrl][j]=m[nrl][j-1]+nlay;
1994:
1995: for (i=nrl+1; i<=nrh; i++) {
1996: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
1997: for (j=ncl+1; j<=nch; j++)
1998: m[i][j]=m[i][j-1]+nlay;
1999: }
2000: return m;
2001: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
2002: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
2003: */
2004: }
2005:
2006: /*************************free ma3x ************************/
2007: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
2008: {
2009: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
2010: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2011: free((FREE_ARG)(m+nrl-NR_END));
2012: }
2013:
2014: /*************** function subdirf ***********/
2015: char *subdirf(char fileres[])
2016: {
2017: /* Caution optionfilefiname is hidden */
2018: strcpy(tmpout,optionfilefiname);
2019: strcat(tmpout,"/"); /* Add to the right */
2020: strcat(tmpout,fileres);
2021: return tmpout;
2022: }
2023:
2024: /*************** function subdirf2 ***********/
2025: char *subdirf2(char fileres[], char *preop)
2026: {
1.314 brouard 2027: /* Example subdirf2(optionfilefiname,"FB_") with optionfilefiname="texte", result="texte/FB_texte"
2028: Errors in subdirf, 2, 3 while printing tmpout is
1.315 brouard 2029: rewritten within the same printf. Workaround: many printfs */
1.126 brouard 2030: /* Caution optionfilefiname is hidden */
2031: strcpy(tmpout,optionfilefiname);
2032: strcat(tmpout,"/");
2033: strcat(tmpout,preop);
2034: strcat(tmpout,fileres);
2035: return tmpout;
2036: }
2037:
2038: /*************** function subdirf3 ***********/
2039: char *subdirf3(char fileres[], char *preop, char *preop2)
2040: {
2041:
2042: /* Caution optionfilefiname is hidden */
2043: strcpy(tmpout,optionfilefiname);
2044: strcat(tmpout,"/");
2045: strcat(tmpout,preop);
2046: strcat(tmpout,preop2);
2047: strcat(tmpout,fileres);
2048: return tmpout;
2049: }
1.213 brouard 2050:
2051: /*************** function subdirfext ***********/
2052: char *subdirfext(char fileres[], char *preop, char *postop)
2053: {
2054:
2055: strcpy(tmpout,preop);
2056: strcat(tmpout,fileres);
2057: strcat(tmpout,postop);
2058: return tmpout;
2059: }
1.126 brouard 2060:
1.213 brouard 2061: /*************** function subdirfext3 ***********/
2062: char *subdirfext3(char fileres[], char *preop, char *postop)
2063: {
2064:
2065: /* Caution optionfilefiname is hidden */
2066: strcpy(tmpout,optionfilefiname);
2067: strcat(tmpout,"/");
2068: strcat(tmpout,preop);
2069: strcat(tmpout,fileres);
2070: strcat(tmpout,postop);
2071: return tmpout;
2072: }
2073:
1.162 brouard 2074: char *asc_diff_time(long time_sec, char ascdiff[])
2075: {
2076: long sec_left, days, hours, minutes;
2077: days = (time_sec) / (60*60*24);
2078: sec_left = (time_sec) % (60*60*24);
2079: hours = (sec_left) / (60*60) ;
2080: sec_left = (sec_left) %(60*60);
2081: minutes = (sec_left) /60;
2082: sec_left = (sec_left) % (60);
2083: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
2084: return ascdiff;
2085: }
2086:
1.126 brouard 2087: /***************** f1dim *************************/
2088: extern int ncom;
2089: extern double *pcom,*xicom;
2090: extern double (*nrfunc)(double []);
2091:
2092: double f1dim(double x)
2093: {
2094: int j;
2095: double f;
2096: double *xt;
2097:
2098: xt=vector(1,ncom);
2099: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
2100: f=(*nrfunc)(xt);
2101: free_vector(xt,1,ncom);
2102: return f;
2103: }
2104:
2105: /*****************brent *************************/
2106: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 2107: {
2108: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
2109: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
2110: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
2111: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
2112: * returned function value.
2113: */
1.126 brouard 2114: int iter;
2115: double a,b,d,etemp;
1.159 brouard 2116: double fu=0,fv,fw,fx;
1.164 brouard 2117: double ftemp=0.;
1.126 brouard 2118: double p,q,r,tol1,tol2,u,v,w,x,xm;
2119: double e=0.0;
2120:
2121: a=(ax < cx ? ax : cx);
2122: b=(ax > cx ? ax : cx);
2123: x=w=v=bx;
2124: fw=fv=fx=(*f)(x);
2125: for (iter=1;iter<=ITMAX;iter++) {
2126: xm=0.5*(a+b);
2127: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
2128: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
2129: printf(".");fflush(stdout);
2130: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 2131: #ifdef DEBUGBRENT
1.126 brouard 2132: 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);
2133: 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);
2134: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
2135: #endif
2136: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
2137: *xmin=x;
2138: return fx;
2139: }
2140: ftemp=fu;
2141: if (fabs(e) > tol1) {
2142: r=(x-w)*(fx-fv);
2143: q=(x-v)*(fx-fw);
2144: p=(x-v)*q-(x-w)*r;
2145: q=2.0*(q-r);
2146: if (q > 0.0) p = -p;
2147: q=fabs(q);
2148: etemp=e;
2149: e=d;
2150: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 2151: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 2152: else {
1.224 brouard 2153: d=p/q;
2154: u=x+d;
2155: if (u-a < tol2 || b-u < tol2)
2156: d=SIGN(tol1,xm-x);
1.126 brouard 2157: }
2158: } else {
2159: d=CGOLD*(e=(x >= xm ? a-x : b-x));
2160: }
2161: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
2162: fu=(*f)(u);
2163: if (fu <= fx) {
2164: if (u >= x) a=x; else b=x;
2165: SHFT(v,w,x,u)
1.183 brouard 2166: SHFT(fv,fw,fx,fu)
2167: } else {
2168: if (u < x) a=u; else b=u;
2169: if (fu <= fw || w == x) {
1.224 brouard 2170: v=w;
2171: w=u;
2172: fv=fw;
2173: fw=fu;
1.183 brouard 2174: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 2175: v=u;
2176: fv=fu;
1.183 brouard 2177: }
2178: }
1.126 brouard 2179: }
2180: nrerror("Too many iterations in brent");
2181: *xmin=x;
2182: return fx;
2183: }
2184:
2185: /****************** mnbrak ***********************/
2186:
2187: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
2188: double (*func)(double))
1.183 brouard 2189: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
2190: the downhill direction (defined by the function as evaluated at the initial points) and returns
2191: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
2192: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
2193: */
1.126 brouard 2194: double ulim,u,r,q, dum;
2195: double fu;
1.187 brouard 2196:
2197: double scale=10.;
2198: int iterscale=0;
2199:
2200: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
2201: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
2202:
2203:
2204: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
2205: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
2206: /* *bx = *ax - (*ax - *bx)/scale; */
2207: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
2208: /* } */
2209:
1.126 brouard 2210: if (*fb > *fa) {
2211: SHFT(dum,*ax,*bx,dum)
1.183 brouard 2212: SHFT(dum,*fb,*fa,dum)
2213: }
1.126 brouard 2214: *cx=(*bx)+GOLD*(*bx-*ax);
2215: *fc=(*func)(*cx);
1.183 brouard 2216: #ifdef DEBUG
1.224 brouard 2217: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
2218: 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 2219: #endif
1.224 brouard 2220: 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 2221: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 2222: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 2223: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 2224: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
2225: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
2226: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 2227: fu=(*func)(u);
1.163 brouard 2228: #ifdef DEBUG
2229: /* f(x)=A(x-u)**2+f(u) */
2230: double A, fparabu;
2231: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2232: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 2233: 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);
2234: 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 2235: /* And thus,it can be that fu > *fc even if fparabu < *fc */
2236: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
2237: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
2238: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 2239: #endif
1.184 brouard 2240: #ifdef MNBRAKORIGINAL
1.183 brouard 2241: #else
1.191 brouard 2242: /* if (fu > *fc) { */
2243: /* #ifdef DEBUG */
2244: /* printf("mnbrak4 fu > fc \n"); */
2245: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
2246: /* #endif */
2247: /* /\* 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 *\\/ *\/ */
2248: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2249: /* dum=u; /\* Shifting c and u *\/ */
2250: /* u = *cx; */
2251: /* *cx = dum; */
2252: /* dum = fu; */
2253: /* fu = *fc; */
2254: /* *fc =dum; */
2255: /* } else { /\* end *\/ */
2256: /* #ifdef DEBUG */
2257: /* printf("mnbrak3 fu < fc \n"); */
2258: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2259: /* #endif */
2260: /* dum=u; /\* Shifting c and u *\/ */
2261: /* u = *cx; */
2262: /* *cx = dum; */
2263: /* dum = fu; */
2264: /* fu = *fc; */
2265: /* *fc =dum; */
2266: /* } */
1.224 brouard 2267: #ifdef DEBUGMNBRAK
2268: double A, fparabu;
2269: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2270: fparabu= *fa - A*(*ax-u)*(*ax-u);
2271: 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);
2272: 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 2273: #endif
1.191 brouard 2274: dum=u; /* Shifting c and u */
2275: u = *cx;
2276: *cx = dum;
2277: dum = fu;
2278: fu = *fc;
2279: *fc =dum;
1.183 brouard 2280: #endif
1.162 brouard 2281: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2282: #ifdef DEBUG
1.224 brouard 2283: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2284: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2285: #endif
1.126 brouard 2286: fu=(*func)(u);
2287: if (fu < *fc) {
1.183 brouard 2288: #ifdef DEBUG
1.224 brouard 2289: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2290: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2291: #endif
2292: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2293: SHFT(*fb,*fc,fu,(*func)(u))
2294: #ifdef DEBUG
2295: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2296: #endif
2297: }
1.162 brouard 2298: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2299: #ifdef DEBUG
1.224 brouard 2300: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2301: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2302: #endif
1.126 brouard 2303: u=ulim;
2304: fu=(*func)(u);
1.183 brouard 2305: } else { /* u could be left to b (if r > q parabola has a maximum) */
2306: #ifdef DEBUG
1.224 brouard 2307: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2308: 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 2309: #endif
1.126 brouard 2310: u=(*cx)+GOLD*(*cx-*bx);
2311: fu=(*func)(u);
1.224 brouard 2312: #ifdef DEBUG
2313: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2314: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2315: #endif
1.183 brouard 2316: } /* end tests */
1.126 brouard 2317: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2318: SHFT(*fa,*fb,*fc,fu)
2319: #ifdef DEBUG
1.224 brouard 2320: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2321: 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 2322: #endif
2323: } /* 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 2324: }
2325:
2326: /*************** linmin ************************/
1.162 brouard 2327: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2328: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2329: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2330: the value of func at the returned location p . This is actually all accomplished by calling the
2331: routines mnbrak and brent .*/
1.126 brouard 2332: int ncom;
2333: double *pcom,*xicom;
2334: double (*nrfunc)(double []);
2335:
1.224 brouard 2336: #ifdef LINMINORIGINAL
1.126 brouard 2337: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2338: #else
2339: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2340: #endif
1.126 brouard 2341: {
2342: double brent(double ax, double bx, double cx,
2343: double (*f)(double), double tol, double *xmin);
2344: double f1dim(double x);
2345: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2346: double *fc, double (*func)(double));
2347: int j;
2348: double xx,xmin,bx,ax;
2349: double fx,fb,fa;
1.187 brouard 2350:
1.203 brouard 2351: #ifdef LINMINORIGINAL
2352: #else
2353: double scale=10., axs, xxs; /* Scale added for infinity */
2354: #endif
2355:
1.126 brouard 2356: ncom=n;
2357: pcom=vector(1,n);
2358: xicom=vector(1,n);
2359: nrfunc=func;
2360: for (j=1;j<=n;j++) {
2361: pcom[j]=p[j];
1.202 brouard 2362: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2363: }
1.187 brouard 2364:
1.203 brouard 2365: #ifdef LINMINORIGINAL
2366: xx=1.;
2367: #else
2368: axs=0.0;
2369: xxs=1.;
2370: do{
2371: xx= xxs;
2372: #endif
1.187 brouard 2373: ax=0.;
2374: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2375: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2376: /* 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)) */
2377: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2378: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2379: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2380: /* 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 2381: #ifdef LINMINORIGINAL
2382: #else
2383: if (fx != fx){
1.224 brouard 2384: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2385: printf("|");
2386: fprintf(ficlog,"|");
1.203 brouard 2387: #ifdef DEBUGLINMIN
1.224 brouard 2388: 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 2389: #endif
2390: }
1.224 brouard 2391: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2392: #endif
2393:
1.191 brouard 2394: #ifdef DEBUGLINMIN
2395: 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 2396: 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 2397: #endif
1.224 brouard 2398: #ifdef LINMINORIGINAL
2399: #else
1.317 brouard 2400: if(fb == fx){ /* Flat function in the direction */
2401: xmin=xx;
1.224 brouard 2402: *flat=1;
1.317 brouard 2403: }else{
1.224 brouard 2404: *flat=0;
2405: #endif
2406: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2407: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2408: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2409: /* fmin = f(p[j] + xmin * xi[j]) */
2410: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2411: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2412: #ifdef DEBUG
1.224 brouard 2413: 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);
2414: 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);
2415: #endif
2416: #ifdef LINMINORIGINAL
2417: #else
2418: }
1.126 brouard 2419: #endif
1.191 brouard 2420: #ifdef DEBUGLINMIN
2421: printf("linmin end ");
1.202 brouard 2422: fprintf(ficlog,"linmin end ");
1.191 brouard 2423: #endif
1.126 brouard 2424: for (j=1;j<=n;j++) {
1.203 brouard 2425: #ifdef LINMINORIGINAL
2426: xi[j] *= xmin;
2427: #else
2428: #ifdef DEBUGLINMIN
2429: if(xxs <1.0)
2430: printf(" before xi[%d]=%12.8f", j,xi[j]);
2431: #endif
2432: 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) */
2433: #ifdef DEBUGLINMIN
2434: if(xxs <1.0)
2435: 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 );
2436: #endif
2437: #endif
1.187 brouard 2438: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2439: }
1.191 brouard 2440: #ifdef DEBUGLINMIN
1.203 brouard 2441: printf("\n");
1.191 brouard 2442: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2443: 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 2444: for (j=1;j<=n;j++) {
1.202 brouard 2445: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2446: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2447: if(j % ncovmodel == 0){
1.191 brouard 2448: printf("\n");
1.202 brouard 2449: fprintf(ficlog,"\n");
2450: }
1.191 brouard 2451: }
1.203 brouard 2452: #else
1.191 brouard 2453: #endif
1.126 brouard 2454: free_vector(xicom,1,n);
2455: free_vector(pcom,1,n);
2456: }
2457:
2458:
2459: /*************** powell ************************/
1.162 brouard 2460: /*
1.317 brouard 2461: Minimization of a function func of n variables. Input consists in an initial starting point
2462: p[1..n] ; an initial matrix xi[1..n][1..n] whose columns contain the initial set of di-
2463: rections (usually the n unit vectors); and ftol, the fractional tolerance in the function value
2464: such that failure to decrease by more than this amount in one iteration signals doneness. On
1.162 brouard 2465: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2466: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2467: */
1.224 brouard 2468: #ifdef LINMINORIGINAL
2469: #else
2470: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2471: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2472: #endif
1.126 brouard 2473: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2474: double (*func)(double []))
2475: {
1.224 brouard 2476: #ifdef LINMINORIGINAL
2477: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2478: double (*func)(double []));
1.224 brouard 2479: #else
1.241 brouard 2480: void linmin(double p[], double xi[], int n, double *fret,
2481: double (*func)(double []),int *flat);
1.224 brouard 2482: #endif
1.239 brouard 2483: int i,ibig,j,jk,k;
1.126 brouard 2484: double del,t,*pt,*ptt,*xit;
1.181 brouard 2485: double directest;
1.126 brouard 2486: double fp,fptt;
2487: double *xits;
2488: int niterf, itmp;
2489:
2490: pt=vector(1,n);
2491: ptt=vector(1,n);
2492: xit=vector(1,n);
2493: xits=vector(1,n);
2494: *fret=(*func)(p);
2495: for (j=1;j<=n;j++) pt[j]=p[j];
1.202 brouard 2496: rcurr_time = time(NULL);
1.126 brouard 2497: for (*iter=1;;++(*iter)) {
2498: ibig=0;
2499: del=0.0;
1.157 brouard 2500: rlast_time=rcurr_time;
2501: /* (void) gettimeofday(&curr_time,&tzp); */
2502: rcurr_time = time(NULL);
2503: curr_time = *localtime(&rcurr_time);
1.324 brouard 2504: 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);
2505: 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);
1.157 brouard 2506: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.324 brouard 2507: fp=(*fret); /* From former iteration or initial value */
1.192 brouard 2508: for (i=1;i<=n;i++) {
1.126 brouard 2509: fprintf(ficrespow," %.12lf", p[i]);
2510: }
1.239 brouard 2511: fprintf(ficrespow,"\n");fflush(ficrespow);
2512: printf("\n#model= 1 + age ");
2513: fprintf(ficlog,"\n#model= 1 + age ");
2514: if(nagesqr==1){
1.241 brouard 2515: printf(" + age*age ");
2516: fprintf(ficlog," + age*age ");
1.239 brouard 2517: }
2518: for(j=1;j <=ncovmodel-2;j++){
2519: if(Typevar[j]==0) {
2520: printf(" + V%d ",Tvar[j]);
2521: fprintf(ficlog," + V%d ",Tvar[j]);
2522: }else if(Typevar[j]==1) {
2523: printf(" + V%d*age ",Tvar[j]);
2524: fprintf(ficlog," + V%d*age ",Tvar[j]);
2525: }else if(Typevar[j]==2) {
2526: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2527: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2528: }
2529: }
1.126 brouard 2530: printf("\n");
1.239 brouard 2531: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2532: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2533: fprintf(ficlog,"\n");
1.239 brouard 2534: for(i=1,jk=1; i <=nlstate; i++){
2535: for(k=1; k <=(nlstate+ndeath); k++){
2536: if (k != i) {
2537: printf("%d%d ",i,k);
2538: fprintf(ficlog,"%d%d ",i,k);
2539: for(j=1; j <=ncovmodel; j++){
2540: printf("%12.7f ",p[jk]);
2541: fprintf(ficlog,"%12.7f ",p[jk]);
2542: jk++;
2543: }
2544: printf("\n");
2545: fprintf(ficlog,"\n");
2546: }
2547: }
2548: }
1.241 brouard 2549: if(*iter <=3 && *iter >1){
1.157 brouard 2550: tml = *localtime(&rcurr_time);
2551: strcpy(strcurr,asctime(&tml));
2552: rforecast_time=rcurr_time;
1.126 brouard 2553: itmp = strlen(strcurr);
2554: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2555: strcurr[itmp-1]='\0';
1.162 brouard 2556: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2557: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2558: for(niterf=10;niterf<=30;niterf+=10){
1.241 brouard 2559: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2560: forecast_time = *localtime(&rforecast_time);
2561: strcpy(strfor,asctime(&forecast_time));
2562: itmp = strlen(strfor);
2563: if(strfor[itmp-1]=='\n')
2564: strfor[itmp-1]='\0';
2565: printf(" - if your program needs %d iterations to converge, convergence will be \n reached in %s i.e.\n on %s (current time is %s);\n",niterf, asc_diff_time(rforecast_time-rcurr_time,tmpout),strfor,strcurr);
2566: fprintf(ficlog," - if your program needs %d iterations to converge, convergence will be \n reached in %s i.e.\n on %s (current time is %s);\n",niterf, asc_diff_time(rforecast_time-rcurr_time,tmpout),strfor,strcurr);
1.126 brouard 2567: }
2568: }
1.187 brouard 2569: for (i=1;i<=n;i++) { /* For each direction i */
2570: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2571: fptt=(*fret);
2572: #ifdef DEBUG
1.203 brouard 2573: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2574: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2575: #endif
1.203 brouard 2576: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2577: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2578: #ifdef LINMINORIGINAL
1.188 brouard 2579: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2580: #else
2581: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2582: flatdir[i]=flat; /* Function is vanishing in that direction i */
2583: #endif
2584: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2585: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2586: /* because that direction will be replaced unless the gain del is small */
2587: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2588: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2589: /* with the new direction. */
2590: del=fabs(fptt-(*fret));
2591: ibig=i;
1.126 brouard 2592: }
2593: #ifdef DEBUG
2594: printf("%d %.12e",i,(*fret));
2595: fprintf(ficlog,"%d %.12e",i,(*fret));
2596: for (j=1;j<=n;j++) {
1.224 brouard 2597: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2598: printf(" x(%d)=%.12e",j,xit[j]);
2599: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2600: }
2601: for(j=1;j<=n;j++) {
1.225 brouard 2602: printf(" p(%d)=%.12e",j,p[j]);
2603: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2604: }
2605: printf("\n");
2606: fprintf(ficlog,"\n");
2607: #endif
1.187 brouard 2608: } /* end loop on each direction i */
2609: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2610: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2611: /* New value of last point Pn is not computed, P(n-1) */
1.319 brouard 2612: for(j=1;j<=n;j++) {
2613: if(flatdir[j] >0){
2614: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2615: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
1.302 brouard 2616: }
1.319 brouard 2617: /* printf("\n"); */
2618: /* fprintf(ficlog,"\n"); */
2619: }
1.243 brouard 2620: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2621: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2622: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2623: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2624: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2625: /* decreased of more than 3.84 */
2626: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2627: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2628: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2629:
1.188 brouard 2630: /* Starting the program with initial values given by a former maximization will simply change */
2631: /* the scales of the directions and the directions, because the are reset to canonical directions */
2632: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2633: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2634: #ifdef DEBUG
2635: int k[2],l;
2636: k[0]=1;
2637: k[1]=-1;
2638: printf("Max: %.12e",(*func)(p));
2639: fprintf(ficlog,"Max: %.12e",(*func)(p));
2640: for (j=1;j<=n;j++) {
2641: printf(" %.12e",p[j]);
2642: fprintf(ficlog," %.12e",p[j]);
2643: }
2644: printf("\n");
2645: fprintf(ficlog,"\n");
2646: for(l=0;l<=1;l++) {
2647: for (j=1;j<=n;j++) {
2648: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2649: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2650: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2651: }
2652: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2653: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2654: }
2655: #endif
2656:
2657: free_vector(xit,1,n);
2658: free_vector(xits,1,n);
2659: free_vector(ptt,1,n);
2660: free_vector(pt,1,n);
2661: return;
1.192 brouard 2662: } /* enough precision */
1.240 brouard 2663: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2664: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2665: ptt[j]=2.0*p[j]-pt[j];
2666: xit[j]=p[j]-pt[j];
2667: pt[j]=p[j];
2668: }
1.181 brouard 2669: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2670: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2671: if (*iter <=4) {
1.225 brouard 2672: #else
2673: #endif
1.224 brouard 2674: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2675: #else
1.161 brouard 2676: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2677: #endif
1.162 brouard 2678: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2679: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2680: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2681: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2682: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2683: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2684: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2685: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2686: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2687: /* Even if f3 <f1, directest can be negative and t >0 */
2688: /* mu² and del² are equal when f3=f1 */
2689: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2690: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2691: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2692: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2693: #ifdef NRCORIGINAL
2694: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2695: #else
2696: 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 2697: t= t- del*SQR(fp-fptt);
1.183 brouard 2698: #endif
1.202 brouard 2699: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2700: #ifdef DEBUG
1.181 brouard 2701: 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);
2702: 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 2703: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2704: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2705: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2706: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2707: 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);
2708: 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);
2709: #endif
1.183 brouard 2710: #ifdef POWELLORIGINAL
2711: if (t < 0.0) { /* Then we use it for new direction */
2712: #else
1.182 brouard 2713: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2714: 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 2715: 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 2716: 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 2717: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2718: }
1.181 brouard 2719: if (directest < 0.0) { /* Then we use it for new direction */
2720: #endif
1.191 brouard 2721: #ifdef DEBUGLINMIN
1.234 brouard 2722: printf("Before linmin in direction P%d-P0\n",n);
2723: for (j=1;j<=n;j++) {
2724: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2725: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2726: if(j % ncovmodel == 0){
2727: printf("\n");
2728: fprintf(ficlog,"\n");
2729: }
2730: }
1.224 brouard 2731: #endif
2732: #ifdef LINMINORIGINAL
1.234 brouard 2733: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2734: #else
1.234 brouard 2735: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2736: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2737: #endif
1.234 brouard 2738:
1.191 brouard 2739: #ifdef DEBUGLINMIN
1.234 brouard 2740: for (j=1;j<=n;j++) {
2741: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2742: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2743: if(j % ncovmodel == 0){
2744: printf("\n");
2745: fprintf(ficlog,"\n");
2746: }
2747: }
1.224 brouard 2748: #endif
1.234 brouard 2749: for (j=1;j<=n;j++) {
2750: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2751: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2752: }
1.224 brouard 2753: #ifdef LINMINORIGINAL
2754: #else
1.234 brouard 2755: for (j=1, flatd=0;j<=n;j++) {
2756: if(flatdir[j]>0)
2757: flatd++;
2758: }
2759: if(flatd >0){
1.255 brouard 2760: printf("%d flat directions: ",flatd);
2761: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2762: for (j=1;j<=n;j++) {
2763: if(flatdir[j]>0){
2764: printf("%d ",j);
2765: fprintf(ficlog,"%d ",j);
2766: }
2767: }
2768: printf("\n");
2769: fprintf(ficlog,"\n");
1.319 brouard 2770: #ifdef FLATSUP
2771: free_vector(xit,1,n);
2772: free_vector(xits,1,n);
2773: free_vector(ptt,1,n);
2774: free_vector(pt,1,n);
2775: return;
2776: #endif
1.234 brouard 2777: }
1.191 brouard 2778: #endif
1.234 brouard 2779: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2780: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2781:
1.126 brouard 2782: #ifdef DEBUG
1.234 brouard 2783: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2784: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2785: for(j=1;j<=n;j++){
2786: printf(" %lf",xit[j]);
2787: fprintf(ficlog," %lf",xit[j]);
2788: }
2789: printf("\n");
2790: fprintf(ficlog,"\n");
1.126 brouard 2791: #endif
1.192 brouard 2792: } /* end of t or directest negative */
1.224 brouard 2793: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2794: #else
1.234 brouard 2795: } /* end if (fptt < fp) */
1.192 brouard 2796: #endif
1.225 brouard 2797: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2798: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2799: #else
1.224 brouard 2800: #endif
1.234 brouard 2801: } /* loop iteration */
1.126 brouard 2802: }
1.234 brouard 2803:
1.126 brouard 2804: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2805:
1.235 brouard 2806: 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 2807: {
1.279 brouard 2808: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij
2809: * (and selected quantitative values in nres)
2810: * by left multiplying the unit
2811: * matrix by transitions matrix until convergence is reached with precision ftolpl
2812: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2813: * Wx is row vector: population in state 1, population in state 2, population dead
2814: * or prevalence in state 1, prevalence in state 2, 0
2815: * newm is the matrix after multiplications, its rows are identical at a factor.
2816: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2817: * Output is prlim.
2818: * Initial matrix pimij
2819: */
1.206 brouard 2820: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2821: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2822: /* 0, 0 , 1} */
2823: /*
2824: * and after some iteration: */
2825: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2826: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2827: /* 0, 0 , 1} */
2828: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2829: /* {0.51571254859325999, 0.4842874514067399, */
2830: /* 0.51326036147820708, 0.48673963852179264} */
2831: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2832:
1.332 brouard 2833: int i, ii,j,k, k1;
1.209 brouard 2834: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2835: /* double **matprod2(); */ /* test */
1.218 brouard 2836: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2837: double **newm;
1.209 brouard 2838: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2839: int ncvloop=0;
1.288 brouard 2840: int first=0;
1.169 brouard 2841:
1.209 brouard 2842: min=vector(1,nlstate);
2843: max=vector(1,nlstate);
2844: meandiff=vector(1,nlstate);
2845:
1.218 brouard 2846: /* Starting with matrix unity */
1.126 brouard 2847: for (ii=1;ii<=nlstate+ndeath;ii++)
2848: for (j=1;j<=nlstate+ndeath;j++){
2849: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2850: }
1.169 brouard 2851:
2852: cov[1]=1.;
2853:
2854: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2855: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2856: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2857: ncvloop++;
1.126 brouard 2858: newm=savm;
2859: /* Covariates have to be included here again */
1.138 brouard 2860: cov[2]=agefin;
1.319 brouard 2861: if(nagesqr==1){
2862: cov[3]= agefin*agefin;
2863: }
1.332 brouard 2864: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
2865: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
2866: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
2867: if(Typevar[k1]==1){ /* A product with age */
2868: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
2869: }else{
2870: cov[2+nagesqr+k1]=precov[nres][k1];
2871: }
2872: }/* End of loop on model equation */
2873:
2874: /* Start of old code (replaced by a loop on position in the model equation */
2875: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only of the model *\/ */
2876: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
2877: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; *\/ */
2878: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TnsdVar[TvarsD[k]])]; */
2879: /* /\* model = 1 +age + V1*V3 + age*V1 + V2 + V1 + age*V2 + V3 + V3*age + V1*V2 */
2880: /* * k 1 2 3 4 5 6 7 8 */
2881: /* *cov[] 1 2 3 4 5 6 7 8 9 10 */
2882: /* *TypeVar[k] 2 1 0 0 1 0 1 2 */
2883: /* *Dummy[k] 0 2 0 0 2 0 2 0 */
2884: /* *Tvar[k] 4 1 2 1 2 3 3 5 */
2885: /* *nsd=3 (1) (2) (3) */
2886: /* *TvarsD[nsd] [1]=2 1 3 */
2887: /* *TnsdVar [2]=2 [1]=1 [3]=3 */
2888: /* *TvarsDind[nsd](=k) [1]=3 [2]=4 [3]=6 */
2889: /* *Tage[] [1]=1 [2]=2 [3]=3 */
2890: /* *Tvard[] [1][1]=1 [2][1]=1 */
2891: /* * [1][2]=3 [2][2]=2 */
2892: /* *Tprod[](=k) [1]=1 [2]=8 */
2893: /* *TvarsDp(=Tvar) [1]=1 [2]=2 [3]=3 [4]=5 */
2894: /* *TvarD (=k) [1]=1 [2]=3 [3]=4 [3]=6 [4]=6 */
2895: /* *TvarsDpType */
2896: /* *si model= 1 + age + V3 + V2*age + V2 + V3*age */
2897: /* * nsd=1 (1) (2) */
2898: /* *TvarsD[nsd] 3 2 */
2899: /* *TnsdVar (3)=1 (2)=2 */
2900: /* *TvarsDind[nsd](=k) [1]=1 [2]=3 */
2901: /* *Tage[] [1]=2 [2]= 3 */
2902: /* *\/ */
2903: /* /\* cov[++k1]=nbcode[TvarsD[k]][codtabm(ij,k)]; *\/ */
2904: /* /\* 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)); *\/ */
2905: /* } */
2906: /* for (k=1; k<=nsq;k++) { /\* For single quantitative varying covariates only of the model *\/ */
2907: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
2908: /* /\* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline *\/ */
2909: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
2910: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][resultmodel[nres][k1]] */
2911: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
2912: /* /\* 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]); *\/ */
2913: /* } */
2914: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
2915: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
2916: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
2917: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
2918: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
2919: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
2920: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
2921: /* } */
2922: /* /\* 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]); *\/ */
2923: /* } */
2924: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
2925: /* /\* 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]); *\/ */
2926: /* if(Dummy[Tvard[k][1]]==0){ */
2927: /* if(Dummy[Tvard[k][2]]==0){ */
2928: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
2929: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
2930: /* }else{ */
2931: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
2932: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
2933: /* } */
2934: /* }else{ */
2935: /* if(Dummy[Tvard[k][2]]==0){ */
2936: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
2937: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
2938: /* }else{ */
2939: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
2940: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
2941: /* } */
2942: /* } */
2943: /* } /\* End product without age *\/ */
2944: /* ENd of old code */
1.138 brouard 2945: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2946: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2947: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 2948: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2949: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.319 brouard 2950: /* age and covariate values of ij are in 'cov' */
1.142 brouard 2951: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 2952:
1.126 brouard 2953: savm=oldm;
2954: oldm=newm;
1.209 brouard 2955:
2956: for(j=1; j<=nlstate; j++){
2957: max[j]=0.;
2958: min[j]=1.;
2959: }
2960: for(i=1;i<=nlstate;i++){
2961: sumnew=0;
2962: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
2963: for(j=1; j<=nlstate; j++){
2964: prlim[i][j]= newm[i][j]/(1-sumnew);
2965: max[j]=FMAX(max[j],prlim[i][j]);
2966: min[j]=FMIN(min[j],prlim[i][j]);
2967: }
2968: }
2969:
1.126 brouard 2970: maxmax=0.;
1.209 brouard 2971: for(j=1; j<=nlstate; j++){
2972: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
2973: maxmax=FMAX(maxmax,meandiff[j]);
2974: /* 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 2975: } /* j loop */
1.203 brouard 2976: *ncvyear= (int)age- (int)agefin;
1.208 brouard 2977: /* 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 2978: if(maxmax < ftolpl){
1.209 brouard 2979: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
2980: free_vector(min,1,nlstate);
2981: free_vector(max,1,nlstate);
2982: free_vector(meandiff,1,nlstate);
1.126 brouard 2983: return prlim;
2984: }
1.288 brouard 2985: } /* agefin loop */
1.208 brouard 2986: /* After some age loop it doesn't converge */
1.288 brouard 2987: if(!first){
2988: first=1;
2989: 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 2990: 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);
2991: }else if (first >=1 && first <10){
2992: 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);
2993: first++;
2994: }else if (first ==10){
2995: 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);
2996: 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");
2997: fprintf(ficlog,"Warning: the stable prevalence no convergence; too many cases, giving up noticing, even in log file\n");
2998: first++;
1.288 brouard 2999: }
3000:
1.209 brouard 3001: /* 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); */
3002: free_vector(min,1,nlstate);
3003: free_vector(max,1,nlstate);
3004: free_vector(meandiff,1,nlstate);
1.208 brouard 3005:
1.169 brouard 3006: return prlim; /* should not reach here */
1.126 brouard 3007: }
3008:
1.217 brouard 3009:
3010: /**** Back Prevalence limit (stable or period prevalence) ****************/
3011:
1.218 brouard 3012: /* 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) */
3013: /* 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 3014: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 3015: {
1.264 brouard 3016: /* 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 3017: matrix by transitions matrix until convergence is reached with precision ftolpl */
3018: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
3019: /* Wx is row vector: population in state 1, population in state 2, population dead */
3020: /* or prevalence in state 1, prevalence in state 2, 0 */
3021: /* newm is the matrix after multiplications, its rows are identical at a factor */
3022: /* Initial matrix pimij */
3023: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
3024: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
3025: /* 0, 0 , 1} */
3026: /*
3027: * and after some iteration: */
3028: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
3029: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
3030: /* 0, 0 , 1} */
3031: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
3032: /* {0.51571254859325999, 0.4842874514067399, */
3033: /* 0.51326036147820708, 0.48673963852179264} */
3034: /* If we start from prlim again, prlim tends to a constant matrix */
3035:
1.332 brouard 3036: int i, ii,j,k, k1;
1.247 brouard 3037: int first=0;
1.217 brouard 3038: double *min, *max, *meandiff, maxmax,sumnew=0.;
3039: /* double **matprod2(); */ /* test */
3040: double **out, cov[NCOVMAX+1], **bmij();
3041: double **newm;
1.218 brouard 3042: double **dnewm, **doldm, **dsavm; /* for use */
3043: double **oldm, **savm; /* for use */
3044:
1.217 brouard 3045: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
3046: int ncvloop=0;
3047:
3048: min=vector(1,nlstate);
3049: max=vector(1,nlstate);
3050: meandiff=vector(1,nlstate);
3051:
1.266 brouard 3052: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
3053: oldm=oldms; savm=savms;
3054:
3055: /* Starting with matrix unity */
3056: for (ii=1;ii<=nlstate+ndeath;ii++)
3057: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 3058: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3059: }
3060:
3061: cov[1]=1.;
3062:
3063: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3064: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 3065: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 3066: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
3067: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 3068: ncvloop++;
1.218 brouard 3069: newm=savm; /* oldm should be kept from previous iteration or unity at start */
3070: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 3071: /* Covariates have to be included here again */
3072: cov[2]=agefin;
1.319 brouard 3073: if(nagesqr==1){
1.217 brouard 3074: cov[3]= agefin*agefin;;
1.319 brouard 3075: }
1.332 brouard 3076: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
3077: if(Typevar[k1]==1){ /* A product with age */
3078: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.242 brouard 3079: }else{
1.332 brouard 3080: cov[2+nagesqr+k1]=precov[nres][k1];
1.242 brouard 3081: }
1.332 brouard 3082: }/* End of loop on model equation */
3083:
3084: /* Old code */
3085:
3086: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
3087: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
3088: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; */
3089: /* /\* 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)); *\/ */
3090: /* } */
3091: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
3092: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
3093: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
3094: /* /\* /\\* 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])]); *\\/ *\/ */
3095: /* /\* } *\/ */
3096: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
3097: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3098: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
3099: /* /\* 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]); *\/ */
3100: /* } */
3101: /* /\* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; *\/ */
3102: /* /\* for (k=1; k<=cptcovprod;k++) /\\* Useless *\\/ *\/ */
3103: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\\/ *\/ */
3104: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3105: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
3106: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age *\\/ ERROR ???*\/ */
3107: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
3108: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3109: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
3110: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3111: /* } */
3112: /* /\* 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]); *\/ */
3113: /* } */
3114: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
3115: /* /\* 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]); *\/ */
3116: /* if(Dummy[Tvard[k][1]]==0){ */
3117: /* if(Dummy[Tvard[k][2]]==0){ */
3118: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3119: /* }else{ */
3120: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3121: /* } */
3122: /* }else{ */
3123: /* if(Dummy[Tvard[k][2]]==0){ */
3124: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3125: /* }else{ */
3126: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3127: /* } */
3128: /* } */
3129: /* } */
1.217 brouard 3130:
3131: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
3132: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
3133: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
3134: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3135: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 3136: /* ij should be linked to the correct index of cov */
3137: /* age and covariate values ij are in 'cov', but we need to pass
3138: * ij for the observed prevalence at age and status and covariate
3139: * number: prevacurrent[(int)agefin][ii][ij]
3140: */
3141: /* 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 *\/ */
3142: /* 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 *\/ */
3143: 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 3144: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 3145: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
3146: /* for(i=1; i<=nlstate+ndeath; i++) { */
3147: /* printf("%d newm= ",i); */
3148: /* for(j=1;j<=nlstate+ndeath;j++) { */
3149: /* printf("%f ",newm[i][j]); */
3150: /* } */
3151: /* printf("oldm * "); */
3152: /* for(j=1;j<=nlstate+ndeath;j++) { */
3153: /* printf("%f ",oldm[i][j]); */
3154: /* } */
1.268 brouard 3155: /* printf(" bmmij "); */
1.266 brouard 3156: /* for(j=1;j<=nlstate+ndeath;j++) { */
3157: /* printf("%f ",pmmij[i][j]); */
3158: /* } */
3159: /* printf("\n"); */
3160: /* } */
3161: /* } */
1.217 brouard 3162: savm=oldm;
3163: oldm=newm;
1.266 brouard 3164:
1.217 brouard 3165: for(j=1; j<=nlstate; j++){
3166: max[j]=0.;
3167: min[j]=1.;
3168: }
3169: for(j=1; j<=nlstate; j++){
3170: for(i=1;i<=nlstate;i++){
1.234 brouard 3171: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
3172: bprlim[i][j]= newm[i][j];
3173: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
3174: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 3175: }
3176: }
1.218 brouard 3177:
1.217 brouard 3178: maxmax=0.;
3179: for(i=1; i<=nlstate; i++){
1.318 brouard 3180: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column, could be nan! */
1.217 brouard 3181: maxmax=FMAX(maxmax,meandiff[i]);
3182: /* 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 3183: } /* i loop */
1.217 brouard 3184: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 3185: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3186: if(maxmax < ftolpl){
1.220 brouard 3187: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3188: free_vector(min,1,nlstate);
3189: free_vector(max,1,nlstate);
3190: free_vector(meandiff,1,nlstate);
3191: return bprlim;
3192: }
1.288 brouard 3193: } /* agefin loop */
1.217 brouard 3194: /* After some age loop it doesn't converge */
1.288 brouard 3195: if(!first){
1.247 brouard 3196: first=1;
3197: 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\
3198: 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);
3199: }
3200: 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 3201: 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);
3202: /* 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); */
3203: free_vector(min,1,nlstate);
3204: free_vector(max,1,nlstate);
3205: free_vector(meandiff,1,nlstate);
3206:
3207: return bprlim; /* should not reach here */
3208: }
3209:
1.126 brouard 3210: /*************** transition probabilities ***************/
3211:
3212: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
3213: {
1.138 brouard 3214: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 3215: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 3216: model to the ncovmodel covariates (including constant and age).
3217: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3218: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3219: ncth covariate in the global vector x is given by the formula:
3220: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3221: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3222: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3223: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 3224: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 3225: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 3226: Sum on j ps[i][j] should equal to 1.
1.138 brouard 3227: */
3228: double s1, lnpijopii;
1.126 brouard 3229: /*double t34;*/
1.164 brouard 3230: int i,j, nc, ii, jj;
1.126 brouard 3231:
1.223 brouard 3232: for(i=1; i<= nlstate; i++){
3233: for(j=1; j<i;j++){
3234: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3235: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3236: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3237: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3238: }
3239: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3240: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3241: }
3242: for(j=i+1; j<=nlstate+ndeath;j++){
3243: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3244: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3245: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3246: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3247: }
3248: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3249: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3250: }
3251: }
1.218 brouard 3252:
1.223 brouard 3253: for(i=1; i<= nlstate; i++){
3254: s1=0;
3255: for(j=1; j<i; j++){
3256: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
1.330 brouard 3257: /* printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
1.223 brouard 3258: }
3259: for(j=i+1; j<=nlstate+ndeath; j++){
3260: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
1.330 brouard 3261: /* printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
1.223 brouard 3262: }
3263: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3264: ps[i][i]=1./(s1+1.);
3265: /* Computing other pijs */
3266: for(j=1; j<i; j++)
1.325 brouard 3267: ps[i][j]= exp(ps[i][j])*ps[i][i];/* Bug valgrind */
1.223 brouard 3268: for(j=i+1; j<=nlstate+ndeath; j++)
3269: ps[i][j]= exp(ps[i][j])*ps[i][i];
3270: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3271: } /* end i */
1.218 brouard 3272:
1.223 brouard 3273: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3274: for(jj=1; jj<= nlstate+ndeath; jj++){
3275: ps[ii][jj]=0;
3276: ps[ii][ii]=1;
3277: }
3278: }
1.294 brouard 3279:
3280:
1.223 brouard 3281: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3282: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3283: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3284: /* } */
3285: /* printf("\n "); */
3286: /* } */
3287: /* printf("\n ");printf("%lf ",cov[2]);*/
3288: /*
3289: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 3290: goto end;*/
1.266 brouard 3291: return ps; /* Pointer is unchanged since its call */
1.126 brouard 3292: }
3293:
1.218 brouard 3294: /*************** backward transition probabilities ***************/
3295:
3296: /* 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 ) */
3297: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
3298: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
3299: {
1.302 brouard 3300: /* 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 3301: * 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 3302: */
1.218 brouard 3303: int i, ii, j,k;
1.222 brouard 3304:
3305: double **out, **pmij();
3306: double sumnew=0.;
1.218 brouard 3307: double agefin;
1.292 brouard 3308: 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 3309: double **dnewm, **dsavm, **doldm;
3310: double **bbmij;
3311:
1.218 brouard 3312: doldm=ddoldms; /* global pointers */
1.222 brouard 3313: dnewm=ddnewms;
3314: dsavm=ddsavms;
1.318 brouard 3315:
3316: /* Debug */
3317: /* printf("Bmij ij=%d, cov[2}=%f\n", ij, cov[2]); */
1.222 brouard 3318: agefin=cov[2];
1.268 brouard 3319: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 3320: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 3321: the observed prevalence (with this covariate ij) at beginning of transition */
3322: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 3323:
3324: /* P_x */
1.325 brouard 3325: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm *//* Bug valgrind */
1.268 brouard 3326: /* outputs pmmij which is a stochastic matrix in row */
3327:
3328: /* Diag(w_x) */
1.292 brouard 3329: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 3330: sumnew=0.;
1.269 brouard 3331: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 3332: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.297 brouard 3333: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 3334: sumnew+=prevacurrent[(int)agefin][ii][ij];
3335: }
3336: if(sumnew >0.01){ /* At least some value in the prevalence */
3337: for (ii=1;ii<=nlstate+ndeath;ii++){
3338: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 3339: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 3340: }
3341: }else{
3342: for (ii=1;ii<=nlstate+ndeath;ii++){
3343: for (j=1;j<=nlstate+ndeath;j++)
3344: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
3345: }
3346: /* if(sumnew <0.9){ */
3347: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3348: /* } */
3349: }
3350: k3=0.0; /* We put the last diagonal to 0 */
3351: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3352: doldm[ii][ii]= k3;
3353: }
3354: /* End doldm, At the end doldm is diag[(w_i)] */
3355:
1.292 brouard 3356: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
3357: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 3358:
1.292 brouard 3359: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 3360: /* 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 3361: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3362: sumnew=0.;
1.222 brouard 3363: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3364: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3365: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3366: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3367: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3368: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3369: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3370: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3371: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3372: /* }else */
1.268 brouard 3373: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3374: } /*End ii */
3375: } /* 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 */
3376:
1.292 brouard 3377: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 3378: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3379: /* end bmij */
1.266 brouard 3380: return ps; /*pointer is unchanged */
1.218 brouard 3381: }
1.217 brouard 3382: /*************** transition probabilities ***************/
3383:
1.218 brouard 3384: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3385: {
3386: /* According to parameters values stored in x and the covariate's values stored in cov,
3387: computes the probability to be observed in state j being in state i by appying the
3388: model to the ncovmodel covariates (including constant and age).
3389: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3390: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3391: ncth covariate in the global vector x is given by the formula:
3392: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3393: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3394: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3395: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3396: Outputs ps[i][j] the probability to be observed in j being in j according to
3397: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3398: */
3399: double s1, lnpijopii;
3400: /*double t34;*/
3401: int i,j, nc, ii, jj;
3402:
1.234 brouard 3403: for(i=1; i<= nlstate; i++){
3404: for(j=1; j<i;j++){
3405: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3406: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3407: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3408: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3409: }
3410: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3411: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3412: }
3413: for(j=i+1; j<=nlstate+ndeath;j++){
3414: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3415: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3416: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3417: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3418: }
3419: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3420: }
3421: }
3422:
3423: for(i=1; i<= nlstate; i++){
3424: s1=0;
3425: for(j=1; j<i; j++){
3426: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3427: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3428: }
3429: for(j=i+1; j<=nlstate+ndeath; j++){
3430: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3431: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3432: }
3433: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3434: ps[i][i]=1./(s1+1.);
3435: /* Computing other pijs */
3436: for(j=1; j<i; j++)
3437: ps[i][j]= exp(ps[i][j])*ps[i][i];
3438: for(j=i+1; j<=nlstate+ndeath; j++)
3439: ps[i][j]= exp(ps[i][j])*ps[i][i];
3440: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3441: } /* end i */
3442:
3443: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3444: for(jj=1; jj<= nlstate+ndeath; jj++){
3445: ps[ii][jj]=0;
3446: ps[ii][ii]=1;
3447: }
3448: }
1.296 brouard 3449: /* Added for prevbcast */ /* Transposed matrix too */
1.234 brouard 3450: for(jj=1; jj<= nlstate+ndeath; jj++){
3451: s1=0.;
3452: for(ii=1; ii<= nlstate+ndeath; ii++){
3453: s1+=ps[ii][jj];
3454: }
3455: for(ii=1; ii<= nlstate; ii++){
3456: ps[ii][jj]=ps[ii][jj]/s1;
3457: }
3458: }
3459: /* Transposition */
3460: for(jj=1; jj<= nlstate+ndeath; jj++){
3461: for(ii=jj; ii<= nlstate+ndeath; ii++){
3462: s1=ps[ii][jj];
3463: ps[ii][jj]=ps[jj][ii];
3464: ps[jj][ii]=s1;
3465: }
3466: }
3467: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3468: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3469: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3470: /* } */
3471: /* printf("\n "); */
3472: /* } */
3473: /* printf("\n ");printf("%lf ",cov[2]);*/
3474: /*
3475: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3476: goto end;*/
3477: return ps;
1.217 brouard 3478: }
3479:
3480:
1.126 brouard 3481: /**************** Product of 2 matrices ******************/
3482:
1.145 brouard 3483: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3484: {
3485: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3486: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3487: /* in, b, out are matrice of pointers which should have been initialized
3488: before: only the contents of out is modified. The function returns
3489: a pointer to pointers identical to out */
1.145 brouard 3490: int i, j, k;
1.126 brouard 3491: for(i=nrl; i<= nrh; i++)
1.145 brouard 3492: for(k=ncolol; k<=ncoloh; k++){
3493: out[i][k]=0.;
3494: for(j=ncl; j<=nch; j++)
3495: out[i][k] +=in[i][j]*b[j][k];
3496: }
1.126 brouard 3497: return out;
3498: }
3499:
3500:
3501: /************* Higher Matrix Product ***************/
3502:
1.235 brouard 3503: 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 3504: {
1.332 brouard 3505: /* 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 3506: 'nhstepm*hstepm*stepm' months (i.e. until
3507: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3508: nhstepm*hstepm matrices.
3509: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3510: (typically every 2 years instead of every month which is too big
3511: for the memory).
3512: Model is determined by parameters x and covariates have to be
3513: included manually here.
3514:
3515: */
3516:
1.330 brouard 3517: int i, j, d, h, k, k1;
1.131 brouard 3518: double **out, cov[NCOVMAX+1];
1.126 brouard 3519: double **newm;
1.187 brouard 3520: double agexact;
1.214 brouard 3521: double agebegin, ageend;
1.126 brouard 3522:
3523: /* Hstepm could be zero and should return the unit matrix */
3524: for (i=1;i<=nlstate+ndeath;i++)
3525: for (j=1;j<=nlstate+ndeath;j++){
3526: oldm[i][j]=(i==j ? 1.0 : 0.0);
3527: po[i][j][0]=(i==j ? 1.0 : 0.0);
3528: }
3529: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3530: for(h=1; h <=nhstepm; h++){
3531: for(d=1; d <=hstepm; d++){
3532: newm=savm;
3533: /* Covariates have to be included here again */
3534: cov[1]=1.;
1.214 brouard 3535: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3536: cov[2]=agexact;
1.319 brouard 3537: if(nagesqr==1){
1.227 brouard 3538: cov[3]= agexact*agexact;
1.319 brouard 3539: }
1.330 brouard 3540: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
3541: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
3542: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.332 brouard 3543: if(Typevar[k1]==1){ /* A product with age */
3544: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
3545: }else{
3546: cov[2+nagesqr+k1]=precov[nres][k1];
3547: }
3548: }/* End of loop on model equation */
3549: /* Old code */
3550: /* if( Dummy[k1]==0 && Typevar[k1]==0 ){ /\* Single dummy *\/ */
3551: /* /\* V(Tvarsel)=Tvalsel=Tresult[nres][pos](value); V(Tvresult[nres][pos] (variable): V(variable)=value) *\/ */
3552: /* /\* for (k=1; k<=nsd;k++) { /\\* For single dummy covariates only *\\/ *\/ */
3553: /* /\* /\\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\\/ *\/ */
3554: /* /\* codtabm(ij,k) (1 & (ij-1) >> (k-1))+1 *\/ */
3555: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3556: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3557: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
3558: /* /\* nsd 1 2 3 *\/ /\* Counting single dummies covar fixed or tv *\/ */
3559: /* /\*TvarsD[nsd] 4 3 1 *\/ /\* ID of single dummy cova fixed or timevary*\/ */
3560: /* /\*TvarsDind[k] 2 3 9 *\/ /\* position K of single dummy cova *\/ */
3561: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];or [codtabm(ij,TnsdVar[TvarsD[k]] *\/ */
3562: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
3563: /* /\* 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]])); *\/ */
3564: /* 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); */
3565: /* printf("hpxij new Dummy precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3566: /* }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /\* Single quantitative variables *\/ */
3567: /* /\* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline *\/ */
3568: /* cov[2+nagesqr+k1]=Tqresult[nres][resultmodel[nres][k1]]; */
3569: /* /\* for (k=1; k<=nsq;k++) { /\\* For single varying covariates only *\\/ *\/ */
3570: /* /\* /\\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\\/ *\/ */
3571: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
3572: /* 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]]); */
3573: /* printf("hpxij new Quanti precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3574: /* }else if( Dummy[k1]==2 ){ /\* For dummy with age product *\/ */
3575: /* /\* Tvar[k1] Variable in the age product age*V1 is 1 *\/ */
3576: /* /\* [Tinvresult[nres][V1] is its value in the resultline nres *\/ */
3577: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvar[k1]]*cov[2]; */
3578: /* 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]); */
3579: /* printf("hpxij new Dummy with age product precov[nres=%d][k1=%d]=%.4f * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
3580:
3581: /* /\* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; *\/ */
3582: /* /\* for (k=1; k<=cptcovage;k++){ /\\* For product with age V1+V1*age +V4 +age*V3 *\\/ *\/ */
3583: /* /\* 1+2 Tage[1]=2 TVar[2]=1 Dummy[2]=2, Tage[2]=4 TVar[4]=3 Dummy[4]=3 quant*\/ */
3584: /* /\* *\/ */
1.330 brouard 3585: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3586: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3587: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
1.332 brouard 3588: /* /\*cptcovage=2 1 2 *\/ */
3589: /* /\*Tage[k]= 5 8 *\/ */
3590: /* }else if( Dummy[k1]==3 ){ /\* For quant with age product *\/ */
3591: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
3592: /* 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]]); */
3593: /* printf("hpxij new Quanti with age product precov[nres=%d][k1=%d] * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
3594: /* /\* if(Dummy[Tage[k]]== 2){ /\\* dummy with age *\\/ *\/ */
3595: /* /\* /\\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\\* dummy with age *\\\/ *\\/ *\/ */
3596: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\\/ *\/ */
3597: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\\/ *\/ */
3598: /* /\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\/ */
3599: /* /\* 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); *\/ */
3600: /* /\* } else if(Dummy[Tage[k]]== 3){ /\\* quantitative with age *\\/ *\/ */
3601: /* /\* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; *\/ */
3602: /* /\* } *\/ */
3603: /* /\* 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]); *\/ */
3604: /* }else if(Typevar[k1]==2 ){ /\* For product (not with age) *\/ */
3605: /* /\* for (k=1; k<=cptcovprod;k++){ /\\* For product without age *\\/ *\/ */
3606: /* /\* /\\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\\/ *\/ */
3607: /* /\* /\\* k 1 2 3 4 5 6 7 8 9 *\\/ *\/ */
3608: /* /\* /\\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\\/ *\/ */
3609: /* /\* /\\*cptcovprod=1 1 2 *\\/ *\/ */
3610: /* /\* /\\*Tprod[]= 4 7 *\\/ *\/ */
3611: /* /\* /\\*Tvard[][1] 4 1 *\\/ *\/ */
3612: /* /\* /\\*Tvard[][2] 3 2 *\\/ *\/ */
1.330 brouard 3613:
1.332 brouard 3614: /* /\* 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])]); *\/ */
3615: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3616: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]]; */
3617: /* 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]]); */
3618: /* printf("hpxij new Product no age product precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3619:
3620: /* /\* if(Dummy[Tvardk[k1][1]]==0){ *\/ */
3621: /* /\* if(Dummy[Tvardk[k1][2]]==0){ /\\* Product of dummies *\\/ *\/ */
3622: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3623: /* /\* cov[2+nagesqr+k1]=Tinvresult[nres][Tvardk[k1][1]] * Tinvresult[nres][Tvardk[k1][2]]; *\/ */
3624: /* /\* 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]])]; *\/ */
3625: /* /\* }else{ /\\* Product of dummy by quantitative *\\/ *\/ */
3626: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,TnsdVar[Tvard[k][1]])] * Tqresult[nres][k]; *\/ */
3627: /* /\* cov[2+nagesqr+k1]=Tresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]]; *\/ */
3628: /* /\* } *\/ */
3629: /* /\* }else{ /\\* Product of quantitative by...*\\/ *\/ */
3630: /* /\* if(Dummy[Tvard[k][2]]==0){ /\\* quant by dummy *\\/ *\/ */
3631: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][Tvard[k][1]]; *\\/ *\/ */
3632: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
3633: /* /\* }else{ /\\* Product of two quant *\\/ *\/ */
3634: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\\/ *\/ */
3635: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
3636: /* /\* } *\/ */
3637: /* /\* }/\\*end of products quantitative *\\/ *\/ */
3638: /* }/\*end of products *\/ */
3639: /* } /\* End of loop on model equation *\/ */
1.235 brouard 3640: /* for (k=1; k<=cptcovn;k++) */
3641: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3642: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3643: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3644: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3645: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3646:
3647:
1.126 brouard 3648: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3649: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.319 brouard 3650: /* right multiplication of oldm by the current matrix */
1.126 brouard 3651: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3652: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3653: /* if((int)age == 70){ */
3654: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3655: /* for(i=1; i<=nlstate+ndeath; i++) { */
3656: /* printf("%d pmmij ",i); */
3657: /* for(j=1;j<=nlstate+ndeath;j++) { */
3658: /* printf("%f ",pmmij[i][j]); */
3659: /* } */
3660: /* printf(" oldm "); */
3661: /* for(j=1;j<=nlstate+ndeath;j++) { */
3662: /* printf("%f ",oldm[i][j]); */
3663: /* } */
3664: /* printf("\n"); */
3665: /* } */
3666: /* } */
1.126 brouard 3667: savm=oldm;
3668: oldm=newm;
3669: }
3670: for(i=1; i<=nlstate+ndeath; i++)
3671: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3672: po[i][j][h]=newm[i][j];
3673: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3674: }
1.128 brouard 3675: /*printf("h=%d ",h);*/
1.126 brouard 3676: } /* end h */
1.267 brouard 3677: /* printf("\n H=%d \n",h); */
1.126 brouard 3678: return po;
3679: }
3680:
1.217 brouard 3681: /************* Higher Back Matrix Product ***************/
1.218 brouard 3682: /* 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 3683: 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 3684: {
1.332 brouard 3685: /* For dummy covariates given in each resultline (for historical, computes the corresponding combination ij),
3686: computes the transition matrix starting at age 'age' over
1.217 brouard 3687: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3688: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3689: nhstepm*hstepm matrices.
3690: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3691: (typically every 2 years instead of every month which is too big
1.217 brouard 3692: for the memory).
1.218 brouard 3693: Model is determined by parameters x and covariates have to be
1.266 brouard 3694: included manually here. Then we use a call to bmij(x and cov)
3695: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3696: */
1.217 brouard 3697:
1.332 brouard 3698: int i, j, d, h, k, k1;
1.266 brouard 3699: double **out, cov[NCOVMAX+1], **bmij();
3700: double **newm, ***newmm;
1.217 brouard 3701: double agexact;
3702: double agebegin, ageend;
1.222 brouard 3703: double **oldm, **savm;
1.217 brouard 3704:
1.266 brouard 3705: newmm=po; /* To be saved */
3706: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3707: /* Hstepm could be zero and should return the unit matrix */
3708: for (i=1;i<=nlstate+ndeath;i++)
3709: for (j=1;j<=nlstate+ndeath;j++){
3710: oldm[i][j]=(i==j ? 1.0 : 0.0);
3711: po[i][j][0]=(i==j ? 1.0 : 0.0);
3712: }
3713: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3714: for(h=1; h <=nhstepm; h++){
3715: for(d=1; d <=hstepm; d++){
3716: newm=savm;
3717: /* Covariates have to be included here again */
3718: cov[1]=1.;
1.271 brouard 3719: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3720: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
1.318 brouard 3721: /* Debug */
3722: /* printf("hBxij age=%lf, agexact=%lf\n", age, agexact); */
1.217 brouard 3723: cov[2]=agexact;
1.332 brouard 3724: if(nagesqr==1){
1.222 brouard 3725: cov[3]= agexact*agexact;
1.332 brouard 3726: }
3727: /** New code */
3728: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
3729: if(Typevar[k1]==1){ /* A product with age */
3730: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.325 brouard 3731: }else{
1.332 brouard 3732: cov[2+nagesqr+k1]=precov[nres][k1];
1.325 brouard 3733: }
1.332 brouard 3734: }/* End of loop on model equation */
3735: /** End of new code */
3736: /** This was old code */
3737: /* for (k=1; k<=nsd;k++){ /\* For single dummy covariates only *\//\* cptcovn error *\/ */
3738: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
3739: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
3740: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])];/\* Bug valgrind *\/ */
3741: /* /\* 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)); *\/ */
3742: /* } */
3743: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
3744: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3745: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
3746: /* /\* 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]); *\/ */
3747: /* } */
3748: /* for (k=1; k<=cptcovage;k++){ /\* Should start at cptcovn+1 *\//\* For product with age *\/ */
3749: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age error!!!*\\/ *\/ */
3750: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
3751: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3752: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
3753: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3754: /* } */
3755: /* /\* 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]); *\/ */
3756: /* } */
3757: /* for (k=1; k<=cptcovprod;k++){ /\* Useless because included in cptcovn *\/ */
3758: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])]*nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3759: /* if(Dummy[Tvard[k][1]]==0){ */
3760: /* if(Dummy[Tvard[k][2]]==0){ */
3761: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][1])]; */
3762: /* }else{ */
3763: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3764: /* } */
3765: /* }else{ */
3766: /* if(Dummy[Tvard[k][2]]==0){ */
3767: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3768: /* }else{ */
3769: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3770: /* } */
3771: /* } */
3772: /* } */
3773: /* /\*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*\/ */
3774: /* /\*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*\/ */
3775: /** End of old code */
3776:
1.218 brouard 3777: /* Careful transposed matrix */
1.266 brouard 3778: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3779: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3780: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3781: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.325 brouard 3782: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);/* Bug valgrind */
1.217 brouard 3783: /* if((int)age == 70){ */
3784: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3785: /* for(i=1; i<=nlstate+ndeath; i++) { */
3786: /* printf("%d pmmij ",i); */
3787: /* for(j=1;j<=nlstate+ndeath;j++) { */
3788: /* printf("%f ",pmmij[i][j]); */
3789: /* } */
3790: /* printf(" oldm "); */
3791: /* for(j=1;j<=nlstate+ndeath;j++) { */
3792: /* printf("%f ",oldm[i][j]); */
3793: /* } */
3794: /* printf("\n"); */
3795: /* } */
3796: /* } */
3797: savm=oldm;
3798: oldm=newm;
3799: }
3800: for(i=1; i<=nlstate+ndeath; i++)
3801: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3802: po[i][j][h]=newm[i][j];
1.268 brouard 3803: /* if(h==nhstepm) */
3804: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3805: }
1.268 brouard 3806: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3807: } /* end h */
1.268 brouard 3808: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3809: return po;
3810: }
3811:
3812:
1.162 brouard 3813: #ifdef NLOPT
3814: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3815: double fret;
3816: double *xt;
3817: int j;
3818: myfunc_data *d2 = (myfunc_data *) pd;
3819: /* xt = (p1-1); */
3820: xt=vector(1,n);
3821: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3822:
3823: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3824: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3825: printf("Function = %.12lf ",fret);
3826: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3827: printf("\n");
3828: free_vector(xt,1,n);
3829: return fret;
3830: }
3831: #endif
1.126 brouard 3832:
3833: /*************** log-likelihood *************/
3834: double func( double *x)
3835: {
1.226 brouard 3836: int i, ii, j, k, mi, d, kk;
3837: int ioffset=0;
3838: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3839: double **out;
3840: double lli; /* Individual log likelihood */
3841: int s1, s2;
1.228 brouard 3842: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
1.226 brouard 3843: double bbh, survp;
3844: long ipmx;
3845: double agexact;
3846: /*extern weight */
3847: /* We are differentiating ll according to initial status */
3848: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3849: /*for(i=1;i<imx;i++)
3850: printf(" %d\n",s[4][i]);
3851: */
1.162 brouard 3852:
1.226 brouard 3853: ++countcallfunc;
1.162 brouard 3854:
1.226 brouard 3855: cov[1]=1.;
1.126 brouard 3856:
1.226 brouard 3857: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3858: ioffset=0;
1.226 brouard 3859: if(mle==1){
3860: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3861: /* Computes the values of the ncovmodel covariates of the model
3862: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3863: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3864: to be observed in j being in i according to the model.
3865: */
1.243 brouard 3866: ioffset=2+nagesqr ;
1.233 brouard 3867: /* Fixed */
1.319 brouard 3868: for (k=1; k<=ncovf;k++){ /* For each fixed covariate dummu or quant or prod */
3869: /* # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi */
3870: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
3871: /* 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 3872: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.319 brouard 3873: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, only V1 is fixed (TvarFind[1]=6)*/
3874: /* V1*V2 (7) TvarFind[2]=7, TvarFind[3]=9 */
1.234 brouard 3875: }
1.226 brouard 3876: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
1.319 brouard 3877: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
1.226 brouard 3878: has been calculated etc */
3879: /* For an individual i, wav[i] gives the number of effective waves */
3880: /* We compute the contribution to Likelihood of each effective transition
3881: mw[mi][i] is real wave of the mi th effectve wave */
3882: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3883: s2=s[mw[mi+1][i]][i];
3884: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i]
3885: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3886: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3887: */
3888: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 3889: 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*/
3890: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; but where is the crossproduct? */
1.242 brouard 3891: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
1.234 brouard 3892: }
3893: for (ii=1;ii<=nlstate+ndeath;ii++)
3894: for (j=1;j<=nlstate+ndeath;j++){
3895: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3896: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3897: }
3898: for(d=0; d<dh[mi][i]; d++){
3899: newm=savm;
3900: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3901: cov[2]=agexact;
3902: if(nagesqr==1)
3903: cov[3]= agexact*agexact; /* Should be changed here */
3904: for (kk=1; kk<=cptcovage;kk++) {
1.318 brouard 3905: if(!FixedV[Tvar[Tage[kk]]])
3906: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
3907: else
3908: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
1.234 brouard 3909: }
3910: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3911: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3912: savm=oldm;
3913: oldm=newm;
3914: } /* end mult */
3915:
3916: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
3917: /* But now since version 0.9 we anticipate for bias at large stepm.
3918: * If stepm is larger than one month (smallest stepm) and if the exact delay
3919: * (in months) between two waves is not a multiple of stepm, we rounded to
3920: * the nearest (and in case of equal distance, to the lowest) interval but now
3921: * we keep into memory the bias bh[mi][i] and also the previous matrix product
3922: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
3923: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 3924: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
3925: * -stepm/2 to stepm/2 .
3926: * For stepm=1 the results are the same as for previous versions of Imach.
3927: * For stepm > 1 the results are less biased than in previous versions.
3928: */
1.234 brouard 3929: s1=s[mw[mi][i]][i];
3930: s2=s[mw[mi+1][i]][i];
3931: bbh=(double)bh[mi][i]/(double)stepm;
3932: /* bias bh is positive if real duration
3933: * is higher than the multiple of stepm and negative otherwise.
3934: */
3935: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
3936: if( s2 > nlstate){
3937: /* i.e. if s2 is a death state and if the date of death is known
3938: then the contribution to the likelihood is the probability to
3939: die between last step unit time and current step unit time,
3940: which is also equal to probability to die before dh
3941: minus probability to die before dh-stepm .
3942: In version up to 0.92 likelihood was computed
3943: as if date of death was unknown. Death was treated as any other
3944: health state: the date of the interview describes the actual state
3945: and not the date of a change in health state. The former idea was
3946: to consider that at each interview the state was recorded
3947: (healthy, disable or death) and IMaCh was corrected; but when we
3948: introduced the exact date of death then we should have modified
3949: the contribution of an exact death to the likelihood. This new
3950: contribution is smaller and very dependent of the step unit
3951: stepm. It is no more the probability to die between last interview
3952: and month of death but the probability to survive from last
3953: interview up to one month before death multiplied by the
3954: probability to die within a month. Thanks to Chris
3955: Jackson for correcting this bug. Former versions increased
3956: mortality artificially. The bad side is that we add another loop
3957: which slows down the processing. The difference can be up to 10%
3958: lower mortality.
3959: */
3960: /* If, at the beginning of the maximization mostly, the
3961: cumulative probability or probability to be dead is
3962: constant (ie = 1) over time d, the difference is equal to
3963: 0. out[s1][3] = savm[s1][3]: probability, being at state
3964: s1 at precedent wave, to be dead a month before current
3965: wave is equal to probability, being at state s1 at
3966: precedent wave, to be dead at mont of the current
3967: wave. Then the observed probability (that this person died)
3968: is null according to current estimated parameter. In fact,
3969: it should be very low but not zero otherwise the log go to
3970: infinity.
3971: */
1.183 brouard 3972: /* #ifdef INFINITYORIGINAL */
3973: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3974: /* #else */
3975: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
3976: /* lli=log(mytinydouble); */
3977: /* else */
3978: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3979: /* #endif */
1.226 brouard 3980: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3981:
1.226 brouard 3982: } else if ( s2==-1 ) { /* alive */
3983: for (j=1,survp=0. ; j<=nlstate; j++)
3984: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3985: /*survp += out[s1][j]; */
3986: lli= log(survp);
3987: }
3988: else if (s2==-4) {
3989: for (j=3,survp=0. ; j<=nlstate; j++)
3990: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3991: lli= log(survp);
3992: }
3993: else if (s2==-5) {
3994: for (j=1,survp=0. ; j<=2; j++)
3995: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3996: lli= log(survp);
3997: }
3998: else{
3999: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4000: /* 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 */
4001: }
4002: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
4003: /*if(lli ==000.0)*/
4004: /*printf("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); */
4005: ipmx +=1;
4006: sw += weight[i];
4007: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4008: /* if (lli < log(mytinydouble)){ */
4009: /* 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); */
4010: /* 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]); */
4011: /* } */
4012: } /* end of wave */
4013: } /* end of individual */
4014: } else if(mle==2){
4015: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.319 brouard 4016: ioffset=2+nagesqr ;
4017: for (k=1; k<=ncovf;k++)
4018: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];
1.226 brouard 4019: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 4020: for(k=1; k <= ncovv ; k++){
4021: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
4022: }
1.226 brouard 4023: for (ii=1;ii<=nlstate+ndeath;ii++)
4024: for (j=1;j<=nlstate+ndeath;j++){
4025: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4026: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4027: }
4028: for(d=0; d<=dh[mi][i]; d++){
4029: newm=savm;
4030: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4031: cov[2]=agexact;
4032: if(nagesqr==1)
4033: cov[3]= agexact*agexact;
4034: for (kk=1; kk<=cptcovage;kk++) {
4035: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4036: }
4037: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4038: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4039: savm=oldm;
4040: oldm=newm;
4041: } /* end mult */
4042:
4043: s1=s[mw[mi][i]][i];
4044: s2=s[mw[mi+1][i]][i];
4045: bbh=(double)bh[mi][i]/(double)stepm;
4046: 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 */
4047: ipmx +=1;
4048: sw += weight[i];
4049: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4050: } /* end of wave */
4051: } /* end of individual */
4052: } else if(mle==3){ /* exponential inter-extrapolation */
4053: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4054: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4055: for(mi=1; mi<= wav[i]-1; mi++){
4056: for (ii=1;ii<=nlstate+ndeath;ii++)
4057: for (j=1;j<=nlstate+ndeath;j++){
4058: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4059: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4060: }
4061: for(d=0; d<dh[mi][i]; d++){
4062: newm=savm;
4063: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4064: cov[2]=agexact;
4065: if(nagesqr==1)
4066: cov[3]= agexact*agexact;
4067: for (kk=1; kk<=cptcovage;kk++) {
4068: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4069: }
4070: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4071: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4072: savm=oldm;
4073: oldm=newm;
4074: } /* end mult */
4075:
4076: s1=s[mw[mi][i]][i];
4077: s2=s[mw[mi+1][i]][i];
4078: bbh=(double)bh[mi][i]/(double)stepm;
4079: 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 */
4080: ipmx +=1;
4081: sw += weight[i];
4082: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4083: } /* end of wave */
4084: } /* end of individual */
4085: }else if (mle==4){ /* ml=4 no inter-extrapolation */
4086: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4087: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4088: for(mi=1; mi<= wav[i]-1; mi++){
4089: for (ii=1;ii<=nlstate+ndeath;ii++)
4090: for (j=1;j<=nlstate+ndeath;j++){
4091: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4092: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4093: }
4094: for(d=0; d<dh[mi][i]; d++){
4095: newm=savm;
4096: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4097: cov[2]=agexact;
4098: if(nagesqr==1)
4099: cov[3]= agexact*agexact;
4100: for (kk=1; kk<=cptcovage;kk++) {
4101: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4102: }
1.126 brouard 4103:
1.226 brouard 4104: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4105: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4106: savm=oldm;
4107: oldm=newm;
4108: } /* end mult */
4109:
4110: s1=s[mw[mi][i]][i];
4111: s2=s[mw[mi+1][i]][i];
4112: if( s2 > nlstate){
4113: lli=log(out[s1][s2] - savm[s1][s2]);
4114: } else if ( s2==-1 ) { /* alive */
4115: for (j=1,survp=0. ; j<=nlstate; j++)
4116: survp += out[s1][j];
4117: lli= log(survp);
4118: }else{
4119: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4120: }
4121: ipmx +=1;
4122: sw += weight[i];
4123: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.126 brouard 4124: /* 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]); */
1.226 brouard 4125: } /* end of wave */
4126: } /* end of individual */
4127: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
4128: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4129: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4130: for(mi=1; mi<= wav[i]-1; mi++){
4131: for (ii=1;ii<=nlstate+ndeath;ii++)
4132: for (j=1;j<=nlstate+ndeath;j++){
4133: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4134: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4135: }
4136: for(d=0; d<dh[mi][i]; d++){
4137: newm=savm;
4138: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4139: cov[2]=agexact;
4140: if(nagesqr==1)
4141: cov[3]= agexact*agexact;
4142: for (kk=1; kk<=cptcovage;kk++) {
4143: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4144: }
1.126 brouard 4145:
1.226 brouard 4146: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4147: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4148: savm=oldm;
4149: oldm=newm;
4150: } /* end mult */
4151:
4152: s1=s[mw[mi][i]][i];
4153: s2=s[mw[mi+1][i]][i];
4154: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4155: ipmx +=1;
4156: sw += weight[i];
4157: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4158: /*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]);*/
4159: } /* end of wave */
4160: } /* end of individual */
4161: } /* End of if */
4162: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
4163: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
4164: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4165: return -l;
1.126 brouard 4166: }
4167:
4168: /*************** log-likelihood *************/
4169: double funcone( double *x)
4170: {
1.228 brouard 4171: /* Same as func but slower because of a lot of printf and if */
1.126 brouard 4172: int i, ii, j, k, mi, d, kk;
1.228 brouard 4173: int ioffset=0;
1.131 brouard 4174: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 4175: double **out;
4176: double lli; /* Individual log likelihood */
4177: double llt;
4178: int s1, s2;
1.228 brouard 4179: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
4180:
1.126 brouard 4181: double bbh, survp;
1.187 brouard 4182: double agexact;
1.214 brouard 4183: double agebegin, ageend;
1.126 brouard 4184: /*extern weight */
4185: /* We are differentiating ll according to initial status */
4186: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
4187: /*for(i=1;i<imx;i++)
4188: printf(" %d\n",s[4][i]);
4189: */
4190: cov[1]=1.;
4191:
4192: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 4193: ioffset=0;
4194: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.243 brouard 4195: /* ioffset=2+nagesqr+cptcovage; */
4196: ioffset=2+nagesqr;
1.232 brouard 4197: /* Fixed */
1.224 brouard 4198: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 4199: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
1.311 brouard 4200: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */
1.232 brouard 4201: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, only V1 is fixed (k=6)*/
4202: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
4203: /* cov[2+6]=covar[Tvar[6]][i]; */
4204: /* cov[2+6]=covar[2][i]; V2 */
4205: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
4206: /* cov[2+7]=covar[Tvar[7]][i]; */
4207: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
4208: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
4209: /* cov[2+9]=covar[Tvar[9]][i]; */
4210: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 4211: }
1.232 brouard 4212: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
4213: /* 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?)*\/ */
4214: /* } */
1.231 brouard 4215: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
4216: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
4217: /* } */
1.225 brouard 4218:
1.233 brouard 4219:
4220: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.232 brouard 4221: /* Wave varying (but not age varying) */
4222: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 4223: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
4224: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
4225: }
1.232 brouard 4226: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
1.242 brouard 4227: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4228: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
4229: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
4230: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
4231: /* printf(" i=%d,mi=%d,itv=%d,TmodelInvind[itv]=%d,cotvar[mw[mi][i]][TmodelInvind[itv]][i]=%f\n", i, mi, itv, TmodelInvind[itv],cotvar[mw[mi][i]][TmodelInvind[itv]][i]); */
1.232 brouard 4232: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 4233: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4234: /* /\* 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]); *\/ */
4235: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 4236: /* } */
1.126 brouard 4237: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 4238: for (j=1;j<=nlstate+ndeath;j++){
4239: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4240: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4241: }
1.214 brouard 4242:
4243: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4244: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
4245: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 4246: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 4247: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
4248: and mw[mi+1][i]. dh depends on stepm.*/
4249: newm=savm;
1.247 brouard 4250: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 4251: cov[2]=agexact;
4252: if(nagesqr==1)
4253: cov[3]= agexact*agexact;
4254: for (kk=1; kk<=cptcovage;kk++) {
4255: if(!FixedV[Tvar[Tage[kk]]])
4256: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4257: else
4258: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
4259: }
4260: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
4261: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
4262: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4263: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4264: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
4265: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
4266: savm=oldm;
4267: oldm=newm;
1.126 brouard 4268: } /* end mult */
4269:
4270: s1=s[mw[mi][i]][i];
4271: s2=s[mw[mi+1][i]][i];
1.217 brouard 4272: /* if(s2==-1){ */
1.268 brouard 4273: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 4274: /* /\* exit(1); *\/ */
4275: /* } */
1.126 brouard 4276: bbh=(double)bh[mi][i]/(double)stepm;
4277: /* bias is positive if real duration
4278: * is higher than the multiple of stepm and negative otherwise.
4279: */
4280: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 4281: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4282: } else if ( s2==-1 ) { /* alive */
1.242 brouard 4283: for (j=1,survp=0. ; j<=nlstate; j++)
4284: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4285: lli= log(survp);
1.126 brouard 4286: }else if (mle==1){
1.242 brouard 4287: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 4288: } else if(mle==2){
1.242 brouard 4289: 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 4290: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 4291: 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 4292: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 4293: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 4294: } else{ /* mle=0 back to 1 */
1.242 brouard 4295: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4296: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 4297: } /* End of if */
4298: ipmx +=1;
4299: sw += weight[i];
4300: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.132 brouard 4301: /*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]); */
1.126 brouard 4302: if(globpr){
1.246 brouard 4303: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 4304: %11.6f %11.6f %11.6f ", \
1.242 brouard 4305: 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 4306: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.242 brouard 4307: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
4308: llt +=ll[k]*gipmx/gsw;
4309: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
4310: }
4311: fprintf(ficresilk," %10.6f\n", -llt);
1.126 brouard 4312: }
1.232 brouard 4313: } /* end of wave */
4314: } /* end of individual */
4315: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
4316: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
4317: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4318: if(globpr==0){ /* First time we count the contributions and weights */
4319: gipmx=ipmx;
4320: gsw=sw;
4321: }
4322: return -l;
1.126 brouard 4323: }
4324:
4325:
4326: /*************** function likelione ***********/
1.292 brouard 4327: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 4328: {
4329: /* This routine should help understanding what is done with
4330: the selection of individuals/waves and
4331: to check the exact contribution to the likelihood.
4332: Plotting could be done.
4333: */
4334: int k;
4335:
4336: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 4337: strcpy(fileresilk,"ILK_");
1.202 brouard 4338: strcat(fileresilk,fileresu);
1.126 brouard 4339: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
4340: printf("Problem with resultfile: %s\n", fileresilk);
4341: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
4342: }
1.214 brouard 4343: 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");
4344: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 4345: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
4346: for(k=1; k<=nlstate; k++)
4347: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
4348: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n");
4349: }
4350:
1.292 brouard 4351: *fretone=(*func)(p);
1.126 brouard 4352: if(*globpri !=0){
4353: fclose(ficresilk);
1.205 brouard 4354: if (mle ==0)
4355: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
4356: else if(mle >=1)
4357: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
4358: 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 4359: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 4360:
4361: for (k=1; k<= nlstate ; k++) {
1.211 brouard 4362: 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> \
1.208 brouard 4363: <img src=\"%s-p%dj.png\">",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
4364: }
1.207 brouard 4365: 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> \
1.204 brouard 4366: <img src=\"%s-ori.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4367: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.204 brouard 4368: <img src=\"%s-dest.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4369: fflush(fichtm);
1.205 brouard 4370: }
1.126 brouard 4371: return;
4372: }
4373:
4374:
4375: /*********** Maximum Likelihood Estimation ***************/
4376:
4377: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
4378: {
1.319 brouard 4379: int i,j,k, jk, jkk=0, iter=0;
1.126 brouard 4380: double **xi;
4381: double fret;
4382: double fretone; /* Only one call to likelihood */
4383: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 4384:
4385: #ifdef NLOPT
4386: int creturn;
4387: nlopt_opt opt;
4388: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
4389: double *lb;
4390: double minf; /* the minimum objective value, upon return */
4391: double * p1; /* Shifted parameters from 0 instead of 1 */
4392: myfunc_data dinst, *d = &dinst;
4393: #endif
4394:
4395:
1.126 brouard 4396: xi=matrix(1,npar,1,npar);
4397: for (i=1;i<=npar;i++)
4398: for (j=1;j<=npar;j++)
4399: xi[i][j]=(i==j ? 1.0 : 0.0);
4400: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 4401: strcpy(filerespow,"POW_");
1.126 brouard 4402: strcat(filerespow,fileres);
4403: if((ficrespow=fopen(filerespow,"w"))==NULL) {
4404: printf("Problem with resultfile: %s\n", filerespow);
4405: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
4406: }
4407: fprintf(ficrespow,"# Powell\n# iter -2*LL");
4408: for (i=1;i<=nlstate;i++)
4409: for(j=1;j<=nlstate+ndeath;j++)
4410: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
4411: fprintf(ficrespow,"\n");
1.162 brouard 4412: #ifdef POWELL
1.319 brouard 4413: #ifdef LINMINORIGINAL
4414: #else /* LINMINORIGINAL */
4415:
4416: flatdir=ivector(1,npar);
4417: for (j=1;j<=npar;j++) flatdir[j]=0;
4418: #endif /*LINMINORIGINAL */
4419:
4420: #ifdef FLATSUP
4421: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4422: /* reorganizing p by suppressing flat directions */
4423: for(i=1, jk=1; i <=nlstate; i++){
4424: for(k=1; k <=(nlstate+ndeath); k++){
4425: if (k != i) {
4426: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4427: if(flatdir[jk]==1){
4428: printf(" To be skipped %d%d flatdir[%d]=%d ",i,k,jk, flatdir[jk]);
4429: }
4430: for(j=1; j <=ncovmodel; j++){
4431: printf("%12.7f ",p[jk]);
4432: jk++;
4433: }
4434: printf("\n");
4435: }
4436: }
4437: }
4438: /* skipping */
4439: /* for(i=1, jk=1, jkk=1;(flatdir[jk]==0)&& (i <=nlstate); i++){ */
4440: for(i=1, jk=1, jkk=1;i <=nlstate; i++){
4441: for(k=1; k <=(nlstate+ndeath); k++){
4442: if (k != i) {
4443: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4444: if(flatdir[jk]==1){
4445: printf(" To be skipped %d%d flatdir[%d]=%d jk=%d p[%d] ",i,k,jk, flatdir[jk],jk, jk);
4446: for(j=1; j <=ncovmodel; jk++,j++){
4447: printf(" p[%d]=%12.7f",jk, p[jk]);
4448: /*q[jjk]=p[jk];*/
4449: }
4450: }else{
4451: printf(" To be kept %d%d flatdir[%d]=%d jk=%d q[%d]=p[%d] ",i,k,jk, flatdir[jk],jk, jkk, jk);
4452: for(j=1; j <=ncovmodel; jk++,jkk++,j++){
4453: printf(" p[%d]=%12.7f=q[%d]",jk, p[jk],jkk);
4454: /*q[jjk]=p[jk];*/
4455: }
4456: }
4457: printf("\n");
4458: }
4459: fflush(stdout);
4460: }
4461: }
4462: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4463: #else /* FLATSUP */
1.126 brouard 4464: powell(p,xi,npar,ftol,&iter,&fret,func);
1.319 brouard 4465: #endif /* FLATSUP */
4466:
4467: #ifdef LINMINORIGINAL
4468: #else
4469: free_ivector(flatdir,1,npar);
4470: #endif /* LINMINORIGINAL*/
4471: #endif /* POWELL */
1.126 brouard 4472:
1.162 brouard 4473: #ifdef NLOPT
4474: #ifdef NEWUOA
4475: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
4476: #else
4477: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
4478: #endif
4479: lb=vector(0,npar-1);
4480: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
4481: nlopt_set_lower_bounds(opt, lb);
4482: nlopt_set_initial_step1(opt, 0.1);
4483:
4484: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
4485: d->function = func;
4486: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
4487: nlopt_set_min_objective(opt, myfunc, d);
4488: nlopt_set_xtol_rel(opt, ftol);
4489: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
4490: printf("nlopt failed! %d\n",creturn);
4491: }
4492: else {
4493: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
4494: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
4495: iter=1; /* not equal */
4496: }
4497: nlopt_destroy(opt);
4498: #endif
1.319 brouard 4499: #ifdef FLATSUP
4500: /* npared = npar -flatd/ncovmodel; */
4501: /* xired= matrix(1,npared,1,npared); */
4502: /* paramred= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); */
4503: /* powell(pred,xired,npared,ftol,&iter,&fret,flatdir,func); */
4504: /* free_matrix(xire,1,npared,1,npared); */
4505: #else /* FLATSUP */
4506: #endif /* FLATSUP */
1.126 brouard 4507: free_matrix(xi,1,npar,1,npar);
4508: fclose(ficrespow);
1.203 brouard 4509: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
4510: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 4511: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 4512:
4513: }
4514:
4515: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 4516: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 4517: {
4518: double **a,**y,*x,pd;
1.203 brouard 4519: /* double **hess; */
1.164 brouard 4520: int i, j;
1.126 brouard 4521: int *indx;
4522:
4523: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 4524: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 4525: void lubksb(double **a, int npar, int *indx, double b[]) ;
4526: void ludcmp(double **a, int npar, int *indx, double *d) ;
4527: double gompertz(double p[]);
1.203 brouard 4528: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 4529:
4530: printf("\nCalculation of the hessian matrix. Wait...\n");
4531: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
4532: for (i=1;i<=npar;i++){
1.203 brouard 4533: printf("%d-",i);fflush(stdout);
4534: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 4535:
4536: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
4537:
4538: /* printf(" %f ",p[i]);
4539: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
4540: }
4541:
4542: for (i=1;i<=npar;i++) {
4543: for (j=1;j<=npar;j++) {
4544: if (j>i) {
1.203 brouard 4545: printf(".%d-%d",i,j);fflush(stdout);
4546: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
4547: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 4548:
4549: hess[j][i]=hess[i][j];
4550: /*printf(" %lf ",hess[i][j]);*/
4551: }
4552: }
4553: }
4554: printf("\n");
4555: fprintf(ficlog,"\n");
4556:
4557: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
4558: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
4559:
4560: a=matrix(1,npar,1,npar);
4561: y=matrix(1,npar,1,npar);
4562: x=vector(1,npar);
4563: indx=ivector(1,npar);
4564: for (i=1;i<=npar;i++)
4565: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
4566: ludcmp(a,npar,indx,&pd);
4567:
4568: for (j=1;j<=npar;j++) {
4569: for (i=1;i<=npar;i++) x[i]=0;
4570: x[j]=1;
4571: lubksb(a,npar,indx,x);
4572: for (i=1;i<=npar;i++){
4573: matcov[i][j]=x[i];
4574: }
4575: }
4576:
4577: printf("\n#Hessian matrix#\n");
4578: fprintf(ficlog,"\n#Hessian matrix#\n");
4579: for (i=1;i<=npar;i++) {
4580: for (j=1;j<=npar;j++) {
1.203 brouard 4581: printf("%.6e ",hess[i][j]);
4582: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 4583: }
4584: printf("\n");
4585: fprintf(ficlog,"\n");
4586: }
4587:
1.203 brouard 4588: /* printf("\n#Covariance matrix#\n"); */
4589: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
4590: /* for (i=1;i<=npar;i++) { */
4591: /* for (j=1;j<=npar;j++) { */
4592: /* printf("%.6e ",matcov[i][j]); */
4593: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
4594: /* } */
4595: /* printf("\n"); */
4596: /* fprintf(ficlog,"\n"); */
4597: /* } */
4598:
1.126 brouard 4599: /* Recompute Inverse */
1.203 brouard 4600: /* for (i=1;i<=npar;i++) */
4601: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
4602: /* ludcmp(a,npar,indx,&pd); */
4603:
4604: /* printf("\n#Hessian matrix recomputed#\n"); */
4605:
4606: /* for (j=1;j<=npar;j++) { */
4607: /* for (i=1;i<=npar;i++) x[i]=0; */
4608: /* x[j]=1; */
4609: /* lubksb(a,npar,indx,x); */
4610: /* for (i=1;i<=npar;i++){ */
4611: /* y[i][j]=x[i]; */
4612: /* printf("%.3e ",y[i][j]); */
4613: /* fprintf(ficlog,"%.3e ",y[i][j]); */
4614: /* } */
4615: /* printf("\n"); */
4616: /* fprintf(ficlog,"\n"); */
4617: /* } */
4618:
4619: /* Verifying the inverse matrix */
4620: #ifdef DEBUGHESS
4621: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 4622:
1.203 brouard 4623: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
4624: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 4625:
4626: for (j=1;j<=npar;j++) {
4627: for (i=1;i<=npar;i++){
1.203 brouard 4628: printf("%.2f ",y[i][j]);
4629: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 4630: }
4631: printf("\n");
4632: fprintf(ficlog,"\n");
4633: }
1.203 brouard 4634: #endif
1.126 brouard 4635:
4636: free_matrix(a,1,npar,1,npar);
4637: free_matrix(y,1,npar,1,npar);
4638: free_vector(x,1,npar);
4639: free_ivector(indx,1,npar);
1.203 brouard 4640: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 4641:
4642:
4643: }
4644:
4645: /*************** hessian matrix ****************/
4646: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 4647: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 4648: int i;
4649: int l=1, lmax=20;
1.203 brouard 4650: double k1,k2, res, fx;
1.132 brouard 4651: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 4652: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
4653: int k=0,kmax=10;
4654: double l1;
4655:
4656: fx=func(x);
4657: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 4658: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 4659: l1=pow(10,l);
4660: delts=delt;
4661: for(k=1 ; k <kmax; k=k+1){
4662: delt = delta*(l1*k);
4663: p2[theta]=x[theta] +delt;
1.145 brouard 4664: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 4665: p2[theta]=x[theta]-delt;
4666: k2=func(p2)-fx;
4667: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 4668: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 4669:
1.203 brouard 4670: #ifdef DEBUGHESSII
1.126 brouard 4671: 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);
4672: 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);
4673: #endif
4674: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
4675: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
4676: k=kmax;
4677: }
4678: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 4679: k=kmax; l=lmax*10;
1.126 brouard 4680: }
4681: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
4682: delts=delt;
4683: }
1.203 brouard 4684: } /* End loop k */
1.126 brouard 4685: }
4686: delti[theta]=delts;
4687: return res;
4688:
4689: }
4690:
1.203 brouard 4691: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 4692: {
4693: int i;
1.164 brouard 4694: int l=1, lmax=20;
1.126 brouard 4695: double k1,k2,k3,k4,res,fx;
1.132 brouard 4696: double p2[MAXPARM+1];
1.203 brouard 4697: int k, kmax=1;
4698: double v1, v2, cv12, lc1, lc2;
1.208 brouard 4699:
4700: int firstime=0;
1.203 brouard 4701:
1.126 brouard 4702: fx=func(x);
1.203 brouard 4703: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 4704: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 4705: p2[thetai]=x[thetai]+delti[thetai]*k;
4706: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4707: k1=func(p2)-fx;
4708:
1.203 brouard 4709: p2[thetai]=x[thetai]+delti[thetai]*k;
4710: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4711: k2=func(p2)-fx;
4712:
1.203 brouard 4713: p2[thetai]=x[thetai]-delti[thetai]*k;
4714: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4715: k3=func(p2)-fx;
4716:
1.203 brouard 4717: p2[thetai]=x[thetai]-delti[thetai]*k;
4718: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4719: k4=func(p2)-fx;
1.203 brouard 4720: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
4721: if(k1*k2*k3*k4 <0.){
1.208 brouard 4722: firstime=1;
1.203 brouard 4723: kmax=kmax+10;
1.208 brouard 4724: }
4725: if(kmax >=10 || firstime ==1){
1.246 brouard 4726: 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);
4727: 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 4728: 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);
4729: 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);
4730: }
4731: #ifdef DEBUGHESSIJ
4732: v1=hess[thetai][thetai];
4733: v2=hess[thetaj][thetaj];
4734: cv12=res;
4735: /* Computing eigen value of Hessian matrix */
4736: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4737: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4738: if ((lc2 <0) || (lc1 <0) ){
4739: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4740: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4741: 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);
4742: 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);
4743: }
1.126 brouard 4744: #endif
4745: }
4746: return res;
4747: }
4748:
1.203 brouard 4749: /* Not done yet: Was supposed to fix if not exactly at the maximum */
4750: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
4751: /* { */
4752: /* int i; */
4753: /* int l=1, lmax=20; */
4754: /* double k1,k2,k3,k4,res,fx; */
4755: /* double p2[MAXPARM+1]; */
4756: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
4757: /* int k=0,kmax=10; */
4758: /* double l1; */
4759:
4760: /* fx=func(x); */
4761: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
4762: /* l1=pow(10,l); */
4763: /* delts=delt; */
4764: /* for(k=1 ; k <kmax; k=k+1){ */
4765: /* delt = delti*(l1*k); */
4766: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
4767: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4768: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4769: /* k1=func(p2)-fx; */
4770:
4771: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4772: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4773: /* k2=func(p2)-fx; */
4774:
4775: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4776: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4777: /* k3=func(p2)-fx; */
4778:
4779: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4780: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4781: /* k4=func(p2)-fx; */
4782: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
4783: /* #ifdef DEBUGHESSIJ */
4784: /* 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); */
4785: /* 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); */
4786: /* #endif */
4787: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
4788: /* k=kmax; */
4789: /* } */
4790: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
4791: /* k=kmax; l=lmax*10; */
4792: /* } */
4793: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
4794: /* delts=delt; */
4795: /* } */
4796: /* } /\* End loop k *\/ */
4797: /* } */
4798: /* delti[theta]=delts; */
4799: /* return res; */
4800: /* } */
4801:
4802:
1.126 brouard 4803: /************** Inverse of matrix **************/
4804: void ludcmp(double **a, int n, int *indx, double *d)
4805: {
4806: int i,imax,j,k;
4807: double big,dum,sum,temp;
4808: double *vv;
4809:
4810: vv=vector(1,n);
4811: *d=1.0;
4812: for (i=1;i<=n;i++) {
4813: big=0.0;
4814: for (j=1;j<=n;j++)
4815: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 4816: if (big == 0.0){
4817: printf(" Singular Hessian matrix at row %d:\n",i);
4818: for (j=1;j<=n;j++) {
4819: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
4820: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
4821: }
4822: fflush(ficlog);
4823: fclose(ficlog);
4824: nrerror("Singular matrix in routine ludcmp");
4825: }
1.126 brouard 4826: vv[i]=1.0/big;
4827: }
4828: for (j=1;j<=n;j++) {
4829: for (i=1;i<j;i++) {
4830: sum=a[i][j];
4831: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
4832: a[i][j]=sum;
4833: }
4834: big=0.0;
4835: for (i=j;i<=n;i++) {
4836: sum=a[i][j];
4837: for (k=1;k<j;k++)
4838: sum -= a[i][k]*a[k][j];
4839: a[i][j]=sum;
4840: if ( (dum=vv[i]*fabs(sum)) >= big) {
4841: big=dum;
4842: imax=i;
4843: }
4844: }
4845: if (j != imax) {
4846: for (k=1;k<=n;k++) {
4847: dum=a[imax][k];
4848: a[imax][k]=a[j][k];
4849: a[j][k]=dum;
4850: }
4851: *d = -(*d);
4852: vv[imax]=vv[j];
4853: }
4854: indx[j]=imax;
4855: if (a[j][j] == 0.0) a[j][j]=TINY;
4856: if (j != n) {
4857: dum=1.0/(a[j][j]);
4858: for (i=j+1;i<=n;i++) a[i][j] *= dum;
4859: }
4860: }
4861: free_vector(vv,1,n); /* Doesn't work */
4862: ;
4863: }
4864:
4865: void lubksb(double **a, int n, int *indx, double b[])
4866: {
4867: int i,ii=0,ip,j;
4868: double sum;
4869:
4870: for (i=1;i<=n;i++) {
4871: ip=indx[i];
4872: sum=b[ip];
4873: b[ip]=b[i];
4874: if (ii)
4875: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
4876: else if (sum) ii=i;
4877: b[i]=sum;
4878: }
4879: for (i=n;i>=1;i--) {
4880: sum=b[i];
4881: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
4882: b[i]=sum/a[i][i];
4883: }
4884: }
4885:
4886: void pstamp(FILE *fichier)
4887: {
1.196 brouard 4888: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 4889: }
4890:
1.297 brouard 4891: void date2dmy(double date,double *day, double *month, double *year){
4892: double yp=0., yp1=0., yp2=0.;
4893:
4894: yp1=modf(date,&yp);/* extracts integral of date in yp and
4895: fractional in yp1 */
4896: *year=yp;
4897: yp2=modf((yp1*12),&yp);
4898: *month=yp;
4899: yp1=modf((yp2*30.5),&yp);
4900: *day=yp;
4901: if(*day==0) *day=1;
4902: if(*month==0) *month=1;
4903: }
4904:
1.253 brouard 4905:
4906:
1.126 brouard 4907: /************ Frequencies ********************/
1.251 brouard 4908: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 4909: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
4910: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 4911: { /* Some frequencies as well as proposing some starting values */
1.332 brouard 4912: /* Frequencies of any combination of dummy covariate used in the model equation */
1.265 brouard 4913: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 4914: int iind=0, iage=0;
4915: int mi; /* Effective wave */
4916: int first;
4917: double ***freq; /* Frequencies */
1.268 brouard 4918: 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 */
4919: 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 4920: double *meanq, *stdq, *idq;
1.226 brouard 4921: double **meanqt;
4922: double *pp, **prop, *posprop, *pospropt;
4923: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
4924: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
4925: double agebegin, ageend;
4926:
4927: pp=vector(1,nlstate);
1.251 brouard 4928: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4929: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
4930: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
4931: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
4932: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 4933: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 4934: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 4935: meanqt=matrix(1,lastpass,1,nqtveff);
4936: strcpy(fileresp,"P_");
4937: strcat(fileresp,fileresu);
4938: /*strcat(fileresphtm,fileresu);*/
4939: if((ficresp=fopen(fileresp,"w"))==NULL) {
4940: printf("Problem with prevalence resultfile: %s\n", fileresp);
4941: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
4942: exit(0);
4943: }
1.240 brouard 4944:
1.226 brouard 4945: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
4946: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
4947: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4948: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4949: fflush(ficlog);
4950: exit(70);
4951: }
4952: else{
4953: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 4954: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4955: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4956: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4957: }
1.319 brouard 4958: 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 4959:
1.226 brouard 4960: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
4961: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
4962: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4963: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4964: fflush(ficlog);
4965: exit(70);
1.240 brouard 4966: } else{
1.226 brouard 4967: 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 4968: ,<hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4969: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4970: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4971: }
1.319 brouard 4972: 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 4973:
1.253 brouard 4974: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
4975: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 4976: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4977: j1=0;
1.126 brouard 4978:
1.227 brouard 4979: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
1.334 ! brouard 4980: j=cptcoveff; /* Only dummy covariates used in the model */
1.330 brouard 4981: /* j=cptcovn; /\* Only dummy covariates of the model *\/ */
1.226 brouard 4982: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 4983:
4984:
1.226 brouard 4985: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
4986: reference=low_education V1=0,V2=0
4987: med_educ V1=1 V2=0,
4988: high_educ V1=0 V2=1
1.330 brouard 4989: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcovn
1.226 brouard 4990: */
1.249 brouard 4991: dateintsum=0;
4992: k2cpt=0;
4993:
1.253 brouard 4994: if(cptcoveff == 0 )
1.265 brouard 4995: nl=1; /* Constant and age model only */
1.253 brouard 4996: else
4997: nl=2;
1.265 brouard 4998:
4999: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
5000: /* Loop on nj=1 or 2 if dummy covariates j!=0
1.330 brouard 5001: * Loop on j1(1 to 2**cptcovn) covariate combination
1.265 brouard 5002: * freq[s1][s2][iage] =0.
5003: * Loop on iind
5004: * ++freq[s1][s2][iage] weighted
5005: * end iind
5006: * if covariate and j!0
5007: * headers Variable on one line
5008: * endif cov j!=0
5009: * header of frequency table by age
5010: * Loop on age
5011: * pp[s1]+=freq[s1][s2][iage] weighted
5012: * pos+=freq[s1][s2][iage] weighted
5013: * Loop on s1 initial state
5014: * fprintf(ficresp
5015: * end s1
5016: * end age
5017: * if j!=0 computes starting values
5018: * end compute starting values
5019: * end j1
5020: * end nl
5021: */
1.253 brouard 5022: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
5023: if(nj==1)
5024: j=0; /* First pass for the constant */
1.265 brouard 5025: else{
1.330 brouard 5026: j=cptcovs; /* Other passes for the covariate values */
1.265 brouard 5027: }
1.251 brouard 5028: first=1;
1.332 brouard 5029: 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 5030: posproptt=0.;
1.330 brouard 5031: /*printf("cptcovn=%d Tvaraff=%d", cptcovn,Tvaraff[1]);
1.251 brouard 5032: scanf("%d", i);*/
5033: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 5034: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 5035: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 5036: freq[i][s2][m]=0;
1.251 brouard 5037:
5038: for (i=1; i<=nlstate; i++) {
1.240 brouard 5039: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 5040: prop[i][m]=0;
5041: posprop[i]=0;
5042: pospropt[i]=0;
5043: }
1.283 brouard 5044: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 5045: idq[z1]=0.;
5046: meanq[z1]=0.;
5047: stdq[z1]=0.;
1.283 brouard 5048: }
5049: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 5050: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 5051: /* meanqt[m][z1]=0.; */
5052: /* } */
5053: /* } */
1.251 brouard 5054: /* dateintsum=0; */
5055: /* k2cpt=0; */
5056:
1.265 brouard 5057: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 5058: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
5059: bool=1;
5060: if(j !=0){
5061: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
1.330 brouard 5062: if (cptcovn >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
5063: for (z1=1; z1<=cptcovn; z1++) { /* loops on covariates in the model */
1.251 brouard 5064: /* if(Tvaraff[z1] ==-20){ */
5065: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
5066: /* }else if(Tvaraff[z1] ==-10){ */
5067: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
1.330 brouard 5068: /* }else */ /* TODO TODO codtabm(j1,z1) or codtabm(j1,Tvaraff[z1]]z1)*/
1.332 brouard 5069: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]){ /* for combination j1 of covariates */
1.265 brouard 5070: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 5071: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
1.332 brouard 5072: /* 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", */
5073: /* bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),*/
5074: /* j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
1.251 brouard 5075: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
5076: } /* Onlyf fixed */
5077: } /* end z1 */
5078: } /* cptcovn > 0 */
5079: } /* end any */
5080: }/* end j==0 */
1.265 brouard 5081: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 5082: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 5083: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 5084: m=mw[mi][iind];
5085: if(j!=0){
5086: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
1.330 brouard 5087: for (z1=1; z1<=cptcovn; z1++) {
1.251 brouard 5088: if( Fixed[Tmodelind[z1]]==1){
5089: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
1.332 brouard 5090: 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 5091: value is -1, we don't select. It differs from the
5092: constant and age model which counts them. */
5093: bool=0; /* not selected */
5094: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
1.334 ! brouard 5095: /* i1=Tvaraff[z1]; */
! 5096: /* i2=TnsdVar[i1]; */
! 5097: /* i3=nbcode[i1][i2]; */
! 5098: /* i4=covar[i1][iind]; */
! 5099: /* if(i4 != i3){ */
! 5100: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) { /* Bug valgrind */
1.251 brouard 5101: bool=0;
5102: }
5103: }
5104: }
5105: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
5106: } /* end j==0 */
5107: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 5108: if(bool==1){ /*Selected */
1.251 brouard 5109: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
5110: and mw[mi+1][iind]. dh depends on stepm. */
5111: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
5112: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
5113: if(m >=firstpass && m <=lastpass){
5114: k2=anint[m][iind]+(mint[m][iind]/12.);
5115: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
5116: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
5117: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
5118: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
5119: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
5120: if (m<lastpass) {
5121: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
5122: /* 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]); */
5123: if(s[m][iind]==-1)
5124: 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.));
5125: 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 5126: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean on known values only */
5127: if(!isnan(covar[ncovcol+z1][iind])){
1.332 brouard 5128: idq[z1]=idq[z1]+weight[iind];
5129: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
5130: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; *//*error*/
5131: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
1.311 brouard 5132: }
1.284 brouard 5133: }
1.251 brouard 5134: /* if((int)agev[m][iind] == 55) */
5135: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
5136: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
5137: 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 5138: }
1.251 brouard 5139: } /* end if between passes */
5140: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
5141: dateintsum=dateintsum+k2; /* on all covariates ?*/
5142: k2cpt++;
5143: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 5144: }
1.251 brouard 5145: }else{
5146: bool=1;
5147: }/* end bool 2 */
5148: } /* end m */
1.284 brouard 5149: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
5150: /* idq[z1]=idq[z1]+weight[iind]; */
5151: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
5152: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
5153: /* } */
1.251 brouard 5154: } /* end bool */
5155: } /* end iind = 1 to imx */
1.319 brouard 5156: /* prop[s][age] is fed for any initial and valid live state as well as
1.251 brouard 5157: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
5158:
5159:
5160: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.330 brouard 5161: if(cptcovn==0 && nj==1) /* no covariate and first pass */
1.265 brouard 5162: pstamp(ficresp);
1.330 brouard 5163: if (cptcovn>0 && j!=0){
1.265 brouard 5164: pstamp(ficresp);
1.251 brouard 5165: printf( "\n#********** Variable ");
5166: fprintf(ficresp, "\n#********** Variable ");
5167: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
5168: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
5169: fprintf(ficlog, "\n#********** Variable ");
1.330 brouard 5170: for (z1=1; z1<=cptcovs; z1++){
1.251 brouard 5171: if(!FixedV[Tvaraff[z1]]){
1.330 brouard 5172: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5173: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5174: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5175: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5176: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.250 brouard 5177: }else{
1.330 brouard 5178: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5179: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5180: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5181: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5182: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.251 brouard 5183: }
5184: }
5185: printf( "**********\n#");
5186: fprintf(ficresp, "**********\n#");
5187: fprintf(ficresphtm, "**********</h3>\n");
5188: fprintf(ficresphtmfr, "**********</h3>\n");
5189: fprintf(ficlog, "**********\n");
5190: }
1.284 brouard 5191: /*
5192: Printing means of quantitative variables if any
5193: */
5194: for (z1=1; z1<= nqfveff; z1++) {
1.311 brouard 5195: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.3g (weighted) individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.312 brouard 5196: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
1.284 brouard 5197: if(weightopt==1){
5198: printf(" Weighted mean and standard deviation of");
5199: fprintf(ficlog," Weighted mean and standard deviation of");
5200: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
5201: }
1.311 brouard 5202: /* mu = \frac{w x}{\sum w}
5203: var = \frac{\sum w (x-mu)^2}{\sum w} = \frac{w x^2}{\sum w} - mu^2
5204: */
5205: 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]));
5206: 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]));
5207: 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 5208: }
5209: /* for (z1=1; z1<= nqtveff; z1++) { */
5210: /* for(m=1;m<=lastpass;m++){ */
5211: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
5212: /* } */
5213: /* } */
1.283 brouard 5214:
1.251 brouard 5215: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.330 brouard 5216: if((cptcovn==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
1.265 brouard 5217: fprintf(ficresp, " Age");
1.332 brouard 5218: if(nj==2) for (z1=1; z1<=cptcovn; z1++) fprintf(ficresp, " V%d=%d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.251 brouard 5219: for(i=1; i<=nlstate;i++) {
1.330 brouard 5220: if((cptcovn==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 5221: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
5222: }
1.330 brouard 5223: if((cptcovn==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 5224: fprintf(ficresphtm, "\n");
5225:
5226: /* Header of frequency table by age */
5227: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
5228: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 5229: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 5230: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5231: if(s2!=0 && m!=0)
5232: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 5233: }
1.226 brouard 5234: }
1.251 brouard 5235: fprintf(ficresphtmfr, "\n");
5236:
5237: /* For each age */
5238: for(iage=iagemin; iage <= iagemax+3; iage++){
5239: fprintf(ficresphtm,"<tr>");
5240: if(iage==iagemax+1){
5241: fprintf(ficlog,"1");
5242: fprintf(ficresphtmfr,"<tr><th>0</th> ");
5243: }else if(iage==iagemax+2){
5244: fprintf(ficlog,"0");
5245: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
5246: }else if(iage==iagemax+3){
5247: fprintf(ficlog,"Total");
5248: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
5249: }else{
1.240 brouard 5250: if(first==1){
1.251 brouard 5251: first=0;
5252: printf("See log file for details...\n");
5253: }
5254: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
5255: fprintf(ficlog,"Age %d", iage);
5256: }
1.265 brouard 5257: for(s1=1; s1 <=nlstate ; s1++){
5258: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
5259: pp[s1] += freq[s1][m][iage];
1.251 brouard 5260: }
1.265 brouard 5261: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5262: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 5263: pos += freq[s1][m][iage];
5264: if(pp[s1]>=1.e-10){
1.251 brouard 5265: if(first==1){
1.265 brouard 5266: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5267: }
1.265 brouard 5268: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5269: }else{
5270: if(first==1)
1.265 brouard 5271: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
5272: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 5273: }
5274: }
5275:
1.265 brouard 5276: for(s1=1; s1 <=nlstate ; s1++){
5277: /* posprop[s1]=0; */
5278: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
5279: pp[s1] += freq[s1][m][iage];
5280: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
5281:
5282: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
5283: pos += pp[s1]; /* pos is the total number of transitions until this age */
5284: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
5285: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5286: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
5287: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5288: }
5289:
5290: /* Writing ficresp */
1.330 brouard 5291: if(cptcovn==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5292: if( iage <= iagemax){
5293: fprintf(ficresp," %d",iage);
5294: }
5295: }else if( nj==2){
5296: if( iage <= iagemax){
5297: fprintf(ficresp," %d",iage);
1.332 brouard 5298: for (z1=1; z1<=cptcovn; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.265 brouard 5299: }
1.240 brouard 5300: }
1.265 brouard 5301: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 5302: if(pos>=1.e-5){
1.251 brouard 5303: if(first==1)
1.265 brouard 5304: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
5305: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 5306: }else{
5307: if(first==1)
1.265 brouard 5308: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
5309: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 5310: }
5311: if( iage <= iagemax){
5312: if(pos>=1.e-5){
1.330 brouard 5313: if(cptcovn==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5314: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5315: }else if( nj==2){
5316: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5317: }
5318: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5319: /*probs[iage][s1][j1]= pp[s1]/pos;*/
5320: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
5321: } else{
1.330 brouard 5322: if((cptcovn==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
1.265 brouard 5323: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 5324: }
1.240 brouard 5325: }
1.265 brouard 5326: pospropt[s1] +=posprop[s1];
5327: } /* end loop s1 */
1.251 brouard 5328: /* pospropt=0.; */
1.265 brouard 5329: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 5330: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5331: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 5332: if(first==1){
1.265 brouard 5333: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5334: }
1.265 brouard 5335: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
5336: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5337: }
1.265 brouard 5338: if(s1!=0 && m!=0)
5339: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 5340: }
1.265 brouard 5341: } /* end loop s1 */
1.251 brouard 5342: posproptt=0.;
1.265 brouard 5343: for(s1=1; s1 <=nlstate; s1++){
5344: posproptt += pospropt[s1];
1.251 brouard 5345: }
5346: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 5347: fprintf(ficresphtm,"</tr>\n");
1.330 brouard 5348: if((cptcovn==0 && nj==1)|| nj==2 ) {
1.265 brouard 5349: if(iage <= iagemax)
5350: fprintf(ficresp,"\n");
1.240 brouard 5351: }
1.251 brouard 5352: if(first==1)
5353: printf("Others in log...\n");
5354: fprintf(ficlog,"\n");
5355: } /* end loop age iage */
1.265 brouard 5356:
1.251 brouard 5357: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 5358: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5359: if(posproptt < 1.e-5){
1.265 brouard 5360: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 5361: }else{
1.265 brouard 5362: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 5363: }
1.226 brouard 5364: }
1.251 brouard 5365: fprintf(ficresphtm,"</tr>\n");
5366: fprintf(ficresphtm,"</table>\n");
5367: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 5368: if(posproptt < 1.e-5){
1.251 brouard 5369: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
5370: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 5371: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
5372: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 5373: invalidvarcomb[j1]=1;
1.226 brouard 5374: }else{
1.251 brouard 5375: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced.</p>",j1);
5376: invalidvarcomb[j1]=0;
1.226 brouard 5377: }
1.251 brouard 5378: fprintf(ficresphtmfr,"</table>\n");
5379: fprintf(ficlog,"\n");
5380: if(j!=0){
5381: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 5382: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5383: for(k=1; k <=(nlstate+ndeath); k++){
5384: if (k != i) {
1.265 brouard 5385: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 5386: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 5387: if(j1==1){ /* All dummy covariates to zero */
5388: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
5389: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 5390: printf("%d%d ",i,k);
5391: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5392: 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]));
5393: 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]));
5394: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 5395: }
1.253 brouard 5396: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
5397: for(iage=iagemin; iage <= iagemax+3; iage++){
5398: x[iage]= (double)iage;
5399: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 5400: /* 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 5401: }
1.268 brouard 5402: /* Some are not finite, but linreg will ignore these ages */
5403: no=0;
1.253 brouard 5404: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 5405: pstart[s1]=b;
5406: pstart[s1-1]=a;
1.252 brouard 5407: }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 */
5408: 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]);
5409: 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 5410: 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 5411: printf("%d%d ",i,k);
5412: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5413: 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 5414: }else{ /* Other cases, like quantitative fixed or varying covariates */
5415: ;
5416: }
5417: /* printf("%12.7f )", param[i][jj][k]); */
5418: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5419: s1++;
1.251 brouard 5420: } /* end jj */
5421: } /* end k!= i */
5422: } /* end k */
1.265 brouard 5423: } /* end i, s1 */
1.251 brouard 5424: } /* end j !=0 */
5425: } /* end selected combination of covariate j1 */
5426: if(j==0){ /* We can estimate starting values from the occurences in each case */
5427: printf("#Freqsummary: Starting values for the constants:\n");
5428: fprintf(ficlog,"\n");
1.265 brouard 5429: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5430: for(k=1; k <=(nlstate+ndeath); k++){
5431: if (k != i) {
5432: printf("%d%d ",i,k);
5433: fprintf(ficlog,"%d%d ",i,k);
5434: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 5435: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 5436: if(jj==1){ /* Age has to be done */
1.265 brouard 5437: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
5438: 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]));
5439: 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 5440: }
5441: /* printf("%12.7f )", param[i][jj][k]); */
5442: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5443: s1++;
1.250 brouard 5444: }
1.251 brouard 5445: printf("\n");
5446: fprintf(ficlog,"\n");
1.250 brouard 5447: }
5448: }
1.284 brouard 5449: } /* end of state i */
1.251 brouard 5450: printf("#Freqsummary\n");
5451: fprintf(ficlog,"\n");
1.265 brouard 5452: for(s1=-1; s1 <=nlstate+ndeath; s1++){
5453: for(s2=-1; s2 <=nlstate+ndeath; s2++){
5454: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
5455: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5456: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5457: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
5458: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
5459: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 5460: /* } */
5461: }
1.265 brouard 5462: } /* end loop s1 */
1.251 brouard 5463:
5464: printf("\n");
5465: fprintf(ficlog,"\n");
5466: } /* end j=0 */
1.249 brouard 5467: } /* end j */
1.252 brouard 5468:
1.253 brouard 5469: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 5470: for(i=1, jk=1; i <=nlstate; i++){
5471: for(j=1; j <=nlstate+ndeath; j++){
5472: if(j!=i){
5473: /*ca[0]= k+'a'-1;ca[1]='\0';*/
5474: printf("%1d%1d",i,j);
5475: fprintf(ficparo,"%1d%1d",i,j);
5476: for(k=1; k<=ncovmodel;k++){
5477: /* printf(" %lf",param[i][j][k]); */
5478: /* fprintf(ficparo," %lf",param[i][j][k]); */
5479: p[jk]=pstart[jk];
5480: printf(" %f ",pstart[jk]);
5481: fprintf(ficparo," %f ",pstart[jk]);
5482: jk++;
5483: }
5484: printf("\n");
5485: fprintf(ficparo,"\n");
5486: }
5487: }
5488: }
5489: } /* end mle=-2 */
1.226 brouard 5490: dateintmean=dateintsum/k2cpt;
1.296 brouard 5491: date2dmy(dateintmean,&jintmean,&mintmean,&aintmean);
1.240 brouard 5492:
1.226 brouard 5493: fclose(ficresp);
5494: fclose(ficresphtm);
5495: fclose(ficresphtmfr);
1.283 brouard 5496: free_vector(idq,1,nqfveff);
1.226 brouard 5497: free_vector(meanq,1,nqfveff);
1.284 brouard 5498: free_vector(stdq,1,nqfveff);
1.226 brouard 5499: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 5500: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
5501: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 5502: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5503: free_vector(pospropt,1,nlstate);
5504: free_vector(posprop,1,nlstate);
1.251 brouard 5505: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5506: free_vector(pp,1,nlstate);
5507: /* End of freqsummary */
5508: }
1.126 brouard 5509:
1.268 brouard 5510: /* Simple linear regression */
5511: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
5512:
5513: /* y=a+bx regression */
5514: double sumx = 0.0; /* sum of x */
5515: double sumx2 = 0.0; /* sum of x**2 */
5516: double sumxy = 0.0; /* sum of x * y */
5517: double sumy = 0.0; /* sum of y */
5518: double sumy2 = 0.0; /* sum of y**2 */
5519: double sume2 = 0.0; /* sum of square or residuals */
5520: double yhat;
5521:
5522: double denom=0;
5523: int i;
5524: int ne=*no;
5525:
5526: for ( i=ifi, ne=0;i<=ila;i++) {
5527: if(!isfinite(x[i]) || !isfinite(y[i])){
5528: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5529: continue;
5530: }
5531: ne=ne+1;
5532: sumx += x[i];
5533: sumx2 += x[i]*x[i];
5534: sumxy += x[i] * y[i];
5535: sumy += y[i];
5536: sumy2 += y[i]*y[i];
5537: denom = (ne * sumx2 - sumx*sumx);
5538: /* 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); */
5539: }
5540:
5541: denom = (ne * sumx2 - sumx*sumx);
5542: if (denom == 0) {
5543: // vertical, slope m is infinity
5544: *b = INFINITY;
5545: *a = 0;
5546: if (r) *r = 0;
5547: return 1;
5548: }
5549:
5550: *b = (ne * sumxy - sumx * sumy) / denom;
5551: *a = (sumy * sumx2 - sumx * sumxy) / denom;
5552: if (r!=NULL) {
5553: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
5554: sqrt((sumx2 - sumx*sumx/ne) *
5555: (sumy2 - sumy*sumy/ne));
5556: }
5557: *no=ne;
5558: for ( i=ifi, ne=0;i<=ila;i++) {
5559: if(!isfinite(x[i]) || !isfinite(y[i])){
5560: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5561: continue;
5562: }
5563: ne=ne+1;
5564: yhat = y[i] - *a -*b* x[i];
5565: sume2 += yhat * yhat ;
5566:
5567: denom = (ne * sumx2 - sumx*sumx);
5568: /* 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); */
5569: }
5570: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
5571: *sa= *sb * sqrt(sumx2/ne);
5572:
5573: return 0;
5574: }
5575:
1.126 brouard 5576: /************ Prevalence ********************/
1.227 brouard 5577: 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)
5578: {
5579: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
5580: in each health status at the date of interview (if between dateprev1 and dateprev2).
5581: We still use firstpass and lastpass as another selection.
5582: */
1.126 brouard 5583:
1.227 brouard 5584: int i, m, jk, j1, bool, z1,j, iv;
5585: int mi; /* Effective wave */
5586: int iage;
5587: double agebegin, ageend;
5588:
5589: double **prop;
5590: double posprop;
5591: double y2; /* in fractional years */
5592: int iagemin, iagemax;
5593: int first; /** to stop verbosity which is redirected to log file */
5594:
5595: iagemin= (int) agemin;
5596: iagemax= (int) agemax;
5597: /*pp=vector(1,nlstate);*/
1.251 brouard 5598: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5599: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
5600: j1=0;
1.222 brouard 5601:
1.227 brouard 5602: /*j=cptcoveff;*/
5603: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 5604:
1.288 brouard 5605: first=0;
1.227 brouard 5606: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of covariate */
5607: for (i=1; i<=nlstate; i++)
1.251 brouard 5608: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 5609: prop[i][iage]=0.0;
5610: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
5611: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
5612: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
5613:
5614: for (i=1; i<=imx; i++) { /* Each individual */
5615: bool=1;
5616: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
5617: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
5618: m=mw[mi][i];
5619: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
5620: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
5621: for (z1=1; z1<=cptcoveff; z1++){
5622: if( Fixed[Tmodelind[z1]]==1){
5623: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
1.332 brouard 5624: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) /* iv=1 to ntv, right modality */
1.227 brouard 5625: bool=0;
5626: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
1.332 brouard 5627: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) {
1.227 brouard 5628: bool=0;
5629: }
5630: }
5631: if(bool==1){ /* Otherwise we skip that wave/person */
5632: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
5633: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
5634: if(m >=firstpass && m <=lastpass){
5635: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
5636: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
5637: if(agev[m][i]==0) agev[m][i]=iagemax+1;
5638: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 5639: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 5640: 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);
5641: exit(1);
5642: }
5643: if (s[m][i]>0 && s[m][i]<=nlstate) {
5644: /*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]]);*/
5645: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
5646: prop[s[m][i]][iagemax+3] += weight[i];
5647: } /* end valid statuses */
5648: } /* end selection of dates */
5649: } /* end selection of waves */
5650: } /* end bool */
5651: } /* end wave */
5652: } /* end individual */
5653: for(i=iagemin; i <= iagemax+3; i++){
5654: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
5655: posprop += prop[jk][i];
5656: }
5657:
5658: for(jk=1; jk <=nlstate ; jk++){
5659: if( i <= iagemax){
5660: if(posprop>=1.e-5){
5661: probs[i][jk][j1]= prop[jk][i]/posprop;
5662: } else{
1.288 brouard 5663: if(!first){
5664: first=1;
1.266 brouard 5665: 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]);
5666: }else{
1.288 brouard 5667: 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 5668: }
5669: }
5670: }
5671: }/* end jk */
5672: }/* end i */
1.222 brouard 5673: /*} *//* end i1 */
1.227 brouard 5674: } /* end j1 */
1.222 brouard 5675:
1.227 brouard 5676: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
5677: /*free_vector(pp,1,nlstate);*/
1.251 brouard 5678: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5679: } /* End of prevalence */
1.126 brouard 5680:
5681: /************* Waves Concatenation ***************/
5682:
5683: 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)
5684: {
1.298 brouard 5685: /* 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 5686: Death is a valid wave (if date is known).
5687: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
5688: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
1.298 brouard 5689: and mw[mi+1][i]. dh depends on stepm. s[m][i] exists for any wave from firstpass to lastpass
1.227 brouard 5690: */
1.126 brouard 5691:
1.224 brouard 5692: int i=0, mi=0, m=0, mli=0;
1.126 brouard 5693: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
5694: double sum=0., jmean=0.;*/
1.224 brouard 5695: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 5696: int j, k=0,jk, ju, jl;
5697: double sum=0.;
5698: first=0;
1.214 brouard 5699: firstwo=0;
1.217 brouard 5700: firsthree=0;
1.218 brouard 5701: firstfour=0;
1.164 brouard 5702: jmin=100000;
1.126 brouard 5703: jmax=-1;
5704: jmean=0.;
1.224 brouard 5705:
5706: /* Treating live states */
1.214 brouard 5707: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 5708: mi=0; /* First valid wave */
1.227 brouard 5709: mli=0; /* Last valid wave */
1.309 brouard 5710: m=firstpass; /* Loop on waves */
5711: while(s[m][i] <= nlstate){ /* a live state or unknown state */
1.227 brouard 5712: 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 */
5713: mli=m-1;/* mw[++mi][i]=m-1; */
5714: }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 5715: 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 5716: mli=m;
1.224 brouard 5717: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
5718: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 5719: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 5720: }
1.309 brouard 5721: else{ /* m = lastpass, eventual special issue with warning */
1.224 brouard 5722: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 5723: break;
1.224 brouard 5724: #else
1.317 brouard 5725: 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 5726: if(firsthree == 0){
1.302 brouard 5727: 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 5728: firsthree=1;
1.317 brouard 5729: }else if(firsthree >=1 && firsthree < 10){
5730: 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);
5731: firsthree++;
5732: }else if(firsthree == 10){
5733: printf("Information, too many Information flags: no more reported to log either\n");
5734: fprintf(ficlog,"Information, too many Information flags: no more reported to log either\n");
5735: firsthree++;
5736: }else{
5737: firsthree++;
1.227 brouard 5738: }
1.309 brouard 5739: mw[++mi][i]=m; /* Valid transition with unknown status */
1.227 brouard 5740: mli=m;
5741: }
5742: if(s[m][i]==-2){ /* Vital status is really unknown */
5743: nbwarn++;
1.309 brouard 5744: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified?not a transition */
1.227 brouard 5745: 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);
5746: 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);
5747: }
5748: break;
5749: }
5750: break;
1.224 brouard 5751: #endif
1.227 brouard 5752: }/* End m >= lastpass */
1.126 brouard 5753: }/* end while */
1.224 brouard 5754:
1.227 brouard 5755: /* 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 5756: /* After last pass */
1.224 brouard 5757: /* Treating death states */
1.214 brouard 5758: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 5759: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
5760: /* } */
1.126 brouard 5761: mi++; /* Death is another wave */
5762: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 5763: /* Only death is a correct wave */
1.126 brouard 5764: mw[mi][i]=m;
1.257 brouard 5765: } /* else not in a death state */
1.224 brouard 5766: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 5767: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 5768: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.309 brouard 5769: 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 5770: nbwarn++;
5771: if(firstfiv==0){
1.309 brouard 5772: 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 5773: firstfiv=1;
5774: }else{
1.309 brouard 5775: 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 5776: }
1.309 brouard 5777: s[m][i]=nlstate+1; /* Fixing the status as death. Be careful if multiple death states */
5778: }else{ /* Month of Death occured afer last wave month, potential bias */
1.227 brouard 5779: nberr++;
5780: if(firstwo==0){
1.309 brouard 5781: 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 5782: firstwo=1;
5783: }
1.309 brouard 5784: 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 5785: }
1.257 brouard 5786: }else{ /* if date of interview is unknown */
1.227 brouard 5787: /* death is known but not confirmed by death status at any wave */
5788: if(firstfour==0){
1.309 brouard 5789: 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 5790: firstfour=1;
5791: }
1.309 brouard 5792: 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 5793: }
1.224 brouard 5794: } /* end if date of death is known */
5795: #endif
1.309 brouard 5796: wav[i]=mi; /* mi should be the last effective wave (or mli), */
5797: /* wav[i]=mw[mi][i]; */
1.126 brouard 5798: if(mi==0){
5799: nbwarn++;
5800: if(first==0){
1.227 brouard 5801: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
5802: first=1;
1.126 brouard 5803: }
5804: if(first==1){
1.227 brouard 5805: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 5806: }
5807: } /* end mi==0 */
5808: } /* End individuals */
1.214 brouard 5809: /* wav and mw are no more changed */
1.223 brouard 5810:
1.317 brouard 5811: printf("Information, you have to check %d informations which haven't been logged!\n",firsthree);
5812: fprintf(ficlog,"Information, you have to check %d informations which haven't been logged!\n",firsthree);
5813:
5814:
1.126 brouard 5815: for(i=1; i<=imx; i++){
5816: for(mi=1; mi<wav[i];mi++){
5817: if (stepm <=0)
1.227 brouard 5818: dh[mi][i]=1;
1.126 brouard 5819: else{
1.260 brouard 5820: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 5821: if (agedc[i] < 2*AGESUP) {
5822: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
5823: if(j==0) j=1; /* Survives at least one month after exam */
5824: else if(j<0){
5825: nberr++;
5826: printf("Error! Negative delay (%d to death) between waves %d and %d of individual %ld at 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]);
5827: j=1; /* Temporary Dangerous patch */
5828: 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);
5829: fprintf(ficlog,"Error! Negative delay (%d to death) between waves %d and %d of individual %ld at 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]);
5830: 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);
5831: }
5832: k=k+1;
5833: if (j >= jmax){
5834: jmax=j;
5835: ijmax=i;
5836: }
5837: if (j <= jmin){
5838: jmin=j;
5839: ijmin=i;
5840: }
5841: sum=sum+j;
5842: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
5843: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
5844: }
5845: }
5846: else{
5847: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 5848: /* 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 5849:
1.227 brouard 5850: k=k+1;
5851: if (j >= jmax) {
5852: jmax=j;
5853: ijmax=i;
5854: }
5855: else if (j <= jmin){
5856: jmin=j;
5857: ijmin=i;
5858: }
5859: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
5860: /*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]);*/
5861: if(j<0){
5862: nberr++;
5863: printf("Error! Negative delay (%d) between waves %d and %d of individual %ld at 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]);
5864: fprintf(ficlog,"Error! Negative delay (%d) between waves %d and %d of individual %ld at 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]);
5865: }
5866: sum=sum+j;
5867: }
5868: jk= j/stepm;
5869: jl= j -jk*stepm;
5870: ju= j -(jk+1)*stepm;
5871: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
5872: if(jl==0){
5873: dh[mi][i]=jk;
5874: bh[mi][i]=0;
5875: }else{ /* We want a negative bias in order to only have interpolation ie
5876: * to avoid the price of an extra matrix product in likelihood */
5877: dh[mi][i]=jk+1;
5878: bh[mi][i]=ju;
5879: }
5880: }else{
5881: if(jl <= -ju){
5882: dh[mi][i]=jk;
5883: bh[mi][i]=jl; /* bias is positive if real duration
5884: * is higher than the multiple of stepm and negative otherwise.
5885: */
5886: }
5887: else{
5888: dh[mi][i]=jk+1;
5889: bh[mi][i]=ju;
5890: }
5891: if(dh[mi][i]==0){
5892: dh[mi][i]=1; /* At least one step */
5893: bh[mi][i]=ju; /* At least one step */
5894: /* 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);*/
5895: }
5896: } /* end if mle */
1.126 brouard 5897: }
5898: } /* end wave */
5899: }
5900: jmean=sum/k;
5901: 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 5902: 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 5903: }
1.126 brouard 5904:
5905: /*********** Tricode ****************************/
1.220 brouard 5906: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 5907: {
5908: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
5909: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
5910: * Boring subroutine which should only output nbcode[Tvar[j]][k]
5911: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
5912: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
5913: */
1.130 brouard 5914:
1.242 brouard 5915: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
5916: int modmaxcovj=0; /* Modality max of covariates j */
5917: int cptcode=0; /* Modality max of covariates j */
5918: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 5919:
5920:
1.242 brouard 5921: /* cptcoveff=0; */
5922: /* *cptcov=0; */
1.126 brouard 5923:
1.242 brouard 5924: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 5925: for (k=1; k <= maxncov; k++)
5926: for(j=1; j<=2; j++)
5927: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 5928:
1.242 brouard 5929: /* Loop on covariates without age and products and no quantitative variable */
5930: for (k=1; k<=cptcovt; k++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */
5931: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
5932: if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5933: switch(Fixed[k]) {
5934: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
1.311 brouard 5935: modmaxcovj=0;
5936: modmincovj=0;
1.242 brouard 5937: 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*/
5938: ij=(int)(covar[Tvar[k]][i]);
5939: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
5940: * If product of Vn*Vm, still boolean *:
5941: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
5942: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
5943: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
5944: modality of the nth covariate of individual i. */
5945: if (ij > modmaxcovj)
5946: modmaxcovj=ij;
5947: else if (ij < modmincovj)
5948: modmincovj=ij;
1.287 brouard 5949: if (ij <0 || ij >1 ){
1.311 brouard 5950: printf("ERROR, IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
5951: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
5952: fflush(ficlog);
5953: exit(1);
1.287 brouard 5954: }
5955: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 5956: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
5957: exit(1);
5958: }else
5959: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
5960: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
5961: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
5962: /* getting the maximum value of the modality of the covariate
5963: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
5964: female ies 1, then modmaxcovj=1.
5965: */
5966: } /* end for loop on individuals i */
5967: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5968: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5969: cptcode=modmaxcovj;
5970: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
5971: /*for (i=0; i<=cptcode; i++) {*/
5972: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
5973: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5974: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5975: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
5976: if( j != -1){
5977: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
5978: covariate for which somebody answered excluding
5979: undefined. Usually 2: 0 and 1. */
5980: }
5981: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
5982: covariate for which somebody answered including
5983: undefined. Usually 3: -1, 0 and 1. */
5984: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
5985: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
5986: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 5987:
1.242 brouard 5988: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
5989: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
5990: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
5991: /* modmincovj=3; modmaxcovj = 7; */
5992: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
5993: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
5994: /* defining two dummy variables: variables V1_1 and V1_2.*/
5995: /* nbcode[Tvar[j]][ij]=k; */
5996: /* nbcode[Tvar[j]][1]=0; */
5997: /* nbcode[Tvar[j]][2]=1; */
5998: /* nbcode[Tvar[j]][3]=2; */
5999: /* To be continued (not working yet). */
6000: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 6001:
6002: /* 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*/
6003: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
6004: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
6005: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
6006: /*, could be restored in the future */
6007: 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 6008: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
6009: break;
6010: }
6011: ij++;
1.287 brouard 6012: 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 6013: cptcode = ij; /* New max modality for covar j */
6014: } /* end of loop on modality i=-1 to 1 or more */
6015: break;
6016: case 1: /* Testing on varying covariate, could be simple and
6017: * should look at waves or product of fixed *
6018: * varying. No time to test -1, assuming 0 and 1 only */
6019: ij=0;
6020: for(i=0; i<=1;i++){
6021: nbcode[Tvar[k]][++ij]=i;
6022: }
6023: break;
6024: default:
6025: break;
6026: } /* end switch */
6027: } /* end dummy test */
1.334 ! brouard 6028: if(Dummy[k]==1 && Typevar[k] !=1){ /* Quantitative covariate and not age product */
1.311 brouard 6029: 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*/
6030: if(isnan(covar[Tvar[k]][i])){
6031: printf("ERROR, IMaCh doesn't treat fixed quantitative covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
6032: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
6033: fflush(ficlog);
6034: exit(1);
6035: }
6036: }
6037: }
1.287 brouard 6038: } /* 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 6039:
6040: for (k=-1; k< maxncov; k++) Ndum[k]=0;
6041: /* Look at fixed dummy (single or product) covariates to check empty modalities */
6042: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
6043: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
6044: 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 */
6045: 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 */
6046: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
6047: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
6048:
6049: ij=0;
6050: /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */
6051: for (k=1; k<= cptcovt; k++) { /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
6052: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
6053: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
6054: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy and non empty in the model */
6055: /* If product not in single variable we don't print results */
6056: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
6057: ++ij;/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, */
6058: 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*/
6059: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
6060: 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 */
6061: if(Fixed[k]!=0)
6062: anyvaryingduminmodel=1;
6063: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
6064: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
6065: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
6066: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
6067: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
6068: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
6069: }
6070: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
6071: /* ij--; */
6072: /* cptcoveff=ij; /\*Number of total covariates*\/ */
1.330 brouard 6073: *cptcov=ij; /* cptcov= Number of total real effective covariates: effective (used as cptcoveff in other functions)
1.242 brouard 6074: * because they can be excluded from the model and real
6075: * if in the model but excluded because missing values, but how to get k from ij?*/
6076: for(j=ij+1; j<= cptcovt; j++){
6077: Tvaraff[j]=0;
6078: Tmodelind[j]=0;
6079: }
6080: for(j=ntveff+1; j<= cptcovt; j++){
6081: TmodelInvind[j]=0;
6082: }
6083: /* To be sorted */
6084: ;
6085: }
1.126 brouard 6086:
1.145 brouard 6087:
1.126 brouard 6088: /*********** Health Expectancies ****************/
6089:
1.235 brouard 6090: 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 6091:
6092: {
6093: /* Health expectancies, no variances */
1.329 brouard 6094: /* cij is the combination in the list of combination of dummy covariates */
6095: /* strstart is a string of time at start of computing */
1.164 brouard 6096: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 6097: int nhstepma, nstepma; /* Decreasing with age */
6098: double age, agelim, hf;
6099: double ***p3mat;
6100: double eip;
6101:
1.238 brouard 6102: /* pstamp(ficreseij); */
1.126 brouard 6103: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
6104: fprintf(ficreseij,"# Age");
6105: for(i=1; i<=nlstate;i++){
6106: for(j=1; j<=nlstate;j++){
6107: fprintf(ficreseij," e%1d%1d ",i,j);
6108: }
6109: fprintf(ficreseij," e%1d. ",i);
6110: }
6111: fprintf(ficreseij,"\n");
6112:
6113:
6114: if(estepm < stepm){
6115: printf ("Problem %d lower than %d\n",estepm, stepm);
6116: }
6117: else hstepm=estepm;
6118: /* We compute the life expectancy from trapezoids spaced every estepm months
6119: * This is mainly to measure the difference between two models: for example
6120: * if stepm=24 months pijx are given only every 2 years and by summing them
6121: * we are calculating an estimate of the Life Expectancy assuming a linear
6122: * progression in between and thus overestimating or underestimating according
6123: * to the curvature of the survival function. If, for the same date, we
6124: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6125: * to compare the new estimate of Life expectancy with the same linear
6126: * hypothesis. A more precise result, taking into account a more precise
6127: * curvature will be obtained if estepm is as small as stepm. */
6128:
6129: /* For example we decided to compute the life expectancy with the smallest unit */
6130: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6131: nhstepm is the number of hstepm from age to agelim
6132: nstepm is the number of stepm from age to agelin.
1.270 brouard 6133: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 6134: and note for a fixed period like estepm months */
6135: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6136: survival function given by stepm (the optimization length). Unfortunately it
6137: means that if the survival funtion is printed only each two years of age and if
6138: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6139: results. So we changed our mind and took the option of the best precision.
6140: */
6141: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6142:
6143: agelim=AGESUP;
6144: /* If stepm=6 months */
6145: /* Computed by stepm unit matrices, product of hstepm matrices, stored
6146: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
6147:
6148: /* nhstepm age range expressed in number of stepm */
6149: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6150: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6151: /* if (stepm >= YEARM) hstepm=1;*/
6152: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6153: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6154:
6155: for (age=bage; age<=fage; age ++){
6156: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6157: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6158: /* if (stepm >= YEARM) hstepm=1;*/
6159: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
6160:
6161: /* If stepm=6 months */
6162: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6163: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
1.330 brouard 6164: /* 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 6165: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 6166:
6167: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6168:
6169: printf("%d|",(int)age);fflush(stdout);
6170: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6171:
6172: /* Computing expectancies */
6173: for(i=1; i<=nlstate;i++)
6174: for(j=1; j<=nlstate;j++)
6175: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6176: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
6177:
6178: /* 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]);*/
6179:
6180: }
6181:
6182: fprintf(ficreseij,"%3.0f",age );
6183: for(i=1; i<=nlstate;i++){
6184: eip=0;
6185: for(j=1; j<=nlstate;j++){
6186: eip +=eij[i][j][(int)age];
6187: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
6188: }
6189: fprintf(ficreseij,"%9.4f", eip );
6190: }
6191: fprintf(ficreseij,"\n");
6192:
6193: }
6194: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6195: printf("\n");
6196: fprintf(ficlog,"\n");
6197:
6198: }
6199:
1.235 brouard 6200: 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 6201:
6202: {
6203: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 6204: to initial status i, ei. .
1.126 brouard 6205: */
6206: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
6207: int nhstepma, nstepma; /* Decreasing with age */
6208: double age, agelim, hf;
6209: double ***p3matp, ***p3matm, ***varhe;
6210: double **dnewm,**doldm;
6211: double *xp, *xm;
6212: double **gp, **gm;
6213: double ***gradg, ***trgradg;
6214: int theta;
6215:
6216: double eip, vip;
6217:
6218: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
6219: xp=vector(1,npar);
6220: xm=vector(1,npar);
6221: dnewm=matrix(1,nlstate*nlstate,1,npar);
6222: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
6223:
6224: pstamp(ficresstdeij);
6225: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
6226: fprintf(ficresstdeij,"# Age");
6227: for(i=1; i<=nlstate;i++){
6228: for(j=1; j<=nlstate;j++)
6229: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
6230: fprintf(ficresstdeij," e%1d. ",i);
6231: }
6232: fprintf(ficresstdeij,"\n");
6233:
6234: pstamp(ficrescveij);
6235: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
6236: fprintf(ficrescveij,"# Age");
6237: for(i=1; i<=nlstate;i++)
6238: for(j=1; j<=nlstate;j++){
6239: cptj= (j-1)*nlstate+i;
6240: for(i2=1; i2<=nlstate;i2++)
6241: for(j2=1; j2<=nlstate;j2++){
6242: cptj2= (j2-1)*nlstate+i2;
6243: if(cptj2 <= cptj)
6244: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
6245: }
6246: }
6247: fprintf(ficrescveij,"\n");
6248:
6249: if(estepm < stepm){
6250: printf ("Problem %d lower than %d\n",estepm, stepm);
6251: }
6252: else hstepm=estepm;
6253: /* We compute the life expectancy from trapezoids spaced every estepm months
6254: * This is mainly to measure the difference between two models: for example
6255: * if stepm=24 months pijx are given only every 2 years and by summing them
6256: * we are calculating an estimate of the Life Expectancy assuming a linear
6257: * progression in between and thus overestimating or underestimating according
6258: * to the curvature of the survival function. If, for the same date, we
6259: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6260: * to compare the new estimate of Life expectancy with the same linear
6261: * hypothesis. A more precise result, taking into account a more precise
6262: * curvature will be obtained if estepm is as small as stepm. */
6263:
6264: /* For example we decided to compute the life expectancy with the smallest unit */
6265: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6266: nhstepm is the number of hstepm from age to agelim
6267: nstepm is the number of stepm from age to agelin.
6268: Look at hpijx to understand the reason of that which relies in memory size
6269: and note for a fixed period like estepm months */
6270: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6271: survival function given by stepm (the optimization length). Unfortunately it
6272: means that if the survival funtion is printed only each two years of age and if
6273: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6274: results. So we changed our mind and took the option of the best precision.
6275: */
6276: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6277:
6278: /* If stepm=6 months */
6279: /* nhstepm age range expressed in number of stepm */
6280: agelim=AGESUP;
6281: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
6282: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6283: /* if (stepm >= YEARM) hstepm=1;*/
6284: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6285:
6286: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6287: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6288: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
6289: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
6290: gp=matrix(0,nhstepm,1,nlstate*nlstate);
6291: gm=matrix(0,nhstepm,1,nlstate*nlstate);
6292:
6293: for (age=bage; age<=fage; age ++){
6294: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6295: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6296: /* if (stepm >= YEARM) hstepm=1;*/
6297: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 6298:
1.126 brouard 6299: /* If stepm=6 months */
6300: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6301: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
6302:
6303: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 6304:
1.126 brouard 6305: /* Computing Variances of health expectancies */
6306: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
6307: decrease memory allocation */
6308: for(theta=1; theta <=npar; theta++){
6309: for(i=1; i<=npar; i++){
1.222 brouard 6310: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6311: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 6312: }
1.235 brouard 6313: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
6314: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 6315:
1.126 brouard 6316: for(j=1; j<= nlstate; j++){
1.222 brouard 6317: for(i=1; i<=nlstate; i++){
6318: for(h=0; h<=nhstepm-1; h++){
6319: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
6320: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
6321: }
6322: }
1.126 brouard 6323: }
1.218 brouard 6324:
1.126 brouard 6325: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 6326: for(h=0; h<=nhstepm-1; h++){
6327: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
6328: }
1.126 brouard 6329: }/* End theta */
6330:
6331:
6332: for(h=0; h<=nhstepm-1; h++)
6333: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 6334: for(theta=1; theta <=npar; theta++)
6335: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 6336:
1.218 brouard 6337:
1.222 brouard 6338: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 6339: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 6340: varhe[ij][ji][(int)age] =0.;
1.218 brouard 6341:
1.222 brouard 6342: printf("%d|",(int)age);fflush(stdout);
6343: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6344: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 6345: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 6346: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
6347: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
6348: for(ij=1;ij<=nlstate*nlstate;ij++)
6349: for(ji=1;ji<=nlstate*nlstate;ji++)
6350: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 6351: }
6352: }
1.320 brouard 6353: /* if((int)age ==50){ */
6354: /* printf(" age=%d cij=%d nres=%d varhe[%d][%d]=%f ",(int)age, cij, nres, 1,2,varhe[1][2]); */
6355: /* } */
1.126 brouard 6356: /* Computing expectancies */
1.235 brouard 6357: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 6358: for(i=1; i<=nlstate;i++)
6359: for(j=1; j<=nlstate;j++)
1.222 brouard 6360: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6361: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 6362:
1.222 brouard 6363: /* 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 6364:
1.222 brouard 6365: }
1.269 brouard 6366:
6367: /* Standard deviation of expectancies ij */
1.126 brouard 6368: fprintf(ficresstdeij,"%3.0f",age );
6369: for(i=1; i<=nlstate;i++){
6370: eip=0.;
6371: vip=0.;
6372: for(j=1; j<=nlstate;j++){
1.222 brouard 6373: eip += eij[i][j][(int)age];
6374: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
6375: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
6376: 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 6377: }
6378: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
6379: }
6380: fprintf(ficresstdeij,"\n");
1.218 brouard 6381:
1.269 brouard 6382: /* Variance of expectancies ij */
1.126 brouard 6383: fprintf(ficrescveij,"%3.0f",age );
6384: for(i=1; i<=nlstate;i++)
6385: for(j=1; j<=nlstate;j++){
1.222 brouard 6386: cptj= (j-1)*nlstate+i;
6387: for(i2=1; i2<=nlstate;i2++)
6388: for(j2=1; j2<=nlstate;j2++){
6389: cptj2= (j2-1)*nlstate+i2;
6390: if(cptj2 <= cptj)
6391: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
6392: }
1.126 brouard 6393: }
6394: fprintf(ficrescveij,"\n");
1.218 brouard 6395:
1.126 brouard 6396: }
6397: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
6398: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
6399: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
6400: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
6401: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6402: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6403: printf("\n");
6404: fprintf(ficlog,"\n");
1.218 brouard 6405:
1.126 brouard 6406: free_vector(xm,1,npar);
6407: free_vector(xp,1,npar);
6408: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
6409: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
6410: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
6411: }
1.218 brouard 6412:
1.126 brouard 6413: /************ Variance ******************/
1.235 brouard 6414: 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 6415: {
1.279 brouard 6416: /** Variance of health expectancies
6417: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
6418: * double **newm;
6419: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
6420: */
1.218 brouard 6421:
6422: /* int movingaverage(); */
6423: double **dnewm,**doldm;
6424: double **dnewmp,**doldmp;
6425: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 6426: int first=0;
1.218 brouard 6427: int k;
6428: double *xp;
1.279 brouard 6429: double **gp, **gm; /**< for var eij */
6430: double ***gradg, ***trgradg; /**< for var eij */
6431: double **gradgp, **trgradgp; /**< for var p point j */
6432: double *gpp, *gmp; /**< for var p point j */
6433: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 6434: double ***p3mat;
6435: double age,agelim, hf;
6436: /* double ***mobaverage; */
6437: int theta;
6438: char digit[4];
6439: char digitp[25];
6440:
6441: char fileresprobmorprev[FILENAMELENGTH];
6442:
6443: if(popbased==1){
6444: if(mobilav!=0)
6445: strcpy(digitp,"-POPULBASED-MOBILAV_");
6446: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
6447: }
6448: else
6449: strcpy(digitp,"-STABLBASED_");
1.126 brouard 6450:
1.218 brouard 6451: /* if (mobilav!=0) { */
6452: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6453: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
6454: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
6455: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
6456: /* } */
6457: /* } */
6458:
6459: strcpy(fileresprobmorprev,"PRMORPREV-");
6460: sprintf(digit,"%-d",ij);
6461: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
6462: strcat(fileresprobmorprev,digit); /* Tvar to be done */
6463: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
6464: strcat(fileresprobmorprev,fileresu);
6465: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
6466: printf("Problem with resultfile: %s\n", fileresprobmorprev);
6467: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
6468: }
6469: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
6470: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
6471: pstamp(ficresprobmorprev);
6472: 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 6473: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
1.334 ! brouard 6474: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */ /* To be done*/
1.332 brouard 6475: fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]);
1.238 brouard 6476: }
6477: for(j=1;j<=cptcoveff;j++)
1.334 ! brouard 6478: fprintf(ficresprobmorprev," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,TnsdVar[Tvaraff[j]])]);
1.238 brouard 6479: fprintf(ficresprobmorprev,"\n");
6480:
1.218 brouard 6481: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
6482: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6483: fprintf(ficresprobmorprev," p.%-d SE",j);
6484: for(i=1; i<=nlstate;i++)
6485: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
6486: }
6487: fprintf(ficresprobmorprev,"\n");
6488:
6489: fprintf(ficgp,"\n# Routine varevsij");
6490: fprintf(ficgp,"\nunset title \n");
6491: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
6492: 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");
6493: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 6494:
1.218 brouard 6495: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6496: pstamp(ficresvij);
6497: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
6498: if(popbased==1)
6499: 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);
6500: else
6501: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
6502: fprintf(ficresvij,"# Age");
6503: for(i=1; i<=nlstate;i++)
6504: for(j=1; j<=nlstate;j++)
6505: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
6506: fprintf(ficresvij,"\n");
6507:
6508: xp=vector(1,npar);
6509: dnewm=matrix(1,nlstate,1,npar);
6510: doldm=matrix(1,nlstate,1,nlstate);
6511: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
6512: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6513:
6514: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
6515: gpp=vector(nlstate+1,nlstate+ndeath);
6516: gmp=vector(nlstate+1,nlstate+ndeath);
6517: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 6518:
1.218 brouard 6519: if(estepm < stepm){
6520: printf ("Problem %d lower than %d\n",estepm, stepm);
6521: }
6522: else hstepm=estepm;
6523: /* For example we decided to compute the life expectancy with the smallest unit */
6524: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6525: nhstepm is the number of hstepm from age to agelim
6526: nstepm is the number of stepm from age to agelim.
6527: Look at function hpijx to understand why because of memory size limitations,
6528: we decided (b) to get a life expectancy respecting the most precise curvature of the
6529: survival function given by stepm (the optimization length). Unfortunately it
6530: means that if the survival funtion is printed every two years of age and if
6531: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6532: results. So we changed our mind and took the option of the best precision.
6533: */
6534: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6535: agelim = AGESUP;
6536: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6537: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6538: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6539: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6540: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
6541: gp=matrix(0,nhstepm,1,nlstate);
6542: gm=matrix(0,nhstepm,1,nlstate);
6543:
6544:
6545: for(theta=1; theta <=npar; theta++){
6546: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
6547: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6548: }
1.279 brouard 6549: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
6550: * returns into prlim .
1.288 brouard 6551: */
1.242 brouard 6552: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 6553:
6554: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 6555: if (popbased==1) {
6556: if(mobilav ==0){
6557: for(i=1; i<=nlstate;i++)
6558: prlim[i][i]=probs[(int)age][i][ij];
6559: }else{ /* mobilav */
6560: for(i=1; i<=nlstate;i++)
6561: prlim[i][i]=mobaverage[(int)age][i][ij];
6562: }
6563: }
1.295 brouard 6564: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h.
1.279 brouard 6565: */
6566: 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 6567: /**< 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 6568: * at horizon h in state j including mortality.
6569: */
1.218 brouard 6570: for(j=1; j<= nlstate; j++){
6571: for(h=0; h<=nhstepm; h++){
6572: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
6573: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
6574: }
6575: }
1.279 brouard 6576: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 6577: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 6578: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 6579: */
6580: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6581: for(i=1,gpp[j]=0.; i<= nlstate; i++)
6582: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 6583: }
6584:
6585: /* Again with minus shift */
1.218 brouard 6586:
6587: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
6588: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6589:
1.242 brouard 6590: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 6591:
6592: if (popbased==1) {
6593: if(mobilav ==0){
6594: for(i=1; i<=nlstate;i++)
6595: prlim[i][i]=probs[(int)age][i][ij];
6596: }else{ /* mobilav */
6597: for(i=1; i<=nlstate;i++)
6598: prlim[i][i]=mobaverage[(int)age][i][ij];
6599: }
6600: }
6601:
1.235 brouard 6602: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 6603:
6604: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
6605: for(h=0; h<=nhstepm; h++){
6606: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
6607: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
6608: }
6609: }
6610: /* This for computing probability of death (h=1 means
6611: computed over hstepm matrices product = hstepm*stepm months)
6612: as a weighted average of prlim.
6613: */
6614: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6615: for(i=1,gmp[j]=0.; i<= nlstate; i++)
6616: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6617: }
1.279 brouard 6618: /* end shifting computations */
6619:
6620: /**< Computing gradient matrix at horizon h
6621: */
1.218 brouard 6622: for(j=1; j<= nlstate; j++) /* vareij */
6623: for(h=0; h<=nhstepm; h++){
6624: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
6625: }
1.279 brouard 6626: /**< Gradient of overall mortality p.3 (or p.j)
6627: */
6628: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 6629: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
6630: }
6631:
6632: } /* End theta */
1.279 brouard 6633:
6634: /* We got the gradient matrix for each theta and state j */
1.218 brouard 6635: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
6636:
6637: for(h=0; h<=nhstepm; h++) /* veij */
6638: for(j=1; j<=nlstate;j++)
6639: for(theta=1; theta <=npar; theta++)
6640: trgradg[h][j][theta]=gradg[h][theta][j];
6641:
6642: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
6643: for(theta=1; theta <=npar; theta++)
6644: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 6645: /**< as well as its transposed matrix
6646: */
1.218 brouard 6647:
6648: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6649: for(i=1;i<=nlstate;i++)
6650: for(j=1;j<=nlstate;j++)
6651: vareij[i][j][(int)age] =0.;
1.279 brouard 6652:
6653: /* Computing trgradg by matcov by gradg at age and summing over h
6654: * and k (nhstepm) formula 15 of article
6655: * Lievre-Brouard-Heathcote
6656: */
6657:
1.218 brouard 6658: for(h=0;h<=nhstepm;h++){
6659: for(k=0;k<=nhstepm;k++){
6660: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
6661: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
6662: for(i=1;i<=nlstate;i++)
6663: for(j=1;j<=nlstate;j++)
6664: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
6665: }
6666: }
6667:
1.279 brouard 6668: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
6669: * p.j overall mortality formula 49 but computed directly because
6670: * we compute the grad (wix pijx) instead of grad (pijx),even if
6671: * wix is independent of theta.
6672: */
1.218 brouard 6673: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
6674: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
6675: for(j=nlstate+1;j<=nlstate+ndeath;j++)
6676: for(i=nlstate+1;i<=nlstate+ndeath;i++)
6677: varppt[j][i]=doldmp[j][i];
6678: /* end ppptj */
6679: /* x centered again */
6680:
1.242 brouard 6681: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 6682:
6683: if (popbased==1) {
6684: if(mobilav ==0){
6685: for(i=1; i<=nlstate;i++)
6686: prlim[i][i]=probs[(int)age][i][ij];
6687: }else{ /* mobilav */
6688: for(i=1; i<=nlstate;i++)
6689: prlim[i][i]=mobaverage[(int)age][i][ij];
6690: }
6691: }
6692:
6693: /* This for computing probability of death (h=1 means
6694: computed over hstepm (estepm) matrices product = hstepm*stepm months)
6695: as a weighted average of prlim.
6696: */
1.235 brouard 6697: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 6698: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6699: for(i=1,gmp[j]=0.;i<= nlstate; i++)
6700: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6701: }
6702: /* end probability of death */
6703:
6704: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
6705: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6706: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
6707: for(i=1; i<=nlstate;i++){
6708: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
6709: }
6710: }
6711: fprintf(ficresprobmorprev,"\n");
6712:
6713: fprintf(ficresvij,"%.0f ",age );
6714: for(i=1; i<=nlstate;i++)
6715: for(j=1; j<=nlstate;j++){
6716: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
6717: }
6718: fprintf(ficresvij,"\n");
6719: free_matrix(gp,0,nhstepm,1,nlstate);
6720: free_matrix(gm,0,nhstepm,1,nlstate);
6721: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
6722: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
6723: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6724: } /* End age */
6725: free_vector(gpp,nlstate+1,nlstate+ndeath);
6726: free_vector(gmp,nlstate+1,nlstate+ndeath);
6727: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
6728: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
6729: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
6730: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
6731: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
6732: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
6733: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
6734: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
6735: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
6736: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
6737: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
6738: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
6739: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
6740: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
6741: 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);
6742: /* 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 6743: */
1.218 brouard 6744: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
6745: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 6746:
1.218 brouard 6747: free_vector(xp,1,npar);
6748: free_matrix(doldm,1,nlstate,1,nlstate);
6749: free_matrix(dnewm,1,nlstate,1,npar);
6750: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6751: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
6752: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6753: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6754: fclose(ficresprobmorprev);
6755: fflush(ficgp);
6756: fflush(fichtm);
6757: } /* end varevsij */
1.126 brouard 6758:
6759: /************ Variance of prevlim ******************/
1.269 brouard 6760: 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 6761: {
1.205 brouard 6762: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 6763: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 6764:
1.268 brouard 6765: double **dnewmpar,**doldm;
1.126 brouard 6766: int i, j, nhstepm, hstepm;
6767: double *xp;
6768: double *gp, *gm;
6769: double **gradg, **trgradg;
1.208 brouard 6770: double **mgm, **mgp;
1.126 brouard 6771: double age,agelim;
6772: int theta;
6773:
6774: pstamp(ficresvpl);
1.288 brouard 6775: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 6776: fprintf(ficresvpl,"# Age ");
6777: if(nresult >=1)
6778: fprintf(ficresvpl," Result# ");
1.126 brouard 6779: for(i=1; i<=nlstate;i++)
6780: fprintf(ficresvpl," %1d-%1d",i,i);
6781: fprintf(ficresvpl,"\n");
6782:
6783: xp=vector(1,npar);
1.268 brouard 6784: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 6785: doldm=matrix(1,nlstate,1,nlstate);
6786:
6787: hstepm=1*YEARM; /* Every year of age */
6788: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6789: agelim = AGESUP;
6790: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6791: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6792: if (stepm >= YEARM) hstepm=1;
6793: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6794: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 6795: mgp=matrix(1,npar,1,nlstate);
6796: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 6797: gp=vector(1,nlstate);
6798: gm=vector(1,nlstate);
6799:
6800: for(theta=1; theta <=npar; theta++){
6801: for(i=1; i<=npar; i++){ /* Computes gradient */
6802: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6803: }
1.288 brouard 6804: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6805: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6806: /* else */
6807: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6808: for(i=1;i<=nlstate;i++){
1.126 brouard 6809: gp[i] = prlim[i][i];
1.208 brouard 6810: mgp[theta][i] = prlim[i][i];
6811: }
1.126 brouard 6812: for(i=1; i<=npar; i++) /* Computes gradient */
6813: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6814: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6815: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6816: /* else */
6817: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6818: for(i=1;i<=nlstate;i++){
1.126 brouard 6819: gm[i] = prlim[i][i];
1.208 brouard 6820: mgm[theta][i] = prlim[i][i];
6821: }
1.126 brouard 6822: for(i=1;i<=nlstate;i++)
6823: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 6824: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 6825: } /* End theta */
6826:
6827: trgradg =matrix(1,nlstate,1,npar);
6828:
6829: for(j=1; j<=nlstate;j++)
6830: for(theta=1; theta <=npar; theta++)
6831: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 6832: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6833: /* printf("\nmgm mgp %d ",(int)age); */
6834: /* for(j=1; j<=nlstate;j++){ */
6835: /* printf(" %d ",j); */
6836: /* for(theta=1; theta <=npar; theta++) */
6837: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6838: /* printf("\n "); */
6839: /* } */
6840: /* } */
6841: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6842: /* printf("\n gradg %d ",(int)age); */
6843: /* for(j=1; j<=nlstate;j++){ */
6844: /* printf("%d ",j); */
6845: /* for(theta=1; theta <=npar; theta++) */
6846: /* printf("%d %lf ",theta,gradg[theta][j]); */
6847: /* printf("\n "); */
6848: /* } */
6849: /* } */
1.126 brouard 6850:
6851: for(i=1;i<=nlstate;i++)
6852: varpl[i][(int)age] =0.;
1.209 brouard 6853: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 6854: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6855: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6856: }else{
1.268 brouard 6857: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6858: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6859: }
1.126 brouard 6860: for(i=1;i<=nlstate;i++)
6861: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6862:
6863: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 6864: if(nresult >=1)
6865: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 6866: for(i=1; i<=nlstate;i++){
1.126 brouard 6867: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 6868: /* for(j=1;j<=nlstate;j++) */
6869: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
6870: }
1.126 brouard 6871: fprintf(ficresvpl,"\n");
6872: free_vector(gp,1,nlstate);
6873: free_vector(gm,1,nlstate);
1.208 brouard 6874: free_matrix(mgm,1,npar,1,nlstate);
6875: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 6876: free_matrix(gradg,1,npar,1,nlstate);
6877: free_matrix(trgradg,1,nlstate,1,npar);
6878: } /* End age */
6879:
6880: free_vector(xp,1,npar);
6881: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 6882: free_matrix(dnewmpar,1,nlstate,1,nlstate);
6883:
6884: }
6885:
6886:
6887: /************ Variance of backprevalence limit ******************/
1.269 brouard 6888: 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 6889: {
6890: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
6891: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
6892:
6893: double **dnewmpar,**doldm;
6894: int i, j, nhstepm, hstepm;
6895: double *xp;
6896: double *gp, *gm;
6897: double **gradg, **trgradg;
6898: double **mgm, **mgp;
6899: double age,agelim;
6900: int theta;
6901:
6902: pstamp(ficresvbl);
6903: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
6904: fprintf(ficresvbl,"# Age ");
6905: if(nresult >=1)
6906: fprintf(ficresvbl," Result# ");
6907: for(i=1; i<=nlstate;i++)
6908: fprintf(ficresvbl," %1d-%1d",i,i);
6909: fprintf(ficresvbl,"\n");
6910:
6911: xp=vector(1,npar);
6912: dnewmpar=matrix(1,nlstate,1,npar);
6913: doldm=matrix(1,nlstate,1,nlstate);
6914:
6915: hstepm=1*YEARM; /* Every year of age */
6916: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6917: agelim = AGEINF;
6918: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
6919: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6920: if (stepm >= YEARM) hstepm=1;
6921: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6922: gradg=matrix(1,npar,1,nlstate);
6923: mgp=matrix(1,npar,1,nlstate);
6924: mgm=matrix(1,npar,1,nlstate);
6925: gp=vector(1,nlstate);
6926: gm=vector(1,nlstate);
6927:
6928: for(theta=1; theta <=npar; theta++){
6929: for(i=1; i<=npar; i++){ /* Computes gradient */
6930: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6931: }
6932: if(mobilavproj > 0 )
6933: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6934: else
6935: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6936: for(i=1;i<=nlstate;i++){
6937: gp[i] = bprlim[i][i];
6938: mgp[theta][i] = bprlim[i][i];
6939: }
6940: for(i=1; i<=npar; i++) /* Computes gradient */
6941: xp[i] = x[i] - (i==theta ?delti[theta]:0);
6942: if(mobilavproj > 0 )
6943: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6944: else
6945: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6946: for(i=1;i<=nlstate;i++){
6947: gm[i] = bprlim[i][i];
6948: mgm[theta][i] = bprlim[i][i];
6949: }
6950: for(i=1;i<=nlstate;i++)
6951: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
6952: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
6953: } /* End theta */
6954:
6955: trgradg =matrix(1,nlstate,1,npar);
6956:
6957: for(j=1; j<=nlstate;j++)
6958: for(theta=1; theta <=npar; theta++)
6959: trgradg[j][theta]=gradg[theta][j];
6960: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6961: /* printf("\nmgm mgp %d ",(int)age); */
6962: /* for(j=1; j<=nlstate;j++){ */
6963: /* printf(" %d ",j); */
6964: /* for(theta=1; theta <=npar; theta++) */
6965: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6966: /* printf("\n "); */
6967: /* } */
6968: /* } */
6969: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6970: /* printf("\n gradg %d ",(int)age); */
6971: /* for(j=1; j<=nlstate;j++){ */
6972: /* printf("%d ",j); */
6973: /* for(theta=1; theta <=npar; theta++) */
6974: /* printf("%d %lf ",theta,gradg[theta][j]); */
6975: /* printf("\n "); */
6976: /* } */
6977: /* } */
6978:
6979: for(i=1;i<=nlstate;i++)
6980: varbpl[i][(int)age] =0.;
6981: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
6982: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6983: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6984: }else{
6985: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6986: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6987: }
6988: for(i=1;i<=nlstate;i++)
6989: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6990:
6991: fprintf(ficresvbl,"%.0f ",age );
6992: if(nresult >=1)
6993: fprintf(ficresvbl,"%d ",nres );
6994: for(i=1; i<=nlstate;i++)
6995: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
6996: fprintf(ficresvbl,"\n");
6997: free_vector(gp,1,nlstate);
6998: free_vector(gm,1,nlstate);
6999: free_matrix(mgm,1,npar,1,nlstate);
7000: free_matrix(mgp,1,npar,1,nlstate);
7001: free_matrix(gradg,1,npar,1,nlstate);
7002: free_matrix(trgradg,1,nlstate,1,npar);
7003: } /* End age */
7004:
7005: free_vector(xp,1,npar);
7006: free_matrix(doldm,1,nlstate,1,npar);
7007: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 7008:
7009: }
7010:
7011: /************ Variance of one-step probabilities ******************/
7012: 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 7013: {
7014: int i, j=0, k1, l1, tj;
7015: int k2, l2, j1, z1;
7016: int k=0, l;
7017: int first=1, first1, first2;
1.326 brouard 7018: int nres=0; /* New */
1.222 brouard 7019: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
7020: double **dnewm,**doldm;
7021: double *xp;
7022: double *gp, *gm;
7023: double **gradg, **trgradg;
7024: double **mu;
7025: double age, cov[NCOVMAX+1];
7026: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
7027: int theta;
7028: char fileresprob[FILENAMELENGTH];
7029: char fileresprobcov[FILENAMELENGTH];
7030: char fileresprobcor[FILENAMELENGTH];
7031: double ***varpij;
7032:
7033: strcpy(fileresprob,"PROB_");
7034: strcat(fileresprob,fileres);
7035: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
7036: printf("Problem with resultfile: %s\n", fileresprob);
7037: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
7038: }
7039: strcpy(fileresprobcov,"PROBCOV_");
7040: strcat(fileresprobcov,fileresu);
7041: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
7042: printf("Problem with resultfile: %s\n", fileresprobcov);
7043: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
7044: }
7045: strcpy(fileresprobcor,"PROBCOR_");
7046: strcat(fileresprobcor,fileresu);
7047: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
7048: printf("Problem with resultfile: %s\n", fileresprobcor);
7049: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
7050: }
7051: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7052: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7053: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7054: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7055: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7056: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7057: pstamp(ficresprob);
7058: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
7059: fprintf(ficresprob,"# Age");
7060: pstamp(ficresprobcov);
7061: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
7062: fprintf(ficresprobcov,"# Age");
7063: pstamp(ficresprobcor);
7064: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
7065: fprintf(ficresprobcor,"# Age");
1.126 brouard 7066:
7067:
1.222 brouard 7068: for(i=1; i<=nlstate;i++)
7069: for(j=1; j<=(nlstate+ndeath);j++){
7070: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
7071: fprintf(ficresprobcov," p%1d-%1d ",i,j);
7072: fprintf(ficresprobcor," p%1d-%1d ",i,j);
7073: }
7074: /* fprintf(ficresprob,"\n");
7075: fprintf(ficresprobcov,"\n");
7076: fprintf(ficresprobcor,"\n");
7077: */
7078: xp=vector(1,npar);
7079: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7080: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
7081: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
7082: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
7083: first=1;
7084: fprintf(ficgp,"\n# Routine varprob");
7085: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
7086: fprintf(fichtm,"\n");
7087:
1.288 brouard 7088: 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 7089: 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);
7090: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 7091: and drawn. It helps understanding how is the covariance between two incidences.\
7092: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 7093: 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 7094: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
7095: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
7096: standard deviations wide on each axis. <br>\
7097: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
7098: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
7099: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
7100:
1.222 brouard 7101: cov[1]=1;
7102: /* tj=cptcoveff; */
1.225 brouard 7103: tj = (int) pow(2,cptcoveff);
1.222 brouard 7104: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
7105: j1=0;
1.332 brouard 7106:
7107: for(nres=1;nres <=nresult; nres++){ /* For each resultline */
7108: for(j1=1; j1<=tj;j1++){ /* For any combination of dummy covariates, fixed and varying */
1.334 ! brouard 7109: 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 7110: if(tj != 1 && TKresult[nres]!= j1)
7111: continue;
7112:
7113: /* for(j1=1; j1<=tj;j1++){ /\* For each valid combination of covariates or only once*\/ */
7114: /* for(nres=1;nres <=1; nres++){ /\* For each resultline *\/ */
7115: /* /\* for(nres=1;nres <=nresult; nres++){ /\\* For each resultline *\\/ *\/ */
1.222 brouard 7116: if (cptcovn>0) {
1.334 ! brouard 7117: fprintf(ficresprob, "\n#********** Variable ");
! 7118: fprintf(ficresprobcov, "\n#********** Variable ");
! 7119: fprintf(ficgp, "\n#********** Variable ");
! 7120: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
! 7121: fprintf(ficresprobcor, "\n#********** Variable ");
! 7122:
! 7123: /* Including quantitative variables of the resultline to be done */
! 7124: for (z1=1; z1<=cptcovs; z1++){ /* Loop on each variable of this resultline */
! 7125: printf("Varprob modelresult[%d][%d]=%d model=%s \n",nres, z1, modelresult[nres][z1], model);
! 7126: fprintf(ficlog,"Varprob modelresult[%d][%d]=%d model=%s \n",nres, z1, modelresult[nres][z1], model);
! 7127: /* fprintf(ficlog,"Varprob modelresult[%d][%d]=%d model=%s resultline[%d]=%s \n",nres, z1, modelresult[nres][z1], model, nres, resultline[nres]); */
! 7128: if(Dummy[modelresult[nres][z1]]==0){/* Dummy variable of the variable in position modelresult in the model corresponding to z1 in resultline */
! 7129: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed referenced to model equation */
! 7130: 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 */
! 7131: 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 */
! 7132: 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 */
! 7133: 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 */
! 7134: 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 */
! 7135: fprintf(ficresprob,"fixed ");
! 7136: fprintf(ficresprobcov,"fixed ");
! 7137: fprintf(ficgp,"fixed ");
! 7138: fprintf(fichtmcov,"fixed ");
! 7139: fprintf(ficresprobcor,"fixed ");
! 7140: }else{
! 7141: fprintf(ficresprob,"varyi ");
! 7142: fprintf(ficresprobcov,"varyi ");
! 7143: fprintf(ficgp,"varyi ");
! 7144: fprintf(fichtmcov,"varyi ");
! 7145: fprintf(ficresprobcor,"varyi ");
! 7146: }
! 7147: }else if(Dummy[modelresult[nres][z1]]==1){ /* Quanti variable */
! 7148: /* For each selected (single) quantitative value */
! 7149: fprintf(ficresprob," V%d=%f ",Tvqresult[nres][z1],Tqresult[nres][z1]);
! 7150: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed */
! 7151: fprintf(ficresprob,"fixed ");
! 7152: fprintf(ficresprobcov,"fixed ");
! 7153: fprintf(ficgp,"fixed ");
! 7154: fprintf(fichtmcov,"fixed ");
! 7155: fprintf(ficresprobcor,"fixed ");
! 7156: }else{
! 7157: fprintf(ficresprob,"varyi ");
! 7158: fprintf(ficresprobcov,"varyi ");
! 7159: fprintf(ficgp,"varyi ");
! 7160: fprintf(fichtmcov,"varyi ");
! 7161: fprintf(ficresprobcor,"varyi ");
! 7162: }
! 7163: }else{
! 7164: 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 */
! 7165: 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 */
! 7166: exit(1);
! 7167: }
! 7168: } /* End loop on variable of this resultline */
! 7169: /* for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]); */
1.222 brouard 7170: fprintf(ficresprob, "**********\n#\n");
7171: fprintf(ficresprobcov, "**********\n#\n");
7172: fprintf(ficgp, "**********\n#\n");
7173: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
7174: fprintf(ficresprobcor, "**********\n#");
7175: if(invalidvarcomb[j1]){
7176: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
7177: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
7178: continue;
7179: }
7180: }
7181: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
7182: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7183: gp=vector(1,(nlstate)*(nlstate+ndeath));
7184: gm=vector(1,(nlstate)*(nlstate+ndeath));
1.334 ! brouard 7185: for (age=bage; age<=fage; age ++){ /* Fo each age we feed the model equation with covariates, using precov as in hpxij() ? */
1.222 brouard 7186: cov[2]=age;
7187: if(nagesqr==1)
7188: cov[3]= age*age;
1.334 ! brouard 7189: /* New code end of combination but for each resultline */
! 7190: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
! 7191: if(Typevar[k1]==1){ /* A product with age */
! 7192: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.326 brouard 7193: }else{
1.334 ! brouard 7194: cov[2+nagesqr+k1]=precov[nres][k1];
1.326 brouard 7195: }
1.334 ! brouard 7196: }/* End of loop on model equation */
! 7197: /* Old code */
! 7198: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
! 7199: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)]; *\/ */
! 7200: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
! 7201: /* /\* Here comes the value of the covariate 'j1' after renumbering k with single dummy covariates *\/ */
! 7202: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(j1,TnsdVar[TvarsD[k]])]; */
! 7203: /* /\*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*\//\* j1 1 2 3 4 */
! 7204: /* * 1 1 1 1 1 */
! 7205: /* * 2 2 1 1 1 */
! 7206: /* * 3 1 2 1 1 */
! 7207: /* *\/ */
! 7208: /* /\* nbcode[1][1]=0 nbcode[1][2]=1;*\/ */
! 7209: /* } */
! 7210: /* /\* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
! 7211: /* /\* ) p nbcode[Tvar[Tage[k]]][(1 & (ij-1) >> (k-1))+1] *\/ */
! 7212: /* /\*for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; *\/ */
! 7213: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
! 7214: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
! 7215: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(j1,TnsdVar[Tvar[Tage[k]]])]*cov[2]; */
! 7216: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
! 7217: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
! 7218: /* 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]); */
! 7219: /* /\* cov[2+nagesqr+Tage[k]]=meanq[k]/idq[k]*cov[2];/\\* Using the mean of quantitative variable Tvar[Tage[k]] /\\* Tqresult[nres][k]; *\\/ *\/ */
! 7220: /* /\* exit(1); *\/ */
! 7221: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
! 7222: /* } */
! 7223: /* /\* cov[2+Tage[k]+nagesqr]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
! 7224: /* } */
! 7225: /* for (k=1; k<=cptcovprod;k++){/\* For product without age *\/ */
! 7226: /* if(Dummy[Tvard[k][1]]==0){ */
! 7227: /* if(Dummy[Tvard[k][2]]==0){ */
! 7228: /* 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]])]; */
! 7229: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
! 7230: /* }else{ /\* Should we use the mean of the quantitative variables? *\/ */
! 7231: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(j1,TnsdVar[Tvard[k][1]])] * Tqresult[nres][resultmodel[nres][k]]; */
! 7232: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
! 7233: /* } */
! 7234: /* }else{ */
! 7235: /* if(Dummy[Tvard[k][2]]==0){ */
! 7236: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(j1,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][TnsdVar[Tvard[k][1]]]; */
! 7237: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
! 7238: /* }else{ */
! 7239: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][TnsdVar[Tvard[k][1]]]* Tqinvresult[nres][TnsdVar[Tvard[k][2]]]; */
! 7240: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
! 7241: /* } */
! 7242: /* } */
! 7243: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
! 7244: /* } */
1.326 brouard 7245: /* For each age and combination of dummy covariates we slightly move the parameters of delti in order to get the gradient*/
1.222 brouard 7246: for(theta=1; theta <=npar; theta++){
7247: for(i=1; i<=npar; i++)
7248: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 7249:
1.222 brouard 7250: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 7251:
1.222 brouard 7252: k=0;
7253: for(i=1; i<= (nlstate); i++){
7254: for(j=1; j<=(nlstate+ndeath);j++){
7255: k=k+1;
7256: gp[k]=pmmij[i][j];
7257: }
7258: }
1.220 brouard 7259:
1.222 brouard 7260: for(i=1; i<=npar; i++)
7261: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 7262:
1.222 brouard 7263: pmij(pmmij,cov,ncovmodel,xp,nlstate);
7264: k=0;
7265: for(i=1; i<=(nlstate); i++){
7266: for(j=1; j<=(nlstate+ndeath);j++){
7267: k=k+1;
7268: gm[k]=pmmij[i][j];
7269: }
7270: }
1.220 brouard 7271:
1.222 brouard 7272: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
7273: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
7274: }
1.126 brouard 7275:
1.222 brouard 7276: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
7277: for(theta=1; theta <=npar; theta++)
7278: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 7279:
1.222 brouard 7280: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
7281: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 7282:
1.222 brouard 7283: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 7284:
1.222 brouard 7285: k=0;
7286: for(i=1; i<=(nlstate); i++){
7287: for(j=1; j<=(nlstate+ndeath);j++){
7288: k=k+1;
7289: mu[k][(int) age]=pmmij[i][j];
7290: }
7291: }
7292: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
7293: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
7294: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 7295:
1.222 brouard 7296: /*printf("\n%d ",(int)age);
7297: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7298: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7299: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7300: }*/
1.220 brouard 7301:
1.222 brouard 7302: fprintf(ficresprob,"\n%d ",(int)age);
7303: fprintf(ficresprobcov,"\n%d ",(int)age);
7304: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 7305:
1.222 brouard 7306: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
7307: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
7308: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7309: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
7310: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
7311: }
7312: i=0;
7313: for (k=1; k<=(nlstate);k++){
7314: for (l=1; l<=(nlstate+ndeath);l++){
7315: i++;
7316: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
7317: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
7318: for (j=1; j<=i;j++){
7319: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
7320: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
7321: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
7322: }
7323: }
7324: }/* end of loop for state */
7325: } /* end of loop for age */
7326: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
7327: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
7328: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7329: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7330:
7331: /* Confidence intervalle of pij */
7332: /*
7333: fprintf(ficgp,"\nunset parametric;unset label");
7334: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
7335: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
7336: 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);
7337: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
7338: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
7339: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
7340: */
7341:
7342: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
7343: first1=1;first2=2;
7344: for (k2=1; k2<=(nlstate);k2++){
7345: for (l2=1; l2<=(nlstate+ndeath);l2++){
7346: if(l2==k2) continue;
7347: j=(k2-1)*(nlstate+ndeath)+l2;
7348: for (k1=1; k1<=(nlstate);k1++){
7349: for (l1=1; l1<=(nlstate+ndeath);l1++){
7350: if(l1==k1) continue;
7351: i=(k1-1)*(nlstate+ndeath)+l1;
7352: if(i<=j) continue;
7353: for (age=bage; age<=fage; age ++){
7354: if ((int)age %5==0){
7355: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
7356: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
7357: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
7358: mu1=mu[i][(int) age]/stepm*YEARM ;
7359: mu2=mu[j][(int) age]/stepm*YEARM;
7360: c12=cv12/sqrt(v1*v2);
7361: /* Computing eigen value of matrix of covariance */
7362: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7363: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7364: if ((lc2 <0) || (lc1 <0) ){
7365: if(first2==1){
7366: first1=0;
7367: 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);
7368: }
7369: 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);
7370: /* lc1=fabs(lc1); */ /* If we want to have them positive */
7371: /* lc2=fabs(lc2); */
7372: }
1.220 brouard 7373:
1.222 brouard 7374: /* Eigen vectors */
1.280 brouard 7375: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
7376: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7377: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7378: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
7379: }else
7380: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 7381: /*v21=sqrt(1.-v11*v11); *//* error */
7382: v21=(lc1-v1)/cv12*v11;
7383: v12=-v21;
7384: v22=v11;
7385: tnalp=v21/v11;
7386: if(first1==1){
7387: first1=0;
7388: 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);
7389: }
7390: 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);
7391: /*printf(fignu*/
7392: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
7393: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
7394: if(first==1){
7395: first=0;
7396: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
7397: fprintf(ficgp,"\nset parametric;unset label");
7398: 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);
7399: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 7400: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 7401: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 7402: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 7403: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
7404: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7405: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7406: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
7407: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7408: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7409: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7410: 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 7411: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
7412: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 7413: }else{
7414: first=0;
7415: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
7416: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7417: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7418: 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 7419: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
7420: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 7421: }/* if first */
7422: } /* age mod 5 */
7423: } /* end loop age */
7424: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7425: first=1;
7426: } /*l12 */
7427: } /* k12 */
7428: } /*l1 */
7429: }/* k1 */
1.332 brouard 7430: } /* loop on combination of covariates j1 */
1.326 brouard 7431: } /* loop on nres */
1.222 brouard 7432: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
7433: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
7434: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
7435: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
7436: free_vector(xp,1,npar);
7437: fclose(ficresprob);
7438: fclose(ficresprobcov);
7439: fclose(ficresprobcor);
7440: fflush(ficgp);
7441: fflush(fichtmcov);
7442: }
1.126 brouard 7443:
7444:
7445: /******************* Printing html file ***********/
1.201 brouard 7446: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 7447: int lastpass, int stepm, int weightopt, char model[],\
7448: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.296 brouard 7449: int popforecast, int mobilav, int prevfcast, int mobilavproj, int prevbcast, int estepm , \
7450: double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \
7451: double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){
1.237 brouard 7452: int jj1, k1, i1, cpt, k4, nres;
1.319 brouard 7453: /* In fact some results are already printed in fichtm which is open */
1.126 brouard 7454: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
7455: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
7456: </ul>");
1.319 brouard 7457: /* fprintf(fichtm,"<ul><li> model=1+age+%s\n \ */
7458: /* </ul>", model); */
1.214 brouard 7459: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
7460: 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",
7461: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
1.332 brouard 7462: 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 7463: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
7464: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 7465: fprintf(fichtm,"\
7466: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 7467: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 7468: fprintf(fichtm,"\
1.217 brouard 7469: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
7470: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
7471: fprintf(fichtm,"\
1.288 brouard 7472: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 7473: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 7474: fprintf(fichtm,"\
1.288 brouard 7475: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 7476: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
7477: fprintf(fichtm,"\
1.211 brouard 7478: - (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 7479: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 7480: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 7481: if(prevfcast==1){
7482: fprintf(fichtm,"\
7483: - Prevalence projections by age and states: \
1.201 brouard 7484: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 7485: }
1.126 brouard 7486:
7487:
1.225 brouard 7488: m=pow(2,cptcoveff);
1.222 brouard 7489: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7490:
1.317 brouard 7491: fprintf(fichtm," \n<ul><li><b>Graphs (first order)</b></li><p>");
1.264 brouard 7492:
7493: jj1=0;
7494:
7495: fprintf(fichtm," \n<ul>");
7496: for(nres=1; nres <= nresult; nres++) /* For each resultline */
7497: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
7498: if(m != 1 && TKresult[nres]!= k1)
7499: continue;
7500: jj1++;
7501: if (cptcovn > 0) {
7502: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
7503: for (cpt=1; cpt<=cptcoveff;cpt++){
7504: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7505: }
7506: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7507: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7508: }
7509: fprintf(fichtm,"\">");
7510:
7511: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
7512: fprintf(fichtm,"************ Results for covariates");
7513: for (cpt=1; cpt<=cptcoveff;cpt++){
7514: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7515: }
7516: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7517: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7518: }
7519: if(invalidvarcomb[k1]){
7520: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
7521: continue;
7522: }
7523: fprintf(fichtm,"</a></li>");
7524: } /* cptcovn >0 */
7525: }
1.317 brouard 7526: fprintf(fichtm," \n</ul>");
1.264 brouard 7527:
1.222 brouard 7528: jj1=0;
1.237 brouard 7529:
7530: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.241 brouard 7531: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
1.253 brouard 7532: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7533: continue;
1.220 brouard 7534:
1.222 brouard 7535: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7536: jj1++;
7537: if (cptcovn > 0) {
1.264 brouard 7538: fprintf(fichtm,"\n<p><a name=\"rescov");
7539: for (cpt=1; cpt<=cptcoveff;cpt++){
7540: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7541: }
7542: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7543: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7544: }
7545: fprintf(fichtm,"\"</a>");
7546:
1.222 brouard 7547: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 7548: for (cpt=1; cpt<=cptcoveff;cpt++){
1.237 brouard 7549: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7550: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
7551: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
7552: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 7553: }
1.237 brouard 7554: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7555: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7556: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);fflush(stdout);
7557: }
7558:
1.230 brouard 7559: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.321 brouard 7560: fprintf(fichtm," (model=%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.222 brouard 7561: if(invalidvarcomb[k1]){
7562: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
7563: printf("\nCombination (%d) ignored because no cases \n",k1);
7564: continue;
7565: }
7566: }
7567: /* aij, bij */
1.259 brouard 7568: 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 7569: <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 7570: /* Pij */
1.241 brouard 7571: 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> \
7572: <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 7573: /* Quasi-incidences */
7574: 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 7575: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 7576: 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 7577: 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> \
7578: <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 7579: /* Survival functions (period) in state j */
7580: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 7581: 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. <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);
7582: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
7583: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.222 brouard 7584: }
7585: /* State specific survival functions (period) */
7586: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 7587: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
7588: And probability to be observed in various states (up to %d) being in state %d at different ages. \
1.329 brouard 7589: <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);
7590: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
7591: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.222 brouard 7592: }
1.288 brouard 7593: /* Period (forward stable) prevalence in each health state */
1.222 brouard 7594: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 7595: 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 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);
7596: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"P_"),subdirf2(optionfilefiname,"P_"));
7597: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.222 brouard 7598: }
1.296 brouard 7599: if(prevbcast==1){
1.288 brouard 7600: /* Backward prevalence in each health state */
1.222 brouard 7601: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 7602: 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> \
1.241 brouard 7603: <img src=\"%s_%d-%d-%d.svg\">", cpt, cpt, nlstate, subdirf2(optionfilefiname,"PB_"),cpt,k1,nres,subdirf2(optionfilefiname,"PB_"),cpt,k1,nres,subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.222 brouard 7604: }
1.217 brouard 7605: }
1.222 brouard 7606: if(prevfcast==1){
1.288 brouard 7607: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 7608: for(cpt=1; cpt<=nlstate;cpt++){
1.314 brouard 7609: 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);
7610: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"F_"),subdirf2(optionfilefiname,"F_"));
7611: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",
7612: subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 7613: }
7614: }
1.296 brouard 7615: if(prevbcast==1){
1.268 brouard 7616: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
7617: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 7618: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
7619: 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 \
7620: 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 7621: 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);
7622: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"FB_"),subdirf2(optionfilefiname,"FB_"));
7623: fprintf(fichtm," <img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
1.268 brouard 7624: }
7625: }
1.220 brouard 7626:
1.222 brouard 7627: for(cpt=1; cpt<=nlstate;cpt++) {
1.314 brouard 7628: 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);
7629: fprintf(fichtm," (data from text file <a href=\"%s.txt\"> %s.txt</a>)\n<br>",subdirf2(optionfilefiname,"E_"),subdirf2(optionfilefiname,"E_"));
7630: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres );
1.222 brouard 7631: }
7632: /* } /\* end i1 *\/ */
7633: }/* End k1 */
7634: fprintf(fichtm,"</ul>");
1.126 brouard 7635:
1.222 brouard 7636: fprintf(fichtm,"\
1.126 brouard 7637: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 7638: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 7639: - 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 7640: But because parameters are usually highly correlated (a higher incidence of disability \
7641: and a higher incidence of recovery can give very close observed transition) it might \
7642: be very useful to look not only at linear confidence intervals estimated from the \
7643: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
7644: (parameters) of the logistic regression, it might be more meaningful to visualize the \
7645: covariance matrix of the one-step probabilities. \
7646: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 7647:
1.222 brouard 7648: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
7649: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
7650: fprintf(fichtm,"\
1.126 brouard 7651: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7652: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 7653:
1.222 brouard 7654: fprintf(fichtm,"\
1.126 brouard 7655: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7656: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
7657: fprintf(fichtm,"\
1.126 brouard 7658: - 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): \
7659: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7660: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 7661: fprintf(fichtm,"\
1.126 brouard 7662: - (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): \
7663: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7664: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 7665: fprintf(fichtm,"\
1.288 brouard 7666: - 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 7667: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
7668: fprintf(fichtm,"\
1.128 brouard 7669: - 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 7670: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
7671: fprintf(fichtm,"\
1.288 brouard 7672: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 7673: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 7674:
7675: /* if(popforecast==1) fprintf(fichtm,"\n */
7676: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
7677: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
7678: /* <br>",fileres,fileres,fileres,fileres); */
7679: /* else */
7680: /* fprintf(fichtm,"\n No population forecast: popforecast = %d (instead of 1) or stepm = %d (instead of 1) or model=%s (instead of .)<br><br></li>\n",popforecast, stepm, model); */
1.222 brouard 7681: fflush(fichtm);
1.126 brouard 7682:
1.225 brouard 7683: m=pow(2,cptcoveff);
1.222 brouard 7684: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7685:
1.317 brouard 7686: fprintf(fichtm," <ul><li><b>Graphs (second order)</b></li><p>");
7687:
7688: jj1=0;
7689:
7690: fprintf(fichtm," \n<ul>");
7691: for(nres=1; nres <= nresult; nres++) /* For each resultline */
7692: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
7693: if(m != 1 && TKresult[nres]!= k1)
7694: continue;
7695: jj1++;
7696: if (cptcovn > 0) {
7697: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescovsecond");
7698: for (cpt=1; cpt<=cptcoveff;cpt++){
7699: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7700: }
7701: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7702: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7703: }
7704: fprintf(fichtm,"\">");
7705:
7706: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
7707: fprintf(fichtm,"************ Results for covariates");
7708: for (cpt=1; cpt<=cptcoveff;cpt++){
7709: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7710: }
7711: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7712: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7713: }
7714: if(invalidvarcomb[k1]){
7715: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
7716: continue;
7717: }
7718: fprintf(fichtm,"</a></li>");
7719: } /* cptcovn >0 */
7720: }
7721: fprintf(fichtm," \n</ul>");
7722:
1.222 brouard 7723: jj1=0;
1.237 brouard 7724:
1.241 brouard 7725: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.222 brouard 7726: for(k1=1; k1<=m;k1++){
1.253 brouard 7727: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7728: continue;
1.222 brouard 7729: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7730: jj1++;
1.126 brouard 7731: if (cptcovn > 0) {
1.317 brouard 7732: fprintf(fichtm,"\n<p><a name=\"rescovsecond");
7733: for (cpt=1; cpt<=cptcoveff;cpt++){
7734: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7735: }
7736: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7737: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7738: }
7739: fprintf(fichtm,"\"</a>");
7740:
1.126 brouard 7741: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.317 brouard 7742: for (cpt=1; cpt<=cptcoveff;cpt++){ /**< cptcoveff number of variables */
1.237 brouard 7743: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);
1.317 brouard 7744: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
1.237 brouard 7745: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
1.317 brouard 7746: }
1.237 brouard 7747: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7748: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7749: }
7750:
1.321 brouard 7751: fprintf(fichtm," (model=%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.220 brouard 7752:
1.222 brouard 7753: if(invalidvarcomb[k1]){
7754: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
7755: continue;
7756: }
1.126 brouard 7757: }
7758: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 7759: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.314 brouard 7760: 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);
7761: fprintf(fichtm," (data from text file <a href=\"%s\">%s</a>)\n <br>",subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
7762: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"V_"), cpt,k1,nres);
1.126 brouard 7763: }
7764: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.314 brouard 7765: health expectancies in each live states (1 to %d). If popbased=1 the smooth (due to the model) \
1.128 brouard 7766: true period expectancies (those weighted with period prevalences are also\
7767: drawn in addition to the population based expectancies computed using\
1.314 brouard 7768: 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);
7769: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>) \n<br>",subdirf2(optionfilefiname,"T_"),subdirf2(optionfilefiname,"T_"));
7770: fprintf(fichtm,"<img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 7771: /* } /\* end i1 *\/ */
7772: }/* End k1 */
1.241 brouard 7773: }/* End nres */
1.222 brouard 7774: fprintf(fichtm,"</ul>");
7775: fflush(fichtm);
1.126 brouard 7776: }
7777:
7778: /******************* Gnuplot file **************/
1.296 brouard 7779: 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 7780:
7781: char dirfileres[132],optfileres[132];
1.264 brouard 7782: char gplotcondition[132], gplotlabel[132];
1.237 brouard 7783: int cpt=0,k1=0,i=0,k=0,j=0,jk=0,k2=0,k3=0,k4=0,ij=0, ijp=0, l=0;
1.211 brouard 7784: int lv=0, vlv=0, kl=0;
1.130 brouard 7785: int ng=0;
1.201 brouard 7786: int vpopbased;
1.223 brouard 7787: int ioffset; /* variable offset for columns */
1.270 brouard 7788: int iyearc=1; /* variable column for year of projection */
7789: int iagec=1; /* variable column for age of projection */
1.235 brouard 7790: int nres=0; /* Index of resultline */
1.266 brouard 7791: int istart=1; /* For starting graphs in projections */
1.219 brouard 7792:
1.126 brouard 7793: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
7794: /* printf("Problem with file %s",optionfilegnuplot); */
7795: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
7796: /* } */
7797:
7798: /*#ifdef windows */
7799: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 7800: /*#endif */
1.225 brouard 7801: m=pow(2,cptcoveff);
1.126 brouard 7802:
1.274 brouard 7803: /* diagram of the model */
7804: fprintf(ficgp,"\n#Diagram of the model \n");
7805: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
7806: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
7807: 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);
7808:
7809: fprintf(ficgp,"\n#Centripete arrows (turning in other direction (1-i) instead of (i-1)) \nset for [i=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);
7810: fprintf(ficgp,"\n#show arrow\nunset label\n");
7811: 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);
7812: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
7813: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
7814: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
7815: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
7816:
1.202 brouard 7817: /* Contribution to likelihood */
7818: /* Plot the probability implied in the likelihood */
1.223 brouard 7819: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
7820: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
7821: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
7822: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 7823: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 7824: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
7825: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 7826: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
7827: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
7828: 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));
7829: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
7830: 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));
7831: for (i=1; i<= nlstate ; i ++) {
7832: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
7833: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
7834: 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);
7835: for (j=2; j<= nlstate+ndeath ; j ++) {
7836: 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);
7837: }
7838: fprintf(ficgp,";\nset out; unset ylabel;\n");
7839: }
7840: /* 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 */
7841: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
7842: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
7843: fprintf(ficgp,"\nset out;unset log\n");
7844: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 7845:
1.126 brouard 7846: strcpy(dirfileres,optionfilefiname);
7847: strcpy(optfileres,"vpl");
1.223 brouard 7848: /* 1eme*/
1.238 brouard 7849: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
7850: for (k1=1; k1<= m ; k1 ++){ /* For each valid combination of covariate */
1.236 brouard 7851: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.238 brouard 7852: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.253 brouard 7853: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7854: continue;
7855: /* We are interested in selected combination by the resultline */
1.246 brouard 7856: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 7857: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 7858: strcpy(gplotlabel,"(");
1.238 brouard 7859: for (k=1; k<=cptcoveff; k++){ /* For each covariate k get corresponding value lv for combination k1 */
1.332 brouard 7860: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the value of the covariate corresponding to k1 combination *\/ */
7861: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.238 brouard 7862: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7863: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7864: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7865: vlv= nbcode[Tvaraff[k]][lv]; /* vlv is the value of the covariate lv, 0 or 1 */
7866: /* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv */
1.246 brouard 7867: /* printf(" V%d=%d ",Tvaraff[k],vlv); */
1.238 brouard 7868: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7869: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7870: }
7871: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.246 brouard 7872: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 7873: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7874: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7875: }
7876: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 7877: /* printf("\n#\n"); */
1.238 brouard 7878: fprintf(ficgp,"\n#\n");
7879: if(invalidvarcomb[k1]){
1.260 brouard 7880: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 7881: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7882: continue;
7883: }
1.235 brouard 7884:
1.241 brouard 7885: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
7886: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 7887: /* fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel); */
1.321 brouard 7888: fprintf(ficgp,"set title \"Alive state %d %s model=%s\" font \"Helvetica,12\"\n",cpt,gplotlabel,model);
1.260 brouard 7889: 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);
7890: /* 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); */
7891: /* k1-1 error should be nres-1*/
1.238 brouard 7892: for (i=1; i<= nlstate ; i ++) {
7893: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7894: else fprintf(ficgp," %%*lf (%%*lf)");
7895: }
1.288 brouard 7896: 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 7897: for (i=1; i<= nlstate ; i ++) {
7898: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7899: else fprintf(ficgp," %%*lf (%%*lf)");
7900: }
1.260 brouard 7901: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 7902: for (i=1; i<= nlstate ; i ++) {
7903: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7904: else fprintf(ficgp," %%*lf (%%*lf)");
7905: }
1.265 brouard 7906: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
7907:
7908: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
7909: if(cptcoveff ==0){
1.271 brouard 7910: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 7911: }else{
7912: kl=0;
7913: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 7914: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
7915: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.265 brouard 7916: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7917: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7918: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7919: vlv= nbcode[Tvaraff[k]][lv];
7920: kl++;
7921: /* 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 *\/ */
7922: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7923: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7924: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7925: if(k==cptcoveff){
7926: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
7927: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
7928: }else{
7929: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7930: kl++;
7931: }
7932: } /* end covariate */
7933: } /* end if no covariate */
7934:
1.296 brouard 7935: if(prevbcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
1.238 brouard 7936: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 7937: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 7938: if(cptcoveff ==0){
1.245 brouard 7939: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 7940: }else{
7941: kl=0;
7942: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 7943: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
7944: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.238 brouard 7945: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7946: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7947: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 7948: /* vlv= nbcode[Tvaraff[k]][lv]; */
7949: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.223 brouard 7950: kl++;
1.238 brouard 7951: /* 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 *\/ */
7952: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7953: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7954: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7955: if(k==cptcoveff){
1.245 brouard 7956: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 7957: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 7958: }else{
1.332 brouard 7959: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]);
1.238 brouard 7960: kl++;
7961: }
7962: } /* end covariate */
7963: } /* end if no covariate */
1.296 brouard 7964: if(prevbcast == 1){
1.268 brouard 7965: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
7966: /* k1-1 error should be nres-1*/
7967: for (i=1; i<= nlstate ; i ++) {
7968: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7969: else fprintf(ficgp," %%*lf (%%*lf)");
7970: }
1.271 brouard 7971: 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 7972: for (i=1; i<= nlstate ; i ++) {
7973: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7974: else fprintf(ficgp," %%*lf (%%*lf)");
7975: }
1.276 brouard 7976: 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 7977: for (i=1; i<= nlstate ; i ++) {
7978: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7979: else fprintf(ficgp," %%*lf (%%*lf)");
7980: }
1.274 brouard 7981: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 7982: } /* end if backprojcast */
1.296 brouard 7983: } /* end if prevbcast */
1.276 brouard 7984: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
7985: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 7986: } /* nres */
1.201 brouard 7987: } /* k1 */
7988: } /* cpt */
1.235 brouard 7989:
7990:
1.126 brouard 7991: /*2 eme*/
1.238 brouard 7992: for (k1=1; k1<= m ; k1 ++){
7993: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7994: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7995: continue;
7996: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 7997: strcpy(gplotlabel,"(");
1.238 brouard 7998: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.332 brouard 7999: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate number corresponding to k1 combination *\/ */
8000: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.223 brouard 8001: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8002: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8003: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 8004: /* vlv= nbcode[Tvaraff[k]][lv]; */
8005: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.223 brouard 8006: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 8007: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 8008: }
1.237 brouard 8009: /* for(k=1; k <= ncovds; k++){ */
1.236 brouard 8010: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 8011: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.236 brouard 8012: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 8013: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 8014: }
1.264 brouard 8015: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8016: fprintf(ficgp,"\n#\n");
1.223 brouard 8017: if(invalidvarcomb[k1]){
8018: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8019: continue;
8020: }
1.219 brouard 8021:
1.241 brouard 8022: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 8023: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 8024: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
8025: if(vpopbased==0){
1.238 brouard 8026: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 8027: }else
1.238 brouard 8028: fprintf(ficgp,"\nreplot ");
8029: for (i=1; i<= nlstate+1 ; i ++) {
8030: k=2*i;
1.261 brouard 8031: 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);
1.238 brouard 8032: for (j=1; j<= nlstate+1 ; j ++) {
8033: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8034: else fprintf(ficgp," %%*lf (%%*lf)");
8035: }
8036: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
8037: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 8038: 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 8039: for (j=1; j<= nlstate+1 ; j ++) {
8040: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8041: else fprintf(ficgp," %%*lf (%%*lf)");
8042: }
8043: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 8044: 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 8045: for (j=1; j<= nlstate+1 ; j ++) {
8046: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8047: else fprintf(ficgp," %%*lf (%%*lf)");
8048: }
8049: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
8050: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
8051: } /* state */
8052: } /* vpopbased */
1.264 brouard 8053: 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 8054: } /* end nres */
8055: } /* k1 end 2 eme*/
8056:
8057:
8058: /*3eme*/
8059: for (k1=1; k1<= m ; k1 ++){
8060: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 8061: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 8062: continue;
8063:
1.332 brouard 8064: for (cpt=1; cpt<= nlstate ; cpt ++) { /* Fragile no verification of covariate values */
1.261 brouard 8065: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 8066: strcpy(gplotlabel,"(");
1.238 brouard 8067: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.332 brouard 8068: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate number corresponding to k1 combination *\/ */
8069: lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /* Should be the covariate value corresponding to combination k1 and covariate k */
1.238 brouard 8070: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8071: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8072: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 8073: /* vlv= nbcode[Tvaraff[k]][lv]; */
8074: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.238 brouard 8075: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 8076: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 8077: }
8078: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.332 brouard 8079: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]);
8080: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]);
1.238 brouard 8081: }
1.264 brouard 8082: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8083: fprintf(ficgp,"\n#\n");
8084: if(invalidvarcomb[k1]){
8085: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8086: continue;
8087: }
8088:
8089: /* k=2+nlstate*(2*cpt-2); */
8090: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 8091: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 8092: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 8093: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 8094: 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 8095: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8096: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8097: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
8098: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8099: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8100: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 8101:
1.238 brouard 8102: */
8103: for (i=1; i< nlstate ; i ++) {
1.261 brouard 8104: 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 8105: /* 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 8106:
1.238 brouard 8107: }
1.261 brouard 8108: 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 8109: }
1.264 brouard 8110: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 8111: } /* end nres */
8112: } /* end kl 3eme */
1.126 brouard 8113:
1.223 brouard 8114: /* 4eme */
1.201 brouard 8115: /* Survival functions (period) from state i in state j by initial state i */
1.238 brouard 8116: for (k1=1; k1<=m; k1++){ /* For each covariate and each value */
8117: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 8118: if(m != 1 && TKresult[nres]!= k1)
1.223 brouard 8119: continue;
1.238 brouard 8120: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 8121: strcpy(gplotlabel,"(");
1.238 brouard 8122: fprintf(ficgp,"\n#\n#\n# Survival functions in state j : 'LIJ_' files, cov=%d state=%d",k1, cpt);
8123: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.332 brouard 8124: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
8125: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate number corresponding to k1 combination *\/ */
1.238 brouard 8126: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8127: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8128: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 8129: /* vlv= nbcode[Tvaraff[k]][lv]; */
8130: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.238 brouard 8131: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 8132: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 8133: }
8134: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.332 brouard 8135: fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]);
8136: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]);
1.238 brouard 8137: }
1.264 brouard 8138: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8139: fprintf(ficgp,"\n#\n");
8140: if(invalidvarcomb[k1]){
8141: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8142: continue;
1.223 brouard 8143: }
1.238 brouard 8144:
1.241 brouard 8145: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 8146: 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 8147: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8148: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8149: k=3;
8150: for (i=1; i<= nlstate ; i ++){
8151: if(i==1){
8152: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8153: }else{
8154: fprintf(ficgp,", '' ");
8155: }
8156: l=(nlstate+ndeath)*(i-1)+1;
8157: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8158: for (j=2; j<= nlstate+ndeath ; j ++)
8159: fprintf(ficgp,"+$%d",k+l+j-1);
8160: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
8161: } /* nlstate */
1.264 brouard 8162: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8163: } /* end cpt state*/
8164: } /* end nres */
8165: } /* end covariate k1 */
8166:
1.220 brouard 8167: /* 5eme */
1.201 brouard 8168: /* Survival functions (period) from state i in state j by final state j */
1.238 brouard 8169: for (k1=1; k1<= m ; k1++){ /* For each covariate combination if any */
8170: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 8171: if(m != 1 && TKresult[nres]!= k1)
1.227 brouard 8172: continue;
1.238 brouard 8173: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 8174: strcpy(gplotlabel,"(");
1.238 brouard 8175: 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);
8176: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.332 brouard 8177: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
8178: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate number corresponding to k1 combination *\/ */
1.238 brouard 8179: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8180: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8181: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 8182: /* vlv= nbcode[Tvaraff[k]][lv]; */
8183: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.238 brouard 8184: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 8185: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 8186: }
8187: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.332 brouard 8188: fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]);
8189: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]);
1.238 brouard 8190: }
1.264 brouard 8191: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8192: fprintf(ficgp,"\n#\n");
8193: if(invalidvarcomb[k1]){
8194: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8195: continue;
8196: }
1.227 brouard 8197:
1.241 brouard 8198: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 8199: 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 8200: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8201: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8202: k=3;
8203: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8204: if(j==1)
8205: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8206: else
8207: fprintf(ficgp,", '' ");
8208: l=(nlstate+ndeath)*(cpt-1) +j;
8209: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
8210: /* for (i=2; i<= nlstate+ndeath ; i ++) */
8211: /* fprintf(ficgp,"+$%d",k+l+i-1); */
8212: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
8213: } /* nlstate */
8214: fprintf(ficgp,", '' ");
8215: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
8216: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8217: l=(nlstate+ndeath)*(cpt-1) +j;
8218: if(j < nlstate)
8219: fprintf(ficgp,"$%d +",k+l);
8220: else
8221: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
8222: }
1.264 brouard 8223: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8224: } /* end cpt state*/
8225: } /* end covariate */
8226: } /* end nres */
1.227 brouard 8227:
1.220 brouard 8228: /* 6eme */
1.202 brouard 8229: /* CV preval stable (period) for each covariate */
1.237 brouard 8230: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
8231: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 8232: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 8233: continue;
1.255 brouard 8234: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 8235: strcpy(gplotlabel,"(");
1.288 brouard 8236: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.225 brouard 8237: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.332 brouard 8238: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate number corresponding to k1 combination *\/ */
8239: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.227 brouard 8240: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8241: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8242: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 8243: /* vlv= nbcode[Tvaraff[k]][lv]; */
8244: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.227 brouard 8245: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 8246: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 8247: }
1.237 brouard 8248: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.332 brouard 8249: fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]);
8250: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]);
1.237 brouard 8251: }
1.264 brouard 8252: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8253: fprintf(ficgp,"\n#\n");
1.223 brouard 8254: if(invalidvarcomb[k1]){
1.227 brouard 8255: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8256: continue;
1.223 brouard 8257: }
1.227 brouard 8258:
1.241 brouard 8259: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 8260: 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 8261: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 8262: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 8263: k=3; /* Offset */
1.255 brouard 8264: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 8265: if(i==1)
8266: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8267: else
8268: fprintf(ficgp,", '' ");
1.255 brouard 8269: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 8270: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8271: for (j=2; j<= nlstate ; j ++)
8272: fprintf(ficgp,"+$%d",k+l+j-1);
8273: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 8274: } /* nlstate */
1.264 brouard 8275: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 8276: } /* end cpt state*/
8277: } /* end covariate */
1.227 brouard 8278:
8279:
1.220 brouard 8280: /* 7eme */
1.296 brouard 8281: if(prevbcast == 1){
1.288 brouard 8282: /* CV backward prevalence for each covariate */
1.237 brouard 8283: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
8284: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 8285: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 8286: continue;
1.268 brouard 8287: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 8288: strcpy(gplotlabel,"(");
1.288 brouard 8289: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 8290: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.332 brouard 8291: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate number corresponding to k1 combination *\/ */
8292: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.227 brouard 8293: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8294: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
1.223 brouard 8295: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 8296: /* vlv= nbcode[Tvaraff[k]][lv]; */
8297: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.227 brouard 8298: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 8299: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 8300: }
1.237 brouard 8301: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.332 brouard 8302: fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]);
8303: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]);
1.237 brouard 8304: }
1.264 brouard 8305: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 8306: fprintf(ficgp,"\n#\n");
8307: if(invalidvarcomb[k1]){
8308: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8309: continue;
8310: }
8311:
1.241 brouard 8312: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 8313: 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 8314: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 8315: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 8316: k=3; /* Offset */
1.268 brouard 8317: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 8318: if(i==1)
8319: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
8320: else
8321: fprintf(ficgp,", '' ");
8322: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 8323: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.324 brouard 8324: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
8325: /* 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 8326: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 8327: /* for (j=2; j<= nlstate ; j ++) */
8328: /* fprintf(ficgp,"+$%d",k+l+j-1); */
8329: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 8330: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 8331: } /* nlstate */
1.264 brouard 8332: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 8333: } /* end cpt state*/
8334: } /* end covariate */
1.296 brouard 8335: } /* End if prevbcast */
1.218 brouard 8336:
1.223 brouard 8337: /* 8eme */
1.218 brouard 8338: if(prevfcast==1){
1.288 brouard 8339: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 8340:
1.237 brouard 8341: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
8342: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 8343: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 8344: continue;
1.211 brouard 8345: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 8346: strcpy(gplotlabel,"(");
1.288 brouard 8347: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 8348: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
1.332 brouard 8349: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
8350: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.227 brouard 8351: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8352: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8353: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 8354: /* vlv= nbcode[Tvaraff[k]][lv]; */
8355: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.227 brouard 8356: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 8357: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 8358: }
1.237 brouard 8359: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.332 brouard 8360: fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]);
8361: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]);
1.237 brouard 8362: }
1.264 brouard 8363: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 8364: fprintf(ficgp,"\n#\n");
8365: if(invalidvarcomb[k1]){
8366: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8367: continue;
8368: }
8369:
8370: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 8371: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 8372: 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 8373: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 8374: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 8375:
8376: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
8377: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
8378: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
8379: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 8380: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8381: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8382: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8383: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 8384: if(i==istart){
1.227 brouard 8385: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
8386: }else{
8387: fprintf(ficgp,",\\\n '' ");
8388: }
8389: if(cptcoveff ==0){ /* No covariate */
8390: ioffset=2; /* Age is in 2 */
8391: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8392: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8393: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8394: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8395: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 8396: if(i==nlstate+1){
1.270 brouard 8397: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 8398: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
8399: fprintf(ficgp,",\\\n '' ");
8400: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 8401: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 8402: offyear, \
1.268 brouard 8403: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 8404: }else
1.227 brouard 8405: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
8406: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
8407: }else{ /* more than 2 covariates */
1.270 brouard 8408: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
8409: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8410: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8411: iyearc=ioffset-1;
8412: iagec=ioffset;
1.227 brouard 8413: fprintf(ficgp," u %d:(",ioffset);
8414: kl=0;
8415: strcpy(gplotcondition,"(");
8416: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
1.332 brouard 8417: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8418: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.227 brouard 8419: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8420: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8421: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 8422: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
8423: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.227 brouard 8424: kl++;
8425: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
8426: kl++;
8427: if(k <cptcoveff && cptcoveff>1)
8428: sprintf(gplotcondition+strlen(gplotcondition)," && ");
8429: }
8430: strcpy(gplotcondition+strlen(gplotcondition),")");
8431: /* 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 *\/ */
8432: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8433: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8434: /* '' 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*/
8435: if(i==nlstate+1){
1.270 brouard 8436: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
8437: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 8438: fprintf(ficgp,",\\\n '' ");
1.270 brouard 8439: fprintf(ficgp," u %d:(",iagec);
8440: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
8441: iyearc, iagec, offyear, \
8442: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 8443: /* '' 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 8444: }else{
8445: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
8446: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
8447: }
8448: } /* end if covariate */
8449: } /* nlstate */
1.264 brouard 8450: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 8451: } /* end cpt state*/
8452: } /* end covariate */
8453: } /* End if prevfcast */
1.227 brouard 8454:
1.296 brouard 8455: if(prevbcast==1){
1.268 brouard 8456: /* Back projection from cross-sectional to stable (mixed) for each covariate */
8457:
8458: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
8459: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8460: if(m != 1 && TKresult[nres]!= k1)
8461: continue;
8462: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
8463: strcpy(gplotlabel,"(");
8464: fprintf(ficgp,"\n#\n#\n#Back projection of prevalence to stable (mixed) back prevalence: 'BPROJ_' files, covariatecombination#=%d originstate=%d",k1, cpt);
8465: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
1.332 brouard 8466: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
8467: lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /* Should be the covariate value corresponding to combination k1 and covariate k */
1.268 brouard 8468: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8469: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8470: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 8471: /* vlv= nbcode[Tvaraff[k]][lv]; */
8472: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.268 brouard 8473: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
8474: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
8475: }
8476: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.332 brouard 8477: fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]);
8478: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]);
1.268 brouard 8479: }
8480: strcpy(gplotlabel+strlen(gplotlabel),")");
8481: fprintf(ficgp,"\n#\n");
8482: if(invalidvarcomb[k1]){
8483: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8484: continue;
8485: }
8486:
8487: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
8488: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
8489: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
8490: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
8491: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8492:
8493: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
8494: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
8495: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
8496: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
8497: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8498: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8499: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8500: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8501: if(i==istart){
8502: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
8503: }else{
8504: fprintf(ficgp,",\\\n '' ");
8505: }
8506: if(cptcoveff ==0){ /* No covariate */
8507: ioffset=2; /* Age is in 2 */
8508: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8509: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8510: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8511: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8512: fprintf(ficgp," u %d:(", ioffset);
8513: if(i==nlstate+1){
1.270 brouard 8514: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 8515: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
8516: fprintf(ficgp,",\\\n '' ");
8517: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 8518: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 8519: offbyear, \
8520: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
8521: }else
8522: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
8523: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
8524: }else{ /* more than 2 covariates */
1.270 brouard 8525: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
8526: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8527: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8528: iyearc=ioffset-1;
8529: iagec=ioffset;
1.268 brouard 8530: fprintf(ficgp," u %d:(",ioffset);
8531: kl=0;
8532: strcpy(gplotcondition,"(");
8533: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
1.332 brouard 8534: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8535: lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /* Should be the covariate value corresponding to combination k1 and covariate k */
1.268 brouard 8536: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8537: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8538: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 8539: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
8540: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.268 brouard 8541: kl++;
8542: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
8543: kl++;
8544: if(k <cptcoveff && cptcoveff>1)
8545: sprintf(gplotcondition+strlen(gplotcondition)," && ");
8546: }
8547: strcpy(gplotcondition+strlen(gplotcondition),")");
8548: /* 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 *\/ */
8549: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8550: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8551: /* '' 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*/
8552: if(i==nlstate+1){
1.270 brouard 8553: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
8554: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 8555: fprintf(ficgp,",\\\n '' ");
1.270 brouard 8556: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 8557: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 8558: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
8559: iyearc,iagec,offbyear, \
8560: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 8561: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
8562: }else{
8563: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
8564: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
8565: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
8566: }
8567: } /* end if covariate */
8568: } /* nlstate */
8569: fprintf(ficgp,"\nset out; unset label;\n");
8570: } /* end cpt state*/
8571: } /* end covariate */
1.296 brouard 8572: } /* End if prevbcast */
1.268 brouard 8573:
1.227 brouard 8574:
1.238 brouard 8575: /* 9eme writing MLE parameters */
8576: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 8577: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 8578: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 8579: for(k=1; k <=(nlstate+ndeath); k++){
8580: if (k != i) {
1.227 brouard 8581: fprintf(ficgp,"# current state %d\n",k);
8582: for(j=1; j <=ncovmodel; j++){
8583: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
8584: jk++;
8585: }
8586: fprintf(ficgp,"\n");
1.126 brouard 8587: }
8588: }
1.223 brouard 8589: }
1.187 brouard 8590: fprintf(ficgp,"##############\n#\n");
1.227 brouard 8591:
1.145 brouard 8592: /*goto avoid;*/
1.238 brouard 8593: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
8594: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 8595: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
8596: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
8597: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
8598: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
8599: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8600: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
8601: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8602: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
8603: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
8604: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8605: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
8606: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
8607: fprintf(ficgp,"#\n");
1.223 brouard 8608: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 8609: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.237 brouard 8610: fprintf(ficgp,"#model=%s \n",model);
1.238 brouard 8611: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 brouard 8612: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
8613: for(k1=1; k1 <=m; k1++) /* For each combination of covariate */
1.237 brouard 8614: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.264 brouard 8615: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 8616: continue;
1.264 brouard 8617: fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1);
8618: strcpy(gplotlabel,"(");
1.276 brouard 8619: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.264 brouard 8620: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
1.332 brouard 8621: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
8622: lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /* Should be the covariate value corresponding to combination k1 and covariate k */
1.264 brouard 8623: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8624: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8625: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 8626: /* vlv= nbcode[Tvaraff[k]][lv]; */
8627: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.264 brouard 8628: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
8629: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
8630: }
1.237 brouard 8631: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.332 brouard 8632: fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]);
8633: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]);
1.237 brouard 8634: }
1.264 brouard 8635: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 8636: fprintf(ficgp,"\n#\n");
1.264 brouard 8637: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 8638: fprintf(ficgp,"\nset key outside ");
8639: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
8640: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 8641: fprintf(ficgp,"\nset ter svg size 640, 480 ");
8642: if (ng==1){
8643: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
8644: fprintf(ficgp,"\nunset log y");
8645: }else if (ng==2){
8646: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
8647: fprintf(ficgp,"\nset log y");
8648: }else if (ng==3){
8649: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
8650: fprintf(ficgp,"\nset log y");
8651: }else
8652: fprintf(ficgp,"\nunset title ");
8653: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
8654: i=1;
8655: for(k2=1; k2<=nlstate; k2++) {
8656: k3=i;
8657: for(k=1; k<=(nlstate+ndeath); k++) {
8658: if (k != k2){
8659: switch( ng) {
8660: case 1:
8661: if(nagesqr==0)
8662: fprintf(ficgp," p%d+p%d*x",i,i+1);
8663: else /* nagesqr =1 */
8664: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
8665: break;
8666: case 2: /* ng=2 */
8667: if(nagesqr==0)
8668: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
8669: else /* nagesqr =1 */
8670: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
8671: break;
8672: case 3:
8673: if(nagesqr==0)
8674: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
8675: else /* nagesqr =1 */
8676: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
8677: break;
8678: }
8679: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 8680: ijp=1; /* product no age */
8681: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
8682: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 8683: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.329 brouard 8684: switch(Typevar[j]){
8685: case 1:
8686: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
8687: if(j==Tage[ij]) { /* Product by age To be looked at!!*//* Bug valgrind */
8688: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
8689: if(DummyV[j]==0){/* Bug valgrind */
8690: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
8691: }else{ /* quantitative */
8692: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
8693: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8694: }
8695: ij++;
1.268 brouard 8696: }
1.237 brouard 8697: }
1.329 brouard 8698: }
8699: break;
8700: case 2:
8701: if(cptcovprod >0){
8702: if(j==Tprod[ijp]) { /* */
8703: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
8704: if(ijp <=cptcovprod) { /* Product */
8705: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
8706: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
8707: /* 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)]); */
8708: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
8709: }else{ /* Vn is dummy and Vm is quanti */
8710: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
8711: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8712: }
8713: }else{ /* Vn*Vm Vn is quanti */
8714: if(DummyV[Tvard[ijp][2]]==0){
8715: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
8716: }else{ /* Both quanti */
8717: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8718: }
1.268 brouard 8719: }
1.329 brouard 8720: ijp++;
1.237 brouard 8721: }
1.329 brouard 8722: } /* end Tprod */
8723: }
8724: break;
8725: case 0:
8726: /* simple covariate */
1.264 brouard 8727: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 8728: if(Dummy[j]==0){
8729: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
8730: }else{ /* quantitative */
8731: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 8732: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 8733: }
1.329 brouard 8734: /* end simple */
8735: break;
8736: default:
8737: break;
8738: } /* end switch */
1.237 brouard 8739: } /* end j */
1.329 brouard 8740: }else{ /* k=k2 */
8741: if(ng !=1 ){ /* For logit formula of log p11 is more difficult to get */
8742: fprintf(ficgp," (1.");i=i-ncovmodel;
8743: }else
8744: i=i-ncovmodel;
1.223 brouard 8745: }
1.227 brouard 8746:
1.223 brouard 8747: if(ng != 1){
8748: fprintf(ficgp,")/(1");
1.227 brouard 8749:
1.264 brouard 8750: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 8751: if(nagesqr==0)
1.264 brouard 8752: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 8753: else /* nagesqr =1 */
1.264 brouard 8754: 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 8755:
1.223 brouard 8756: ij=1;
1.329 brouard 8757: ijp=1;
8758: /* for(j=3; j <=ncovmodel-nagesqr; j++){ */
8759: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
8760: switch(Typevar[j]){
8761: case 1:
8762: if(cptcovage >0){
8763: if(j==Tage[ij]) { /* Bug valgrind */
8764: if(ij <=cptcovage) { /* Bug valgrind */
8765: if(DummyV[j]==0){/* Bug valgrind */
8766: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]); */
8767: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,nbcode[Tvar[j]][codtabm(k1,j)]); */
8768: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]);
8769: /* fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);; */
8770: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8771: }else{ /* quantitative */
8772: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
8773: fprintf(ficgp,"+p%d*%f*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
8774: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
8775: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8776: }
8777: ij++;
8778: }
8779: }
8780: }
8781: break;
8782: case 2:
8783: if(cptcovprod >0){
8784: if(j==Tprod[ijp]) { /* */
8785: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
8786: if(ijp <=cptcovprod) { /* Product */
8787: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
8788: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
8789: /* 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)]); */
8790: fprintf(ficgp,"+p%d*%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
8791: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
8792: }else{ /* Vn is dummy and Vm is quanti */
8793: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
8794: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8795: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
8796: }
8797: }else{ /* Vn*Vm Vn is quanti */
8798: if(DummyV[Tvard[ijp][2]]==0){
8799: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
8800: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
8801: }else{ /* Both quanti */
8802: fprintf(ficgp,"+p%d*%f*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8803: /* fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
8804: }
8805: }
8806: ijp++;
8807: }
8808: } /* end Tprod */
8809: } /* end if */
8810: break;
8811: case 0:
8812: /* simple covariate */
8813: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
8814: if(Dummy[j]==0){
8815: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
8816: fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]); /* */
8817: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
8818: }else{ /* quantitative */
8819: fprintf(ficgp,"+p%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* */
8820: /* fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* *\/ */
8821: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8822: }
8823: /* end simple */
8824: /* fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);/\* Valgrind bug nbcode *\/ */
8825: break;
8826: default:
8827: break;
8828: } /* end switch */
1.223 brouard 8829: }
8830: fprintf(ficgp,")");
8831: }
8832: fprintf(ficgp,")");
8833: if(ng ==2)
1.276 brouard 8834: 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 8835: else /* ng= 3 */
1.276 brouard 8836: 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 8837: }else{ /* end ng <> 1 */
1.223 brouard 8838: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 8839: 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 8840: }
8841: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
8842: fprintf(ficgp,",");
8843: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
8844: fprintf(ficgp,",");
8845: i=i+ncovmodel;
8846: } /* end k */
8847: } /* end k2 */
1.276 brouard 8848: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
8849: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.264 brouard 8850: } /* end k1 */
1.223 brouard 8851: } /* end ng */
8852: /* avoid: */
8853: fflush(ficgp);
1.126 brouard 8854: } /* end gnuplot */
8855:
8856:
8857: /*************** Moving average **************/
1.219 brouard 8858: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 8859: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 8860:
1.222 brouard 8861: int i, cpt, cptcod;
8862: int modcovmax =1;
8863: int mobilavrange, mob;
8864: int iage=0;
1.288 brouard 8865: int firstA1=0, firstA2=0;
1.222 brouard 8866:
1.266 brouard 8867: double sum=0., sumr=0.;
1.222 brouard 8868: double age;
1.266 brouard 8869: double *sumnewp, *sumnewm, *sumnewmr;
8870: double *agemingood, *agemaxgood;
8871: double *agemingoodr, *agemaxgoodr;
1.222 brouard 8872:
8873:
1.278 brouard 8874: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
8875: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 8876:
8877: sumnewp = vector(1,ncovcombmax);
8878: sumnewm = vector(1,ncovcombmax);
1.266 brouard 8879: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 8880: agemingood = vector(1,ncovcombmax);
1.266 brouard 8881: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 8882: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 8883: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 8884:
8885: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 8886: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 8887: sumnewp[cptcod]=0.;
1.266 brouard 8888: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
8889: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 8890: }
8891: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
8892:
1.266 brouard 8893: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
8894: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 8895: else mobilavrange=mobilav;
8896: for (age=bage; age<=fage; age++)
8897: for (i=1; i<=nlstate;i++)
8898: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
8899: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8900: /* We keep the original values on the extreme ages bage, fage and for
8901: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
8902: we use a 5 terms etc. until the borders are no more concerned.
8903: */
8904: for (mob=3;mob <=mobilavrange;mob=mob+2){
8905: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 8906: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
8907: sumnewm[cptcod]=0.;
8908: for (i=1; i<=nlstate;i++){
1.222 brouard 8909: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
8910: for (cpt=1;cpt<=(mob-1)/2;cpt++){
8911: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
8912: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
8913: }
8914: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 8915: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8916: } /* end i */
8917: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
8918: } /* end cptcod */
1.222 brouard 8919: }/* end age */
8920: }/* end mob */
1.266 brouard 8921: }else{
8922: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 8923: return -1;
1.266 brouard 8924: }
8925:
8926: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 8927: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
8928: if(invalidvarcomb[cptcod]){
8929: printf("\nCombination (%d) ignored because no cases \n",cptcod);
8930: continue;
8931: }
1.219 brouard 8932:
1.266 brouard 8933: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
8934: sumnewm[cptcod]=0.;
8935: sumnewmr[cptcod]=0.;
8936: for (i=1; i<=nlstate;i++){
8937: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8938: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8939: }
8940: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8941: agemingoodr[cptcod]=age;
8942: }
8943: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8944: agemingood[cptcod]=age;
8945: }
8946: } /* age */
8947: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 8948: sumnewm[cptcod]=0.;
1.266 brouard 8949: sumnewmr[cptcod]=0.;
1.222 brouard 8950: for (i=1; i<=nlstate;i++){
8951: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8952: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8953: }
8954: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8955: agemaxgoodr[cptcod]=age;
1.222 brouard 8956: }
8957: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 8958: agemaxgood[cptcod]=age;
8959: }
8960: } /* age */
8961: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
8962: /* but they will change */
1.288 brouard 8963: firstA1=0;firstA2=0;
1.266 brouard 8964: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
8965: sumnewm[cptcod]=0.;
8966: sumnewmr[cptcod]=0.;
8967: for (i=1; i<=nlstate;i++){
8968: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8969: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8970: }
8971: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8972: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8973: agemaxgoodr[cptcod]=age; /* age min */
8974: for (i=1; i<=nlstate;i++)
8975: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8976: }else{ /* bad we change the value with the values of good ages */
8977: for (i=1; i<=nlstate;i++){
8978: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
8979: } /* i */
8980: } /* end bad */
8981: }else{
8982: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8983: agemaxgood[cptcod]=age;
8984: }else{ /* bad we change the value with the values of good ages */
8985: for (i=1; i<=nlstate;i++){
8986: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
8987: } /* i */
8988: } /* end bad */
8989: }/* end else */
8990: sum=0.;sumr=0.;
8991: for (i=1; i<=nlstate;i++){
8992: sum+=mobaverage[(int)age][i][cptcod];
8993: sumr+=probs[(int)age][i][cptcod];
8994: }
8995: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 8996: if(!firstA1){
8997: firstA1=1;
8998: 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);
8999: }
9000: 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 9001: } /* end bad */
9002: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
9003: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 9004: if(!firstA2){
9005: firstA2=1;
9006: 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);
9007: }
9008: 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 9009: } /* end bad */
9010: }/* age */
1.266 brouard 9011:
9012: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 9013: sumnewm[cptcod]=0.;
1.266 brouard 9014: sumnewmr[cptcod]=0.;
1.222 brouard 9015: for (i=1; i<=nlstate;i++){
9016: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 9017: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9018: }
9019: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
9020: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
9021: agemingoodr[cptcod]=age;
9022: for (i=1; i<=nlstate;i++)
9023: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9024: }else{ /* bad we change the value with the values of good ages */
9025: for (i=1; i<=nlstate;i++){
9026: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
9027: } /* i */
9028: } /* end bad */
9029: }else{
9030: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9031: agemingood[cptcod]=age;
9032: }else{ /* bad */
9033: for (i=1; i<=nlstate;i++){
9034: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
9035: } /* i */
9036: } /* end bad */
9037: }/* end else */
9038: sum=0.;sumr=0.;
9039: for (i=1; i<=nlstate;i++){
9040: sum+=mobaverage[(int)age][i][cptcod];
9041: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 9042: }
1.266 brouard 9043: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 9044: 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 9045: } /* end bad */
9046: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
9047: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 9048: 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 9049: } /* end bad */
9050: }/* age */
1.266 brouard 9051:
1.222 brouard 9052:
9053: for (age=bage; age<=fage; age++){
1.235 brouard 9054: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 9055: sumnewp[cptcod]=0.;
9056: sumnewm[cptcod]=0.;
9057: for (i=1; i<=nlstate;i++){
9058: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
9059: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9060: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
9061: }
9062: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
9063: }
9064: /* printf("\n"); */
9065: /* } */
1.266 brouard 9066:
1.222 brouard 9067: /* brutal averaging */
1.266 brouard 9068: /* for (i=1; i<=nlstate;i++){ */
9069: /* for (age=1; age<=bage; age++){ */
9070: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
9071: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
9072: /* } */
9073: /* for (age=fage; age<=AGESUP; age++){ */
9074: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
9075: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
9076: /* } */
9077: /* } /\* end i status *\/ */
9078: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
9079: /* for (age=1; age<=AGESUP; age++){ */
9080: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
9081: /* mobaverage[(int)age][i][cptcod]=0.; */
9082: /* } */
9083: /* } */
1.222 brouard 9084: }/* end cptcod */
1.266 brouard 9085: free_vector(agemaxgoodr,1, ncovcombmax);
9086: free_vector(agemaxgood,1, ncovcombmax);
9087: free_vector(agemingood,1, ncovcombmax);
9088: free_vector(agemingoodr,1, ncovcombmax);
9089: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 9090: free_vector(sumnewm,1, ncovcombmax);
9091: free_vector(sumnewp,1, ncovcombmax);
9092: return 0;
9093: }/* End movingaverage */
1.218 brouard 9094:
1.126 brouard 9095:
1.296 brouard 9096:
1.126 brouard 9097: /************** Forecasting ******************/
1.296 brouard 9098: /* 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)*/
9099: 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){
9100: /* dateintemean, mean date of interviews
9101: dateprojd, year, month, day of starting projection
9102: dateprojf date of end of projection;year of end of projection (same day and month as proj1).
1.126 brouard 9103: agemin, agemax range of age
9104: dateprev1 dateprev2 range of dates during which prevalence is computed
9105: */
1.296 brouard 9106: /* double anprojd, mprojd, jprojd; */
9107: /* double anprojf, mprojf, jprojf; */
1.267 brouard 9108: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 9109: double agec; /* generic age */
1.296 brouard 9110: double agelim, ppij, yp,yp1,yp2;
1.126 brouard 9111: double *popeffectif,*popcount;
9112: double ***p3mat;
1.218 brouard 9113: /* double ***mobaverage; */
1.126 brouard 9114: char fileresf[FILENAMELENGTH];
9115:
9116: agelim=AGESUP;
1.211 brouard 9117: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
9118: in each health status at the date of interview (if between dateprev1 and dateprev2).
9119: We still use firstpass and lastpass as another selection.
9120: */
1.214 brouard 9121: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
9122: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 9123:
1.201 brouard 9124: strcpy(fileresf,"F_");
9125: strcat(fileresf,fileresu);
1.126 brouard 9126: if((ficresf=fopen(fileresf,"w"))==NULL) {
9127: printf("Problem with forecast resultfile: %s\n", fileresf);
9128: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
9129: }
1.235 brouard 9130: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
9131: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 9132:
1.225 brouard 9133: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 9134:
9135:
9136: stepsize=(int) (stepm+YEARM-1)/YEARM;
9137: if (stepm<=12) stepsize=1;
9138: if(estepm < stepm){
9139: printf ("Problem %d lower than %d\n",estepm, stepm);
9140: }
1.270 brouard 9141: else{
9142: hstepm=estepm;
9143: }
9144: if(estepm > stepm){ /* Yes every two year */
9145: stepsize=2;
9146: }
1.296 brouard 9147: hstepm=hstepm/stepm;
1.126 brouard 9148:
1.296 brouard 9149:
9150: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
9151: /* fractional in yp1 *\/ */
9152: /* aintmean=yp; */
9153: /* yp2=modf((yp1*12),&yp); */
9154: /* mintmean=yp; */
9155: /* yp1=modf((yp2*30.5),&yp); */
9156: /* jintmean=yp; */
9157: /* if(jintmean==0) jintmean=1; */
9158: /* if(mintmean==0) mintmean=1; */
1.126 brouard 9159:
1.296 brouard 9160:
9161: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */
9162: /* date2dmy(dateprojd,&jprojd, &mprojd, &anprojd); */
9163: /* date2dmy(dateprojf,&jprojf, &mprojf, &anprojf); */
1.227 brouard 9164: i1=pow(2,cptcoveff);
1.126 brouard 9165: if (cptcovn < 1){i1=1;}
9166:
1.296 brouard 9167: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.126 brouard 9168:
9169: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 9170:
1.126 brouard 9171: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 9172: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.332 brouard 9173: 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) */
1.253 brouard 9174: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 9175: continue;
1.227 brouard 9176: if(invalidvarcomb[k]){
9177: printf("\nCombination (%d) projection ignored because no cases \n",k);
9178: continue;
9179: }
9180: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
9181: for(j=1;j<=cptcoveff;j++) {
1.332 brouard 9182: /* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); */
9183: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.227 brouard 9184: }
1.235 brouard 9185: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 9186: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 9187: }
1.227 brouard 9188: fprintf(ficresf," yearproj age");
9189: for(j=1; j<=nlstate+ndeath;j++){
9190: for(i=1; i<=nlstate;i++)
9191: fprintf(ficresf," p%d%d",i,j);
9192: fprintf(ficresf," wp.%d",j);
9193: }
1.296 brouard 9194: for (yearp=0; yearp<=(anprojf-anprojd);yearp +=stepsize) {
1.227 brouard 9195: fprintf(ficresf,"\n");
1.296 brouard 9196: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jprojd,mprojd,anprojd+yearp);
1.270 brouard 9197: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
9198: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 9199: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
9200: nhstepm = nhstepm/hstepm;
9201: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9202: oldm=oldms;savm=savms;
1.268 brouard 9203: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 9204: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 9205: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 9206: for (h=0; h<=nhstepm; h++){
9207: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 9208: break;
9209: }
9210: }
9211: fprintf(ficresf,"\n");
9212: for(j=1;j<=cptcoveff;j++)
1.332 brouard 9213: /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Tvaraff not correct *\/ */
9214: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /* TnsdVar[Tvaraff] correct */
1.296 brouard 9215: fprintf(ficresf,"%.f %.f ",anprojd+yearp,agec+h*hstepm/YEARM*stepm);
1.268 brouard 9216:
9217: for(j=1; j<=nlstate+ndeath;j++) {
9218: ppij=0.;
9219: for(i=1; i<=nlstate;i++) {
1.278 brouard 9220: if (mobilav>=1)
9221: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
9222: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
9223: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
9224: }
1.268 brouard 9225: fprintf(ficresf," %.3f", p3mat[i][j][h]);
9226: } /* end i */
9227: fprintf(ficresf," %.3f", ppij);
9228: }/* end j */
1.227 brouard 9229: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9230: } /* end agec */
1.266 brouard 9231: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
9232: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 9233: } /* end yearp */
9234: } /* end k */
1.219 brouard 9235:
1.126 brouard 9236: fclose(ficresf);
1.215 brouard 9237: printf("End of Computing forecasting \n");
9238: fprintf(ficlog,"End of Computing forecasting\n");
9239:
1.126 brouard 9240: }
9241:
1.269 brouard 9242: /************** Back Forecasting ******************/
1.296 brouard 9243: /* 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){ */
9244: 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){
9245: /* back1, year, month, day of starting backprojection
1.267 brouard 9246: agemin, agemax range of age
9247: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 9248: anback2 year of end of backprojection (same day and month as back1).
9249: prevacurrent and prev are prevalences.
1.267 brouard 9250: */
9251: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
9252: double agec; /* generic age */
1.302 brouard 9253: double agelim, ppij, ppi, yp,yp1,yp2; /* ,jintmean,mintmean,aintmean;*/
1.267 brouard 9254: double *popeffectif,*popcount;
9255: double ***p3mat;
9256: /* double ***mobaverage; */
9257: char fileresfb[FILENAMELENGTH];
9258:
1.268 brouard 9259: agelim=AGEINF;
1.267 brouard 9260: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
9261: in each health status at the date of interview (if between dateprev1 and dateprev2).
9262: We still use firstpass and lastpass as another selection.
9263: */
9264: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
9265: /* firstpass, lastpass, stepm, weightopt, model); */
9266:
9267: /*Do we need to compute prevalence again?*/
9268:
9269: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
9270:
9271: strcpy(fileresfb,"FB_");
9272: strcat(fileresfb,fileresu);
9273: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
9274: printf("Problem with back forecast resultfile: %s\n", fileresfb);
9275: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
9276: }
9277: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
9278: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
9279:
9280: if (cptcoveff==0) ncodemax[cptcoveff]=1;
9281:
9282:
9283: stepsize=(int) (stepm+YEARM-1)/YEARM;
9284: if (stepm<=12) stepsize=1;
9285: if(estepm < stepm){
9286: printf ("Problem %d lower than %d\n",estepm, stepm);
9287: }
1.270 brouard 9288: else{
9289: hstepm=estepm;
9290: }
9291: if(estepm >= stepm){ /* Yes every two year */
9292: stepsize=2;
9293: }
1.267 brouard 9294:
9295: hstepm=hstepm/stepm;
1.296 brouard 9296: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
9297: /* fractional in yp1 *\/ */
9298: /* aintmean=yp; */
9299: /* yp2=modf((yp1*12),&yp); */
9300: /* mintmean=yp; */
9301: /* yp1=modf((yp2*30.5),&yp); */
9302: /* jintmean=yp; */
9303: /* if(jintmean==0) jintmean=1; */
9304: /* if(mintmean==0) jintmean=1; */
1.267 brouard 9305:
9306: i1=pow(2,cptcoveff);
9307: if (cptcovn < 1){i1=1;}
9308:
1.296 brouard 9309: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
9310: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 9311:
9312: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
9313:
9314: for(nres=1; nres <= nresult; nres++) /* For each resultline */
9315: for(k=1; k<=i1;k++){
9316: if(i1 != 1 && TKresult[nres]!= k)
9317: continue;
9318: if(invalidvarcomb[k]){
9319: printf("\nCombination (%d) projection ignored because no cases \n",k);
9320: continue;
9321: }
1.268 brouard 9322: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.267 brouard 9323: for(j=1;j<=cptcoveff;j++) {
1.332 brouard 9324: fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.267 brouard 9325: }
9326: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
9327: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
9328: }
9329: fprintf(ficresfb," yearbproj age");
9330: for(j=1; j<=nlstate+ndeath;j++){
9331: for(i=1; i<=nlstate;i++)
1.268 brouard 9332: fprintf(ficresfb," b%d%d",i,j);
9333: fprintf(ficresfb," b.%d",j);
1.267 brouard 9334: }
1.296 brouard 9335: for (yearp=0; yearp>=(anbackf-anbackd);yearp -=stepsize) {
1.267 brouard 9336: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
9337: fprintf(ficresfb,"\n");
1.296 brouard 9338: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jbackd,mbackd,anbackd+yearp);
1.273 brouard 9339: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 9340: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
9341: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 9342: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 9343: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 9344: nhstepm = nhstepm/hstepm;
9345: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9346: oldm=oldms;savm=savms;
1.268 brouard 9347: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 9348: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 9349: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 9350: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
9351: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
9352: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 9353: for (h=0; h<=nhstepm; h++){
1.268 brouard 9354: if (h*hstepm/YEARM*stepm ==-yearp) {
9355: break;
9356: }
9357: }
9358: fprintf(ficresfb,"\n");
9359: for(j=1;j<=cptcoveff;j++)
1.332 brouard 9360: fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.296 brouard 9361: fprintf(ficresfb,"%.f %.f ",anbackd+yearp,agec-h*hstepm/YEARM*stepm);
1.268 brouard 9362: for(i=1; i<=nlstate+ndeath;i++) {
9363: ppij=0.;ppi=0.;
9364: for(j=1; j<=nlstate;j++) {
9365: /* if (mobilav==1) */
1.269 brouard 9366: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
9367: ppi=ppi+prevacurrent[(int)agec][j][k];
9368: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
9369: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 9370: /* else { */
9371: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
9372: /* } */
1.268 brouard 9373: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
9374: } /* end j */
9375: if(ppi <0.99){
9376: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
9377: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
9378: }
9379: fprintf(ficresfb," %.3f", ppij);
9380: }/* end j */
1.267 brouard 9381: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9382: } /* end agec */
9383: } /* end yearp */
9384: } /* end k */
1.217 brouard 9385:
1.267 brouard 9386: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 9387:
1.267 brouard 9388: fclose(ficresfb);
9389: printf("End of Computing Back forecasting \n");
9390: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 9391:
1.267 brouard 9392: }
1.217 brouard 9393:
1.269 brouard 9394: /* Variance of prevalence limit: varprlim */
9395: 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 9396: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 9397:
9398: char fileresvpl[FILENAMELENGTH];
9399: FILE *ficresvpl;
9400: double **oldm, **savm;
9401: double **varpl; /* Variances of prevalence limits by age */
9402: int i1, k, nres, j ;
9403:
9404: strcpy(fileresvpl,"VPL_");
9405: strcat(fileresvpl,fileresu);
9406: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 9407: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 9408: exit(0);
9409: }
1.288 brouard 9410: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
9411: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 9412:
9413: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
9414: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
9415:
9416: i1=pow(2,cptcoveff);
9417: if (cptcovn < 1){i1=1;}
9418:
9419: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.332 brouard 9420: for(k=1; k<=i1;k++){ /* We find the combination equivalent to result line values of dummies */
1.269 brouard 9421: if(i1 != 1 && TKresult[nres]!= k)
9422: continue;
9423: fprintf(ficresvpl,"\n#****** ");
9424: printf("\n#****** ");
9425: fprintf(ficlog,"\n#****** ");
9426: for(j=1;j<=cptcoveff;j++) {
1.332 brouard 9427: fprintf(ficresvpl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
9428: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
9429: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.269 brouard 9430: }
9431: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.332 brouard 9432: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]);
9433: fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]);
9434: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]);
1.269 brouard 9435: }
9436: fprintf(ficresvpl,"******\n");
9437: printf("******\n");
9438: fprintf(ficlog,"******\n");
9439:
9440: varpl=matrix(1,nlstate,(int) bage, (int) fage);
9441: oldm=oldms;savm=savms;
9442: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
9443: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
9444: /*}*/
9445: }
9446:
9447: fclose(ficresvpl);
1.288 brouard 9448: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
9449: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 9450:
9451: }
9452: /* Variance of back prevalence: varbprlim */
9453: 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){
9454: /*------- Variance of back (stable) prevalence------*/
9455:
9456: char fileresvbl[FILENAMELENGTH];
9457: FILE *ficresvbl;
9458:
9459: double **oldm, **savm;
9460: double **varbpl; /* Variances of back prevalence limits by age */
9461: int i1, k, nres, j ;
9462:
9463: strcpy(fileresvbl,"VBL_");
9464: strcat(fileresvbl,fileresu);
9465: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
9466: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
9467: exit(0);
9468: }
9469: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
9470: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
9471:
9472:
9473: i1=pow(2,cptcoveff);
9474: if (cptcovn < 1){i1=1;}
9475:
9476: for(nres=1; nres <= nresult; nres++) /* For each resultline */
9477: for(k=1; k<=i1;k++){
9478: if(i1 != 1 && TKresult[nres]!= k)
9479: continue;
9480: fprintf(ficresvbl,"\n#****** ");
9481: printf("\n#****** ");
9482: fprintf(ficlog,"\n#****** ");
9483: for(j=1;j<=cptcoveff;j++) {
1.332 brouard 9484: fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
9485: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
9486: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.269 brouard 9487: }
9488: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.332 brouard 9489: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]);
9490: fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]);
9491: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]);
1.269 brouard 9492: }
9493: fprintf(ficresvbl,"******\n");
9494: printf("******\n");
9495: fprintf(ficlog,"******\n");
9496:
9497: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
9498: oldm=oldms;savm=savms;
9499:
9500: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
9501: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
9502: /*}*/
9503: }
9504:
9505: fclose(ficresvbl);
9506: printf("done variance-covariance of back prevalence\n");fflush(stdout);
9507: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
9508:
9509: } /* End of varbprlim */
9510:
1.126 brouard 9511: /************** Forecasting *****not tested NB*************/
1.227 brouard 9512: /* 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 9513:
1.227 brouard 9514: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
9515: /* int *popage; */
9516: /* double calagedatem, agelim, kk1, kk2; */
9517: /* double *popeffectif,*popcount; */
9518: /* double ***p3mat,***tabpop,***tabpopprev; */
9519: /* /\* double ***mobaverage; *\/ */
9520: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 9521:
1.227 brouard 9522: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9523: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9524: /* agelim=AGESUP; */
9525: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 9526:
1.227 brouard 9527: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 9528:
9529:
1.227 brouard 9530: /* strcpy(filerespop,"POP_"); */
9531: /* strcat(filerespop,fileresu); */
9532: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
9533: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
9534: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
9535: /* } */
9536: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
9537: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 9538:
1.227 brouard 9539: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 9540:
1.227 brouard 9541: /* /\* if (mobilav!=0) { *\/ */
9542: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
9543: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
9544: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
9545: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
9546: /* /\* } *\/ */
9547: /* /\* } *\/ */
1.126 brouard 9548:
1.227 brouard 9549: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
9550: /* if (stepm<=12) stepsize=1; */
1.126 brouard 9551:
1.227 brouard 9552: /* agelim=AGESUP; */
1.126 brouard 9553:
1.227 brouard 9554: /* hstepm=1; */
9555: /* hstepm=hstepm/stepm; */
1.218 brouard 9556:
1.227 brouard 9557: /* if (popforecast==1) { */
9558: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
9559: /* printf("Problem with population file : %s\n",popfile);exit(0); */
9560: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
9561: /* } */
9562: /* popage=ivector(0,AGESUP); */
9563: /* popeffectif=vector(0,AGESUP); */
9564: /* popcount=vector(0,AGESUP); */
1.126 brouard 9565:
1.227 brouard 9566: /* i=1; */
9567: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 9568:
1.227 brouard 9569: /* imx=i; */
9570: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
9571: /* } */
1.218 brouard 9572:
1.227 brouard 9573: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
9574: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
9575: /* k=k+1; */
9576: /* fprintf(ficrespop,"\n#******"); */
9577: /* for(j=1;j<=cptcoveff;j++) { */
9578: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
9579: /* } */
9580: /* fprintf(ficrespop,"******\n"); */
9581: /* fprintf(ficrespop,"# Age"); */
9582: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
9583: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 9584:
1.227 brouard 9585: /* for (cpt=0; cpt<=0;cpt++) { */
9586: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 9587:
1.227 brouard 9588: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
9589: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
9590: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 9591:
1.227 brouard 9592: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9593: /* oldm=oldms;savm=savms; */
9594: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 9595:
1.227 brouard 9596: /* for (h=0; h<=nhstepm; h++){ */
9597: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
9598: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
9599: /* } */
9600: /* for(j=1; j<=nlstate+ndeath;j++) { */
9601: /* kk1=0.;kk2=0; */
9602: /* for(i=1; i<=nlstate;i++) { */
9603: /* if (mobilav==1) */
9604: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
9605: /* else { */
9606: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
9607: /* } */
9608: /* } */
9609: /* if (h==(int)(calagedatem+12*cpt)){ */
9610: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
9611: /* /\*fprintf(ficrespop," %.3f", kk1); */
9612: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
9613: /* } */
9614: /* } */
9615: /* for(i=1; i<=nlstate;i++){ */
9616: /* kk1=0.; */
9617: /* for(j=1; j<=nlstate;j++){ */
9618: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
9619: /* } */
9620: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
9621: /* } */
1.218 brouard 9622:
1.227 brouard 9623: /* if (h==(int)(calagedatem+12*cpt)) */
9624: /* for(j=1; j<=nlstate;j++) */
9625: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
9626: /* } */
9627: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9628: /* } */
9629: /* } */
1.218 brouard 9630:
1.227 brouard 9631: /* /\******\/ */
1.218 brouard 9632:
1.227 brouard 9633: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
9634: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
9635: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
9636: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
9637: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 9638:
1.227 brouard 9639: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9640: /* oldm=oldms;savm=savms; */
9641: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
9642: /* for (h=0; h<=nhstepm; h++){ */
9643: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
9644: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
9645: /* } */
9646: /* for(j=1; j<=nlstate+ndeath;j++) { */
9647: /* kk1=0.;kk2=0; */
9648: /* for(i=1; i<=nlstate;i++) { */
9649: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
9650: /* } */
9651: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
9652: /* } */
9653: /* } */
9654: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9655: /* } */
9656: /* } */
9657: /* } */
9658: /* } */
1.218 brouard 9659:
1.227 brouard 9660: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 9661:
1.227 brouard 9662: /* if (popforecast==1) { */
9663: /* free_ivector(popage,0,AGESUP); */
9664: /* free_vector(popeffectif,0,AGESUP); */
9665: /* free_vector(popcount,0,AGESUP); */
9666: /* } */
9667: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9668: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9669: /* fclose(ficrespop); */
9670: /* } /\* End of popforecast *\/ */
1.218 brouard 9671:
1.126 brouard 9672: int fileappend(FILE *fichier, char *optionfich)
9673: {
9674: if((fichier=fopen(optionfich,"a"))==NULL) {
9675: printf("Problem with file: %s\n", optionfich);
9676: fprintf(ficlog,"Problem with file: %s\n", optionfich);
9677: return (0);
9678: }
9679: fflush(fichier);
9680: return (1);
9681: }
9682:
9683:
9684: /**************** function prwizard **********************/
9685: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
9686: {
9687:
9688: /* Wizard to print covariance matrix template */
9689:
1.164 brouard 9690: char ca[32], cb[32];
9691: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 9692: int numlinepar;
9693:
9694: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
9695: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
9696: for(i=1; i <=nlstate; i++){
9697: jj=0;
9698: for(j=1; j <=nlstate+ndeath; j++){
9699: if(j==i) continue;
9700: jj++;
9701: /*ca[0]= k+'a'-1;ca[1]='\0';*/
9702: printf("%1d%1d",i,j);
9703: fprintf(ficparo,"%1d%1d",i,j);
9704: for(k=1; k<=ncovmodel;k++){
9705: /* printf(" %lf",param[i][j][k]); */
9706: /* fprintf(ficparo," %lf",param[i][j][k]); */
9707: printf(" 0.");
9708: fprintf(ficparo," 0.");
9709: }
9710: printf("\n");
9711: fprintf(ficparo,"\n");
9712: }
9713: }
9714: printf("# Scales (for hessian or gradient estimation)\n");
9715: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
9716: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
9717: for(i=1; i <=nlstate; i++){
9718: jj=0;
9719: for(j=1; j <=nlstate+ndeath; j++){
9720: if(j==i) continue;
9721: jj++;
9722: fprintf(ficparo,"%1d%1d",i,j);
9723: printf("%1d%1d",i,j);
9724: fflush(stdout);
9725: for(k=1; k<=ncovmodel;k++){
9726: /* printf(" %le",delti3[i][j][k]); */
9727: /* fprintf(ficparo," %le",delti3[i][j][k]); */
9728: printf(" 0.");
9729: fprintf(ficparo," 0.");
9730: }
9731: numlinepar++;
9732: printf("\n");
9733: fprintf(ficparo,"\n");
9734: }
9735: }
9736: printf("# Covariance matrix\n");
9737: /* # 121 Var(a12)\n\ */
9738: /* # 122 Cov(b12,a12) Var(b12)\n\ */
9739: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
9740: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
9741: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
9742: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
9743: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
9744: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
9745: fflush(stdout);
9746: fprintf(ficparo,"# Covariance matrix\n");
9747: /* # 121 Var(a12)\n\ */
9748: /* # 122 Cov(b12,a12) Var(b12)\n\ */
9749: /* # ...\n\ */
9750: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
9751:
9752: for(itimes=1;itimes<=2;itimes++){
9753: jj=0;
9754: for(i=1; i <=nlstate; i++){
9755: for(j=1; j <=nlstate+ndeath; j++){
9756: if(j==i) continue;
9757: for(k=1; k<=ncovmodel;k++){
9758: jj++;
9759: ca[0]= k+'a'-1;ca[1]='\0';
9760: if(itimes==1){
9761: printf("#%1d%1d%d",i,j,k);
9762: fprintf(ficparo,"#%1d%1d%d",i,j,k);
9763: }else{
9764: printf("%1d%1d%d",i,j,k);
9765: fprintf(ficparo,"%1d%1d%d",i,j,k);
9766: /* printf(" %.5le",matcov[i][j]); */
9767: }
9768: ll=0;
9769: for(li=1;li <=nlstate; li++){
9770: for(lj=1;lj <=nlstate+ndeath; lj++){
9771: if(lj==li) continue;
9772: for(lk=1;lk<=ncovmodel;lk++){
9773: ll++;
9774: if(ll<=jj){
9775: cb[0]= lk +'a'-1;cb[1]='\0';
9776: if(ll<jj){
9777: if(itimes==1){
9778: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
9779: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
9780: }else{
9781: printf(" 0.");
9782: fprintf(ficparo," 0.");
9783: }
9784: }else{
9785: if(itimes==1){
9786: printf(" Var(%s%1d%1d)",ca,i,j);
9787: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
9788: }else{
9789: printf(" 0.");
9790: fprintf(ficparo," 0.");
9791: }
9792: }
9793: }
9794: } /* end lk */
9795: } /* end lj */
9796: } /* end li */
9797: printf("\n");
9798: fprintf(ficparo,"\n");
9799: numlinepar++;
9800: } /* end k*/
9801: } /*end j */
9802: } /* end i */
9803: } /* end itimes */
9804:
9805: } /* end of prwizard */
9806: /******************* Gompertz Likelihood ******************************/
9807: double gompertz(double x[])
9808: {
1.302 brouard 9809: double A=0.0,B=0.,L=0.0,sump=0.,num=0.;
1.126 brouard 9810: int i,n=0; /* n is the size of the sample */
9811:
1.220 brouard 9812: for (i=1;i<=imx ; i++) {
1.126 brouard 9813: sump=sump+weight[i];
9814: /* sump=sump+1;*/
9815: num=num+1;
9816: }
1.302 brouard 9817: L=0.0;
9818: /* agegomp=AGEGOMP; */
1.126 brouard 9819: /* for (i=0; i<=imx; i++)
9820: 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]);*/
9821:
1.302 brouard 9822: for (i=1;i<=imx ; i++) {
9823: /* mu(a)=mu(agecomp)*exp(teta*(age-agegomp))
9824: mu(a)=x[1]*exp(x[2]*(age-agegomp)); x[1] and x[2] are per year.
9825: * L= Product mu(agedeces)exp(-\int_ageexam^agedc mu(u) du ) for a death between agedc (in month)
9826: * and agedc +1 month, cens[i]=0: log(x[1]/YEARM)
9827: * +
9828: * exp(-\int_ageexam^agecens mu(u) du ) when censored, cens[i]=1
9829: */
9830: if (wav[i] > 1 || agedc[i] < AGESUP) {
9831: if (cens[i] == 1){
9832: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
9833: } else if (cens[i] == 0){
1.126 brouard 9834: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
1.302 brouard 9835: +log(x[1]/YEARM) +x[2]*(agedc[i]-agegomp)+log(YEARM);
9836: } else
9837: printf("Gompertz cens[%d] neither 1 nor 0\n",i);
1.126 brouard 9838: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
1.302 brouard 9839: L=L+A*weight[i];
1.126 brouard 9840: /* 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 9841: }
9842: }
1.126 brouard 9843:
1.302 brouard 9844: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
1.126 brouard 9845:
9846: return -2*L*num/sump;
9847: }
9848:
1.136 brouard 9849: #ifdef GSL
9850: /******************* Gompertz_f Likelihood ******************************/
9851: double gompertz_f(const gsl_vector *v, void *params)
9852: {
1.302 brouard 9853: double A=0.,B=0.,LL=0.0,sump=0.,num=0.;
1.136 brouard 9854: double *x= (double *) v->data;
9855: int i,n=0; /* n is the size of the sample */
9856:
9857: for (i=0;i<=imx-1 ; i++) {
9858: sump=sump+weight[i];
9859: /* sump=sump+1;*/
9860: num=num+1;
9861: }
9862:
9863:
9864: /* for (i=0; i<=imx; i++)
9865: 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]);*/
9866: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
9867: for (i=1;i<=imx ; i++)
9868: {
9869: if (cens[i] == 1 && wav[i]>1)
9870: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
9871:
9872: if (cens[i] == 0 && wav[i]>1)
9873: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
9874: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
9875:
9876: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
9877: if (wav[i] > 1 ) { /* ??? */
9878: LL=LL+A*weight[i];
9879: /* 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]);*/
9880: }
9881: }
9882:
9883: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
9884: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
9885:
9886: return -2*LL*num/sump;
9887: }
9888: #endif
9889:
1.126 brouard 9890: /******************* Printing html file ***********/
1.201 brouard 9891: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 9892: int lastpass, int stepm, int weightopt, char model[],\
9893: int imx, double p[],double **matcov,double agemortsup){
9894: int i,k;
9895:
9896: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
9897: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
9898: for (i=1;i<=2;i++)
9899: 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 9900: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 9901: fprintf(fichtm,"</ul>");
9902:
9903: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
9904:
9905: 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>");
9906:
9907: for (k=agegomp;k<(agemortsup-2);k++)
9908: 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]);
9909:
9910:
9911: fflush(fichtm);
9912: }
9913:
9914: /******************* Gnuplot file **************/
1.201 brouard 9915: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 9916:
9917: char dirfileres[132],optfileres[132];
1.164 brouard 9918:
1.126 brouard 9919: int ng;
9920:
9921:
9922: /*#ifdef windows */
9923: fprintf(ficgp,"cd \"%s\" \n",pathc);
9924: /*#endif */
9925:
9926:
9927: strcpy(dirfileres,optionfilefiname);
9928: strcpy(optfileres,"vpl");
1.199 brouard 9929: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 9930: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 9931: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 9932: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 9933: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
9934:
9935: }
9936:
1.136 brouard 9937: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
9938: {
1.126 brouard 9939:
1.136 brouard 9940: /*-------- data file ----------*/
9941: FILE *fic;
9942: char dummy[]=" ";
1.240 brouard 9943: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 9944: int lstra;
1.136 brouard 9945: int linei, month, year,iout;
1.302 brouard 9946: int noffset=0; /* This is the offset if BOM data file */
1.136 brouard 9947: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 9948: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 9949: char *stratrunc;
1.223 brouard 9950:
1.240 brouard 9951: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
9952: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.328 brouard 9953: for(v=1;v<NCOVMAX;v++){
9954: DummyV[v]=0;
9955: FixedV[v]=0;
9956: }
1.126 brouard 9957:
1.240 brouard 9958: for(v=1; v <=ncovcol;v++){
9959: DummyV[v]=0;
9960: FixedV[v]=0;
9961: }
9962: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
9963: DummyV[v]=1;
9964: FixedV[v]=0;
9965: }
9966: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
9967: DummyV[v]=0;
9968: FixedV[v]=1;
9969: }
9970: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
9971: DummyV[v]=1;
9972: FixedV[v]=1;
9973: }
9974: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
9975: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
9976: fprintf(ficlog,"Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
9977: }
1.126 brouard 9978:
1.136 brouard 9979: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 9980: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
9981: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 9982: }
1.126 brouard 9983:
1.302 brouard 9984: /* Is it a BOM UTF-8 Windows file? */
9985: /* First data line */
9986: linei=0;
9987: while(fgets(line, MAXLINE, fic)) {
9988: noffset=0;
9989: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
9990: {
9991: noffset=noffset+3;
9992: printf("# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);fflush(stdout);
9993: fprintf(ficlog,"# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);
9994: fflush(ficlog); return 1;
9995: }
9996: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
9997: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
9998: {
9999: noffset=noffset+2;
1.304 brouard 10000: 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);
10001: 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 10002: fflush(ficlog); return 1;
10003: }
10004: else if( line[0] == 0 && line[1] == 0)
10005: {
10006: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
10007: noffset=noffset+4;
1.304 brouard 10008: 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);
10009: 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 10010: fflush(ficlog); return 1;
10011: }
10012: } else{
10013: ;/*printf(" Not a BOM file\n");*/
10014: }
10015: /* If line starts with a # it is a comment */
10016: if (line[noffset] == '#') {
10017: linei=linei+1;
10018: break;
10019: }else{
10020: break;
10021: }
10022: }
10023: fclose(fic);
10024: if((fic=fopen(datafile,"r"))==NULL) {
10025: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
10026: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
10027: }
10028: /* Not a Bom file */
10029:
1.136 brouard 10030: i=1;
10031: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
10032: linei=linei+1;
10033: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
10034: if(line[j] == '\t')
10035: line[j] = ' ';
10036: }
10037: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
10038: ;
10039: };
10040: line[j+1]=0; /* Trims blanks at end of line */
10041: if(line[0]=='#'){
10042: fprintf(ficlog,"Comment line\n%s\n",line);
10043: printf("Comment line\n%s\n",line);
10044: continue;
10045: }
10046: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 10047: strcpy(line, linetmp);
1.223 brouard 10048:
10049: /* Loops on waves */
10050: for (j=maxwav;j>=1;j--){
10051: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 10052: cutv(stra, strb, line, ' ');
10053: if(strb[0]=='.') { /* Missing value */
10054: lval=-1;
10055: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
10056: cotvar[j][ntv+iv][i]=-1; /* For performance reasons */
10057: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
10058: 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);
10059: 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);
10060: return 1;
10061: }
10062: }else{
10063: errno=0;
10064: /* what_kind_of_number(strb); */
10065: dval=strtod(strb,&endptr);
10066: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
10067: /* if(strb != endptr && *endptr == '\0') */
10068: /* dval=dlval; */
10069: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
10070: if( strb[0]=='\0' || (*endptr != '\0')){
10071: 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);
10072: 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);
10073: return 1;
10074: }
10075: cotqvar[j][iv][i]=dval;
10076: cotvar[j][ntv+iv][i]=dval;
10077: }
10078: strcpy(line,stra);
1.223 brouard 10079: }/* end loop ntqv */
1.225 brouard 10080:
1.223 brouard 10081: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 10082: cutv(stra, strb, line, ' ');
10083: if(strb[0]=='.') { /* Missing value */
10084: lval=-1;
10085: }else{
10086: errno=0;
10087: lval=strtol(strb,&endptr,10);
10088: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
10089: if( strb[0]=='\0' || (*endptr != '\0')){
10090: 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);
10091: 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);
10092: return 1;
10093: }
10094: }
10095: if(lval <-1 || lval >1){
10096: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10097: 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 10098: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10099: For example, for multinomial values like 1, 2 and 3,\n \
10100: build V1=0 V2=0 for the reference value (1),\n \
10101: V1=1 V2=0 for (2) \n \
1.223 brouard 10102: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10103: output of IMaCh is often meaningless.\n \
1.319 brouard 10104: Exiting.\n",lval,linei, i,line,iv,j);
1.238 brouard 10105: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10106: 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 10107: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10108: For example, for multinomial values like 1, 2 and 3,\n \
10109: build V1=0 V2=0 for the reference value (1),\n \
10110: V1=1 V2=0 for (2) \n \
1.223 brouard 10111: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10112: output of IMaCh is often meaningless.\n \
1.319 brouard 10113: Exiting.\n",lval,linei, i,line,iv,j);fflush(ficlog);
1.238 brouard 10114: return 1;
10115: }
10116: cotvar[j][iv][i]=(double)(lval);
10117: strcpy(line,stra);
1.223 brouard 10118: }/* end loop ntv */
1.225 brouard 10119:
1.223 brouard 10120: /* Statuses at wave */
1.137 brouard 10121: cutv(stra, strb, line, ' ');
1.223 brouard 10122: if(strb[0]=='.') { /* Missing value */
1.238 brouard 10123: lval=-1;
1.136 brouard 10124: }else{
1.238 brouard 10125: errno=0;
10126: lval=strtol(strb,&endptr,10);
10127: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
10128: if( strb[0]=='\0' || (*endptr != '\0')){
10129: 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);
10130: 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);
10131: return 1;
10132: }
1.136 brouard 10133: }
1.225 brouard 10134:
1.136 brouard 10135: s[j][i]=lval;
1.225 brouard 10136:
1.223 brouard 10137: /* Date of Interview */
1.136 brouard 10138: strcpy(line,stra);
10139: cutv(stra, strb,line,' ');
1.169 brouard 10140: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10141: }
1.169 brouard 10142: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 10143: month=99;
10144: year=9999;
1.136 brouard 10145: }else{
1.225 brouard 10146: 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);
10147: 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);
10148: return 1;
1.136 brouard 10149: }
10150: anint[j][i]= (double) year;
1.302 brouard 10151: mint[j][i]= (double)month;
10152: /* if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){ */
10153: /* 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]); */
10154: /* 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]); */
10155: /* } */
1.136 brouard 10156: strcpy(line,stra);
1.223 brouard 10157: } /* End loop on waves */
1.225 brouard 10158:
1.223 brouard 10159: /* Date of death */
1.136 brouard 10160: cutv(stra, strb,line,' ');
1.169 brouard 10161: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10162: }
1.169 brouard 10163: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 10164: month=99;
10165: year=9999;
10166: }else{
1.141 brouard 10167: 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 10168: 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);
10169: return 1;
1.136 brouard 10170: }
10171: andc[i]=(double) year;
10172: moisdc[i]=(double) month;
10173: strcpy(line,stra);
10174:
1.223 brouard 10175: /* Date of birth */
1.136 brouard 10176: cutv(stra, strb,line,' ');
1.169 brouard 10177: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10178: }
1.169 brouard 10179: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 10180: month=99;
10181: year=9999;
10182: }else{
1.141 brouard 10183: 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);
10184: 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 10185: return 1;
1.136 brouard 10186: }
10187: if (year==9999) {
1.141 brouard 10188: 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);
10189: 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 10190: return 1;
10191:
1.136 brouard 10192: }
10193: annais[i]=(double)(year);
1.302 brouard 10194: moisnais[i]=(double)(month);
10195: for (j=1;j<=maxwav;j++){
10196: if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){
10197: 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]);
10198: 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]);
10199: }
10200: }
10201:
1.136 brouard 10202: strcpy(line,stra);
1.225 brouard 10203:
1.223 brouard 10204: /* Sample weight */
1.136 brouard 10205: cutv(stra, strb,line,' ');
10206: errno=0;
10207: dval=strtod(strb,&endptr);
10208: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 10209: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
10210: 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 10211: fflush(ficlog);
10212: return 1;
10213: }
10214: weight[i]=dval;
10215: strcpy(line,stra);
1.225 brouard 10216:
1.223 brouard 10217: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
10218: cutv(stra, strb, line, ' ');
10219: if(strb[0]=='.') { /* Missing value */
1.225 brouard 10220: lval=-1;
1.311 brouard 10221: coqvar[iv][i]=NAN;
10222: covar[ncovcol+iv][i]=NAN; /* including qvar in standard covar for performance reasons */
1.223 brouard 10223: }else{
1.225 brouard 10224: errno=0;
10225: /* what_kind_of_number(strb); */
10226: dval=strtod(strb,&endptr);
10227: /* if(strb != endptr && *endptr == '\0') */
10228: /* dval=dlval; */
10229: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
10230: if( strb[0]=='\0' || (*endptr != '\0')){
10231: 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);
10232: 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);
10233: return 1;
10234: }
10235: coqvar[iv][i]=dval;
1.226 brouard 10236: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 10237: }
10238: strcpy(line,stra);
10239: }/* end loop nqv */
1.136 brouard 10240:
1.223 brouard 10241: /* Covariate values */
1.136 brouard 10242: for (j=ncovcol;j>=1;j--){
10243: cutv(stra, strb,line,' ');
1.223 brouard 10244: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 10245: lval=-1;
1.136 brouard 10246: }else{
1.225 brouard 10247: errno=0;
10248: lval=strtol(strb,&endptr,10);
10249: if( strb[0]=='\0' || (*endptr != '\0')){
10250: 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);
10251: 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);
10252: return 1;
10253: }
1.136 brouard 10254: }
10255: if(lval <-1 || lval >1){
1.225 brouard 10256: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 10257: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
10258: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 10259: For example, for multinomial values like 1, 2 and 3,\n \
10260: build V1=0 V2=0 for the reference value (1),\n \
10261: V1=1 V2=0 for (2) \n \
1.136 brouard 10262: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 10263: output of IMaCh is often meaningless.\n \
1.136 brouard 10264: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 10265: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 10266: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
10267: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 10268: For example, for multinomial values like 1, 2 and 3,\n \
10269: build V1=0 V2=0 for the reference value (1),\n \
10270: V1=1 V2=0 for (2) \n \
1.136 brouard 10271: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 10272: output of IMaCh is often meaningless.\n \
1.136 brouard 10273: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 10274: return 1;
1.136 brouard 10275: }
10276: covar[j][i]=(double)(lval);
10277: strcpy(line,stra);
10278: }
10279: lstra=strlen(stra);
1.225 brouard 10280:
1.136 brouard 10281: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
10282: stratrunc = &(stra[lstra-9]);
10283: num[i]=atol(stratrunc);
10284: }
10285: else
10286: num[i]=atol(stra);
10287: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
10288: 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;}*/
10289:
10290: i=i+1;
10291: } /* End loop reading data */
1.225 brouard 10292:
1.136 brouard 10293: *imax=i-1; /* Number of individuals */
10294: fclose(fic);
1.225 brouard 10295:
1.136 brouard 10296: return (0);
1.164 brouard 10297: /* endread: */
1.225 brouard 10298: printf("Exiting readdata: ");
10299: fclose(fic);
10300: return (1);
1.223 brouard 10301: }
1.126 brouard 10302:
1.234 brouard 10303: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 10304: char *p1 = *stri, *p2 = *stri;
1.235 brouard 10305: while (*p2 == ' ')
1.234 brouard 10306: p2++;
10307: /* while ((*p1++ = *p2++) !=0) */
10308: /* ; */
10309: /* do */
10310: /* while (*p2 == ' ') */
10311: /* p2++; */
10312: /* while (*p1++ == *p2++); */
10313: *stri=p2;
1.145 brouard 10314: }
10315:
1.330 brouard 10316: int decoderesult( char resultline[], int nres)
1.230 brouard 10317: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
10318: {
1.235 brouard 10319: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 10320: char resultsav[MAXLINE];
1.330 brouard 10321: /* int resultmodel[MAXLINE]; */
1.334 ! brouard 10322: /* int modelresult[MAXLINE]; */
1.230 brouard 10323: char stra[80], strb[80], strc[80], strd[80],stre[80];
10324:
1.234 brouard 10325: removefirstspace(&resultline);
1.332 brouard 10326: printf("decoderesult:%s\n",resultline);
1.230 brouard 10327:
1.332 brouard 10328: strcpy(resultsav,resultline);
10329: printf("Decoderesult resultsav=\"%s\" resultline=\"%s\"\n", resultsav, resultline);
1.230 brouard 10330: if (strlen(resultsav) >1){
1.334 ! brouard 10331: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' in this resultline */
1.230 brouard 10332: }
1.253 brouard 10333: if(j == 0){ /* Resultline but no = */
10334: TKresult[nres]=0; /* Combination for the nresult and the model */
10335: return (0);
10336: }
1.234 brouard 10337: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
1.334 ! brouard 10338: 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, %s.\n",j, cptcovs, model);
! 10339: 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, %s.\n",j, cptcovs, model);
1.332 brouard 10340: /* return 1;*/
1.234 brouard 10341: }
1.334 ! brouard 10342: for(k=1; k<=j;k++){ /* Loop on any covariate of the RESULT LINE */
1.234 brouard 10343: if(nbocc(resultsav,'=') >1){
1.318 brouard 10344: 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 10345: /* 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 10346: cutl(strc,strd,strb,'='); /* strb:"V4=1" strc="1" strd="V4" */
1.332 brouard 10347: /* If a blank, then strc="V4=" and strd='\0' */
10348: if(strc[0]=='\0'){
10349: printf("Error in resultline, probably a blank after the \"%s\", \"result:%s\", stra=\"%s\" resultsav=\"%s\"\n",strb,resultline, stra, resultsav);
10350: fprintf(ficlog,"Error in resultline, probably a blank after the \"V%s=\", resultline=%s\n",strb,resultline);
10351: return 1;
10352: }
1.234 brouard 10353: }else
10354: cutl(strc,strd,resultsav,'=');
1.318 brouard 10355: Tvalsel[k]=atof(strc); /* 1 */ /* Tvalsel of k is the float value of the kth covariate appearing in this result line */
1.234 brouard 10356:
1.230 brouard 10357: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
1.318 brouard 10358: 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 10359: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
10360: /* cptcovsel++; */
10361: if (nbocc(stra,'=') >0)
10362: strcpy(resultsav,stra); /* and analyzes it */
10363: }
1.235 brouard 10364: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 10365: /* 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 10366: 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 10367: if(Typevar[k1]==0){ /* Single covariate in model */
10368: /* 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.234 brouard 10369: match=0;
1.318 brouard 10370: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
10371: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 ! brouard 10372: modelresult[nres][k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.318 brouard 10373: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
1.234 brouard 10374: break;
10375: }
10376: }
10377: if(match == 0){
1.332 brouard 10378: printf("Error in result line (Dummy single): V%d is missing in result: %s according to model=%s. Tvar[k1=%d]=%d is different from Tvarsel[k2=%d]=%d.\n",Tvar[k1], resultline, model,k1, Tvar[k1], k2, Tvarsel[k2]);
10379: fprintf(ficlog,"Error in result line (Dummy single): V%d is missing in result: %s according to model=%s\n",Tvar[k1], resultline, model);
1.310 brouard 10380: return 1;
1.234 brouard 10381: }
1.332 brouard 10382: }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*/
10383: /* We feed resultmodel[k1]=k2; */
10384: match=0;
10385: 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 */
10386: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 ! brouard 10387: 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 10388: resultmodel[nres][k1]=k2; /* Added here */
10389: printf("Decoderesult first modelresult[k2=%d]=%d (k1) V%d*AGE\n",k2,k1,Tvar[k1]);
10390: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
10391: break;
10392: }
10393: }
10394: if(match == 0){
10395: printf("Error in result line (Product with age): V%d is missing in result: %s according to model=%s (Tvarsel[k2=%d]=%d)\n",Tvar[k1], resultline, model, k2, Tvarsel[k2]);
1.333 brouard 10396: fprintf(ficlog,"Error in result line (Product with age): V%d is missing in result: %s according to model=%s (Tvarsel[k2=%d]=%d)\n",Tvar[k1], resultline, model, k2, Tvarsel[k2]);
1.332 brouard 10397: return 1;
10398: }
10399: }else if(Typevar[k1]==2){ /* Product No age We want to get the position in the resultline of the product in the model line*/
10400: /* resultmodel[nres][of such a Vn * Vm product k1] is not unique, so can't exist, we feed Tvard[k1][1] and [2] */
10401: match=0;
10402: 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]);
10403: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
10404: if(Tvardk[k1][1]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
10405: /* modelresult[k2]=k1; */
10406: printf("Decoderesult first Product modelresult[k2=%d]=%d (k1) V%d * \n",k2,k1,Tvarsel[k2]);
10407: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
10408: }
10409: }
10410: if(match == 0){
10411: printf("Error in result line (Product without age first variable): V%d is missing in result: %s according to model=%s\n",Tvardk[k1][1], resultline, model);
1.333 brouard 10412: fprintf(ficlog,"Error in result line (Product without age first variable): V%d is missing in result: %s according to model=%s\n",Tvardk[k1][1], resultline, model);
1.332 brouard 10413: return 1;
10414: }
10415: match=0;
10416: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
10417: if(Tvardk[k1][2]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
10418: /* modelresult[k2]=k1;*/
10419: printf("Decoderesult second Product modelresult[k2=%d]=%d (k1) * V%d \n ",k2,k1,Tvarsel[k2]);
10420: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
10421: break;
10422: }
10423: }
10424: if(match == 0){
10425: printf("Error in result line (Product without age second variable): V%d is missing in result: %s according to model=%s\n",Tvardk[k1][2], resultline, model);
1.333 brouard 10426: fprintf(ficlog,"Error in result line (Product without age second variable): V%d is missing in result : %s according to model=%s\n",Tvardk[k1][2], resultline, model);
1.332 brouard 10427: return 1;
10428: }
10429: }/* End of testing */
1.333 brouard 10430: }/* End loop cptcovt */
1.235 brouard 10431: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 10432: /* Feeds resultmodel[nres][k1]=k2 for single covariate (k1) in the model equation */
1.334 ! brouard 10433: 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)
! 10434: * Loop on resultline variables: result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 10435: match=0;
1.318 brouard 10436: 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 10437: if(Typevar[k1]==0){ /* Single only */
1.237 brouard 10438: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.330 brouard 10439: 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 10440: 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 10441: ++match;
10442: }
10443: }
10444: }
10445: if(match == 0){
1.332 brouard 10446: printf("Error in result line: variable V%d is missing in model; result: %s, model=%s\n",Tvarsel[k2], resultline, model);
10447: fprintf(ficlog,"Error in result line: variable V%d is missing in model; result: %s, model=%s\n",Tvarsel[k2], resultline, model);
1.310 brouard 10448: return 1;
1.234 brouard 10449: }else if(match > 1){
10450: printf("Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
1.310 brouard 10451: fprintf(ficlog,"Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
10452: return 1;
1.234 brouard 10453: }
10454: }
1.334 ! brouard 10455: /* cptcovres=j /\* Number of variables in the resultline is equal to cptcovs and thus useless *\/ */
1.234 brouard 10456: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 10457: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.330 brouard 10458: /* nres=1st result line: V4=1 V5=25.1 V3=0 V2=8 V1=1 */
10459: /* 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*/
10460: /* nres=2nd result line: V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.235 brouard 10461: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
10462: /* 1 0 0 0 */
10463: /* 2 1 0 0 */
10464: /* 3 0 1 0 */
1.330 brouard 10465: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 (nres=2)*/
1.235 brouard 10466: /* 5 0 0 1 */
1.330 brouard 10467: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 (nres=1)*/
1.235 brouard 10468: /* 7 0 1 1 */
10469: /* 8 1 1 1 */
1.237 brouard 10470: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
10471: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
10472: /* V5*age V5 known which value for nres? */
10473: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.334 ! brouard 10474: 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.
! 10475: * loop on position k1 in the MODEL LINE */
1.331 brouard 10476: /* k counting number of combination of single dummies in the equation model */
10477: /* k4 counting single dummies in the equation model */
10478: /* k4q counting single quantitatives in the equation model */
1.334 ! brouard 10479: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Dummy and Single, k1 is sorting according to MODEL, but k3 to resultline */
! 10480: /* 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 10481: /* 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 10482: /* Value in the (current nres) resultline of the variable at the k1th position in the model equation resultmodel[nres][k1]= k3 */
1.332 brouard 10483: /* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline */
10484: /* k3 is the position in the nres result line of the k1th variable of the model equation */
10485: /* Tvarsel[k3]: Name of the variable at the k3th position in the result line. */
10486: /* Tvalsel[k3]: Value of the variable at the k3th position in the result line. */
10487: /* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.334 ! brouard 10488: /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 10489: /* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1.330 brouard 10490: /* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.332 brouard 10491: k3= resultmodel[nres][k1]; /* From position k1 in model get position k3 in result line */
10492: /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
10493: 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 10494: 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 10495: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][Name]=Value; stores the value into the name of the variable. */
1.332 brouard 10496: /* Tinvresult[nres][4]=1 */
1.334 ! brouard 10497: /* Tresult[nres][k4+1]=Tvalsel[k3];/\* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) *\/ */
! 10498: Tresult[nres][k3]=Tvalsel[k3];/* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) */
! 10499: /* Tvresult[nres][k4+1]=(int)Tvarsel[k3];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
! 10500: Tvresult[nres][k3]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
1.237 brouard 10501: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.334 ! brouard 10502: precov[nres][k1]=Tvalsel[k3]; /* Value from resultline of the variable at the k1 position in the model */
1.332 brouard 10503: 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 10504: k4++;;
1.331 brouard 10505: }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Quantitative and single */
1.330 brouard 10506: /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.332 brouard 10507: /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.330 brouard 10508: /* Tqinvresult[nres][Name of a quantitative variable]= value of the variable in the result line */
1.332 brouard 10509: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 5 =k3q */
10510: k2q=(int)Tvarsel[k3q]; /* Name of variable at k3q th position in the resultline */
10511: /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.334 ! brouard 10512: /* Tqresult[nres][k4q+1]=Tvalsel[k3q]; /\* Tqresult[nres][1]=25.1 *\/ */
! 10513: /* Tvresult[nres][k4q+1]=(int)Tvarsel[k3q];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
! 10514: /* Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /\* Tvqresult[nres][1]=5 *\/ */
! 10515: Tqresult[nres][k3q]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
! 10516: Tvresult[nres][k3q]=(int)Tvarsel[k3q];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
! 10517: Tvqresult[nres][k3q]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
1.237 brouard 10518: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.330 brouard 10519: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.332 brouard 10520: precov[nres][k1]=Tvalsel[k3q];
10521: 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 10522: k4q++;;
1.331 brouard 10523: }else if( Dummy[k1]==2 ){ /* For dummy with age product */
10524: /* Tvar[k1]; */ /* Age variable */
1.332 brouard 10525: /* Wrong we want the value of variable name Tvar[k1] */
10526:
10527: k3= resultmodel[nres][k1]; /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
1.331 brouard 10528: 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)*/
1.334 ! brouard 10529: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][4]=1 */
1.332 brouard 10530: precov[nres][k1]=Tvalsel[k3];
10531: 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 10532: }else if( Dummy[k1]==3 ){ /* For quant with age product */
1.332 brouard 10533: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 25.1=k3q */
1.331 brouard 10534: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.334 ! brouard 10535: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* TinvDoQresult[nres][5]=25.1 */
1.332 brouard 10536: precov[nres][k1]=Tvalsel[k3q];
1.334 ! brouard 10537: 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]);
1.331 brouard 10538: }else if(Typevar[k1]==2 ){ /* For product quant or dummy (not with age) */
1.332 brouard 10539: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
10540: 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 10541: }else{
1.332 brouard 10542: printf("Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
10543: fprintf(ficlog,"Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
1.235 brouard 10544: }
10545: }
1.234 brouard 10546:
1.334 ! brouard 10547: TKresult[nres]=++k; /* Number of combinations of dummies for the nresult and the model =Tvalsel[k3]*pow(2,k4) + 1*/
1.230 brouard 10548: return (0);
10549: }
1.235 brouard 10550:
1.230 brouard 10551: int decodemodel( char model[], int lastobs)
10552: /**< This routine decodes the model and returns:
1.224 brouard 10553: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
10554: * - nagesqr = 1 if age*age in the model, otherwise 0.
10555: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
10556: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
10557: * - cptcovage number of covariates with age*products =2
10558: * - cptcovs number of simple covariates
10559: * - 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
10560: * which is a new column after the 9 (ncovcol) variables.
1.319 brouard 10561: * - if k is a product Vn*Vm, covar[k][i] is filled with correct values for each individual
1.224 brouard 10562: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
10563: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
10564: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
10565: */
1.319 brouard 10566: /* 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 10567: {
1.238 brouard 10568: int i, j, k, ks, v;
1.227 brouard 10569: int j1, k1, k2, k3, k4;
1.136 brouard 10570: char modelsav[80];
1.145 brouard 10571: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 10572: char *strpt;
1.136 brouard 10573:
1.145 brouard 10574: /*removespace(model);*/
1.136 brouard 10575: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 10576: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 10577: if (strstr(model,"AGE") !=0){
1.192 brouard 10578: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
10579: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 10580: return 1;
10581: }
1.141 brouard 10582: if (strstr(model,"v") !=0){
10583: printf("Error. 'v' must be in upper case 'V' model=%s ",model);
10584: fprintf(ficlog,"Error. 'v' must be in upper case model=%s ",model);fflush(ficlog);
10585: return 1;
10586: }
1.187 brouard 10587: strcpy(modelsav,model);
10588: if ((strpt=strstr(model,"age*age")) !=0){
10589: printf(" strpt=%s, model=%s\n",strpt, model);
10590: if(strpt != model){
1.234 brouard 10591: printf("Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 10592: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 10593: corresponding column of parameters.\n",model);
1.234 brouard 10594: fprintf(ficlog,"Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 10595: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 10596: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 10597: return 1;
1.225 brouard 10598: }
1.187 brouard 10599: nagesqr=1;
10600: if (strstr(model,"+age*age") !=0)
1.234 brouard 10601: substrchaine(modelsav, model, "+age*age");
1.187 brouard 10602: else if (strstr(model,"age*age+") !=0)
1.234 brouard 10603: substrchaine(modelsav, model, "age*age+");
1.187 brouard 10604: else
1.234 brouard 10605: substrchaine(modelsav, model, "age*age");
1.187 brouard 10606: }else
10607: nagesqr=0;
10608: if (strlen(modelsav) >1){
10609: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
10610: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 10611: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 10612: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 10613: * cst, age and age*age
10614: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
10615: /* including age products which are counted in cptcovage.
10616: * but the covariates which are products must be treated
10617: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 10618: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
10619: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 10620:
10621:
1.187 brouard 10622: /* Design
10623: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
10624: * < ncovcol=8 >
10625: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
10626: * k= 1 2 3 4 5 6 7 8
10627: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
10628: * covar[k,i], value of kth covariate if not including age for individual i:
1.224 brouard 10629: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
10630: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 10631: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
10632: * Tage[++cptcovage]=k
10633: * if products, new covar are created after ncovcol with k1
10634: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
10635: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
10636: * 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
10637: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
10638: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
10639: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
10640: * < ncovcol=8 >
10641: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
10642: * k= 1 2 3 4 5 6 7 8 9 10 11 12
10643: * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8
1.319 brouard 10644: * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
1.187 brouard 10645: * p Tprod[1]@2={ 6, 5}
10646: *p Tvard[1][1]@4= {7, 8, 5, 6}
10647: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
10648: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
1.319 brouard 10649: *How to reorganize? Tvars(orted)
1.187 brouard 10650: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
10651: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
10652: * {2, 1, 4, 8, 5, 6, 3, 7}
10653: * Struct []
10654: */
1.225 brouard 10655:
1.187 brouard 10656: /* This loop fills the array Tvar from the string 'model'.*/
10657: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
10658: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
10659: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
10660: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
10661: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
10662: /* k=1 Tvar[1]=2 (from V2) */
10663: /* k=5 Tvar[5] */
10664: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 10665: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 10666: /* } */
1.198 brouard 10667: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 10668: /*
10669: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 10670: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
10671: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
10672: }
1.187 brouard 10673: cptcovage=0;
1.319 brouard 10674: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model line */
10675: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+' cutl from left to right
10676: 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" */
10677: if (nbocc(modelsav,'+')==0)
10678: strcpy(strb,modelsav); /* and analyzes it */
1.234 brouard 10679: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
10680: /*scanf("%d",i);*/
1.319 brouard 10681: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V5*age+ V4+V3*age strb=V3*age */
10682: cutl(strc,strd,strb,'*'); /**< k=1 strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 */
1.234 brouard 10683: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
10684: /* covar is not filled and then is empty */
10685: cptcovprod--;
10686: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
1.319 brouard 10687: 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 */
1.234 brouard 10688: Typevar[k]=1; /* 1 for age product */
1.319 brouard 10689: cptcovage++; /* Counts the number of covariates which include age as a product */
10690: Tage[cptcovage]=k; /* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
1.234 brouard 10691: /*printf("stre=%s ", stre);*/
10692: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
10693: cptcovprod--;
10694: cutl(stre,strb,strc,'V');
10695: Tvar[k]=atoi(stre);
10696: Typevar[k]=1; /* 1 for age product */
10697: cptcovage++;
10698: Tage[cptcovage]=k;
10699: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
10700: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
10701: cptcovn++;
10702: cptcovprodnoage++;k1++;
10703: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
10704: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* For model-covariate k tells which data-covariate to use but
10705: because this model-covariate is a construction we invent a new column
10706: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
1.319 brouard 10707: If already ncovcol=4 and model=V2 + V1 +V1*V4 +age*V3 +V3*V2
10708: thus after V4 we invent V5 and V6 because age*V3 will be computed in 4
10709: Tvar[3=V1*V4]=4+1=5 Tvar[5=V3*V2]=4 + 2= 6, Tvar[4=age*V3]=4 etc */
1.234 brouard 10710: Typevar[k]=2; /* 2 for double fixed dummy covariates */
10711: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
10712: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
1.319 brouard 10713: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 */
1.234 brouard 10714: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
1.330 brouard 10715: Tvardk[k][1] =atoi(strc); /* m 1 for V1*/
1.234 brouard 10716: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
1.330 brouard 10717: Tvardk[k][2] =atoi(stre); /* n 4 for V4*/
1.234 brouard 10718: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
10719: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
10720: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 10721: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 10722: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
10723: for (i=1; i<=lastobs;i++){
10724: /* Computes the new covariate which is a product of
10725: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
10726: covar[ncovcol+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
10727: }
10728: } /* End age is not in the model */
10729: } /* End if model includes a product */
1.319 brouard 10730: else { /* not a product */
1.234 brouard 10731: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
10732: /* scanf("%d",i);*/
10733: cutl(strd,strc,strb,'V');
10734: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
10735: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
10736: Tvar[k]=atoi(strd);
10737: Typevar[k]=0; /* 0 for simple covariates */
10738: }
10739: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 10740: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 10741: scanf("%d",i);*/
1.187 brouard 10742: } /* end of loop + on total covariates */
10743: } /* end if strlen(modelsave == 0) age*age might exist */
10744: } /* end if strlen(model == 0) */
1.136 brouard 10745:
10746: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
10747: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 10748:
1.136 brouard 10749: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 10750: printf("cptcovprod=%d ", cptcovprod);
10751: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
10752: scanf("%d ",i);*/
10753:
10754:
1.230 brouard 10755: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
10756: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 10757: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
10758: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
10759: k = 1 2 3 4 5 6 7 8 9
10760: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
1.319 brouard 10761: Typevar[k]= 0 0 0 2 1 0 2 1 0
1.227 brouard 10762: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
10763: Dummy[k] 1 0 0 0 3 1 1 2 3
10764: Tmodelind[combination of covar]=k;
1.225 brouard 10765: */
10766: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 10767: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 10768: /* 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 10769: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.318 brouard 10770: printf("Model=1+age+%s\n\
1.227 brouard 10771: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
10772: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
10773: 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 10774: fprintf(ficlog,"Model=1+age+%s\n\
1.227 brouard 10775: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
10776: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
10777: 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);
1.285 brouard 10778: for(k=-1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;}
1.234 brouard 10779: for(k=1, ncovf=0, nsd=0, nsq=0, ncovv=0, ncova=0, ncoveff=0, nqfveff=0, ntveff=0, nqtveff=0;k<=cptcovt; k++){ /* or cptocvt */
10780: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 10781: Fixed[k]= 0;
10782: Dummy[k]= 0;
1.225 brouard 10783: ncoveff++;
1.232 brouard 10784: ncovf++;
1.234 brouard 10785: nsd++;
10786: modell[k].maintype= FTYPE;
10787: TvarsD[nsd]=Tvar[k];
10788: TvarsDind[nsd]=k;
1.330 brouard 10789: TnsdVar[Tvar[k]]=nsd;
1.234 brouard 10790: TvarF[ncovf]=Tvar[k];
10791: TvarFind[ncovf]=k;
10792: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
10793: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
10794: }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /* Product of fixed dummy (<=ncovcol) covariates */
10795: Fixed[k]= 0;
10796: Dummy[k]= 0;
10797: ncoveff++;
10798: ncovf++;
10799: modell[k].maintype= FTYPE;
10800: TvarF[ncovf]=Tvar[k];
1.330 brouard 10801: /* TnsdVar[Tvar[k]]=nsd; */ /* To be done */
1.234 brouard 10802: TvarFind[ncovf]=k;
1.230 brouard 10803: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 10804: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.240 brouard 10805: }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 10806: Fixed[k]= 0;
10807: Dummy[k]= 1;
1.230 brouard 10808: nqfveff++;
1.234 brouard 10809: modell[k].maintype= FTYPE;
10810: modell[k].subtype= FQ;
10811: nsq++;
1.334 ! brouard 10812: TvarsQ[nsq]=Tvar[k]; /* Gives the variable name (extended to products) of first nsq simple quantitative covariates (fixed or time vary see below */
! 10813: TvarsQind[nsq]=k; /* Gives the position in the model equation of the first nsq simple quantitative covariates (fixed or time vary) */
1.232 brouard 10814: ncovf++;
1.234 brouard 10815: TvarF[ncovf]=Tvar[k];
10816: TvarFind[ncovf]=k;
1.231 brouard 10817: 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 10818: 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 10819: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.227 brouard 10820: Fixed[k]= 1;
10821: Dummy[k]= 0;
1.225 brouard 10822: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 10823: modell[k].maintype= VTYPE;
10824: modell[k].subtype= VD;
10825: nsd++;
10826: TvarsD[nsd]=Tvar[k];
10827: TvarsDind[nsd]=k;
1.330 brouard 10828: TnsdVar[Tvar[k]]=nsd; /* To be verified */
1.234 brouard 10829: ncovv++; /* Only simple time varying variables */
10830: TvarV[ncovv]=Tvar[k];
1.242 brouard 10831: 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 10832: 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 */
10833: 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 10834: 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);
10835: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 10836: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.234 brouard 10837: Fixed[k]= 1;
10838: Dummy[k]= 1;
10839: nqtveff++;
10840: modell[k].maintype= VTYPE;
10841: modell[k].subtype= VQ;
10842: ncovv++; /* Only simple time varying variables */
10843: nsq++;
1.334 ! brouard 10844: 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) */
! 10845: 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 10846: TvarV[ncovv]=Tvar[k];
1.242 brouard 10847: 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 10848: 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 */
10849: 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 10850: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
10851: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
10852: printf("Quasi TmodelQind[%d]=%d,Tvar[TmodelQind[%d]]=V%d, ncovcol=%d, nqv=%d, ntv=%d,Tvar[k]- ncovcol-nqv-ntv=%d\n",nqtveff,k,nqtveff,Tvar[k], ncovcol, nqv, ntv, Tvar[k]- ncovcol-nqv-ntv);
1.228 brouard 10853: printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv);
1.227 brouard 10854: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 10855: ncova++;
10856: TvarA[ncova]=Tvar[k];
10857: TvarAind[ncova]=k;
1.231 brouard 10858: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 10859: Fixed[k]= 2;
10860: Dummy[k]= 2;
10861: modell[k].maintype= ATYPE;
10862: modell[k].subtype= APFD;
10863: /* ncoveff++; */
1.227 brouard 10864: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 10865: Fixed[k]= 2;
10866: Dummy[k]= 3;
10867: modell[k].maintype= ATYPE;
10868: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
10869: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 10870: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 10871: Fixed[k]= 3;
10872: Dummy[k]= 2;
10873: modell[k].maintype= ATYPE;
10874: modell[k].subtype= APVD; /* Product age * varying dummy */
10875: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 10876: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 10877: Fixed[k]= 3;
10878: Dummy[k]= 3;
10879: modell[k].maintype= ATYPE;
10880: modell[k].subtype= APVQ; /* Product age * varying quantitative */
10881: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 10882: }
10883: }else if (Typevar[k] == 2) { /* product without age */
10884: k1=Tposprod[k];
10885: if(Tvard[k1][1] <=ncovcol){
1.240 brouard 10886: if(Tvard[k1][2] <=ncovcol){
10887: Fixed[k]= 1;
10888: Dummy[k]= 0;
10889: modell[k].maintype= FTYPE;
10890: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
10891: ncovf++; /* Fixed variables without age */
10892: TvarF[ncovf]=Tvar[k];
10893: TvarFind[ncovf]=k;
10894: }else if(Tvard[k1][2] <=ncovcol+nqv){
10895: Fixed[k]= 0; /* or 2 ?*/
10896: Dummy[k]= 1;
10897: modell[k].maintype= FTYPE;
10898: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
10899: ncovf++; /* Varying variables without age */
10900: TvarF[ncovf]=Tvar[k];
10901: TvarFind[ncovf]=k;
10902: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10903: Fixed[k]= 1;
10904: Dummy[k]= 0;
10905: modell[k].maintype= VTYPE;
10906: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
10907: ncovv++; /* Varying variables without age */
10908: TvarV[ncovv]=Tvar[k];
10909: TvarVind[ncovv]=k;
10910: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10911: Fixed[k]= 1;
10912: Dummy[k]= 1;
10913: modell[k].maintype= VTYPE;
10914: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
10915: ncovv++; /* Varying variables without age */
10916: TvarV[ncovv]=Tvar[k];
10917: TvarVind[ncovv]=k;
10918: }
1.227 brouard 10919: }else if(Tvard[k1][1] <=ncovcol+nqv){
1.240 brouard 10920: if(Tvard[k1][2] <=ncovcol){
10921: Fixed[k]= 0; /* or 2 ?*/
10922: Dummy[k]= 1;
10923: modell[k].maintype= FTYPE;
10924: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
10925: ncovf++; /* Fixed variables without age */
10926: TvarF[ncovf]=Tvar[k];
10927: TvarFind[ncovf]=k;
10928: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10929: Fixed[k]= 1;
10930: Dummy[k]= 1;
10931: modell[k].maintype= VTYPE;
10932: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
10933: ncovv++; /* Varying variables without age */
10934: TvarV[ncovv]=Tvar[k];
10935: TvarVind[ncovv]=k;
10936: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10937: Fixed[k]= 1;
10938: Dummy[k]= 1;
10939: modell[k].maintype= VTYPE;
10940: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
10941: ncovv++; /* Varying variables without age */
10942: TvarV[ncovv]=Tvar[k];
10943: TvarVind[ncovv]=k;
10944: ncovv++; /* Varying variables without age */
10945: TvarV[ncovv]=Tvar[k];
10946: TvarVind[ncovv]=k;
10947: }
1.227 brouard 10948: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){
1.240 brouard 10949: if(Tvard[k1][2] <=ncovcol){
10950: Fixed[k]= 1;
10951: Dummy[k]= 1;
10952: modell[k].maintype= VTYPE;
10953: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
10954: ncovv++; /* Varying variables without age */
10955: TvarV[ncovv]=Tvar[k];
10956: TvarVind[ncovv]=k;
10957: }else if(Tvard[k1][2] <=ncovcol+nqv){
10958: Fixed[k]= 1;
10959: Dummy[k]= 1;
10960: modell[k].maintype= VTYPE;
10961: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
10962: ncovv++; /* Varying variables without age */
10963: TvarV[ncovv]=Tvar[k];
10964: TvarVind[ncovv]=k;
10965: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10966: Fixed[k]= 1;
10967: Dummy[k]= 0;
10968: modell[k].maintype= VTYPE;
10969: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
10970: ncovv++; /* Varying variables without age */
10971: TvarV[ncovv]=Tvar[k];
10972: TvarVind[ncovv]=k;
10973: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10974: Fixed[k]= 1;
10975: Dummy[k]= 1;
10976: modell[k].maintype= VTYPE;
10977: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
10978: ncovv++; /* Varying variables without age */
10979: TvarV[ncovv]=Tvar[k];
10980: TvarVind[ncovv]=k;
10981: }
1.227 brouard 10982: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 10983: if(Tvard[k1][2] <=ncovcol){
10984: Fixed[k]= 1;
10985: Dummy[k]= 1;
10986: modell[k].maintype= VTYPE;
10987: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
10988: ncovv++; /* Varying variables without age */
10989: TvarV[ncovv]=Tvar[k];
10990: TvarVind[ncovv]=k;
10991: }else if(Tvard[k1][2] <=ncovcol+nqv){
10992: Fixed[k]= 1;
10993: Dummy[k]= 1;
10994: modell[k].maintype= VTYPE;
10995: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
10996: ncovv++; /* Varying variables without age */
10997: TvarV[ncovv]=Tvar[k];
10998: TvarVind[ncovv]=k;
10999: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
11000: Fixed[k]= 1;
11001: Dummy[k]= 1;
11002: modell[k].maintype= VTYPE;
11003: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
11004: ncovv++; /* Varying variables without age */
11005: TvarV[ncovv]=Tvar[k];
11006: TvarVind[ncovv]=k;
11007: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
11008: Fixed[k]= 1;
11009: Dummy[k]= 1;
11010: modell[k].maintype= VTYPE;
11011: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
11012: ncovv++; /* Varying variables without age */
11013: TvarV[ncovv]=Tvar[k];
11014: TvarVind[ncovv]=k;
11015: }
1.227 brouard 11016: }else{
1.240 brouard 11017: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
11018: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
11019: } /*end k1*/
1.225 brouard 11020: }else{
1.226 brouard 11021: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
11022: 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 11023: }
1.227 brouard 11024: 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]);
1.231 brouard 11025: printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype);
1.227 brouard 11026: 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]);
11027: }
11028: /* Searching for doublons in the model */
11029: for(k1=1; k1<= cptcovt;k1++){
11030: for(k2=1; k2 <k1;k2++){
1.285 brouard 11031: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
11032: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 11033: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
11034: if(Tvar[k1]==Tvar[k2]){
1.285 brouard 11035: printf("Error duplication in the model=%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]);
11036: fprintf(ficlog,"Error duplication in the model=%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 11037: return(1);
11038: }
11039: }else if (Typevar[k1] ==2){
11040: k3=Tposprod[k1];
11041: k4=Tposprod[k2];
11042: 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])) ){
11043: printf("Error duplication in the model=%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]]);
11044: fprintf(ficlog,"Error duplication in the model=%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);
11045: return(1);
11046: }
11047: }
1.227 brouard 11048: }
11049: }
1.225 brouard 11050: }
11051: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
11052: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 11053: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
11054: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 11055: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 11056: /*endread:*/
1.225 brouard 11057: printf("Exiting decodemodel: ");
11058: return (1);
1.136 brouard 11059: }
11060:
1.169 brouard 11061: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 11062: {/* Check ages at death */
1.136 brouard 11063: int i, m;
1.218 brouard 11064: int firstone=0;
11065:
1.136 brouard 11066: for (i=1; i<=imx; i++) {
11067: for(m=2; (m<= maxwav); m++) {
11068: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
11069: anint[m][i]=9999;
1.216 brouard 11070: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
11071: s[m][i]=-1;
1.136 brouard 11072: }
11073: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 11074: *nberr = *nberr + 1;
1.218 brouard 11075: if(firstone == 0){
11076: firstone=1;
1.260 brouard 11077: 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 11078: }
1.262 brouard 11079: 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 11080: s[m][i]=-1; /* Droping the death status */
1.136 brouard 11081: }
11082: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 11083: (*nberr)++;
1.259 brouard 11084: 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 11085: 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 11086: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 11087: }
11088: }
11089: }
11090:
11091: for (i=1; i<=imx; i++) {
11092: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
11093: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 11094: 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 11095: if (s[m][i] >= nlstate+1) {
1.169 brouard 11096: if(agedc[i]>0){
11097: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 11098: agev[m][i]=agedc[i];
1.214 brouard 11099: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 11100: }else {
1.136 brouard 11101: if ((int)andc[i]!=9999){
11102: nbwarn++;
11103: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
11104: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
11105: agev[m][i]=-1;
11106: }
11107: }
1.169 brouard 11108: } /* agedc > 0 */
1.214 brouard 11109: } /* end if */
1.136 brouard 11110: else if(s[m][i] !=9){ /* Standard case, age in fractional
11111: years but with the precision of a month */
11112: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
11113: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
11114: agev[m][i]=1;
11115: else if(agev[m][i] < *agemin){
11116: *agemin=agev[m][i];
11117: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
11118: }
11119: else if(agev[m][i] >*agemax){
11120: *agemax=agev[m][i];
1.156 brouard 11121: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 11122: }
11123: /*agev[m][i]=anint[m][i]-annais[i];*/
11124: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 11125: } /* en if 9*/
1.136 brouard 11126: else { /* =9 */
1.214 brouard 11127: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 11128: agev[m][i]=1;
11129: s[m][i]=-1;
11130: }
11131: }
1.214 brouard 11132: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 11133: agev[m][i]=1;
1.214 brouard 11134: else{
11135: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
11136: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
11137: agev[m][i]=0;
11138: }
11139: } /* End for lastpass */
11140: }
1.136 brouard 11141:
11142: for (i=1; i<=imx; i++) {
11143: for(m=firstpass; (m<=lastpass); m++){
11144: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 11145: (*nberr)++;
1.136 brouard 11146: 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);
11147: 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);
11148: return 1;
11149: }
11150: }
11151: }
11152:
11153: /*for (i=1; i<=imx; i++){
11154: for (m=firstpass; (m<lastpass); m++){
11155: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
11156: }
11157:
11158: }*/
11159:
11160:
1.139 brouard 11161: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
11162: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 11163:
11164: return (0);
1.164 brouard 11165: /* endread:*/
1.136 brouard 11166: printf("Exiting calandcheckages: ");
11167: return (1);
11168: }
11169:
1.172 brouard 11170: #if defined(_MSC_VER)
11171: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
11172: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
11173: //#include "stdafx.h"
11174: //#include <stdio.h>
11175: //#include <tchar.h>
11176: //#include <windows.h>
11177: //#include <iostream>
11178: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
11179:
11180: LPFN_ISWOW64PROCESS fnIsWow64Process;
11181:
11182: BOOL IsWow64()
11183: {
11184: BOOL bIsWow64 = FALSE;
11185:
11186: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
11187: // (HANDLE, PBOOL);
11188:
11189: //LPFN_ISWOW64PROCESS fnIsWow64Process;
11190:
11191: HMODULE module = GetModuleHandle(_T("kernel32"));
11192: const char funcName[] = "IsWow64Process";
11193: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
11194: GetProcAddress(module, funcName);
11195:
11196: if (NULL != fnIsWow64Process)
11197: {
11198: if (!fnIsWow64Process(GetCurrentProcess(),
11199: &bIsWow64))
11200: //throw std::exception("Unknown error");
11201: printf("Unknown error\n");
11202: }
11203: return bIsWow64 != FALSE;
11204: }
11205: #endif
1.177 brouard 11206:
1.191 brouard 11207: void syscompilerinfo(int logged)
1.292 brouard 11208: {
11209: #include <stdint.h>
11210:
11211: /* #include "syscompilerinfo.h"*/
1.185 brouard 11212: /* command line Intel compiler 32bit windows, XP compatible:*/
11213: /* /GS /W3 /Gy
11214: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
11215: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
11216: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 11217: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
11218: */
11219: /* 64 bits */
1.185 brouard 11220: /*
11221: /GS /W3 /Gy
11222: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
11223: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
11224: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
11225: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
11226: /* Optimization are useless and O3 is slower than O2 */
11227: /*
11228: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
11229: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
11230: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
11231: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
11232: */
1.186 brouard 11233: /* Link is */ /* /OUT:"visual studio
1.185 brouard 11234: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
11235: /PDB:"visual studio
11236: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
11237: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
11238: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
11239: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
11240: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
11241: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
11242: uiAccess='false'"
11243: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
11244: /NOLOGO /TLBID:1
11245: */
1.292 brouard 11246:
11247:
1.177 brouard 11248: #if defined __INTEL_COMPILER
1.178 brouard 11249: #if defined(__GNUC__)
11250: struct utsname sysInfo; /* For Intel on Linux and OS/X */
11251: #endif
1.177 brouard 11252: #elif defined(__GNUC__)
1.179 brouard 11253: #ifndef __APPLE__
1.174 brouard 11254: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 11255: #endif
1.177 brouard 11256: struct utsname sysInfo;
1.178 brouard 11257: int cross = CROSS;
11258: if (cross){
11259: printf("Cross-");
1.191 brouard 11260: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 11261: }
1.174 brouard 11262: #endif
11263:
1.191 brouard 11264: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 11265: #if defined(__clang__)
1.191 brouard 11266: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 11267: #endif
11268: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 11269: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 11270: #endif
11271: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 11272: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 11273: #endif
11274: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 11275: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 11276: #endif
11277: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 11278: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 11279: #endif
11280: #if defined(_MSC_VER)
1.191 brouard 11281: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 11282: #endif
11283: #if defined(__PGI)
1.191 brouard 11284: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 11285: #endif
11286: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 11287: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 11288: #endif
1.191 brouard 11289: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 11290:
1.167 brouard 11291: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
11292: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
11293: // Windows (x64 and x86)
1.191 brouard 11294: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 11295: #elif __unix__ // all unices, not all compilers
11296: // Unix
1.191 brouard 11297: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 11298: #elif __linux__
11299: // linux
1.191 brouard 11300: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 11301: #elif __APPLE__
1.174 brouard 11302: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 11303: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 11304: #endif
11305:
11306: /* __MINGW32__ */
11307: /* __CYGWIN__ */
11308: /* __MINGW64__ */
11309: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
11310: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
11311: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
11312: /* _WIN64 // Defined for applications for Win64. */
11313: /* _M_X64 // Defined for compilations that target x64 processors. */
11314: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 11315:
1.167 brouard 11316: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 11317: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 11318: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 11319: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 11320: #else
1.191 brouard 11321: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 11322: #endif
11323:
1.169 brouard 11324: #if defined(__GNUC__)
11325: # if defined(__GNUC_PATCHLEVEL__)
11326: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
11327: + __GNUC_MINOR__ * 100 \
11328: + __GNUC_PATCHLEVEL__)
11329: # else
11330: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
11331: + __GNUC_MINOR__ * 100)
11332: # endif
1.174 brouard 11333: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 11334: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 11335:
11336: if (uname(&sysInfo) != -1) {
11337: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 11338: 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 11339: }
11340: else
11341: perror("uname() error");
1.179 brouard 11342: //#ifndef __INTEL_COMPILER
11343: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 11344: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 11345: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 11346: #endif
1.169 brouard 11347: #endif
1.172 brouard 11348:
1.286 brouard 11349: // void main ()
1.172 brouard 11350: // {
1.169 brouard 11351: #if defined(_MSC_VER)
1.174 brouard 11352: if (IsWow64()){
1.191 brouard 11353: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
11354: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 11355: }
11356: else{
1.191 brouard 11357: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
11358: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 11359: }
1.172 brouard 11360: // printf("\nPress Enter to continue...");
11361: // getchar();
11362: // }
11363:
1.169 brouard 11364: #endif
11365:
1.167 brouard 11366:
1.219 brouard 11367: }
1.136 brouard 11368:
1.219 brouard 11369: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 11370: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.332 brouard 11371: /* Computes the prevalence limit for each combination of the dummy covariates */
1.235 brouard 11372: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 11373: /* double ftolpl = 1.e-10; */
1.180 brouard 11374: double age, agebase, agelim;
1.203 brouard 11375: double tot;
1.180 brouard 11376:
1.202 brouard 11377: strcpy(filerespl,"PL_");
11378: strcat(filerespl,fileresu);
11379: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 11380: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
11381: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 11382: }
1.288 brouard 11383: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
11384: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 11385: pstamp(ficrespl);
1.288 brouard 11386: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 11387: fprintf(ficrespl,"#Age ");
11388: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
11389: fprintf(ficrespl,"\n");
1.180 brouard 11390:
1.219 brouard 11391: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 11392:
1.219 brouard 11393: agebase=ageminpar;
11394: agelim=agemaxpar;
1.180 brouard 11395:
1.227 brouard 11396: /* i1=pow(2,ncoveff); */
1.234 brouard 11397: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 11398: if (cptcovn < 1){i1=1;}
1.180 brouard 11399:
1.238 brouard 11400: for(k=1; k<=i1;k++){ /* For each combination k of dummy covariates in the model */
11401: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 11402: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 11403: continue;
1.235 brouard 11404:
1.238 brouard 11405: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
11406: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
11407: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
11408: /* k=k+1; */
11409: /* to clean */
1.332 brouard 11410: /*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*/
1.238 brouard 11411: fprintf(ficrespl,"#******");
11412: printf("#******");
11413: fprintf(ficlog,"#******");
11414: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
1.332 brouard 11415: /* fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Here problem for varying dummy*\/ */
11416: fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /* Here problem for varying dummy*/
11417: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
11418: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.238 brouard 11419: }
11420: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
11421: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
11422: fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
11423: fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
11424: }
11425: fprintf(ficrespl,"******\n");
11426: printf("******\n");
11427: fprintf(ficlog,"******\n");
11428: if(invalidvarcomb[k]){
11429: printf("\nCombination (%d) ignored because no case \n",k);
11430: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
11431: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
11432: continue;
11433: }
1.219 brouard 11434:
1.238 brouard 11435: fprintf(ficrespl,"#Age ");
11436: for(j=1;j<=cptcoveff;j++) {
1.332 brouard 11437: fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.238 brouard 11438: }
11439: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
11440: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 11441:
1.238 brouard 11442: for (age=agebase; age<=agelim; age++){
11443: /* for (age=agebase; age<=agebase; age++){ */
11444: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres);
11445: fprintf(ficrespl,"%.0f ",age );
11446: for(j=1;j<=cptcoveff;j++)
1.332 brouard 11447: fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.238 brouard 11448: tot=0.;
11449: for(i=1; i<=nlstate;i++){
11450: tot += prlim[i][i];
11451: fprintf(ficrespl," %.5f", prlim[i][i]);
11452: }
11453: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
11454: } /* Age */
11455: /* was end of cptcod */
11456: } /* cptcov */
11457: } /* nres */
1.219 brouard 11458: return 0;
1.180 brouard 11459: }
11460:
1.218 brouard 11461: 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 11462: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 11463:
11464: /* Computes the back prevalence limit for any combination of covariate values
11465: * at any age between ageminpar and agemaxpar
11466: */
1.235 brouard 11467: int i, j, k, i1, nres=0 ;
1.217 brouard 11468: /* double ftolpl = 1.e-10; */
11469: double age, agebase, agelim;
11470: double tot;
1.218 brouard 11471: /* double ***mobaverage; */
11472: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 11473:
11474: strcpy(fileresplb,"PLB_");
11475: strcat(fileresplb,fileresu);
11476: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 11477: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
11478: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 11479: }
1.288 brouard 11480: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
11481: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 11482: pstamp(ficresplb);
1.288 brouard 11483: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 11484: fprintf(ficresplb,"#Age ");
11485: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
11486: fprintf(ficresplb,"\n");
11487:
1.218 brouard 11488:
11489: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
11490:
11491: agebase=ageminpar;
11492: agelim=agemaxpar;
11493:
11494:
1.227 brouard 11495: i1=pow(2,cptcoveff);
1.218 brouard 11496: if (cptcovn < 1){i1=1;}
1.227 brouard 11497:
1.238 brouard 11498: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
11499: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 11500: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 11501: continue;
1.332 brouard 11502: /*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*/
1.238 brouard 11503: fprintf(ficresplb,"#******");
11504: printf("#******");
11505: fprintf(ficlog,"#******");
11506: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
1.332 brouard 11507: fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
11508: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
11509: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.238 brouard 11510: }
11511: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.332 brouard 11512: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]);
11513: fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]);
11514: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]);
1.238 brouard 11515: }
11516: fprintf(ficresplb,"******\n");
11517: printf("******\n");
11518: fprintf(ficlog,"******\n");
11519: if(invalidvarcomb[k]){
11520: printf("\nCombination (%d) ignored because no cases \n",k);
11521: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
11522: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
11523: continue;
11524: }
1.218 brouard 11525:
1.238 brouard 11526: fprintf(ficresplb,"#Age ");
11527: for(j=1;j<=cptcoveff;j++) {
1.332 brouard 11528: fprintf(ficresplb,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.238 brouard 11529: }
11530: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
11531: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 11532:
11533:
1.238 brouard 11534: for (age=agebase; age<=agelim; age++){
11535: /* for (age=agebase; age<=agebase; age++){ */
11536: if(mobilavproj > 0){
11537: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
11538: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 11539: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 11540: }else if (mobilavproj == 0){
11541: 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);
11542: 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);
11543: exit(1);
11544: }else{
11545: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 11546: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 11547: /* printf("TOTOT\n"); */
11548: /* exit(1); */
1.238 brouard 11549: }
11550: fprintf(ficresplb,"%.0f ",age );
11551: for(j=1;j<=cptcoveff;j++)
1.332 brouard 11552: fprintf(ficresplb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.238 brouard 11553: tot=0.;
11554: for(i=1; i<=nlstate;i++){
11555: tot += bprlim[i][i];
11556: fprintf(ficresplb," %.5f", bprlim[i][i]);
11557: }
11558: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
11559: } /* Age */
11560: /* was end of cptcod */
1.255 brouard 11561: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.238 brouard 11562: } /* end of any combination */
11563: } /* end of nres */
1.218 brouard 11564: /* hBijx(p, bage, fage); */
11565: /* fclose(ficrespijb); */
11566:
11567: return 0;
1.217 brouard 11568: }
1.218 brouard 11569:
1.180 brouard 11570: int hPijx(double *p, int bage, int fage){
11571: /*------------- h Pij x at various ages ------------*/
11572:
11573: int stepsize;
11574: int agelim;
11575: int hstepm;
11576: int nhstepm;
1.235 brouard 11577: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 11578:
11579: double agedeb;
11580: double ***p3mat;
11581:
1.201 brouard 11582: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
1.180 brouard 11583: if((ficrespij=fopen(filerespij,"w"))==NULL) {
11584: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
11585: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
11586: }
11587: printf("Computing pij: result on file '%s' \n", filerespij);
11588: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
11589:
11590: stepsize=(int) (stepm+YEARM-1)/YEARM;
11591: /*if (stepm<=24) stepsize=2;*/
11592:
11593: agelim=AGESUP;
11594: hstepm=stepsize*YEARM; /* Every year of age */
11595: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
1.218 brouard 11596:
1.180 brouard 11597: /* hstepm=1; aff par mois*/
11598: pstamp(ficrespij);
11599: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
1.227 brouard 11600: i1= pow(2,cptcoveff);
1.218 brouard 11601: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
11602: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
11603: /* k=k+1; */
1.235 brouard 11604: for(nres=1; nres <= nresult; nres++) /* For each resultline */
11605: for(k=1; k<=i1;k++){
1.253 brouard 11606: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 11607: continue;
1.183 brouard 11608: fprintf(ficrespij,"\n#****** ");
1.227 brouard 11609: for(j=1;j<=cptcoveff;j++)
1.332 brouard 11610: fprintf(ficrespij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.235 brouard 11611: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
11612: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
11613: fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
11614: }
1.183 brouard 11615: fprintf(ficrespij,"******\n");
11616:
11617: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
11618: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
11619: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
11620:
11621: /* nhstepm=nhstepm*YEARM; aff par mois*/
1.180 brouard 11622:
1.183 brouard 11623: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11624: oldm=oldms;savm=savms;
1.235 brouard 11625: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.183 brouard 11626: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
11627: for(i=1; i<=nlstate;i++)
11628: for(j=1; j<=nlstate+ndeath;j++)
11629: fprintf(ficrespij," %1d-%1d",i,j);
11630: fprintf(ficrespij,"\n");
11631: for (h=0; h<=nhstepm; h++){
11632: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
11633: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.180 brouard 11634: for(i=1; i<=nlstate;i++)
11635: for(j=1; j<=nlstate+ndeath;j++)
1.183 brouard 11636: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.180 brouard 11637: fprintf(ficrespij,"\n");
11638: }
1.183 brouard 11639: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11640: fprintf(ficrespij,"\n");
11641: }
1.180 brouard 11642: /*}*/
11643: }
1.218 brouard 11644: return 0;
1.180 brouard 11645: }
1.218 brouard 11646:
11647: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 11648: /*------------- h Bij x at various ages ------------*/
11649:
11650: int stepsize;
1.218 brouard 11651: /* int agelim; */
11652: int ageminl;
1.217 brouard 11653: int hstepm;
11654: int nhstepm;
1.238 brouard 11655: int h, i, i1, j, k, nres;
1.218 brouard 11656:
1.217 brouard 11657: double agedeb;
11658: double ***p3mat;
1.218 brouard 11659:
11660: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
11661: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
11662: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
11663: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
11664: }
11665: printf("Computing pij back: result on file '%s' \n", filerespijb);
11666: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
11667:
11668: stepsize=(int) (stepm+YEARM-1)/YEARM;
11669: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 11670:
1.218 brouard 11671: /* agelim=AGESUP; */
1.289 brouard 11672: ageminl=AGEINF; /* was 30 */
1.218 brouard 11673: hstepm=stepsize*YEARM; /* Every year of age */
11674: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
11675:
11676: /* hstepm=1; aff par mois*/
11677: pstamp(ficrespijb);
1.255 brouard 11678: 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 11679: i1= pow(2,cptcoveff);
1.218 brouard 11680: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
11681: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
11682: /* k=k+1; */
1.238 brouard 11683: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
11684: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 11685: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 11686: continue;
11687: fprintf(ficrespijb,"\n#****** ");
11688: for(j=1;j<=cptcoveff;j++)
1.332 brouard 11689: fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.238 brouard 11690: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.332 brouard 11691: fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]);
1.238 brouard 11692: }
11693: fprintf(ficrespijb,"******\n");
1.264 brouard 11694: if(invalidvarcomb[k]){ /* Is it necessary here? */
1.238 brouard 11695: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
11696: continue;
11697: }
11698:
11699: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
11700: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
11701: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
1.297 brouard 11702: 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 */
11703: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 or 28*/
1.238 brouard 11704:
11705: /* nhstepm=nhstepm*YEARM; aff par mois*/
11706:
1.266 brouard 11707: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
11708: /* and memory limitations if stepm is small */
11709:
1.238 brouard 11710: /* oldm=oldms;savm=savms; */
11711: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.325 brouard 11712: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);/* Bug valgrind */
1.238 brouard 11713: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
1.255 brouard 11714: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
1.217 brouard 11715: for(i=1; i<=nlstate;i++)
11716: for(j=1; j<=nlstate+ndeath;j++)
1.238 brouard 11717: fprintf(ficrespijb," %1d-%1d",i,j);
1.217 brouard 11718: fprintf(ficrespijb,"\n");
1.238 brouard 11719: for (h=0; h<=nhstepm; h++){
11720: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
11721: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
11722: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
11723: for(i=1; i<=nlstate;i++)
11724: for(j=1; j<=nlstate+ndeath;j++)
1.325 brouard 11725: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);/* Bug valgrind */
1.238 brouard 11726: fprintf(ficrespijb,"\n");
11727: }
11728: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11729: fprintf(ficrespijb,"\n");
11730: } /* end age deb */
11731: } /* end combination */
11732: } /* end nres */
1.218 brouard 11733: return 0;
11734: } /* hBijx */
1.217 brouard 11735:
1.180 brouard 11736:
1.136 brouard 11737: /***********************************************/
11738: /**************** Main Program *****************/
11739: /***********************************************/
11740:
11741: int main(int argc, char *argv[])
11742: {
11743: #ifdef GSL
11744: const gsl_multimin_fminimizer_type *T;
11745: size_t iteri = 0, it;
11746: int rval = GSL_CONTINUE;
11747: int status = GSL_SUCCESS;
11748: double ssval;
11749: #endif
11750: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 11751: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
11752: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 11753: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 11754: int jj, ll, li, lj, lk;
1.136 brouard 11755: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 11756: int num_filled;
1.136 brouard 11757: int itimes;
11758: int NDIM=2;
11759: int vpopbased=0;
1.235 brouard 11760: int nres=0;
1.258 brouard 11761: int endishere=0;
1.277 brouard 11762: int noffset=0;
1.274 brouard 11763: int ncurrv=0; /* Temporary variable */
11764:
1.164 brouard 11765: char ca[32], cb[32];
1.136 brouard 11766: /* FILE *fichtm; *//* Html File */
11767: /* FILE *ficgp;*/ /*Gnuplot File */
11768: struct stat info;
1.191 brouard 11769: double agedeb=0.;
1.194 brouard 11770:
11771: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 11772: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 11773:
1.165 brouard 11774: double fret;
1.191 brouard 11775: double dum=0.; /* Dummy variable */
1.136 brouard 11776: double ***p3mat;
1.218 brouard 11777: /* double ***mobaverage; */
1.319 brouard 11778: double wald;
1.164 brouard 11779:
11780: char line[MAXLINE];
1.197 brouard 11781: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
11782:
1.234 brouard 11783: char modeltemp[MAXLINE];
1.332 brouard 11784: char resultline[MAXLINE], resultlineori[MAXLINE];
1.230 brouard 11785:
1.136 brouard 11786: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 11787: char *tok, *val; /* pathtot */
1.334 ! brouard 11788: /* int firstobs=1, lastobs=10; /\* nobs = lastobs-firstobs declared globally ;*\/ */
1.195 brouard 11789: int c, h , cpt, c2;
1.191 brouard 11790: int jl=0;
11791: int i1, j1, jk, stepsize=0;
1.194 brouard 11792: int count=0;
11793:
1.164 brouard 11794: int *tab;
1.136 brouard 11795: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.296 brouard 11796: /* double anprojd, mprojd, jprojd; /\* For eventual projections *\/ */
11797: /* double anprojf, mprojf, jprojf; */
11798: /* double jintmean,mintmean,aintmean; */
11799: int prvforecast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
11800: int prvbackcast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
11801: double yrfproj= 10.0; /* Number of years of forward projections */
11802: double yrbproj= 10.0; /* Number of years of backward projections */
11803: int prevbcast=0; /* defined as global for mlikeli and mle, replacing backcast */
1.136 brouard 11804: int mobilav=0,popforecast=0;
1.191 brouard 11805: int hstepm=0, nhstepm=0;
1.136 brouard 11806: int agemortsup;
11807: float sumlpop=0.;
11808: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
11809: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
11810:
1.191 brouard 11811: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 11812: double ftolpl=FTOL;
11813: double **prlim;
1.217 brouard 11814: double **bprlim;
1.317 brouard 11815: double ***param; /* Matrix of parameters, param[i][j][k] param=ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel)
11816: state of origin, state of destination including death, for each covariate: constante, age, and V1 V2 etc. */
1.251 brouard 11817: double ***paramstart; /* Matrix of starting parameter values */
11818: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 11819: double **matcov; /* Matrix of covariance */
1.203 brouard 11820: double **hess; /* Hessian matrix */
1.136 brouard 11821: double ***delti3; /* Scale */
11822: double *delti; /* Scale */
11823: double ***eij, ***vareij;
11824: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 11825:
1.136 brouard 11826: double *epj, vepp;
1.164 brouard 11827:
1.273 brouard 11828: double dateprev1, dateprev2;
1.296 brouard 11829: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0, dateprojd=0, dateprojf=0;
11830: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0, datebackd=0, datebackf=0;
11831:
1.217 brouard 11832:
1.136 brouard 11833: double **ximort;
1.145 brouard 11834: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 11835: int *dcwave;
11836:
1.164 brouard 11837: char z[1]="c";
1.136 brouard 11838:
11839: /*char *strt;*/
11840: char strtend[80];
1.126 brouard 11841:
1.164 brouard 11842:
1.126 brouard 11843: /* setlocale (LC_ALL, ""); */
11844: /* bindtextdomain (PACKAGE, LOCALEDIR); */
11845: /* textdomain (PACKAGE); */
11846: /* setlocale (LC_CTYPE, ""); */
11847: /* setlocale (LC_MESSAGES, ""); */
11848:
11849: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 11850: rstart_time = time(NULL);
11851: /* (void) gettimeofday(&start_time,&tzp);*/
11852: start_time = *localtime(&rstart_time);
1.126 brouard 11853: curr_time=start_time;
1.157 brouard 11854: /*tml = *localtime(&start_time.tm_sec);*/
11855: /* strcpy(strstart,asctime(&tml)); */
11856: strcpy(strstart,asctime(&start_time));
1.126 brouard 11857:
11858: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 11859: /* tp.tm_sec = tp.tm_sec +86400; */
11860: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 11861: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
11862: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
11863: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 11864: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 11865: /* strt=asctime(&tmg); */
11866: /* printf("Time(after) =%s",strstart); */
11867: /* (void) time (&time_value);
11868: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
11869: * tm = *localtime(&time_value);
11870: * strstart=asctime(&tm);
11871: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
11872: */
11873:
11874: nberr=0; /* Number of errors and warnings */
11875: nbwarn=0;
1.184 brouard 11876: #ifdef WIN32
11877: _getcwd(pathcd, size);
11878: #else
1.126 brouard 11879: getcwd(pathcd, size);
1.184 brouard 11880: #endif
1.191 brouard 11881: syscompilerinfo(0);
1.196 brouard 11882: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 11883: if(argc <=1){
11884: printf("\nEnter the parameter file name: ");
1.205 brouard 11885: if(!fgets(pathr,FILENAMELENGTH,stdin)){
11886: printf("ERROR Empty parameter file name\n");
11887: goto end;
11888: }
1.126 brouard 11889: i=strlen(pathr);
11890: if(pathr[i-1]=='\n')
11891: pathr[i-1]='\0';
1.156 brouard 11892: i=strlen(pathr);
1.205 brouard 11893: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 11894: pathr[i-1]='\0';
1.205 brouard 11895: }
11896: i=strlen(pathr);
11897: if( i==0 ){
11898: printf("ERROR Empty parameter file name\n");
11899: goto end;
11900: }
11901: for (tok = pathr; tok != NULL; ){
1.126 brouard 11902: printf("Pathr |%s|\n",pathr);
11903: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
11904: printf("val= |%s| pathr=%s\n",val,pathr);
11905: strcpy (pathtot, val);
11906: if(pathr[0] == '\0') break; /* Dirty */
11907: }
11908: }
1.281 brouard 11909: else if (argc<=2){
11910: strcpy(pathtot,argv[1]);
11911: }
1.126 brouard 11912: else{
11913: strcpy(pathtot,argv[1]);
1.281 brouard 11914: strcpy(z,argv[2]);
11915: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 11916: }
11917: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
11918: /*cygwin_split_path(pathtot,path,optionfile);
11919: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
11920: /* cutv(path,optionfile,pathtot,'\\');*/
11921:
11922: /* Split argv[0], imach program to get pathimach */
11923: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
11924: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
11925: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
11926: /* strcpy(pathimach,argv[0]); */
11927: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
11928: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
11929: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 11930: #ifdef WIN32
11931: _chdir(path); /* Can be a relative path */
11932: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
11933: #else
1.126 brouard 11934: chdir(path); /* Can be a relative path */
1.184 brouard 11935: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
11936: #endif
11937: printf("Current directory %s!\n",pathcd);
1.126 brouard 11938: strcpy(command,"mkdir ");
11939: strcat(command,optionfilefiname);
11940: if((outcmd=system(command)) != 0){
1.169 brouard 11941: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 11942: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
11943: /* fclose(ficlog); */
11944: /* exit(1); */
11945: }
11946: /* if((imk=mkdir(optionfilefiname))<0){ */
11947: /* perror("mkdir"); */
11948: /* } */
11949:
11950: /*-------- arguments in the command line --------*/
11951:
1.186 brouard 11952: /* Main Log file */
1.126 brouard 11953: strcat(filelog, optionfilefiname);
11954: strcat(filelog,".log"); /* */
11955: if((ficlog=fopen(filelog,"w"))==NULL) {
11956: printf("Problem with logfile %s\n",filelog);
11957: goto end;
11958: }
11959: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 11960: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 11961: fprintf(ficlog,"\nEnter the parameter file name: \n");
11962: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
11963: path=%s \n\
11964: optionfile=%s\n\
11965: optionfilext=%s\n\
1.156 brouard 11966: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 11967:
1.197 brouard 11968: syscompilerinfo(1);
1.167 brouard 11969:
1.126 brouard 11970: printf("Local time (at start):%s",strstart);
11971: fprintf(ficlog,"Local time (at start): %s",strstart);
11972: fflush(ficlog);
11973: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 11974: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 11975:
11976: /* */
11977: strcpy(fileres,"r");
11978: strcat(fileres, optionfilefiname);
1.201 brouard 11979: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 11980: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 11981: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 11982:
1.186 brouard 11983: /* Main ---------arguments file --------*/
1.126 brouard 11984:
11985: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 11986: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
11987: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 11988: fflush(ficlog);
1.149 brouard 11989: /* goto end; */
11990: exit(70);
1.126 brouard 11991: }
11992:
11993: strcpy(filereso,"o");
1.201 brouard 11994: strcat(filereso,fileresu);
1.126 brouard 11995: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
11996: printf("Problem with Output resultfile: %s\n", filereso);
11997: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
11998: fflush(ficlog);
11999: goto end;
12000: }
1.278 brouard 12001: /*-------- Rewriting parameter file ----------*/
12002: strcpy(rfileres,"r"); /* "Rparameterfile */
12003: strcat(rfileres,optionfilefiname); /* Parameter file first name */
12004: strcat(rfileres,"."); /* */
12005: strcat(rfileres,optionfilext); /* Other files have txt extension */
12006: if((ficres =fopen(rfileres,"w"))==NULL) {
12007: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
12008: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
12009: fflush(ficlog);
12010: goto end;
12011: }
12012: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 12013:
1.278 brouard 12014:
1.126 brouard 12015: /* Reads comments: lines beginning with '#' */
12016: numlinepar=0;
1.277 brouard 12017: /* Is it a BOM UTF-8 Windows file? */
12018: /* First parameter line */
1.197 brouard 12019: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 12020: noffset=0;
12021: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
12022: {
12023: noffset=noffset+3;
12024: printf("# File is an UTF8 Bom.\n"); // 0xBF
12025: }
1.302 brouard 12026: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
12027: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
1.277 brouard 12028: {
12029: noffset=noffset+2;
12030: printf("# File is an UTF16BE BOM file\n");
12031: }
12032: else if( line[0] == 0 && line[1] == 0)
12033: {
12034: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
12035: noffset=noffset+4;
12036: printf("# File is an UTF16BE BOM file\n");
12037: }
12038: } else{
12039: ;/*printf(" Not a BOM file\n");*/
12040: }
12041:
1.197 brouard 12042: /* If line starts with a # it is a comment */
1.277 brouard 12043: if (line[noffset] == '#') {
1.197 brouard 12044: numlinepar++;
12045: fputs(line,stdout);
12046: fputs(line,ficparo);
1.278 brouard 12047: fputs(line,ficres);
1.197 brouard 12048: fputs(line,ficlog);
12049: continue;
12050: }else
12051: break;
12052: }
12053: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
12054: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
12055: if (num_filled != 5) {
12056: printf("Should be 5 parameters\n");
1.283 brouard 12057: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 12058: }
1.126 brouard 12059: numlinepar++;
1.197 brouard 12060: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 12061: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
12062: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
12063: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 12064: }
12065: /* Second parameter line */
12066: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 12067: /* while(fscanf(ficpar,"%[^\n]", line)) { */
12068: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 12069: if (line[0] == '#') {
12070: numlinepar++;
1.283 brouard 12071: printf("%s",line);
12072: fprintf(ficres,"%s",line);
12073: fprintf(ficparo,"%s",line);
12074: fprintf(ficlog,"%s",line);
1.197 brouard 12075: continue;
12076: }else
12077: break;
12078: }
1.223 brouard 12079: 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", \
12080: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
12081: if (num_filled != 11) {
12082: 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 12083: printf("but line=%s\n",line);
1.283 brouard 12084: 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");
12085: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 12086: }
1.286 brouard 12087: if( lastpass > maxwav){
12088: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
12089: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
12090: fflush(ficlog);
12091: goto end;
12092: }
12093: 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 12094: 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 12095: 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 12096: 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 12097: }
1.203 brouard 12098: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 12099: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 12100: /* Third parameter line */
12101: while(fgets(line, MAXLINE, ficpar)) {
12102: /* If line starts with a # it is a comment */
12103: if (line[0] == '#') {
12104: numlinepar++;
1.283 brouard 12105: printf("%s",line);
12106: fprintf(ficres,"%s",line);
12107: fprintf(ficparo,"%s",line);
12108: fprintf(ficlog,"%s",line);
1.197 brouard 12109: continue;
12110: }else
12111: break;
12112: }
1.201 brouard 12113: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.279 brouard 12114: if (num_filled != 1){
1.302 brouard 12115: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
12116: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
1.197 brouard 12117: model[0]='\0';
12118: goto end;
12119: }
12120: else{
12121: if (model[0]=='+'){
12122: for(i=1; i<=strlen(model);i++)
12123: modeltemp[i-1]=model[i];
1.201 brouard 12124: strcpy(model,modeltemp);
1.197 brouard 12125: }
12126: }
1.199 brouard 12127: /* printf(" model=1+age%s modeltemp= %s, model=%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 12128: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 12129: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
12130: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
12131: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 12132: }
12133: /* 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); */
12134: /* numlinepar=numlinepar+3; /\* In general *\/ */
12135: /* 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 12136: /* 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); */
12137: /* 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 12138: fflush(ficlog);
1.190 brouard 12139: /* if(model[0]=='#'|| model[0]== '\0'){ */
12140: if(model[0]=='#'){
1.279 brouard 12141: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
12142: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
12143: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 12144: if(mle != -1){
1.279 brouard 12145: 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 12146: exit(1);
12147: }
12148: }
1.126 brouard 12149: while((c=getc(ficpar))=='#' && c!= EOF){
12150: ungetc(c,ficpar);
12151: fgets(line, MAXLINE, ficpar);
12152: numlinepar++;
1.195 brouard 12153: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
12154: z[0]=line[1];
12155: }
12156: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 12157: fputs(line, stdout);
12158: //puts(line);
1.126 brouard 12159: fputs(line,ficparo);
12160: fputs(line,ficlog);
12161: }
12162: ungetc(c,ficpar);
12163:
12164:
1.290 brouard 12165: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
12166: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
12167: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
12168: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /**< Time varying covariate (dummy and quantitative)*/
1.136 brouard 12169: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
12170: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
12171: v1+v2*age+v2*v3 makes cptcovn = 3
12172: */
12173: if (strlen(model)>1)
1.187 brouard 12174: 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 12175: else
1.187 brouard 12176: ncovmodel=2; /* Constant and age */
1.133 brouard 12177: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
12178: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 12179: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
12180: 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);
12181: 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);
12182: fflush(stdout);
12183: fclose (ficlog);
12184: goto end;
12185: }
1.126 brouard 12186: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
12187: delti=delti3[1][1];
12188: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
12189: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 12190: /* We could also provide initial parameters values giving by simple logistic regression
12191: * only one way, that is without matrix product. We will have nlstate maximizations */
12192: /* for(i=1;i<nlstate;i++){ */
12193: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
12194: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
12195: /* } */
1.126 brouard 12196: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 12197: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
12198: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 12199: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12200: fclose (ficparo);
12201: fclose (ficlog);
12202: goto end;
12203: exit(0);
1.220 brouard 12204: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 12205: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 12206: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
12207: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 12208: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
12209: matcov=matrix(1,npar,1,npar);
1.203 brouard 12210: hess=matrix(1,npar,1,npar);
1.220 brouard 12211: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 12212: /* Read guessed parameters */
1.126 brouard 12213: /* Reads comments: lines beginning with '#' */
12214: while((c=getc(ficpar))=='#' && c!= EOF){
12215: ungetc(c,ficpar);
12216: fgets(line, MAXLINE, ficpar);
12217: numlinepar++;
1.141 brouard 12218: fputs(line,stdout);
1.126 brouard 12219: fputs(line,ficparo);
12220: fputs(line,ficlog);
12221: }
12222: ungetc(c,ficpar);
12223:
12224: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 12225: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 12226: for(i=1; i <=nlstate; i++){
1.234 brouard 12227: j=0;
1.126 brouard 12228: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 12229: if(jj==i) continue;
12230: j++;
1.292 brouard 12231: while((c=getc(ficpar))=='#' && c!= EOF){
12232: ungetc(c,ficpar);
12233: fgets(line, MAXLINE, ficpar);
12234: numlinepar++;
12235: fputs(line,stdout);
12236: fputs(line,ficparo);
12237: fputs(line,ficlog);
12238: }
12239: ungetc(c,ficpar);
1.234 brouard 12240: fscanf(ficpar,"%1d%1d",&i1,&j1);
12241: if ((i1 != i) || (j1 != jj)){
12242: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 12243: It might be a problem of design; if ncovcol and the model are correct\n \
12244: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 12245: exit(1);
12246: }
12247: fprintf(ficparo,"%1d%1d",i1,j1);
12248: if(mle==1)
12249: printf("%1d%1d",i,jj);
12250: fprintf(ficlog,"%1d%1d",i,jj);
12251: for(k=1; k<=ncovmodel;k++){
12252: fscanf(ficpar," %lf",¶m[i][j][k]);
12253: if(mle==1){
12254: printf(" %lf",param[i][j][k]);
12255: fprintf(ficlog," %lf",param[i][j][k]);
12256: }
12257: else
12258: fprintf(ficlog," %lf",param[i][j][k]);
12259: fprintf(ficparo," %lf",param[i][j][k]);
12260: }
12261: fscanf(ficpar,"\n");
12262: numlinepar++;
12263: if(mle==1)
12264: printf("\n");
12265: fprintf(ficlog,"\n");
12266: fprintf(ficparo,"\n");
1.126 brouard 12267: }
12268: }
12269: fflush(ficlog);
1.234 brouard 12270:
1.251 brouard 12271: /* Reads parameters values */
1.126 brouard 12272: p=param[1][1];
1.251 brouard 12273: pstart=paramstart[1][1];
1.126 brouard 12274:
12275: /* Reads comments: lines beginning with '#' */
12276: while((c=getc(ficpar))=='#' && c!= EOF){
12277: ungetc(c,ficpar);
12278: fgets(line, MAXLINE, ficpar);
12279: numlinepar++;
1.141 brouard 12280: fputs(line,stdout);
1.126 brouard 12281: fputs(line,ficparo);
12282: fputs(line,ficlog);
12283: }
12284: ungetc(c,ficpar);
12285:
12286: for(i=1; i <=nlstate; i++){
12287: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 12288: fscanf(ficpar,"%1d%1d",&i1,&j1);
12289: if ( (i1-i) * (j1-j) != 0){
12290: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
12291: exit(1);
12292: }
12293: printf("%1d%1d",i,j);
12294: fprintf(ficparo,"%1d%1d",i1,j1);
12295: fprintf(ficlog,"%1d%1d",i1,j1);
12296: for(k=1; k<=ncovmodel;k++){
12297: fscanf(ficpar,"%le",&delti3[i][j][k]);
12298: printf(" %le",delti3[i][j][k]);
12299: fprintf(ficparo," %le",delti3[i][j][k]);
12300: fprintf(ficlog," %le",delti3[i][j][k]);
12301: }
12302: fscanf(ficpar,"\n");
12303: numlinepar++;
12304: printf("\n");
12305: fprintf(ficparo,"\n");
12306: fprintf(ficlog,"\n");
1.126 brouard 12307: }
12308: }
12309: fflush(ficlog);
1.234 brouard 12310:
1.145 brouard 12311: /* Reads covariance matrix */
1.126 brouard 12312: delti=delti3[1][1];
1.220 brouard 12313:
12314:
1.126 brouard 12315: /* 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 12316:
1.126 brouard 12317: /* Reads comments: lines beginning with '#' */
12318: while((c=getc(ficpar))=='#' && c!= EOF){
12319: ungetc(c,ficpar);
12320: fgets(line, MAXLINE, ficpar);
12321: numlinepar++;
1.141 brouard 12322: fputs(line,stdout);
1.126 brouard 12323: fputs(line,ficparo);
12324: fputs(line,ficlog);
12325: }
12326: ungetc(c,ficpar);
1.220 brouard 12327:
1.126 brouard 12328: matcov=matrix(1,npar,1,npar);
1.203 brouard 12329: hess=matrix(1,npar,1,npar);
1.131 brouard 12330: for(i=1; i <=npar; i++)
12331: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 12332:
1.194 brouard 12333: /* Scans npar lines */
1.126 brouard 12334: for(i=1; i <=npar; i++){
1.226 brouard 12335: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 12336: if(count != 3){
1.226 brouard 12337: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 12338: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
12339: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 12340: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 12341: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
12342: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 12343: exit(1);
1.220 brouard 12344: }else{
1.226 brouard 12345: if(mle==1)
12346: printf("%1d%1d%d",i1,j1,jk);
12347: }
12348: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
12349: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 12350: for(j=1; j <=i; j++){
1.226 brouard 12351: fscanf(ficpar," %le",&matcov[i][j]);
12352: if(mle==1){
12353: printf(" %.5le",matcov[i][j]);
12354: }
12355: fprintf(ficlog," %.5le",matcov[i][j]);
12356: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 12357: }
12358: fscanf(ficpar,"\n");
12359: numlinepar++;
12360: if(mle==1)
1.220 brouard 12361: printf("\n");
1.126 brouard 12362: fprintf(ficlog,"\n");
12363: fprintf(ficparo,"\n");
12364: }
1.194 brouard 12365: /* End of read covariance matrix npar lines */
1.126 brouard 12366: for(i=1; i <=npar; i++)
12367: for(j=i+1;j<=npar;j++)
1.226 brouard 12368: matcov[i][j]=matcov[j][i];
1.126 brouard 12369:
12370: if(mle==1)
12371: printf("\n");
12372: fprintf(ficlog,"\n");
12373:
12374: fflush(ficlog);
12375:
12376: } /* End of mle != -3 */
1.218 brouard 12377:
1.186 brouard 12378: /* Main data
12379: */
1.290 brouard 12380: nobs=lastobs-firstobs+1; /* was = lastobs;*/
12381: /* num=lvector(1,n); */
12382: /* moisnais=vector(1,n); */
12383: /* annais=vector(1,n); */
12384: /* moisdc=vector(1,n); */
12385: /* andc=vector(1,n); */
12386: /* weight=vector(1,n); */
12387: /* agedc=vector(1,n); */
12388: /* cod=ivector(1,n); */
12389: /* for(i=1;i<=n;i++){ */
12390: num=lvector(firstobs,lastobs);
12391: moisnais=vector(firstobs,lastobs);
12392: annais=vector(firstobs,lastobs);
12393: moisdc=vector(firstobs,lastobs);
12394: andc=vector(firstobs,lastobs);
12395: weight=vector(firstobs,lastobs);
12396: agedc=vector(firstobs,lastobs);
12397: cod=ivector(firstobs,lastobs);
12398: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 12399: num[i]=0;
12400: moisnais[i]=0;
12401: annais[i]=0;
12402: moisdc[i]=0;
12403: andc[i]=0;
12404: agedc[i]=0;
12405: cod[i]=0;
12406: weight[i]=1.0; /* Equal weights, 1 by default */
12407: }
1.290 brouard 12408: mint=matrix(1,maxwav,firstobs,lastobs);
12409: anint=matrix(1,maxwav,firstobs,lastobs);
1.325 brouard 12410: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
12411: printf("BUG ncovmodel=%d NCOVMAX=%d 2**ncovmodel=%f BUG\n",ncovmodel,NCOVMAX,pow(2,ncovmodel));
1.126 brouard 12412: tab=ivector(1,NCOVMAX);
1.144 brouard 12413: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 12414: 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 12415:
1.136 brouard 12416: /* Reads data from file datafile */
12417: if (readdata(datafile, firstobs, lastobs, &imx)==1)
12418: goto end;
12419:
12420: /* Calculation of the number of parameters from char model */
1.234 brouard 12421: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 12422: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
12423: k=3 V4 Tvar[k=3]= 4 (from V4)
12424: k=2 V1 Tvar[k=2]= 1 (from V1)
12425: k=1 Tvar[1]=2 (from V2)
1.234 brouard 12426: */
12427:
12428: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
12429: TvarsDind=ivector(1,NCOVMAX); /* */
1.330 brouard 12430: TnsdVar=ivector(1,NCOVMAX); /* */
1.234 brouard 12431: TvarsD=ivector(1,NCOVMAX); /* */
12432: TvarsQind=ivector(1,NCOVMAX); /* */
12433: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 12434: TvarF=ivector(1,NCOVMAX); /* */
12435: TvarFind=ivector(1,NCOVMAX); /* */
12436: TvarV=ivector(1,NCOVMAX); /* */
12437: TvarVind=ivector(1,NCOVMAX); /* */
12438: TvarA=ivector(1,NCOVMAX); /* */
12439: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 12440: TvarFD=ivector(1,NCOVMAX); /* */
12441: TvarFDind=ivector(1,NCOVMAX); /* */
12442: TvarFQ=ivector(1,NCOVMAX); /* */
12443: TvarFQind=ivector(1,NCOVMAX); /* */
12444: TvarVD=ivector(1,NCOVMAX); /* */
12445: TvarVDind=ivector(1,NCOVMAX); /* */
12446: TvarVQ=ivector(1,NCOVMAX); /* */
12447: TvarVQind=ivector(1,NCOVMAX); /* */
12448:
1.230 brouard 12449: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 12450: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 12451: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
12452: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
12453: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.137 brouard 12454: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
12455: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
12456: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
12457: */
12458: /* For model-covariate k tells which data-covariate to use but
12459: because this model-covariate is a construction we invent a new column
12460: ncovcol + k1
12461: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
12462: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 12463: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
12464: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 12465: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
12466: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 12467: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 12468: */
1.145 brouard 12469: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
12470: 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 12471: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
12472: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.330 brouard 12473: Tvardk=imatrix(1,NCOVMAX,1,2);
1.145 brouard 12474: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 12475: 4 covariates (3 plus signs)
12476: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
1.328 brouard 12477: */
12478: for(i=1;i<NCOVMAX;i++)
12479: Tage[i]=0;
1.230 brouard 12480: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 12481: * individual dummy, fixed or varying:
12482: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
12483: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 12484: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
12485: * V1 df, V2 qf, V3 & V4 dv, V5 qv
12486: * Tmodelind[1]@9={9,0,3,2,}*/
12487: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
12488: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 12489: * individual quantitative, fixed or varying:
12490: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
12491: * 3, 1, 0, 0, 0, 0, 0, 0},
12492: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 12493: /* Main decodemodel */
12494:
1.187 brouard 12495:
1.223 brouard 12496: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 12497: goto end;
12498:
1.137 brouard 12499: if((double)(lastobs-imx)/(double)imx > 1.10){
12500: nbwarn++;
12501: 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);
12502: 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);
12503: }
1.136 brouard 12504: /* if(mle==1){*/
1.137 brouard 12505: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
12506: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 12507: }
12508:
12509: /*-calculation of age at interview from date of interview and age at death -*/
12510: agev=matrix(1,maxwav,1,imx);
12511:
12512: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
12513: goto end;
12514:
1.126 brouard 12515:
1.136 brouard 12516: agegomp=(int)agemin;
1.290 brouard 12517: free_vector(moisnais,firstobs,lastobs);
12518: free_vector(annais,firstobs,lastobs);
1.126 brouard 12519: /* free_matrix(mint,1,maxwav,1,n);
12520: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 12521: /* free_vector(moisdc,1,n); */
12522: /* free_vector(andc,1,n); */
1.145 brouard 12523: /* */
12524:
1.126 brouard 12525: wav=ivector(1,imx);
1.214 brouard 12526: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
12527: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
12528: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
12529: 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.*/
12530: bh=imatrix(1,lastpass-firstpass+2,1,imx);
12531: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 12532:
12533: /* Concatenates waves */
1.214 brouard 12534: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
12535: Death is a valid wave (if date is known).
12536: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
12537: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
12538: and mw[mi+1][i]. dh depends on stepm.
12539: */
12540:
1.126 brouard 12541: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 12542: /* Concatenates waves */
1.145 brouard 12543:
1.290 brouard 12544: free_vector(moisdc,firstobs,lastobs);
12545: free_vector(andc,firstobs,lastobs);
1.215 brouard 12546:
1.126 brouard 12547: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
12548: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
12549: ncodemax[1]=1;
1.145 brouard 12550: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 12551: cptcoveff=0;
1.220 brouard 12552: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
12553: tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; */
1.227 brouard 12554: }
12555:
12556: ncovcombmax=pow(2,cptcoveff);
12557: invalidvarcomb=ivector(1, ncovcombmax);
12558: for(i=1;i<ncovcombmax;i++)
12559: invalidvarcomb[i]=0;
12560:
1.211 brouard 12561: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 12562: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 12563: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 12564:
1.200 brouard 12565: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 12566: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 12567: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 12568: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
12569: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
12570: * (currently 0 or 1) in the data.
12571: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
12572: * corresponding modality (h,j).
12573: */
12574:
1.145 brouard 12575: h=0;
12576: /*if (cptcovn > 0) */
1.126 brouard 12577: m=pow(2,cptcoveff);
12578:
1.144 brouard 12579: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 12580: * For k=4 covariates, h goes from 1 to m=2**k
12581: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
12582: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.329 brouard 12583: * h\k 1 2 3 4 * h-1\k-1 4 3 2 1
12584: *______________________________ *______________________
12585: * 1 i=1 1 i=1 1 i=1 1 i=1 1 * 0 0 0 0 0
12586: * 2 2 1 1 1 * 1 0 0 0 1
12587: * 3 i=2 1 2 1 1 * 2 0 0 1 0
12588: * 4 2 2 1 1 * 3 0 0 1 1
12589: * 5 i=3 1 i=2 1 2 1 * 4 0 1 0 0
12590: * 6 2 1 2 1 * 5 0 1 0 1
12591: * 7 i=4 1 2 2 1 * 6 0 1 1 0
12592: * 8 2 2 2 1 * 7 0 1 1 1
12593: * 9 i=5 1 i=3 1 i=2 1 2 * 8 1 0 0 0
12594: * 10 2 1 1 2 * 9 1 0 0 1
12595: * 11 i=6 1 2 1 2 * 10 1 0 1 0
12596: * 12 2 2 1 2 * 11 1 0 1 1
12597: * 13 i=7 1 i=4 1 2 2 * 12 1 1 0 0
12598: * 14 2 1 2 2 * 13 1 1 0 1
12599: * 15 i=8 1 2 2 2 * 14 1 1 1 0
12600: * 16 2 2 2 2 * 15 1 1 1 1
12601: */
1.212 brouard 12602: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 12603: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
12604: * and the value of each covariate?
12605: * V1=1, V2=1, V3=2, V4=1 ?
12606: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
12607: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
12608: * In order to get the real value in the data, we use nbcode
12609: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
12610: * We are keeping this crazy system in order to be able (in the future?)
12611: * to have more than 2 values (0 or 1) for a covariate.
12612: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
12613: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
12614: * bbbbbbbb
12615: * 76543210
12616: * h-1 00000101 (6-1=5)
1.219 brouard 12617: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 12618: * &
12619: * 1 00000001 (1)
1.219 brouard 12620: * 00000000 = 1 & ((h-1) >> (k-1))
12621: * +1= 00000001 =1
1.211 brouard 12622: *
12623: * h=14, k=3 => h'=h-1=13, k'=k-1=2
12624: * h' 1101 =2^3+2^2+0x2^1+2^0
12625: * >>k' 11
12626: * & 00000001
12627: * = 00000001
12628: * +1 = 00000010=2 = codtabm(14,3)
12629: * Reverse h=6 and m=16?
12630: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
12631: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
12632: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
12633: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
12634: * V3=decodtabm(14,3,2**4)=2
12635: * h'=13 1101 =2^3+2^2+0x2^1+2^0
12636: *(h-1) >> (j-1) 0011 =13 >> 2
12637: * &1 000000001
12638: * = 000000001
12639: * +1= 000000010 =2
12640: * 2211
12641: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
12642: * V3=2
1.220 brouard 12643: * codtabm and decodtabm are identical
1.211 brouard 12644: */
12645:
1.145 brouard 12646:
12647: free_ivector(Ndum,-1,NCOVMAX);
12648:
12649:
1.126 brouard 12650:
1.186 brouard 12651: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 12652: strcpy(optionfilegnuplot,optionfilefiname);
12653: if(mle==-3)
1.201 brouard 12654: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 12655: strcat(optionfilegnuplot,".gp");
12656:
12657: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
12658: printf("Problem with file %s",optionfilegnuplot);
12659: }
12660: else{
1.204 brouard 12661: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 12662: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 12663: //fprintf(ficgp,"set missing 'NaNq'\n");
12664: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 12665: }
12666: /* fclose(ficgp);*/
1.186 brouard 12667:
12668:
12669: /* Initialisation of --------- index.htm --------*/
1.126 brouard 12670:
12671: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
12672: if(mle==-3)
1.201 brouard 12673: strcat(optionfilehtm,"-MORT_");
1.126 brouard 12674: strcat(optionfilehtm,".htm");
12675: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 12676: printf("Problem with %s \n",optionfilehtm);
12677: exit(0);
1.126 brouard 12678: }
12679:
12680: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
12681: strcat(optionfilehtmcov,"-cov.htm");
12682: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
12683: printf("Problem with %s \n",optionfilehtmcov), exit(0);
12684: }
12685: else{
12686: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
12687: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 12688: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 12689: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
12690: }
12691:
1.332 brouard 12692: fprintf(fichtm,"<html><head>\n<head>\n<meta charset=\"utf-8\"/><meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n<title>IMaCh %s</title></head>\n <body><font size=\"7\"><a href=http:/euroreves.ined.fr/imach>IMaCh for Interpolated Markov Chain</a> </font><br>\n<font size=\"3\">Sponsored by Copyright (C) 2002-2015 <a href=http://www.ined.fr>INED</a>-EUROREVES-Institut de longévité-2013-2022-Japan Society for the Promotion of Sciences 日本学術振興会 (<a href=https://www.jsps.go.jp/english/e-grants/>Grant-in-Aid for Scientific Research 25293121</a>) - <a href=https://software.intel.com/en-us>Intel Software 2015-2018</a></font><br> \
1.204 brouard 12693: <hr size=\"2\" color=\"#EC5E5E\"> \n\
12694: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 12695: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 12696: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\
1.126 brouard 12697: \n\
12698: <hr size=\"2\" color=\"#EC5E5E\">\
12699: <ul><li><h4>Parameter files</h4>\n\
12700: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
12701: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
12702: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
12703: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
12704: - Date and time at start: %s</ul>\n",\
12705: optionfilehtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model,\
12706: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
12707: fileres,fileres,\
12708: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
12709: fflush(fichtm);
12710:
12711: strcpy(pathr,path);
12712: strcat(pathr,optionfilefiname);
1.184 brouard 12713: #ifdef WIN32
12714: _chdir(optionfilefiname); /* Move to directory named optionfile */
12715: #else
1.126 brouard 12716: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 12717: #endif
12718:
1.126 brouard 12719:
1.220 brouard 12720: /* Calculates basic frequencies. Computes observed prevalence at single age
12721: and for any valid combination of covariates
1.126 brouard 12722: and prints on file fileres'p'. */
1.251 brouard 12723: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 12724: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 12725:
12726: fprintf(fichtm,"\n");
1.286 brouard 12727: 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 12728: ftol, stepm);
12729: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
12730: ncurrv=1;
12731: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
12732: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
12733: ncurrv=i;
12734: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 12735: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 12736: ncurrv=i;
12737: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 12738: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 12739: ncurrv=i;
12740: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
12741: 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", \
12742: nlstate, ndeath, maxwav, mle, weightopt);
12743:
12744: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
12745: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
12746:
12747:
1.317 brouard 12748: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Number of (used) observations=%d <br>\n\
1.126 brouard 12749: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
12750: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 12751: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 12752: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 12753: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
12754: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
12755: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
12756: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 12757:
1.126 brouard 12758: /* For Powell, parameters are in a vector p[] starting at p[1]
12759: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
12760: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
12761:
12762: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 12763: /* For mortality only */
1.126 brouard 12764: if (mle==-3){
1.136 brouard 12765: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 12766: for(i=1;i<=NDIM;i++)
12767: for(j=1;j<=NDIM;j++)
12768: ximort[i][j]=0.;
1.186 brouard 12769: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 12770: cens=ivector(firstobs,lastobs);
12771: ageexmed=vector(firstobs,lastobs);
12772: agecens=vector(firstobs,lastobs);
12773: dcwave=ivector(firstobs,lastobs);
1.223 brouard 12774:
1.126 brouard 12775: for (i=1; i<=imx; i++){
12776: dcwave[i]=-1;
12777: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 12778: if (s[m][i]>nlstate) {
12779: dcwave[i]=m;
12780: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
12781: break;
12782: }
1.126 brouard 12783: }
1.226 brouard 12784:
1.126 brouard 12785: for (i=1; i<=imx; i++) {
12786: if (wav[i]>0){
1.226 brouard 12787: ageexmed[i]=agev[mw[1][i]][i];
12788: j=wav[i];
12789: agecens[i]=1.;
12790:
12791: if (ageexmed[i]> 1 && wav[i] > 0){
12792: agecens[i]=agev[mw[j][i]][i];
12793: cens[i]= 1;
12794: }else if (ageexmed[i]< 1)
12795: cens[i]= -1;
12796: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
12797: cens[i]=0 ;
1.126 brouard 12798: }
12799: else cens[i]=-1;
12800: }
12801:
12802: for (i=1;i<=NDIM;i++) {
12803: for (j=1;j<=NDIM;j++)
1.226 brouard 12804: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 12805: }
12806:
1.302 brouard 12807: p[1]=0.0268; p[NDIM]=0.083;
12808: /* printf("%lf %lf", p[1], p[2]); */
1.126 brouard 12809:
12810:
1.136 brouard 12811: #ifdef GSL
12812: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 12813: #else
1.126 brouard 12814: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 12815: #endif
1.201 brouard 12816: strcpy(filerespow,"POW-MORT_");
12817: strcat(filerespow,fileresu);
1.126 brouard 12818: if((ficrespow=fopen(filerespow,"w"))==NULL) {
12819: printf("Problem with resultfile: %s\n", filerespow);
12820: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
12821: }
1.136 brouard 12822: #ifdef GSL
12823: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 12824: #else
1.126 brouard 12825: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 12826: #endif
1.126 brouard 12827: /* for (i=1;i<=nlstate;i++)
12828: for(j=1;j<=nlstate+ndeath;j++)
12829: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
12830: */
12831: fprintf(ficrespow,"\n");
1.136 brouard 12832: #ifdef GSL
12833: /* gsl starts here */
12834: T = gsl_multimin_fminimizer_nmsimplex;
12835: gsl_multimin_fminimizer *sfm = NULL;
12836: gsl_vector *ss, *x;
12837: gsl_multimin_function minex_func;
12838:
12839: /* Initial vertex size vector */
12840: ss = gsl_vector_alloc (NDIM);
12841:
12842: if (ss == NULL){
12843: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
12844: }
12845: /* Set all step sizes to 1 */
12846: gsl_vector_set_all (ss, 0.001);
12847:
12848: /* Starting point */
1.126 brouard 12849:
1.136 brouard 12850: x = gsl_vector_alloc (NDIM);
12851:
12852: if (x == NULL){
12853: gsl_vector_free(ss);
12854: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
12855: }
12856:
12857: /* Initialize method and iterate */
12858: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 12859: /* gsl_vector_set(x, 0, 0.0268); */
12860: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 12861: gsl_vector_set(x, 0, p[1]);
12862: gsl_vector_set(x, 1, p[2]);
12863:
12864: minex_func.f = &gompertz_f;
12865: minex_func.n = NDIM;
12866: minex_func.params = (void *)&p; /* ??? */
12867:
12868: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
12869: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
12870:
12871: printf("Iterations beginning .....\n\n");
12872: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
12873:
12874: iteri=0;
12875: while (rval == GSL_CONTINUE){
12876: iteri++;
12877: status = gsl_multimin_fminimizer_iterate(sfm);
12878:
12879: if (status) printf("error: %s\n", gsl_strerror (status));
12880: fflush(0);
12881:
12882: if (status)
12883: break;
12884:
12885: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
12886: ssval = gsl_multimin_fminimizer_size (sfm);
12887:
12888: if (rval == GSL_SUCCESS)
12889: printf ("converged to a local maximum at\n");
12890:
12891: printf("%5d ", iteri);
12892: for (it = 0; it < NDIM; it++){
12893: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
12894: }
12895: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
12896: }
12897:
12898: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
12899:
12900: gsl_vector_free(x); /* initial values */
12901: gsl_vector_free(ss); /* inital step size */
12902: for (it=0; it<NDIM; it++){
12903: p[it+1]=gsl_vector_get(sfm->x,it);
12904: fprintf(ficrespow," %.12lf", p[it]);
12905: }
12906: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
12907: #endif
12908: #ifdef POWELL
12909: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
12910: #endif
1.126 brouard 12911: fclose(ficrespow);
12912:
1.203 brouard 12913: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 12914:
12915: for(i=1; i <=NDIM; i++)
12916: for(j=i+1;j<=NDIM;j++)
1.220 brouard 12917: matcov[i][j]=matcov[j][i];
1.126 brouard 12918:
12919: printf("\nCovariance matrix\n ");
1.203 brouard 12920: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 12921: for(i=1; i <=NDIM; i++) {
12922: for(j=1;j<=NDIM;j++){
1.220 brouard 12923: printf("%f ",matcov[i][j]);
12924: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 12925: }
1.203 brouard 12926: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 12927: }
12928:
12929: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 12930: for (i=1;i<=NDIM;i++) {
1.126 brouard 12931: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 12932: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
12933: }
1.302 brouard 12934: lsurv=vector(agegomp,AGESUP);
12935: lpop=vector(agegomp,AGESUP);
12936: tpop=vector(agegomp,AGESUP);
1.126 brouard 12937: lsurv[agegomp]=100000;
12938:
12939: for (k=agegomp;k<=AGESUP;k++) {
12940: agemortsup=k;
12941: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
12942: }
12943:
12944: for (k=agegomp;k<agemortsup;k++)
12945: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
12946:
12947: for (k=agegomp;k<agemortsup;k++){
12948: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
12949: sumlpop=sumlpop+lpop[k];
12950: }
12951:
12952: tpop[agegomp]=sumlpop;
12953: for (k=agegomp;k<(agemortsup-3);k++){
12954: /* tpop[k+1]=2;*/
12955: tpop[k+1]=tpop[k]-lpop[k];
12956: }
12957:
12958:
12959: printf("\nAge lx qx dx Lx Tx e(x)\n");
12960: for (k=agegomp;k<(agemortsup-2);k++)
12961: 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]);
12962:
12963:
12964: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 12965: ageminpar=50;
12966: agemaxpar=100;
1.194 brouard 12967: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
12968: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
12969: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12970: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
12971: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
12972: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12973: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 12974: }else{
12975: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
12976: 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 12977: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 12978: }
1.201 brouard 12979: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 12980: stepm, weightopt,\
12981: model,imx,p,matcov,agemortsup);
12982:
1.302 brouard 12983: free_vector(lsurv,agegomp,AGESUP);
12984: free_vector(lpop,agegomp,AGESUP);
12985: free_vector(tpop,agegomp,AGESUP);
1.220 brouard 12986: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 12987: free_ivector(dcwave,firstobs,lastobs);
12988: free_vector(agecens,firstobs,lastobs);
12989: free_vector(ageexmed,firstobs,lastobs);
12990: free_ivector(cens,firstobs,lastobs);
1.220 brouard 12991: #ifdef GSL
1.136 brouard 12992: #endif
1.186 brouard 12993: } /* Endof if mle==-3 mortality only */
1.205 brouard 12994: /* Standard */
12995: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
12996: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
12997: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 12998: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 12999: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
13000: for (k=1; k<=npar;k++)
13001: printf(" %d %8.5f",k,p[k]);
13002: printf("\n");
1.205 brouard 13003: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
13004: /* mlikeli uses func not funcone */
1.247 brouard 13005: /* for(i=1;i<nlstate;i++){ */
13006: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
13007: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
13008: /* } */
1.205 brouard 13009: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
13010: }
13011: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
13012: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
13013: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
13014: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
13015: }
13016: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 13017: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
13018: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
13019: for (k=1; k<=npar;k++)
13020: printf(" %d %8.5f",k,p[k]);
13021: printf("\n");
13022:
13023: /*--------- results files --------------*/
1.283 brouard 13024: /* 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 13025:
13026:
13027: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 13028: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); /* Printing model equation */
1.126 brouard 13029: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 13030:
13031: printf("#model= 1 + age ");
13032: fprintf(ficres,"#model= 1 + age ");
13033: fprintf(ficlog,"#model= 1 + age ");
13034: fprintf(fichtm,"\n<ul><li> model=1+age+%s\n \
13035: </ul>", model);
13036:
13037: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">\n");
13038: fprintf(fichtm, "<tr><th>Model=</th><th>1</th><th>+ age</th>");
13039: if(nagesqr==1){
13040: printf(" + age*age ");
13041: fprintf(ficres," + age*age ");
13042: fprintf(ficlog," + age*age ");
13043: fprintf(fichtm, "<th>+ age*age</th>");
13044: }
13045: for(j=1;j <=ncovmodel-2;j++){
13046: if(Typevar[j]==0) {
13047: printf(" + V%d ",Tvar[j]);
13048: fprintf(ficres," + V%d ",Tvar[j]);
13049: fprintf(ficlog," + V%d ",Tvar[j]);
13050: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
13051: }else if(Typevar[j]==1) {
13052: printf(" + V%d*age ",Tvar[j]);
13053: fprintf(ficres," + V%d*age ",Tvar[j]);
13054: fprintf(ficlog," + V%d*age ",Tvar[j]);
13055: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
13056: }else if(Typevar[j]==2) {
13057: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13058: fprintf(ficres," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13059: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13060: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13061: }
13062: }
13063: printf("\n");
13064: fprintf(ficres,"\n");
13065: fprintf(ficlog,"\n");
13066: fprintf(fichtm, "</tr>");
13067: fprintf(fichtm, "\n");
13068:
13069:
1.126 brouard 13070: for(i=1,jk=1; i <=nlstate; i++){
13071: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 13072: if (k != i) {
1.319 brouard 13073: fprintf(fichtm, "<tr>");
1.225 brouard 13074: printf("%d%d ",i,k);
13075: fprintf(ficlog,"%d%d ",i,k);
13076: fprintf(ficres,"%1d%1d ",i,k);
1.319 brouard 13077: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 13078: for(j=1; j <=ncovmodel; j++){
13079: printf("%12.7f ",p[jk]);
13080: fprintf(ficlog,"%12.7f ",p[jk]);
13081: fprintf(ficres,"%12.7f ",p[jk]);
1.319 brouard 13082: fprintf(fichtm, "<td>%12.7f</td>",p[jk]);
1.225 brouard 13083: jk++;
13084: }
13085: printf("\n");
13086: fprintf(ficlog,"\n");
13087: fprintf(ficres,"\n");
1.319 brouard 13088: fprintf(fichtm, "</tr>\n");
1.225 brouard 13089: }
1.126 brouard 13090: }
13091: }
1.319 brouard 13092: /* fprintf(fichtm,"</tr>\n"); */
13093: fprintf(fichtm,"</table>\n");
13094: fprintf(fichtm, "\n");
13095:
1.203 brouard 13096: if(mle != 0){
13097: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 13098: ftolhess=ftol; /* Usually correct */
1.203 brouard 13099: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
13100: 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");
13101: 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 13102: 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 13103: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">");
13104: fprintf(fichtm, "\n<tr><th>Model=</th><th>1</th><th>+ age</th>");
13105: if(nagesqr==1){
13106: printf(" + age*age ");
13107: fprintf(ficres," + age*age ");
13108: fprintf(ficlog," + age*age ");
13109: fprintf(fichtm, "<th>+ age*age</th>");
13110: }
13111: for(j=1;j <=ncovmodel-2;j++){
13112: if(Typevar[j]==0) {
13113: printf(" + V%d ",Tvar[j]);
13114: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
13115: }else if(Typevar[j]==1) {
13116: printf(" + V%d*age ",Tvar[j]);
13117: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
13118: }else if(Typevar[j]==2) {
13119: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13120: }
13121: }
13122: fprintf(fichtm, "</tr>\n");
13123:
1.203 brouard 13124: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 13125: for(k=1; k <=(nlstate+ndeath); k++){
13126: if (k != i) {
1.319 brouard 13127: fprintf(fichtm, "<tr valign=top>");
1.225 brouard 13128: printf("%d%d ",i,k);
13129: fprintf(ficlog,"%d%d ",i,k);
1.319 brouard 13130: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 13131: for(j=1; j <=ncovmodel; j++){
1.319 brouard 13132: wald=p[jk]/sqrt(matcov[jk][jk]);
1.324 brouard 13133: 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]));
13134: 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 13135: if(fabs(wald) > 1.96){
1.321 brouard 13136: fprintf(fichtm, "<td><b>%12.7f</b></br> (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
1.319 brouard 13137: }else{
13138: fprintf(fichtm, "<td>%12.7f (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
13139: }
1.324 brouard 13140: fprintf(fichtm,"W=%8.3f</br>",wald);
1.319 brouard 13141: 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 13142: jk++;
13143: }
13144: printf("\n");
13145: fprintf(ficlog,"\n");
1.319 brouard 13146: fprintf(fichtm, "</tr>\n");
1.225 brouard 13147: }
13148: }
1.193 brouard 13149: }
1.203 brouard 13150: } /* end of hesscov and Wald tests */
1.319 brouard 13151: fprintf(fichtm,"</table>\n");
1.225 brouard 13152:
1.203 brouard 13153: /* */
1.126 brouard 13154: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
13155: printf("# Scales (for hessian or gradient estimation)\n");
13156: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
13157: for(i=1,jk=1; i <=nlstate; i++){
13158: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 13159: if (j!=i) {
13160: fprintf(ficres,"%1d%1d",i,j);
13161: printf("%1d%1d",i,j);
13162: fprintf(ficlog,"%1d%1d",i,j);
13163: for(k=1; k<=ncovmodel;k++){
13164: printf(" %.5e",delti[jk]);
13165: fprintf(ficlog," %.5e",delti[jk]);
13166: fprintf(ficres," %.5e",delti[jk]);
13167: jk++;
13168: }
13169: printf("\n");
13170: fprintf(ficlog,"\n");
13171: fprintf(ficres,"\n");
13172: }
1.126 brouard 13173: }
13174: }
13175:
13176: 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");
1.203 brouard 13177: if(mle >= 1) /* To big for the screen */
1.126 brouard 13178: 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");
13179: 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");
13180: /* # 121 Var(a12)\n\ */
13181: /* # 122 Cov(b12,a12) Var(b12)\n\ */
13182: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
13183: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
13184: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
13185: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
13186: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
13187: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
13188:
13189:
13190: /* Just to have a covariance matrix which will be more understandable
13191: even is we still don't want to manage dictionary of variables
13192: */
13193: for(itimes=1;itimes<=2;itimes++){
13194: jj=0;
13195: for(i=1; i <=nlstate; i++){
1.225 brouard 13196: for(j=1; j <=nlstate+ndeath; j++){
13197: if(j==i) continue;
13198: for(k=1; k<=ncovmodel;k++){
13199: jj++;
13200: ca[0]= k+'a'-1;ca[1]='\0';
13201: if(itimes==1){
13202: if(mle>=1)
13203: printf("#%1d%1d%d",i,j,k);
13204: fprintf(ficlog,"#%1d%1d%d",i,j,k);
13205: fprintf(ficres,"#%1d%1d%d",i,j,k);
13206: }else{
13207: if(mle>=1)
13208: printf("%1d%1d%d",i,j,k);
13209: fprintf(ficlog,"%1d%1d%d",i,j,k);
13210: fprintf(ficres,"%1d%1d%d",i,j,k);
13211: }
13212: ll=0;
13213: for(li=1;li <=nlstate; li++){
13214: for(lj=1;lj <=nlstate+ndeath; lj++){
13215: if(lj==li) continue;
13216: for(lk=1;lk<=ncovmodel;lk++){
13217: ll++;
13218: if(ll<=jj){
13219: cb[0]= lk +'a'-1;cb[1]='\0';
13220: if(ll<jj){
13221: if(itimes==1){
13222: if(mle>=1)
13223: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
13224: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
13225: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
13226: }else{
13227: if(mle>=1)
13228: printf(" %.5e",matcov[jj][ll]);
13229: fprintf(ficlog," %.5e",matcov[jj][ll]);
13230: fprintf(ficres," %.5e",matcov[jj][ll]);
13231: }
13232: }else{
13233: if(itimes==1){
13234: if(mle>=1)
13235: printf(" Var(%s%1d%1d)",ca,i,j);
13236: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
13237: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
13238: }else{
13239: if(mle>=1)
13240: printf(" %.7e",matcov[jj][ll]);
13241: fprintf(ficlog," %.7e",matcov[jj][ll]);
13242: fprintf(ficres," %.7e",matcov[jj][ll]);
13243: }
13244: }
13245: }
13246: } /* end lk */
13247: } /* end lj */
13248: } /* end li */
13249: if(mle>=1)
13250: printf("\n");
13251: fprintf(ficlog,"\n");
13252: fprintf(ficres,"\n");
13253: numlinepar++;
13254: } /* end k*/
13255: } /*end j */
1.126 brouard 13256: } /* end i */
13257: } /* end itimes */
13258:
13259: fflush(ficlog);
13260: fflush(ficres);
1.225 brouard 13261: while(fgets(line, MAXLINE, ficpar)) {
13262: /* If line starts with a # it is a comment */
13263: if (line[0] == '#') {
13264: numlinepar++;
13265: fputs(line,stdout);
13266: fputs(line,ficparo);
13267: fputs(line,ficlog);
1.299 brouard 13268: fputs(line,ficres);
1.225 brouard 13269: continue;
13270: }else
13271: break;
13272: }
13273:
1.209 brouard 13274: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
13275: /* ungetc(c,ficpar); */
13276: /* fgets(line, MAXLINE, ficpar); */
13277: /* fputs(line,stdout); */
13278: /* fputs(line,ficparo); */
13279: /* } */
13280: /* ungetc(c,ficpar); */
1.126 brouard 13281:
13282: estepm=0;
1.209 brouard 13283: 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 13284:
13285: if (num_filled != 6) {
13286: 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);
13287: 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);
13288: goto end;
13289: }
13290: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
13291: }
13292: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
13293: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
13294:
1.209 brouard 13295: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 13296: if (estepm==0 || estepm < stepm) estepm=stepm;
13297: if (fage <= 2) {
13298: bage = ageminpar;
13299: fage = agemaxpar;
13300: }
13301:
13302: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 13303: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
13304: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 13305:
1.186 brouard 13306: /* Other stuffs, more or less useful */
1.254 brouard 13307: while(fgets(line, MAXLINE, ficpar)) {
13308: /* If line starts with a # it is a comment */
13309: if (line[0] == '#') {
13310: numlinepar++;
13311: fputs(line,stdout);
13312: fputs(line,ficparo);
13313: fputs(line,ficlog);
1.299 brouard 13314: fputs(line,ficres);
1.254 brouard 13315: continue;
13316: }else
13317: break;
13318: }
13319:
13320: 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){
13321:
13322: if (num_filled != 7) {
13323: 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);
13324: 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);
13325: goto end;
13326: }
13327: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
13328: 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);
13329: 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);
13330: 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 13331: }
1.254 brouard 13332:
13333: while(fgets(line, MAXLINE, ficpar)) {
13334: /* If line starts with a # it is a comment */
13335: if (line[0] == '#') {
13336: numlinepar++;
13337: fputs(line,stdout);
13338: fputs(line,ficparo);
13339: fputs(line,ficlog);
1.299 brouard 13340: fputs(line,ficres);
1.254 brouard 13341: continue;
13342: }else
13343: break;
1.126 brouard 13344: }
13345:
13346:
13347: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
13348: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
13349:
1.254 brouard 13350: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
13351: if (num_filled != 1) {
13352: 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);
13353: 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);
13354: goto end;
13355: }
13356: printf("pop_based=%d\n",popbased);
13357: fprintf(ficlog,"pop_based=%d\n",popbased);
13358: fprintf(ficparo,"pop_based=%d\n",popbased);
13359: fprintf(ficres,"pop_based=%d\n",popbased);
13360: }
13361:
1.258 brouard 13362: /* Results */
1.332 brouard 13363: /* Value of covariate in each resultine will be compututed (if product) and sorted according to model rank */
13364: /* It is precov[] because we need the varying age in order to compute the real cov[] of the model equation */
13365: precov=matrix(1,MAXRESULTLINESPONE,1,NCOVMAX+1);
1.307 brouard 13366: endishere=0;
1.258 brouard 13367: nresult=0;
1.308 brouard 13368: parameterline=0;
1.258 brouard 13369: do{
13370: if(!fgets(line, MAXLINE, ficpar)){
13371: endishere=1;
1.308 brouard 13372: parameterline=15;
1.258 brouard 13373: }else if (line[0] == '#') {
13374: /* If line starts with a # it is a comment */
1.254 brouard 13375: numlinepar++;
13376: fputs(line,stdout);
13377: fputs(line,ficparo);
13378: fputs(line,ficlog);
1.299 brouard 13379: fputs(line,ficres);
1.254 brouard 13380: continue;
1.258 brouard 13381: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
13382: parameterline=11;
1.296 brouard 13383: else if(sscanf(line,"prevbackcast=%[^\n]\n",modeltemp))
1.258 brouard 13384: parameterline=12;
1.307 brouard 13385: else if(sscanf(line,"result:%[^\n]\n",modeltemp)){
1.258 brouard 13386: parameterline=13;
1.307 brouard 13387: }
1.258 brouard 13388: else{
13389: parameterline=14;
1.254 brouard 13390: }
1.308 brouard 13391: switch (parameterline){ /* =0 only if only comments */
1.258 brouard 13392: case 11:
1.296 brouard 13393: 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)){
13394: 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 13395: 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);
13396: 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);
13397: 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);
13398: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 13399: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
13400: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
1.296 brouard 13401: prvforecast = 1;
13402: }
13403: else if((num_filled=sscanf(line,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",&prevfcast,&yrfproj,&mobilavproj)) !=EOF){/* && (num_filled == 3))*/
1.313 brouard 13404: printf("prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
13405: fprintf(ficlog,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
13406: fprintf(ficres,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
1.296 brouard 13407: prvforecast = 2;
13408: }
13409: else {
13410: 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);
13411: 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);
13412: goto end;
1.258 brouard 13413: }
1.254 brouard 13414: break;
1.258 brouard 13415: case 12:
1.296 brouard 13416: 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)){
13417: 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);
13418: 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);
13419: 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);
13420: 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);
13421: /* day and month of back2 are not used but only year anback2.*/
1.273 brouard 13422: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
13423: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.296 brouard 13424: prvbackcast = 1;
13425: }
13426: else if((num_filled=sscanf(line,"prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",&prevbcast,&yrbproj,&mobilavproj)) ==3){/* && (num_filled == 3))*/
1.313 brouard 13427: printf("prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
13428: fprintf(ficlog,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
13429: fprintf(ficres,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
1.296 brouard 13430: prvbackcast = 2;
13431: }
13432: else {
13433: 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);
13434: 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);
13435: goto end;
1.258 brouard 13436: }
1.230 brouard 13437: break;
1.258 brouard 13438: case 13:
1.332 brouard 13439: num_filled=sscanf(line,"result:%[^\n]\n",resultlineori);
1.307 brouard 13440: nresult++; /* Sum of resultlines */
1.332 brouard 13441: printf("Result %d: result:%s\n",nresult, resultlineori);
13442: /* removefirstspace(&resultlineori); */
13443:
13444: if(strstr(resultlineori,"v") !=0){
13445: printf("Error. 'v' must be in upper case 'V' result: %s ",resultlineori);
13446: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultlineori);fflush(ficlog);
13447: return 1;
13448: }
13449: trimbb(resultline, resultlineori); /* Suppressing double blank in the resultline */
13450: printf("Decoderesult resultline=\"%s\" resultlineori=\"%s\"\n", resultline, resultlineori);
1.318 brouard 13451: if(nresult > MAXRESULTLINESPONE-1){
13452: 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);
13453: 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 13454: goto end;
13455: }
1.332 brouard 13456:
1.310 brouard 13457: if(!decoderesult(resultline, nresult)){ /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
1.314 brouard 13458: fprintf(ficparo,"result: %s\n",resultline);
13459: fprintf(ficres,"result: %s\n",resultline);
13460: fprintf(ficlog,"result: %s\n",resultline);
1.310 brouard 13461: } else
13462: goto end;
1.307 brouard 13463: break;
13464: case 14:
13465: printf("Error: Unknown command '%s'\n",line);
13466: fprintf(ficlog,"Error: Unknown command '%s'\n",line);
1.314 brouard 13467: if(line[0] == ' ' || line[0] == '\n'){
13468: printf("It should not be an empty line '%s'\n",line);
13469: fprintf(ficlog,"It should not be an empty line '%s'\n",line);
13470: }
1.307 brouard 13471: if(ncovmodel >=2 && nresult==0 ){
13472: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
13473: fprintf(ficlog,"ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 13474: }
1.307 brouard 13475: /* goto end; */
13476: break;
1.308 brouard 13477: case 15:
13478: printf("End of resultlines.\n");
13479: fprintf(ficlog,"End of resultlines.\n");
13480: break;
13481: default: /* parameterline =0 */
1.307 brouard 13482: nresult=1;
13483: decoderesult(".",nresult ); /* No covariate */
1.258 brouard 13484: } /* End switch parameterline */
13485: }while(endishere==0); /* End do */
1.126 brouard 13486:
1.230 brouard 13487: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 13488: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 13489:
13490: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 13491: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 13492: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 13493: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
13494: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 13495: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 13496: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
13497: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 13498: }else{
1.270 brouard 13499: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
1.296 brouard 13500: /* It seems that anprojd which is computed from the mean year at interview which is known yet because of freqsummary */
13501: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */ /* Done in freqsummary */
13502: if(prvforecast==1){
13503: dateprojd=(jproj1+12*mproj1+365*anproj1)/365;
13504: jprojd=jproj1;
13505: mprojd=mproj1;
13506: anprojd=anproj1;
13507: dateprojf=(jproj2+12*mproj2+365*anproj2)/365;
13508: jprojf=jproj2;
13509: mprojf=mproj2;
13510: anprojf=anproj2;
13511: } else if(prvforecast == 2){
13512: dateprojd=dateintmean;
13513: date2dmy(dateprojd,&jprojd, &mprojd, &anprojd);
13514: dateprojf=dateintmean+yrfproj;
13515: date2dmy(dateprojf,&jprojf, &mprojf, &anprojf);
13516: }
13517: if(prvbackcast==1){
13518: datebackd=(jback1+12*mback1+365*anback1)/365;
13519: jbackd=jback1;
13520: mbackd=mback1;
13521: anbackd=anback1;
13522: datebackf=(jback2+12*mback2+365*anback2)/365;
13523: jbackf=jback2;
13524: mbackf=mback2;
13525: anbackf=anback2;
13526: } else if(prvbackcast == 2){
13527: datebackd=dateintmean;
13528: date2dmy(datebackd,&jbackd, &mbackd, &anbackd);
13529: datebackf=dateintmean-yrbproj;
13530: date2dmy(datebackf,&jbackf, &mbackf, &anbackf);
13531: }
13532:
13533: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage);
1.220 brouard 13534: }
13535: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.296 brouard 13536: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,prevbcast, estepm, \
13537: jprev1,mprev1,anprev1,dateprev1, dateprojd, datebackd,jprev2,mprev2,anprev2,dateprev2,dateprojf, datebackf);
1.220 brouard 13538:
1.225 brouard 13539: /*------------ free_vector -------------*/
13540: /* chdir(path); */
1.220 brouard 13541:
1.215 brouard 13542: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
13543: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
13544: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
13545: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 13546: free_lvector(num,firstobs,lastobs);
13547: free_vector(agedc,firstobs,lastobs);
1.126 brouard 13548: /*free_matrix(covar,0,NCOVMAX,1,n);*/
13549: /*free_matrix(covar,1,NCOVMAX,1,n);*/
13550: fclose(ficparo);
13551: fclose(ficres);
1.220 brouard 13552:
13553:
1.186 brouard 13554: /* Other results (useful)*/
1.220 brouard 13555:
13556:
1.126 brouard 13557: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 13558: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
13559: prlim=matrix(1,nlstate,1,nlstate);
1.332 brouard 13560: /* Computes the prevalence limit for each combination k of the dummy covariates by calling prevalim(k) */
1.209 brouard 13561: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 13562: fclose(ficrespl);
13563:
13564: /*------------- h Pij x at various ages ------------*/
1.180 brouard 13565: /*#include "hpijx.h"*/
1.332 brouard 13566: /** 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?*/
13567: /* calls hpxij with combination k */
1.180 brouard 13568: hPijx(p, bage, fage);
1.145 brouard 13569: fclose(ficrespij);
1.227 brouard 13570:
1.220 brouard 13571: /* ncovcombmax= pow(2,cptcoveff); */
1.332 brouard 13572: /*-------------- Variance of one-step probabilities for a combination ij or for nres ?---*/
1.145 brouard 13573: k=1;
1.126 brouard 13574: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 13575:
1.269 brouard 13576: /* Prevalence for each covariate combination in probs[age][status][cov] */
13577: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
13578: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 13579: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 13580: for(k=1;k<=ncovcombmax;k++)
13581: probs[i][j][k]=0.;
1.269 brouard 13582: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
13583: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 13584: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 13585: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
13586: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 13587: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 13588: for(k=1;k<=ncovcombmax;k++)
13589: mobaverages[i][j][k]=0.;
1.219 brouard 13590: mobaverage=mobaverages;
13591: if (mobilav!=0) {
1.235 brouard 13592: printf("Movingaveraging observed prevalence\n");
1.258 brouard 13593: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 13594: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
13595: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
13596: printf(" Error in movingaverage mobilav=%d\n",mobilav);
13597: }
1.269 brouard 13598: } else if (mobilavproj !=0) {
1.235 brouard 13599: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 13600: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 13601: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
13602: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
13603: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
13604: }
1.269 brouard 13605: }else{
13606: printf("Internal error moving average\n");
13607: fflush(stdout);
13608: exit(1);
1.219 brouard 13609: }
13610: }/* end if moving average */
1.227 brouard 13611:
1.126 brouard 13612: /*---------- Forecasting ------------------*/
1.296 brouard 13613: if(prevfcast==1){
13614: /* /\* if(stepm ==1){*\/ */
13615: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
13616: /*This done previously after freqsummary.*/
13617: /* dateprojd=(jproj1+12*mproj1+365*anproj1)/365; */
13618: /* dateprojf=(jproj2+12*mproj2+365*anproj2)/365; */
13619:
13620: /* } else if (prvforecast==2){ */
13621: /* /\* if(stepm ==1){*\/ */
13622: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
13623: /* } */
13624: /*prevforecast(fileresu, dateintmean, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);*/
13625: prevforecast(fileresu,dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, p, cptcoveff);
1.126 brouard 13626: }
1.269 brouard 13627:
1.296 brouard 13628: /* Prevbcasting */
13629: if(prevbcast==1){
1.219 brouard 13630: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
13631: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
13632: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
13633:
13634: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
13635:
13636: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 13637:
1.219 brouard 13638: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
13639: fclose(ficresplb);
13640:
1.222 brouard 13641: hBijx(p, bage, fage, mobaverage);
13642: fclose(ficrespijb);
1.219 brouard 13643:
1.296 brouard 13644: /* /\* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, *\/ */
13645: /* /\* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); *\/ */
13646: /* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, */
13647: /* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
13648: prevbackforecast(fileresu, mobaverage, dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2,
13649: mobilavproj, bage, fage, firstpass, lastpass, p, cptcoveff);
13650:
13651:
1.269 brouard 13652: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 13653:
13654:
1.269 brouard 13655: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 13656: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
13657: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
13658: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.296 brouard 13659: } /* end Prevbcasting */
1.268 brouard 13660:
1.186 brouard 13661:
13662: /* ------ Other prevalence ratios------------ */
1.126 brouard 13663:
1.215 brouard 13664: free_ivector(wav,1,imx);
13665: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
13666: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
13667: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 13668:
13669:
1.127 brouard 13670: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 13671:
1.201 brouard 13672: strcpy(filerese,"E_");
13673: strcat(filerese,fileresu);
1.126 brouard 13674: if((ficreseij=fopen(filerese,"w"))==NULL) {
13675: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
13676: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
13677: }
1.208 brouard 13678: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
13679: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 13680:
13681: pstamp(ficreseij);
1.219 brouard 13682:
1.235 brouard 13683: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
13684: if (cptcovn < 1){i1=1;}
13685:
13686: for(nres=1; nres <= nresult; nres++) /* For each resultline */
13687: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 13688: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 13689: continue;
1.219 brouard 13690: fprintf(ficreseij,"\n#****** ");
1.235 brouard 13691: printf("\n#****** ");
1.225 brouard 13692: for(j=1;j<=cptcoveff;j++) {
1.332 brouard 13693: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
13694: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.235 brouard 13695: }
13696: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.334 ! brouard 13697: printf(" V%d=%f ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]); /* TvarsQ[j] gives the name of the jth quantitative (fixed or time v) */
! 13698: fprintf(ficreseij,"V%d=%f ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]);
1.219 brouard 13699: }
13700: fprintf(ficreseij,"******\n");
1.235 brouard 13701: printf("******\n");
1.219 brouard 13702:
13703: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
13704: oldm=oldms;savm=savms;
1.330 brouard 13705: /* 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 13706: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 13707:
1.219 brouard 13708: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 13709: }
13710: fclose(ficreseij);
1.208 brouard 13711: printf("done evsij\n");fflush(stdout);
13712: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 13713:
1.218 brouard 13714:
1.227 brouard 13715: /*---------- State-specific expectancies and variances ------------*/
1.218 brouard 13716:
1.201 brouard 13717: strcpy(filerest,"T_");
13718: strcat(filerest,fileresu);
1.127 brouard 13719: if((ficrest=fopen(filerest,"w"))==NULL) {
13720: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
13721: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
13722: }
1.208 brouard 13723: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
13724: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 13725: strcpy(fileresstde,"STDE_");
13726: strcat(fileresstde,fileresu);
1.126 brouard 13727: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 13728: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
13729: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 13730: }
1.227 brouard 13731: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
13732: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 13733:
1.201 brouard 13734: strcpy(filerescve,"CVE_");
13735: strcat(filerescve,fileresu);
1.126 brouard 13736: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 13737: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
13738: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 13739: }
1.227 brouard 13740: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
13741: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 13742:
1.201 brouard 13743: strcpy(fileresv,"V_");
13744: strcat(fileresv,fileresu);
1.126 brouard 13745: if((ficresvij=fopen(fileresv,"w"))==NULL) {
13746: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
13747: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
13748: }
1.227 brouard 13749: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
13750: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 13751:
1.235 brouard 13752: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
13753: if (cptcovn < 1){i1=1;}
13754:
1.334 ! brouard 13755: for(nres=1; nres <= nresult; nres++) /* For each resultline, find the combination and output results according to the values of dummies and then quanti. */
! 13756: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying. For each nres and each value at position k
! 13757: * we know Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline
! 13758: * Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline
! 13759: * and Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
! 13760: /* */
! 13761: 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 13762: continue;
1.321 brouard 13763: printf("\n# model %s \n#****** Result for:", model);
13764: fprintf(ficrest,"\n# model %s \n#****** Result for:", model);
13765: fprintf(ficlog,"\n# model %s \n#****** Result for:", model);
1.334 ! brouard 13766: /* It might not be a good idea to mix dummies and quantitative */
! 13767: /* 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 *\/ */
! 13768: 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 */
! 13769: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /\* Output by variables in the resultline *\/ */
! 13770: /* Tvaraff[j] is the name of the dummy variable in position j in the equation model:
! 13771: * Tvaraff[1]@9={4, 3, 0, 0, 0, 0, 0, 0, 0}, in model=V5+V4+V3+V4*V3+V5*age
! 13772: * (V5 is quanti) V4 and V3 are dummies
! 13773: * TnsdVar[4] is the position 1 and TnsdVar[3]=2 in codtabm(k,l)(V4 V3)=V4 V3
! 13774: * l=1 l=2
! 13775: * k=1 1 1 0 0
! 13776: * k=2 2 1 1 0
! 13777: * k=3 [1] [2] 0 1
! 13778: * k=4 2 2 1 1
! 13779: * If nres=1 result: V3=1 V4=0 then k=3 and outputs
! 13780: * If nres=2 result: V4=1 V3=0 then k=2 and outputs
! 13781: * nres=1 =>k=3 j=1 V4= nbcode[4][codtabm(3,1)=1)=0; j=2 V3= nbcode[3][codtabm(3,2)=2]=1
! 13782: * nres=2 =>k=2 j=1 V4= nbcode[4][codtabm(2,1)=2)=1; j=2 V3= nbcode[3][codtabm(2,2)=1]=0
! 13783: */
! 13784: /* Tvresult[nres][j] Name of the variable at position j in this resultline */
! 13785: /* Tresult[nres][j] Value of this variable at position j could be a float if quantitative */
! 13786: /* We give up with the combinations!! */
! 13787: 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 */
! 13788:
! 13789: if(Dummy[modelresult[nres][j]]==0){/* Dummy variable of the variable in position modelresult in the model corresponding to j in resultline */
! 13790: printf("V%d=%d ",Tvresult[nres][j],Tresult[nres][j]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
! 13791: fprintf(ficlog,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
! 13792: fprintf(ficrest,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
! 13793: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
! 13794: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
! 13795: }else{
! 13796: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
! 13797: }
! 13798: /* fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
! 13799: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
! 13800: }else if(Dummy[modelresult[nres][j]]==1){ /* Quanti variable */
! 13801: /* For each selected (single) quantitative value */
! 13802: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
! 13803: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
! 13804: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
! 13805: }else{
! 13806: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
! 13807: }
! 13808: }else{
! 13809: 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 */
! 13810: 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 */
! 13811: exit(1);
! 13812: }
1.227 brouard 13813: }
1.334 ! brouard 13814: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
! 13815: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /\* Wrong j is not in the equation model *\/ */
! 13816: /* fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
! 13817: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
! 13818: /* } */
1.208 brouard 13819: fprintf(ficrest,"******\n");
1.227 brouard 13820: fprintf(ficlog,"******\n");
13821: printf("******\n");
1.208 brouard 13822:
13823: fprintf(ficresstdeij,"\n#****** ");
13824: fprintf(ficrescveij,"\n#****** ");
1.225 brouard 13825: for(j=1;j<=cptcoveff;j++) {
1.334 ! brouard 13826: fprintf(ficresstdeij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
! 13827: /* fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
! 13828: /* fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
! 13829: }
! 13830: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value, TvarsQind gives the position of a quantitative in model equation */
! 13831: fprintf(ficresstdeij," V%d=%f ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
! 13832: fprintf(ficrescveij," V%d=%f ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
1.235 brouard 13833: }
1.208 brouard 13834: fprintf(ficresstdeij,"******\n");
13835: fprintf(ficrescveij,"******\n");
13836:
13837: fprintf(ficresvij,"\n#****** ");
1.238 brouard 13838: /* pstamp(ficresvij); */
1.225 brouard 13839: for(j=1;j<=cptcoveff;j++)
1.332 brouard 13840: fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[TnsdVar[Tvaraff[j]]])]);
1.235 brouard 13841: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.332 brouard 13842: /* fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); /\* To solve *\/ */
13843: fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /* Solved */
1.235 brouard 13844: }
1.208 brouard 13845: fprintf(ficresvij,"******\n");
13846:
13847: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
13848: oldm=oldms;savm=savms;
1.235 brouard 13849: printf(" cvevsij ");
13850: fprintf(ficlog, " cvevsij ");
13851: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 13852: printf(" end cvevsij \n ");
13853: fprintf(ficlog, " end cvevsij \n ");
13854:
13855: /*
13856: */
13857: /* goto endfree; */
13858:
13859: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
13860: pstamp(ficrest);
13861:
1.269 brouard 13862: epj=vector(1,nlstate+1);
1.208 brouard 13863: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 13864: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
13865: cptcod= 0; /* To be deleted */
13866: printf("varevsij vpopbased=%d \n",vpopbased);
13867: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 13868: 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 */
1.227 brouard 13869: fprintf(ficrest,"# Total life expectancy with std error and decomposition into time to be expected in each health state\n# (weighted average of eij where weights are ");
13870: if(vpopbased==1)
13871: 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);
13872: else
1.288 brouard 13873: fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 13874: fprintf(ficrest,"# Age popbased mobilav e.. (std) ");
13875: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
13876: fprintf(ficrest,"\n");
13877: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 13878: printf("Computing age specific forward period (stable) prevalences in each health state \n");
13879: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 13880: for(age=bage; age <=fage ;age++){
1.235 brouard 13881: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 13882: if (vpopbased==1) {
13883: if(mobilav ==0){
13884: for(i=1; i<=nlstate;i++)
13885: prlim[i][i]=probs[(int)age][i][k];
13886: }else{ /* mobilav */
13887: for(i=1; i<=nlstate;i++)
13888: prlim[i][i]=mobaverage[(int)age][i][k];
13889: }
13890: }
1.219 brouard 13891:
1.227 brouard 13892: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
13893: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
13894: /* printf(" age %4.0f ",age); */
13895: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
13896: for(i=1, epj[j]=0.;i <=nlstate;i++) {
13897: epj[j] += prlim[i][i]*eij[i][j][(int)age];
13898: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
13899: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
13900: }
13901: epj[nlstate+1] +=epj[j];
13902: }
13903: /* printf(" age %4.0f \n",age); */
1.219 brouard 13904:
1.227 brouard 13905: for(i=1, vepp=0.;i <=nlstate;i++)
13906: for(j=1;j <=nlstate;j++)
13907: vepp += vareij[i][j][(int)age];
13908: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
13909: for(j=1;j <=nlstate;j++){
13910: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
13911: }
13912: fprintf(ficrest,"\n");
13913: }
1.208 brouard 13914: } /* End vpopbased */
1.269 brouard 13915: free_vector(epj,1,nlstate+1);
1.208 brouard 13916: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
13917: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 13918: printf("done selection\n");fflush(stdout);
13919: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 13920:
1.235 brouard 13921: } /* End k selection */
1.227 brouard 13922:
13923: printf("done State-specific expectancies\n");fflush(stdout);
13924: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
13925:
1.288 brouard 13926: /* variance-covariance of forward period prevalence*/
1.269 brouard 13927: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 13928:
1.227 brouard 13929:
1.290 brouard 13930: free_vector(weight,firstobs,lastobs);
1.330 brouard 13931: free_imatrix(Tvardk,1,NCOVMAX,1,2);
1.227 brouard 13932: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 13933: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
13934: free_matrix(anint,1,maxwav,firstobs,lastobs);
13935: free_matrix(mint,1,maxwav,firstobs,lastobs);
13936: free_ivector(cod,firstobs,lastobs);
1.227 brouard 13937: free_ivector(tab,1,NCOVMAX);
13938: fclose(ficresstdeij);
13939: fclose(ficrescveij);
13940: fclose(ficresvij);
13941: fclose(ficrest);
13942: fclose(ficpar);
13943:
13944:
1.126 brouard 13945: /*---------- End : free ----------------*/
1.219 brouard 13946: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 13947: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
13948: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 13949: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
13950: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 13951: } /* mle==-3 arrives here for freeing */
1.227 brouard 13952: /* endfree:*/
13953: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
13954: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
13955: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.290 brouard 13956: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs);
13957: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
13958: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
13959: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 13960: free_matrix(matcov,1,npar,1,npar);
13961: free_matrix(hess,1,npar,1,npar);
13962: /*free_vector(delti,1,npar);*/
13963: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
13964: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 13965: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 13966: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
13967:
13968: free_ivector(ncodemax,1,NCOVMAX);
13969: free_ivector(ncodemaxwundef,1,NCOVMAX);
13970: free_ivector(Dummy,-1,NCOVMAX);
13971: free_ivector(Fixed,-1,NCOVMAX);
1.238 brouard 13972: free_ivector(DummyV,1,NCOVMAX);
13973: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 13974: free_ivector(Typevar,-1,NCOVMAX);
13975: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 13976: free_ivector(TvarsQ,1,NCOVMAX);
13977: free_ivector(TvarsQind,1,NCOVMAX);
13978: free_ivector(TvarsD,1,NCOVMAX);
1.330 brouard 13979: free_ivector(TnsdVar,1,NCOVMAX);
1.234 brouard 13980: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 13981: free_ivector(TvarFD,1,NCOVMAX);
13982: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 13983: free_ivector(TvarF,1,NCOVMAX);
13984: free_ivector(TvarFind,1,NCOVMAX);
13985: free_ivector(TvarV,1,NCOVMAX);
13986: free_ivector(TvarVind,1,NCOVMAX);
13987: free_ivector(TvarA,1,NCOVMAX);
13988: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 13989: free_ivector(TvarFQ,1,NCOVMAX);
13990: free_ivector(TvarFQind,1,NCOVMAX);
13991: free_ivector(TvarVD,1,NCOVMAX);
13992: free_ivector(TvarVDind,1,NCOVMAX);
13993: free_ivector(TvarVQ,1,NCOVMAX);
13994: free_ivector(TvarVQind,1,NCOVMAX);
1.230 brouard 13995: free_ivector(Tvarsel,1,NCOVMAX);
13996: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 13997: free_ivector(Tposprod,1,NCOVMAX);
13998: free_ivector(Tprod,1,NCOVMAX);
13999: free_ivector(Tvaraff,1,NCOVMAX);
14000: free_ivector(invalidvarcomb,1,ncovcombmax);
14001: free_ivector(Tage,1,NCOVMAX);
14002: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 14003: free_ivector(TmodelInvind,1,NCOVMAX);
14004: free_ivector(TmodelInvQind,1,NCOVMAX);
1.332 brouard 14005:
14006: free_matrix(precov, 1,MAXRESULTLINESPONE,1,NCOVMAX+1); /* Could be elsewhere ?*/
14007:
1.227 brouard 14008: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
14009: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 14010: fflush(fichtm);
14011: fflush(ficgp);
14012:
1.227 brouard 14013:
1.126 brouard 14014: if((nberr >0) || (nbwarn>0)){
1.216 brouard 14015: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
14016: 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 14017: }else{
14018: printf("End of Imach\n");
14019: fprintf(ficlog,"End of Imach\n");
14020: }
14021: printf("See log file on %s\n",filelog);
14022: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 14023: /*(void) gettimeofday(&end_time,&tzp);*/
14024: rend_time = time(NULL);
14025: end_time = *localtime(&rend_time);
14026: /* tml = *localtime(&end_time.tm_sec); */
14027: strcpy(strtend,asctime(&end_time));
1.126 brouard 14028: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
14029: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 14030: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 14031:
1.157 brouard 14032: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
14033: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
14034: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 14035: /* printf("Total time was %d uSec.\n", total_usecs);*/
14036: /* if(fileappend(fichtm,optionfilehtm)){ */
14037: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
14038: fclose(fichtm);
14039: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
14040: fclose(fichtmcov);
14041: fclose(ficgp);
14042: fclose(ficlog);
14043: /*------ End -----------*/
1.227 brouard 14044:
1.281 brouard 14045:
14046: /* Executes gnuplot */
1.227 brouard 14047:
14048: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 14049: #ifdef WIN32
1.227 brouard 14050: if (_chdir(pathcd) != 0)
14051: printf("Can't move to directory %s!\n",path);
14052: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 14053: #else
1.227 brouard 14054: if(chdir(pathcd) != 0)
14055: printf("Can't move to directory %s!\n", path);
14056: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 14057: #endif
1.126 brouard 14058: printf("Current directory %s!\n",pathcd);
14059: /*strcat(plotcmd,CHARSEPARATOR);*/
14060: sprintf(plotcmd,"gnuplot");
1.157 brouard 14061: #ifdef _WIN32
1.126 brouard 14062: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
14063: #endif
14064: if(!stat(plotcmd,&info)){
1.158 brouard 14065: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 14066: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 14067: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 14068: }else
14069: strcpy(pplotcmd,plotcmd);
1.157 brouard 14070: #ifdef __unix
1.126 brouard 14071: strcpy(plotcmd,GNUPLOTPROGRAM);
14072: if(!stat(plotcmd,&info)){
1.158 brouard 14073: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 14074: }else
14075: strcpy(pplotcmd,plotcmd);
14076: #endif
14077: }else
14078: strcpy(pplotcmd,plotcmd);
14079:
14080: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 14081: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 brouard 14082: strcpy(pplotcmd,plotcmd);
1.227 brouard 14083:
1.126 brouard 14084: if((outcmd=system(plotcmd)) != 0){
1.292 brouard 14085: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 14086: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 14087: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 brouard 14088: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 14089: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 brouard 14090: strcpy(plotcmd,pplotcmd);
14091: }
1.126 brouard 14092: }
1.158 brouard 14093: printf(" Successful, please wait...");
1.126 brouard 14094: while (z[0] != 'q') {
14095: /* chdir(path); */
1.154 brouard 14096: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 14097: scanf("%s",z);
14098: /* if (z[0] == 'c') system("./imach"); */
14099: if (z[0] == 'e') {
1.158 brouard 14100: #ifdef __APPLE__
1.152 brouard 14101: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 14102: #elif __linux
14103: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 14104: #else
1.152 brouard 14105: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 14106: #endif
14107: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
14108: system(pplotcmd);
1.126 brouard 14109: }
14110: else if (z[0] == 'g') system(plotcmd);
14111: else if (z[0] == 'q') exit(0);
14112: }
1.227 brouard 14113: end:
1.126 brouard 14114: while (z[0] != 'q') {
1.195 brouard 14115: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 14116: scanf("%s",z);
14117: }
1.283 brouard 14118: printf("End\n");
1.282 brouard 14119: exit(0);
1.126 brouard 14120: }
FreeBSD-CVSweb <freebsd-cvsweb@FreeBSD.org>
![[BACK]](/icons/small/back.gif){kind=icon}
Return to imach.c CVS log ![[TXT]](/icons/small/text.gif){kind=icon}
![[DIR]](/icons/small/dir.gif){kind=icon}
Up to [Local Repository] / imach / src