Annotation of imach/src/imach.c, revision 1.339
1.339 ! brouard 1: /* $Id: imach.c,v 1.338 2022/09/04 17:40:33 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.339 ! brouard 4: Revision 1.338 2022/09/04 17:40:33 brouard
! 5: Summary: 0.99r36
! 6:
! 7: * imach.c (Module): Now the easy runs i.e. without result or
! 8: model=1+age only did not work. The defautl combination should be 1
! 9: and not 0 because everything hasn't been tranformed yet.
! 10:
1.338 brouard 11: Revision 1.337 2022/09/02 14:26:02 brouard
12: Summary: version 0.99r35
13:
14: * src/imach.c: Version 0.99r35 because it outputs same results with
15: 1+age+V1+V1*age for females and 1+age for females only
16: (education=1 noweight)
17:
1.337 brouard 18: Revision 1.336 2022/08/31 09:52:36 brouard
19: *** empty log message ***
20:
1.336 brouard 21: Revision 1.335 2022/08/31 08:23:16 brouard
22: Summary: improvements...
23:
1.335 brouard 24: Revision 1.334 2022/08/25 09:08:41 brouard
25: Summary: In progress for quantitative
26:
1.334 brouard 27: Revision 1.333 2022/08/21 09:10:30 brouard
28: * src/imach.c (Module): Version 0.99r33 A lot of changes in
29: reassigning covariates: my first idea was that people will always
30: use the first covariate V1 into the model but in fact they are
31: producing data with many covariates and can use an equation model
32: with some of the covariate; it means that in a model V2+V3 instead
33: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
34: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
35: the equation model is restricted to two variables only (V2, V3)
36: and the combination for V2 should be codtabm(k,1) instead of
37: (codtabm(k,2), and the code should be
38: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
39: made. All of these should be simplified once a day like we did in
40: hpxij() for example by using precov[nres] which is computed in
41: decoderesult for each nres of each resultline. Loop should be done
42: on the equation model globally by distinguishing only product with
43: age (which are changing with age) and no more on type of
44: covariates, single dummies, single covariates.
45:
1.333 brouard 46: Revision 1.332 2022/08/21 09:06:25 brouard
47: Summary: Version 0.99r33
48:
49: * src/imach.c (Module): Version 0.99r33 A lot of changes in
50: reassigning covariates: my first idea was that people will always
51: use the first covariate V1 into the model but in fact they are
52: producing data with many covariates and can use an equation model
53: with some of the covariate; it means that in a model V2+V3 instead
54: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
55: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
56: the equation model is restricted to two variables only (V2, V3)
57: and the combination for V2 should be codtabm(k,1) instead of
58: (codtabm(k,2), and the code should be
59: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
60: made. All of these should be simplified once a day like we did in
61: hpxij() for example by using precov[nres] which is computed in
62: decoderesult for each nres of each resultline. Loop should be done
63: on the equation model globally by distinguishing only product with
64: age (which are changing with age) and no more on type of
65: covariates, single dummies, single covariates.
66:
1.332 brouard 67: Revision 1.331 2022/08/07 05:40:09 brouard
68: *** empty log message ***
69:
1.331 brouard 70: Revision 1.330 2022/08/06 07:18:25 brouard
71: Summary: last 0.99r31
72:
73: * imach.c (Module): Version of imach using partly decoderesult to rebuild xpxij function
74:
1.330 brouard 75: Revision 1.329 2022/08/03 17:29:54 brouard
76: * imach.c (Module): Many errors in graphs fixed with Vn*age covariates.
77:
1.329 brouard 78: Revision 1.328 2022/07/27 17:40:48 brouard
79: Summary: valgrind bug fixed by initializing to zero DummyV as well as Tage
80:
1.328 brouard 81: Revision 1.327 2022/07/27 14:47:35 brouard
82: Summary: Still a problem for one-step probabilities in case of quantitative variables
83:
1.327 brouard 84: Revision 1.326 2022/07/26 17:33:55 brouard
85: Summary: some test with nres=1
86:
1.326 brouard 87: Revision 1.325 2022/07/25 14:27:23 brouard
88: Summary: r30
89:
90: * imach.c (Module): Error cptcovn instead of nsd in bmij (was
91: coredumped, revealed by Feiuno, thank you.
92:
1.325 brouard 93: Revision 1.324 2022/07/23 17:44:26 brouard
94: *** empty log message ***
95:
1.324 brouard 96: Revision 1.323 2022/07/22 12:30:08 brouard
97: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
98:
1.323 brouard 99: Revision 1.322 2022/07/22 12:27:48 brouard
100: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
101:
1.322 brouard 102: Revision 1.321 2022/07/22 12:04:24 brouard
103: Summary: r28
104:
105: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
106:
1.321 brouard 107: Revision 1.320 2022/06/02 05:10:11 brouard
108: *** empty log message ***
109:
1.320 brouard 110: Revision 1.319 2022/06/02 04:45:11 brouard
111: * imach.c (Module): Adding the Wald tests from the log to the main
112: htm for better display of the maximum likelihood estimators.
113:
1.319 brouard 114: Revision 1.318 2022/05/24 08:10:59 brouard
115: * imach.c (Module): Some attempts to find a bug of wrong estimates
116: of confidencce intervals with product in the equation modelC
117:
1.318 brouard 118: Revision 1.317 2022/05/15 15:06:23 brouard
119: * imach.c (Module): Some minor improvements
120:
1.317 brouard 121: Revision 1.316 2022/05/11 15:11:31 brouard
122: Summary: r27
123:
1.316 brouard 124: Revision 1.315 2022/05/11 15:06:32 brouard
125: *** empty log message ***
126:
1.315 brouard 127: Revision 1.314 2022/04/13 17:43:09 brouard
128: * imach.c (Module): Adding link to text data files
129:
1.314 brouard 130: Revision 1.313 2022/04/11 15:57:42 brouard
131: * imach.c (Module): Error in rewriting the 'r' file with yearsfproj or yearsbproj fixed
132:
1.313 brouard 133: Revision 1.312 2022/04/05 21:24:39 brouard
134: *** empty log message ***
135:
1.312 brouard 136: Revision 1.311 2022/04/05 21:03:51 brouard
137: Summary: Fixed quantitative covariates
138:
139: Fixed covariates (dummy or quantitative)
140: with missing values have never been allowed but are ERRORS and
141: program quits. Standard deviations of fixed covariates were
142: wrongly computed. Mean and standard deviations of time varying
143: covariates are still not computed.
144:
1.311 brouard 145: Revision 1.310 2022/03/17 08:45:53 brouard
146: Summary: 99r25
147:
148: Improving detection of errors: result lines should be compatible with
149: the model.
150:
1.310 brouard 151: Revision 1.309 2021/05/20 12:39:14 brouard
152: Summary: Version 0.99r24
153:
1.309 brouard 154: Revision 1.308 2021/03/31 13:11:57 brouard
155: Summary: Version 0.99r23
156:
157:
158: * imach.c (Module): Still bugs in the result loop. Thank to Holly Benett
159:
1.308 brouard 160: Revision 1.307 2021/03/08 18:11:32 brouard
161: Summary: 0.99r22 fixed bug on result:
162:
1.307 brouard 163: Revision 1.306 2021/02/20 15:44:02 brouard
164: Summary: Version 0.99r21
165:
166: * imach.c (Module): Fix bug on quitting after result lines!
167: (Module): Version 0.99r21
168:
1.306 brouard 169: Revision 1.305 2021/02/20 15:28:30 brouard
170: * imach.c (Module): Fix bug on quitting after result lines!
171:
1.305 brouard 172: Revision 1.304 2021/02/12 11:34:20 brouard
173: * imach.c (Module): The use of a Windows BOM (huge) file is now an error
174:
1.304 brouard 175: Revision 1.303 2021/02/11 19:50:15 brouard
176: * (Module): imach.c Someone entered 'results:' instead of 'result:'. Now it is an error which is printed.
177:
1.303 brouard 178: Revision 1.302 2020/02/22 21:00:05 brouard
179: * (Module): imach.c Update mle=-3 (for computing Life expectancy
180: and life table from the data without any state)
181:
1.302 brouard 182: Revision 1.301 2019/06/04 13:51:20 brouard
183: Summary: Error in 'r'parameter file backcast yearsbproj instead of yearsfproj
184:
1.301 brouard 185: Revision 1.300 2019/05/22 19:09:45 brouard
186: Summary: version 0.99r19 of May 2019
187:
1.300 brouard 188: Revision 1.299 2019/05/22 18:37:08 brouard
189: Summary: Cleaned 0.99r19
190:
1.299 brouard 191: Revision 1.298 2019/05/22 18:19:56 brouard
192: *** empty log message ***
193:
1.298 brouard 194: Revision 1.297 2019/05/22 17:56:10 brouard
195: Summary: Fix bug by moving date2dmy and nhstepm which gaefin=-1
196:
1.297 brouard 197: Revision 1.296 2019/05/20 13:03:18 brouard
198: Summary: Projection syntax simplified
199:
200:
201: We can now start projections, forward or backward, from the mean date
202: of inteviews up to or down to a number of years of projection:
203: prevforecast=1 yearsfproj=15.3 mobil_average=0
204: or
205: prevforecast=1 starting-proj-date=1/1/2007 final-proj-date=12/31/2017 mobil_average=0
206: or
207: prevbackcast=1 yearsbproj=12.3 mobil_average=1
208: or
209: prevbackcast=1 starting-back-date=1/10/1999 final-back-date=1/1/1985 mobil_average=1
210:
1.296 brouard 211: Revision 1.295 2019/05/18 09:52:50 brouard
212: Summary: doxygen tex bug
213:
1.295 brouard 214: Revision 1.294 2019/05/16 14:54:33 brouard
215: Summary: There was some wrong lines added
216:
1.294 brouard 217: Revision 1.293 2019/05/09 15:17:34 brouard
218: *** empty log message ***
219:
1.293 brouard 220: Revision 1.292 2019/05/09 14:17:20 brouard
221: Summary: Some updates
222:
1.292 brouard 223: Revision 1.291 2019/05/09 13:44:18 brouard
224: Summary: Before ncovmax
225:
1.291 brouard 226: Revision 1.290 2019/05/09 13:39:37 brouard
227: Summary: 0.99r18 unlimited number of individuals
228:
229: 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.
230:
1.290 brouard 231: Revision 1.289 2018/12/13 09:16:26 brouard
232: Summary: Bug for young ages (<-30) will be in r17
233:
1.289 brouard 234: Revision 1.288 2018/05/02 20:58:27 brouard
235: Summary: Some bugs fixed
236:
1.288 brouard 237: Revision 1.287 2018/05/01 17:57:25 brouard
238: Summary: Bug fixed by providing frequencies only for non missing covariates
239:
1.287 brouard 240: Revision 1.286 2018/04/27 14:27:04 brouard
241: Summary: some minor bugs
242:
1.286 brouard 243: Revision 1.285 2018/04/21 21:02:16 brouard
244: Summary: Some bugs fixed, valgrind tested
245:
1.285 brouard 246: Revision 1.284 2018/04/20 05:22:13 brouard
247: Summary: Computing mean and stdeviation of fixed quantitative variables
248:
1.284 brouard 249: Revision 1.283 2018/04/19 14:49:16 brouard
250: Summary: Some minor bugs fixed
251:
1.283 brouard 252: Revision 1.282 2018/02/27 22:50:02 brouard
253: *** empty log message ***
254:
1.282 brouard 255: Revision 1.281 2018/02/27 19:25:23 brouard
256: Summary: Adding second argument for quitting
257:
1.281 brouard 258: Revision 1.280 2018/02/21 07:58:13 brouard
259: Summary: 0.99r15
260:
261: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
262:
1.280 brouard 263: Revision 1.279 2017/07/20 13:35:01 brouard
264: Summary: temporary working
265:
1.279 brouard 266: Revision 1.278 2017/07/19 14:09:02 brouard
267: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
268:
1.278 brouard 269: Revision 1.277 2017/07/17 08:53:49 brouard
270: Summary: BOM files can be read now
271:
1.277 brouard 272: Revision 1.276 2017/06/30 15:48:31 brouard
273: Summary: Graphs improvements
274:
1.276 brouard 275: Revision 1.275 2017/06/30 13:39:33 brouard
276: Summary: Saito's color
277:
1.275 brouard 278: Revision 1.274 2017/06/29 09:47:08 brouard
279: Summary: Version 0.99r14
280:
1.274 brouard 281: Revision 1.273 2017/06/27 11:06:02 brouard
282: Summary: More documentation on projections
283:
1.273 brouard 284: Revision 1.272 2017/06/27 10:22:40 brouard
285: Summary: Color of backprojection changed from 6 to 5(yellow)
286:
1.272 brouard 287: Revision 1.271 2017/06/27 10:17:50 brouard
288: Summary: Some bug with rint
289:
1.271 brouard 290: Revision 1.270 2017/05/24 05:45:29 brouard
291: *** empty log message ***
292:
1.270 brouard 293: Revision 1.269 2017/05/23 08:39:25 brouard
294: Summary: Code into subroutine, cleanings
295:
1.269 brouard 296: Revision 1.268 2017/05/18 20:09:32 brouard
297: Summary: backprojection and confidence intervals of backprevalence
298:
1.268 brouard 299: Revision 1.267 2017/05/13 10:25:05 brouard
300: Summary: temporary save for backprojection
301:
1.267 brouard 302: Revision 1.266 2017/05/13 07:26:12 brouard
303: Summary: Version 0.99r13 (improvements and bugs fixed)
304:
1.266 brouard 305: Revision 1.265 2017/04/26 16:22:11 brouard
306: Summary: imach 0.99r13 Some bugs fixed
307:
1.265 brouard 308: Revision 1.264 2017/04/26 06:01:29 brouard
309: Summary: Labels in graphs
310:
1.264 brouard 311: Revision 1.263 2017/04/24 15:23:15 brouard
312: Summary: to save
313:
1.263 brouard 314: Revision 1.262 2017/04/18 16:48:12 brouard
315: *** empty log message ***
316:
1.262 brouard 317: Revision 1.261 2017/04/05 10:14:09 brouard
318: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
319:
1.261 brouard 320: Revision 1.260 2017/04/04 17:46:59 brouard
321: Summary: Gnuplot indexations fixed (humm)
322:
1.260 brouard 323: Revision 1.259 2017/04/04 13:01:16 brouard
324: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
325:
1.259 brouard 326: Revision 1.258 2017/04/03 10:17:47 brouard
327: Summary: Version 0.99r12
328:
329: Some cleanings, conformed with updated documentation.
330:
1.258 brouard 331: Revision 1.257 2017/03/29 16:53:30 brouard
332: Summary: Temp
333:
1.257 brouard 334: Revision 1.256 2017/03/27 05:50:23 brouard
335: Summary: Temporary
336:
1.256 brouard 337: Revision 1.255 2017/03/08 16:02:28 brouard
338: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
339:
1.255 brouard 340: Revision 1.254 2017/03/08 07:13:00 brouard
341: Summary: Fixing data parameter line
342:
1.254 brouard 343: Revision 1.253 2016/12/15 11:59:41 brouard
344: Summary: 0.99 in progress
345:
1.253 brouard 346: Revision 1.252 2016/09/15 21:15:37 brouard
347: *** empty log message ***
348:
1.252 brouard 349: Revision 1.251 2016/09/15 15:01:13 brouard
350: Summary: not working
351:
1.251 brouard 352: Revision 1.250 2016/09/08 16:07:27 brouard
353: Summary: continue
354:
1.250 brouard 355: Revision 1.249 2016/09/07 17:14:18 brouard
356: Summary: Starting values from frequencies
357:
1.249 brouard 358: Revision 1.248 2016/09/07 14:10:18 brouard
359: *** empty log message ***
360:
1.248 brouard 361: Revision 1.247 2016/09/02 11:11:21 brouard
362: *** empty log message ***
363:
1.247 brouard 364: Revision 1.246 2016/09/02 08:49:22 brouard
365: *** empty log message ***
366:
1.246 brouard 367: Revision 1.245 2016/09/02 07:25:01 brouard
368: *** empty log message ***
369:
1.245 brouard 370: Revision 1.244 2016/09/02 07:17:34 brouard
371: *** empty log message ***
372:
1.244 brouard 373: Revision 1.243 2016/09/02 06:45:35 brouard
374: *** empty log message ***
375:
1.243 brouard 376: Revision 1.242 2016/08/30 15:01:20 brouard
377: Summary: Fixing a lots
378:
1.242 brouard 379: Revision 1.241 2016/08/29 17:17:25 brouard
380: Summary: gnuplot problem in Back projection to fix
381:
1.241 brouard 382: Revision 1.240 2016/08/29 07:53:18 brouard
383: Summary: Better
384:
1.240 brouard 385: Revision 1.239 2016/08/26 15:51:03 brouard
386: Summary: Improvement in Powell output in order to copy and paste
387:
388: Author:
389:
1.239 brouard 390: Revision 1.238 2016/08/26 14:23:35 brouard
391: Summary: Starting tests of 0.99
392:
1.238 brouard 393: Revision 1.237 2016/08/26 09:20:19 brouard
394: Summary: to valgrind
395:
1.237 brouard 396: Revision 1.236 2016/08/25 10:50:18 brouard
397: *** empty log message ***
398:
1.236 brouard 399: Revision 1.235 2016/08/25 06:59:23 brouard
400: *** empty log message ***
401:
1.235 brouard 402: Revision 1.234 2016/08/23 16:51:20 brouard
403: *** empty log message ***
404:
1.234 brouard 405: Revision 1.233 2016/08/23 07:40:50 brouard
406: Summary: not working
407:
1.233 brouard 408: Revision 1.232 2016/08/22 14:20:21 brouard
409: Summary: not working
410:
1.232 brouard 411: Revision 1.231 2016/08/22 07:17:15 brouard
412: Summary: not working
413:
1.231 brouard 414: Revision 1.230 2016/08/22 06:55:53 brouard
415: Summary: Not working
416:
1.230 brouard 417: Revision 1.229 2016/07/23 09:45:53 brouard
418: Summary: Completing for func too
419:
1.229 brouard 420: Revision 1.228 2016/07/22 17:45:30 brouard
421: Summary: Fixing some arrays, still debugging
422:
1.227 brouard 423: Revision 1.226 2016/07/12 18:42:34 brouard
424: Summary: temp
425:
1.226 brouard 426: Revision 1.225 2016/07/12 08:40:03 brouard
427: Summary: saving but not running
428:
1.225 brouard 429: Revision 1.224 2016/07/01 13:16:01 brouard
430: Summary: Fixes
431:
1.224 brouard 432: Revision 1.223 2016/02/19 09:23:35 brouard
433: Summary: temporary
434:
1.223 brouard 435: Revision 1.222 2016/02/17 08:14:50 brouard
436: Summary: Probably last 0.98 stable version 0.98r6
437:
1.222 brouard 438: Revision 1.221 2016/02/15 23:35:36 brouard
439: Summary: minor bug
440:
1.220 brouard 441: Revision 1.219 2016/02/15 00:48:12 brouard
442: *** empty log message ***
443:
1.219 brouard 444: Revision 1.218 2016/02/12 11:29:23 brouard
445: Summary: 0.99 Back projections
446:
1.218 brouard 447: Revision 1.217 2015/12/23 17:18:31 brouard
448: Summary: Experimental backcast
449:
1.217 brouard 450: Revision 1.216 2015/12/18 17:32:11 brouard
451: Summary: 0.98r4 Warning and status=-2
452:
453: Version 0.98r4 is now:
454: - displaying an error when status is -1, date of interview unknown and date of death known;
455: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
456: Older changes concerning s=-2, dating from 2005 have been supersed.
457:
1.216 brouard 458: Revision 1.215 2015/12/16 08:52:24 brouard
459: Summary: 0.98r4 working
460:
1.215 brouard 461: Revision 1.214 2015/12/16 06:57:54 brouard
462: Summary: temporary not working
463:
1.214 brouard 464: Revision 1.213 2015/12/11 18:22:17 brouard
465: Summary: 0.98r4
466:
1.213 brouard 467: Revision 1.212 2015/11/21 12:47:24 brouard
468: Summary: minor typo
469:
1.212 brouard 470: Revision 1.211 2015/11/21 12:41:11 brouard
471: Summary: 0.98r3 with some graph of projected cross-sectional
472:
473: Author: Nicolas Brouard
474:
1.211 brouard 475: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 476: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 477: Summary: Adding ftolpl parameter
478: Author: N Brouard
479:
480: We had difficulties to get smoothed confidence intervals. It was due
481: to the period prevalence which wasn't computed accurately. The inner
482: parameter ftolpl is now an outer parameter of the .imach parameter
483: file after estepm. If ftolpl is small 1.e-4 and estepm too,
484: computation are long.
485:
1.209 brouard 486: Revision 1.208 2015/11/17 14:31:57 brouard
487: Summary: temporary
488:
1.208 brouard 489: Revision 1.207 2015/10/27 17:36:57 brouard
490: *** empty log message ***
491:
1.207 brouard 492: Revision 1.206 2015/10/24 07:14:11 brouard
493: *** empty log message ***
494:
1.206 brouard 495: Revision 1.205 2015/10/23 15:50:53 brouard
496: Summary: 0.98r3 some clarification for graphs on likelihood contributions
497:
1.205 brouard 498: Revision 1.204 2015/10/01 16:20:26 brouard
499: Summary: Some new graphs of contribution to likelihood
500:
1.204 brouard 501: Revision 1.203 2015/09/30 17:45:14 brouard
502: Summary: looking at better estimation of the hessian
503:
504: Also a better criteria for convergence to the period prevalence And
505: therefore adding the number of years needed to converge. (The
506: prevalence in any alive state shold sum to one
507:
1.203 brouard 508: Revision 1.202 2015/09/22 19:45:16 brouard
509: Summary: Adding some overall graph on contribution to likelihood. Might change
510:
1.202 brouard 511: Revision 1.201 2015/09/15 17:34:58 brouard
512: Summary: 0.98r0
513:
514: - Some new graphs like suvival functions
515: - Some bugs fixed like model=1+age+V2.
516:
1.201 brouard 517: Revision 1.200 2015/09/09 16:53:55 brouard
518: Summary: Big bug thanks to Flavia
519:
520: Even model=1+age+V2. did not work anymore
521:
1.200 brouard 522: Revision 1.199 2015/09/07 14:09:23 brouard
523: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
524:
1.199 brouard 525: Revision 1.198 2015/09/03 07:14:39 brouard
526: Summary: 0.98q5 Flavia
527:
1.198 brouard 528: Revision 1.197 2015/09/01 18:24:39 brouard
529: *** empty log message ***
530:
1.197 brouard 531: Revision 1.196 2015/08/18 23:17:52 brouard
532: Summary: 0.98q5
533:
1.196 brouard 534: Revision 1.195 2015/08/18 16:28:39 brouard
535: Summary: Adding a hack for testing purpose
536:
537: After reading the title, ftol and model lines, if the comment line has
538: a q, starting with #q, the answer at the end of the run is quit. It
539: permits to run test files in batch with ctest. The former workaround was
540: $ echo q | imach foo.imach
541:
1.195 brouard 542: Revision 1.194 2015/08/18 13:32:00 brouard
543: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
544:
1.194 brouard 545: Revision 1.193 2015/08/04 07:17:42 brouard
546: Summary: 0.98q4
547:
1.193 brouard 548: Revision 1.192 2015/07/16 16:49:02 brouard
549: Summary: Fixing some outputs
550:
1.192 brouard 551: Revision 1.191 2015/07/14 10:00:33 brouard
552: Summary: Some fixes
553:
1.191 brouard 554: Revision 1.190 2015/05/05 08:51:13 brouard
555: Summary: Adding digits in output parameters (7 digits instead of 6)
556:
557: Fix 1+age+.
558:
1.190 brouard 559: Revision 1.189 2015/04/30 14:45:16 brouard
560: Summary: 0.98q2
561:
1.189 brouard 562: Revision 1.188 2015/04/30 08:27:53 brouard
563: *** empty log message ***
564:
1.188 brouard 565: Revision 1.187 2015/04/29 09:11:15 brouard
566: *** empty log message ***
567:
1.187 brouard 568: Revision 1.186 2015/04/23 12:01:52 brouard
569: Summary: V1*age is working now, version 0.98q1
570:
571: Some codes had been disabled in order to simplify and Vn*age was
572: working in the optimization phase, ie, giving correct MLE parameters,
573: but, as usual, outputs were not correct and program core dumped.
574:
1.186 brouard 575: Revision 1.185 2015/03/11 13:26:42 brouard
576: Summary: Inclusion of compile and links command line for Intel Compiler
577:
1.185 brouard 578: Revision 1.184 2015/03/11 11:52:39 brouard
579: Summary: Back from Windows 8. Intel Compiler
580:
1.184 brouard 581: Revision 1.183 2015/03/10 20:34:32 brouard
582: Summary: 0.98q0, trying with directest, mnbrak fixed
583:
584: We use directest instead of original Powell test; probably no
585: incidence on the results, but better justifications;
586: We fixed Numerical Recipes mnbrak routine which was wrong and gave
587: wrong results.
588:
1.183 brouard 589: Revision 1.182 2015/02/12 08:19:57 brouard
590: Summary: Trying to keep directest which seems simpler and more general
591: Author: Nicolas Brouard
592:
1.182 brouard 593: Revision 1.181 2015/02/11 23:22:24 brouard
594: Summary: Comments on Powell added
595:
596: Author:
597:
1.181 brouard 598: Revision 1.180 2015/02/11 17:33:45 brouard
599: Summary: Finishing move from main to function (hpijx and prevalence_limit)
600:
1.180 brouard 601: Revision 1.179 2015/01/04 09:57:06 brouard
602: Summary: back to OS/X
603:
1.179 brouard 604: Revision 1.178 2015/01/04 09:35:48 brouard
605: *** empty log message ***
606:
1.178 brouard 607: Revision 1.177 2015/01/03 18:40:56 brouard
608: Summary: Still testing ilc32 on OSX
609:
1.177 brouard 610: Revision 1.176 2015/01/03 16:45:04 brouard
611: *** empty log message ***
612:
1.176 brouard 613: Revision 1.175 2015/01/03 16:33:42 brouard
614: *** empty log message ***
615:
1.175 brouard 616: Revision 1.174 2015/01/03 16:15:49 brouard
617: Summary: Still in cross-compilation
618:
1.174 brouard 619: Revision 1.173 2015/01/03 12:06:26 brouard
620: Summary: trying to detect cross-compilation
621:
1.173 brouard 622: Revision 1.172 2014/12/27 12:07:47 brouard
623: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
624:
1.172 brouard 625: Revision 1.171 2014/12/23 13:26:59 brouard
626: Summary: Back from Visual C
627:
628: Still problem with utsname.h on Windows
629:
1.171 brouard 630: Revision 1.170 2014/12/23 11:17:12 brouard
631: Summary: Cleaning some \%% back to %%
632:
633: The escape was mandatory for a specific compiler (which one?), but too many warnings.
634:
1.170 brouard 635: Revision 1.169 2014/12/22 23:08:31 brouard
636: Summary: 0.98p
637:
638: Outputs some informations on compiler used, OS etc. Testing on different platforms.
639:
1.169 brouard 640: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 641: Summary: update
1.169 brouard 642:
1.168 brouard 643: Revision 1.167 2014/12/22 13:50:56 brouard
644: Summary: Testing uname and compiler version and if compiled 32 or 64
645:
646: Testing on Linux 64
647:
1.167 brouard 648: Revision 1.166 2014/12/22 11:40:47 brouard
649: *** empty log message ***
650:
1.166 brouard 651: Revision 1.165 2014/12/16 11:20:36 brouard
652: Summary: After compiling on Visual C
653:
654: * imach.c (Module): Merging 1.61 to 1.162
655:
1.165 brouard 656: Revision 1.164 2014/12/16 10:52:11 brouard
657: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
658:
659: * imach.c (Module): Merging 1.61 to 1.162
660:
1.164 brouard 661: Revision 1.163 2014/12/16 10:30:11 brouard
662: * imach.c (Module): Merging 1.61 to 1.162
663:
1.163 brouard 664: Revision 1.162 2014/09/25 11:43:39 brouard
665: Summary: temporary backup 0.99!
666:
1.162 brouard 667: Revision 1.1 2014/09/16 11:06:58 brouard
668: Summary: With some code (wrong) for nlopt
669:
670: Author:
671:
672: Revision 1.161 2014/09/15 20:41:41 brouard
673: Summary: Problem with macro SQR on Intel compiler
674:
1.161 brouard 675: Revision 1.160 2014/09/02 09:24:05 brouard
676: *** empty log message ***
677:
1.160 brouard 678: Revision 1.159 2014/09/01 10:34:10 brouard
679: Summary: WIN32
680: Author: Brouard
681:
1.159 brouard 682: Revision 1.158 2014/08/27 17:11:51 brouard
683: *** empty log message ***
684:
1.158 brouard 685: Revision 1.157 2014/08/27 16:26:55 brouard
686: Summary: Preparing windows Visual studio version
687: Author: Brouard
688:
689: In order to compile on Visual studio, time.h is now correct and time_t
690: and tm struct should be used. difftime should be used but sometimes I
691: just make the differences in raw time format (time(&now).
692: Trying to suppress #ifdef LINUX
693: Add xdg-open for __linux in order to open default browser.
694:
1.157 brouard 695: Revision 1.156 2014/08/25 20:10:10 brouard
696: *** empty log message ***
697:
1.156 brouard 698: Revision 1.155 2014/08/25 18:32:34 brouard
699: Summary: New compile, minor changes
700: Author: Brouard
701:
1.155 brouard 702: Revision 1.154 2014/06/20 17:32:08 brouard
703: Summary: Outputs now all graphs of convergence to period prevalence
704:
1.154 brouard 705: Revision 1.153 2014/06/20 16:45:46 brouard
706: Summary: If 3 live state, convergence to period prevalence on same graph
707: Author: Brouard
708:
1.153 brouard 709: Revision 1.152 2014/06/18 17:54:09 brouard
710: Summary: open browser, use gnuplot on same dir than imach if not found in the path
711:
1.152 brouard 712: Revision 1.151 2014/06/18 16:43:30 brouard
713: *** empty log message ***
714:
1.151 brouard 715: Revision 1.150 2014/06/18 16:42:35 brouard
716: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
717: Author: brouard
718:
1.150 brouard 719: Revision 1.149 2014/06/18 15:51:14 brouard
720: Summary: Some fixes in parameter files errors
721: Author: Nicolas Brouard
722:
1.149 brouard 723: Revision 1.148 2014/06/17 17:38:48 brouard
724: Summary: Nothing new
725: Author: Brouard
726:
727: Just a new packaging for OS/X version 0.98nS
728:
1.148 brouard 729: Revision 1.147 2014/06/16 10:33:11 brouard
730: *** empty log message ***
731:
1.147 brouard 732: Revision 1.146 2014/06/16 10:20:28 brouard
733: Summary: Merge
734: Author: Brouard
735:
736: Merge, before building revised version.
737:
1.146 brouard 738: Revision 1.145 2014/06/10 21:23:15 brouard
739: Summary: Debugging with valgrind
740: Author: Nicolas Brouard
741:
742: Lot of changes in order to output the results with some covariates
743: After the Edimburgh REVES conference 2014, it seems mandatory to
744: improve the code.
745: No more memory valgrind error but a lot has to be done in order to
746: continue the work of splitting the code into subroutines.
747: Also, decodemodel has been improved. Tricode is still not
748: optimal. nbcode should be improved. Documentation has been added in
749: the source code.
750:
1.144 brouard 751: Revision 1.143 2014/01/26 09:45:38 brouard
752: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
753:
754: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
755: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
756:
1.143 brouard 757: Revision 1.142 2014/01/26 03:57:36 brouard
758: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
759:
760: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
761:
1.142 brouard 762: Revision 1.141 2014/01/26 02:42:01 brouard
763: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
764:
1.141 brouard 765: Revision 1.140 2011/09/02 10:37:54 brouard
766: Summary: times.h is ok with mingw32 now.
767:
1.140 brouard 768: Revision 1.139 2010/06/14 07:50:17 brouard
769: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
770: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
771:
1.139 brouard 772: Revision 1.138 2010/04/30 18:19:40 brouard
773: *** empty log message ***
774:
1.138 brouard 775: Revision 1.137 2010/04/29 18:11:38 brouard
776: (Module): Checking covariates for more complex models
777: than V1+V2. A lot of change to be done. Unstable.
778:
1.137 brouard 779: Revision 1.136 2010/04/26 20:30:53 brouard
780: (Module): merging some libgsl code. Fixing computation
781: of likelione (using inter/intrapolation if mle = 0) in order to
782: get same likelihood as if mle=1.
783: Some cleaning of code and comments added.
784:
1.136 brouard 785: Revision 1.135 2009/10/29 15:33:14 brouard
786: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
787:
1.135 brouard 788: Revision 1.134 2009/10/29 13:18:53 brouard
789: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
790:
1.134 brouard 791: Revision 1.133 2009/07/06 10:21:25 brouard
792: just nforces
793:
1.133 brouard 794: Revision 1.132 2009/07/06 08:22:05 brouard
795: Many tings
796:
1.132 brouard 797: Revision 1.131 2009/06/20 16:22:47 brouard
798: Some dimensions resccaled
799:
1.131 brouard 800: Revision 1.130 2009/05/26 06:44:34 brouard
801: (Module): Max Covariate is now set to 20 instead of 8. A
802: lot of cleaning with variables initialized to 0. Trying to make
803: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
804:
1.130 brouard 805: Revision 1.129 2007/08/31 13:49:27 lievre
806: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
807:
1.129 lievre 808: Revision 1.128 2006/06/30 13:02:05 brouard
809: (Module): Clarifications on computing e.j
810:
1.128 brouard 811: Revision 1.127 2006/04/28 18:11:50 brouard
812: (Module): Yes the sum of survivors was wrong since
813: imach-114 because nhstepm was no more computed in the age
814: loop. Now we define nhstepma in the age loop.
815: (Module): In order to speed up (in case of numerous covariates) we
816: compute health expectancies (without variances) in a first step
817: and then all the health expectancies with variances or standard
818: deviation (needs data from the Hessian matrices) which slows the
819: computation.
820: In the future we should be able to stop the program is only health
821: expectancies and graph are needed without standard deviations.
822:
1.127 brouard 823: Revision 1.126 2006/04/28 17:23:28 brouard
824: (Module): Yes the sum of survivors was wrong since
825: imach-114 because nhstepm was no more computed in the age
826: loop. Now we define nhstepma in the age loop.
827: Version 0.98h
828:
1.126 brouard 829: Revision 1.125 2006/04/04 15:20:31 lievre
830: Errors in calculation of health expectancies. Age was not initialized.
831: Forecasting file added.
832:
833: Revision 1.124 2006/03/22 17:13:53 lievre
834: Parameters are printed with %lf instead of %f (more numbers after the comma).
835: The log-likelihood is printed in the log file
836:
837: Revision 1.123 2006/03/20 10:52:43 brouard
838: * imach.c (Module): <title> changed, corresponds to .htm file
839: name. <head> headers where missing.
840:
841: * imach.c (Module): Weights can have a decimal point as for
842: English (a comma might work with a correct LC_NUMERIC environment,
843: otherwise the weight is truncated).
844: Modification of warning when the covariates values are not 0 or
845: 1.
846: Version 0.98g
847:
848: Revision 1.122 2006/03/20 09:45:41 brouard
849: (Module): Weights can have a decimal point as for
850: English (a comma might work with a correct LC_NUMERIC environment,
851: otherwise the weight is truncated).
852: Modification of warning when the covariates values are not 0 or
853: 1.
854: Version 0.98g
855:
856: Revision 1.121 2006/03/16 17:45:01 lievre
857: * imach.c (Module): Comments concerning covariates added
858:
859: * imach.c (Module): refinements in the computation of lli if
860: status=-2 in order to have more reliable computation if stepm is
861: not 1 month. Version 0.98f
862:
863: Revision 1.120 2006/03/16 15:10:38 lievre
864: (Module): refinements in the computation of lli if
865: status=-2 in order to have more reliable computation if stepm is
866: not 1 month. Version 0.98f
867:
868: Revision 1.119 2006/03/15 17:42:26 brouard
869: (Module): Bug if status = -2, the loglikelihood was
870: computed as likelihood omitting the logarithm. Version O.98e
871:
872: Revision 1.118 2006/03/14 18:20:07 brouard
873: (Module): varevsij Comments added explaining the second
874: table of variances if popbased=1 .
875: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
876: (Module): Function pstamp added
877: (Module): Version 0.98d
878:
879: Revision 1.117 2006/03/14 17:16:22 brouard
880: (Module): varevsij Comments added explaining the second
881: table of variances if popbased=1 .
882: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
883: (Module): Function pstamp added
884: (Module): Version 0.98d
885:
886: Revision 1.116 2006/03/06 10:29:27 brouard
887: (Module): Variance-covariance wrong links and
888: varian-covariance of ej. is needed (Saito).
889:
890: Revision 1.115 2006/02/27 12:17:45 brouard
891: (Module): One freematrix added in mlikeli! 0.98c
892:
893: Revision 1.114 2006/02/26 12:57:58 brouard
894: (Module): Some improvements in processing parameter
895: filename with strsep.
896:
897: Revision 1.113 2006/02/24 14:20:24 brouard
898: (Module): Memory leaks checks with valgrind and:
899: datafile was not closed, some imatrix were not freed and on matrix
900: allocation too.
901:
902: Revision 1.112 2006/01/30 09:55:26 brouard
903: (Module): Back to gnuplot.exe instead of wgnuplot.exe
904:
905: Revision 1.111 2006/01/25 20:38:18 brouard
906: (Module): Lots of cleaning and bugs added (Gompertz)
907: (Module): Comments can be added in data file. Missing date values
908: can be a simple dot '.'.
909:
910: Revision 1.110 2006/01/25 00:51:50 brouard
911: (Module): Lots of cleaning and bugs added (Gompertz)
912:
913: Revision 1.109 2006/01/24 19:37:15 brouard
914: (Module): Comments (lines starting with a #) are allowed in data.
915:
916: Revision 1.108 2006/01/19 18:05:42 lievre
917: Gnuplot problem appeared...
918: To be fixed
919:
920: Revision 1.107 2006/01/19 16:20:37 brouard
921: Test existence of gnuplot in imach path
922:
923: Revision 1.106 2006/01/19 13:24:36 brouard
924: Some cleaning and links added in html output
925:
926: Revision 1.105 2006/01/05 20:23:19 lievre
927: *** empty log message ***
928:
929: Revision 1.104 2005/09/30 16:11:43 lievre
930: (Module): sump fixed, loop imx fixed, and simplifications.
931: (Module): If the status is missing at the last wave but we know
932: that the person is alive, then we can code his/her status as -2
933: (instead of missing=-1 in earlier versions) and his/her
934: contributions to the likelihood is 1 - Prob of dying from last
935: health status (= 1-p13= p11+p12 in the easiest case of somebody in
936: the healthy state at last known wave). Version is 0.98
937:
938: Revision 1.103 2005/09/30 15:54:49 lievre
939: (Module): sump fixed, loop imx fixed, and simplifications.
940:
941: Revision 1.102 2004/09/15 17:31:30 brouard
942: Add the possibility to read data file including tab characters.
943:
944: Revision 1.101 2004/09/15 10:38:38 brouard
945: Fix on curr_time
946:
947: Revision 1.100 2004/07/12 18:29:06 brouard
948: Add version for Mac OS X. Just define UNIX in Makefile
949:
950: Revision 1.99 2004/06/05 08:57:40 brouard
951: *** empty log message ***
952:
953: Revision 1.98 2004/05/16 15:05:56 brouard
954: New version 0.97 . First attempt to estimate force of mortality
955: directly from the data i.e. without the need of knowing the health
956: state at each age, but using a Gompertz model: log u =a + b*age .
957: This is the basic analysis of mortality and should be done before any
958: other analysis, in order to test if the mortality estimated from the
959: cross-longitudinal survey is different from the mortality estimated
960: from other sources like vital statistic data.
961:
962: The same imach parameter file can be used but the option for mle should be -3.
963:
1.324 brouard 964: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 965: former routines in order to include the new code within the former code.
966:
967: The output is very simple: only an estimate of the intercept and of
968: the slope with 95% confident intervals.
969:
970: Current limitations:
971: A) Even if you enter covariates, i.e. with the
972: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
973: B) There is no computation of Life Expectancy nor Life Table.
974:
975: Revision 1.97 2004/02/20 13:25:42 lievre
976: Version 0.96d. Population forecasting command line is (temporarily)
977: suppressed.
978:
979: Revision 1.96 2003/07/15 15:38:55 brouard
980: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
981: rewritten within the same printf. Workaround: many printfs.
982:
983: Revision 1.95 2003/07/08 07:54:34 brouard
984: * imach.c (Repository):
985: (Repository): Using imachwizard code to output a more meaningful covariance
986: matrix (cov(a12,c31) instead of numbers.
987:
988: Revision 1.94 2003/06/27 13:00:02 brouard
989: Just cleaning
990:
991: Revision 1.93 2003/06/25 16:33:55 brouard
992: (Module): On windows (cygwin) function asctime_r doesn't
993: exist so I changed back to asctime which exists.
994: (Module): Version 0.96b
995:
996: Revision 1.92 2003/06/25 16:30:45 brouard
997: (Module): On windows (cygwin) function asctime_r doesn't
998: exist so I changed back to asctime which exists.
999:
1000: Revision 1.91 2003/06/25 15:30:29 brouard
1001: * imach.c (Repository): Duplicated warning errors corrected.
1002: (Repository): Elapsed time after each iteration is now output. It
1003: helps to forecast when convergence will be reached. Elapsed time
1004: is stamped in powell. We created a new html file for the graphs
1005: concerning matrix of covariance. It has extension -cov.htm.
1006:
1007: Revision 1.90 2003/06/24 12:34:15 brouard
1008: (Module): Some bugs corrected for windows. Also, when
1009: mle=-1 a template is output in file "or"mypar.txt with the design
1010: of the covariance matrix to be input.
1011:
1012: Revision 1.89 2003/06/24 12:30:52 brouard
1013: (Module): Some bugs corrected for windows. Also, when
1014: mle=-1 a template is output in file "or"mypar.txt with the design
1015: of the covariance matrix to be input.
1016:
1017: Revision 1.88 2003/06/23 17:54:56 brouard
1018: * 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.
1019:
1020: Revision 1.87 2003/06/18 12:26:01 brouard
1021: Version 0.96
1022:
1023: Revision 1.86 2003/06/17 20:04:08 brouard
1024: (Module): Change position of html and gnuplot routines and added
1025: routine fileappend.
1026:
1027: Revision 1.85 2003/06/17 13:12:43 brouard
1028: * imach.c (Repository): Check when date of death was earlier that
1029: current date of interview. It may happen when the death was just
1030: prior to the death. In this case, dh was negative and likelihood
1031: was wrong (infinity). We still send an "Error" but patch by
1032: assuming that the date of death was just one stepm after the
1033: interview.
1034: (Repository): Because some people have very long ID (first column)
1035: we changed int to long in num[] and we added a new lvector for
1036: memory allocation. But we also truncated to 8 characters (left
1037: truncation)
1038: (Repository): No more line truncation errors.
1039:
1040: Revision 1.84 2003/06/13 21:44:43 brouard
1041: * imach.c (Repository): Replace "freqsummary" at a correct
1042: place. It differs from routine "prevalence" which may be called
1043: many times. Probs is memory consuming and must be used with
1044: parcimony.
1045: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
1046:
1047: Revision 1.83 2003/06/10 13:39:11 lievre
1048: *** empty log message ***
1049:
1050: Revision 1.82 2003/06/05 15:57:20 brouard
1051: Add log in imach.c and fullversion number is now printed.
1052:
1053: */
1054: /*
1055: Interpolated Markov Chain
1056:
1057: Short summary of the programme:
1058:
1.227 brouard 1059: This program computes Healthy Life Expectancies or State-specific
1060: (if states aren't health statuses) Expectancies from
1061: cross-longitudinal data. Cross-longitudinal data consist in:
1062:
1063: -1- a first survey ("cross") where individuals from different ages
1064: are interviewed on their health status or degree of disability (in
1065: the case of a health survey which is our main interest)
1066:
1067: -2- at least a second wave of interviews ("longitudinal") which
1068: measure each change (if any) in individual health status. Health
1069: expectancies are computed from the time spent in each health state
1070: according to a model. More health states you consider, more time is
1071: necessary to reach the Maximum Likelihood of the parameters involved
1072: in the model. The simplest model is the multinomial logistic model
1073: where pij is the probability to be observed in state j at the second
1074: wave conditional to be observed in state i at the first
1075: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
1076: etc , where 'age' is age and 'sex' is a covariate. If you want to
1077: have a more complex model than "constant and age", you should modify
1078: the program where the markup *Covariates have to be included here
1079: again* invites you to do it. More covariates you add, slower the
1.126 brouard 1080: convergence.
1081:
1082: The advantage of this computer programme, compared to a simple
1083: multinomial logistic model, is clear when the delay between waves is not
1084: identical for each individual. Also, if a individual missed an
1085: intermediate interview, the information is lost, but taken into
1086: account using an interpolation or extrapolation.
1087:
1088: hPijx is the probability to be observed in state i at age x+h
1089: conditional to the observed state i at age x. The delay 'h' can be
1090: split into an exact number (nh*stepm) of unobserved intermediate
1091: states. This elementary transition (by month, quarter,
1092: semester or year) is modelled as a multinomial logistic. The hPx
1093: matrix is simply the matrix product of nh*stepm elementary matrices
1094: and the contribution of each individual to the likelihood is simply
1095: hPijx.
1096:
1097: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 1098: of the life expectancies. It also computes the period (stable) prevalence.
1099:
1100: Back prevalence and projections:
1.227 brouard 1101:
1102: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
1103: double agemaxpar, double ftolpl, int *ncvyearp, double
1104: dateprev1,double dateprev2, int firstpass, int lastpass, int
1105: mobilavproj)
1106:
1107: Computes the back prevalence limit for any combination of
1108: covariate values k at any age between ageminpar and agemaxpar and
1109: returns it in **bprlim. In the loops,
1110:
1111: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
1112: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
1113:
1114: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 1115: Computes for any combination of covariates k and any age between bage and fage
1116: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
1117: oldm=oldms;savm=savms;
1.227 brouard 1118:
1.267 brouard 1119: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 1120: Computes the transition matrix starting at age 'age' over
1121: 'nhstepm*hstepm*stepm' months (i.e. until
1122: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 1123: nhstepm*hstepm matrices.
1124:
1125: Returns p3mat[i][j][h] after calling
1126: p3mat[i][j][h]=matprod2(newm,
1127: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
1128: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
1129: oldm);
1.226 brouard 1130:
1131: Important routines
1132:
1133: - func (or funcone), computes logit (pij) distinguishing
1134: o fixed variables (single or product dummies or quantitative);
1135: o varying variables by:
1136: (1) wave (single, product dummies, quantitative),
1137: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
1138: % fixed dummy (treated) or quantitative (not done because time-consuming);
1139: % varying dummy (not done) or quantitative (not done);
1140: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
1141: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
1142: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
1.325 brouard 1143: o There are 2**cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
1.226 brouard 1144: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 1145:
1.226 brouard 1146:
1147:
1.324 brouard 1148: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
1149: Institut national d'études démographiques, Paris.
1.126 brouard 1150: This software have been partly granted by Euro-REVES, a concerted action
1151: from the European Union.
1152: It is copyrighted identically to a GNU software product, ie programme and
1153: software can be distributed freely for non commercial use. Latest version
1154: can be accessed at http://euroreves.ined.fr/imach .
1155:
1156: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
1157: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
1158:
1159: **********************************************************************/
1160: /*
1161: main
1162: read parameterfile
1163: read datafile
1164: concatwav
1165: freqsummary
1166: if (mle >= 1)
1167: mlikeli
1168: print results files
1169: if mle==1
1170: computes hessian
1171: read end of parameter file: agemin, agemax, bage, fage, estepm
1172: begin-prev-date,...
1173: open gnuplot file
1174: open html file
1.145 brouard 1175: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
1176: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
1177: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
1178: freexexit2 possible for memory heap.
1179:
1180: h Pij x | pij_nom ficrestpij
1181: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
1182: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
1183: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
1184:
1185: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
1186: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
1187: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
1188: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
1189: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
1190:
1.126 brouard 1191: forecasting if prevfcast==1 prevforecast call prevalence()
1192: health expectancies
1193: Variance-covariance of DFLE
1194: prevalence()
1195: movingaverage()
1196: varevsij()
1197: if popbased==1 varevsij(,popbased)
1198: total life expectancies
1199: Variance of period (stable) prevalence
1200: end
1201: */
1202:
1.187 brouard 1203: /* #define DEBUG */
1204: /* #define DEBUGBRENT */
1.203 brouard 1205: /* #define DEBUGLINMIN */
1206: /* #define DEBUGHESS */
1207: #define DEBUGHESSIJ
1.224 brouard 1208: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 1209: #define POWELL /* Instead of NLOPT */
1.224 brouard 1210: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 1211: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
1212: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.319 brouard 1213: /* #define FLATSUP *//* Suppresses directions where likelihood is flat */
1.126 brouard 1214:
1215: #include <math.h>
1216: #include <stdio.h>
1217: #include <stdlib.h>
1218: #include <string.h>
1.226 brouard 1219: #include <ctype.h>
1.159 brouard 1220:
1221: #ifdef _WIN32
1222: #include <io.h>
1.172 brouard 1223: #include <windows.h>
1224: #include <tchar.h>
1.159 brouard 1225: #else
1.126 brouard 1226: #include <unistd.h>
1.159 brouard 1227: #endif
1.126 brouard 1228:
1229: #include <limits.h>
1230: #include <sys/types.h>
1.171 brouard 1231:
1232: #if defined(__GNUC__)
1233: #include <sys/utsname.h> /* Doesn't work on Windows */
1234: #endif
1235:
1.126 brouard 1236: #include <sys/stat.h>
1237: #include <errno.h>
1.159 brouard 1238: /* extern int errno; */
1.126 brouard 1239:
1.157 brouard 1240: /* #ifdef LINUX */
1241: /* #include <time.h> */
1242: /* #include "timeval.h" */
1243: /* #else */
1244: /* #include <sys/time.h> */
1245: /* #endif */
1246:
1.126 brouard 1247: #include <time.h>
1248:
1.136 brouard 1249: #ifdef GSL
1250: #include <gsl/gsl_errno.h>
1251: #include <gsl/gsl_multimin.h>
1252: #endif
1253:
1.167 brouard 1254:
1.162 brouard 1255: #ifdef NLOPT
1256: #include <nlopt.h>
1257: typedef struct {
1258: double (* function)(double [] );
1259: } myfunc_data ;
1260: #endif
1261:
1.126 brouard 1262: /* #include <libintl.h> */
1263: /* #define _(String) gettext (String) */
1264:
1.251 brouard 1265: #define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1266:
1267: #define GNUPLOTPROGRAM "gnuplot"
1268: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1.329 brouard 1269: #define FILENAMELENGTH 256
1.126 brouard 1270:
1271: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1272: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1273:
1.144 brouard 1274: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
1275: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1276:
1277: #define NINTERVMAX 8
1.144 brouard 1278: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1279: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.325 brouard 1280: #define NCOVMAX 30 /**< Maximum number of covariates used in the model, including generated covariates V1*V2 or V1*age */
1.197 brouard 1281: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1282: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1283: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1284: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1285: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1286: /* #define AGESUP 130 */
1.288 brouard 1287: /* #define AGESUP 150 */
1288: #define AGESUP 200
1.268 brouard 1289: #define AGEINF 0
1.218 brouard 1290: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1291: #define AGEBASE 40
1.194 brouard 1292: #define AGEOVERFLOW 1.e20
1.164 brouard 1293: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1294: #ifdef _WIN32
1295: #define DIRSEPARATOR '\\'
1296: #define CHARSEPARATOR "\\"
1297: #define ODIRSEPARATOR '/'
1298: #else
1.126 brouard 1299: #define DIRSEPARATOR '/'
1300: #define CHARSEPARATOR "/"
1301: #define ODIRSEPARATOR '\\'
1302: #endif
1303:
1.339 ! brouard 1304: /* $Id: imach.c,v 1.338 2022/09/04 17:40:33 brouard Exp $ */
1.126 brouard 1305: /* $State: Exp $ */
1.196 brouard 1306: #include "version.h"
1307: char version[]=__IMACH_VERSION__;
1.337 brouard 1308: char copyright[]="September 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";
1.339 ! brouard 1309: char fullversion[]="$Revision: 1.338 $ $Date: 2022/09/04 17:40:33 $";
1.126 brouard 1310: char strstart[80];
1311: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1312: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.187 brouard 1313: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.330 brouard 1314: /* Number of covariates model (1)=V2+V1+ V3*age+V2*V4 */
1315: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
1.335 brouard 1316: int cptcovn=0; /**< cptcovn decodemodel: number of covariates k of the models excluding age*products =6 and age*age but including products */
1.330 brouard 1317: int cptcovt=0; /**< cptcovt: total number of covariates of the model (2) nbocc(+)+1 = 8 excepting constant and age and age*age */
1.335 brouard 1318: int cptcovs=0; /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
1319: int cptcovsnq=0; /**< cptcovsnq number of SIMPLE covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1320: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1321: int cptcovprodnoage=0; /**< Number of covariate products without age */
1.335 brouard 1322: int cptcoveff=0; /* Total number of single dummy covariates (fixed or time varying) to vary for printing results (2**cptcoveff combinations of dummies)(computed in tricode as cptcov) */
1.233 brouard 1323: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1324: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.339 ! brouard 1325: int ncovvt=0; /* Total number of effective (wave) varying covariates (dummy or quantitative or products [without age]) in the model */
1.232 brouard 1326: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 1327: int nsd=0; /**< Total number of single dummy variables (output) */
1328: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1329: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1330: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1331: int ntveff=0; /**< ntveff number of effective time varying variables */
1332: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1333: int cptcov=0; /* Working variable */
1.334 brouard 1334: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs+1 declared globally ;*/
1.290 brouard 1335: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1336: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.302 brouard 1337: int npar=NPARMAX; /* Number of parameters (nlstate+ndeath-1)*nlstate*ncovmodel; */
1.126 brouard 1338: int nlstate=2; /* Number of live states */
1339: int ndeath=1; /* Number of dead states */
1.130 brouard 1340: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.339 ! brouard 1341: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable*/
! 1342: int ncovcolt=0; /* ncovcolt=ncovcol+nqv+ntv+nqtv; total of covariates in the data, not in the model equation*/
1.126 brouard 1343: int popbased=0;
1344:
1345: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1346: int maxwav=0; /* Maxim number of waves */
1347: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1348: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1349: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1350: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1351: int mle=1, weightopt=0;
1.126 brouard 1352: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1353: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1354: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1355: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1356: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1357: int selected(int kvar); /* Is covariate kvar selected for printing results */
1358:
1.130 brouard 1359: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1360: double **matprod2(); /* test */
1.126 brouard 1361: double **oldm, **newm, **savm; /* Working pointers to matrices */
1362: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1363: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1364:
1.136 brouard 1365: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1366: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1367: FILE *ficlog, *ficrespow;
1.130 brouard 1368: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1369: double fretone; /* Only one call to likelihood */
1.130 brouard 1370: long ipmx=0; /* Number of contributions */
1.126 brouard 1371: double sw; /* Sum of weights */
1372: char filerespow[FILENAMELENGTH];
1373: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1374: FILE *ficresilk;
1375: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1376: FILE *ficresprobmorprev;
1377: FILE *fichtm, *fichtmcov; /* Html File */
1378: FILE *ficreseij;
1379: char filerese[FILENAMELENGTH];
1380: FILE *ficresstdeij;
1381: char fileresstde[FILENAMELENGTH];
1382: FILE *ficrescveij;
1383: char filerescve[FILENAMELENGTH];
1384: FILE *ficresvij;
1385: char fileresv[FILENAMELENGTH];
1.269 brouard 1386:
1.126 brouard 1387: char title[MAXLINE];
1.234 brouard 1388: char model[MAXLINE]; /**< The model line */
1.217 brouard 1389: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1390: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1391: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1392: char command[FILENAMELENGTH];
1393: int outcmd=0;
1394:
1.217 brouard 1395: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1396: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1397: char filelog[FILENAMELENGTH]; /* Log file */
1398: char filerest[FILENAMELENGTH];
1399: char fileregp[FILENAMELENGTH];
1400: char popfile[FILENAMELENGTH];
1401:
1402: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1403:
1.157 brouard 1404: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1405: /* struct timezone tzp; */
1406: /* extern int gettimeofday(); */
1407: struct tm tml, *gmtime(), *localtime();
1408:
1409: extern time_t time();
1410:
1411: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1412: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1413: struct tm tm;
1414:
1.126 brouard 1415: char strcurr[80], strfor[80];
1416:
1417: char *endptr;
1418: long lval;
1419: double dval;
1420:
1421: #define NR_END 1
1422: #define FREE_ARG char*
1423: #define FTOL 1.0e-10
1424:
1425: #define NRANSI
1.240 brouard 1426: #define ITMAX 200
1427: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1428:
1429: #define TOL 2.0e-4
1430:
1431: #define CGOLD 0.3819660
1432: #define ZEPS 1.0e-10
1433: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1434:
1435: #define GOLD 1.618034
1436: #define GLIMIT 100.0
1437: #define TINY 1.0e-20
1438:
1439: static double maxarg1,maxarg2;
1440: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1441: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1442:
1443: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1444: #define rint(a) floor(a+0.5)
1.166 brouard 1445: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1446: #define mytinydouble 1.0e-16
1.166 brouard 1447: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1448: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1449: /* static double dsqrarg; */
1450: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1451: static double sqrarg;
1452: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1453: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1454: int agegomp= AGEGOMP;
1455:
1456: int imx;
1457: int stepm=1;
1458: /* Stepm, step in month: minimum step interpolation*/
1459:
1460: int estepm;
1461: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1462:
1463: int m,nb;
1464: long *num;
1.197 brouard 1465: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1466: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1467: covariate for which somebody answered excluding
1468: undefined. Usually 2: 0 and 1. */
1469: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1470: covariate for which somebody answered including
1471: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1472: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1473: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1474: double ***mobaverage, ***mobaverages; /* New global variable */
1.332 brouard 1475: 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 1476: double *ageexmed,*agecens;
1477: double dateintmean=0;
1.296 brouard 1478: double anprojd, mprojd, jprojd; /* For eventual projections */
1479: double anprojf, mprojf, jprojf;
1.126 brouard 1480:
1.296 brouard 1481: double anbackd, mbackd, jbackd; /* For eventual backprojections */
1482: double anbackf, mbackf, jbackf;
1483: double jintmean,mintmean,aintmean;
1.126 brouard 1484: double *weight;
1485: int **s; /* Status */
1.141 brouard 1486: double *agedc;
1.145 brouard 1487: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1488: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1489: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1490: double **coqvar; /* Fixed quantitative covariate nqv */
1491: double ***cotvar; /* Time varying covariate ntv */
1.225 brouard 1492: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1493: double idx;
1494: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.319 brouard 1495: /* Some documentation */
1496: /* Design original data
1497: * V1 V2 V3 V4 V5 V6 V7 V8 Weight ddb ddth d1st s1 V9 V10 V11 V12 s2 V9 V10 V11 V12
1498: * < ncovcol=6 > nqv=2 (V7 V8) dv dv dv qtv dv dv dvv qtv
1499: * ntv=3 nqtv=1
1.330 brouard 1500: * cptcovn number of covariates (not including constant and age or age*age) = number of plus sign + 1 = 10+1=11
1.319 brouard 1501: * For time varying covariate, quanti or dummies
1502: * cotqvar[wav][iv(1 to nqtv)][i]= [1][12][i]=(V12) quanti
1503: * cotvar[wav][ntv+iv][i]= [3+(1 to nqtv)][i]=(V12) quanti
1504: * cotvar[wav][iv(1 to ntv)][i]= [1][1][i]=(V9) dummies at wav 1
1505: * cotvar[wav][iv(1 to ntv)][i]= [1][2][i]=(V10) dummies at wav 1
1.332 brouard 1506: * covar[Vk,i], value of the Vkth fixed covariate dummy or quanti for individual i:
1.319 brouard 1507: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
1508: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 + V9 + V9*age + V10
1509: * k= 1 2 3 4 5 6 7 8 9 10 11
1510: */
1511: /* According to the model, more columns can be added to covar by the product of covariates */
1.318 brouard 1512: /* 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
1513: # States 1=Coresidence, 2 Living alone, 3 Institution
1514: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1515: */
1.319 brouard 1516: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1517: /* k 1 2 3 4 5 6 7 8 9 */
1518: /*Typevar[k]= 0 0 0 2 1 0 2 1 0 *//*0 for simple covariate (dummy, quantitative,*/
1519: /* fixed or varying), 1 for age product, 2 for*/
1520: /* product */
1521: /*Dummy[k]= 1 0 0 1 3 1 1 2 0 *//*Dummy[k] 0=dummy (0 1), 1 quantitative */
1522: /*(single or product without age), 2 dummy*/
1523: /* with age product, 3 quant with age product*/
1524: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1525: /* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */
1.330 brouard 1526: /*TnsdVar[Tvar] 1 2 3 */
1.337 brouard 1527: /*Tvaraff[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1.319 brouard 1528: /*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1.338 brouard 1529: /*TvarsDind[nsd] 2 3 9 */ /* position K of single dummy cova */
1.319 brouard 1530: /* nsq 1 2 */ /* Counting single quantit tv */
1531: /* TvarsQ[k] 5 2 */ /* Number of single quantitative cova */
1532: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1533: /* Tprod[i]=k 1 2 */ /* Position in model of the ith prod without age */
1534: /* cptcovage 1 2 */ /* Counting cov*age in the model equation */
1535: /* Tage[cptcovage]=k 5 8 */ /* Position in the model of ith cov*age */
1536: /* Tvard[1][1]@4={4,3,1,2} V4*V3 V1*V2 */ /* Position in model of the ith prod without age */
1.330 brouard 1537: /* 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 1538: /* 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 1539: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.234 brouard 1540: /* Type */
1541: /* V 1 2 3 4 5 */
1542: /* F F V V V */
1543: /* D Q D D Q */
1544: /* */
1545: int *TvarsD;
1.330 brouard 1546: int *TnsdVar;
1.234 brouard 1547: int *TvarsDind;
1548: int *TvarsQ;
1549: int *TvarsQind;
1550:
1.318 brouard 1551: #define MAXRESULTLINESPONE 10+1
1.235 brouard 1552: int nresult=0;
1.258 brouard 1553: int parameterline=0; /* # of the parameter (type) line */
1.334 brouard 1554: int TKresult[MAXRESULTLINESPONE]; /* TKresult[nres]=k for each resultline nres give the corresponding combination of dummies */
1555: int resultmodel[MAXRESULTLINESPONE][NCOVMAX];/* resultmodel[k1]=k3: k1th position in the model corresponds to the k3 position in the resultline */
1556: int modelresult[MAXRESULTLINESPONE][NCOVMAX];/* modelresult[k3]=k1: k1th position in the model corresponds to the k3 position in the resultline */
1557: int Tresult[MAXRESULTLINESPONE][NCOVMAX];/* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1558: int Tinvresult[MAXRESULTLINESPONE][NCOVMAX];/* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1559: double TinvDoQresult[MAXRESULTLINESPONE][NCOVMAX];/* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.334 brouard 1560: int Tvresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1561: double Tqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.318 brouard 1562: double Tqinvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
1.332 brouard 1563: int Tvqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.318 brouard 1564:
1565: /* 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
1566: # States 1=Coresidence, 2 Living alone, 3 Institution
1567: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1568: */
1.234 brouard 1569: /* 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 1570: 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 */
1571: 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 */
1572: 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 */
1573: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1574: 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 */
1575: 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 1576: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1577: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1578: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1579: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1580: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1581: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1582: 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 */
1583: int *TvarVQind; /* TvarVQind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple time varying quantitative variable */
1.339 ! brouard 1584: int *TvarVV; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
! 1585: int *TvarVVind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
! 1586: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
! 1587: /* model V1+V3+age*V1+age*V3+V1*V3 */
! 1588: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
! 1589: /* TvarVV={3,1,3}, for V3 and then the product V1*V3 is decomposed into V1 and V3 */
! 1590: /* TvarVVind={2,5,5}, for V3 and then the product V1*V3 is decomposed into V1 and V3 */
1.230 brouard 1591: int *Tvarsel; /**< Selected covariates for output */
1592: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1593: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1594: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1595: 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 1596: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1597: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1598: int *Tage;
1.227 brouard 1599: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1600: 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 1601: 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*/
1602: 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 1603: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1604: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1605: int **Tvard;
1.330 brouard 1606: int **Tvardk;
1.227 brouard 1607: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1608: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1609: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1610: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1611: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1612: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1613: double *lsurv, *lpop, *tpop;
1614:
1.231 brouard 1615: #define FD 1; /* Fixed dummy covariate */
1616: #define FQ 2; /* Fixed quantitative covariate */
1617: #define FP 3; /* Fixed product covariate */
1618: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1619: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1620: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1621: #define VD 10; /* Varying dummy covariate */
1622: #define VQ 11; /* Varying quantitative covariate */
1623: #define VP 12; /* Varying product covariate */
1624: #define VPDD 13; /* Varying product dummy*dummy covariate */
1625: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1626: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1627: #define APFD 16; /* Age product * fixed dummy covariate */
1628: #define APFQ 17; /* Age product * fixed quantitative covariate */
1629: #define APVD 18; /* Age product * varying dummy covariate */
1630: #define APVQ 19; /* Age product * varying quantitative covariate */
1631:
1632: #define FTYPE 1; /* Fixed covariate */
1633: #define VTYPE 2; /* Varying covariate (loop in wave) */
1634: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1635:
1636: struct kmodel{
1637: int maintype; /* main type */
1638: int subtype; /* subtype */
1639: };
1640: struct kmodel modell[NCOVMAX];
1641:
1.143 brouard 1642: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1643: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1644:
1645: /**************** split *************************/
1646: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1647: {
1648: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1649: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1650: */
1651: char *ss; /* pointer */
1.186 brouard 1652: int l1=0, l2=0; /* length counters */
1.126 brouard 1653:
1654: l1 = strlen(path ); /* length of path */
1655: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1656: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1657: if ( ss == NULL ) { /* no directory, so determine current directory */
1658: strcpy( name, path ); /* we got the fullname name because no directory */
1659: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1660: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1661: /* get current working directory */
1662: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1663: #ifdef WIN32
1664: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1665: #else
1666: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1667: #endif
1.126 brouard 1668: return( GLOCK_ERROR_GETCWD );
1669: }
1670: /* got dirc from getcwd*/
1671: printf(" DIRC = %s \n",dirc);
1.205 brouard 1672: } else { /* strip directory from path */
1.126 brouard 1673: ss++; /* after this, the filename */
1674: l2 = strlen( ss ); /* length of filename */
1675: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1676: strcpy( name, ss ); /* save file name */
1677: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1678: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1679: printf(" DIRC2 = %s \n",dirc);
1680: }
1681: /* We add a separator at the end of dirc if not exists */
1682: l1 = strlen( dirc ); /* length of directory */
1683: if( dirc[l1-1] != DIRSEPARATOR ){
1684: dirc[l1] = DIRSEPARATOR;
1685: dirc[l1+1] = 0;
1686: printf(" DIRC3 = %s \n",dirc);
1687: }
1688: ss = strrchr( name, '.' ); /* find last / */
1689: if (ss >0){
1690: ss++;
1691: strcpy(ext,ss); /* save extension */
1692: l1= strlen( name);
1693: l2= strlen(ss)+1;
1694: strncpy( finame, name, l1-l2);
1695: finame[l1-l2]= 0;
1696: }
1697:
1698: return( 0 ); /* we're done */
1699: }
1700:
1701:
1702: /******************************************/
1703:
1704: void replace_back_to_slash(char *s, char*t)
1705: {
1706: int i;
1707: int lg=0;
1708: i=0;
1709: lg=strlen(t);
1710: for(i=0; i<= lg; i++) {
1711: (s[i] = t[i]);
1712: if (t[i]== '\\') s[i]='/';
1713: }
1714: }
1715:
1.132 brouard 1716: char *trimbb(char *out, char *in)
1.137 brouard 1717: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1718: char *s;
1719: s=out;
1720: while (*in != '\0'){
1.137 brouard 1721: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1722: in++;
1723: }
1724: *out++ = *in++;
1725: }
1726: *out='\0';
1727: return s;
1728: }
1729:
1.187 brouard 1730: /* char *substrchaine(char *out, char *in, char *chain) */
1731: /* { */
1732: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1733: /* char *s, *t; */
1734: /* t=in;s=out; */
1735: /* while ((*in != *chain) && (*in != '\0')){ */
1736: /* *out++ = *in++; */
1737: /* } */
1738:
1739: /* /\* *in matches *chain *\/ */
1740: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1741: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1742: /* } */
1743: /* in--; chain--; */
1744: /* while ( (*in != '\0')){ */
1745: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1746: /* *out++ = *in++; */
1747: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1748: /* } */
1749: /* *out='\0'; */
1750: /* out=s; */
1751: /* return out; */
1752: /* } */
1753: char *substrchaine(char *out, char *in, char *chain)
1754: {
1755: /* Substract chain 'chain' from 'in', return and output 'out' */
1756: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1757:
1758: char *strloc;
1759:
1760: strcpy (out, in);
1761: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1762: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1763: if(strloc != NULL){
1764: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1765: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1766: /* strcpy (strloc, strloc +strlen(chain));*/
1767: }
1768: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1769: return out;
1770: }
1771:
1772:
1.145 brouard 1773: char *cutl(char *blocc, char *alocc, char *in, char occ)
1774: {
1.187 brouard 1775: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1776: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.310 brouard 1777: gives alocc="abcdef" and blocc="ghi2j".
1.145 brouard 1778: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1779: */
1.160 brouard 1780: char *s, *t;
1.145 brouard 1781: t=in;s=in;
1782: while ((*in != occ) && (*in != '\0')){
1783: *alocc++ = *in++;
1784: }
1785: if( *in == occ){
1786: *(alocc)='\0';
1787: s=++in;
1788: }
1789:
1790: if (s == t) {/* occ not found */
1791: *(alocc-(in-s))='\0';
1792: in=s;
1793: }
1794: while ( *in != '\0'){
1795: *blocc++ = *in++;
1796: }
1797:
1798: *blocc='\0';
1799: return t;
1800: }
1.137 brouard 1801: char *cutv(char *blocc, char *alocc, char *in, char occ)
1802: {
1.187 brouard 1803: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1804: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1805: gives blocc="abcdef2ghi" and alocc="j".
1806: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1807: */
1808: char *s, *t;
1809: t=in;s=in;
1810: while (*in != '\0'){
1811: while( *in == occ){
1812: *blocc++ = *in++;
1813: s=in;
1814: }
1815: *blocc++ = *in++;
1816: }
1817: if (s == t) /* occ not found */
1818: *(blocc-(in-s))='\0';
1819: else
1820: *(blocc-(in-s)-1)='\0';
1821: in=s;
1822: while ( *in != '\0'){
1823: *alocc++ = *in++;
1824: }
1825:
1826: *alocc='\0';
1827: return s;
1828: }
1829:
1.126 brouard 1830: int nbocc(char *s, char occ)
1831: {
1832: int i,j=0;
1833: int lg=20;
1834: i=0;
1835: lg=strlen(s);
1836: for(i=0; i<= lg; i++) {
1.234 brouard 1837: if (s[i] == occ ) j++;
1.126 brouard 1838: }
1839: return j;
1840: }
1841:
1.137 brouard 1842: /* void cutv(char *u,char *v, char*t, char occ) */
1843: /* { */
1844: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1845: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1846: /* gives u="abcdef2ghi" and v="j" *\/ */
1847: /* int i,lg,j,p=0; */
1848: /* i=0; */
1849: /* lg=strlen(t); */
1850: /* for(j=0; j<=lg-1; j++) { */
1851: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1852: /* } */
1.126 brouard 1853:
1.137 brouard 1854: /* for(j=0; j<p; j++) { */
1855: /* (u[j] = t[j]); */
1856: /* } */
1857: /* u[p]='\0'; */
1.126 brouard 1858:
1.137 brouard 1859: /* for(j=0; j<= lg; j++) { */
1860: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1861: /* } */
1862: /* } */
1.126 brouard 1863:
1.160 brouard 1864: #ifdef _WIN32
1865: char * strsep(char **pp, const char *delim)
1866: {
1867: char *p, *q;
1868:
1869: if ((p = *pp) == NULL)
1870: return 0;
1871: if ((q = strpbrk (p, delim)) != NULL)
1872: {
1873: *pp = q + 1;
1874: *q = '\0';
1875: }
1876: else
1877: *pp = 0;
1878: return p;
1879: }
1880: #endif
1881:
1.126 brouard 1882: /********************** nrerror ********************/
1883:
1884: void nrerror(char error_text[])
1885: {
1886: fprintf(stderr,"ERREUR ...\n");
1887: fprintf(stderr,"%s\n",error_text);
1888: exit(EXIT_FAILURE);
1889: }
1890: /*********************** vector *******************/
1891: double *vector(int nl, int nh)
1892: {
1893: double *v;
1894: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1895: if (!v) nrerror("allocation failure in vector");
1896: return v-nl+NR_END;
1897: }
1898:
1899: /************************ free vector ******************/
1900: void free_vector(double*v, int nl, int nh)
1901: {
1902: free((FREE_ARG)(v+nl-NR_END));
1903: }
1904:
1905: /************************ivector *******************************/
1906: int *ivector(long nl,long nh)
1907: {
1908: int *v;
1909: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1910: if (!v) nrerror("allocation failure in ivector");
1911: return v-nl+NR_END;
1912: }
1913:
1914: /******************free ivector **************************/
1915: void free_ivector(int *v, long nl, long nh)
1916: {
1917: free((FREE_ARG)(v+nl-NR_END));
1918: }
1919:
1920: /************************lvector *******************************/
1921: long *lvector(long nl,long nh)
1922: {
1923: long *v;
1924: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1925: if (!v) nrerror("allocation failure in ivector");
1926: return v-nl+NR_END;
1927: }
1928:
1929: /******************free lvector **************************/
1930: void free_lvector(long *v, long nl, long nh)
1931: {
1932: free((FREE_ARG)(v+nl-NR_END));
1933: }
1934:
1935: /******************* imatrix *******************************/
1936: int **imatrix(long nrl, long nrh, long ncl, long nch)
1937: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1938: {
1939: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1940: int **m;
1941:
1942: /* allocate pointers to rows */
1943: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1944: if (!m) nrerror("allocation failure 1 in matrix()");
1945: m += NR_END;
1946: m -= nrl;
1947:
1948:
1949: /* allocate rows and set pointers to them */
1950: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
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:
1957: /* return pointer to array of pointers to rows */
1958: return m;
1959: }
1960:
1961: /****************** free_imatrix *************************/
1962: void free_imatrix(m,nrl,nrh,ncl,nch)
1963: int **m;
1964: long nch,ncl,nrh,nrl;
1965: /* free an int matrix allocated by imatrix() */
1966: {
1967: free((FREE_ARG) (m[nrl]+ncl-NR_END));
1968: free((FREE_ARG) (m+nrl-NR_END));
1969: }
1970:
1971: /******************* matrix *******************************/
1972: double **matrix(long nrl, long nrh, long ncl, long nch)
1973: {
1974: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
1975: double **m;
1976:
1977: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1978: if (!m) nrerror("allocation failure 1 in matrix()");
1979: m += NR_END;
1980: m -= nrl;
1981:
1982: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1983: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1984: m[nrl] += NR_END;
1985: m[nrl] -= ncl;
1986:
1987: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1988: return m;
1.145 brouard 1989: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
1990: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
1991: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 1992: */
1993: }
1994:
1995: /*************************free matrix ************************/
1996: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
1997: {
1998: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1999: free((FREE_ARG)(m+nrl-NR_END));
2000: }
2001:
2002: /******************* ma3x *******************************/
2003: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
2004: {
2005: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
2006: double ***m;
2007:
2008: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
2009: if (!m) nrerror("allocation failure 1 in matrix()");
2010: m += NR_END;
2011: m -= nrl;
2012:
2013: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
2014: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2015: m[nrl] += NR_END;
2016: m[nrl] -= ncl;
2017:
2018: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2019:
2020: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
2021: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
2022: m[nrl][ncl] += NR_END;
2023: m[nrl][ncl] -= nll;
2024: for (j=ncl+1; j<=nch; j++)
2025: m[nrl][j]=m[nrl][j-1]+nlay;
2026:
2027: for (i=nrl+1; i<=nrh; i++) {
2028: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
2029: for (j=ncl+1; j<=nch; j++)
2030: m[i][j]=m[i][j-1]+nlay;
2031: }
2032: return m;
2033: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
2034: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
2035: */
2036: }
2037:
2038: /*************************free ma3x ************************/
2039: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
2040: {
2041: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
2042: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2043: free((FREE_ARG)(m+nrl-NR_END));
2044: }
2045:
2046: /*************** function subdirf ***********/
2047: char *subdirf(char fileres[])
2048: {
2049: /* Caution optionfilefiname is hidden */
2050: strcpy(tmpout,optionfilefiname);
2051: strcat(tmpout,"/"); /* Add to the right */
2052: strcat(tmpout,fileres);
2053: return tmpout;
2054: }
2055:
2056: /*************** function subdirf2 ***********/
2057: char *subdirf2(char fileres[], char *preop)
2058: {
1.314 brouard 2059: /* Example subdirf2(optionfilefiname,"FB_") with optionfilefiname="texte", result="texte/FB_texte"
2060: Errors in subdirf, 2, 3 while printing tmpout is
1.315 brouard 2061: rewritten within the same printf. Workaround: many printfs */
1.126 brouard 2062: /* Caution optionfilefiname is hidden */
2063: strcpy(tmpout,optionfilefiname);
2064: strcat(tmpout,"/");
2065: strcat(tmpout,preop);
2066: strcat(tmpout,fileres);
2067: return tmpout;
2068: }
2069:
2070: /*************** function subdirf3 ***********/
2071: char *subdirf3(char fileres[], char *preop, char *preop2)
2072: {
2073:
2074: /* Caution optionfilefiname is hidden */
2075: strcpy(tmpout,optionfilefiname);
2076: strcat(tmpout,"/");
2077: strcat(tmpout,preop);
2078: strcat(tmpout,preop2);
2079: strcat(tmpout,fileres);
2080: return tmpout;
2081: }
1.213 brouard 2082:
2083: /*************** function subdirfext ***********/
2084: char *subdirfext(char fileres[], char *preop, char *postop)
2085: {
2086:
2087: strcpy(tmpout,preop);
2088: strcat(tmpout,fileres);
2089: strcat(tmpout,postop);
2090: return tmpout;
2091: }
1.126 brouard 2092:
1.213 brouard 2093: /*************** function subdirfext3 ***********/
2094: char *subdirfext3(char fileres[], char *preop, char *postop)
2095: {
2096:
2097: /* Caution optionfilefiname is hidden */
2098: strcpy(tmpout,optionfilefiname);
2099: strcat(tmpout,"/");
2100: strcat(tmpout,preop);
2101: strcat(tmpout,fileres);
2102: strcat(tmpout,postop);
2103: return tmpout;
2104: }
2105:
1.162 brouard 2106: char *asc_diff_time(long time_sec, char ascdiff[])
2107: {
2108: long sec_left, days, hours, minutes;
2109: days = (time_sec) / (60*60*24);
2110: sec_left = (time_sec) % (60*60*24);
2111: hours = (sec_left) / (60*60) ;
2112: sec_left = (sec_left) %(60*60);
2113: minutes = (sec_left) /60;
2114: sec_left = (sec_left) % (60);
2115: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
2116: return ascdiff;
2117: }
2118:
1.126 brouard 2119: /***************** f1dim *************************/
2120: extern int ncom;
2121: extern double *pcom,*xicom;
2122: extern double (*nrfunc)(double []);
2123:
2124: double f1dim(double x)
2125: {
2126: int j;
2127: double f;
2128: double *xt;
2129:
2130: xt=vector(1,ncom);
2131: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
2132: f=(*nrfunc)(xt);
2133: free_vector(xt,1,ncom);
2134: return f;
2135: }
2136:
2137: /*****************brent *************************/
2138: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 2139: {
2140: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
2141: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
2142: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
2143: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
2144: * returned function value.
2145: */
1.126 brouard 2146: int iter;
2147: double a,b,d,etemp;
1.159 brouard 2148: double fu=0,fv,fw,fx;
1.164 brouard 2149: double ftemp=0.;
1.126 brouard 2150: double p,q,r,tol1,tol2,u,v,w,x,xm;
2151: double e=0.0;
2152:
2153: a=(ax < cx ? ax : cx);
2154: b=(ax > cx ? ax : cx);
2155: x=w=v=bx;
2156: fw=fv=fx=(*f)(x);
2157: for (iter=1;iter<=ITMAX;iter++) {
2158: xm=0.5*(a+b);
2159: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
2160: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
2161: printf(".");fflush(stdout);
2162: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 2163: #ifdef DEBUGBRENT
1.126 brouard 2164: 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);
2165: 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);
2166: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
2167: #endif
2168: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
2169: *xmin=x;
2170: return fx;
2171: }
2172: ftemp=fu;
2173: if (fabs(e) > tol1) {
2174: r=(x-w)*(fx-fv);
2175: q=(x-v)*(fx-fw);
2176: p=(x-v)*q-(x-w)*r;
2177: q=2.0*(q-r);
2178: if (q > 0.0) p = -p;
2179: q=fabs(q);
2180: etemp=e;
2181: e=d;
2182: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 2183: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 2184: else {
1.224 brouard 2185: d=p/q;
2186: u=x+d;
2187: if (u-a < tol2 || b-u < tol2)
2188: d=SIGN(tol1,xm-x);
1.126 brouard 2189: }
2190: } else {
2191: d=CGOLD*(e=(x >= xm ? a-x : b-x));
2192: }
2193: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
2194: fu=(*f)(u);
2195: if (fu <= fx) {
2196: if (u >= x) a=x; else b=x;
2197: SHFT(v,w,x,u)
1.183 brouard 2198: SHFT(fv,fw,fx,fu)
2199: } else {
2200: if (u < x) a=u; else b=u;
2201: if (fu <= fw || w == x) {
1.224 brouard 2202: v=w;
2203: w=u;
2204: fv=fw;
2205: fw=fu;
1.183 brouard 2206: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 2207: v=u;
2208: fv=fu;
1.183 brouard 2209: }
2210: }
1.126 brouard 2211: }
2212: nrerror("Too many iterations in brent");
2213: *xmin=x;
2214: return fx;
2215: }
2216:
2217: /****************** mnbrak ***********************/
2218:
2219: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
2220: double (*func)(double))
1.183 brouard 2221: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
2222: the downhill direction (defined by the function as evaluated at the initial points) and returns
2223: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
2224: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
2225: */
1.126 brouard 2226: double ulim,u,r,q, dum;
2227: double fu;
1.187 brouard 2228:
2229: double scale=10.;
2230: int iterscale=0;
2231:
2232: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
2233: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
2234:
2235:
2236: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
2237: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
2238: /* *bx = *ax - (*ax - *bx)/scale; */
2239: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
2240: /* } */
2241:
1.126 brouard 2242: if (*fb > *fa) {
2243: SHFT(dum,*ax,*bx,dum)
1.183 brouard 2244: SHFT(dum,*fb,*fa,dum)
2245: }
1.126 brouard 2246: *cx=(*bx)+GOLD*(*bx-*ax);
2247: *fc=(*func)(*cx);
1.183 brouard 2248: #ifdef DEBUG
1.224 brouard 2249: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
2250: 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 2251: #endif
1.224 brouard 2252: 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 2253: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 2254: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 2255: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 2256: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
2257: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
2258: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 2259: fu=(*func)(u);
1.163 brouard 2260: #ifdef DEBUG
2261: /* f(x)=A(x-u)**2+f(u) */
2262: double A, fparabu;
2263: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2264: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 2265: 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);
2266: 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 2267: /* And thus,it can be that fu > *fc even if fparabu < *fc */
2268: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
2269: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
2270: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 2271: #endif
1.184 brouard 2272: #ifdef MNBRAKORIGINAL
1.183 brouard 2273: #else
1.191 brouard 2274: /* if (fu > *fc) { */
2275: /* #ifdef DEBUG */
2276: /* printf("mnbrak4 fu > fc \n"); */
2277: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
2278: /* #endif */
2279: /* /\* 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 *\\/ *\/ */
2280: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2281: /* dum=u; /\* Shifting c and u *\/ */
2282: /* u = *cx; */
2283: /* *cx = dum; */
2284: /* dum = fu; */
2285: /* fu = *fc; */
2286: /* *fc =dum; */
2287: /* } else { /\* end *\/ */
2288: /* #ifdef DEBUG */
2289: /* printf("mnbrak3 fu < fc \n"); */
2290: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2291: /* #endif */
2292: /* dum=u; /\* Shifting c and u *\/ */
2293: /* u = *cx; */
2294: /* *cx = dum; */
2295: /* dum = fu; */
2296: /* fu = *fc; */
2297: /* *fc =dum; */
2298: /* } */
1.224 brouard 2299: #ifdef DEBUGMNBRAK
2300: double A, fparabu;
2301: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2302: fparabu= *fa - A*(*ax-u)*(*ax-u);
2303: 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);
2304: 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 2305: #endif
1.191 brouard 2306: dum=u; /* Shifting c and u */
2307: u = *cx;
2308: *cx = dum;
2309: dum = fu;
2310: fu = *fc;
2311: *fc =dum;
1.183 brouard 2312: #endif
1.162 brouard 2313: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2314: #ifdef DEBUG
1.224 brouard 2315: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2316: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2317: #endif
1.126 brouard 2318: fu=(*func)(u);
2319: if (fu < *fc) {
1.183 brouard 2320: #ifdef DEBUG
1.224 brouard 2321: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2322: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2323: #endif
2324: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2325: SHFT(*fb,*fc,fu,(*func)(u))
2326: #ifdef DEBUG
2327: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2328: #endif
2329: }
1.162 brouard 2330: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2331: #ifdef DEBUG
1.224 brouard 2332: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2333: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2334: #endif
1.126 brouard 2335: u=ulim;
2336: fu=(*func)(u);
1.183 brouard 2337: } else { /* u could be left to b (if r > q parabola has a maximum) */
2338: #ifdef DEBUG
1.224 brouard 2339: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2340: 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 2341: #endif
1.126 brouard 2342: u=(*cx)+GOLD*(*cx-*bx);
2343: fu=(*func)(u);
1.224 brouard 2344: #ifdef DEBUG
2345: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2346: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2347: #endif
1.183 brouard 2348: } /* end tests */
1.126 brouard 2349: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2350: SHFT(*fa,*fb,*fc,fu)
2351: #ifdef DEBUG
1.224 brouard 2352: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2353: 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 2354: #endif
2355: } /* 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 2356: }
2357:
2358: /*************** linmin ************************/
1.162 brouard 2359: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2360: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2361: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2362: the value of func at the returned location p . This is actually all accomplished by calling the
2363: routines mnbrak and brent .*/
1.126 brouard 2364: int ncom;
2365: double *pcom,*xicom;
2366: double (*nrfunc)(double []);
2367:
1.224 brouard 2368: #ifdef LINMINORIGINAL
1.126 brouard 2369: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2370: #else
2371: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2372: #endif
1.126 brouard 2373: {
2374: double brent(double ax, double bx, double cx,
2375: double (*f)(double), double tol, double *xmin);
2376: double f1dim(double x);
2377: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2378: double *fc, double (*func)(double));
2379: int j;
2380: double xx,xmin,bx,ax;
2381: double fx,fb,fa;
1.187 brouard 2382:
1.203 brouard 2383: #ifdef LINMINORIGINAL
2384: #else
2385: double scale=10., axs, xxs; /* Scale added for infinity */
2386: #endif
2387:
1.126 brouard 2388: ncom=n;
2389: pcom=vector(1,n);
2390: xicom=vector(1,n);
2391: nrfunc=func;
2392: for (j=1;j<=n;j++) {
2393: pcom[j]=p[j];
1.202 brouard 2394: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2395: }
1.187 brouard 2396:
1.203 brouard 2397: #ifdef LINMINORIGINAL
2398: xx=1.;
2399: #else
2400: axs=0.0;
2401: xxs=1.;
2402: do{
2403: xx= xxs;
2404: #endif
1.187 brouard 2405: ax=0.;
2406: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2407: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2408: /* 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)) */
2409: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2410: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2411: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2412: /* 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 2413: #ifdef LINMINORIGINAL
2414: #else
2415: if (fx != fx){
1.224 brouard 2416: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2417: printf("|");
2418: fprintf(ficlog,"|");
1.203 brouard 2419: #ifdef DEBUGLINMIN
1.224 brouard 2420: 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 2421: #endif
2422: }
1.224 brouard 2423: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2424: #endif
2425:
1.191 brouard 2426: #ifdef DEBUGLINMIN
2427: 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 2428: 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 2429: #endif
1.224 brouard 2430: #ifdef LINMINORIGINAL
2431: #else
1.317 brouard 2432: if(fb == fx){ /* Flat function in the direction */
2433: xmin=xx;
1.224 brouard 2434: *flat=1;
1.317 brouard 2435: }else{
1.224 brouard 2436: *flat=0;
2437: #endif
2438: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2439: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2440: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2441: /* fmin = f(p[j] + xmin * xi[j]) */
2442: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2443: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2444: #ifdef DEBUG
1.224 brouard 2445: 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);
2446: 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);
2447: #endif
2448: #ifdef LINMINORIGINAL
2449: #else
2450: }
1.126 brouard 2451: #endif
1.191 brouard 2452: #ifdef DEBUGLINMIN
2453: printf("linmin end ");
1.202 brouard 2454: fprintf(ficlog,"linmin end ");
1.191 brouard 2455: #endif
1.126 brouard 2456: for (j=1;j<=n;j++) {
1.203 brouard 2457: #ifdef LINMINORIGINAL
2458: xi[j] *= xmin;
2459: #else
2460: #ifdef DEBUGLINMIN
2461: if(xxs <1.0)
2462: printf(" before xi[%d]=%12.8f", j,xi[j]);
2463: #endif
2464: 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) */
2465: #ifdef DEBUGLINMIN
2466: if(xxs <1.0)
2467: 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 );
2468: #endif
2469: #endif
1.187 brouard 2470: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2471: }
1.191 brouard 2472: #ifdef DEBUGLINMIN
1.203 brouard 2473: printf("\n");
1.191 brouard 2474: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2475: 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 2476: for (j=1;j<=n;j++) {
1.202 brouard 2477: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2478: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2479: if(j % ncovmodel == 0){
1.191 brouard 2480: printf("\n");
1.202 brouard 2481: fprintf(ficlog,"\n");
2482: }
1.191 brouard 2483: }
1.203 brouard 2484: #else
1.191 brouard 2485: #endif
1.126 brouard 2486: free_vector(xicom,1,n);
2487: free_vector(pcom,1,n);
2488: }
2489:
2490:
2491: /*************** powell ************************/
1.162 brouard 2492: /*
1.317 brouard 2493: Minimization of a function func of n variables. Input consists in an initial starting point
2494: p[1..n] ; an initial matrix xi[1..n][1..n] whose columns contain the initial set of di-
2495: rections (usually the n unit vectors); and ftol, the fractional tolerance in the function value
2496: such that failure to decrease by more than this amount in one iteration signals doneness. On
1.162 brouard 2497: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2498: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2499: */
1.224 brouard 2500: #ifdef LINMINORIGINAL
2501: #else
2502: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2503: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2504: #endif
1.126 brouard 2505: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2506: double (*func)(double []))
2507: {
1.224 brouard 2508: #ifdef LINMINORIGINAL
2509: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2510: double (*func)(double []));
1.224 brouard 2511: #else
1.241 brouard 2512: void linmin(double p[], double xi[], int n, double *fret,
2513: double (*func)(double []),int *flat);
1.224 brouard 2514: #endif
1.239 brouard 2515: int i,ibig,j,jk,k;
1.126 brouard 2516: double del,t,*pt,*ptt,*xit;
1.181 brouard 2517: double directest;
1.126 brouard 2518: double fp,fptt;
2519: double *xits;
2520: int niterf, itmp;
2521:
2522: pt=vector(1,n);
2523: ptt=vector(1,n);
2524: xit=vector(1,n);
2525: xits=vector(1,n);
2526: *fret=(*func)(p);
2527: for (j=1;j<=n;j++) pt[j]=p[j];
1.338 brouard 2528: rcurr_time = time(NULL);
2529: fp=(*fret); /* Initialisation */
1.126 brouard 2530: for (*iter=1;;++(*iter)) {
2531: ibig=0;
2532: del=0.0;
1.157 brouard 2533: rlast_time=rcurr_time;
2534: /* (void) gettimeofday(&curr_time,&tzp); */
2535: rcurr_time = time(NULL);
2536: curr_time = *localtime(&rcurr_time);
1.337 brouard 2537: /* 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); */
2538: /* 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); */
2539: printf("\nPowell iter=%d -2*LL=%.12f gain=%.3lg %ld sec. %ld sec.",*iter,*fret,fp-*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
2540: fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f gain=%.3lg %ld sec. %ld sec.",*iter,*fret,fp-*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
1.157 brouard 2541: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.324 brouard 2542: fp=(*fret); /* From former iteration or initial value */
1.192 brouard 2543: for (i=1;i<=n;i++) {
1.126 brouard 2544: fprintf(ficrespow," %.12lf", p[i]);
2545: }
1.239 brouard 2546: fprintf(ficrespow,"\n");fflush(ficrespow);
2547: printf("\n#model= 1 + age ");
2548: fprintf(ficlog,"\n#model= 1 + age ");
2549: if(nagesqr==1){
1.241 brouard 2550: printf(" + age*age ");
2551: fprintf(ficlog," + age*age ");
1.239 brouard 2552: }
2553: for(j=1;j <=ncovmodel-2;j++){
2554: if(Typevar[j]==0) {
2555: printf(" + V%d ",Tvar[j]);
2556: fprintf(ficlog," + V%d ",Tvar[j]);
2557: }else if(Typevar[j]==1) {
2558: printf(" + V%d*age ",Tvar[j]);
2559: fprintf(ficlog," + V%d*age ",Tvar[j]);
2560: }else if(Typevar[j]==2) {
2561: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2562: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2563: }
2564: }
1.126 brouard 2565: printf("\n");
1.239 brouard 2566: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2567: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2568: fprintf(ficlog,"\n");
1.239 brouard 2569: for(i=1,jk=1; i <=nlstate; i++){
2570: for(k=1; k <=(nlstate+ndeath); k++){
2571: if (k != i) {
2572: printf("%d%d ",i,k);
2573: fprintf(ficlog,"%d%d ",i,k);
2574: for(j=1; j <=ncovmodel; j++){
2575: printf("%12.7f ",p[jk]);
2576: fprintf(ficlog,"%12.7f ",p[jk]);
2577: jk++;
2578: }
2579: printf("\n");
2580: fprintf(ficlog,"\n");
2581: }
2582: }
2583: }
1.241 brouard 2584: if(*iter <=3 && *iter >1){
1.157 brouard 2585: tml = *localtime(&rcurr_time);
2586: strcpy(strcurr,asctime(&tml));
2587: rforecast_time=rcurr_time;
1.126 brouard 2588: itmp = strlen(strcurr);
2589: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2590: strcurr[itmp-1]='\0';
1.162 brouard 2591: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2592: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2593: for(niterf=10;niterf<=30;niterf+=10){
1.241 brouard 2594: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2595: forecast_time = *localtime(&rforecast_time);
2596: strcpy(strfor,asctime(&forecast_time));
2597: itmp = strlen(strfor);
2598: if(strfor[itmp-1]=='\n')
2599: strfor[itmp-1]='\0';
2600: 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);
2601: 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 2602: }
2603: }
1.187 brouard 2604: for (i=1;i<=n;i++) { /* For each direction i */
2605: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2606: fptt=(*fret);
2607: #ifdef DEBUG
1.203 brouard 2608: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2609: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2610: #endif
1.203 brouard 2611: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2612: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2613: #ifdef LINMINORIGINAL
1.188 brouard 2614: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2615: #else
2616: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2617: flatdir[i]=flat; /* Function is vanishing in that direction i */
2618: #endif
2619: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2620: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2621: /* because that direction will be replaced unless the gain del is small */
2622: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2623: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2624: /* with the new direction. */
2625: del=fabs(fptt-(*fret));
2626: ibig=i;
1.126 brouard 2627: }
2628: #ifdef DEBUG
2629: printf("%d %.12e",i,(*fret));
2630: fprintf(ficlog,"%d %.12e",i,(*fret));
2631: for (j=1;j<=n;j++) {
1.224 brouard 2632: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2633: printf(" x(%d)=%.12e",j,xit[j]);
2634: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2635: }
2636: for(j=1;j<=n;j++) {
1.225 brouard 2637: printf(" p(%d)=%.12e",j,p[j]);
2638: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2639: }
2640: printf("\n");
2641: fprintf(ficlog,"\n");
2642: #endif
1.187 brouard 2643: } /* end loop on each direction i */
2644: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2645: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2646: /* New value of last point Pn is not computed, P(n-1) */
1.319 brouard 2647: for(j=1;j<=n;j++) {
2648: if(flatdir[j] >0){
2649: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2650: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
1.302 brouard 2651: }
1.319 brouard 2652: /* printf("\n"); */
2653: /* fprintf(ficlog,"\n"); */
2654: }
1.243 brouard 2655: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2656: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2657: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2658: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2659: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2660: /* decreased of more than 3.84 */
2661: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2662: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2663: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2664:
1.188 brouard 2665: /* Starting the program with initial values given by a former maximization will simply change */
2666: /* the scales of the directions and the directions, because the are reset to canonical directions */
2667: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2668: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2669: #ifdef DEBUG
2670: int k[2],l;
2671: k[0]=1;
2672: k[1]=-1;
2673: printf("Max: %.12e",(*func)(p));
2674: fprintf(ficlog,"Max: %.12e",(*func)(p));
2675: for (j=1;j<=n;j++) {
2676: printf(" %.12e",p[j]);
2677: fprintf(ficlog," %.12e",p[j]);
2678: }
2679: printf("\n");
2680: fprintf(ficlog,"\n");
2681: for(l=0;l<=1;l++) {
2682: for (j=1;j<=n;j++) {
2683: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2684: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2685: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2686: }
2687: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2688: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2689: }
2690: #endif
2691:
2692: free_vector(xit,1,n);
2693: free_vector(xits,1,n);
2694: free_vector(ptt,1,n);
2695: free_vector(pt,1,n);
2696: return;
1.192 brouard 2697: } /* enough precision */
1.240 brouard 2698: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2699: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2700: ptt[j]=2.0*p[j]-pt[j];
2701: xit[j]=p[j]-pt[j];
2702: pt[j]=p[j];
2703: }
1.181 brouard 2704: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2705: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2706: if (*iter <=4) {
1.225 brouard 2707: #else
2708: #endif
1.224 brouard 2709: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2710: #else
1.161 brouard 2711: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2712: #endif
1.162 brouard 2713: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2714: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2715: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2716: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2717: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2718: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2719: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2720: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2721: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2722: /* Even if f3 <f1, directest can be negative and t >0 */
2723: /* mu² and del² are equal when f3=f1 */
2724: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2725: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2726: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2727: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2728: #ifdef NRCORIGINAL
2729: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2730: #else
2731: 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 2732: t= t- del*SQR(fp-fptt);
1.183 brouard 2733: #endif
1.202 brouard 2734: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2735: #ifdef DEBUG
1.181 brouard 2736: 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);
2737: 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 2738: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2739: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2740: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2741: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2742: 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);
2743: 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);
2744: #endif
1.183 brouard 2745: #ifdef POWELLORIGINAL
2746: if (t < 0.0) { /* Then we use it for new direction */
2747: #else
1.182 brouard 2748: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2749: 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 2750: 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 2751: 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 2752: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2753: }
1.181 brouard 2754: if (directest < 0.0) { /* Then we use it for new direction */
2755: #endif
1.191 brouard 2756: #ifdef DEBUGLINMIN
1.234 brouard 2757: printf("Before linmin in direction P%d-P0\n",n);
2758: for (j=1;j<=n;j++) {
2759: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2760: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2761: if(j % ncovmodel == 0){
2762: printf("\n");
2763: fprintf(ficlog,"\n");
2764: }
2765: }
1.224 brouard 2766: #endif
2767: #ifdef LINMINORIGINAL
1.234 brouard 2768: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2769: #else
1.234 brouard 2770: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2771: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2772: #endif
1.234 brouard 2773:
1.191 brouard 2774: #ifdef DEBUGLINMIN
1.234 brouard 2775: for (j=1;j<=n;j++) {
2776: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2777: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2778: if(j % ncovmodel == 0){
2779: printf("\n");
2780: fprintf(ficlog,"\n");
2781: }
2782: }
1.224 brouard 2783: #endif
1.234 brouard 2784: for (j=1;j<=n;j++) {
2785: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2786: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2787: }
1.224 brouard 2788: #ifdef LINMINORIGINAL
2789: #else
1.234 brouard 2790: for (j=1, flatd=0;j<=n;j++) {
2791: if(flatdir[j]>0)
2792: flatd++;
2793: }
2794: if(flatd >0){
1.255 brouard 2795: printf("%d flat directions: ",flatd);
2796: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2797: for (j=1;j<=n;j++) {
2798: if(flatdir[j]>0){
2799: printf("%d ",j);
2800: fprintf(ficlog,"%d ",j);
2801: }
2802: }
2803: printf("\n");
2804: fprintf(ficlog,"\n");
1.319 brouard 2805: #ifdef FLATSUP
2806: free_vector(xit,1,n);
2807: free_vector(xits,1,n);
2808: free_vector(ptt,1,n);
2809: free_vector(pt,1,n);
2810: return;
2811: #endif
1.234 brouard 2812: }
1.191 brouard 2813: #endif
1.234 brouard 2814: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2815: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2816:
1.126 brouard 2817: #ifdef DEBUG
1.234 brouard 2818: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2819: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2820: for(j=1;j<=n;j++){
2821: printf(" %lf",xit[j]);
2822: fprintf(ficlog," %lf",xit[j]);
2823: }
2824: printf("\n");
2825: fprintf(ficlog,"\n");
1.126 brouard 2826: #endif
1.192 brouard 2827: } /* end of t or directest negative */
1.224 brouard 2828: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2829: #else
1.234 brouard 2830: } /* end if (fptt < fp) */
1.192 brouard 2831: #endif
1.225 brouard 2832: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2833: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2834: #else
1.224 brouard 2835: #endif
1.234 brouard 2836: } /* loop iteration */
1.126 brouard 2837: }
1.234 brouard 2838:
1.126 brouard 2839: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2840:
1.235 brouard 2841: 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 2842: {
1.338 brouard 2843: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij . Nicely done
1.279 brouard 2844: * (and selected quantitative values in nres)
2845: * by left multiplying the unit
2846: * matrix by transitions matrix until convergence is reached with precision ftolpl
2847: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2848: * Wx is row vector: population in state 1, population in state 2, population dead
2849: * or prevalence in state 1, prevalence in state 2, 0
2850: * newm is the matrix after multiplications, its rows are identical at a factor.
2851: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2852: * Output is prlim.
2853: * Initial matrix pimij
2854: */
1.206 brouard 2855: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2856: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2857: /* 0, 0 , 1} */
2858: /*
2859: * and after some iteration: */
2860: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2861: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2862: /* 0, 0 , 1} */
2863: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2864: /* {0.51571254859325999, 0.4842874514067399, */
2865: /* 0.51326036147820708, 0.48673963852179264} */
2866: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2867:
1.332 brouard 2868: int i, ii,j,k, k1;
1.209 brouard 2869: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2870: /* double **matprod2(); */ /* test */
1.218 brouard 2871: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2872: double **newm;
1.209 brouard 2873: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2874: int ncvloop=0;
1.288 brouard 2875: int first=0;
1.169 brouard 2876:
1.209 brouard 2877: min=vector(1,nlstate);
2878: max=vector(1,nlstate);
2879: meandiff=vector(1,nlstate);
2880:
1.218 brouard 2881: /* Starting with matrix unity */
1.126 brouard 2882: for (ii=1;ii<=nlstate+ndeath;ii++)
2883: for (j=1;j<=nlstate+ndeath;j++){
2884: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2885: }
1.169 brouard 2886:
2887: cov[1]=1.;
2888:
2889: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2890: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2891: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2892: ncvloop++;
1.126 brouard 2893: newm=savm;
2894: /* Covariates have to be included here again */
1.138 brouard 2895: cov[2]=agefin;
1.319 brouard 2896: if(nagesqr==1){
2897: cov[3]= agefin*agefin;
2898: }
1.332 brouard 2899: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
2900: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
2901: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
2902: if(Typevar[k1]==1){ /* A product with age */
2903: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
2904: }else{
2905: cov[2+nagesqr+k1]=precov[nres][k1];
2906: }
2907: }/* End of loop on model equation */
2908:
2909: /* Start of old code (replaced by a loop on position in the model equation */
2910: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only of the model *\/ */
2911: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
2912: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; *\/ */
2913: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TnsdVar[TvarsD[k]])]; */
2914: /* /\* model = 1 +age + V1*V3 + age*V1 + V2 + V1 + age*V2 + V3 + V3*age + V1*V2 */
2915: /* * k 1 2 3 4 5 6 7 8 */
2916: /* *cov[] 1 2 3 4 5 6 7 8 9 10 */
2917: /* *TypeVar[k] 2 1 0 0 1 0 1 2 */
2918: /* *Dummy[k] 0 2 0 0 2 0 2 0 */
2919: /* *Tvar[k] 4 1 2 1 2 3 3 5 */
2920: /* *nsd=3 (1) (2) (3) */
2921: /* *TvarsD[nsd] [1]=2 1 3 */
2922: /* *TnsdVar [2]=2 [1]=1 [3]=3 */
2923: /* *TvarsDind[nsd](=k) [1]=3 [2]=4 [3]=6 */
2924: /* *Tage[] [1]=1 [2]=2 [3]=3 */
2925: /* *Tvard[] [1][1]=1 [2][1]=1 */
2926: /* * [1][2]=3 [2][2]=2 */
2927: /* *Tprod[](=k) [1]=1 [2]=8 */
2928: /* *TvarsDp(=Tvar) [1]=1 [2]=2 [3]=3 [4]=5 */
2929: /* *TvarD (=k) [1]=1 [2]=3 [3]=4 [3]=6 [4]=6 */
2930: /* *TvarsDpType */
2931: /* *si model= 1 + age + V3 + V2*age + V2 + V3*age */
2932: /* * nsd=1 (1) (2) */
2933: /* *TvarsD[nsd] 3 2 */
2934: /* *TnsdVar (3)=1 (2)=2 */
2935: /* *TvarsDind[nsd](=k) [1]=1 [2]=3 */
2936: /* *Tage[] [1]=2 [2]= 3 */
2937: /* *\/ */
2938: /* /\* cov[++k1]=nbcode[TvarsD[k]][codtabm(ij,k)]; *\/ */
2939: /* /\* 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)); *\/ */
2940: /* } */
2941: /* for (k=1; k<=nsq;k++) { /\* For single quantitative varying covariates only of the model *\/ */
2942: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
2943: /* /\* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline *\/ */
2944: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
2945: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][resultmodel[nres][k1]] */
2946: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
2947: /* /\* 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]); *\/ */
2948: /* } */
2949: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
2950: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
2951: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
2952: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
2953: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
2954: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
2955: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
2956: /* } */
2957: /* /\* 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]); *\/ */
2958: /* } */
2959: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
2960: /* /\* 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]); *\/ */
2961: /* if(Dummy[Tvard[k][1]]==0){ */
2962: /* if(Dummy[Tvard[k][2]]==0){ */
2963: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
2964: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
2965: /* }else{ */
2966: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
2967: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
2968: /* } */
2969: /* }else{ */
2970: /* if(Dummy[Tvard[k][2]]==0){ */
2971: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
2972: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
2973: /* }else{ */
2974: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
2975: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
2976: /* } */
2977: /* } */
2978: /* } /\* End product without age *\/ */
2979: /* ENd of old code */
1.138 brouard 2980: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2981: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2982: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 2983: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2984: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.319 brouard 2985: /* age and covariate values of ij are in 'cov' */
1.142 brouard 2986: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 2987:
1.126 brouard 2988: savm=oldm;
2989: oldm=newm;
1.209 brouard 2990:
2991: for(j=1; j<=nlstate; j++){
2992: max[j]=0.;
2993: min[j]=1.;
2994: }
2995: for(i=1;i<=nlstate;i++){
2996: sumnew=0;
2997: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
2998: for(j=1; j<=nlstate; j++){
2999: prlim[i][j]= newm[i][j]/(1-sumnew);
3000: max[j]=FMAX(max[j],prlim[i][j]);
3001: min[j]=FMIN(min[j],prlim[i][j]);
3002: }
3003: }
3004:
1.126 brouard 3005: maxmax=0.;
1.209 brouard 3006: for(j=1; j<=nlstate; j++){
3007: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
3008: maxmax=FMAX(maxmax,meandiff[j]);
3009: /* 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 3010: } /* j loop */
1.203 brouard 3011: *ncvyear= (int)age- (int)agefin;
1.208 brouard 3012: /* 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 3013: if(maxmax < ftolpl){
1.209 brouard 3014: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
3015: free_vector(min,1,nlstate);
3016: free_vector(max,1,nlstate);
3017: free_vector(meandiff,1,nlstate);
1.126 brouard 3018: return prlim;
3019: }
1.288 brouard 3020: } /* agefin loop */
1.208 brouard 3021: /* After some age loop it doesn't converge */
1.288 brouard 3022: if(!first){
3023: first=1;
3024: 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 3025: 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);
3026: }else if (first >=1 && first <10){
3027: 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);
3028: first++;
3029: }else if (first ==10){
3030: 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);
3031: 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");
3032: fprintf(ficlog,"Warning: the stable prevalence no convergence; too many cases, giving up noticing, even in log file\n");
3033: first++;
1.288 brouard 3034: }
3035:
1.209 brouard 3036: /* 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); */
3037: free_vector(min,1,nlstate);
3038: free_vector(max,1,nlstate);
3039: free_vector(meandiff,1,nlstate);
1.208 brouard 3040:
1.169 brouard 3041: return prlim; /* should not reach here */
1.126 brouard 3042: }
3043:
1.217 brouard 3044:
3045: /**** Back Prevalence limit (stable or period prevalence) ****************/
3046:
1.218 brouard 3047: /* 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) */
3048: /* 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 3049: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 3050: {
1.264 brouard 3051: /* 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 3052: matrix by transitions matrix until convergence is reached with precision ftolpl */
3053: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
3054: /* Wx is row vector: population in state 1, population in state 2, population dead */
3055: /* or prevalence in state 1, prevalence in state 2, 0 */
3056: /* newm is the matrix after multiplications, its rows are identical at a factor */
3057: /* Initial matrix pimij */
3058: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
3059: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
3060: /* 0, 0 , 1} */
3061: /*
3062: * and after some iteration: */
3063: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
3064: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
3065: /* 0, 0 , 1} */
3066: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
3067: /* {0.51571254859325999, 0.4842874514067399, */
3068: /* 0.51326036147820708, 0.48673963852179264} */
3069: /* If we start from prlim again, prlim tends to a constant matrix */
3070:
1.332 brouard 3071: int i, ii,j,k, k1;
1.247 brouard 3072: int first=0;
1.217 brouard 3073: double *min, *max, *meandiff, maxmax,sumnew=0.;
3074: /* double **matprod2(); */ /* test */
3075: double **out, cov[NCOVMAX+1], **bmij();
3076: double **newm;
1.218 brouard 3077: double **dnewm, **doldm, **dsavm; /* for use */
3078: double **oldm, **savm; /* for use */
3079:
1.217 brouard 3080: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
3081: int ncvloop=0;
3082:
3083: min=vector(1,nlstate);
3084: max=vector(1,nlstate);
3085: meandiff=vector(1,nlstate);
3086:
1.266 brouard 3087: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
3088: oldm=oldms; savm=savms;
3089:
3090: /* Starting with matrix unity */
3091: for (ii=1;ii<=nlstate+ndeath;ii++)
3092: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 3093: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3094: }
3095:
3096: cov[1]=1.;
3097:
3098: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3099: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 3100: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 3101: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
3102: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 3103: ncvloop++;
1.218 brouard 3104: newm=savm; /* oldm should be kept from previous iteration or unity at start */
3105: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 3106: /* Covariates have to be included here again */
3107: cov[2]=agefin;
1.319 brouard 3108: if(nagesqr==1){
1.217 brouard 3109: cov[3]= agefin*agefin;;
1.319 brouard 3110: }
1.332 brouard 3111: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
3112: if(Typevar[k1]==1){ /* A product with age */
3113: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.242 brouard 3114: }else{
1.332 brouard 3115: cov[2+nagesqr+k1]=precov[nres][k1];
1.242 brouard 3116: }
1.332 brouard 3117: }/* End of loop on model equation */
3118:
3119: /* Old code */
3120:
3121: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
3122: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
3123: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; */
3124: /* /\* 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)); *\/ */
3125: /* } */
3126: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
3127: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
3128: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
3129: /* /\* /\\* 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])]); *\\/ *\/ */
3130: /* /\* } *\/ */
3131: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
3132: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3133: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
3134: /* /\* 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]); *\/ */
3135: /* } */
3136: /* /\* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; *\/ */
3137: /* /\* for (k=1; k<=cptcovprod;k++) /\\* Useless *\\/ *\/ */
3138: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\\/ *\/ */
3139: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3140: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
3141: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age *\\/ ERROR ???*\/ */
3142: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
3143: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3144: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
3145: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3146: /* } */
3147: /* /\* 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]); *\/ */
3148: /* } */
3149: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
3150: /* /\* 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]); *\/ */
3151: /* if(Dummy[Tvard[k][1]]==0){ */
3152: /* if(Dummy[Tvard[k][2]]==0){ */
3153: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3154: /* }else{ */
3155: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3156: /* } */
3157: /* }else{ */
3158: /* if(Dummy[Tvard[k][2]]==0){ */
3159: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3160: /* }else{ */
3161: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3162: /* } */
3163: /* } */
3164: /* } */
1.217 brouard 3165:
3166: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
3167: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
3168: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
3169: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3170: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 3171: /* ij should be linked to the correct index of cov */
3172: /* age and covariate values ij are in 'cov', but we need to pass
3173: * ij for the observed prevalence at age and status and covariate
3174: * number: prevacurrent[(int)agefin][ii][ij]
3175: */
3176: /* 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 *\/ */
3177: /* 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 *\/ */
3178: 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 3179: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 3180: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
3181: /* for(i=1; i<=nlstate+ndeath; i++) { */
3182: /* printf("%d newm= ",i); */
3183: /* for(j=1;j<=nlstate+ndeath;j++) { */
3184: /* printf("%f ",newm[i][j]); */
3185: /* } */
3186: /* printf("oldm * "); */
3187: /* for(j=1;j<=nlstate+ndeath;j++) { */
3188: /* printf("%f ",oldm[i][j]); */
3189: /* } */
1.268 brouard 3190: /* printf(" bmmij "); */
1.266 brouard 3191: /* for(j=1;j<=nlstate+ndeath;j++) { */
3192: /* printf("%f ",pmmij[i][j]); */
3193: /* } */
3194: /* printf("\n"); */
3195: /* } */
3196: /* } */
1.217 brouard 3197: savm=oldm;
3198: oldm=newm;
1.266 brouard 3199:
1.217 brouard 3200: for(j=1; j<=nlstate; j++){
3201: max[j]=0.;
3202: min[j]=1.;
3203: }
3204: for(j=1; j<=nlstate; j++){
3205: for(i=1;i<=nlstate;i++){
1.234 brouard 3206: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
3207: bprlim[i][j]= newm[i][j];
3208: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
3209: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 3210: }
3211: }
1.218 brouard 3212:
1.217 brouard 3213: maxmax=0.;
3214: for(i=1; i<=nlstate; i++){
1.318 brouard 3215: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column, could be nan! */
1.217 brouard 3216: maxmax=FMAX(maxmax,meandiff[i]);
3217: /* 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 3218: } /* i loop */
1.217 brouard 3219: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 3220: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3221: if(maxmax < ftolpl){
1.220 brouard 3222: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3223: free_vector(min,1,nlstate);
3224: free_vector(max,1,nlstate);
3225: free_vector(meandiff,1,nlstate);
3226: return bprlim;
3227: }
1.288 brouard 3228: } /* agefin loop */
1.217 brouard 3229: /* After some age loop it doesn't converge */
1.288 brouard 3230: if(!first){
1.247 brouard 3231: first=1;
3232: 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\
3233: 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);
3234: }
3235: 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 3236: 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);
3237: /* 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); */
3238: free_vector(min,1,nlstate);
3239: free_vector(max,1,nlstate);
3240: free_vector(meandiff,1,nlstate);
3241:
3242: return bprlim; /* should not reach here */
3243: }
3244:
1.126 brouard 3245: /*************** transition probabilities ***************/
3246:
3247: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
3248: {
1.138 brouard 3249: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 3250: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 3251: model to the ncovmodel covariates (including constant and age).
3252: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3253: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3254: ncth covariate in the global vector x is given by the formula:
3255: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3256: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3257: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3258: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 3259: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 3260: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 3261: Sum on j ps[i][j] should equal to 1.
1.138 brouard 3262: */
3263: double s1, lnpijopii;
1.126 brouard 3264: /*double t34;*/
1.164 brouard 3265: int i,j, nc, ii, jj;
1.126 brouard 3266:
1.223 brouard 3267: for(i=1; i<= nlstate; i++){
3268: for(j=1; j<i;j++){
3269: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3270: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3271: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3272: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3273: }
3274: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3275: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3276: }
3277: for(j=i+1; j<=nlstate+ndeath;j++){
3278: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3279: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3280: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3281: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3282: }
3283: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3284: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3285: }
3286: }
1.218 brouard 3287:
1.223 brouard 3288: for(i=1; i<= nlstate; i++){
3289: s1=0;
3290: for(j=1; j<i; j++){
1.339 ! brouard 3291: /* printf("debug1 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 3292: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3293: }
3294: for(j=i+1; j<=nlstate+ndeath; j++){
1.339 ! brouard 3295: /* printf("debug2 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 3296: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3297: }
3298: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3299: ps[i][i]=1./(s1+1.);
3300: /* Computing other pijs */
3301: for(j=1; j<i; j++)
1.325 brouard 3302: ps[i][j]= exp(ps[i][j])*ps[i][i];/* Bug valgrind */
1.223 brouard 3303: for(j=i+1; j<=nlstate+ndeath; j++)
3304: ps[i][j]= exp(ps[i][j])*ps[i][i];
3305: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3306: } /* end i */
1.218 brouard 3307:
1.223 brouard 3308: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3309: for(jj=1; jj<= nlstate+ndeath; jj++){
3310: ps[ii][jj]=0;
3311: ps[ii][ii]=1;
3312: }
3313: }
1.294 brouard 3314:
3315:
1.223 brouard 3316: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3317: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3318: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3319: /* } */
3320: /* printf("\n "); */
3321: /* } */
3322: /* printf("\n ");printf("%lf ",cov[2]);*/
3323: /*
3324: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 3325: goto end;*/
1.266 brouard 3326: return ps; /* Pointer is unchanged since its call */
1.126 brouard 3327: }
3328:
1.218 brouard 3329: /*************** backward transition probabilities ***************/
3330:
3331: /* 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 ) */
3332: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
3333: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
3334: {
1.302 brouard 3335: /* 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 3336: * 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 3337: */
1.218 brouard 3338: int i, ii, j,k;
1.222 brouard 3339:
3340: double **out, **pmij();
3341: double sumnew=0.;
1.218 brouard 3342: double agefin;
1.292 brouard 3343: 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 3344: double **dnewm, **dsavm, **doldm;
3345: double **bbmij;
3346:
1.218 brouard 3347: doldm=ddoldms; /* global pointers */
1.222 brouard 3348: dnewm=ddnewms;
3349: dsavm=ddsavms;
1.318 brouard 3350:
3351: /* Debug */
3352: /* printf("Bmij ij=%d, cov[2}=%f\n", ij, cov[2]); */
1.222 brouard 3353: agefin=cov[2];
1.268 brouard 3354: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 3355: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 3356: the observed prevalence (with this covariate ij) at beginning of transition */
3357: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 3358:
3359: /* P_x */
1.325 brouard 3360: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm *//* Bug valgrind */
1.268 brouard 3361: /* outputs pmmij which is a stochastic matrix in row */
3362:
3363: /* Diag(w_x) */
1.292 brouard 3364: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 3365: sumnew=0.;
1.269 brouard 3366: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 3367: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.297 brouard 3368: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 3369: sumnew+=prevacurrent[(int)agefin][ii][ij];
3370: }
3371: if(sumnew >0.01){ /* At least some value in the prevalence */
3372: for (ii=1;ii<=nlstate+ndeath;ii++){
3373: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 3374: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 3375: }
3376: }else{
3377: for (ii=1;ii<=nlstate+ndeath;ii++){
3378: for (j=1;j<=nlstate+ndeath;j++)
3379: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
3380: }
3381: /* if(sumnew <0.9){ */
3382: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3383: /* } */
3384: }
3385: k3=0.0; /* We put the last diagonal to 0 */
3386: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3387: doldm[ii][ii]= k3;
3388: }
3389: /* End doldm, At the end doldm is diag[(w_i)] */
3390:
1.292 brouard 3391: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
3392: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 3393:
1.292 brouard 3394: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 3395: /* 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 3396: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3397: sumnew=0.;
1.222 brouard 3398: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3399: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3400: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3401: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3402: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3403: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3404: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3405: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3406: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3407: /* }else */
1.268 brouard 3408: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3409: } /*End ii */
3410: } /* 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 */
3411:
1.292 brouard 3412: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 3413: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3414: /* end bmij */
1.266 brouard 3415: return ps; /*pointer is unchanged */
1.218 brouard 3416: }
1.217 brouard 3417: /*************** transition probabilities ***************/
3418:
1.218 brouard 3419: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3420: {
3421: /* According to parameters values stored in x and the covariate's values stored in cov,
3422: computes the probability to be observed in state j being in state i by appying the
3423: model to the ncovmodel covariates (including constant and age).
3424: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3425: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3426: ncth covariate in the global vector x is given by the formula:
3427: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3428: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3429: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3430: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3431: Outputs ps[i][j] the probability to be observed in j being in j according to
3432: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3433: */
3434: double s1, lnpijopii;
3435: /*double t34;*/
3436: int i,j, nc, ii, jj;
3437:
1.234 brouard 3438: for(i=1; i<= nlstate; i++){
3439: for(j=1; j<i;j++){
3440: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3441: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3442: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3443: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3444: }
3445: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3446: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3447: }
3448: for(j=i+1; j<=nlstate+ndeath;j++){
3449: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3450: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3451: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3452: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3453: }
3454: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3455: }
3456: }
3457:
3458: for(i=1; i<= nlstate; i++){
3459: s1=0;
3460: for(j=1; j<i; j++){
3461: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3462: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3463: }
3464: for(j=i+1; j<=nlstate+ndeath; j++){
3465: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3466: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3467: }
3468: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3469: ps[i][i]=1./(s1+1.);
3470: /* Computing other pijs */
3471: for(j=1; j<i; j++)
3472: ps[i][j]= exp(ps[i][j])*ps[i][i];
3473: for(j=i+1; j<=nlstate+ndeath; j++)
3474: ps[i][j]= exp(ps[i][j])*ps[i][i];
3475: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3476: } /* end i */
3477:
3478: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3479: for(jj=1; jj<= nlstate+ndeath; jj++){
3480: ps[ii][jj]=0;
3481: ps[ii][ii]=1;
3482: }
3483: }
1.296 brouard 3484: /* Added for prevbcast */ /* Transposed matrix too */
1.234 brouard 3485: for(jj=1; jj<= nlstate+ndeath; jj++){
3486: s1=0.;
3487: for(ii=1; ii<= nlstate+ndeath; ii++){
3488: s1+=ps[ii][jj];
3489: }
3490: for(ii=1; ii<= nlstate; ii++){
3491: ps[ii][jj]=ps[ii][jj]/s1;
3492: }
3493: }
3494: /* Transposition */
3495: for(jj=1; jj<= nlstate+ndeath; jj++){
3496: for(ii=jj; ii<= nlstate+ndeath; ii++){
3497: s1=ps[ii][jj];
3498: ps[ii][jj]=ps[jj][ii];
3499: ps[jj][ii]=s1;
3500: }
3501: }
3502: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3503: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3504: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3505: /* } */
3506: /* printf("\n "); */
3507: /* } */
3508: /* printf("\n ");printf("%lf ",cov[2]);*/
3509: /*
3510: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3511: goto end;*/
3512: return ps;
1.217 brouard 3513: }
3514:
3515:
1.126 brouard 3516: /**************** Product of 2 matrices ******************/
3517:
1.145 brouard 3518: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3519: {
3520: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3521: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3522: /* in, b, out are matrice of pointers which should have been initialized
3523: before: only the contents of out is modified. The function returns
3524: a pointer to pointers identical to out */
1.145 brouard 3525: int i, j, k;
1.126 brouard 3526: for(i=nrl; i<= nrh; i++)
1.145 brouard 3527: for(k=ncolol; k<=ncoloh; k++){
3528: out[i][k]=0.;
3529: for(j=ncl; j<=nch; j++)
3530: out[i][k] +=in[i][j]*b[j][k];
3531: }
1.126 brouard 3532: return out;
3533: }
3534:
3535:
3536: /************* Higher Matrix Product ***************/
3537:
1.235 brouard 3538: 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 3539: {
1.336 brouard 3540: /* Already optimized with precov.
3541: 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 3542: 'nhstepm*hstepm*stepm' months (i.e. until
3543: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3544: nhstepm*hstepm matrices.
3545: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3546: (typically every 2 years instead of every month which is too big
3547: for the memory).
3548: Model is determined by parameters x and covariates have to be
3549: included manually here.
3550:
3551: */
3552:
1.330 brouard 3553: int i, j, d, h, k, k1;
1.131 brouard 3554: double **out, cov[NCOVMAX+1];
1.126 brouard 3555: double **newm;
1.187 brouard 3556: double agexact;
1.214 brouard 3557: double agebegin, ageend;
1.126 brouard 3558:
3559: /* Hstepm could be zero and should return the unit matrix */
3560: for (i=1;i<=nlstate+ndeath;i++)
3561: for (j=1;j<=nlstate+ndeath;j++){
3562: oldm[i][j]=(i==j ? 1.0 : 0.0);
3563: po[i][j][0]=(i==j ? 1.0 : 0.0);
3564: }
3565: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3566: for(h=1; h <=nhstepm; h++){
3567: for(d=1; d <=hstepm; d++){
3568: newm=savm;
3569: /* Covariates have to be included here again */
3570: cov[1]=1.;
1.214 brouard 3571: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3572: cov[2]=agexact;
1.319 brouard 3573: if(nagesqr==1){
1.227 brouard 3574: cov[3]= agexact*agexact;
1.319 brouard 3575: }
1.330 brouard 3576: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
3577: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
3578: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.332 brouard 3579: if(Typevar[k1]==1){ /* A product with age */
3580: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
3581: }else{
3582: cov[2+nagesqr+k1]=precov[nres][k1];
3583: }
3584: }/* End of loop on model equation */
3585: /* Old code */
3586: /* if( Dummy[k1]==0 && Typevar[k1]==0 ){ /\* Single dummy *\/ */
3587: /* /\* V(Tvarsel)=Tvalsel=Tresult[nres][pos](value); V(Tvresult[nres][pos] (variable): V(variable)=value) *\/ */
3588: /* /\* for (k=1; k<=nsd;k++) { /\\* For single dummy covariates only *\\/ *\/ */
3589: /* /\* /\\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\\/ *\/ */
3590: /* /\* codtabm(ij,k) (1 & (ij-1) >> (k-1))+1 *\/ */
3591: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3592: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3593: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
3594: /* /\* nsd 1 2 3 *\/ /\* Counting single dummies covar fixed or tv *\/ */
3595: /* /\*TvarsD[nsd] 4 3 1 *\/ /\* ID of single dummy cova fixed or timevary*\/ */
3596: /* /\*TvarsDind[k] 2 3 9 *\/ /\* position K of single dummy cova *\/ */
3597: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];or [codtabm(ij,TnsdVar[TvarsD[k]] *\/ */
3598: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
3599: /* /\* 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]])); *\/ */
3600: /* 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); */
3601: /* printf("hpxij new Dummy precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3602: /* }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /\* Single quantitative variables *\/ */
3603: /* /\* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline *\/ */
3604: /* cov[2+nagesqr+k1]=Tqresult[nres][resultmodel[nres][k1]]; */
3605: /* /\* for (k=1; k<=nsq;k++) { /\\* For single varying covariates only *\\/ *\/ */
3606: /* /\* /\\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\\/ *\/ */
3607: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
3608: /* 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]]); */
3609: /* printf("hpxij new Quanti precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3610: /* }else if( Dummy[k1]==2 ){ /\* For dummy with age product *\/ */
3611: /* /\* Tvar[k1] Variable in the age product age*V1 is 1 *\/ */
3612: /* /\* [Tinvresult[nres][V1] is its value in the resultline nres *\/ */
3613: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvar[k1]]*cov[2]; */
3614: /* 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]); */
3615: /* printf("hpxij new Dummy with age product precov[nres=%d][k1=%d]=%.4f * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
3616:
3617: /* /\* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; *\/ */
3618: /* /\* for (k=1; k<=cptcovage;k++){ /\\* For product with age V1+V1*age +V4 +age*V3 *\\/ *\/ */
3619: /* /\* 1+2 Tage[1]=2 TVar[2]=1 Dummy[2]=2, Tage[2]=4 TVar[4]=3 Dummy[4]=3 quant*\/ */
3620: /* /\* *\/ */
1.330 brouard 3621: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3622: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3623: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
1.332 brouard 3624: /* /\*cptcovage=2 1 2 *\/ */
3625: /* /\*Tage[k]= 5 8 *\/ */
3626: /* }else if( Dummy[k1]==3 ){ /\* For quant with age product *\/ */
3627: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
3628: /* 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]]); */
3629: /* printf("hpxij new Quanti with age product precov[nres=%d][k1=%d] * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
3630: /* /\* if(Dummy[Tage[k]]== 2){ /\\* dummy with age *\\/ *\/ */
3631: /* /\* /\\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\\* dummy with age *\\\/ *\\/ *\/ */
3632: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\\/ *\/ */
3633: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\\/ *\/ */
3634: /* /\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\/ */
3635: /* /\* 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); *\/ */
3636: /* /\* } else if(Dummy[Tage[k]]== 3){ /\\* quantitative with age *\\/ *\/ */
3637: /* /\* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; *\/ */
3638: /* /\* } *\/ */
3639: /* /\* 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]); *\/ */
3640: /* }else if(Typevar[k1]==2 ){ /\* For product (not with age) *\/ */
3641: /* /\* for (k=1; k<=cptcovprod;k++){ /\\* For product without age *\\/ *\/ */
3642: /* /\* /\\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\\/ *\/ */
3643: /* /\* /\\* k 1 2 3 4 5 6 7 8 9 *\\/ *\/ */
3644: /* /\* /\\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\\/ *\/ */
3645: /* /\* /\\*cptcovprod=1 1 2 *\\/ *\/ */
3646: /* /\* /\\*Tprod[]= 4 7 *\\/ *\/ */
3647: /* /\* /\\*Tvard[][1] 4 1 *\\/ *\/ */
3648: /* /\* /\\*Tvard[][2] 3 2 *\\/ *\/ */
1.330 brouard 3649:
1.332 brouard 3650: /* /\* 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])]); *\/ */
3651: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3652: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]]; */
3653: /* 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]]); */
3654: /* printf("hpxij new Product no age product precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3655:
3656: /* /\* if(Dummy[Tvardk[k1][1]]==0){ *\/ */
3657: /* /\* if(Dummy[Tvardk[k1][2]]==0){ /\\* Product of dummies *\\/ *\/ */
3658: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3659: /* /\* cov[2+nagesqr+k1]=Tinvresult[nres][Tvardk[k1][1]] * Tinvresult[nres][Tvardk[k1][2]]; *\/ */
3660: /* /\* 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]])]; *\/ */
3661: /* /\* }else{ /\\* Product of dummy by quantitative *\\/ *\/ */
3662: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,TnsdVar[Tvard[k][1]])] * Tqresult[nres][k]; *\/ */
3663: /* /\* cov[2+nagesqr+k1]=Tresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]]; *\/ */
3664: /* /\* } *\/ */
3665: /* /\* }else{ /\\* Product of quantitative by...*\\/ *\/ */
3666: /* /\* if(Dummy[Tvard[k][2]]==0){ /\\* quant by dummy *\\/ *\/ */
3667: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][Tvard[k][1]]; *\\/ *\/ */
3668: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
3669: /* /\* }else{ /\\* Product of two quant *\\/ *\/ */
3670: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\\/ *\/ */
3671: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
3672: /* /\* } *\/ */
3673: /* /\* }/\\*end of products quantitative *\\/ *\/ */
3674: /* }/\*end of products *\/ */
3675: /* } /\* End of loop on model equation *\/ */
1.235 brouard 3676: /* for (k=1; k<=cptcovn;k++) */
3677: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3678: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3679: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3680: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3681: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3682:
3683:
1.126 brouard 3684: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3685: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.319 brouard 3686: /* right multiplication of oldm by the current matrix */
1.126 brouard 3687: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3688: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3689: /* if((int)age == 70){ */
3690: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3691: /* for(i=1; i<=nlstate+ndeath; i++) { */
3692: /* printf("%d pmmij ",i); */
3693: /* for(j=1;j<=nlstate+ndeath;j++) { */
3694: /* printf("%f ",pmmij[i][j]); */
3695: /* } */
3696: /* printf(" oldm "); */
3697: /* for(j=1;j<=nlstate+ndeath;j++) { */
3698: /* printf("%f ",oldm[i][j]); */
3699: /* } */
3700: /* printf("\n"); */
3701: /* } */
3702: /* } */
1.126 brouard 3703: savm=oldm;
3704: oldm=newm;
3705: }
3706: for(i=1; i<=nlstate+ndeath; i++)
3707: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3708: po[i][j][h]=newm[i][j];
3709: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3710: }
1.128 brouard 3711: /*printf("h=%d ",h);*/
1.126 brouard 3712: } /* end h */
1.267 brouard 3713: /* printf("\n H=%d \n",h); */
1.126 brouard 3714: return po;
3715: }
3716:
1.217 brouard 3717: /************* Higher Back Matrix Product ***************/
1.218 brouard 3718: /* 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 3719: 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 3720: {
1.332 brouard 3721: /* For dummy covariates given in each resultline (for historical, computes the corresponding combination ij),
3722: computes the transition matrix starting at age 'age' over
1.217 brouard 3723: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3724: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3725: nhstepm*hstepm matrices.
3726: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3727: (typically every 2 years instead of every month which is too big
1.217 brouard 3728: for the memory).
1.218 brouard 3729: Model is determined by parameters x and covariates have to be
1.266 brouard 3730: included manually here. Then we use a call to bmij(x and cov)
3731: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3732: */
1.217 brouard 3733:
1.332 brouard 3734: int i, j, d, h, k, k1;
1.266 brouard 3735: double **out, cov[NCOVMAX+1], **bmij();
3736: double **newm, ***newmm;
1.217 brouard 3737: double agexact;
3738: double agebegin, ageend;
1.222 brouard 3739: double **oldm, **savm;
1.217 brouard 3740:
1.266 brouard 3741: newmm=po; /* To be saved */
3742: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3743: /* Hstepm could be zero and should return the unit matrix */
3744: for (i=1;i<=nlstate+ndeath;i++)
3745: for (j=1;j<=nlstate+ndeath;j++){
3746: oldm[i][j]=(i==j ? 1.0 : 0.0);
3747: po[i][j][0]=(i==j ? 1.0 : 0.0);
3748: }
3749: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3750: for(h=1; h <=nhstepm; h++){
3751: for(d=1; d <=hstepm; d++){
3752: newm=savm;
3753: /* Covariates have to be included here again */
3754: cov[1]=1.;
1.271 brouard 3755: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3756: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
1.318 brouard 3757: /* Debug */
3758: /* printf("hBxij age=%lf, agexact=%lf\n", age, agexact); */
1.217 brouard 3759: cov[2]=agexact;
1.332 brouard 3760: if(nagesqr==1){
1.222 brouard 3761: cov[3]= agexact*agexact;
1.332 brouard 3762: }
3763: /** New code */
3764: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
3765: if(Typevar[k1]==1){ /* A product with age */
3766: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.325 brouard 3767: }else{
1.332 brouard 3768: cov[2+nagesqr+k1]=precov[nres][k1];
1.325 brouard 3769: }
1.332 brouard 3770: }/* End of loop on model equation */
3771: /** End of new code */
3772: /** This was old code */
3773: /* for (k=1; k<=nsd;k++){ /\* For single dummy covariates only *\//\* cptcovn error *\/ */
3774: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
3775: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
3776: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])];/\* Bug valgrind *\/ */
3777: /* /\* 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)); *\/ */
3778: /* } */
3779: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
3780: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3781: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
3782: /* /\* 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]); *\/ */
3783: /* } */
3784: /* for (k=1; k<=cptcovage;k++){ /\* Should start at cptcovn+1 *\//\* For product with age *\/ */
3785: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age error!!!*\\/ *\/ */
3786: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
3787: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3788: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
3789: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3790: /* } */
3791: /* /\* 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]); *\/ */
3792: /* } */
3793: /* for (k=1; k<=cptcovprod;k++){ /\* Useless because included in cptcovn *\/ */
3794: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])]*nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3795: /* if(Dummy[Tvard[k][1]]==0){ */
3796: /* if(Dummy[Tvard[k][2]]==0){ */
3797: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][1])]; */
3798: /* }else{ */
3799: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3800: /* } */
3801: /* }else{ */
3802: /* if(Dummy[Tvard[k][2]]==0){ */
3803: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3804: /* }else{ */
3805: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3806: /* } */
3807: /* } */
3808: /* } */
3809: /* /\*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*\/ */
3810: /* /\*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*\/ */
3811: /** End of old code */
3812:
1.218 brouard 3813: /* Careful transposed matrix */
1.266 brouard 3814: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3815: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3816: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3817: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.325 brouard 3818: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);/* Bug valgrind */
1.217 brouard 3819: /* if((int)age == 70){ */
3820: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3821: /* for(i=1; i<=nlstate+ndeath; i++) { */
3822: /* printf("%d pmmij ",i); */
3823: /* for(j=1;j<=nlstate+ndeath;j++) { */
3824: /* printf("%f ",pmmij[i][j]); */
3825: /* } */
3826: /* printf(" oldm "); */
3827: /* for(j=1;j<=nlstate+ndeath;j++) { */
3828: /* printf("%f ",oldm[i][j]); */
3829: /* } */
3830: /* printf("\n"); */
3831: /* } */
3832: /* } */
3833: savm=oldm;
3834: oldm=newm;
3835: }
3836: for(i=1; i<=nlstate+ndeath; i++)
3837: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3838: po[i][j][h]=newm[i][j];
1.268 brouard 3839: /* if(h==nhstepm) */
3840: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3841: }
1.268 brouard 3842: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3843: } /* end h */
1.268 brouard 3844: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3845: return po;
3846: }
3847:
3848:
1.162 brouard 3849: #ifdef NLOPT
3850: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3851: double fret;
3852: double *xt;
3853: int j;
3854: myfunc_data *d2 = (myfunc_data *) pd;
3855: /* xt = (p1-1); */
3856: xt=vector(1,n);
3857: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3858:
3859: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3860: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3861: printf("Function = %.12lf ",fret);
3862: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3863: printf("\n");
3864: free_vector(xt,1,n);
3865: return fret;
3866: }
3867: #endif
1.126 brouard 3868:
3869: /*************** log-likelihood *************/
3870: double func( double *x)
3871: {
1.336 brouard 3872: int i, ii, j, k, mi, d, kk, kf=0;
1.226 brouard 3873: int ioffset=0;
1.339 ! brouard 3874: int ipos=0,iposold=0,ncovv=0;
! 3875:
1.226 brouard 3876: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3877: double **out;
3878: double lli; /* Individual log likelihood */
3879: int s1, s2;
1.228 brouard 3880: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
1.336 brouard 3881:
1.226 brouard 3882: double bbh, survp;
3883: double agexact;
1.336 brouard 3884: double agebegin, ageend;
1.226 brouard 3885: /*extern weight */
3886: /* We are differentiating ll according to initial status */
3887: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3888: /*for(i=1;i<imx;i++)
3889: printf(" %d\n",s[4][i]);
3890: */
1.162 brouard 3891:
1.226 brouard 3892: ++countcallfunc;
1.162 brouard 3893:
1.226 brouard 3894: cov[1]=1.;
1.126 brouard 3895:
1.226 brouard 3896: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3897: ioffset=0;
1.226 brouard 3898: if(mle==1){
3899: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3900: /* Computes the values of the ncovmodel covariates of the model
3901: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3902: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3903: to be observed in j being in i according to the model.
3904: */
1.243 brouard 3905: ioffset=2+nagesqr ;
1.233 brouard 3906: /* Fixed */
1.336 brouard 3907: for (kf=1; kf<=ncovf;kf++){ /* For each fixed covariate dummu or quant or prod */
1.319 brouard 3908: /* # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi */
3909: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
3910: /* 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 3911: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.336 brouard 3912: cov[ioffset+TvarFind[kf]]=covar[Tvar[TvarFind[kf]]][i];/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, only V1 is fixed (TvarFind[1]=6)*/
1.319 brouard 3913: /* V1*V2 (7) TvarFind[2]=7, TvarFind[3]=9 */
1.234 brouard 3914: }
1.226 brouard 3915: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
1.319 brouard 3916: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
1.226 brouard 3917: has been calculated etc */
3918: /* For an individual i, wav[i] gives the number of effective waves */
3919: /* We compute the contribution to Likelihood of each effective transition
3920: mw[mi][i] is real wave of the mi th effectve wave */
3921: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3922: s2=s[mw[mi+1][i]][i];
3923: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i]
3924: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3925: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3926: */
1.336 brouard 3927: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
3928: /* Wave varying (but not age varying) */
1.339 ! brouard 3929: /* 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*\/ */
! 3930: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; but where is the crossproduct? *\/ */
! 3931: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
! 3932: /* } */
! 3933: for(ncovv=1, ipos=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age )*/
! 3934: itv=TvarVV[ncovv]; /* TvarVV={3, 1, 3} */
! 3935: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] */
! 3936: if(ipos!=iposold){ /* Not a product or first of a product */
! 3937: /* TvarFind={1,0,0,0} */
! 3938: if(TvarFind[itv]==0){
! 3939: cov[ioffset+ipos]= cotvar[mw[mi][i]][ncovv][i]; /* Should be covar if fixed covar[Tvar[TvarFind[itv]]][i]*/
! 3940: }else{
! 3941: cov[ioffset+ipos]=covar[Tvar[TvarFind[itv]]][i];
! 3942: }
! 3943: }else{
! 3944: if(TvarFind[itv]==0){
! 3945: cov[ioffset+ipos]*= cotvar[mw[mi][i]][ncovv][i]; /* Should be covar if fixed covar[Tvar[TvarFind[itv]]][i]*/
! 3946: }else{
! 3947: cov[ioffset+ipos]*=covar[Tvar[TvarFind[itv]]][i];
! 3948: }
! 3949: }
! 3950: iposold=ipos;
! 3951: /* For products */
1.234 brouard 3952: }
1.339 ! brouard 3953: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
! 3954: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
! 3955: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
! 3956: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
! 3957: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
! 3958: /* 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]); */
! 3959: /* } */
! 3960: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
! 3961: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
! 3962: /* /\* 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]); *\/ */
! 3963: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
! 3964: /* } */
! 3965: /* for products of time varying to be done */
1.234 brouard 3966: for (ii=1;ii<=nlstate+ndeath;ii++)
3967: for (j=1;j<=nlstate+ndeath;j++){
3968: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3969: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3970: }
1.336 brouard 3971:
3972: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
3973: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
1.234 brouard 3974: for(d=0; d<dh[mi][i]; d++){
3975: newm=savm;
3976: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3977: cov[2]=agexact;
3978: if(nagesqr==1)
3979: cov[3]= agexact*agexact; /* Should be changed here */
3980: for (kk=1; kk<=cptcovage;kk++) {
1.318 brouard 3981: if(!FixedV[Tvar[Tage[kk]]])
3982: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
3983: else
1.339 ! brouard 3984: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]*agexact;
1.234 brouard 3985: }
3986: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3987: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3988: savm=oldm;
3989: oldm=newm;
3990: } /* end mult */
3991:
3992: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
3993: /* But now since version 0.9 we anticipate for bias at large stepm.
3994: * If stepm is larger than one month (smallest stepm) and if the exact delay
3995: * (in months) between two waves is not a multiple of stepm, we rounded to
3996: * the nearest (and in case of equal distance, to the lowest) interval but now
3997: * we keep into memory the bias bh[mi][i] and also the previous matrix product
3998: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
3999: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 4000: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
4001: * -stepm/2 to stepm/2 .
4002: * For stepm=1 the results are the same as for previous versions of Imach.
4003: * For stepm > 1 the results are less biased than in previous versions.
4004: */
1.234 brouard 4005: s1=s[mw[mi][i]][i];
4006: s2=s[mw[mi+1][i]][i];
4007: bbh=(double)bh[mi][i]/(double)stepm;
4008: /* bias bh is positive if real duration
4009: * is higher than the multiple of stepm and negative otherwise.
4010: */
4011: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
4012: if( s2 > nlstate){
4013: /* i.e. if s2 is a death state and if the date of death is known
4014: then the contribution to the likelihood is the probability to
4015: die between last step unit time and current step unit time,
4016: which is also equal to probability to die before dh
4017: minus probability to die before dh-stepm .
4018: In version up to 0.92 likelihood was computed
4019: as if date of death was unknown. Death was treated as any other
4020: health state: the date of the interview describes the actual state
4021: and not the date of a change in health state. The former idea was
4022: to consider that at each interview the state was recorded
4023: (healthy, disable or death) and IMaCh was corrected; but when we
4024: introduced the exact date of death then we should have modified
4025: the contribution of an exact death to the likelihood. This new
4026: contribution is smaller and very dependent of the step unit
4027: stepm. It is no more the probability to die between last interview
4028: and month of death but the probability to survive from last
4029: interview up to one month before death multiplied by the
4030: probability to die within a month. Thanks to Chris
4031: Jackson for correcting this bug. Former versions increased
4032: mortality artificially. The bad side is that we add another loop
4033: which slows down the processing. The difference can be up to 10%
4034: lower mortality.
4035: */
4036: /* If, at the beginning of the maximization mostly, the
4037: cumulative probability or probability to be dead is
4038: constant (ie = 1) over time d, the difference is equal to
4039: 0. out[s1][3] = savm[s1][3]: probability, being at state
4040: s1 at precedent wave, to be dead a month before current
4041: wave is equal to probability, being at state s1 at
4042: precedent wave, to be dead at mont of the current
4043: wave. Then the observed probability (that this person died)
4044: is null according to current estimated parameter. In fact,
4045: it should be very low but not zero otherwise the log go to
4046: infinity.
4047: */
1.183 brouard 4048: /* #ifdef INFINITYORIGINAL */
4049: /* lli=log(out[s1][s2] - savm[s1][s2]); */
4050: /* #else */
4051: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
4052: /* lli=log(mytinydouble); */
4053: /* else */
4054: /* lli=log(out[s1][s2] - savm[s1][s2]); */
4055: /* #endif */
1.226 brouard 4056: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4057:
1.226 brouard 4058: } else if ( s2==-1 ) { /* alive */
4059: for (j=1,survp=0. ; j<=nlstate; j++)
4060: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4061: /*survp += out[s1][j]; */
4062: lli= log(survp);
4063: }
1.336 brouard 4064: /* else if (s2==-4) { */
4065: /* for (j=3,survp=0. ; j<=nlstate; j++) */
4066: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
4067: /* lli= log(survp); */
4068: /* } */
4069: /* else if (s2==-5) { */
4070: /* for (j=1,survp=0. ; j<=2; j++) */
4071: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
4072: /* lli= log(survp); */
4073: /* } */
1.226 brouard 4074: else{
4075: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4076: /* 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 */
4077: }
4078: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
4079: /*if(lli ==000.0)*/
4080: /*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); */
4081: ipmx +=1;
4082: sw += weight[i];
4083: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4084: /* if (lli < log(mytinydouble)){ */
4085: /* 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); */
4086: /* 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]); */
4087: /* } */
4088: } /* end of wave */
4089: } /* end of individual */
4090: } else if(mle==2){
4091: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.319 brouard 4092: ioffset=2+nagesqr ;
4093: for (k=1; k<=ncovf;k++)
4094: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];
1.226 brouard 4095: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 4096: for(k=1; k <= ncovv ; k++){
4097: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
4098: }
1.226 brouard 4099: for (ii=1;ii<=nlstate+ndeath;ii++)
4100: for (j=1;j<=nlstate+ndeath;j++){
4101: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4102: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4103: }
4104: for(d=0; d<=dh[mi][i]; d++){
4105: newm=savm;
4106: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4107: cov[2]=agexact;
4108: if(nagesqr==1)
4109: cov[3]= agexact*agexact;
4110: for (kk=1; kk<=cptcovage;kk++) {
4111: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4112: }
4113: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4114: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4115: savm=oldm;
4116: oldm=newm;
4117: } /* end mult */
4118:
4119: s1=s[mw[mi][i]][i];
4120: s2=s[mw[mi+1][i]][i];
4121: bbh=(double)bh[mi][i]/(double)stepm;
4122: 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 */
4123: ipmx +=1;
4124: sw += weight[i];
4125: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4126: } /* end of wave */
4127: } /* end of individual */
4128: } else if(mle==3){ /* exponential inter-extrapolation */
4129: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4130: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4131: for(mi=1; mi<= wav[i]-1; mi++){
4132: for (ii=1;ii<=nlstate+ndeath;ii++)
4133: for (j=1;j<=nlstate+ndeath;j++){
4134: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4135: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4136: }
4137: for(d=0; d<dh[mi][i]; d++){
4138: newm=savm;
4139: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4140: cov[2]=agexact;
4141: if(nagesqr==1)
4142: cov[3]= agexact*agexact;
4143: for (kk=1; kk<=cptcovage;kk++) {
4144: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4145: }
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: bbh=(double)bh[mi][i]/(double)stepm;
4155: 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 */
4156: ipmx +=1;
4157: sw += weight[i];
4158: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4159: } /* end of wave */
4160: } /* end of individual */
4161: }else if (mle==4){ /* ml=4 no inter-extrapolation */
4162: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4163: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4164: for(mi=1; mi<= wav[i]-1; mi++){
4165: for (ii=1;ii<=nlstate+ndeath;ii++)
4166: for (j=1;j<=nlstate+ndeath;j++){
4167: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4168: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4169: }
4170: for(d=0; d<dh[mi][i]; d++){
4171: newm=savm;
4172: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4173: cov[2]=agexact;
4174: if(nagesqr==1)
4175: cov[3]= agexact*agexact;
4176: for (kk=1; kk<=cptcovage;kk++) {
4177: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4178: }
1.126 brouard 4179:
1.226 brouard 4180: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4181: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4182: savm=oldm;
4183: oldm=newm;
4184: } /* end mult */
4185:
4186: s1=s[mw[mi][i]][i];
4187: s2=s[mw[mi+1][i]][i];
4188: if( s2 > nlstate){
4189: lli=log(out[s1][s2] - savm[s1][s2]);
4190: } else if ( s2==-1 ) { /* alive */
4191: for (j=1,survp=0. ; j<=nlstate; j++)
4192: survp += out[s1][j];
4193: lli= log(survp);
4194: }else{
4195: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4196: }
4197: ipmx +=1;
4198: sw += weight[i];
4199: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.126 brouard 4200: /* 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 4201: } /* end of wave */
4202: } /* end of individual */
4203: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
4204: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4205: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4206: for(mi=1; mi<= wav[i]-1; mi++){
4207: for (ii=1;ii<=nlstate+ndeath;ii++)
4208: for (j=1;j<=nlstate+ndeath;j++){
4209: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4210: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4211: }
4212: for(d=0; d<dh[mi][i]; d++){
4213: newm=savm;
4214: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4215: cov[2]=agexact;
4216: if(nagesqr==1)
4217: cov[3]= agexact*agexact;
4218: for (kk=1; kk<=cptcovage;kk++) {
4219: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4220: }
1.126 brouard 4221:
1.226 brouard 4222: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4223: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4224: savm=oldm;
4225: oldm=newm;
4226: } /* end mult */
4227:
4228: s1=s[mw[mi][i]][i];
4229: s2=s[mw[mi+1][i]][i];
4230: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4231: ipmx +=1;
4232: sw += weight[i];
4233: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4234: /*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]);*/
4235: } /* end of wave */
4236: } /* end of individual */
4237: } /* End of if */
4238: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
4239: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
4240: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4241: return -l;
1.126 brouard 4242: }
4243:
4244: /*************** log-likelihood *************/
4245: double funcone( double *x)
4246: {
1.228 brouard 4247: /* Same as func but slower because of a lot of printf and if */
1.335 brouard 4248: int i, ii, j, k, mi, d, kk, kf=0;
1.228 brouard 4249: int ioffset=0;
1.339 ! brouard 4250: int ipos=0,iposold=0,ncovv=0;
! 4251:
1.131 brouard 4252: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 4253: double **out;
4254: double lli; /* Individual log likelihood */
4255: double llt;
4256: int s1, s2;
1.228 brouard 4257: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
4258:
1.126 brouard 4259: double bbh, survp;
1.187 brouard 4260: double agexact;
1.214 brouard 4261: double agebegin, ageend;
1.126 brouard 4262: /*extern weight */
4263: /* We are differentiating ll according to initial status */
4264: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
4265: /*for(i=1;i<imx;i++)
4266: printf(" %d\n",s[4][i]);
4267: */
4268: cov[1]=1.;
4269:
4270: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 4271: ioffset=0;
4272: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.336 brouard 4273: /* Computes the values of the ncovmodel covariates of the model
4274: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
4275: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
4276: to be observed in j being in i according to the model.
4277: */
1.243 brouard 4278: /* ioffset=2+nagesqr+cptcovage; */
4279: ioffset=2+nagesqr;
1.232 brouard 4280: /* Fixed */
1.224 brouard 4281: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 4282: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
1.335 brouard 4283: for (kf=1; kf<=ncovf;kf++){ /* Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */
1.339 ! brouard 4284: /* printf("Debug3 TvarFind[%d]=%d",kf, TvarFind[kf]); */
! 4285: /* printf(" Tvar[TvarFind[kf]]=%d", Tvar[TvarFind[kf]]); */
! 4286: /* printf(" i=%d covar[Tvar[TvarFind[kf]]][i]=%f\n",i,covar[Tvar[TvarFind[kf]]][i]); */
1.335 brouard 4287: cov[ioffset+TvarFind[kf]]=covar[Tvar[TvarFind[kf]]][i];/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, only V1 is fixed (k=6)*/
1.232 brouard 4288: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
4289: /* cov[2+6]=covar[Tvar[6]][i]; */
4290: /* cov[2+6]=covar[2][i]; V2 */
4291: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
4292: /* cov[2+7]=covar[Tvar[7]][i]; */
4293: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
4294: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
4295: /* cov[2+9]=covar[Tvar[9]][i]; */
4296: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 4297: }
1.336 brouard 4298: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
4299: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
4300: has been calculated etc */
4301: /* For an individual i, wav[i] gives the number of effective waves */
4302: /* We compute the contribution to Likelihood of each effective transition
4303: mw[mi][i] is real wave of the mi th effectve wave */
4304: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
4305: s2=s[mw[mi+1][i]][i];
4306: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i]
4307: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
4308: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
4309: */
4310: /* This part may be useless now because everythin should be in covar */
1.232 brouard 4311: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
4312: /* 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?)*\/ */
4313: /* } */
1.231 brouard 4314: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
4315: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
4316: /* } */
1.225 brouard 4317:
1.233 brouard 4318:
4319: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.339 ! brouard 4320: /* Wave varying (but not age varying) *//* V1+V3+age*V1+age*V3+V1*V3 with V4 tv and V5 tvq k= 1 to 5 and extra at V(5+1)=6 for V1*V3 */
! 4321: /* for(k=1; k <= ncovv ; k++){ /\* Varying covariates (single and product but no age )*\/ */
! 4322: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; *\/ */
! 4323: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
! 4324: /* } */
! 4325:
! 4326: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
! 4327: /* model V1+V3+age*V1+age*V3+V1*V3 */
! 4328: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
! 4329: /* TvarVV[1]=V3 (first time varying in the model equation, TvarVV[2]=V1 (in V1*V3) TvarVV[3]=3(V3) */
! 4330: /* We need the position of the time varying or product in the model */
! 4331: /* TvarVVind={2,5,5}, for V3 at position 2 and then the product V1*V3 is decomposed into V1 and V3 but at same position 5 */
! 4332: /* TvarVV gives the variable name */
! 4333: for(ncovv=1, ipos=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age )*/
! 4334: itv=TvarVV[ncovv]; /* TvarVV={3, 1, 3} */
! 4335: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] */
! 4336: if(ipos!=iposold){ /* Not a product or first of a product */
! 4337: /* TvarFind={1,0,0,0} */
! 4338: if(TvarFind[itv]==0){
! 4339: cov[ioffset+ipos]= cotvar[mw[mi][i]][ncovv][i]; /* Should be covar if fixed covar[Tvar[TvarFind[itv]]][i]*/
! 4340: }else{
! 4341: cov[ioffset+ipos]=covar[Tvar[TvarFind[itv]]][i];
! 4342: }
! 4343: }else{
! 4344: if(TvarFind[itv]==0){
! 4345: cov[ioffset+ipos]*= cotvar[mw[mi][i]][ncovv][i]; /* Should be covar if fixed covar[Tvar[TvarFind[itv]]][i]*/
! 4346: }else{
! 4347: cov[ioffset+ipos]*=covar[Tvar[TvarFind[itv]]][i];
! 4348: }
! 4349: }
! 4350: iposold=ipos;
! 4351: /* For products */
! 4352: }
! 4353: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates single *\/ */
! 4354: /* iv=TvarVDind[itv]; /\* iv, position in the model equation of time varying covariate itv *\/ */
! 4355: /* /\* "V1+V3+age*V1+age*V3+V1*V3" with V3 time varying *\/ */
! 4356: /* /\* 1 2 3 4 5 *\/ */
! 4357: /* /\*itv 1 *\/ */
! 4358: /* /\* TvarVInd[1]= 2 *\/ */
! 4359: /* /\* iv= Tvar[Tmodelind[itv]]-ncovcol-nqv; /\\* Counting the # varying covariate from 1 to ntveff *\\/ *\/ */
! 4360: /* /\* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; *\/ */
! 4361: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; *\/ */
! 4362: /* /\* k=ioffset-2-nagesqr-cptcovage+itv; /\\* position in simple model *\\/ *\/ */
! 4363: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; *\/ */
! 4364: /* cov[ioffset+iv]=cotvar[mw[mi][i]][itv][i]; */
! 4365: /* /\* printf(" i=%d,mi=%d,itv=%d,TmodelInvind[itv]=%d,cotvar[mw[mi][i]][itv][i]=%f\n", i, mi, itv, TvarVDind[itv],cotvar[mw[mi][i]][itv][i]); *\/ */
! 4366: /* } */
1.232 brouard 4367: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 4368: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4369: /* /\* 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]); *\/ */
4370: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 4371: /* } */
1.126 brouard 4372: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 4373: for (j=1;j<=nlstate+ndeath;j++){
4374: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4375: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4376: }
1.214 brouard 4377:
4378: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4379: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
4380: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 4381: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 4382: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
4383: and mw[mi+1][i]. dh depends on stepm.*/
4384: newm=savm;
1.247 brouard 4385: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 4386: cov[2]=agexact;
4387: if(nagesqr==1)
4388: cov[3]= agexact*agexact;
4389: for (kk=1; kk<=cptcovage;kk++) {
4390: if(!FixedV[Tvar[Tage[kk]]])
4391: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4392: else
1.339 ! brouard 4393: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]*agexact;
1.242 brouard 4394: }
4395: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
4396: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
4397: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4398: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4399: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
4400: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
4401: savm=oldm;
4402: oldm=newm;
1.126 brouard 4403: } /* end mult */
1.336 brouard 4404: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
4405: /* But now since version 0.9 we anticipate for bias at large stepm.
4406: * If stepm is larger than one month (smallest stepm) and if the exact delay
4407: * (in months) between two waves is not a multiple of stepm, we rounded to
4408: * the nearest (and in case of equal distance, to the lowest) interval but now
4409: * we keep into memory the bias bh[mi][i] and also the previous matrix product
4410: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
4411: * probability in order to take into account the bias as a fraction of the way
4412: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
4413: * -stepm/2 to stepm/2 .
4414: * For stepm=1 the results are the same as for previous versions of Imach.
4415: * For stepm > 1 the results are less biased than in previous versions.
4416: */
1.126 brouard 4417: s1=s[mw[mi][i]][i];
4418: s2=s[mw[mi+1][i]][i];
1.217 brouard 4419: /* if(s2==-1){ */
1.268 brouard 4420: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 4421: /* /\* exit(1); *\/ */
4422: /* } */
1.126 brouard 4423: bbh=(double)bh[mi][i]/(double)stepm;
4424: /* bias is positive if real duration
4425: * is higher than the multiple of stepm and negative otherwise.
4426: */
4427: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 4428: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4429: } else if ( s2==-1 ) { /* alive */
1.242 brouard 4430: for (j=1,survp=0. ; j<=nlstate; j++)
4431: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4432: lli= log(survp);
1.126 brouard 4433: }else if (mle==1){
1.242 brouard 4434: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 4435: } else if(mle==2){
1.242 brouard 4436: 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 4437: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 4438: 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 4439: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 4440: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 4441: } else{ /* mle=0 back to 1 */
1.242 brouard 4442: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4443: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 4444: } /* End of if */
4445: ipmx +=1;
4446: sw += weight[i];
4447: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.335 brouard 4448: /* printf("Funcone 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],(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2])); */
1.126 brouard 4449: if(globpr){
1.246 brouard 4450: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 4451: %11.6f %11.6f %11.6f ", \
1.242 brouard 4452: 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 4453: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.335 brouard 4454: /* printf("%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\ */
4455: /* %11.6f %11.6f %11.6f ", \ */
4456: /* num[i], agebegin, ageend, i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],weight[i]*gipmx/gsw, */
4457: /* 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2])); */
1.242 brouard 4458: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
4459: llt +=ll[k]*gipmx/gsw;
4460: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
1.335 brouard 4461: /* printf(" %10.6f",-ll[k]*gipmx/gsw); */
1.242 brouard 4462: }
4463: fprintf(ficresilk," %10.6f\n", -llt);
1.335 brouard 4464: /* printf(" %10.6f\n", -llt); */
1.126 brouard 4465: }
1.335 brouard 4466: } /* end of wave */
4467: } /* end of individual */
4468: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
1.232 brouard 4469: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
1.335 brouard 4470: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4471: if(globpr==0){ /* First time we count the contributions and weights */
4472: gipmx=ipmx;
4473: gsw=sw;
4474: }
1.232 brouard 4475: return -l;
1.126 brouard 4476: }
4477:
4478:
4479: /*************** function likelione ***********/
1.292 brouard 4480: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 4481: {
4482: /* This routine should help understanding what is done with
4483: the selection of individuals/waves and
4484: to check the exact contribution to the likelihood.
4485: Plotting could be done.
4486: */
4487: int k;
4488:
4489: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 4490: strcpy(fileresilk,"ILK_");
1.202 brouard 4491: strcat(fileresilk,fileresu);
1.126 brouard 4492: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
4493: printf("Problem with resultfile: %s\n", fileresilk);
4494: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
4495: }
1.214 brouard 4496: 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");
4497: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 4498: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
4499: for(k=1; k<=nlstate; k++)
4500: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
4501: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n");
4502: }
4503:
1.292 brouard 4504: *fretone=(*func)(p);
1.126 brouard 4505: if(*globpri !=0){
4506: fclose(ficresilk);
1.205 brouard 4507: if (mle ==0)
4508: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
4509: else if(mle >=1)
4510: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
4511: 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 4512: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 4513:
4514: for (k=1; k<= nlstate ; k++) {
1.211 brouard 4515: 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 4516: <img src=\"%s-p%dj.png\">",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
4517: }
1.207 brouard 4518: 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 4519: <img src=\"%s-ori.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4520: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.204 brouard 4521: <img src=\"%s-dest.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4522: fflush(fichtm);
1.205 brouard 4523: }
1.126 brouard 4524: return;
4525: }
4526:
4527:
4528: /*********** Maximum Likelihood Estimation ***************/
4529:
4530: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
4531: {
1.319 brouard 4532: int i,j,k, jk, jkk=0, iter=0;
1.126 brouard 4533: double **xi;
4534: double fret;
4535: double fretone; /* Only one call to likelihood */
4536: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 4537:
4538: #ifdef NLOPT
4539: int creturn;
4540: nlopt_opt opt;
4541: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
4542: double *lb;
4543: double minf; /* the minimum objective value, upon return */
4544: double * p1; /* Shifted parameters from 0 instead of 1 */
4545: myfunc_data dinst, *d = &dinst;
4546: #endif
4547:
4548:
1.126 brouard 4549: xi=matrix(1,npar,1,npar);
4550: for (i=1;i<=npar;i++)
4551: for (j=1;j<=npar;j++)
4552: xi[i][j]=(i==j ? 1.0 : 0.0);
4553: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 4554: strcpy(filerespow,"POW_");
1.126 brouard 4555: strcat(filerespow,fileres);
4556: if((ficrespow=fopen(filerespow,"w"))==NULL) {
4557: printf("Problem with resultfile: %s\n", filerespow);
4558: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
4559: }
4560: fprintf(ficrespow,"# Powell\n# iter -2*LL");
4561: for (i=1;i<=nlstate;i++)
4562: for(j=1;j<=nlstate+ndeath;j++)
4563: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
4564: fprintf(ficrespow,"\n");
1.162 brouard 4565: #ifdef POWELL
1.319 brouard 4566: #ifdef LINMINORIGINAL
4567: #else /* LINMINORIGINAL */
4568:
4569: flatdir=ivector(1,npar);
4570: for (j=1;j<=npar;j++) flatdir[j]=0;
4571: #endif /*LINMINORIGINAL */
4572:
4573: #ifdef FLATSUP
4574: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4575: /* reorganizing p by suppressing flat directions */
4576: for(i=1, jk=1; i <=nlstate; i++){
4577: for(k=1; k <=(nlstate+ndeath); k++){
4578: if (k != i) {
4579: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4580: if(flatdir[jk]==1){
4581: printf(" To be skipped %d%d flatdir[%d]=%d ",i,k,jk, flatdir[jk]);
4582: }
4583: for(j=1; j <=ncovmodel; j++){
4584: printf("%12.7f ",p[jk]);
4585: jk++;
4586: }
4587: printf("\n");
4588: }
4589: }
4590: }
4591: /* skipping */
4592: /* for(i=1, jk=1, jkk=1;(flatdir[jk]==0)&& (i <=nlstate); i++){ */
4593: for(i=1, jk=1, jkk=1;i <=nlstate; i++){
4594: for(k=1; k <=(nlstate+ndeath); k++){
4595: if (k != i) {
4596: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4597: if(flatdir[jk]==1){
4598: printf(" To be skipped %d%d flatdir[%d]=%d jk=%d p[%d] ",i,k,jk, flatdir[jk],jk, jk);
4599: for(j=1; j <=ncovmodel; jk++,j++){
4600: printf(" p[%d]=%12.7f",jk, p[jk]);
4601: /*q[jjk]=p[jk];*/
4602: }
4603: }else{
4604: printf(" To be kept %d%d flatdir[%d]=%d jk=%d q[%d]=p[%d] ",i,k,jk, flatdir[jk],jk, jkk, jk);
4605: for(j=1; j <=ncovmodel; jk++,jkk++,j++){
4606: printf(" p[%d]=%12.7f=q[%d]",jk, p[jk],jkk);
4607: /*q[jjk]=p[jk];*/
4608: }
4609: }
4610: printf("\n");
4611: }
4612: fflush(stdout);
4613: }
4614: }
4615: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4616: #else /* FLATSUP */
1.126 brouard 4617: powell(p,xi,npar,ftol,&iter,&fret,func);
1.319 brouard 4618: #endif /* FLATSUP */
4619:
4620: #ifdef LINMINORIGINAL
4621: #else
4622: free_ivector(flatdir,1,npar);
4623: #endif /* LINMINORIGINAL*/
4624: #endif /* POWELL */
1.126 brouard 4625:
1.162 brouard 4626: #ifdef NLOPT
4627: #ifdef NEWUOA
4628: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
4629: #else
4630: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
4631: #endif
4632: lb=vector(0,npar-1);
4633: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
4634: nlopt_set_lower_bounds(opt, lb);
4635: nlopt_set_initial_step1(opt, 0.1);
4636:
4637: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
4638: d->function = func;
4639: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
4640: nlopt_set_min_objective(opt, myfunc, d);
4641: nlopt_set_xtol_rel(opt, ftol);
4642: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
4643: printf("nlopt failed! %d\n",creturn);
4644: }
4645: else {
4646: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
4647: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
4648: iter=1; /* not equal */
4649: }
4650: nlopt_destroy(opt);
4651: #endif
1.319 brouard 4652: #ifdef FLATSUP
4653: /* npared = npar -flatd/ncovmodel; */
4654: /* xired= matrix(1,npared,1,npared); */
4655: /* paramred= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); */
4656: /* powell(pred,xired,npared,ftol,&iter,&fret,flatdir,func); */
4657: /* free_matrix(xire,1,npared,1,npared); */
4658: #else /* FLATSUP */
4659: #endif /* FLATSUP */
1.126 brouard 4660: free_matrix(xi,1,npar,1,npar);
4661: fclose(ficrespow);
1.203 brouard 4662: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
4663: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 4664: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 4665:
4666: }
4667:
4668: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 4669: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 4670: {
4671: double **a,**y,*x,pd;
1.203 brouard 4672: /* double **hess; */
1.164 brouard 4673: int i, j;
1.126 brouard 4674: int *indx;
4675:
4676: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 4677: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 4678: void lubksb(double **a, int npar, int *indx, double b[]) ;
4679: void ludcmp(double **a, int npar, int *indx, double *d) ;
4680: double gompertz(double p[]);
1.203 brouard 4681: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 4682:
4683: printf("\nCalculation of the hessian matrix. Wait...\n");
4684: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
4685: for (i=1;i<=npar;i++){
1.203 brouard 4686: printf("%d-",i);fflush(stdout);
4687: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 4688:
4689: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
4690:
4691: /* printf(" %f ",p[i]);
4692: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
4693: }
4694:
4695: for (i=1;i<=npar;i++) {
4696: for (j=1;j<=npar;j++) {
4697: if (j>i) {
1.203 brouard 4698: printf(".%d-%d",i,j);fflush(stdout);
4699: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
4700: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 4701:
4702: hess[j][i]=hess[i][j];
4703: /*printf(" %lf ",hess[i][j]);*/
4704: }
4705: }
4706: }
4707: printf("\n");
4708: fprintf(ficlog,"\n");
4709:
4710: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
4711: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
4712:
4713: a=matrix(1,npar,1,npar);
4714: y=matrix(1,npar,1,npar);
4715: x=vector(1,npar);
4716: indx=ivector(1,npar);
4717: for (i=1;i<=npar;i++)
4718: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
4719: ludcmp(a,npar,indx,&pd);
4720:
4721: for (j=1;j<=npar;j++) {
4722: for (i=1;i<=npar;i++) x[i]=0;
4723: x[j]=1;
4724: lubksb(a,npar,indx,x);
4725: for (i=1;i<=npar;i++){
4726: matcov[i][j]=x[i];
4727: }
4728: }
4729:
4730: printf("\n#Hessian matrix#\n");
4731: fprintf(ficlog,"\n#Hessian matrix#\n");
4732: for (i=1;i<=npar;i++) {
4733: for (j=1;j<=npar;j++) {
1.203 brouard 4734: printf("%.6e ",hess[i][j]);
4735: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 4736: }
4737: printf("\n");
4738: fprintf(ficlog,"\n");
4739: }
4740:
1.203 brouard 4741: /* printf("\n#Covariance matrix#\n"); */
4742: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
4743: /* for (i=1;i<=npar;i++) { */
4744: /* for (j=1;j<=npar;j++) { */
4745: /* printf("%.6e ",matcov[i][j]); */
4746: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
4747: /* } */
4748: /* printf("\n"); */
4749: /* fprintf(ficlog,"\n"); */
4750: /* } */
4751:
1.126 brouard 4752: /* Recompute Inverse */
1.203 brouard 4753: /* for (i=1;i<=npar;i++) */
4754: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
4755: /* ludcmp(a,npar,indx,&pd); */
4756:
4757: /* printf("\n#Hessian matrix recomputed#\n"); */
4758:
4759: /* for (j=1;j<=npar;j++) { */
4760: /* for (i=1;i<=npar;i++) x[i]=0; */
4761: /* x[j]=1; */
4762: /* lubksb(a,npar,indx,x); */
4763: /* for (i=1;i<=npar;i++){ */
4764: /* y[i][j]=x[i]; */
4765: /* printf("%.3e ",y[i][j]); */
4766: /* fprintf(ficlog,"%.3e ",y[i][j]); */
4767: /* } */
4768: /* printf("\n"); */
4769: /* fprintf(ficlog,"\n"); */
4770: /* } */
4771:
4772: /* Verifying the inverse matrix */
4773: #ifdef DEBUGHESS
4774: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 4775:
1.203 brouard 4776: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
4777: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 4778:
4779: for (j=1;j<=npar;j++) {
4780: for (i=1;i<=npar;i++){
1.203 brouard 4781: printf("%.2f ",y[i][j]);
4782: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 4783: }
4784: printf("\n");
4785: fprintf(ficlog,"\n");
4786: }
1.203 brouard 4787: #endif
1.126 brouard 4788:
4789: free_matrix(a,1,npar,1,npar);
4790: free_matrix(y,1,npar,1,npar);
4791: free_vector(x,1,npar);
4792: free_ivector(indx,1,npar);
1.203 brouard 4793: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 4794:
4795:
4796: }
4797:
4798: /*************** hessian matrix ****************/
4799: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 4800: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 4801: int i;
4802: int l=1, lmax=20;
1.203 brouard 4803: double k1,k2, res, fx;
1.132 brouard 4804: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 4805: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
4806: int k=0,kmax=10;
4807: double l1;
4808:
4809: fx=func(x);
4810: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 4811: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 4812: l1=pow(10,l);
4813: delts=delt;
4814: for(k=1 ; k <kmax; k=k+1){
4815: delt = delta*(l1*k);
4816: p2[theta]=x[theta] +delt;
1.145 brouard 4817: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 4818: p2[theta]=x[theta]-delt;
4819: k2=func(p2)-fx;
4820: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 4821: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 4822:
1.203 brouard 4823: #ifdef DEBUGHESSII
1.126 brouard 4824: 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);
4825: 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);
4826: #endif
4827: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
4828: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
4829: k=kmax;
4830: }
4831: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 4832: k=kmax; l=lmax*10;
1.126 brouard 4833: }
4834: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
4835: delts=delt;
4836: }
1.203 brouard 4837: } /* End loop k */
1.126 brouard 4838: }
4839: delti[theta]=delts;
4840: return res;
4841:
4842: }
4843:
1.203 brouard 4844: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 4845: {
4846: int i;
1.164 brouard 4847: int l=1, lmax=20;
1.126 brouard 4848: double k1,k2,k3,k4,res,fx;
1.132 brouard 4849: double p2[MAXPARM+1];
1.203 brouard 4850: int k, kmax=1;
4851: double v1, v2, cv12, lc1, lc2;
1.208 brouard 4852:
4853: int firstime=0;
1.203 brouard 4854:
1.126 brouard 4855: fx=func(x);
1.203 brouard 4856: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 4857: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 4858: p2[thetai]=x[thetai]+delti[thetai]*k;
4859: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4860: k1=func(p2)-fx;
4861:
1.203 brouard 4862: p2[thetai]=x[thetai]+delti[thetai]*k;
4863: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4864: k2=func(p2)-fx;
4865:
1.203 brouard 4866: p2[thetai]=x[thetai]-delti[thetai]*k;
4867: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4868: k3=func(p2)-fx;
4869:
1.203 brouard 4870: p2[thetai]=x[thetai]-delti[thetai]*k;
4871: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4872: k4=func(p2)-fx;
1.203 brouard 4873: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
4874: if(k1*k2*k3*k4 <0.){
1.208 brouard 4875: firstime=1;
1.203 brouard 4876: kmax=kmax+10;
1.208 brouard 4877: }
4878: if(kmax >=10 || firstime ==1){
1.246 brouard 4879: 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);
4880: 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 4881: 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);
4882: 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);
4883: }
4884: #ifdef DEBUGHESSIJ
4885: v1=hess[thetai][thetai];
4886: v2=hess[thetaj][thetaj];
4887: cv12=res;
4888: /* Computing eigen value of Hessian matrix */
4889: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4890: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4891: if ((lc2 <0) || (lc1 <0) ){
4892: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4893: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4894: 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);
4895: 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);
4896: }
1.126 brouard 4897: #endif
4898: }
4899: return res;
4900: }
4901:
1.203 brouard 4902: /* Not done yet: Was supposed to fix if not exactly at the maximum */
4903: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
4904: /* { */
4905: /* int i; */
4906: /* int l=1, lmax=20; */
4907: /* double k1,k2,k3,k4,res,fx; */
4908: /* double p2[MAXPARM+1]; */
4909: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
4910: /* int k=0,kmax=10; */
4911: /* double l1; */
4912:
4913: /* fx=func(x); */
4914: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
4915: /* l1=pow(10,l); */
4916: /* delts=delt; */
4917: /* for(k=1 ; k <kmax; k=k+1){ */
4918: /* delt = delti*(l1*k); */
4919: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
4920: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4921: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4922: /* k1=func(p2)-fx; */
4923:
4924: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4925: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4926: /* k2=func(p2)-fx; */
4927:
4928: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4929: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4930: /* k3=func(p2)-fx; */
4931:
4932: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4933: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4934: /* k4=func(p2)-fx; */
4935: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
4936: /* #ifdef DEBUGHESSIJ */
4937: /* 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); */
4938: /* 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); */
4939: /* #endif */
4940: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
4941: /* k=kmax; */
4942: /* } */
4943: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
4944: /* k=kmax; l=lmax*10; */
4945: /* } */
4946: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
4947: /* delts=delt; */
4948: /* } */
4949: /* } /\* End loop k *\/ */
4950: /* } */
4951: /* delti[theta]=delts; */
4952: /* return res; */
4953: /* } */
4954:
4955:
1.126 brouard 4956: /************** Inverse of matrix **************/
4957: void ludcmp(double **a, int n, int *indx, double *d)
4958: {
4959: int i,imax,j,k;
4960: double big,dum,sum,temp;
4961: double *vv;
4962:
4963: vv=vector(1,n);
4964: *d=1.0;
4965: for (i=1;i<=n;i++) {
4966: big=0.0;
4967: for (j=1;j<=n;j++)
4968: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 4969: if (big == 0.0){
4970: printf(" Singular Hessian matrix at row %d:\n",i);
4971: for (j=1;j<=n;j++) {
4972: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
4973: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
4974: }
4975: fflush(ficlog);
4976: fclose(ficlog);
4977: nrerror("Singular matrix in routine ludcmp");
4978: }
1.126 brouard 4979: vv[i]=1.0/big;
4980: }
4981: for (j=1;j<=n;j++) {
4982: for (i=1;i<j;i++) {
4983: sum=a[i][j];
4984: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
4985: a[i][j]=sum;
4986: }
4987: big=0.0;
4988: for (i=j;i<=n;i++) {
4989: sum=a[i][j];
4990: for (k=1;k<j;k++)
4991: sum -= a[i][k]*a[k][j];
4992: a[i][j]=sum;
4993: if ( (dum=vv[i]*fabs(sum)) >= big) {
4994: big=dum;
4995: imax=i;
4996: }
4997: }
4998: if (j != imax) {
4999: for (k=1;k<=n;k++) {
5000: dum=a[imax][k];
5001: a[imax][k]=a[j][k];
5002: a[j][k]=dum;
5003: }
5004: *d = -(*d);
5005: vv[imax]=vv[j];
5006: }
5007: indx[j]=imax;
5008: if (a[j][j] == 0.0) a[j][j]=TINY;
5009: if (j != n) {
5010: dum=1.0/(a[j][j]);
5011: for (i=j+1;i<=n;i++) a[i][j] *= dum;
5012: }
5013: }
5014: free_vector(vv,1,n); /* Doesn't work */
5015: ;
5016: }
5017:
5018: void lubksb(double **a, int n, int *indx, double b[])
5019: {
5020: int i,ii=0,ip,j;
5021: double sum;
5022:
5023: for (i=1;i<=n;i++) {
5024: ip=indx[i];
5025: sum=b[ip];
5026: b[ip]=b[i];
5027: if (ii)
5028: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
5029: else if (sum) ii=i;
5030: b[i]=sum;
5031: }
5032: for (i=n;i>=1;i--) {
5033: sum=b[i];
5034: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
5035: b[i]=sum/a[i][i];
5036: }
5037: }
5038:
5039: void pstamp(FILE *fichier)
5040: {
1.196 brouard 5041: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 5042: }
5043:
1.297 brouard 5044: void date2dmy(double date,double *day, double *month, double *year){
5045: double yp=0., yp1=0., yp2=0.;
5046:
5047: yp1=modf(date,&yp);/* extracts integral of date in yp and
5048: fractional in yp1 */
5049: *year=yp;
5050: yp2=modf((yp1*12),&yp);
5051: *month=yp;
5052: yp1=modf((yp2*30.5),&yp);
5053: *day=yp;
5054: if(*day==0) *day=1;
5055: if(*month==0) *month=1;
5056: }
5057:
1.253 brouard 5058:
5059:
1.126 brouard 5060: /************ Frequencies ********************/
1.251 brouard 5061: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 5062: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
5063: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 5064: { /* Some frequencies as well as proposing some starting values */
1.332 brouard 5065: /* Frequencies of any combination of dummy covariate used in the model equation */
1.265 brouard 5066: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 5067: int iind=0, iage=0;
5068: int mi; /* Effective wave */
5069: int first;
5070: double ***freq; /* Frequencies */
1.268 brouard 5071: 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 */
5072: 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 5073: double *meanq, *stdq, *idq;
1.226 brouard 5074: double **meanqt;
5075: double *pp, **prop, *posprop, *pospropt;
5076: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
5077: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
5078: double agebegin, ageend;
5079:
5080: pp=vector(1,nlstate);
1.251 brouard 5081: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 5082: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
5083: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
5084: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
5085: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 5086: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 5087: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 5088: meanqt=matrix(1,lastpass,1,nqtveff);
5089: strcpy(fileresp,"P_");
5090: strcat(fileresp,fileresu);
5091: /*strcat(fileresphtm,fileresu);*/
5092: if((ficresp=fopen(fileresp,"w"))==NULL) {
5093: printf("Problem with prevalence resultfile: %s\n", fileresp);
5094: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
5095: exit(0);
5096: }
1.240 brouard 5097:
1.226 brouard 5098: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
5099: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
5100: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
5101: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
5102: fflush(ficlog);
5103: exit(70);
5104: }
5105: else{
5106: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 5107: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 5108: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 5109: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
5110: }
1.319 brouard 5111: 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 5112:
1.226 brouard 5113: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
5114: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
5115: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
5116: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
5117: fflush(ficlog);
5118: exit(70);
1.240 brouard 5119: } else{
1.226 brouard 5120: 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 5121: ,<hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 5122: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 5123: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
5124: }
1.319 brouard 5125: 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 5126:
1.253 brouard 5127: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
5128: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 5129: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 5130: j1=0;
1.126 brouard 5131:
1.227 brouard 5132: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
1.335 brouard 5133: j=cptcoveff; /* Only simple dummy covariates used in the model */
1.330 brouard 5134: /* j=cptcovn; /\* Only dummy covariates of the model *\/ */
1.226 brouard 5135: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 5136:
5137:
1.226 brouard 5138: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
5139: reference=low_education V1=0,V2=0
5140: med_educ V1=1 V2=0,
5141: high_educ V1=0 V2=1
1.330 brouard 5142: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcovn
1.226 brouard 5143: */
1.249 brouard 5144: dateintsum=0;
5145: k2cpt=0;
5146:
1.253 brouard 5147: if(cptcoveff == 0 )
1.265 brouard 5148: nl=1; /* Constant and age model only */
1.253 brouard 5149: else
5150: nl=2;
1.265 brouard 5151:
5152: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
5153: /* Loop on nj=1 or 2 if dummy covariates j!=0
1.335 brouard 5154: * Loop on j1(1 to 2**cptcoveff) covariate combination
1.265 brouard 5155: * freq[s1][s2][iage] =0.
5156: * Loop on iind
5157: * ++freq[s1][s2][iage] weighted
5158: * end iind
5159: * if covariate and j!0
5160: * headers Variable on one line
5161: * endif cov j!=0
5162: * header of frequency table by age
5163: * Loop on age
5164: * pp[s1]+=freq[s1][s2][iage] weighted
5165: * pos+=freq[s1][s2][iage] weighted
5166: * Loop on s1 initial state
5167: * fprintf(ficresp
5168: * end s1
5169: * end age
5170: * if j!=0 computes starting values
5171: * end compute starting values
5172: * end j1
5173: * end nl
5174: */
1.253 brouard 5175: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
5176: if(nj==1)
5177: j=0; /* First pass for the constant */
1.265 brouard 5178: else{
1.335 brouard 5179: j=cptcoveff; /* Other passes for the covariate values number of simple covariates in the model V2+V1 =2 (simple dummy fixed or time varying) */
1.265 brouard 5180: }
1.251 brouard 5181: first=1;
1.332 brouard 5182: 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 5183: posproptt=0.;
1.330 brouard 5184: /*printf("cptcovn=%d Tvaraff=%d", cptcovn,Tvaraff[1]);
1.251 brouard 5185: scanf("%d", i);*/
5186: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 5187: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 5188: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 5189: freq[i][s2][m]=0;
1.251 brouard 5190:
5191: for (i=1; i<=nlstate; i++) {
1.240 brouard 5192: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 5193: prop[i][m]=0;
5194: posprop[i]=0;
5195: pospropt[i]=0;
5196: }
1.283 brouard 5197: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 5198: idq[z1]=0.;
5199: meanq[z1]=0.;
5200: stdq[z1]=0.;
1.283 brouard 5201: }
5202: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 5203: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 5204: /* meanqt[m][z1]=0.; */
5205: /* } */
5206: /* } */
1.251 brouard 5207: /* dateintsum=0; */
5208: /* k2cpt=0; */
5209:
1.265 brouard 5210: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 5211: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
5212: bool=1;
5213: if(j !=0){
5214: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
1.335 brouard 5215: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
5216: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
1.251 brouard 5217: /* if(Tvaraff[z1] ==-20){ */
5218: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
5219: /* }else if(Tvaraff[z1] ==-10){ */
5220: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
1.330 brouard 5221: /* }else */ /* TODO TODO codtabm(j1,z1) or codtabm(j1,Tvaraff[z1]]z1)*/
1.335 brouard 5222: /* if( iind >=imx-3) printf("Searching error iind=%d Tvaraff[z1]=%d covar[Tvaraff[z1]][iind]=%.f TnsdVar[Tvaraff[z1]]=%d, cptcoveff=%d, cptcovs=%d \n",iind, Tvaraff[z1], covar[Tvaraff[z1]][iind],TnsdVar[Tvaraff[z1]],cptcoveff, cptcovs); */
5223: if(Tvaraff[z1]<1 || Tvaraff[z1]>=NCOVMAX)
1.338 brouard 5224: printf("Error Tvaraff[z1]=%d<1 or >=%d, cptcoveff=%d model=1+age+%s\n",Tvaraff[z1],NCOVMAX, cptcoveff, model);
1.332 brouard 5225: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]){ /* for combination j1 of covariates */
1.265 brouard 5226: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 5227: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
1.332 brouard 5228: /* 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", */
5229: /* bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),*/
5230: /* j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
1.251 brouard 5231: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
5232: } /* Onlyf fixed */
5233: } /* end z1 */
1.335 brouard 5234: } /* cptcoveff > 0 */
1.251 brouard 5235: } /* end any */
5236: }/* end j==0 */
1.265 brouard 5237: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 5238: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 5239: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 5240: m=mw[mi][iind];
5241: if(j!=0){
5242: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
1.335 brouard 5243: for (z1=1; z1<=cptcoveff; z1++) {
1.251 brouard 5244: if( Fixed[Tmodelind[z1]]==1){
5245: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
1.332 brouard 5246: 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 5247: value is -1, we don't select. It differs from the
5248: constant and age model which counts them. */
5249: bool=0; /* not selected */
5250: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
1.334 brouard 5251: /* i1=Tvaraff[z1]; */
5252: /* i2=TnsdVar[i1]; */
5253: /* i3=nbcode[i1][i2]; */
5254: /* i4=covar[i1][iind]; */
5255: /* if(i4 != i3){ */
5256: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) { /* Bug valgrind */
1.251 brouard 5257: bool=0;
5258: }
5259: }
5260: }
5261: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
5262: } /* end j==0 */
5263: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 5264: if(bool==1){ /*Selected */
1.251 brouard 5265: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
5266: and mw[mi+1][iind]. dh depends on stepm. */
5267: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
5268: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
5269: if(m >=firstpass && m <=lastpass){
5270: k2=anint[m][iind]+(mint[m][iind]/12.);
5271: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
5272: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
5273: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
5274: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
5275: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
5276: if (m<lastpass) {
5277: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
5278: /* 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]); */
5279: if(s[m][iind]==-1)
5280: 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.));
5281: 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 5282: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean on known values only */
5283: if(!isnan(covar[ncovcol+z1][iind])){
1.332 brouard 5284: idq[z1]=idq[z1]+weight[iind];
5285: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
5286: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; *//*error*/
5287: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
1.311 brouard 5288: }
1.284 brouard 5289: }
1.251 brouard 5290: /* if((int)agev[m][iind] == 55) */
5291: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
5292: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
5293: 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 5294: }
1.251 brouard 5295: } /* end if between passes */
5296: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
5297: dateintsum=dateintsum+k2; /* on all covariates ?*/
5298: k2cpt++;
5299: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 5300: }
1.251 brouard 5301: }else{
5302: bool=1;
5303: }/* end bool 2 */
5304: } /* end m */
1.284 brouard 5305: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
5306: /* idq[z1]=idq[z1]+weight[iind]; */
5307: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
5308: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
5309: /* } */
1.251 brouard 5310: } /* end bool */
5311: } /* end iind = 1 to imx */
1.319 brouard 5312: /* prop[s][age] is fed for any initial and valid live state as well as
1.251 brouard 5313: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
5314:
5315:
5316: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.335 brouard 5317: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
1.265 brouard 5318: pstamp(ficresp);
1.335 brouard 5319: if (cptcoveff>0 && j!=0){
1.265 brouard 5320: pstamp(ficresp);
1.251 brouard 5321: printf( "\n#********** Variable ");
5322: fprintf(ficresp, "\n#********** Variable ");
5323: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
5324: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
5325: fprintf(ficlog, "\n#********** Variable ");
1.330 brouard 5326: for (z1=1; z1<=cptcovs; z1++){
1.251 brouard 5327: if(!FixedV[Tvaraff[z1]]){
1.330 brouard 5328: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5329: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5330: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5331: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5332: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.250 brouard 5333: }else{
1.330 brouard 5334: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5335: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5336: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5337: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5338: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.251 brouard 5339: }
5340: }
5341: printf( "**********\n#");
5342: fprintf(ficresp, "**********\n#");
5343: fprintf(ficresphtm, "**********</h3>\n");
5344: fprintf(ficresphtmfr, "**********</h3>\n");
5345: fprintf(ficlog, "**********\n");
5346: }
1.284 brouard 5347: /*
5348: Printing means of quantitative variables if any
5349: */
5350: for (z1=1; z1<= nqfveff; z1++) {
1.311 brouard 5351: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.3g (weighted) individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.312 brouard 5352: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
1.284 brouard 5353: if(weightopt==1){
5354: printf(" Weighted mean and standard deviation of");
5355: fprintf(ficlog," Weighted mean and standard deviation of");
5356: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
5357: }
1.311 brouard 5358: /* mu = \frac{w x}{\sum w}
5359: var = \frac{\sum w (x-mu)^2}{\sum w} = \frac{w x^2}{\sum w} - mu^2
5360: */
5361: 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]));
5362: 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]));
5363: 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 5364: }
5365: /* for (z1=1; z1<= nqtveff; z1++) { */
5366: /* for(m=1;m<=lastpass;m++){ */
5367: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
5368: /* } */
5369: /* } */
1.283 brouard 5370:
1.251 brouard 5371: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.335 brouard 5372: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
1.265 brouard 5373: fprintf(ficresp, " Age");
1.335 brouard 5374: if(nj==2) for (z1=1; z1<=cptcoveff; z1++) {
5375: printf(" V%d=%d, z1=%d, Tvaraff[z1]=%d, j1=%d, TnsdVar[Tvaraff[%d]]=%d |",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])], z1, Tvaraff[z1], j1,z1,TnsdVar[Tvaraff[z1]]);
5376: fprintf(ficresp, " V%d=%d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5377: }
1.251 brouard 5378: for(i=1; i<=nlstate;i++) {
1.335 brouard 5379: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 5380: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
5381: }
1.335 brouard 5382: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 5383: fprintf(ficresphtm, "\n");
5384:
5385: /* Header of frequency table by age */
5386: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
5387: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 5388: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 5389: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5390: if(s2!=0 && m!=0)
5391: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 5392: }
1.226 brouard 5393: }
1.251 brouard 5394: fprintf(ficresphtmfr, "\n");
5395:
5396: /* For each age */
5397: for(iage=iagemin; iage <= iagemax+3; iage++){
5398: fprintf(ficresphtm,"<tr>");
5399: if(iage==iagemax+1){
5400: fprintf(ficlog,"1");
5401: fprintf(ficresphtmfr,"<tr><th>0</th> ");
5402: }else if(iage==iagemax+2){
5403: fprintf(ficlog,"0");
5404: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
5405: }else if(iage==iagemax+3){
5406: fprintf(ficlog,"Total");
5407: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
5408: }else{
1.240 brouard 5409: if(first==1){
1.251 brouard 5410: first=0;
5411: printf("See log file for details...\n");
5412: }
5413: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
5414: fprintf(ficlog,"Age %d", iage);
5415: }
1.265 brouard 5416: for(s1=1; s1 <=nlstate ; s1++){
5417: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
5418: pp[s1] += freq[s1][m][iage];
1.251 brouard 5419: }
1.265 brouard 5420: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5421: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 5422: pos += freq[s1][m][iage];
5423: if(pp[s1]>=1.e-10){
1.251 brouard 5424: if(first==1){
1.265 brouard 5425: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5426: }
1.265 brouard 5427: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5428: }else{
5429: if(first==1)
1.265 brouard 5430: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
5431: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 5432: }
5433: }
5434:
1.265 brouard 5435: for(s1=1; s1 <=nlstate ; s1++){
5436: /* posprop[s1]=0; */
5437: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
5438: pp[s1] += freq[s1][m][iage];
5439: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
5440:
5441: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
5442: pos += pp[s1]; /* pos is the total number of transitions until this age */
5443: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
5444: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5445: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
5446: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5447: }
5448:
5449: /* Writing ficresp */
1.335 brouard 5450: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5451: if( iage <= iagemax){
5452: fprintf(ficresp," %d",iage);
5453: }
5454: }else if( nj==2){
5455: if( iage <= iagemax){
5456: fprintf(ficresp," %d",iage);
1.335 brouard 5457: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.265 brouard 5458: }
1.240 brouard 5459: }
1.265 brouard 5460: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 5461: if(pos>=1.e-5){
1.251 brouard 5462: if(first==1)
1.265 brouard 5463: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
5464: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 5465: }else{
5466: if(first==1)
1.265 brouard 5467: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
5468: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 5469: }
5470: if( iage <= iagemax){
5471: if(pos>=1.e-5){
1.335 brouard 5472: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5473: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5474: }else if( nj==2){
5475: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5476: }
5477: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5478: /*probs[iage][s1][j1]= pp[s1]/pos;*/
5479: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
5480: } else{
1.335 brouard 5481: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
1.265 brouard 5482: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 5483: }
1.240 brouard 5484: }
1.265 brouard 5485: pospropt[s1] +=posprop[s1];
5486: } /* end loop s1 */
1.251 brouard 5487: /* pospropt=0.; */
1.265 brouard 5488: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 5489: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5490: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 5491: if(first==1){
1.265 brouard 5492: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5493: }
1.265 brouard 5494: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
5495: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5496: }
1.265 brouard 5497: if(s1!=0 && m!=0)
5498: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 5499: }
1.265 brouard 5500: } /* end loop s1 */
1.251 brouard 5501: posproptt=0.;
1.265 brouard 5502: for(s1=1; s1 <=nlstate; s1++){
5503: posproptt += pospropt[s1];
1.251 brouard 5504: }
5505: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 5506: fprintf(ficresphtm,"</tr>\n");
1.335 brouard 5507: if((cptcoveff==0 && nj==1)|| nj==2 ) {
1.265 brouard 5508: if(iage <= iagemax)
5509: fprintf(ficresp,"\n");
1.240 brouard 5510: }
1.251 brouard 5511: if(first==1)
5512: printf("Others in log...\n");
5513: fprintf(ficlog,"\n");
5514: } /* end loop age iage */
1.265 brouard 5515:
1.251 brouard 5516: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 5517: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5518: if(posproptt < 1.e-5){
1.265 brouard 5519: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 5520: }else{
1.265 brouard 5521: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 5522: }
1.226 brouard 5523: }
1.251 brouard 5524: fprintf(ficresphtm,"</tr>\n");
5525: fprintf(ficresphtm,"</table>\n");
5526: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 5527: if(posproptt < 1.e-5){
1.251 brouard 5528: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
5529: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 5530: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
5531: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 5532: invalidvarcomb[j1]=1;
1.226 brouard 5533: }else{
1.338 brouard 5534: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced (or no resultline).</p>",j1);
1.251 brouard 5535: invalidvarcomb[j1]=0;
1.226 brouard 5536: }
1.251 brouard 5537: fprintf(ficresphtmfr,"</table>\n");
5538: fprintf(ficlog,"\n");
5539: if(j!=0){
5540: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 5541: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5542: for(k=1; k <=(nlstate+ndeath); k++){
5543: if (k != i) {
1.265 brouard 5544: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 5545: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 5546: if(j1==1){ /* All dummy covariates to zero */
5547: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
5548: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 5549: printf("%d%d ",i,k);
5550: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5551: 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]));
5552: 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]));
5553: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 5554: }
1.253 brouard 5555: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
5556: for(iage=iagemin; iage <= iagemax+3; iage++){
5557: x[iage]= (double)iage;
5558: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 5559: /* 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 5560: }
1.268 brouard 5561: /* Some are not finite, but linreg will ignore these ages */
5562: no=0;
1.253 brouard 5563: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 5564: pstart[s1]=b;
5565: pstart[s1-1]=a;
1.252 brouard 5566: }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 */
5567: 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]);
5568: 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 5569: 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 5570: printf("%d%d ",i,k);
5571: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5572: 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 5573: }else{ /* Other cases, like quantitative fixed or varying covariates */
5574: ;
5575: }
5576: /* printf("%12.7f )", param[i][jj][k]); */
5577: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5578: s1++;
1.251 brouard 5579: } /* end jj */
5580: } /* end k!= i */
5581: } /* end k */
1.265 brouard 5582: } /* end i, s1 */
1.251 brouard 5583: } /* end j !=0 */
5584: } /* end selected combination of covariate j1 */
5585: if(j==0){ /* We can estimate starting values from the occurences in each case */
5586: printf("#Freqsummary: Starting values for the constants:\n");
5587: fprintf(ficlog,"\n");
1.265 brouard 5588: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5589: for(k=1; k <=(nlstate+ndeath); k++){
5590: if (k != i) {
5591: printf("%d%d ",i,k);
5592: fprintf(ficlog,"%d%d ",i,k);
5593: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 5594: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 5595: if(jj==1){ /* Age has to be done */
1.265 brouard 5596: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
5597: 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]));
5598: 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 5599: }
5600: /* printf("%12.7f )", param[i][jj][k]); */
5601: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5602: s1++;
1.250 brouard 5603: }
1.251 brouard 5604: printf("\n");
5605: fprintf(ficlog,"\n");
1.250 brouard 5606: }
5607: }
1.284 brouard 5608: } /* end of state i */
1.251 brouard 5609: printf("#Freqsummary\n");
5610: fprintf(ficlog,"\n");
1.265 brouard 5611: for(s1=-1; s1 <=nlstate+ndeath; s1++){
5612: for(s2=-1; s2 <=nlstate+ndeath; s2++){
5613: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
5614: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5615: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5616: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
5617: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
5618: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 5619: /* } */
5620: }
1.265 brouard 5621: } /* end loop s1 */
1.251 brouard 5622:
5623: printf("\n");
5624: fprintf(ficlog,"\n");
5625: } /* end j=0 */
1.249 brouard 5626: } /* end j */
1.252 brouard 5627:
1.253 brouard 5628: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 5629: for(i=1, jk=1; i <=nlstate; i++){
5630: for(j=1; j <=nlstate+ndeath; j++){
5631: if(j!=i){
5632: /*ca[0]= k+'a'-1;ca[1]='\0';*/
5633: printf("%1d%1d",i,j);
5634: fprintf(ficparo,"%1d%1d",i,j);
5635: for(k=1; k<=ncovmodel;k++){
5636: /* printf(" %lf",param[i][j][k]); */
5637: /* fprintf(ficparo," %lf",param[i][j][k]); */
5638: p[jk]=pstart[jk];
5639: printf(" %f ",pstart[jk]);
5640: fprintf(ficparo," %f ",pstart[jk]);
5641: jk++;
5642: }
5643: printf("\n");
5644: fprintf(ficparo,"\n");
5645: }
5646: }
5647: }
5648: } /* end mle=-2 */
1.226 brouard 5649: dateintmean=dateintsum/k2cpt;
1.296 brouard 5650: date2dmy(dateintmean,&jintmean,&mintmean,&aintmean);
1.240 brouard 5651:
1.226 brouard 5652: fclose(ficresp);
5653: fclose(ficresphtm);
5654: fclose(ficresphtmfr);
1.283 brouard 5655: free_vector(idq,1,nqfveff);
1.226 brouard 5656: free_vector(meanq,1,nqfveff);
1.284 brouard 5657: free_vector(stdq,1,nqfveff);
1.226 brouard 5658: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 5659: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
5660: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 5661: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5662: free_vector(pospropt,1,nlstate);
5663: free_vector(posprop,1,nlstate);
1.251 brouard 5664: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5665: free_vector(pp,1,nlstate);
5666: /* End of freqsummary */
5667: }
1.126 brouard 5668:
1.268 brouard 5669: /* Simple linear regression */
5670: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
5671:
5672: /* y=a+bx regression */
5673: double sumx = 0.0; /* sum of x */
5674: double sumx2 = 0.0; /* sum of x**2 */
5675: double sumxy = 0.0; /* sum of x * y */
5676: double sumy = 0.0; /* sum of y */
5677: double sumy2 = 0.0; /* sum of y**2 */
5678: double sume2 = 0.0; /* sum of square or residuals */
5679: double yhat;
5680:
5681: double denom=0;
5682: int i;
5683: int ne=*no;
5684:
5685: for ( i=ifi, ne=0;i<=ila;i++) {
5686: if(!isfinite(x[i]) || !isfinite(y[i])){
5687: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5688: continue;
5689: }
5690: ne=ne+1;
5691: sumx += x[i];
5692: sumx2 += x[i]*x[i];
5693: sumxy += x[i] * y[i];
5694: sumy += y[i];
5695: sumy2 += y[i]*y[i];
5696: denom = (ne * sumx2 - sumx*sumx);
5697: /* 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); */
5698: }
5699:
5700: denom = (ne * sumx2 - sumx*sumx);
5701: if (denom == 0) {
5702: // vertical, slope m is infinity
5703: *b = INFINITY;
5704: *a = 0;
5705: if (r) *r = 0;
5706: return 1;
5707: }
5708:
5709: *b = (ne * sumxy - sumx * sumy) / denom;
5710: *a = (sumy * sumx2 - sumx * sumxy) / denom;
5711: if (r!=NULL) {
5712: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
5713: sqrt((sumx2 - sumx*sumx/ne) *
5714: (sumy2 - sumy*sumy/ne));
5715: }
5716: *no=ne;
5717: for ( i=ifi, ne=0;i<=ila;i++) {
5718: if(!isfinite(x[i]) || !isfinite(y[i])){
5719: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5720: continue;
5721: }
5722: ne=ne+1;
5723: yhat = y[i] - *a -*b* x[i];
5724: sume2 += yhat * yhat ;
5725:
5726: denom = (ne * sumx2 - sumx*sumx);
5727: /* 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); */
5728: }
5729: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
5730: *sa= *sb * sqrt(sumx2/ne);
5731:
5732: return 0;
5733: }
5734:
1.126 brouard 5735: /************ Prevalence ********************/
1.227 brouard 5736: 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)
5737: {
5738: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
5739: in each health status at the date of interview (if between dateprev1 and dateprev2).
5740: We still use firstpass and lastpass as another selection.
5741: */
1.126 brouard 5742:
1.227 brouard 5743: int i, m, jk, j1, bool, z1,j, iv;
5744: int mi; /* Effective wave */
5745: int iage;
5746: double agebegin, ageend;
5747:
5748: double **prop;
5749: double posprop;
5750: double y2; /* in fractional years */
5751: int iagemin, iagemax;
5752: int first; /** to stop verbosity which is redirected to log file */
5753:
5754: iagemin= (int) agemin;
5755: iagemax= (int) agemax;
5756: /*pp=vector(1,nlstate);*/
1.251 brouard 5757: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5758: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
5759: j1=0;
1.222 brouard 5760:
1.227 brouard 5761: /*j=cptcoveff;*/
5762: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 5763:
1.288 brouard 5764: first=0;
1.335 brouard 5765: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of simple dummy covariates */
1.227 brouard 5766: for (i=1; i<=nlstate; i++)
1.251 brouard 5767: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 5768: prop[i][iage]=0.0;
5769: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
5770: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
5771: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
5772:
5773: for (i=1; i<=imx; i++) { /* Each individual */
5774: bool=1;
5775: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
5776: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
5777: m=mw[mi][i];
5778: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
5779: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
5780: for (z1=1; z1<=cptcoveff; z1++){
5781: if( Fixed[Tmodelind[z1]]==1){
5782: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
1.332 brouard 5783: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) /* iv=1 to ntv, right modality */
1.227 brouard 5784: bool=0;
5785: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
1.332 brouard 5786: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) {
1.227 brouard 5787: bool=0;
5788: }
5789: }
5790: if(bool==1){ /* Otherwise we skip that wave/person */
5791: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
5792: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
5793: if(m >=firstpass && m <=lastpass){
5794: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
5795: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
5796: if(agev[m][i]==0) agev[m][i]=iagemax+1;
5797: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 5798: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 5799: 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);
5800: exit(1);
5801: }
5802: if (s[m][i]>0 && s[m][i]<=nlstate) {
5803: /*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]]);*/
5804: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
5805: prop[s[m][i]][iagemax+3] += weight[i];
5806: } /* end valid statuses */
5807: } /* end selection of dates */
5808: } /* end selection of waves */
5809: } /* end bool */
5810: } /* end wave */
5811: } /* end individual */
5812: for(i=iagemin; i <= iagemax+3; i++){
5813: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
5814: posprop += prop[jk][i];
5815: }
5816:
5817: for(jk=1; jk <=nlstate ; jk++){
5818: if( i <= iagemax){
5819: if(posprop>=1.e-5){
5820: probs[i][jk][j1]= prop[jk][i]/posprop;
5821: } else{
1.288 brouard 5822: if(!first){
5823: first=1;
1.266 brouard 5824: 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]);
5825: }else{
1.288 brouard 5826: 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 5827: }
5828: }
5829: }
5830: }/* end jk */
5831: }/* end i */
1.222 brouard 5832: /*} *//* end i1 */
1.227 brouard 5833: } /* end j1 */
1.222 brouard 5834:
1.227 brouard 5835: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
5836: /*free_vector(pp,1,nlstate);*/
1.251 brouard 5837: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5838: } /* End of prevalence */
1.126 brouard 5839:
5840: /************* Waves Concatenation ***************/
5841:
5842: 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)
5843: {
1.298 brouard 5844: /* 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 5845: Death is a valid wave (if date is known).
5846: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
5847: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
1.298 brouard 5848: and mw[mi+1][i]. dh depends on stepm. s[m][i] exists for any wave from firstpass to lastpass
1.227 brouard 5849: */
1.126 brouard 5850:
1.224 brouard 5851: int i=0, mi=0, m=0, mli=0;
1.126 brouard 5852: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
5853: double sum=0., jmean=0.;*/
1.224 brouard 5854: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 5855: int j, k=0,jk, ju, jl;
5856: double sum=0.;
5857: first=0;
1.214 brouard 5858: firstwo=0;
1.217 brouard 5859: firsthree=0;
1.218 brouard 5860: firstfour=0;
1.164 brouard 5861: jmin=100000;
1.126 brouard 5862: jmax=-1;
5863: jmean=0.;
1.224 brouard 5864:
5865: /* Treating live states */
1.214 brouard 5866: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 5867: mi=0; /* First valid wave */
1.227 brouard 5868: mli=0; /* Last valid wave */
1.309 brouard 5869: m=firstpass; /* Loop on waves */
5870: while(s[m][i] <= nlstate){ /* a live state or unknown state */
1.227 brouard 5871: 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 */
5872: mli=m-1;/* mw[++mi][i]=m-1; */
5873: }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 5874: 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 5875: mli=m;
1.224 brouard 5876: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
5877: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 5878: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 5879: }
1.309 brouard 5880: else{ /* m = lastpass, eventual special issue with warning */
1.224 brouard 5881: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 5882: break;
1.224 brouard 5883: #else
1.317 brouard 5884: 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 5885: if(firsthree == 0){
1.302 brouard 5886: 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 5887: firsthree=1;
1.317 brouard 5888: }else if(firsthree >=1 && firsthree < 10){
5889: 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);
5890: firsthree++;
5891: }else if(firsthree == 10){
5892: printf("Information, too many Information flags: no more reported to log either\n");
5893: fprintf(ficlog,"Information, too many Information flags: no more reported to log either\n");
5894: firsthree++;
5895: }else{
5896: firsthree++;
1.227 brouard 5897: }
1.309 brouard 5898: mw[++mi][i]=m; /* Valid transition with unknown status */
1.227 brouard 5899: mli=m;
5900: }
5901: if(s[m][i]==-2){ /* Vital status is really unknown */
5902: nbwarn++;
1.309 brouard 5903: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified?not a transition */
1.227 brouard 5904: 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);
5905: 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);
5906: }
5907: break;
5908: }
5909: break;
1.224 brouard 5910: #endif
1.227 brouard 5911: }/* End m >= lastpass */
1.126 brouard 5912: }/* end while */
1.224 brouard 5913:
1.227 brouard 5914: /* 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 5915: /* After last pass */
1.224 brouard 5916: /* Treating death states */
1.214 brouard 5917: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 5918: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
5919: /* } */
1.126 brouard 5920: mi++; /* Death is another wave */
5921: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 5922: /* Only death is a correct wave */
1.126 brouard 5923: mw[mi][i]=m;
1.257 brouard 5924: } /* else not in a death state */
1.224 brouard 5925: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 5926: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 5927: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.309 brouard 5928: 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 5929: nbwarn++;
5930: if(firstfiv==0){
1.309 brouard 5931: 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 5932: firstfiv=1;
5933: }else{
1.309 brouard 5934: 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 5935: }
1.309 brouard 5936: s[m][i]=nlstate+1; /* Fixing the status as death. Be careful if multiple death states */
5937: }else{ /* Month of Death occured afer last wave month, potential bias */
1.227 brouard 5938: nberr++;
5939: if(firstwo==0){
1.309 brouard 5940: 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 5941: firstwo=1;
5942: }
1.309 brouard 5943: 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 5944: }
1.257 brouard 5945: }else{ /* if date of interview is unknown */
1.227 brouard 5946: /* death is known but not confirmed by death status at any wave */
5947: if(firstfour==0){
1.309 brouard 5948: 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 5949: firstfour=1;
5950: }
1.309 brouard 5951: 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 5952: }
1.224 brouard 5953: } /* end if date of death is known */
5954: #endif
1.309 brouard 5955: wav[i]=mi; /* mi should be the last effective wave (or mli), */
5956: /* wav[i]=mw[mi][i]; */
1.126 brouard 5957: if(mi==0){
5958: nbwarn++;
5959: if(first==0){
1.227 brouard 5960: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
5961: first=1;
1.126 brouard 5962: }
5963: if(first==1){
1.227 brouard 5964: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 5965: }
5966: } /* end mi==0 */
5967: } /* End individuals */
1.214 brouard 5968: /* wav and mw are no more changed */
1.223 brouard 5969:
1.317 brouard 5970: printf("Information, you have to check %d informations which haven't been logged!\n",firsthree);
5971: fprintf(ficlog,"Information, you have to check %d informations which haven't been logged!\n",firsthree);
5972:
5973:
1.126 brouard 5974: for(i=1; i<=imx; i++){
5975: for(mi=1; mi<wav[i];mi++){
5976: if (stepm <=0)
1.227 brouard 5977: dh[mi][i]=1;
1.126 brouard 5978: else{
1.260 brouard 5979: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 5980: if (agedc[i] < 2*AGESUP) {
5981: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
5982: if(j==0) j=1; /* Survives at least one month after exam */
5983: else if(j<0){
5984: nberr++;
5985: 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]);
5986: j=1; /* Temporary Dangerous patch */
5987: 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);
5988: 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]);
5989: 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);
5990: }
5991: k=k+1;
5992: if (j >= jmax){
5993: jmax=j;
5994: ijmax=i;
5995: }
5996: if (j <= jmin){
5997: jmin=j;
5998: ijmin=i;
5999: }
6000: sum=sum+j;
6001: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
6002: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
6003: }
6004: }
6005: else{
6006: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 6007: /* 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 6008:
1.227 brouard 6009: k=k+1;
6010: if (j >= jmax) {
6011: jmax=j;
6012: ijmax=i;
6013: }
6014: else if (j <= jmin){
6015: jmin=j;
6016: ijmin=i;
6017: }
6018: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
6019: /*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]);*/
6020: if(j<0){
6021: nberr++;
6022: 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]);
6023: 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]);
6024: }
6025: sum=sum+j;
6026: }
6027: jk= j/stepm;
6028: jl= j -jk*stepm;
6029: ju= j -(jk+1)*stepm;
6030: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
6031: if(jl==0){
6032: dh[mi][i]=jk;
6033: bh[mi][i]=0;
6034: }else{ /* We want a negative bias in order to only have interpolation ie
6035: * to avoid the price of an extra matrix product in likelihood */
6036: dh[mi][i]=jk+1;
6037: bh[mi][i]=ju;
6038: }
6039: }else{
6040: if(jl <= -ju){
6041: dh[mi][i]=jk;
6042: bh[mi][i]=jl; /* bias is positive if real duration
6043: * is higher than the multiple of stepm and negative otherwise.
6044: */
6045: }
6046: else{
6047: dh[mi][i]=jk+1;
6048: bh[mi][i]=ju;
6049: }
6050: if(dh[mi][i]==0){
6051: dh[mi][i]=1; /* At least one step */
6052: bh[mi][i]=ju; /* At least one step */
6053: /* 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);*/
6054: }
6055: } /* end if mle */
1.126 brouard 6056: }
6057: } /* end wave */
6058: }
6059: jmean=sum/k;
6060: 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 6061: 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 6062: }
1.126 brouard 6063:
6064: /*********** Tricode ****************************/
1.220 brouard 6065: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 6066: {
6067: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
6068: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
6069: * Boring subroutine which should only output nbcode[Tvar[j]][k]
6070: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
6071: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
6072: */
1.130 brouard 6073:
1.242 brouard 6074: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
6075: int modmaxcovj=0; /* Modality max of covariates j */
6076: int cptcode=0; /* Modality max of covariates j */
6077: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 6078:
6079:
1.242 brouard 6080: /* cptcoveff=0; */
6081: /* *cptcov=0; */
1.126 brouard 6082:
1.242 brouard 6083: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 6084: for (k=1; k <= maxncov; k++)
6085: for(j=1; j<=2; j++)
6086: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 6087:
1.242 brouard 6088: /* Loop on covariates without age and products and no quantitative variable */
1.335 brouard 6089: for (k=1; k<=cptcovt; k++) { /* cptcovt: total number of covariates of the model (2) nbocc(+)+1 = 8 excepting constant and age and age*age */
1.242 brouard 6090: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
1.339 ! brouard 6091: printf("Testing k=%d, cptcovt=%d\n",k, cptcovt);
! 6092: if(Dummy[k]==0 && Typevar[k] !=1 && Typevar[k] != 2){ /* Dummy covariate and not age product nor fixed product */
1.242 brouard 6093: switch(Fixed[k]) {
6094: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
1.311 brouard 6095: modmaxcovj=0;
6096: modmincovj=0;
1.242 brouard 6097: for (i=1; i<=imx; i++) { /* Loop on individuals: reads the data file to get the maximum value of the modality of this covariate Vj*/
1.339 ! brouard 6098: /* printf("Waiting for error tricode Tvar[%d]=%d i=%d (int)(covar[Tvar[k]][i]=%d\n",k,Tvar[k], i, (int)(covar[Tvar[k]][i])); */
1.242 brouard 6099: ij=(int)(covar[Tvar[k]][i]);
6100: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
6101: * If product of Vn*Vm, still boolean *:
6102: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
6103: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
6104: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
6105: modality of the nth covariate of individual i. */
6106: if (ij > modmaxcovj)
6107: modmaxcovj=ij;
6108: else if (ij < modmincovj)
6109: modmincovj=ij;
1.287 brouard 6110: if (ij <0 || ij >1 ){
1.311 brouard 6111: printf("ERROR, IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
6112: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
6113: fflush(ficlog);
6114: exit(1);
1.287 brouard 6115: }
6116: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 6117: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
6118: exit(1);
6119: }else
6120: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
6121: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
6122: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
6123: /* getting the maximum value of the modality of the covariate
6124: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
6125: female ies 1, then modmaxcovj=1.
6126: */
6127: } /* end for loop on individuals i */
6128: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
6129: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
6130: cptcode=modmaxcovj;
6131: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
6132: /*for (i=0; i<=cptcode; i++) {*/
6133: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
6134: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
6135: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
6136: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
6137: if( j != -1){
6138: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
6139: covariate for which somebody answered excluding
6140: undefined. Usually 2: 0 and 1. */
6141: }
6142: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
6143: covariate for which somebody answered including
6144: undefined. Usually 3: -1, 0 and 1. */
6145: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
6146: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
6147: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 6148:
1.242 brouard 6149: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
6150: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
6151: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
6152: /* modmincovj=3; modmaxcovj = 7; */
6153: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
6154: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
6155: /* defining two dummy variables: variables V1_1 and V1_2.*/
6156: /* nbcode[Tvar[j]][ij]=k; */
6157: /* nbcode[Tvar[j]][1]=0; */
6158: /* nbcode[Tvar[j]][2]=1; */
6159: /* nbcode[Tvar[j]][3]=2; */
6160: /* To be continued (not working yet). */
6161: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 6162:
6163: /* 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*/
6164: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
6165: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
6166: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
6167: /*, could be restored in the future */
6168: 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 6169: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
6170: break;
6171: }
6172: ij++;
1.287 brouard 6173: 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 6174: cptcode = ij; /* New max modality for covar j */
6175: } /* end of loop on modality i=-1 to 1 or more */
6176: break;
6177: case 1: /* Testing on varying covariate, could be simple and
6178: * should look at waves or product of fixed *
6179: * varying. No time to test -1, assuming 0 and 1 only */
6180: ij=0;
6181: for(i=0; i<=1;i++){
6182: nbcode[Tvar[k]][++ij]=i;
6183: }
6184: break;
6185: default:
6186: break;
6187: } /* end switch */
6188: } /* end dummy test */
1.334 brouard 6189: if(Dummy[k]==1 && Typevar[k] !=1){ /* Quantitative covariate and not age product */
1.311 brouard 6190: for (i=1; i<=imx; i++) { /* Loop on individuals: reads the data file to get the maximum value of the modality of this covariate Vj*/
1.335 brouard 6191: if(Tvar[k]<=0 || Tvar[k]>=NCOVMAX){
6192: printf("Error k=%d \n",k);
6193: exit(1);
6194: }
1.311 brouard 6195: if(isnan(covar[Tvar[k]][i])){
6196: printf("ERROR, IMaCh doesn't treat fixed quantitative covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
6197: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
6198: fflush(ficlog);
6199: exit(1);
6200: }
6201: }
1.335 brouard 6202: } /* end Quanti */
1.287 brouard 6203: } /* 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 6204:
6205: for (k=-1; k< maxncov; k++) Ndum[k]=0;
6206: /* Look at fixed dummy (single or product) covariates to check empty modalities */
6207: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
6208: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
6209: 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 */
6210: 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 */
6211: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
6212: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
6213:
6214: ij=0;
6215: /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */
1.335 brouard 6216: for (k=1; k<= cptcovt; k++) { /* cptcovt: total number of covariates of the model (2) nbocc(+)+1 = 8 excepting constant and age and age*age */
6217: /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
1.242 brouard 6218: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
6219: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
1.335 brouard 6220: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy simple and non empty in the model */
6221: /* Typevar[k] =0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
6222: /* Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product*/
1.242 brouard 6223: /* If product not in single variable we don't print results */
6224: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
1.335 brouard 6225: ++ij;/* V5 + V4 + V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V1, *//* V5 quanti, V2 quanti, V4, V3, V1 dummies */
6226: /* k= 1 2 3 4 5 6 7 8 9 */
6227: /* Tvar[k]= 5 4 3 6 5 2 7 1 1 */
6228: /* ij 1 2 3 */
6229: /* Tvaraff[ij]= 4 3 1 */
6230: /* Tmodelind[ij]=2 3 9 */
6231: /* TmodelInvind[ij]=2 1 1 */
1.242 brouard 6232: 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*/
6233: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
6234: 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 */
6235: if(Fixed[k]!=0)
6236: anyvaryingduminmodel=1;
6237: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
6238: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
6239: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
6240: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
6241: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
6242: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
6243: }
6244: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
6245: /* ij--; */
6246: /* cptcoveff=ij; /\*Number of total covariates*\/ */
1.335 brouard 6247: *cptcov=ij; /* cptcov= Number of total real effective simple dummies (fixed or time arying) effective (used as cptcoveff in other functions)
1.242 brouard 6248: * because they can be excluded from the model and real
6249: * if in the model but excluded because missing values, but how to get k from ij?*/
6250: for(j=ij+1; j<= cptcovt; j++){
6251: Tvaraff[j]=0;
6252: Tmodelind[j]=0;
6253: }
6254: for(j=ntveff+1; j<= cptcovt; j++){
6255: TmodelInvind[j]=0;
6256: }
6257: /* To be sorted */
6258: ;
6259: }
1.126 brouard 6260:
1.145 brouard 6261:
1.126 brouard 6262: /*********** Health Expectancies ****************/
6263:
1.235 brouard 6264: 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 6265:
6266: {
6267: /* Health expectancies, no variances */
1.329 brouard 6268: /* cij is the combination in the list of combination of dummy covariates */
6269: /* strstart is a string of time at start of computing */
1.164 brouard 6270: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 6271: int nhstepma, nstepma; /* Decreasing with age */
6272: double age, agelim, hf;
6273: double ***p3mat;
6274: double eip;
6275:
1.238 brouard 6276: /* pstamp(ficreseij); */
1.126 brouard 6277: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
6278: fprintf(ficreseij,"# Age");
6279: for(i=1; i<=nlstate;i++){
6280: for(j=1; j<=nlstate;j++){
6281: fprintf(ficreseij," e%1d%1d ",i,j);
6282: }
6283: fprintf(ficreseij," e%1d. ",i);
6284: }
6285: fprintf(ficreseij,"\n");
6286:
6287:
6288: if(estepm < stepm){
6289: printf ("Problem %d lower than %d\n",estepm, stepm);
6290: }
6291: else hstepm=estepm;
6292: /* We compute the life expectancy from trapezoids spaced every estepm months
6293: * This is mainly to measure the difference between two models: for example
6294: * if stepm=24 months pijx are given only every 2 years and by summing them
6295: * we are calculating an estimate of the Life Expectancy assuming a linear
6296: * progression in between and thus overestimating or underestimating according
6297: * to the curvature of the survival function. If, for the same date, we
6298: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6299: * to compare the new estimate of Life expectancy with the same linear
6300: * hypothesis. A more precise result, taking into account a more precise
6301: * curvature will be obtained if estepm is as small as stepm. */
6302:
6303: /* For example we decided to compute the life expectancy with the smallest unit */
6304: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6305: nhstepm is the number of hstepm from age to agelim
6306: nstepm is the number of stepm from age to agelin.
1.270 brouard 6307: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 6308: and note for a fixed period like estepm months */
6309: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6310: survival function given by stepm (the optimization length). Unfortunately it
6311: means that if the survival funtion is printed only each two years of age and if
6312: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6313: results. So we changed our mind and took the option of the best precision.
6314: */
6315: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6316:
6317: agelim=AGESUP;
6318: /* If stepm=6 months */
6319: /* Computed by stepm unit matrices, product of hstepm matrices, stored
6320: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
6321:
6322: /* nhstepm age range expressed in number of stepm */
6323: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6324: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6325: /* if (stepm >= YEARM) hstepm=1;*/
6326: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6327: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6328:
6329: for (age=bage; age<=fage; age ++){
6330: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6331: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6332: /* if (stepm >= YEARM) hstepm=1;*/
6333: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
6334:
6335: /* If stepm=6 months */
6336: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6337: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
1.330 brouard 6338: /* 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 6339: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 6340:
6341: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6342:
6343: printf("%d|",(int)age);fflush(stdout);
6344: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6345:
6346: /* Computing expectancies */
6347: for(i=1; i<=nlstate;i++)
6348: for(j=1; j<=nlstate;j++)
6349: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6350: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
6351:
6352: /* 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]);*/
6353:
6354: }
6355:
6356: fprintf(ficreseij,"%3.0f",age );
6357: for(i=1; i<=nlstate;i++){
6358: eip=0;
6359: for(j=1; j<=nlstate;j++){
6360: eip +=eij[i][j][(int)age];
6361: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
6362: }
6363: fprintf(ficreseij,"%9.4f", eip );
6364: }
6365: fprintf(ficreseij,"\n");
6366:
6367: }
6368: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6369: printf("\n");
6370: fprintf(ficlog,"\n");
6371:
6372: }
6373:
1.235 brouard 6374: 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 6375:
6376: {
6377: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 6378: to initial status i, ei. .
1.126 brouard 6379: */
1.336 brouard 6380: /* Very time consuming function, but already optimized with precov */
1.126 brouard 6381: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
6382: int nhstepma, nstepma; /* Decreasing with age */
6383: double age, agelim, hf;
6384: double ***p3matp, ***p3matm, ***varhe;
6385: double **dnewm,**doldm;
6386: double *xp, *xm;
6387: double **gp, **gm;
6388: double ***gradg, ***trgradg;
6389: int theta;
6390:
6391: double eip, vip;
6392:
6393: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
6394: xp=vector(1,npar);
6395: xm=vector(1,npar);
6396: dnewm=matrix(1,nlstate*nlstate,1,npar);
6397: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
6398:
6399: pstamp(ficresstdeij);
6400: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
6401: fprintf(ficresstdeij,"# Age");
6402: for(i=1; i<=nlstate;i++){
6403: for(j=1; j<=nlstate;j++)
6404: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
6405: fprintf(ficresstdeij," e%1d. ",i);
6406: }
6407: fprintf(ficresstdeij,"\n");
6408:
6409: pstamp(ficrescveij);
6410: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
6411: fprintf(ficrescveij,"# Age");
6412: for(i=1; i<=nlstate;i++)
6413: for(j=1; j<=nlstate;j++){
6414: cptj= (j-1)*nlstate+i;
6415: for(i2=1; i2<=nlstate;i2++)
6416: for(j2=1; j2<=nlstate;j2++){
6417: cptj2= (j2-1)*nlstate+i2;
6418: if(cptj2 <= cptj)
6419: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
6420: }
6421: }
6422: fprintf(ficrescveij,"\n");
6423:
6424: if(estepm < stepm){
6425: printf ("Problem %d lower than %d\n",estepm, stepm);
6426: }
6427: else hstepm=estepm;
6428: /* We compute the life expectancy from trapezoids spaced every estepm months
6429: * This is mainly to measure the difference between two models: for example
6430: * if stepm=24 months pijx are given only every 2 years and by summing them
6431: * we are calculating an estimate of the Life Expectancy assuming a linear
6432: * progression in between and thus overestimating or underestimating according
6433: * to the curvature of the survival function. If, for the same date, we
6434: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6435: * to compare the new estimate of Life expectancy with the same linear
6436: * hypothesis. A more precise result, taking into account a more precise
6437: * curvature will be obtained if estepm is as small as stepm. */
6438:
6439: /* For example we decided to compute the life expectancy with the smallest unit */
6440: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6441: nhstepm is the number of hstepm from age to agelim
6442: nstepm is the number of stepm from age to agelin.
6443: Look at hpijx to understand the reason of that which relies in memory size
6444: and note for a fixed period like estepm months */
6445: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6446: survival function given by stepm (the optimization length). Unfortunately it
6447: means that if the survival funtion is printed only each two years of age and if
6448: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6449: results. So we changed our mind and took the option of the best precision.
6450: */
6451: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6452:
6453: /* If stepm=6 months */
6454: /* nhstepm age range expressed in number of stepm */
6455: agelim=AGESUP;
6456: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
6457: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6458: /* if (stepm >= YEARM) hstepm=1;*/
6459: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6460:
6461: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6462: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6463: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
6464: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
6465: gp=matrix(0,nhstepm,1,nlstate*nlstate);
6466: gm=matrix(0,nhstepm,1,nlstate*nlstate);
6467:
6468: for (age=bage; age<=fage; age ++){
6469: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6470: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6471: /* if (stepm >= YEARM) hstepm=1;*/
6472: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 6473:
1.126 brouard 6474: /* If stepm=6 months */
6475: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6476: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
6477:
6478: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 6479:
1.126 brouard 6480: /* Computing Variances of health expectancies */
6481: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
6482: decrease memory allocation */
6483: for(theta=1; theta <=npar; theta++){
6484: for(i=1; i<=npar; i++){
1.222 brouard 6485: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6486: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 6487: }
1.235 brouard 6488: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
6489: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 6490:
1.126 brouard 6491: for(j=1; j<= nlstate; j++){
1.222 brouard 6492: for(i=1; i<=nlstate; i++){
6493: for(h=0; h<=nhstepm-1; h++){
6494: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
6495: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
6496: }
6497: }
1.126 brouard 6498: }
1.218 brouard 6499:
1.126 brouard 6500: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 6501: for(h=0; h<=nhstepm-1; h++){
6502: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
6503: }
1.126 brouard 6504: }/* End theta */
6505:
6506:
6507: for(h=0; h<=nhstepm-1; h++)
6508: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 6509: for(theta=1; theta <=npar; theta++)
6510: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 6511:
1.218 brouard 6512:
1.222 brouard 6513: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 6514: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 6515: varhe[ij][ji][(int)age] =0.;
1.218 brouard 6516:
1.222 brouard 6517: printf("%d|",(int)age);fflush(stdout);
6518: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6519: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 6520: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 6521: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
6522: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
6523: for(ij=1;ij<=nlstate*nlstate;ij++)
6524: for(ji=1;ji<=nlstate*nlstate;ji++)
6525: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 6526: }
6527: }
1.320 brouard 6528: /* if((int)age ==50){ */
6529: /* printf(" age=%d cij=%d nres=%d varhe[%d][%d]=%f ",(int)age, cij, nres, 1,2,varhe[1][2]); */
6530: /* } */
1.126 brouard 6531: /* Computing expectancies */
1.235 brouard 6532: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 6533: for(i=1; i<=nlstate;i++)
6534: for(j=1; j<=nlstate;j++)
1.222 brouard 6535: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6536: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 6537:
1.222 brouard 6538: /* 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 6539:
1.222 brouard 6540: }
1.269 brouard 6541:
6542: /* Standard deviation of expectancies ij */
1.126 brouard 6543: fprintf(ficresstdeij,"%3.0f",age );
6544: for(i=1; i<=nlstate;i++){
6545: eip=0.;
6546: vip=0.;
6547: for(j=1; j<=nlstate;j++){
1.222 brouard 6548: eip += eij[i][j][(int)age];
6549: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
6550: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
6551: 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 6552: }
6553: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
6554: }
6555: fprintf(ficresstdeij,"\n");
1.218 brouard 6556:
1.269 brouard 6557: /* Variance of expectancies ij */
1.126 brouard 6558: fprintf(ficrescveij,"%3.0f",age );
6559: for(i=1; i<=nlstate;i++)
6560: for(j=1; j<=nlstate;j++){
1.222 brouard 6561: cptj= (j-1)*nlstate+i;
6562: for(i2=1; i2<=nlstate;i2++)
6563: for(j2=1; j2<=nlstate;j2++){
6564: cptj2= (j2-1)*nlstate+i2;
6565: if(cptj2 <= cptj)
6566: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
6567: }
1.126 brouard 6568: }
6569: fprintf(ficrescveij,"\n");
1.218 brouard 6570:
1.126 brouard 6571: }
6572: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
6573: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
6574: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
6575: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
6576: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6577: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6578: printf("\n");
6579: fprintf(ficlog,"\n");
1.218 brouard 6580:
1.126 brouard 6581: free_vector(xm,1,npar);
6582: free_vector(xp,1,npar);
6583: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
6584: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
6585: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
6586: }
1.218 brouard 6587:
1.126 brouard 6588: /************ Variance ******************/
1.235 brouard 6589: 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 6590: {
1.279 brouard 6591: /** Variance of health expectancies
6592: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
6593: * double **newm;
6594: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
6595: */
1.218 brouard 6596:
6597: /* int movingaverage(); */
6598: double **dnewm,**doldm;
6599: double **dnewmp,**doldmp;
6600: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 6601: int first=0;
1.218 brouard 6602: int k;
6603: double *xp;
1.279 brouard 6604: double **gp, **gm; /**< for var eij */
6605: double ***gradg, ***trgradg; /**< for var eij */
6606: double **gradgp, **trgradgp; /**< for var p point j */
6607: double *gpp, *gmp; /**< for var p point j */
6608: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 6609: double ***p3mat;
6610: double age,agelim, hf;
6611: /* double ***mobaverage; */
6612: int theta;
6613: char digit[4];
6614: char digitp[25];
6615:
6616: char fileresprobmorprev[FILENAMELENGTH];
6617:
6618: if(popbased==1){
6619: if(mobilav!=0)
6620: strcpy(digitp,"-POPULBASED-MOBILAV_");
6621: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
6622: }
6623: else
6624: strcpy(digitp,"-STABLBASED_");
1.126 brouard 6625:
1.218 brouard 6626: /* if (mobilav!=0) { */
6627: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6628: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
6629: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
6630: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
6631: /* } */
6632: /* } */
6633:
6634: strcpy(fileresprobmorprev,"PRMORPREV-");
6635: sprintf(digit,"%-d",ij);
6636: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
6637: strcat(fileresprobmorprev,digit); /* Tvar to be done */
6638: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
6639: strcat(fileresprobmorprev,fileresu);
6640: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
6641: printf("Problem with resultfile: %s\n", fileresprobmorprev);
6642: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
6643: }
6644: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
6645: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
6646: pstamp(ficresprobmorprev);
6647: 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 6648: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
1.337 brouard 6649:
6650: /* We use TinvDoQresult[nres][resultmodel[nres][j] we sort according to the equation model and the resultline: it is a choice */
6651: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ /\* To be done*\/ */
6652: /* fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
6653: /* } */
6654: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */ /* To be done*/
6655: fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 6656: }
1.337 brouard 6657: /* for(j=1;j<=cptcoveff;j++) */
6658: /* fprintf(ficresprobmorprev," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,TnsdVar[Tvaraff[j]])]); */
1.238 brouard 6659: fprintf(ficresprobmorprev,"\n");
6660:
1.218 brouard 6661: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
6662: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6663: fprintf(ficresprobmorprev," p.%-d SE",j);
6664: for(i=1; i<=nlstate;i++)
6665: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
6666: }
6667: fprintf(ficresprobmorprev,"\n");
6668:
6669: fprintf(ficgp,"\n# Routine varevsij");
6670: fprintf(ficgp,"\nunset title \n");
6671: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
6672: 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");
6673: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 6674:
1.218 brouard 6675: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6676: pstamp(ficresvij);
6677: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
6678: if(popbased==1)
6679: 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);
6680: else
6681: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
6682: fprintf(ficresvij,"# Age");
6683: for(i=1; i<=nlstate;i++)
6684: for(j=1; j<=nlstate;j++)
6685: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
6686: fprintf(ficresvij,"\n");
6687:
6688: xp=vector(1,npar);
6689: dnewm=matrix(1,nlstate,1,npar);
6690: doldm=matrix(1,nlstate,1,nlstate);
6691: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
6692: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6693:
6694: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
6695: gpp=vector(nlstate+1,nlstate+ndeath);
6696: gmp=vector(nlstate+1,nlstate+ndeath);
6697: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 6698:
1.218 brouard 6699: if(estepm < stepm){
6700: printf ("Problem %d lower than %d\n",estepm, stepm);
6701: }
6702: else hstepm=estepm;
6703: /* For example we decided to compute the life expectancy with the smallest unit */
6704: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6705: nhstepm is the number of hstepm from age to agelim
6706: nstepm is the number of stepm from age to agelim.
6707: Look at function hpijx to understand why because of memory size limitations,
6708: we decided (b) to get a life expectancy respecting the most precise curvature of the
6709: survival function given by stepm (the optimization length). Unfortunately it
6710: means that if the survival funtion is printed every two years of age and if
6711: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6712: results. So we changed our mind and took the option of the best precision.
6713: */
6714: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6715: agelim = AGESUP;
6716: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6717: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6718: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6719: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6720: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
6721: gp=matrix(0,nhstepm,1,nlstate);
6722: gm=matrix(0,nhstepm,1,nlstate);
6723:
6724:
6725: for(theta=1; theta <=npar; theta++){
6726: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
6727: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6728: }
1.279 brouard 6729: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
6730: * returns into prlim .
1.288 brouard 6731: */
1.242 brouard 6732: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 6733:
6734: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 6735: if (popbased==1) {
6736: if(mobilav ==0){
6737: for(i=1; i<=nlstate;i++)
6738: prlim[i][i]=probs[(int)age][i][ij];
6739: }else{ /* mobilav */
6740: for(i=1; i<=nlstate;i++)
6741: prlim[i][i]=mobaverage[(int)age][i][ij];
6742: }
6743: }
1.295 brouard 6744: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h.
1.279 brouard 6745: */
6746: 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 6747: /**< 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 6748: * at horizon h in state j including mortality.
6749: */
1.218 brouard 6750: for(j=1; j<= nlstate; j++){
6751: for(h=0; h<=nhstepm; h++){
6752: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
6753: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
6754: }
6755: }
1.279 brouard 6756: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 6757: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 6758: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 6759: */
6760: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6761: for(i=1,gpp[j]=0.; i<= nlstate; i++)
6762: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 6763: }
6764:
6765: /* Again with minus shift */
1.218 brouard 6766:
6767: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
6768: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6769:
1.242 brouard 6770: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 6771:
6772: if (popbased==1) {
6773: if(mobilav ==0){
6774: for(i=1; i<=nlstate;i++)
6775: prlim[i][i]=probs[(int)age][i][ij];
6776: }else{ /* mobilav */
6777: for(i=1; i<=nlstate;i++)
6778: prlim[i][i]=mobaverage[(int)age][i][ij];
6779: }
6780: }
6781:
1.235 brouard 6782: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 6783:
6784: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
6785: for(h=0; h<=nhstepm; h++){
6786: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
6787: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
6788: }
6789: }
6790: /* This for computing probability of death (h=1 means
6791: computed over hstepm matrices product = hstepm*stepm months)
6792: as a weighted average of prlim.
6793: */
6794: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6795: for(i=1,gmp[j]=0.; i<= nlstate; i++)
6796: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6797: }
1.279 brouard 6798: /* end shifting computations */
6799:
6800: /**< Computing gradient matrix at horizon h
6801: */
1.218 brouard 6802: for(j=1; j<= nlstate; j++) /* vareij */
6803: for(h=0; h<=nhstepm; h++){
6804: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
6805: }
1.279 brouard 6806: /**< Gradient of overall mortality p.3 (or p.j)
6807: */
6808: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 6809: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
6810: }
6811:
6812: } /* End theta */
1.279 brouard 6813:
6814: /* We got the gradient matrix for each theta and state j */
1.218 brouard 6815: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
6816:
6817: for(h=0; h<=nhstepm; h++) /* veij */
6818: for(j=1; j<=nlstate;j++)
6819: for(theta=1; theta <=npar; theta++)
6820: trgradg[h][j][theta]=gradg[h][theta][j];
6821:
6822: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
6823: for(theta=1; theta <=npar; theta++)
6824: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 6825: /**< as well as its transposed matrix
6826: */
1.218 brouard 6827:
6828: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6829: for(i=1;i<=nlstate;i++)
6830: for(j=1;j<=nlstate;j++)
6831: vareij[i][j][(int)age] =0.;
1.279 brouard 6832:
6833: /* Computing trgradg by matcov by gradg at age and summing over h
6834: * and k (nhstepm) formula 15 of article
6835: * Lievre-Brouard-Heathcote
6836: */
6837:
1.218 brouard 6838: for(h=0;h<=nhstepm;h++){
6839: for(k=0;k<=nhstepm;k++){
6840: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
6841: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
6842: for(i=1;i<=nlstate;i++)
6843: for(j=1;j<=nlstate;j++)
6844: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
6845: }
6846: }
6847:
1.279 brouard 6848: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
6849: * p.j overall mortality formula 49 but computed directly because
6850: * we compute the grad (wix pijx) instead of grad (pijx),even if
6851: * wix is independent of theta.
6852: */
1.218 brouard 6853: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
6854: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
6855: for(j=nlstate+1;j<=nlstate+ndeath;j++)
6856: for(i=nlstate+1;i<=nlstate+ndeath;i++)
6857: varppt[j][i]=doldmp[j][i];
6858: /* end ppptj */
6859: /* x centered again */
6860:
1.242 brouard 6861: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 6862:
6863: if (popbased==1) {
6864: if(mobilav ==0){
6865: for(i=1; i<=nlstate;i++)
6866: prlim[i][i]=probs[(int)age][i][ij];
6867: }else{ /* mobilav */
6868: for(i=1; i<=nlstate;i++)
6869: prlim[i][i]=mobaverage[(int)age][i][ij];
6870: }
6871: }
6872:
6873: /* This for computing probability of death (h=1 means
6874: computed over hstepm (estepm) matrices product = hstepm*stepm months)
6875: as a weighted average of prlim.
6876: */
1.235 brouard 6877: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 6878: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6879: for(i=1,gmp[j]=0.;i<= nlstate; i++)
6880: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6881: }
6882: /* end probability of death */
6883:
6884: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
6885: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6886: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
6887: for(i=1; i<=nlstate;i++){
6888: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
6889: }
6890: }
6891: fprintf(ficresprobmorprev,"\n");
6892:
6893: fprintf(ficresvij,"%.0f ",age );
6894: for(i=1; i<=nlstate;i++)
6895: for(j=1; j<=nlstate;j++){
6896: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
6897: }
6898: fprintf(ficresvij,"\n");
6899: free_matrix(gp,0,nhstepm,1,nlstate);
6900: free_matrix(gm,0,nhstepm,1,nlstate);
6901: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
6902: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
6903: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6904: } /* End age */
6905: free_vector(gpp,nlstate+1,nlstate+ndeath);
6906: free_vector(gmp,nlstate+1,nlstate+ndeath);
6907: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
6908: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
6909: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
6910: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
6911: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
6912: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
6913: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
6914: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
6915: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
6916: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
6917: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
6918: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
6919: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
6920: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
6921: 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);
6922: /* 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 6923: */
1.218 brouard 6924: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
6925: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 6926:
1.218 brouard 6927: free_vector(xp,1,npar);
6928: free_matrix(doldm,1,nlstate,1,nlstate);
6929: free_matrix(dnewm,1,nlstate,1,npar);
6930: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6931: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
6932: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6933: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6934: fclose(ficresprobmorprev);
6935: fflush(ficgp);
6936: fflush(fichtm);
6937: } /* end varevsij */
1.126 brouard 6938:
6939: /************ Variance of prevlim ******************/
1.269 brouard 6940: 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 6941: {
1.205 brouard 6942: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 6943: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 6944:
1.268 brouard 6945: double **dnewmpar,**doldm;
1.126 brouard 6946: int i, j, nhstepm, hstepm;
6947: double *xp;
6948: double *gp, *gm;
6949: double **gradg, **trgradg;
1.208 brouard 6950: double **mgm, **mgp;
1.126 brouard 6951: double age,agelim;
6952: int theta;
6953:
6954: pstamp(ficresvpl);
1.288 brouard 6955: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 6956: fprintf(ficresvpl,"# Age ");
6957: if(nresult >=1)
6958: fprintf(ficresvpl," Result# ");
1.126 brouard 6959: for(i=1; i<=nlstate;i++)
6960: fprintf(ficresvpl," %1d-%1d",i,i);
6961: fprintf(ficresvpl,"\n");
6962:
6963: xp=vector(1,npar);
1.268 brouard 6964: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 6965: doldm=matrix(1,nlstate,1,nlstate);
6966:
6967: hstepm=1*YEARM; /* Every year of age */
6968: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6969: agelim = AGESUP;
6970: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6971: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6972: if (stepm >= YEARM) hstepm=1;
6973: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6974: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 6975: mgp=matrix(1,npar,1,nlstate);
6976: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 6977: gp=vector(1,nlstate);
6978: gm=vector(1,nlstate);
6979:
6980: for(theta=1; theta <=npar; theta++){
6981: for(i=1; i<=npar; i++){ /* Computes gradient */
6982: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6983: }
1.288 brouard 6984: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6985: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6986: /* else */
6987: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6988: for(i=1;i<=nlstate;i++){
1.126 brouard 6989: gp[i] = prlim[i][i];
1.208 brouard 6990: mgp[theta][i] = prlim[i][i];
6991: }
1.126 brouard 6992: for(i=1; i<=npar; i++) /* Computes gradient */
6993: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6994: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6995: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6996: /* else */
6997: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6998: for(i=1;i<=nlstate;i++){
1.126 brouard 6999: gm[i] = prlim[i][i];
1.208 brouard 7000: mgm[theta][i] = prlim[i][i];
7001: }
1.126 brouard 7002: for(i=1;i<=nlstate;i++)
7003: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 7004: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 7005: } /* End theta */
7006:
7007: trgradg =matrix(1,nlstate,1,npar);
7008:
7009: for(j=1; j<=nlstate;j++)
7010: for(theta=1; theta <=npar; theta++)
7011: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 7012: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7013: /* printf("\nmgm mgp %d ",(int)age); */
7014: /* for(j=1; j<=nlstate;j++){ */
7015: /* printf(" %d ",j); */
7016: /* for(theta=1; theta <=npar; theta++) */
7017: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
7018: /* printf("\n "); */
7019: /* } */
7020: /* } */
7021: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7022: /* printf("\n gradg %d ",(int)age); */
7023: /* for(j=1; j<=nlstate;j++){ */
7024: /* printf("%d ",j); */
7025: /* for(theta=1; theta <=npar; theta++) */
7026: /* printf("%d %lf ",theta,gradg[theta][j]); */
7027: /* printf("\n "); */
7028: /* } */
7029: /* } */
1.126 brouard 7030:
7031: for(i=1;i<=nlstate;i++)
7032: varpl[i][(int)age] =0.;
1.209 brouard 7033: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 7034: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7035: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 7036: }else{
1.268 brouard 7037: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7038: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 7039: }
1.126 brouard 7040: for(i=1;i<=nlstate;i++)
7041: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
7042:
7043: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 7044: if(nresult >=1)
7045: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 7046: for(i=1; i<=nlstate;i++){
1.126 brouard 7047: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 7048: /* for(j=1;j<=nlstate;j++) */
7049: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
7050: }
1.126 brouard 7051: fprintf(ficresvpl,"\n");
7052: free_vector(gp,1,nlstate);
7053: free_vector(gm,1,nlstate);
1.208 brouard 7054: free_matrix(mgm,1,npar,1,nlstate);
7055: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 7056: free_matrix(gradg,1,npar,1,nlstate);
7057: free_matrix(trgradg,1,nlstate,1,npar);
7058: } /* End age */
7059:
7060: free_vector(xp,1,npar);
7061: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 7062: free_matrix(dnewmpar,1,nlstate,1,nlstate);
7063:
7064: }
7065:
7066:
7067: /************ Variance of backprevalence limit ******************/
1.269 brouard 7068: 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 7069: {
7070: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
7071: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
7072:
7073: double **dnewmpar,**doldm;
7074: int i, j, nhstepm, hstepm;
7075: double *xp;
7076: double *gp, *gm;
7077: double **gradg, **trgradg;
7078: double **mgm, **mgp;
7079: double age,agelim;
7080: int theta;
7081:
7082: pstamp(ficresvbl);
7083: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
7084: fprintf(ficresvbl,"# Age ");
7085: if(nresult >=1)
7086: fprintf(ficresvbl," Result# ");
7087: for(i=1; i<=nlstate;i++)
7088: fprintf(ficresvbl," %1d-%1d",i,i);
7089: fprintf(ficresvbl,"\n");
7090:
7091: xp=vector(1,npar);
7092: dnewmpar=matrix(1,nlstate,1,npar);
7093: doldm=matrix(1,nlstate,1,nlstate);
7094:
7095: hstepm=1*YEARM; /* Every year of age */
7096: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
7097: agelim = AGEINF;
7098: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
7099: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7100: if (stepm >= YEARM) hstepm=1;
7101: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
7102: gradg=matrix(1,npar,1,nlstate);
7103: mgp=matrix(1,npar,1,nlstate);
7104: mgm=matrix(1,npar,1,nlstate);
7105: gp=vector(1,nlstate);
7106: gm=vector(1,nlstate);
7107:
7108: for(theta=1; theta <=npar; theta++){
7109: for(i=1; i<=npar; i++){ /* Computes gradient */
7110: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7111: }
7112: if(mobilavproj > 0 )
7113: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7114: else
7115: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7116: for(i=1;i<=nlstate;i++){
7117: gp[i] = bprlim[i][i];
7118: mgp[theta][i] = bprlim[i][i];
7119: }
7120: for(i=1; i<=npar; i++) /* Computes gradient */
7121: xp[i] = x[i] - (i==theta ?delti[theta]:0);
7122: if(mobilavproj > 0 )
7123: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7124: else
7125: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7126: for(i=1;i<=nlstate;i++){
7127: gm[i] = bprlim[i][i];
7128: mgm[theta][i] = bprlim[i][i];
7129: }
7130: for(i=1;i<=nlstate;i++)
7131: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
7132: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
7133: } /* End theta */
7134:
7135: trgradg =matrix(1,nlstate,1,npar);
7136:
7137: for(j=1; j<=nlstate;j++)
7138: for(theta=1; theta <=npar; theta++)
7139: trgradg[j][theta]=gradg[theta][j];
7140: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7141: /* printf("\nmgm mgp %d ",(int)age); */
7142: /* for(j=1; j<=nlstate;j++){ */
7143: /* printf(" %d ",j); */
7144: /* for(theta=1; theta <=npar; theta++) */
7145: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
7146: /* printf("\n "); */
7147: /* } */
7148: /* } */
7149: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7150: /* printf("\n gradg %d ",(int)age); */
7151: /* for(j=1; j<=nlstate;j++){ */
7152: /* printf("%d ",j); */
7153: /* for(theta=1; theta <=npar; theta++) */
7154: /* printf("%d %lf ",theta,gradg[theta][j]); */
7155: /* printf("\n "); */
7156: /* } */
7157: /* } */
7158:
7159: for(i=1;i<=nlstate;i++)
7160: varbpl[i][(int)age] =0.;
7161: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
7162: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7163: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
7164: }else{
7165: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7166: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
7167: }
7168: for(i=1;i<=nlstate;i++)
7169: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
7170:
7171: fprintf(ficresvbl,"%.0f ",age );
7172: if(nresult >=1)
7173: fprintf(ficresvbl,"%d ",nres );
7174: for(i=1; i<=nlstate;i++)
7175: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
7176: fprintf(ficresvbl,"\n");
7177: free_vector(gp,1,nlstate);
7178: free_vector(gm,1,nlstate);
7179: free_matrix(mgm,1,npar,1,nlstate);
7180: free_matrix(mgp,1,npar,1,nlstate);
7181: free_matrix(gradg,1,npar,1,nlstate);
7182: free_matrix(trgradg,1,nlstate,1,npar);
7183: } /* End age */
7184:
7185: free_vector(xp,1,npar);
7186: free_matrix(doldm,1,nlstate,1,npar);
7187: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 7188:
7189: }
7190:
7191: /************ Variance of one-step probabilities ******************/
7192: 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 7193: {
7194: int i, j=0, k1, l1, tj;
7195: int k2, l2, j1, z1;
7196: int k=0, l;
7197: int first=1, first1, first2;
1.326 brouard 7198: int nres=0; /* New */
1.222 brouard 7199: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
7200: double **dnewm,**doldm;
7201: double *xp;
7202: double *gp, *gm;
7203: double **gradg, **trgradg;
7204: double **mu;
7205: double age, cov[NCOVMAX+1];
7206: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
7207: int theta;
7208: char fileresprob[FILENAMELENGTH];
7209: char fileresprobcov[FILENAMELENGTH];
7210: char fileresprobcor[FILENAMELENGTH];
7211: double ***varpij;
7212:
7213: strcpy(fileresprob,"PROB_");
7214: strcat(fileresprob,fileres);
7215: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
7216: printf("Problem with resultfile: %s\n", fileresprob);
7217: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
7218: }
7219: strcpy(fileresprobcov,"PROBCOV_");
7220: strcat(fileresprobcov,fileresu);
7221: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
7222: printf("Problem with resultfile: %s\n", fileresprobcov);
7223: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
7224: }
7225: strcpy(fileresprobcor,"PROBCOR_");
7226: strcat(fileresprobcor,fileresu);
7227: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
7228: printf("Problem with resultfile: %s\n", fileresprobcor);
7229: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
7230: }
7231: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7232: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7233: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7234: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7235: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7236: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7237: pstamp(ficresprob);
7238: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
7239: fprintf(ficresprob,"# Age");
7240: pstamp(ficresprobcov);
7241: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
7242: fprintf(ficresprobcov,"# Age");
7243: pstamp(ficresprobcor);
7244: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
7245: fprintf(ficresprobcor,"# Age");
1.126 brouard 7246:
7247:
1.222 brouard 7248: for(i=1; i<=nlstate;i++)
7249: for(j=1; j<=(nlstate+ndeath);j++){
7250: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
7251: fprintf(ficresprobcov," p%1d-%1d ",i,j);
7252: fprintf(ficresprobcor," p%1d-%1d ",i,j);
7253: }
7254: /* fprintf(ficresprob,"\n");
7255: fprintf(ficresprobcov,"\n");
7256: fprintf(ficresprobcor,"\n");
7257: */
7258: xp=vector(1,npar);
7259: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7260: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
7261: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
7262: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
7263: first=1;
7264: fprintf(ficgp,"\n# Routine varprob");
7265: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
7266: fprintf(fichtm,"\n");
7267:
1.288 brouard 7268: 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 7269: 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);
7270: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 7271: and drawn. It helps understanding how is the covariance between two incidences.\
7272: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 7273: 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 7274: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
7275: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
7276: standard deviations wide on each axis. <br>\
7277: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
7278: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
7279: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
7280:
1.222 brouard 7281: cov[1]=1;
7282: /* tj=cptcoveff; */
1.225 brouard 7283: tj = (int) pow(2,cptcoveff);
1.222 brouard 7284: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
7285: j1=0;
1.332 brouard 7286:
7287: for(nres=1;nres <=nresult; nres++){ /* For each resultline */
7288: for(j1=1; j1<=tj;j1++){ /* For any combination of dummy covariates, fixed and varying */
1.334 brouard 7289: 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 7290: if(tj != 1 && TKresult[nres]!= j1)
7291: continue;
7292:
7293: /* for(j1=1; j1<=tj;j1++){ /\* For each valid combination of covariates or only once*\/ */
7294: /* for(nres=1;nres <=1; nres++){ /\* For each resultline *\/ */
7295: /* /\* for(nres=1;nres <=nresult; nres++){ /\\* For each resultline *\\/ *\/ */
1.222 brouard 7296: if (cptcovn>0) {
1.334 brouard 7297: fprintf(ficresprob, "\n#********** Variable ");
7298: fprintf(ficresprobcov, "\n#********** Variable ");
7299: fprintf(ficgp, "\n#********** Variable ");
7300: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
7301: fprintf(ficresprobcor, "\n#********** Variable ");
7302:
7303: /* Including quantitative variables of the resultline to be done */
7304: for (z1=1; z1<=cptcovs; z1++){ /* Loop on each variable of this resultline */
1.338 brouard 7305: printf("Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model);
7306: fprintf(ficlog,"Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model);
7307: /* fprintf(ficlog,"Varprob modelresult[%d][%d]=%d model=1+age+%s resultline[%d]=%s \n",nres, z1, modelresult[nres][z1], model, nres, resultline[nres]); */
1.334 brouard 7308: if(Dummy[modelresult[nres][z1]]==0){/* Dummy variable of the variable in position modelresult in the model corresponding to z1 in resultline */
7309: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed referenced to model equation */
7310: 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 */
7311: 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 */
7312: 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 */
7313: 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 */
7314: 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 */
7315: fprintf(ficresprob,"fixed ");
7316: fprintf(ficresprobcov,"fixed ");
7317: fprintf(ficgp,"fixed ");
7318: fprintf(fichtmcov,"fixed ");
7319: fprintf(ficresprobcor,"fixed ");
7320: }else{
7321: fprintf(ficresprob,"varyi ");
7322: fprintf(ficresprobcov,"varyi ");
7323: fprintf(ficgp,"varyi ");
7324: fprintf(fichtmcov,"varyi ");
7325: fprintf(ficresprobcor,"varyi ");
7326: }
7327: }else if(Dummy[modelresult[nres][z1]]==1){ /* Quanti variable */
7328: /* For each selected (single) quantitative value */
1.337 brouard 7329: fprintf(ficresprob," V%d=%lg ",Tvqresult[nres][z1],Tqresult[nres][z1]);
1.334 brouard 7330: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed */
7331: fprintf(ficresprob,"fixed ");
7332: fprintf(ficresprobcov,"fixed ");
7333: fprintf(ficgp,"fixed ");
7334: fprintf(fichtmcov,"fixed ");
7335: fprintf(ficresprobcor,"fixed ");
7336: }else{
7337: fprintf(ficresprob,"varyi ");
7338: fprintf(ficresprobcov,"varyi ");
7339: fprintf(ficgp,"varyi ");
7340: fprintf(fichtmcov,"varyi ");
7341: fprintf(ficresprobcor,"varyi ");
7342: }
7343: }else{
7344: 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 */
7345: 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 */
7346: exit(1);
7347: }
7348: } /* End loop on variable of this resultline */
7349: /* for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]); */
1.222 brouard 7350: fprintf(ficresprob, "**********\n#\n");
7351: fprintf(ficresprobcov, "**********\n#\n");
7352: fprintf(ficgp, "**********\n#\n");
7353: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
7354: fprintf(ficresprobcor, "**********\n#");
7355: if(invalidvarcomb[j1]){
7356: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
7357: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
7358: continue;
7359: }
7360: }
7361: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
7362: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7363: gp=vector(1,(nlstate)*(nlstate+ndeath));
7364: gm=vector(1,(nlstate)*(nlstate+ndeath));
1.334 brouard 7365: for (age=bage; age<=fage; age ++){ /* Fo each age we feed the model equation with covariates, using precov as in hpxij() ? */
1.222 brouard 7366: cov[2]=age;
7367: if(nagesqr==1)
7368: cov[3]= age*age;
1.334 brouard 7369: /* New code end of combination but for each resultline */
7370: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
7371: if(Typevar[k1]==1){ /* A product with age */
7372: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.326 brouard 7373: }else{
1.334 brouard 7374: cov[2+nagesqr+k1]=precov[nres][k1];
1.326 brouard 7375: }
1.334 brouard 7376: }/* End of loop on model equation */
7377: /* Old code */
7378: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
7379: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)]; *\/ */
7380: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
7381: /* /\* Here comes the value of the covariate 'j1' after renumbering k with single dummy covariates *\/ */
7382: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(j1,TnsdVar[TvarsD[k]])]; */
7383: /* /\*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*\//\* j1 1 2 3 4 */
7384: /* * 1 1 1 1 1 */
7385: /* * 2 2 1 1 1 */
7386: /* * 3 1 2 1 1 */
7387: /* *\/ */
7388: /* /\* nbcode[1][1]=0 nbcode[1][2]=1;*\/ */
7389: /* } */
7390: /* /\* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
7391: /* /\* ) p nbcode[Tvar[Tage[k]]][(1 & (ij-1) >> (k-1))+1] *\/ */
7392: /* /\*for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; *\/ */
7393: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
7394: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
7395: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(j1,TnsdVar[Tvar[Tage[k]]])]*cov[2]; */
7396: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
7397: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
7398: /* 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]); */
7399: /* /\* cov[2+nagesqr+Tage[k]]=meanq[k]/idq[k]*cov[2];/\\* Using the mean of quantitative variable Tvar[Tage[k]] /\\* Tqresult[nres][k]; *\\/ *\/ */
7400: /* /\* exit(1); *\/ */
7401: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
7402: /* } */
7403: /* /\* cov[2+Tage[k]+nagesqr]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
7404: /* } */
7405: /* for (k=1; k<=cptcovprod;k++){/\* For product without age *\/ */
7406: /* if(Dummy[Tvard[k][1]]==0){ */
7407: /* if(Dummy[Tvard[k][2]]==0){ */
7408: /* 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]])]; */
7409: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
7410: /* }else{ /\* Should we use the mean of the quantitative variables? *\/ */
7411: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(j1,TnsdVar[Tvard[k][1]])] * Tqresult[nres][resultmodel[nres][k]]; */
7412: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
7413: /* } */
7414: /* }else{ */
7415: /* if(Dummy[Tvard[k][2]]==0){ */
7416: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(j1,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][TnsdVar[Tvard[k][1]]]; */
7417: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
7418: /* }else{ */
7419: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][TnsdVar[Tvard[k][1]]]* Tqinvresult[nres][TnsdVar[Tvard[k][2]]]; */
7420: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
7421: /* } */
7422: /* } */
7423: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
7424: /* } */
1.326 brouard 7425: /* For each age and combination of dummy covariates we slightly move the parameters of delti in order to get the gradient*/
1.222 brouard 7426: for(theta=1; theta <=npar; theta++){
7427: for(i=1; i<=npar; i++)
7428: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 7429:
1.222 brouard 7430: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 7431:
1.222 brouard 7432: k=0;
7433: for(i=1; i<= (nlstate); i++){
7434: for(j=1; j<=(nlstate+ndeath);j++){
7435: k=k+1;
7436: gp[k]=pmmij[i][j];
7437: }
7438: }
1.220 brouard 7439:
1.222 brouard 7440: for(i=1; i<=npar; i++)
7441: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 7442:
1.222 brouard 7443: pmij(pmmij,cov,ncovmodel,xp,nlstate);
7444: k=0;
7445: for(i=1; i<=(nlstate); i++){
7446: for(j=1; j<=(nlstate+ndeath);j++){
7447: k=k+1;
7448: gm[k]=pmmij[i][j];
7449: }
7450: }
1.220 brouard 7451:
1.222 brouard 7452: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
7453: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
7454: }
1.126 brouard 7455:
1.222 brouard 7456: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
7457: for(theta=1; theta <=npar; theta++)
7458: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 7459:
1.222 brouard 7460: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
7461: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 7462:
1.222 brouard 7463: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 7464:
1.222 brouard 7465: k=0;
7466: for(i=1; i<=(nlstate); i++){
7467: for(j=1; j<=(nlstate+ndeath);j++){
7468: k=k+1;
7469: mu[k][(int) age]=pmmij[i][j];
7470: }
7471: }
7472: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
7473: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
7474: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 7475:
1.222 brouard 7476: /*printf("\n%d ",(int)age);
7477: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7478: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7479: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7480: }*/
1.220 brouard 7481:
1.222 brouard 7482: fprintf(ficresprob,"\n%d ",(int)age);
7483: fprintf(ficresprobcov,"\n%d ",(int)age);
7484: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 7485:
1.222 brouard 7486: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
7487: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
7488: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7489: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
7490: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
7491: }
7492: i=0;
7493: for (k=1; k<=(nlstate);k++){
7494: for (l=1; l<=(nlstate+ndeath);l++){
7495: i++;
7496: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
7497: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
7498: for (j=1; j<=i;j++){
7499: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
7500: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
7501: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
7502: }
7503: }
7504: }/* end of loop for state */
7505: } /* end of loop for age */
7506: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
7507: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
7508: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7509: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7510:
7511: /* Confidence intervalle of pij */
7512: /*
7513: fprintf(ficgp,"\nunset parametric;unset label");
7514: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
7515: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
7516: 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);
7517: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
7518: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
7519: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
7520: */
7521:
7522: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
7523: first1=1;first2=2;
7524: for (k2=1; k2<=(nlstate);k2++){
7525: for (l2=1; l2<=(nlstate+ndeath);l2++){
7526: if(l2==k2) continue;
7527: j=(k2-1)*(nlstate+ndeath)+l2;
7528: for (k1=1; k1<=(nlstate);k1++){
7529: for (l1=1; l1<=(nlstate+ndeath);l1++){
7530: if(l1==k1) continue;
7531: i=(k1-1)*(nlstate+ndeath)+l1;
7532: if(i<=j) continue;
7533: for (age=bage; age<=fage; age ++){
7534: if ((int)age %5==0){
7535: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
7536: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
7537: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
7538: mu1=mu[i][(int) age]/stepm*YEARM ;
7539: mu2=mu[j][(int) age]/stepm*YEARM;
7540: c12=cv12/sqrt(v1*v2);
7541: /* Computing eigen value of matrix of covariance */
7542: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7543: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7544: if ((lc2 <0) || (lc1 <0) ){
7545: if(first2==1){
7546: first1=0;
7547: 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);
7548: }
7549: 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);
7550: /* lc1=fabs(lc1); */ /* If we want to have them positive */
7551: /* lc2=fabs(lc2); */
7552: }
1.220 brouard 7553:
1.222 brouard 7554: /* Eigen vectors */
1.280 brouard 7555: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
7556: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7557: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7558: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
7559: }else
7560: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 7561: /*v21=sqrt(1.-v11*v11); *//* error */
7562: v21=(lc1-v1)/cv12*v11;
7563: v12=-v21;
7564: v22=v11;
7565: tnalp=v21/v11;
7566: if(first1==1){
7567: first1=0;
7568: 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);
7569: }
7570: 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);
7571: /*printf(fignu*/
7572: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
7573: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
7574: if(first==1){
7575: first=0;
7576: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
7577: fprintf(ficgp,"\nset parametric;unset label");
7578: 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);
7579: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 7580: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 7581: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 7582: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 7583: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
7584: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7585: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7586: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
7587: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7588: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7589: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7590: 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 7591: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
7592: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 7593: }else{
7594: first=0;
7595: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
7596: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7597: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7598: 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 7599: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
7600: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 7601: }/* if first */
7602: } /* age mod 5 */
7603: } /* end loop age */
7604: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7605: first=1;
7606: } /*l12 */
7607: } /* k12 */
7608: } /*l1 */
7609: }/* k1 */
1.332 brouard 7610: } /* loop on combination of covariates j1 */
1.326 brouard 7611: } /* loop on nres */
1.222 brouard 7612: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
7613: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
7614: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
7615: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
7616: free_vector(xp,1,npar);
7617: fclose(ficresprob);
7618: fclose(ficresprobcov);
7619: fclose(ficresprobcor);
7620: fflush(ficgp);
7621: fflush(fichtmcov);
7622: }
1.126 brouard 7623:
7624:
7625: /******************* Printing html file ***********/
1.201 brouard 7626: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 7627: int lastpass, int stepm, int weightopt, char model[],\
7628: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.296 brouard 7629: int popforecast, int mobilav, int prevfcast, int mobilavproj, int prevbcast, int estepm , \
7630: double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \
7631: double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){
1.237 brouard 7632: int jj1, k1, i1, cpt, k4, nres;
1.319 brouard 7633: /* In fact some results are already printed in fichtm which is open */
1.126 brouard 7634: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
7635: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
7636: </ul>");
1.319 brouard 7637: /* fprintf(fichtm,"<ul><li> model=1+age+%s\n \ */
7638: /* </ul>", model); */
1.214 brouard 7639: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
7640: 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",
7641: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
1.332 brouard 7642: 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 7643: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
7644: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 7645: fprintf(fichtm,"\
7646: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 7647: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 7648: fprintf(fichtm,"\
1.217 brouard 7649: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
7650: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
7651: fprintf(fichtm,"\
1.288 brouard 7652: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 7653: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 7654: fprintf(fichtm,"\
1.288 brouard 7655: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 7656: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
7657: fprintf(fichtm,"\
1.211 brouard 7658: - (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 7659: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 7660: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 7661: if(prevfcast==1){
7662: fprintf(fichtm,"\
7663: - Prevalence projections by age and states: \
1.201 brouard 7664: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 7665: }
1.126 brouard 7666:
7667:
1.225 brouard 7668: m=pow(2,cptcoveff);
1.222 brouard 7669: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7670:
1.317 brouard 7671: fprintf(fichtm," \n<ul><li><b>Graphs (first order)</b></li><p>");
1.264 brouard 7672:
7673: jj1=0;
7674:
7675: fprintf(fichtm," \n<ul>");
1.337 brouard 7676: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
7677: /* k1=nres; */
1.338 brouard 7678: k1=TKresult[nres];
7679: if(TKresult[nres]==0)k1=1; /* To be checked for no result */
1.337 brouard 7680: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
7681: /* if(m != 1 && TKresult[nres]!= k1) */
7682: /* continue; */
1.264 brouard 7683: jj1++;
7684: if (cptcovn > 0) {
7685: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
1.337 brouard 7686: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
7687: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 7688: }
1.337 brouard 7689: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
7690: /* fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
7691: /* } */
7692: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
7693: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
7694: /* } */
1.264 brouard 7695: fprintf(fichtm,"\">");
7696:
7697: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
7698: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 7699: for (cpt=1; cpt<=cptcovs;cpt++){
7700: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 7701: }
1.337 brouard 7702: /* fprintf(fichtm,"************ Results for covariates"); */
7703: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
7704: /* fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
7705: /* } */
7706: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
7707: /* fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
7708: /* } */
1.264 brouard 7709: if(invalidvarcomb[k1]){
7710: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
7711: continue;
7712: }
7713: fprintf(fichtm,"</a></li>");
7714: } /* cptcovn >0 */
7715: }
1.317 brouard 7716: fprintf(fichtm," \n</ul>");
1.264 brouard 7717:
1.222 brouard 7718: jj1=0;
1.237 brouard 7719:
1.337 brouard 7720: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
7721: /* k1=nres; */
1.338 brouard 7722: k1=TKresult[nres];
7723: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 7724: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
7725: /* if(m != 1 && TKresult[nres]!= k1) */
7726: /* continue; */
1.220 brouard 7727:
1.222 brouard 7728: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7729: jj1++;
7730: if (cptcovn > 0) {
1.264 brouard 7731: fprintf(fichtm,"\n<p><a name=\"rescov");
1.337 brouard 7732: for (cpt=1; cpt<=cptcovs;cpt++){
7733: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 7734: }
1.337 brouard 7735: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
7736: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
7737: /* } */
1.264 brouard 7738: fprintf(fichtm,"\"</a>");
7739:
1.222 brouard 7740: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 7741: for (cpt=1; cpt<=cptcovs;cpt++){
7742: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
7743: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 7744: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
7745: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 7746: }
1.230 brouard 7747: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.338 brouard 7748: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.222 brouard 7749: if(invalidvarcomb[k1]){
7750: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
7751: printf("\nCombination (%d) ignored because no cases \n",k1);
7752: continue;
7753: }
7754: }
7755: /* aij, bij */
1.259 brouard 7756: 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 7757: <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 7758: /* Pij */
1.241 brouard 7759: 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> \
7760: <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 7761: /* Quasi-incidences */
7762: 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 7763: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 7764: 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 7765: 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> \
7766: <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 7767: /* Survival functions (period) in state j */
7768: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 7769: 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);
7770: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
7771: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.222 brouard 7772: }
7773: /* State specific survival functions (period) */
7774: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 7775: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
7776: And probability to be observed in various states (up to %d) being in state %d at different ages. \
1.329 brouard 7777: <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);
7778: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
7779: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.222 brouard 7780: }
1.288 brouard 7781: /* Period (forward stable) prevalence in each health state */
1.222 brouard 7782: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 7783: 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);
1.338 brouard 7784: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
1.329 brouard 7785: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.222 brouard 7786: }
1.296 brouard 7787: if(prevbcast==1){
1.288 brouard 7788: /* Backward prevalence in each health state */
1.222 brouard 7789: for(cpt=1; cpt<=nlstate;cpt++){
1.338 brouard 7790: fprintf(fichtm,"<br>\n- Convergence to mixed (stable) back prevalence in state %d. Or probability for a person to be in state %d at a younger age, knowing that she/he was in state (1 to %d) at different older ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br>", cpt, cpt, nlstate, subdirf2(optionfilefiname,"PB_"),cpt,k1,nres,subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
7791: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJB_"),subdirf2(optionfilefiname,"PIJB_"));
7792: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.222 brouard 7793: }
1.217 brouard 7794: }
1.222 brouard 7795: if(prevfcast==1){
1.288 brouard 7796: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 7797: for(cpt=1; cpt<=nlstate;cpt++){
1.314 brouard 7798: 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);
7799: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"F_"),subdirf2(optionfilefiname,"F_"));
7800: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",
7801: subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 7802: }
7803: }
1.296 brouard 7804: if(prevbcast==1){
1.268 brouard 7805: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
7806: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 7807: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
7808: 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 \
7809: 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 7810: 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);
7811: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"FB_"),subdirf2(optionfilefiname,"FB_"));
7812: fprintf(fichtm," <img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
1.268 brouard 7813: }
7814: }
1.220 brouard 7815:
1.222 brouard 7816: for(cpt=1; cpt<=nlstate;cpt++) {
1.314 brouard 7817: 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);
7818: fprintf(fichtm," (data from text file <a href=\"%s.txt\"> %s.txt</a>)\n<br>",subdirf2(optionfilefiname,"E_"),subdirf2(optionfilefiname,"E_"));
7819: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres );
1.222 brouard 7820: }
7821: /* } /\* end i1 *\/ */
1.337 brouard 7822: }/* End k1=nres */
1.222 brouard 7823: fprintf(fichtm,"</ul>");
1.126 brouard 7824:
1.222 brouard 7825: fprintf(fichtm,"\
1.126 brouard 7826: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 7827: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 7828: - 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 7829: But because parameters are usually highly correlated (a higher incidence of disability \
7830: and a higher incidence of recovery can give very close observed transition) it might \
7831: be very useful to look not only at linear confidence intervals estimated from the \
7832: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
7833: (parameters) of the logistic regression, it might be more meaningful to visualize the \
7834: covariance matrix of the one-step probabilities. \
7835: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 7836:
1.222 brouard 7837: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
7838: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
7839: fprintf(fichtm,"\
1.126 brouard 7840: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7841: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 7842:
1.222 brouard 7843: fprintf(fichtm,"\
1.126 brouard 7844: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7845: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
7846: fprintf(fichtm,"\
1.126 brouard 7847: - 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): \
7848: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7849: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 7850: fprintf(fichtm,"\
1.126 brouard 7851: - (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): \
7852: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7853: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 7854: fprintf(fichtm,"\
1.288 brouard 7855: - 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 7856: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
7857: fprintf(fichtm,"\
1.128 brouard 7858: - 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 7859: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
7860: fprintf(fichtm,"\
1.288 brouard 7861: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 7862: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 7863:
7864: /* if(popforecast==1) fprintf(fichtm,"\n */
7865: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
7866: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
7867: /* <br>",fileres,fileres,fileres,fileres); */
7868: /* else */
1.338 brouard 7869: /* fprintf(fichtm,"\n No population forecast: popforecast = %d (instead of 1) or stepm = %d (instead of 1) or model=1+age+%s (instead of .)<br><br></li>\n",popforecast, stepm, model); */
1.222 brouard 7870: fflush(fichtm);
1.126 brouard 7871:
1.225 brouard 7872: m=pow(2,cptcoveff);
1.222 brouard 7873: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7874:
1.317 brouard 7875: fprintf(fichtm," <ul><li><b>Graphs (second order)</b></li><p>");
7876:
7877: jj1=0;
7878:
7879: fprintf(fichtm," \n<ul>");
1.337 brouard 7880: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
7881: /* k1=nres; */
1.338 brouard 7882: k1=TKresult[nres];
1.337 brouard 7883: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
7884: /* if(m != 1 && TKresult[nres]!= k1) */
7885: /* continue; */
1.317 brouard 7886: jj1++;
7887: if (cptcovn > 0) {
7888: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescovsecond");
1.337 brouard 7889: for (cpt=1; cpt<=cptcovs;cpt++){
7890: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 7891: }
7892: fprintf(fichtm,"\">");
7893:
7894: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
7895: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 7896: for (cpt=1; cpt<=cptcovs;cpt++){
7897: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 7898: }
7899: if(invalidvarcomb[k1]){
7900: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
7901: continue;
7902: }
7903: fprintf(fichtm,"</a></li>");
7904: } /* cptcovn >0 */
1.337 brouard 7905: } /* End nres */
1.317 brouard 7906: fprintf(fichtm," \n</ul>");
7907:
1.222 brouard 7908: jj1=0;
1.237 brouard 7909:
1.241 brouard 7910: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 7911: /* k1=nres; */
1.338 brouard 7912: k1=TKresult[nres];
7913: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 7914: /* for(k1=1; k1<=m;k1++){ */
7915: /* if(m != 1 && TKresult[nres]!= k1) */
7916: /* continue; */
1.222 brouard 7917: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7918: jj1++;
1.126 brouard 7919: if (cptcovn > 0) {
1.317 brouard 7920: fprintf(fichtm,"\n<p><a name=\"rescovsecond");
1.337 brouard 7921: for (cpt=1; cpt<=cptcovs;cpt++){
7922: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 7923: }
7924: fprintf(fichtm,"\"</a>");
7925:
1.126 brouard 7926: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 7927: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcoveff number of variables */
7928: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
7929: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 7930: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
1.317 brouard 7931: }
1.237 brouard 7932:
1.338 brouard 7933: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.220 brouard 7934:
1.222 brouard 7935: if(invalidvarcomb[k1]){
7936: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
7937: continue;
7938: }
1.337 brouard 7939: } /* If cptcovn >0 */
1.126 brouard 7940: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 7941: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.314 brouard 7942: 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);
7943: fprintf(fichtm," (data from text file <a href=\"%s\">%s</a>)\n <br>",subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
7944: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"V_"), cpt,k1,nres);
1.126 brouard 7945: }
7946: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.314 brouard 7947: health expectancies in each live states (1 to %d). If popbased=1 the smooth (due to the model) \
1.128 brouard 7948: true period expectancies (those weighted with period prevalences are also\
7949: drawn in addition to the population based expectancies computed using\
1.314 brouard 7950: 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);
7951: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>) \n<br>",subdirf2(optionfilefiname,"T_"),subdirf2(optionfilefiname,"T_"));
7952: fprintf(fichtm,"<img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 7953: /* } /\* end i1 *\/ */
1.241 brouard 7954: }/* End nres */
1.222 brouard 7955: fprintf(fichtm,"</ul>");
7956: fflush(fichtm);
1.126 brouard 7957: }
7958:
7959: /******************* Gnuplot file **************/
1.296 brouard 7960: 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 7961:
7962: char dirfileres[132],optfileres[132];
1.264 brouard 7963: char gplotcondition[132], gplotlabel[132];
1.237 brouard 7964: 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 7965: int lv=0, vlv=0, kl=0;
1.130 brouard 7966: int ng=0;
1.201 brouard 7967: int vpopbased;
1.223 brouard 7968: int ioffset; /* variable offset for columns */
1.270 brouard 7969: int iyearc=1; /* variable column for year of projection */
7970: int iagec=1; /* variable column for age of projection */
1.235 brouard 7971: int nres=0; /* Index of resultline */
1.266 brouard 7972: int istart=1; /* For starting graphs in projections */
1.219 brouard 7973:
1.126 brouard 7974: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
7975: /* printf("Problem with file %s",optionfilegnuplot); */
7976: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
7977: /* } */
7978:
7979: /*#ifdef windows */
7980: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 7981: /*#endif */
1.225 brouard 7982: m=pow(2,cptcoveff);
1.126 brouard 7983:
1.274 brouard 7984: /* diagram of the model */
7985: fprintf(ficgp,"\n#Diagram of the model \n");
7986: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
7987: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
7988: 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);
7989:
7990: 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);
7991: fprintf(ficgp,"\n#show arrow\nunset label\n");
7992: 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);
7993: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
7994: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
7995: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
7996: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
7997:
1.202 brouard 7998: /* Contribution to likelihood */
7999: /* Plot the probability implied in the likelihood */
1.223 brouard 8000: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
8001: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
8002: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
8003: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 8004: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 8005: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
8006: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 8007: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
8008: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
8009: 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));
8010: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
8011: 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));
8012: for (i=1; i<= nlstate ; i ++) {
8013: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
8014: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
8015: 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);
8016: for (j=2; j<= nlstate+ndeath ; j ++) {
8017: 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);
8018: }
8019: fprintf(ficgp,";\nset out; unset ylabel;\n");
8020: }
8021: /* 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 */
8022: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
8023: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
8024: fprintf(ficgp,"\nset out;unset log\n");
8025: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 8026:
1.126 brouard 8027: strcpy(dirfileres,optionfilefiname);
8028: strcpy(optfileres,"vpl");
1.223 brouard 8029: /* 1eme*/
1.238 brouard 8030: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
1.337 brouard 8031: /* for (k1=1; k1<= m ; k1 ++){ /\* For each valid combination of covariate *\/ */
1.236 brouard 8032: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8033: k1=TKresult[nres];
1.338 brouard 8034: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.238 brouard 8035: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.337 brouard 8036: /* if(m != 1 && TKresult[nres]!= k1) */
8037: /* continue; */
1.238 brouard 8038: /* We are interested in selected combination by the resultline */
1.246 brouard 8039: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 8040: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 8041: strcpy(gplotlabel,"(");
1.337 brouard 8042: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8043: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8044: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8045:
8046: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate k get corresponding value lv for combination k1 *\/ */
8047: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the value of the covariate corresponding to k1 combination *\\/ *\/ */
8048: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8049: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8050: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8051: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8052: /* vlv= nbcode[Tvaraff[k]][lv]; /\* vlv is the value of the covariate lv, 0 or 1 *\/ */
8053: /* /\* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv *\/ */
8054: /* /\* printf(" V%d=%d ",Tvaraff[k],vlv); *\/ */
8055: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8056: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8057: /* } */
8058: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8059: /* /\* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); *\/ */
8060: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8061: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.264 brouard 8062: }
8063: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 8064: /* printf("\n#\n"); */
1.238 brouard 8065: fprintf(ficgp,"\n#\n");
8066: if(invalidvarcomb[k1]){
1.260 brouard 8067: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 8068: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8069: continue;
8070: }
1.235 brouard 8071:
1.241 brouard 8072: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
8073: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 8074: /* fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel); */
1.338 brouard 8075: fprintf(ficgp,"set title \"Alive state %d %s model=1+age+%s\" font \"Helvetica,12\"\n",cpt,gplotlabel,model);
1.260 brouard 8076: 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);
8077: /* 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); */
8078: /* k1-1 error should be nres-1*/
1.238 brouard 8079: for (i=1; i<= nlstate ; i ++) {
8080: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8081: else fprintf(ficgp," %%*lf (%%*lf)");
8082: }
1.288 brouard 8083: 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 8084: for (i=1; i<= nlstate ; i ++) {
8085: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8086: else fprintf(ficgp," %%*lf (%%*lf)");
8087: }
1.260 brouard 8088: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 8089: for (i=1; i<= nlstate ; i ++) {
8090: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8091: else fprintf(ficgp," %%*lf (%%*lf)");
8092: }
1.265 brouard 8093: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
8094:
8095: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
8096: if(cptcoveff ==0){
1.271 brouard 8097: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 8098: }else{
8099: kl=0;
8100: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 8101: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
8102: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.265 brouard 8103: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8104: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8105: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8106: vlv= nbcode[Tvaraff[k]][lv];
8107: kl++;
8108: /* 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 *\/ */
8109: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8110: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8111: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
8112: if(k==cptcoveff){
8113: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
8114: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
8115: }else{
8116: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
8117: kl++;
8118: }
8119: } /* end covariate */
8120: } /* end if no covariate */
8121:
1.296 brouard 8122: if(prevbcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
1.238 brouard 8123: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 8124: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 8125: if(cptcoveff ==0){
1.245 brouard 8126: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 8127: }else{
8128: kl=0;
8129: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 8130: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
8131: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.238 brouard 8132: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8133: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8134: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 8135: /* vlv= nbcode[Tvaraff[k]][lv]; */
8136: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.223 brouard 8137: kl++;
1.238 brouard 8138: /* 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 *\/ */
8139: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8140: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8141: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
8142: if(k==cptcoveff){
1.245 brouard 8143: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 8144: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 8145: }else{
1.332 brouard 8146: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]);
1.238 brouard 8147: kl++;
8148: }
8149: } /* end covariate */
8150: } /* end if no covariate */
1.296 brouard 8151: if(prevbcast == 1){
1.268 brouard 8152: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
8153: /* k1-1 error should be nres-1*/
8154: for (i=1; i<= nlstate ; i ++) {
8155: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8156: else fprintf(ficgp," %%*lf (%%*lf)");
8157: }
1.271 brouard 8158: 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 8159: for (i=1; i<= nlstate ; i ++) {
8160: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8161: else fprintf(ficgp," %%*lf (%%*lf)");
8162: }
1.276 brouard 8163: 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 8164: for (i=1; i<= nlstate ; i ++) {
8165: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8166: else fprintf(ficgp," %%*lf (%%*lf)");
8167: }
1.274 brouard 8168: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 8169: } /* end if backprojcast */
1.296 brouard 8170: } /* end if prevbcast */
1.276 brouard 8171: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
8172: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 8173: } /* nres */
1.337 brouard 8174: /* } /\* k1 *\/ */
1.201 brouard 8175: } /* cpt */
1.235 brouard 8176:
8177:
1.126 brouard 8178: /*2 eme*/
1.337 brouard 8179: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 8180: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8181: k1=TKresult[nres];
1.338 brouard 8182: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8183: /* if(m != 1 && TKresult[nres]!= k1) */
8184: /* continue; */
1.238 brouard 8185: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 8186: strcpy(gplotlabel,"(");
1.337 brouard 8187: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8188: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8189: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8190: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8191: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8192: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8193: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8194: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8195: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8196: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8197: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8198: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8199: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8200: /* } */
8201: /* /\* for(k=1; k <= ncovds; k++){ *\/ */
8202: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8203: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8204: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8205: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 8206: }
1.264 brouard 8207: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8208: fprintf(ficgp,"\n#\n");
1.223 brouard 8209: if(invalidvarcomb[k1]){
8210: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8211: continue;
8212: }
1.219 brouard 8213:
1.241 brouard 8214: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 8215: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 8216: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
8217: if(vpopbased==0){
1.238 brouard 8218: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 8219: }else
1.238 brouard 8220: fprintf(ficgp,"\nreplot ");
8221: for (i=1; i<= nlstate+1 ; i ++) {
8222: k=2*i;
1.261 brouard 8223: 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 8224: for (j=1; j<= nlstate+1 ; j ++) {
8225: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8226: else fprintf(ficgp," %%*lf (%%*lf)");
8227: }
8228: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
8229: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 8230: 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 8231: for (j=1; j<= nlstate+1 ; j ++) {
8232: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8233: else fprintf(ficgp," %%*lf (%%*lf)");
8234: }
8235: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 8236: 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 8237: for (j=1; j<= nlstate+1 ; j ++) {
8238: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8239: else fprintf(ficgp," %%*lf (%%*lf)");
8240: }
8241: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
8242: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
8243: } /* state */
8244: } /* vpopbased */
1.264 brouard 8245: 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 8246: } /* end nres */
1.337 brouard 8247: /* } /\* k1 end 2 eme*\/ */
1.238 brouard 8248:
8249:
8250: /*3eme*/
1.337 brouard 8251: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 8252: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8253: k1=TKresult[nres];
1.338 brouard 8254: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8255: /* if(m != 1 && TKresult[nres]!= k1) */
8256: /* continue; */
1.238 brouard 8257:
1.332 brouard 8258: for (cpt=1; cpt<= nlstate ; cpt ++) { /* Fragile no verification of covariate values */
1.261 brouard 8259: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 8260: strcpy(gplotlabel,"(");
1.337 brouard 8261: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8262: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8263: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8264: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8265: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8266: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8267: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8268: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8269: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8270: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8271: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8272: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8273: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8274: /* } */
8275: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8276: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
8277: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
8278: }
1.264 brouard 8279: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8280: fprintf(ficgp,"\n#\n");
8281: if(invalidvarcomb[k1]){
8282: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8283: continue;
8284: }
8285:
8286: /* k=2+nlstate*(2*cpt-2); */
8287: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 8288: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 8289: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 8290: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 8291: 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 8292: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8293: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8294: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
8295: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8296: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8297: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 8298:
1.238 brouard 8299: */
8300: for (i=1; i< nlstate ; i ++) {
1.261 brouard 8301: 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 8302: /* 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 8303:
1.238 brouard 8304: }
1.261 brouard 8305: 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 8306: }
1.264 brouard 8307: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 8308: } /* end nres */
1.337 brouard 8309: /* } /\* end kl 3eme *\/ */
1.126 brouard 8310:
1.223 brouard 8311: /* 4eme */
1.201 brouard 8312: /* Survival functions (period) from state i in state j by initial state i */
1.337 brouard 8313: /* for (k1=1; k1<=m; k1++){ /\* For each covariate and each value *\/ */
1.238 brouard 8314: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8315: k1=TKresult[nres];
1.338 brouard 8316: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8317: /* if(m != 1 && TKresult[nres]!= k1) */
8318: /* continue; */
1.238 brouard 8319: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 8320: strcpy(gplotlabel,"(");
1.337 brouard 8321: fprintf(ficgp,"\n#\n#\n# Survival functions in state %d : 'LIJ_' files, cov=%d state=%d", cpt, k1, cpt);
8322: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8323: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8324: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8325: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8326: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8327: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8328: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8329: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8330: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8331: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8332: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8333: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8334: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8335: /* } */
8336: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8337: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8338: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 8339: }
1.264 brouard 8340: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8341: fprintf(ficgp,"\n#\n");
8342: if(invalidvarcomb[k1]){
8343: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8344: continue;
1.223 brouard 8345: }
1.238 brouard 8346:
1.241 brouard 8347: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 8348: 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 8349: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8350: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8351: k=3;
8352: for (i=1; i<= nlstate ; i ++){
8353: if(i==1){
8354: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8355: }else{
8356: fprintf(ficgp,", '' ");
8357: }
8358: l=(nlstate+ndeath)*(i-1)+1;
8359: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8360: for (j=2; j<= nlstate+ndeath ; j ++)
8361: fprintf(ficgp,"+$%d",k+l+j-1);
8362: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
8363: } /* nlstate */
1.264 brouard 8364: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8365: } /* end cpt state*/
8366: } /* end nres */
1.337 brouard 8367: /* } /\* end covariate k1 *\/ */
1.238 brouard 8368:
1.220 brouard 8369: /* 5eme */
1.201 brouard 8370: /* Survival functions (period) from state i in state j by final state j */
1.337 brouard 8371: /* for (k1=1; k1<= m ; k1++){ /\* For each covariate combination if any *\/ */
1.238 brouard 8372: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8373: k1=TKresult[nres];
1.338 brouard 8374: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8375: /* if(m != 1 && TKresult[nres]!= k1) */
8376: /* continue; */
1.238 brouard 8377: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 8378: strcpy(gplotlabel,"(");
1.238 brouard 8379: fprintf(ficgp,"\n#\n#\n# Survival functions in state j and all livestates from state i by final state j: 'lij' files, cov=%d state=%d",k1, cpt);
1.337 brouard 8380: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8381: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8382: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8383: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8384: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8385: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8386: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8387: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8388: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8389: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8390: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8391: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8392: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8393: /* } */
8394: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8395: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8396: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 8397: }
1.264 brouard 8398: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8399: fprintf(ficgp,"\n#\n");
8400: if(invalidvarcomb[k1]){
8401: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8402: continue;
8403: }
1.227 brouard 8404:
1.241 brouard 8405: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 8406: 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 8407: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8408: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8409: k=3;
8410: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8411: if(j==1)
8412: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8413: else
8414: fprintf(ficgp,", '' ");
8415: l=(nlstate+ndeath)*(cpt-1) +j;
8416: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
8417: /* for (i=2; i<= nlstate+ndeath ; i ++) */
8418: /* fprintf(ficgp,"+$%d",k+l+i-1); */
8419: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
8420: } /* nlstate */
8421: fprintf(ficgp,", '' ");
8422: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
8423: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8424: l=(nlstate+ndeath)*(cpt-1) +j;
8425: if(j < nlstate)
8426: fprintf(ficgp,"$%d +",k+l);
8427: else
8428: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
8429: }
1.264 brouard 8430: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8431: } /* end cpt state*/
1.337 brouard 8432: /* } /\* end covariate *\/ */
1.238 brouard 8433: } /* end nres */
1.227 brouard 8434:
1.220 brouard 8435: /* 6eme */
1.202 brouard 8436: /* CV preval stable (period) for each covariate */
1.337 brouard 8437: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8438: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8439: k1=TKresult[nres];
1.338 brouard 8440: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8441: /* if(m != 1 && TKresult[nres]!= k1) */
8442: /* continue; */
1.255 brouard 8443: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 8444: strcpy(gplotlabel,"(");
1.288 brouard 8445: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 8446: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8447: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8448: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8449: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8450: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8451: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8452: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8453: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8454: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8455: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8456: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8457: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8458: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8459: /* } */
8460: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8461: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8462: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 8463: }
1.264 brouard 8464: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8465: fprintf(ficgp,"\n#\n");
1.223 brouard 8466: if(invalidvarcomb[k1]){
1.227 brouard 8467: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8468: continue;
1.223 brouard 8469: }
1.227 brouard 8470:
1.241 brouard 8471: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 8472: 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 8473: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 8474: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 8475: k=3; /* Offset */
1.255 brouard 8476: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 8477: if(i==1)
8478: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8479: else
8480: fprintf(ficgp,", '' ");
1.255 brouard 8481: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 8482: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8483: for (j=2; j<= nlstate ; j ++)
8484: fprintf(ficgp,"+$%d",k+l+j-1);
8485: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 8486: } /* nlstate */
1.264 brouard 8487: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 8488: } /* end cpt state*/
8489: } /* end covariate */
1.227 brouard 8490:
8491:
1.220 brouard 8492: /* 7eme */
1.296 brouard 8493: if(prevbcast == 1){
1.288 brouard 8494: /* CV backward prevalence for each covariate */
1.337 brouard 8495: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8496: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8497: k1=TKresult[nres];
1.338 brouard 8498: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8499: /* if(m != 1 && TKresult[nres]!= k1) */
8500: /* continue; */
1.268 brouard 8501: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 8502: strcpy(gplotlabel,"(");
1.288 brouard 8503: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 8504: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8505: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8506: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8507: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8508: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8509: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8510: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8511: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8512: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8513: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8514: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8515: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8516: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8517: /* } */
8518: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8519: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8520: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 8521: }
1.264 brouard 8522: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 8523: fprintf(ficgp,"\n#\n");
8524: if(invalidvarcomb[k1]){
8525: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8526: continue;
8527: }
8528:
1.241 brouard 8529: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 8530: 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 8531: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 8532: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 8533: k=3; /* Offset */
1.268 brouard 8534: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 8535: if(i==1)
8536: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
8537: else
8538: fprintf(ficgp,", '' ");
8539: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 8540: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.324 brouard 8541: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
8542: /* 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 8543: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 8544: /* for (j=2; j<= nlstate ; j ++) */
8545: /* fprintf(ficgp,"+$%d",k+l+j-1); */
8546: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 8547: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 8548: } /* nlstate */
1.264 brouard 8549: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 8550: } /* end cpt state*/
8551: } /* end covariate */
1.296 brouard 8552: } /* End if prevbcast */
1.218 brouard 8553:
1.223 brouard 8554: /* 8eme */
1.218 brouard 8555: if(prevfcast==1){
1.288 brouard 8556: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 8557:
1.337 brouard 8558: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8559: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8560: k1=TKresult[nres];
1.338 brouard 8561: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8562: /* if(m != 1 && TKresult[nres]!= k1) */
8563: /* continue; */
1.211 brouard 8564: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 8565: strcpy(gplotlabel,"(");
1.288 brouard 8566: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 8567: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8568: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8569: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8570: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
8571: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
8572: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8573: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8574: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8575: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8576: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8577: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8578: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8579: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8580: /* } */
8581: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8582: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8583: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 8584: }
1.264 brouard 8585: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 8586: fprintf(ficgp,"\n#\n");
8587: if(invalidvarcomb[k1]){
8588: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8589: continue;
8590: }
8591:
8592: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 8593: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 8594: 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 8595: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 8596: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 8597:
8598: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
8599: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
8600: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
8601: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 8602: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8603: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8604: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8605: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 8606: if(i==istart){
1.227 brouard 8607: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
8608: }else{
8609: fprintf(ficgp,",\\\n '' ");
8610: }
8611: if(cptcoveff ==0){ /* No covariate */
8612: ioffset=2; /* Age is in 2 */
8613: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8614: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8615: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8616: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8617: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 8618: if(i==nlstate+1){
1.270 brouard 8619: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 8620: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
8621: fprintf(ficgp,",\\\n '' ");
8622: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 8623: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 8624: offyear, \
1.268 brouard 8625: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 8626: }else
1.227 brouard 8627: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
8628: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
8629: }else{ /* more than 2 covariates */
1.270 brouard 8630: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
8631: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8632: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8633: iyearc=ioffset-1;
8634: iagec=ioffset;
1.227 brouard 8635: fprintf(ficgp," u %d:(",ioffset);
8636: kl=0;
8637: strcpy(gplotcondition,"(");
8638: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
1.332 brouard 8639: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8640: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.227 brouard 8641: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8642: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8643: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 8644: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
8645: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.227 brouard 8646: kl++;
8647: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
8648: kl++;
8649: if(k <cptcoveff && cptcoveff>1)
8650: sprintf(gplotcondition+strlen(gplotcondition)," && ");
8651: }
8652: strcpy(gplotcondition+strlen(gplotcondition),")");
8653: /* 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 *\/ */
8654: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8655: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8656: /* '' 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*/
8657: if(i==nlstate+1){
1.270 brouard 8658: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
8659: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 8660: fprintf(ficgp,",\\\n '' ");
1.270 brouard 8661: fprintf(ficgp," u %d:(",iagec);
8662: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
8663: iyearc, iagec, offyear, \
8664: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 8665: /* '' 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 8666: }else{
8667: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
8668: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
8669: }
8670: } /* end if covariate */
8671: } /* nlstate */
1.264 brouard 8672: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 8673: } /* end cpt state*/
8674: } /* end covariate */
8675: } /* End if prevfcast */
1.227 brouard 8676:
1.296 brouard 8677: if(prevbcast==1){
1.268 brouard 8678: /* Back projection from cross-sectional to stable (mixed) for each covariate */
8679:
1.337 brouard 8680: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.268 brouard 8681: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8682: k1=TKresult[nres];
1.338 brouard 8683: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8684: /* if(m != 1 && TKresult[nres]!= k1) */
8685: /* continue; */
1.268 brouard 8686: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
8687: strcpy(gplotlabel,"(");
8688: fprintf(ficgp,"\n#\n#\n#Back projection of prevalence to stable (mixed) back prevalence: 'BPROJ_' files, covariatecombination#=%d originstate=%d",k1, cpt);
1.337 brouard 8689: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8690: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8691: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8692: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
8693: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
8694: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8695: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8696: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8697: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8698: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8699: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8700: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8701: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8702: /* } */
8703: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8704: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8705: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.268 brouard 8706: }
8707: strcpy(gplotlabel+strlen(gplotlabel),")");
8708: fprintf(ficgp,"\n#\n");
8709: if(invalidvarcomb[k1]){
8710: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8711: continue;
8712: }
8713:
8714: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
8715: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
8716: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
8717: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
8718: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8719:
8720: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
8721: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
8722: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
8723: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
8724: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8725: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8726: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8727: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8728: if(i==istart){
8729: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
8730: }else{
8731: fprintf(ficgp,",\\\n '' ");
8732: }
8733: if(cptcoveff ==0){ /* No covariate */
8734: ioffset=2; /* Age is in 2 */
8735: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8736: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8737: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8738: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8739: fprintf(ficgp," u %d:(", ioffset);
8740: if(i==nlstate+1){
1.270 brouard 8741: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 8742: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
8743: fprintf(ficgp,",\\\n '' ");
8744: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 8745: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 8746: offbyear, \
8747: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
8748: }else
8749: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
8750: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
8751: }else{ /* more than 2 covariates */
1.270 brouard 8752: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
8753: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8754: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8755: iyearc=ioffset-1;
8756: iagec=ioffset;
1.268 brouard 8757: fprintf(ficgp," u %d:(",ioffset);
8758: kl=0;
8759: strcpy(gplotcondition,"(");
1.337 brouard 8760: for (k=1; k<=cptcovs; k++){ /* For each covariate k of the resultline, get corresponding value lv for combination k1 */
1.338 brouard 8761: if(Dummy[modelresult[nres][k]]==0){ /* To be verified */
1.337 brouard 8762: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate writing the chain of conditions *\/ */
8763: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8764: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8765: lv=Tvresult[nres][k];
8766: vlv=TinvDoQresult[nres][Tvresult[nres][k]];
8767: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8768: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8769: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8770: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
8771: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8772: kl++;
8773: /* sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); */
8774: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%lg " ,kl,Tvresult[nres][k], kl+1,TinvDoQresult[nres][Tvresult[nres][k]]);
8775: kl++;
1.338 brouard 8776: if(k <cptcovs && cptcovs>1)
1.337 brouard 8777: sprintf(gplotcondition+strlen(gplotcondition)," && ");
8778: }
1.268 brouard 8779: }
8780: strcpy(gplotcondition+strlen(gplotcondition),")");
8781: /* 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 *\/ */
8782: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8783: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8784: /* '' 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*/
8785: if(i==nlstate+1){
1.270 brouard 8786: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
8787: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 8788: fprintf(ficgp,",\\\n '' ");
1.270 brouard 8789: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 8790: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 8791: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
8792: iyearc,iagec,offbyear, \
8793: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 8794: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
8795: }else{
8796: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
8797: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
8798: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
8799: }
8800: } /* end if covariate */
8801: } /* nlstate */
8802: fprintf(ficgp,"\nset out; unset label;\n");
8803: } /* end cpt state*/
8804: } /* end covariate */
1.296 brouard 8805: } /* End if prevbcast */
1.268 brouard 8806:
1.227 brouard 8807:
1.238 brouard 8808: /* 9eme writing MLE parameters */
8809: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 8810: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 8811: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 8812: for(k=1; k <=(nlstate+ndeath); k++){
8813: if (k != i) {
1.227 brouard 8814: fprintf(ficgp,"# current state %d\n",k);
8815: for(j=1; j <=ncovmodel; j++){
8816: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
8817: jk++;
8818: }
8819: fprintf(ficgp,"\n");
1.126 brouard 8820: }
8821: }
1.223 brouard 8822: }
1.187 brouard 8823: fprintf(ficgp,"##############\n#\n");
1.227 brouard 8824:
1.145 brouard 8825: /*goto avoid;*/
1.238 brouard 8826: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
8827: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 8828: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
8829: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
8830: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
8831: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
8832: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8833: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
8834: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8835: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
8836: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
8837: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8838: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
8839: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
8840: fprintf(ficgp,"#\n");
1.223 brouard 8841: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 8842: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.338 brouard 8843: fprintf(ficgp,"#model=1+age+%s \n",model);
1.238 brouard 8844: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 brouard 8845: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
1.337 brouard 8846: /* for(k1=1; k1 <=m; k1++) /\* For each combination of covariate *\/ */
1.237 brouard 8847: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8848: /* k1=nres; */
1.338 brouard 8849: k1=TKresult[nres];
8850: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8851: fprintf(ficgp,"\n\n# Resultline k1=%d ",k1);
1.264 brouard 8852: strcpy(gplotlabel,"(");
1.276 brouard 8853: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.337 brouard 8854: for (k=1; k<=cptcovs; k++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
8855: /* for each resultline nres, and position k, Tvresult[nres][k] gives the name of the variable and
8856: TinvDoQresult[nres][Tvresult[nres][k]] gives its value double or integer) */
8857: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8858: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8859: }
8860: /* if(m != 1 && TKresult[nres]!= k1) */
8861: /* continue; */
8862: /* fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1); */
8863: /* strcpy(gplotlabel,"("); */
8864: /* /\*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*\/ */
8865: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
8866: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
8867: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8868: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8869: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8870: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8871: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8872: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8873: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8874: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8875: /* } */
8876: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8877: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8878: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8879: /* } */
1.264 brouard 8880: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 8881: fprintf(ficgp,"\n#\n");
1.264 brouard 8882: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 8883: fprintf(ficgp,"\nset key outside ");
8884: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
8885: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 8886: fprintf(ficgp,"\nset ter svg size 640, 480 ");
8887: if (ng==1){
8888: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
8889: fprintf(ficgp,"\nunset log y");
8890: }else if (ng==2){
8891: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
8892: fprintf(ficgp,"\nset log y");
8893: }else if (ng==3){
8894: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
8895: fprintf(ficgp,"\nset log y");
8896: }else
8897: fprintf(ficgp,"\nunset title ");
8898: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
8899: i=1;
8900: for(k2=1; k2<=nlstate; k2++) {
8901: k3=i;
8902: for(k=1; k<=(nlstate+ndeath); k++) {
8903: if (k != k2){
8904: switch( ng) {
8905: case 1:
8906: if(nagesqr==0)
8907: fprintf(ficgp," p%d+p%d*x",i,i+1);
8908: else /* nagesqr =1 */
8909: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
8910: break;
8911: case 2: /* ng=2 */
8912: if(nagesqr==0)
8913: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
8914: else /* nagesqr =1 */
8915: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
8916: break;
8917: case 3:
8918: if(nagesqr==0)
8919: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
8920: else /* nagesqr =1 */
8921: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
8922: break;
8923: }
8924: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 8925: ijp=1; /* product no age */
8926: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
8927: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 8928: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.329 brouard 8929: switch(Typevar[j]){
8930: case 1:
8931: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
8932: if(j==Tage[ij]) { /* Product by age To be looked at!!*//* Bug valgrind */
8933: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
8934: if(DummyV[j]==0){/* Bug valgrind */
8935: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
8936: }else{ /* quantitative */
8937: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
8938: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8939: }
8940: ij++;
1.268 brouard 8941: }
1.237 brouard 8942: }
1.329 brouard 8943: }
8944: break;
8945: case 2:
8946: if(cptcovprod >0){
8947: if(j==Tprod[ijp]) { /* */
8948: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
8949: if(ijp <=cptcovprod) { /* Product */
8950: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
8951: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
8952: /* 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)]); */
8953: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
8954: }else{ /* Vn is dummy and Vm is quanti */
8955: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
8956: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8957: }
8958: }else{ /* Vn*Vm Vn is quanti */
8959: if(DummyV[Tvard[ijp][2]]==0){
8960: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
8961: }else{ /* Both quanti */
8962: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8963: }
1.268 brouard 8964: }
1.329 brouard 8965: ijp++;
1.237 brouard 8966: }
1.329 brouard 8967: } /* end Tprod */
8968: }
8969: break;
8970: case 0:
8971: /* simple covariate */
1.264 brouard 8972: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 8973: if(Dummy[j]==0){
8974: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
8975: }else{ /* quantitative */
8976: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 8977: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 8978: }
1.329 brouard 8979: /* end simple */
8980: break;
8981: default:
8982: break;
8983: } /* end switch */
1.237 brouard 8984: } /* end j */
1.329 brouard 8985: }else{ /* k=k2 */
8986: if(ng !=1 ){ /* For logit formula of log p11 is more difficult to get */
8987: fprintf(ficgp," (1.");i=i-ncovmodel;
8988: }else
8989: i=i-ncovmodel;
1.223 brouard 8990: }
1.227 brouard 8991:
1.223 brouard 8992: if(ng != 1){
8993: fprintf(ficgp,")/(1");
1.227 brouard 8994:
1.264 brouard 8995: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 8996: if(nagesqr==0)
1.264 brouard 8997: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 8998: else /* nagesqr =1 */
1.264 brouard 8999: 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 9000:
1.223 brouard 9001: ij=1;
1.329 brouard 9002: ijp=1;
9003: /* for(j=3; j <=ncovmodel-nagesqr; j++){ */
9004: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
9005: switch(Typevar[j]){
9006: case 1:
9007: if(cptcovage >0){
9008: if(j==Tage[ij]) { /* Bug valgrind */
9009: if(ij <=cptcovage) { /* Bug valgrind */
9010: if(DummyV[j]==0){/* Bug valgrind */
9011: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]); */
9012: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,nbcode[Tvar[j]][codtabm(k1,j)]); */
9013: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]);
9014: /* fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);; */
9015: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9016: }else{ /* quantitative */
9017: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
9018: fprintf(ficgp,"+p%d*%f*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
9019: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
9020: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9021: }
9022: ij++;
9023: }
9024: }
9025: }
9026: break;
9027: case 2:
9028: if(cptcovprod >0){
9029: if(j==Tprod[ijp]) { /* */
9030: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9031: if(ijp <=cptcovprod) { /* Product */
9032: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
9033: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
9034: /* 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)]); */
9035: fprintf(ficgp,"+p%d*%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9036: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
9037: }else{ /* Vn is dummy and Vm is quanti */
9038: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
9039: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9040: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9041: }
9042: }else{ /* Vn*Vm Vn is quanti */
9043: if(DummyV[Tvard[ijp][2]]==0){
9044: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
9045: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
9046: }else{ /* Both quanti */
9047: fprintf(ficgp,"+p%d*%f*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9048: /* fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9049: }
9050: }
9051: ijp++;
9052: }
9053: } /* end Tprod */
9054: } /* end if */
9055: break;
9056: case 0:
9057: /* simple covariate */
9058: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
9059: if(Dummy[j]==0){
9060: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
9061: fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]); /* */
9062: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
9063: }else{ /* quantitative */
9064: fprintf(ficgp,"+p%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* */
9065: /* fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* *\/ */
9066: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9067: }
9068: /* end simple */
9069: /* fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);/\* Valgrind bug nbcode *\/ */
9070: break;
9071: default:
9072: break;
9073: } /* end switch */
1.223 brouard 9074: }
9075: fprintf(ficgp,")");
9076: }
9077: fprintf(ficgp,")");
9078: if(ng ==2)
1.276 brouard 9079: 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 9080: else /* ng= 3 */
1.276 brouard 9081: 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 9082: }else{ /* end ng <> 1 */
1.223 brouard 9083: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 9084: 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 9085: }
9086: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
9087: fprintf(ficgp,",");
9088: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
9089: fprintf(ficgp,",");
9090: i=i+ncovmodel;
9091: } /* end k */
9092: } /* end k2 */
1.276 brouard 9093: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
9094: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.337 brouard 9095: } /* end resultline */
1.223 brouard 9096: } /* end ng */
9097: /* avoid: */
9098: fflush(ficgp);
1.126 brouard 9099: } /* end gnuplot */
9100:
9101:
9102: /*************** Moving average **************/
1.219 brouard 9103: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 9104: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 9105:
1.222 brouard 9106: int i, cpt, cptcod;
9107: int modcovmax =1;
9108: int mobilavrange, mob;
9109: int iage=0;
1.288 brouard 9110: int firstA1=0, firstA2=0;
1.222 brouard 9111:
1.266 brouard 9112: double sum=0., sumr=0.;
1.222 brouard 9113: double age;
1.266 brouard 9114: double *sumnewp, *sumnewm, *sumnewmr;
9115: double *agemingood, *agemaxgood;
9116: double *agemingoodr, *agemaxgoodr;
1.222 brouard 9117:
9118:
1.278 brouard 9119: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
9120: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 9121:
9122: sumnewp = vector(1,ncovcombmax);
9123: sumnewm = vector(1,ncovcombmax);
1.266 brouard 9124: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 9125: agemingood = vector(1,ncovcombmax);
1.266 brouard 9126: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 9127: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 9128: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 9129:
9130: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 9131: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 9132: sumnewp[cptcod]=0.;
1.266 brouard 9133: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
9134: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 9135: }
9136: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
9137:
1.266 brouard 9138: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
9139: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 9140: else mobilavrange=mobilav;
9141: for (age=bage; age<=fage; age++)
9142: for (i=1; i<=nlstate;i++)
9143: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
9144: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9145: /* We keep the original values on the extreme ages bage, fage and for
9146: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
9147: we use a 5 terms etc. until the borders are no more concerned.
9148: */
9149: for (mob=3;mob <=mobilavrange;mob=mob+2){
9150: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 9151: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
9152: sumnewm[cptcod]=0.;
9153: for (i=1; i<=nlstate;i++){
1.222 brouard 9154: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
9155: for (cpt=1;cpt<=(mob-1)/2;cpt++){
9156: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
9157: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
9158: }
9159: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 9160: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9161: } /* end i */
9162: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
9163: } /* end cptcod */
1.222 brouard 9164: }/* end age */
9165: }/* end mob */
1.266 brouard 9166: }else{
9167: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 9168: return -1;
1.266 brouard 9169: }
9170:
9171: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 9172: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
9173: if(invalidvarcomb[cptcod]){
9174: printf("\nCombination (%d) ignored because no cases \n",cptcod);
9175: continue;
9176: }
1.219 brouard 9177:
1.266 brouard 9178: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
9179: sumnewm[cptcod]=0.;
9180: sumnewmr[cptcod]=0.;
9181: for (i=1; i<=nlstate;i++){
9182: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9183: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9184: }
9185: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9186: agemingoodr[cptcod]=age;
9187: }
9188: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9189: agemingood[cptcod]=age;
9190: }
9191: } /* age */
9192: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 9193: sumnewm[cptcod]=0.;
1.266 brouard 9194: sumnewmr[cptcod]=0.;
1.222 brouard 9195: for (i=1; i<=nlstate;i++){
9196: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 9197: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9198: }
9199: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9200: agemaxgoodr[cptcod]=age;
1.222 brouard 9201: }
9202: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 9203: agemaxgood[cptcod]=age;
9204: }
9205: } /* age */
9206: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
9207: /* but they will change */
1.288 brouard 9208: firstA1=0;firstA2=0;
1.266 brouard 9209: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
9210: sumnewm[cptcod]=0.;
9211: sumnewmr[cptcod]=0.;
9212: for (i=1; i<=nlstate;i++){
9213: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9214: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9215: }
9216: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
9217: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9218: agemaxgoodr[cptcod]=age; /* age min */
9219: for (i=1; i<=nlstate;i++)
9220: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9221: }else{ /* bad we change the value with the values of good ages */
9222: for (i=1; i<=nlstate;i++){
9223: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
9224: } /* i */
9225: } /* end bad */
9226: }else{
9227: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9228: agemaxgood[cptcod]=age;
9229: }else{ /* bad we change the value with the values of good ages */
9230: for (i=1; i<=nlstate;i++){
9231: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
9232: } /* i */
9233: } /* end bad */
9234: }/* end else */
9235: sum=0.;sumr=0.;
9236: for (i=1; i<=nlstate;i++){
9237: sum+=mobaverage[(int)age][i][cptcod];
9238: sumr+=probs[(int)age][i][cptcod];
9239: }
9240: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 9241: if(!firstA1){
9242: firstA1=1;
9243: 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);
9244: }
9245: 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 9246: } /* end bad */
9247: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
9248: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 9249: if(!firstA2){
9250: firstA2=1;
9251: 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);
9252: }
9253: 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 9254: } /* end bad */
9255: }/* age */
1.266 brouard 9256:
9257: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 9258: sumnewm[cptcod]=0.;
1.266 brouard 9259: sumnewmr[cptcod]=0.;
1.222 brouard 9260: for (i=1; i<=nlstate;i++){
9261: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 9262: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9263: }
9264: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
9265: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
9266: agemingoodr[cptcod]=age;
9267: for (i=1; i<=nlstate;i++)
9268: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9269: }else{ /* bad we change the value with the values of good ages */
9270: for (i=1; i<=nlstate;i++){
9271: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
9272: } /* i */
9273: } /* end bad */
9274: }else{
9275: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9276: agemingood[cptcod]=age;
9277: }else{ /* bad */
9278: for (i=1; i<=nlstate;i++){
9279: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
9280: } /* i */
9281: } /* end bad */
9282: }/* end else */
9283: sum=0.;sumr=0.;
9284: for (i=1; i<=nlstate;i++){
9285: sum+=mobaverage[(int)age][i][cptcod];
9286: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 9287: }
1.266 brouard 9288: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 9289: 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 9290: } /* end bad */
9291: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
9292: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 9293: 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 9294: } /* end bad */
9295: }/* age */
1.266 brouard 9296:
1.222 brouard 9297:
9298: for (age=bage; age<=fage; age++){
1.235 brouard 9299: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 9300: sumnewp[cptcod]=0.;
9301: sumnewm[cptcod]=0.;
9302: for (i=1; i<=nlstate;i++){
9303: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
9304: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9305: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
9306: }
9307: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
9308: }
9309: /* printf("\n"); */
9310: /* } */
1.266 brouard 9311:
1.222 brouard 9312: /* brutal averaging */
1.266 brouard 9313: /* for (i=1; i<=nlstate;i++){ */
9314: /* for (age=1; age<=bage; age++){ */
9315: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
9316: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
9317: /* } */
9318: /* for (age=fage; age<=AGESUP; age++){ */
9319: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
9320: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
9321: /* } */
9322: /* } /\* end i status *\/ */
9323: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
9324: /* for (age=1; age<=AGESUP; age++){ */
9325: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
9326: /* mobaverage[(int)age][i][cptcod]=0.; */
9327: /* } */
9328: /* } */
1.222 brouard 9329: }/* end cptcod */
1.266 brouard 9330: free_vector(agemaxgoodr,1, ncovcombmax);
9331: free_vector(agemaxgood,1, ncovcombmax);
9332: free_vector(agemingood,1, ncovcombmax);
9333: free_vector(agemingoodr,1, ncovcombmax);
9334: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 9335: free_vector(sumnewm,1, ncovcombmax);
9336: free_vector(sumnewp,1, ncovcombmax);
9337: return 0;
9338: }/* End movingaverage */
1.218 brouard 9339:
1.126 brouard 9340:
1.296 brouard 9341:
1.126 brouard 9342: /************** Forecasting ******************/
1.296 brouard 9343: /* 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)*/
9344: 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){
9345: /* dateintemean, mean date of interviews
9346: dateprojd, year, month, day of starting projection
9347: dateprojf date of end of projection;year of end of projection (same day and month as proj1).
1.126 brouard 9348: agemin, agemax range of age
9349: dateprev1 dateprev2 range of dates during which prevalence is computed
9350: */
1.296 brouard 9351: /* double anprojd, mprojd, jprojd; */
9352: /* double anprojf, mprojf, jprojf; */
1.267 brouard 9353: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 9354: double agec; /* generic age */
1.296 brouard 9355: double agelim, ppij, yp,yp1,yp2;
1.126 brouard 9356: double *popeffectif,*popcount;
9357: double ***p3mat;
1.218 brouard 9358: /* double ***mobaverage; */
1.126 brouard 9359: char fileresf[FILENAMELENGTH];
9360:
9361: agelim=AGESUP;
1.211 brouard 9362: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
9363: in each health status at the date of interview (if between dateprev1 and dateprev2).
9364: We still use firstpass and lastpass as another selection.
9365: */
1.214 brouard 9366: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
9367: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 9368:
1.201 brouard 9369: strcpy(fileresf,"F_");
9370: strcat(fileresf,fileresu);
1.126 brouard 9371: if((ficresf=fopen(fileresf,"w"))==NULL) {
9372: printf("Problem with forecast resultfile: %s\n", fileresf);
9373: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
9374: }
1.235 brouard 9375: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
9376: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 9377:
1.225 brouard 9378: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 9379:
9380:
9381: stepsize=(int) (stepm+YEARM-1)/YEARM;
9382: if (stepm<=12) stepsize=1;
9383: if(estepm < stepm){
9384: printf ("Problem %d lower than %d\n",estepm, stepm);
9385: }
1.270 brouard 9386: else{
9387: hstepm=estepm;
9388: }
9389: if(estepm > stepm){ /* Yes every two year */
9390: stepsize=2;
9391: }
1.296 brouard 9392: hstepm=hstepm/stepm;
1.126 brouard 9393:
1.296 brouard 9394:
9395: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
9396: /* fractional in yp1 *\/ */
9397: /* aintmean=yp; */
9398: /* yp2=modf((yp1*12),&yp); */
9399: /* mintmean=yp; */
9400: /* yp1=modf((yp2*30.5),&yp); */
9401: /* jintmean=yp; */
9402: /* if(jintmean==0) jintmean=1; */
9403: /* if(mintmean==0) mintmean=1; */
1.126 brouard 9404:
1.296 brouard 9405:
9406: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */
9407: /* date2dmy(dateprojd,&jprojd, &mprojd, &anprojd); */
9408: /* date2dmy(dateprojf,&jprojf, &mprojf, &anprojf); */
1.227 brouard 9409: i1=pow(2,cptcoveff);
1.126 brouard 9410: if (cptcovn < 1){i1=1;}
9411:
1.296 brouard 9412: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.126 brouard 9413:
9414: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 9415:
1.126 brouard 9416: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 9417: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.332 brouard 9418: 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 9419: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 9420: continue;
1.227 brouard 9421: if(invalidvarcomb[k]){
9422: printf("\nCombination (%d) projection ignored because no cases \n",k);
9423: continue;
9424: }
9425: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
9426: for(j=1;j<=cptcoveff;j++) {
1.332 brouard 9427: /* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); */
9428: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.227 brouard 9429: }
1.235 brouard 9430: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 9431: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 9432: }
1.227 brouard 9433: fprintf(ficresf," yearproj age");
9434: for(j=1; j<=nlstate+ndeath;j++){
9435: for(i=1; i<=nlstate;i++)
9436: fprintf(ficresf," p%d%d",i,j);
9437: fprintf(ficresf," wp.%d",j);
9438: }
1.296 brouard 9439: for (yearp=0; yearp<=(anprojf-anprojd);yearp +=stepsize) {
1.227 brouard 9440: fprintf(ficresf,"\n");
1.296 brouard 9441: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jprojd,mprojd,anprojd+yearp);
1.270 brouard 9442: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
9443: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 9444: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
9445: nhstepm = nhstepm/hstepm;
9446: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9447: oldm=oldms;savm=savms;
1.268 brouard 9448: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 9449: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 9450: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 9451: for (h=0; h<=nhstepm; h++){
9452: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 9453: break;
9454: }
9455: }
9456: fprintf(ficresf,"\n");
9457: for(j=1;j<=cptcoveff;j++)
1.332 brouard 9458: /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Tvaraff not correct *\/ */
9459: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /* TnsdVar[Tvaraff] correct */
1.296 brouard 9460: fprintf(ficresf,"%.f %.f ",anprojd+yearp,agec+h*hstepm/YEARM*stepm);
1.268 brouard 9461:
9462: for(j=1; j<=nlstate+ndeath;j++) {
9463: ppij=0.;
9464: for(i=1; i<=nlstate;i++) {
1.278 brouard 9465: if (mobilav>=1)
9466: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
9467: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
9468: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
9469: }
1.268 brouard 9470: fprintf(ficresf," %.3f", p3mat[i][j][h]);
9471: } /* end i */
9472: fprintf(ficresf," %.3f", ppij);
9473: }/* end j */
1.227 brouard 9474: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9475: } /* end agec */
1.266 brouard 9476: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
9477: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 9478: } /* end yearp */
9479: } /* end k */
1.219 brouard 9480:
1.126 brouard 9481: fclose(ficresf);
1.215 brouard 9482: printf("End of Computing forecasting \n");
9483: fprintf(ficlog,"End of Computing forecasting\n");
9484:
1.126 brouard 9485: }
9486:
1.269 brouard 9487: /************** Back Forecasting ******************/
1.296 brouard 9488: /* 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){ */
9489: 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){
9490: /* back1, year, month, day of starting backprojection
1.267 brouard 9491: agemin, agemax range of age
9492: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 9493: anback2 year of end of backprojection (same day and month as back1).
9494: prevacurrent and prev are prevalences.
1.267 brouard 9495: */
9496: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
9497: double agec; /* generic age */
1.302 brouard 9498: double agelim, ppij, ppi, yp,yp1,yp2; /* ,jintmean,mintmean,aintmean;*/
1.267 brouard 9499: double *popeffectif,*popcount;
9500: double ***p3mat;
9501: /* double ***mobaverage; */
9502: char fileresfb[FILENAMELENGTH];
9503:
1.268 brouard 9504: agelim=AGEINF;
1.267 brouard 9505: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
9506: in each health status at the date of interview (if between dateprev1 and dateprev2).
9507: We still use firstpass and lastpass as another selection.
9508: */
9509: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
9510: /* firstpass, lastpass, stepm, weightopt, model); */
9511:
9512: /*Do we need to compute prevalence again?*/
9513:
9514: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
9515:
9516: strcpy(fileresfb,"FB_");
9517: strcat(fileresfb,fileresu);
9518: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
9519: printf("Problem with back forecast resultfile: %s\n", fileresfb);
9520: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
9521: }
9522: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
9523: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
9524:
9525: if (cptcoveff==0) ncodemax[cptcoveff]=1;
9526:
9527:
9528: stepsize=(int) (stepm+YEARM-1)/YEARM;
9529: if (stepm<=12) stepsize=1;
9530: if(estepm < stepm){
9531: printf ("Problem %d lower than %d\n",estepm, stepm);
9532: }
1.270 brouard 9533: else{
9534: hstepm=estepm;
9535: }
9536: if(estepm >= stepm){ /* Yes every two year */
9537: stepsize=2;
9538: }
1.267 brouard 9539:
9540: hstepm=hstepm/stepm;
1.296 brouard 9541: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
9542: /* fractional in yp1 *\/ */
9543: /* aintmean=yp; */
9544: /* yp2=modf((yp1*12),&yp); */
9545: /* mintmean=yp; */
9546: /* yp1=modf((yp2*30.5),&yp); */
9547: /* jintmean=yp; */
9548: /* if(jintmean==0) jintmean=1; */
9549: /* if(mintmean==0) jintmean=1; */
1.267 brouard 9550:
9551: i1=pow(2,cptcoveff);
9552: if (cptcovn < 1){i1=1;}
9553:
1.296 brouard 9554: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
9555: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 9556:
9557: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
9558:
9559: for(nres=1; nres <= nresult; nres++) /* For each resultline */
9560: for(k=1; k<=i1;k++){
9561: if(i1 != 1 && TKresult[nres]!= k)
9562: continue;
9563: if(invalidvarcomb[k]){
9564: printf("\nCombination (%d) projection ignored because no cases \n",k);
9565: continue;
9566: }
1.268 brouard 9567: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.267 brouard 9568: for(j=1;j<=cptcoveff;j++) {
1.332 brouard 9569: fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.267 brouard 9570: }
9571: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
9572: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
9573: }
9574: fprintf(ficresfb," yearbproj age");
9575: for(j=1; j<=nlstate+ndeath;j++){
9576: for(i=1; i<=nlstate;i++)
1.268 brouard 9577: fprintf(ficresfb," b%d%d",i,j);
9578: fprintf(ficresfb," b.%d",j);
1.267 brouard 9579: }
1.296 brouard 9580: for (yearp=0; yearp>=(anbackf-anbackd);yearp -=stepsize) {
1.267 brouard 9581: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
9582: fprintf(ficresfb,"\n");
1.296 brouard 9583: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jbackd,mbackd,anbackd+yearp);
1.273 brouard 9584: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 9585: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
9586: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 9587: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 9588: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 9589: nhstepm = nhstepm/hstepm;
9590: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9591: oldm=oldms;savm=savms;
1.268 brouard 9592: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 9593: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 9594: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 9595: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
9596: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
9597: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 9598: for (h=0; h<=nhstepm; h++){
1.268 brouard 9599: if (h*hstepm/YEARM*stepm ==-yearp) {
9600: break;
9601: }
9602: }
9603: fprintf(ficresfb,"\n");
9604: for(j=1;j<=cptcoveff;j++)
1.332 brouard 9605: fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.296 brouard 9606: fprintf(ficresfb,"%.f %.f ",anbackd+yearp,agec-h*hstepm/YEARM*stepm);
1.268 brouard 9607: for(i=1; i<=nlstate+ndeath;i++) {
9608: ppij=0.;ppi=0.;
9609: for(j=1; j<=nlstate;j++) {
9610: /* if (mobilav==1) */
1.269 brouard 9611: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
9612: ppi=ppi+prevacurrent[(int)agec][j][k];
9613: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
9614: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 9615: /* else { */
9616: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
9617: /* } */
1.268 brouard 9618: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
9619: } /* end j */
9620: if(ppi <0.99){
9621: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
9622: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
9623: }
9624: fprintf(ficresfb," %.3f", ppij);
9625: }/* end j */
1.267 brouard 9626: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9627: } /* end agec */
9628: } /* end yearp */
9629: } /* end k */
1.217 brouard 9630:
1.267 brouard 9631: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 9632:
1.267 brouard 9633: fclose(ficresfb);
9634: printf("End of Computing Back forecasting \n");
9635: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 9636:
1.267 brouard 9637: }
1.217 brouard 9638:
1.269 brouard 9639: /* Variance of prevalence limit: varprlim */
9640: 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 9641: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 9642:
9643: char fileresvpl[FILENAMELENGTH];
9644: FILE *ficresvpl;
9645: double **oldm, **savm;
9646: double **varpl; /* Variances of prevalence limits by age */
9647: int i1, k, nres, j ;
9648:
9649: strcpy(fileresvpl,"VPL_");
9650: strcat(fileresvpl,fileresu);
9651: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 9652: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 9653: exit(0);
9654: }
1.288 brouard 9655: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
9656: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 9657:
9658: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
9659: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
9660:
9661: i1=pow(2,cptcoveff);
9662: if (cptcovn < 1){i1=1;}
9663:
1.337 brouard 9664: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
9665: k=TKresult[nres];
1.338 brouard 9666: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 9667: /* for(k=1; k<=i1;k++){ /\* We find the combination equivalent to result line values of dummies *\/ */
1.269 brouard 9668: if(i1 != 1 && TKresult[nres]!= k)
9669: continue;
9670: fprintf(ficresvpl,"\n#****** ");
9671: printf("\n#****** ");
9672: fprintf(ficlog,"\n#****** ");
1.337 brouard 9673: for(j=1;j<=cptcovs;j++) {
9674: fprintf(ficresvpl,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
9675: fprintf(ficlog,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
9676: printf("V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
9677: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
9678: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.269 brouard 9679: }
1.337 brouard 9680: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
9681: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
9682: /* fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
9683: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
9684: /* } */
1.269 brouard 9685: fprintf(ficresvpl,"******\n");
9686: printf("******\n");
9687: fprintf(ficlog,"******\n");
9688:
9689: varpl=matrix(1,nlstate,(int) bage, (int) fage);
9690: oldm=oldms;savm=savms;
9691: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
9692: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
9693: /*}*/
9694: }
9695:
9696: fclose(ficresvpl);
1.288 brouard 9697: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
9698: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 9699:
9700: }
9701: /* Variance of back prevalence: varbprlim */
9702: 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){
9703: /*------- Variance of back (stable) prevalence------*/
9704:
9705: char fileresvbl[FILENAMELENGTH];
9706: FILE *ficresvbl;
9707:
9708: double **oldm, **savm;
9709: double **varbpl; /* Variances of back prevalence limits by age */
9710: int i1, k, nres, j ;
9711:
9712: strcpy(fileresvbl,"VBL_");
9713: strcat(fileresvbl,fileresu);
9714: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
9715: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
9716: exit(0);
9717: }
9718: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
9719: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
9720:
9721:
9722: i1=pow(2,cptcoveff);
9723: if (cptcovn < 1){i1=1;}
9724:
1.337 brouard 9725: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
9726: k=TKresult[nres];
1.338 brouard 9727: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 9728: /* for(k=1; k<=i1;k++){ */
9729: /* if(i1 != 1 && TKresult[nres]!= k) */
9730: /* continue; */
1.269 brouard 9731: fprintf(ficresvbl,"\n#****** ");
9732: printf("\n#****** ");
9733: fprintf(ficlog,"\n#****** ");
1.337 brouard 9734: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */
1.338 brouard 9735: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
9736: fprintf(ficresvbl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
9737: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
1.337 brouard 9738: /* for(j=1;j<=cptcoveff;j++) { */
9739: /* fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
9740: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
9741: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
9742: /* } */
9743: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
9744: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
9745: /* fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
9746: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
1.269 brouard 9747: }
9748: fprintf(ficresvbl,"******\n");
9749: printf("******\n");
9750: fprintf(ficlog,"******\n");
9751:
9752: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
9753: oldm=oldms;savm=savms;
9754:
9755: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
9756: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
9757: /*}*/
9758: }
9759:
9760: fclose(ficresvbl);
9761: printf("done variance-covariance of back prevalence\n");fflush(stdout);
9762: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
9763:
9764: } /* End of varbprlim */
9765:
1.126 brouard 9766: /************** Forecasting *****not tested NB*************/
1.227 brouard 9767: /* 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 9768:
1.227 brouard 9769: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
9770: /* int *popage; */
9771: /* double calagedatem, agelim, kk1, kk2; */
9772: /* double *popeffectif,*popcount; */
9773: /* double ***p3mat,***tabpop,***tabpopprev; */
9774: /* /\* double ***mobaverage; *\/ */
9775: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 9776:
1.227 brouard 9777: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9778: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9779: /* agelim=AGESUP; */
9780: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 9781:
1.227 brouard 9782: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 9783:
9784:
1.227 brouard 9785: /* strcpy(filerespop,"POP_"); */
9786: /* strcat(filerespop,fileresu); */
9787: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
9788: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
9789: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
9790: /* } */
9791: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
9792: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 9793:
1.227 brouard 9794: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 9795:
1.227 brouard 9796: /* /\* if (mobilav!=0) { *\/ */
9797: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
9798: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
9799: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
9800: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
9801: /* /\* } *\/ */
9802: /* /\* } *\/ */
1.126 brouard 9803:
1.227 brouard 9804: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
9805: /* if (stepm<=12) stepsize=1; */
1.126 brouard 9806:
1.227 brouard 9807: /* agelim=AGESUP; */
1.126 brouard 9808:
1.227 brouard 9809: /* hstepm=1; */
9810: /* hstepm=hstepm/stepm; */
1.218 brouard 9811:
1.227 brouard 9812: /* if (popforecast==1) { */
9813: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
9814: /* printf("Problem with population file : %s\n",popfile);exit(0); */
9815: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
9816: /* } */
9817: /* popage=ivector(0,AGESUP); */
9818: /* popeffectif=vector(0,AGESUP); */
9819: /* popcount=vector(0,AGESUP); */
1.126 brouard 9820:
1.227 brouard 9821: /* i=1; */
9822: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 9823:
1.227 brouard 9824: /* imx=i; */
9825: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
9826: /* } */
1.218 brouard 9827:
1.227 brouard 9828: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
9829: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
9830: /* k=k+1; */
9831: /* fprintf(ficrespop,"\n#******"); */
9832: /* for(j=1;j<=cptcoveff;j++) { */
9833: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
9834: /* } */
9835: /* fprintf(ficrespop,"******\n"); */
9836: /* fprintf(ficrespop,"# Age"); */
9837: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
9838: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 9839:
1.227 brouard 9840: /* for (cpt=0; cpt<=0;cpt++) { */
9841: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 9842:
1.227 brouard 9843: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
9844: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
9845: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 9846:
1.227 brouard 9847: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9848: /* oldm=oldms;savm=savms; */
9849: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 9850:
1.227 brouard 9851: /* for (h=0; h<=nhstepm; h++){ */
9852: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
9853: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
9854: /* } */
9855: /* for(j=1; j<=nlstate+ndeath;j++) { */
9856: /* kk1=0.;kk2=0; */
9857: /* for(i=1; i<=nlstate;i++) { */
9858: /* if (mobilav==1) */
9859: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
9860: /* else { */
9861: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
9862: /* } */
9863: /* } */
9864: /* if (h==(int)(calagedatem+12*cpt)){ */
9865: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
9866: /* /\*fprintf(ficrespop," %.3f", kk1); */
9867: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
9868: /* } */
9869: /* } */
9870: /* for(i=1; i<=nlstate;i++){ */
9871: /* kk1=0.; */
9872: /* for(j=1; j<=nlstate;j++){ */
9873: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
9874: /* } */
9875: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
9876: /* } */
1.218 brouard 9877:
1.227 brouard 9878: /* if (h==(int)(calagedatem+12*cpt)) */
9879: /* for(j=1; j<=nlstate;j++) */
9880: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
9881: /* } */
9882: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9883: /* } */
9884: /* } */
1.218 brouard 9885:
1.227 brouard 9886: /* /\******\/ */
1.218 brouard 9887:
1.227 brouard 9888: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
9889: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
9890: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
9891: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
9892: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 9893:
1.227 brouard 9894: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9895: /* oldm=oldms;savm=savms; */
9896: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
9897: /* for (h=0; h<=nhstepm; h++){ */
9898: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
9899: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
9900: /* } */
9901: /* for(j=1; j<=nlstate+ndeath;j++) { */
9902: /* kk1=0.;kk2=0; */
9903: /* for(i=1; i<=nlstate;i++) { */
9904: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
9905: /* } */
9906: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
9907: /* } */
9908: /* } */
9909: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9910: /* } */
9911: /* } */
9912: /* } */
9913: /* } */
1.218 brouard 9914:
1.227 brouard 9915: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 9916:
1.227 brouard 9917: /* if (popforecast==1) { */
9918: /* free_ivector(popage,0,AGESUP); */
9919: /* free_vector(popeffectif,0,AGESUP); */
9920: /* free_vector(popcount,0,AGESUP); */
9921: /* } */
9922: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9923: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9924: /* fclose(ficrespop); */
9925: /* } /\* End of popforecast *\/ */
1.218 brouard 9926:
1.126 brouard 9927: int fileappend(FILE *fichier, char *optionfich)
9928: {
9929: if((fichier=fopen(optionfich,"a"))==NULL) {
9930: printf("Problem with file: %s\n", optionfich);
9931: fprintf(ficlog,"Problem with file: %s\n", optionfich);
9932: return (0);
9933: }
9934: fflush(fichier);
9935: return (1);
9936: }
9937:
9938:
9939: /**************** function prwizard **********************/
9940: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
9941: {
9942:
9943: /* Wizard to print covariance matrix template */
9944:
1.164 brouard 9945: char ca[32], cb[32];
9946: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 9947: int numlinepar;
9948:
9949: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
9950: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
9951: for(i=1; i <=nlstate; i++){
9952: jj=0;
9953: for(j=1; j <=nlstate+ndeath; j++){
9954: if(j==i) continue;
9955: jj++;
9956: /*ca[0]= k+'a'-1;ca[1]='\0';*/
9957: printf("%1d%1d",i,j);
9958: fprintf(ficparo,"%1d%1d",i,j);
9959: for(k=1; k<=ncovmodel;k++){
9960: /* printf(" %lf",param[i][j][k]); */
9961: /* fprintf(ficparo," %lf",param[i][j][k]); */
9962: printf(" 0.");
9963: fprintf(ficparo," 0.");
9964: }
9965: printf("\n");
9966: fprintf(ficparo,"\n");
9967: }
9968: }
9969: printf("# Scales (for hessian or gradient estimation)\n");
9970: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
9971: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
9972: for(i=1; i <=nlstate; i++){
9973: jj=0;
9974: for(j=1; j <=nlstate+ndeath; j++){
9975: if(j==i) continue;
9976: jj++;
9977: fprintf(ficparo,"%1d%1d",i,j);
9978: printf("%1d%1d",i,j);
9979: fflush(stdout);
9980: for(k=1; k<=ncovmodel;k++){
9981: /* printf(" %le",delti3[i][j][k]); */
9982: /* fprintf(ficparo," %le",delti3[i][j][k]); */
9983: printf(" 0.");
9984: fprintf(ficparo," 0.");
9985: }
9986: numlinepar++;
9987: printf("\n");
9988: fprintf(ficparo,"\n");
9989: }
9990: }
9991: printf("# Covariance matrix\n");
9992: /* # 121 Var(a12)\n\ */
9993: /* # 122 Cov(b12,a12) Var(b12)\n\ */
9994: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
9995: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
9996: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
9997: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
9998: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
9999: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
10000: fflush(stdout);
10001: fprintf(ficparo,"# Covariance matrix\n");
10002: /* # 121 Var(a12)\n\ */
10003: /* # 122 Cov(b12,a12) Var(b12)\n\ */
10004: /* # ...\n\ */
10005: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
10006:
10007: for(itimes=1;itimes<=2;itimes++){
10008: jj=0;
10009: for(i=1; i <=nlstate; i++){
10010: for(j=1; j <=nlstate+ndeath; j++){
10011: if(j==i) continue;
10012: for(k=1; k<=ncovmodel;k++){
10013: jj++;
10014: ca[0]= k+'a'-1;ca[1]='\0';
10015: if(itimes==1){
10016: printf("#%1d%1d%d",i,j,k);
10017: fprintf(ficparo,"#%1d%1d%d",i,j,k);
10018: }else{
10019: printf("%1d%1d%d",i,j,k);
10020: fprintf(ficparo,"%1d%1d%d",i,j,k);
10021: /* printf(" %.5le",matcov[i][j]); */
10022: }
10023: ll=0;
10024: for(li=1;li <=nlstate; li++){
10025: for(lj=1;lj <=nlstate+ndeath; lj++){
10026: if(lj==li) continue;
10027: for(lk=1;lk<=ncovmodel;lk++){
10028: ll++;
10029: if(ll<=jj){
10030: cb[0]= lk +'a'-1;cb[1]='\0';
10031: if(ll<jj){
10032: if(itimes==1){
10033: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10034: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10035: }else{
10036: printf(" 0.");
10037: fprintf(ficparo," 0.");
10038: }
10039: }else{
10040: if(itimes==1){
10041: printf(" Var(%s%1d%1d)",ca,i,j);
10042: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
10043: }else{
10044: printf(" 0.");
10045: fprintf(ficparo," 0.");
10046: }
10047: }
10048: }
10049: } /* end lk */
10050: } /* end lj */
10051: } /* end li */
10052: printf("\n");
10053: fprintf(ficparo,"\n");
10054: numlinepar++;
10055: } /* end k*/
10056: } /*end j */
10057: } /* end i */
10058: } /* end itimes */
10059:
10060: } /* end of prwizard */
10061: /******************* Gompertz Likelihood ******************************/
10062: double gompertz(double x[])
10063: {
1.302 brouard 10064: double A=0.0,B=0.,L=0.0,sump=0.,num=0.;
1.126 brouard 10065: int i,n=0; /* n is the size of the sample */
10066:
1.220 brouard 10067: for (i=1;i<=imx ; i++) {
1.126 brouard 10068: sump=sump+weight[i];
10069: /* sump=sump+1;*/
10070: num=num+1;
10071: }
1.302 brouard 10072: L=0.0;
10073: /* agegomp=AGEGOMP; */
1.126 brouard 10074: /* for (i=0; i<=imx; i++)
10075: 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]);*/
10076:
1.302 brouard 10077: for (i=1;i<=imx ; i++) {
10078: /* mu(a)=mu(agecomp)*exp(teta*(age-agegomp))
10079: mu(a)=x[1]*exp(x[2]*(age-agegomp)); x[1] and x[2] are per year.
10080: * L= Product mu(agedeces)exp(-\int_ageexam^agedc mu(u) du ) for a death between agedc (in month)
10081: * and agedc +1 month, cens[i]=0: log(x[1]/YEARM)
10082: * +
10083: * exp(-\int_ageexam^agecens mu(u) du ) when censored, cens[i]=1
10084: */
10085: if (wav[i] > 1 || agedc[i] < AGESUP) {
10086: if (cens[i] == 1){
10087: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
10088: } else if (cens[i] == 0){
1.126 brouard 10089: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
1.302 brouard 10090: +log(x[1]/YEARM) +x[2]*(agedc[i]-agegomp)+log(YEARM);
10091: } else
10092: printf("Gompertz cens[%d] neither 1 nor 0\n",i);
1.126 brouard 10093: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
1.302 brouard 10094: L=L+A*weight[i];
1.126 brouard 10095: /* 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 10096: }
10097: }
1.126 brouard 10098:
1.302 brouard 10099: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
1.126 brouard 10100:
10101: return -2*L*num/sump;
10102: }
10103:
1.136 brouard 10104: #ifdef GSL
10105: /******************* Gompertz_f Likelihood ******************************/
10106: double gompertz_f(const gsl_vector *v, void *params)
10107: {
1.302 brouard 10108: double A=0.,B=0.,LL=0.0,sump=0.,num=0.;
1.136 brouard 10109: double *x= (double *) v->data;
10110: int i,n=0; /* n is the size of the sample */
10111:
10112: for (i=0;i<=imx-1 ; i++) {
10113: sump=sump+weight[i];
10114: /* sump=sump+1;*/
10115: num=num+1;
10116: }
10117:
10118:
10119: /* for (i=0; i<=imx; i++)
10120: 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]);*/
10121: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
10122: for (i=1;i<=imx ; i++)
10123: {
10124: if (cens[i] == 1 && wav[i]>1)
10125: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
10126:
10127: if (cens[i] == 0 && wav[i]>1)
10128: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
10129: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
10130:
10131: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
10132: if (wav[i] > 1 ) { /* ??? */
10133: LL=LL+A*weight[i];
10134: /* 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]);*/
10135: }
10136: }
10137:
10138: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
10139: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
10140:
10141: return -2*LL*num/sump;
10142: }
10143: #endif
10144:
1.126 brouard 10145: /******************* Printing html file ***********/
1.201 brouard 10146: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 10147: int lastpass, int stepm, int weightopt, char model[],\
10148: int imx, double p[],double **matcov,double agemortsup){
10149: int i,k;
10150:
10151: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
10152: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
10153: for (i=1;i<=2;i++)
10154: 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 10155: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 10156: fprintf(fichtm,"</ul>");
10157:
10158: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
10159:
10160: 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>");
10161:
10162: for (k=agegomp;k<(agemortsup-2);k++)
10163: 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]);
10164:
10165:
10166: fflush(fichtm);
10167: }
10168:
10169: /******************* Gnuplot file **************/
1.201 brouard 10170: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 10171:
10172: char dirfileres[132],optfileres[132];
1.164 brouard 10173:
1.126 brouard 10174: int ng;
10175:
10176:
10177: /*#ifdef windows */
10178: fprintf(ficgp,"cd \"%s\" \n",pathc);
10179: /*#endif */
10180:
10181:
10182: strcpy(dirfileres,optionfilefiname);
10183: strcpy(optfileres,"vpl");
1.199 brouard 10184: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 10185: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 10186: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 10187: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 10188: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
10189:
10190: }
10191:
1.136 brouard 10192: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
10193: {
1.126 brouard 10194:
1.136 brouard 10195: /*-------- data file ----------*/
10196: FILE *fic;
10197: char dummy[]=" ";
1.240 brouard 10198: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 10199: int lstra;
1.136 brouard 10200: int linei, month, year,iout;
1.302 brouard 10201: int noffset=0; /* This is the offset if BOM data file */
1.136 brouard 10202: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 10203: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 10204: char *stratrunc;
1.223 brouard 10205:
1.240 brouard 10206: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
10207: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.328 brouard 10208: for(v=1;v<NCOVMAX;v++){
10209: DummyV[v]=0;
10210: FixedV[v]=0;
10211: }
1.126 brouard 10212:
1.240 brouard 10213: for(v=1; v <=ncovcol;v++){
10214: DummyV[v]=0;
10215: FixedV[v]=0;
10216: }
10217: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
10218: DummyV[v]=1;
10219: FixedV[v]=0;
10220: }
10221: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
10222: DummyV[v]=0;
10223: FixedV[v]=1;
10224: }
10225: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
10226: DummyV[v]=1;
10227: FixedV[v]=1;
10228: }
10229: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
10230: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
10231: 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]);
10232: }
1.339 ! brouard 10233:
! 10234: ncovcolt=ncovcol+nqv+ntv+nqtv; /* total of covariates in the data, not in the model equation */
! 10235:
1.136 brouard 10236: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 10237: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
10238: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 10239: }
1.126 brouard 10240:
1.302 brouard 10241: /* Is it a BOM UTF-8 Windows file? */
10242: /* First data line */
10243: linei=0;
10244: while(fgets(line, MAXLINE, fic)) {
10245: noffset=0;
10246: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
10247: {
10248: noffset=noffset+3;
10249: printf("# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);fflush(stdout);
10250: fprintf(ficlog,"# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);
10251: fflush(ficlog); return 1;
10252: }
10253: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
10254: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
10255: {
10256: noffset=noffset+2;
1.304 brouard 10257: 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);
10258: 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 10259: fflush(ficlog); return 1;
10260: }
10261: else if( line[0] == 0 && line[1] == 0)
10262: {
10263: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
10264: noffset=noffset+4;
1.304 brouard 10265: 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);
10266: 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 10267: fflush(ficlog); return 1;
10268: }
10269: } else{
10270: ;/*printf(" Not a BOM file\n");*/
10271: }
10272: /* If line starts with a # it is a comment */
10273: if (line[noffset] == '#') {
10274: linei=linei+1;
10275: break;
10276: }else{
10277: break;
10278: }
10279: }
10280: fclose(fic);
10281: if((fic=fopen(datafile,"r"))==NULL) {
10282: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
10283: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
10284: }
10285: /* Not a Bom file */
10286:
1.136 brouard 10287: i=1;
10288: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
10289: linei=linei+1;
10290: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
10291: if(line[j] == '\t')
10292: line[j] = ' ';
10293: }
10294: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
10295: ;
10296: };
10297: line[j+1]=0; /* Trims blanks at end of line */
10298: if(line[0]=='#'){
10299: fprintf(ficlog,"Comment line\n%s\n",line);
10300: printf("Comment line\n%s\n",line);
10301: continue;
10302: }
10303: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 10304: strcpy(line, linetmp);
1.223 brouard 10305:
10306: /* Loops on waves */
10307: for (j=maxwav;j>=1;j--){
10308: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 10309: cutv(stra, strb, line, ' ');
10310: if(strb[0]=='.') { /* Missing value */
10311: lval=-1;
10312: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
10313: cotvar[j][ntv+iv][i]=-1; /* For performance reasons */
10314: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
10315: 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);
10316: 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);
10317: return 1;
10318: }
10319: }else{
10320: errno=0;
10321: /* what_kind_of_number(strb); */
10322: dval=strtod(strb,&endptr);
10323: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
10324: /* if(strb != endptr && *endptr == '\0') */
10325: /* dval=dlval; */
10326: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
10327: if( strb[0]=='\0' || (*endptr != '\0')){
10328: 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);
10329: 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);
10330: return 1;
10331: }
10332: cotqvar[j][iv][i]=dval;
10333: cotvar[j][ntv+iv][i]=dval;
10334: }
10335: strcpy(line,stra);
1.223 brouard 10336: }/* end loop ntqv */
1.225 brouard 10337:
1.223 brouard 10338: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 10339: cutv(stra, strb, line, ' ');
10340: if(strb[0]=='.') { /* Missing value */
10341: lval=-1;
10342: }else{
10343: errno=0;
10344: lval=strtol(strb,&endptr,10);
10345: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
10346: if( strb[0]=='\0' || (*endptr != '\0')){
10347: 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);
10348: 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);
10349: return 1;
10350: }
10351: }
10352: if(lval <-1 || lval >1){
10353: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10354: 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 10355: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10356: For example, for multinomial values like 1, 2 and 3,\n \
10357: build V1=0 V2=0 for the reference value (1),\n \
10358: V1=1 V2=0 for (2) \n \
1.223 brouard 10359: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10360: output of IMaCh is often meaningless.\n \
1.319 brouard 10361: Exiting.\n",lval,linei, i,line,iv,j);
1.238 brouard 10362: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10363: 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 10364: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10365: For example, for multinomial values like 1, 2 and 3,\n \
10366: build V1=0 V2=0 for the reference value (1),\n \
10367: V1=1 V2=0 for (2) \n \
1.223 brouard 10368: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10369: output of IMaCh is often meaningless.\n \
1.319 brouard 10370: Exiting.\n",lval,linei, i,line,iv,j);fflush(ficlog);
1.238 brouard 10371: return 1;
10372: }
10373: cotvar[j][iv][i]=(double)(lval);
10374: strcpy(line,stra);
1.223 brouard 10375: }/* end loop ntv */
1.225 brouard 10376:
1.223 brouard 10377: /* Statuses at wave */
1.137 brouard 10378: cutv(stra, strb, line, ' ');
1.223 brouard 10379: if(strb[0]=='.') { /* Missing value */
1.238 brouard 10380: lval=-1;
1.136 brouard 10381: }else{
1.238 brouard 10382: errno=0;
10383: lval=strtol(strb,&endptr,10);
10384: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
10385: if( strb[0]=='\0' || (*endptr != '\0')){
10386: 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);
10387: 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);
10388: return 1;
10389: }
1.136 brouard 10390: }
1.225 brouard 10391:
1.136 brouard 10392: s[j][i]=lval;
1.225 brouard 10393:
1.223 brouard 10394: /* Date of Interview */
1.136 brouard 10395: strcpy(line,stra);
10396: cutv(stra, strb,line,' ');
1.169 brouard 10397: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10398: }
1.169 brouard 10399: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 10400: month=99;
10401: year=9999;
1.136 brouard 10402: }else{
1.225 brouard 10403: 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);
10404: 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);
10405: return 1;
1.136 brouard 10406: }
10407: anint[j][i]= (double) year;
1.302 brouard 10408: mint[j][i]= (double)month;
10409: /* if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){ */
10410: /* 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]); */
10411: /* 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]); */
10412: /* } */
1.136 brouard 10413: strcpy(line,stra);
1.223 brouard 10414: } /* End loop on waves */
1.225 brouard 10415:
1.223 brouard 10416: /* Date of death */
1.136 brouard 10417: cutv(stra, strb,line,' ');
1.169 brouard 10418: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10419: }
1.169 brouard 10420: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 10421: month=99;
10422: year=9999;
10423: }else{
1.141 brouard 10424: 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 10425: 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);
10426: return 1;
1.136 brouard 10427: }
10428: andc[i]=(double) year;
10429: moisdc[i]=(double) month;
10430: strcpy(line,stra);
10431:
1.223 brouard 10432: /* Date of birth */
1.136 brouard 10433: cutv(stra, strb,line,' ');
1.169 brouard 10434: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10435: }
1.169 brouard 10436: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 10437: month=99;
10438: year=9999;
10439: }else{
1.141 brouard 10440: 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);
10441: 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 10442: return 1;
1.136 brouard 10443: }
10444: if (year==9999) {
1.141 brouard 10445: 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);
10446: 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 10447: return 1;
10448:
1.136 brouard 10449: }
10450: annais[i]=(double)(year);
1.302 brouard 10451: moisnais[i]=(double)(month);
10452: for (j=1;j<=maxwav;j++){
10453: if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){
10454: 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]);
10455: 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]);
10456: }
10457: }
10458:
1.136 brouard 10459: strcpy(line,stra);
1.225 brouard 10460:
1.223 brouard 10461: /* Sample weight */
1.136 brouard 10462: cutv(stra, strb,line,' ');
10463: errno=0;
10464: dval=strtod(strb,&endptr);
10465: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 10466: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
10467: 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 10468: fflush(ficlog);
10469: return 1;
10470: }
10471: weight[i]=dval;
10472: strcpy(line,stra);
1.225 brouard 10473:
1.223 brouard 10474: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
10475: cutv(stra, strb, line, ' ');
10476: if(strb[0]=='.') { /* Missing value */
1.225 brouard 10477: lval=-1;
1.311 brouard 10478: coqvar[iv][i]=NAN;
10479: covar[ncovcol+iv][i]=NAN; /* including qvar in standard covar for performance reasons */
1.223 brouard 10480: }else{
1.225 brouard 10481: errno=0;
10482: /* what_kind_of_number(strb); */
10483: dval=strtod(strb,&endptr);
10484: /* if(strb != endptr && *endptr == '\0') */
10485: /* dval=dlval; */
10486: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
10487: if( strb[0]=='\0' || (*endptr != '\0')){
10488: 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);
10489: 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);
10490: return 1;
10491: }
10492: coqvar[iv][i]=dval;
1.226 brouard 10493: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 10494: }
10495: strcpy(line,stra);
10496: }/* end loop nqv */
1.136 brouard 10497:
1.223 brouard 10498: /* Covariate values */
1.136 brouard 10499: for (j=ncovcol;j>=1;j--){
10500: cutv(stra, strb,line,' ');
1.223 brouard 10501: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 10502: lval=-1;
1.136 brouard 10503: }else{
1.225 brouard 10504: errno=0;
10505: lval=strtol(strb,&endptr,10);
10506: if( strb[0]=='\0' || (*endptr != '\0')){
10507: 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);
10508: 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);
10509: return 1;
10510: }
1.136 brouard 10511: }
10512: if(lval <-1 || lval >1){
1.225 brouard 10513: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 10514: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
10515: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 10516: For example, for multinomial values like 1, 2 and 3,\n \
10517: build V1=0 V2=0 for the reference value (1),\n \
10518: V1=1 V2=0 for (2) \n \
1.136 brouard 10519: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 10520: output of IMaCh is often meaningless.\n \
1.136 brouard 10521: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 10522: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 10523: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
10524: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 10525: For example, for multinomial values like 1, 2 and 3,\n \
10526: build V1=0 V2=0 for the reference value (1),\n \
10527: V1=1 V2=0 for (2) \n \
1.136 brouard 10528: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 10529: output of IMaCh is often meaningless.\n \
1.136 brouard 10530: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 10531: return 1;
1.136 brouard 10532: }
10533: covar[j][i]=(double)(lval);
10534: strcpy(line,stra);
10535: }
10536: lstra=strlen(stra);
1.225 brouard 10537:
1.136 brouard 10538: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
10539: stratrunc = &(stra[lstra-9]);
10540: num[i]=atol(stratrunc);
10541: }
10542: else
10543: num[i]=atol(stra);
10544: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
10545: 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;}*/
10546:
10547: i=i+1;
10548: } /* End loop reading data */
1.225 brouard 10549:
1.136 brouard 10550: *imax=i-1; /* Number of individuals */
10551: fclose(fic);
1.225 brouard 10552:
1.136 brouard 10553: return (0);
1.164 brouard 10554: /* endread: */
1.225 brouard 10555: printf("Exiting readdata: ");
10556: fclose(fic);
10557: return (1);
1.223 brouard 10558: }
1.126 brouard 10559:
1.234 brouard 10560: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 10561: char *p1 = *stri, *p2 = *stri;
1.235 brouard 10562: while (*p2 == ' ')
1.234 brouard 10563: p2++;
10564: /* while ((*p1++ = *p2++) !=0) */
10565: /* ; */
10566: /* do */
10567: /* while (*p2 == ' ') */
10568: /* p2++; */
10569: /* while (*p1++ == *p2++); */
10570: *stri=p2;
1.145 brouard 10571: }
10572:
1.330 brouard 10573: int decoderesult( char resultline[], int nres)
1.230 brouard 10574: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
10575: {
1.235 brouard 10576: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 10577: char resultsav[MAXLINE];
1.330 brouard 10578: /* int resultmodel[MAXLINE]; */
1.334 brouard 10579: /* int modelresult[MAXLINE]; */
1.230 brouard 10580: char stra[80], strb[80], strc[80], strd[80],stre[80];
10581:
1.234 brouard 10582: removefirstspace(&resultline);
1.332 brouard 10583: printf("decoderesult:%s\n",resultline);
1.230 brouard 10584:
1.332 brouard 10585: strcpy(resultsav,resultline);
10586: printf("Decoderesult resultsav=\"%s\" resultline=\"%s\"\n", resultsav, resultline);
1.230 brouard 10587: if (strlen(resultsav) >1){
1.334 brouard 10588: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' in this resultline */
1.230 brouard 10589: }
1.253 brouard 10590: if(j == 0){ /* Resultline but no = */
10591: TKresult[nres]=0; /* Combination for the nresult and the model */
10592: return (0);
10593: }
1.234 brouard 10594: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
1.334 brouard 10595: 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);
10596: 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 10597: /* return 1;*/
1.234 brouard 10598: }
1.334 brouard 10599: for(k=1; k<=j;k++){ /* Loop on any covariate of the RESULT LINE */
1.234 brouard 10600: if(nbocc(resultsav,'=') >1){
1.318 brouard 10601: 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 10602: /* 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 10603: cutl(strc,strd,strb,'='); /* strb:"V4=1" strc="1" strd="V4" */
1.332 brouard 10604: /* If a blank, then strc="V4=" and strd='\0' */
10605: if(strc[0]=='\0'){
10606: printf("Error in resultline, probably a blank after the \"%s\", \"result:%s\", stra=\"%s\" resultsav=\"%s\"\n",strb,resultline, stra, resultsav);
10607: fprintf(ficlog,"Error in resultline, probably a blank after the \"V%s=\", resultline=%s\n",strb,resultline);
10608: return 1;
10609: }
1.234 brouard 10610: }else
10611: cutl(strc,strd,resultsav,'=');
1.318 brouard 10612: Tvalsel[k]=atof(strc); /* 1 */ /* Tvalsel of k is the float value of the kth covariate appearing in this result line */
1.234 brouard 10613:
1.230 brouard 10614: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
1.318 brouard 10615: 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 10616: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
10617: /* cptcovsel++; */
10618: if (nbocc(stra,'=') >0)
10619: strcpy(resultsav,stra); /* and analyzes it */
10620: }
1.235 brouard 10621: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 10622: /* 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 10623: 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 10624: if(Typevar[k1]==0){ /* Single covariate in model */
10625: /* 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.234 brouard 10626: match=0;
1.318 brouard 10627: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
10628: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 10629: modelresult[nres][k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.318 brouard 10630: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
1.234 brouard 10631: break;
10632: }
10633: }
10634: if(match == 0){
1.338 brouard 10635: printf("Error in result line (Dummy single): V%d is missing in result: %s according to model=1+age+%s. Tvar[k1=%d]=%d is different from Tvarsel[k2=%d]=%d.\n",Tvar[k1], resultline, model,k1, Tvar[k1], k2, Tvarsel[k2]);
10636: fprintf(ficlog,"Error in result line (Dummy single): V%d is missing in result: %s according to model=1+age+%s\n",Tvar[k1], resultline, model);
1.310 brouard 10637: return 1;
1.234 brouard 10638: }
1.332 brouard 10639: }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*/
10640: /* We feed resultmodel[k1]=k2; */
10641: match=0;
10642: 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 */
10643: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 10644: 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 10645: resultmodel[nres][k1]=k2; /* Added here */
10646: printf("Decoderesult first modelresult[k2=%d]=%d (k1) V%d*AGE\n",k2,k1,Tvar[k1]);
10647: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
10648: break;
10649: }
10650: }
10651: if(match == 0){
1.338 brouard 10652: printf("Error in result line (Product with age): V%d is missing in result: %s according to model=1+age+%s (Tvarsel[k2=%d]=%d)\n",Tvar[k1], resultline, model, k2, Tvarsel[k2]);
10653: fprintf(ficlog,"Error in result line (Product with age): V%d is missing in result: %s according to model=1+age+%s (Tvarsel[k2=%d]=%d)\n",Tvar[k1], resultline, model, k2, Tvarsel[k2]);
1.332 brouard 10654: return 1;
10655: }
10656: }else if(Typevar[k1]==2){ /* Product No age We want to get the position in the resultline of the product in the model line*/
10657: /* resultmodel[nres][of such a Vn * Vm product k1] is not unique, so can't exist, we feed Tvard[k1][1] and [2] */
10658: match=0;
10659: 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]);
10660: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
10661: if(Tvardk[k1][1]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
10662: /* modelresult[k2]=k1; */
10663: printf("Decoderesult first Product modelresult[k2=%d]=%d (k1) V%d * \n",k2,k1,Tvarsel[k2]);
10664: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
10665: }
10666: }
10667: if(match == 0){
1.338 brouard 10668: printf("Error in result line (Product without age first variable): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][1], resultline, model);
10669: fprintf(ficlog,"Error in result line (Product without age first variable): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][1], resultline, model);
1.332 brouard 10670: return 1;
10671: }
10672: match=0;
10673: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
10674: if(Tvardk[k1][2]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
10675: /* modelresult[k2]=k1;*/
10676: printf("Decoderesult second Product modelresult[k2=%d]=%d (k1) * V%d \n ",k2,k1,Tvarsel[k2]);
10677: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
10678: break;
10679: }
10680: }
10681: if(match == 0){
1.338 brouard 10682: printf("Error in result line (Product without age second variable): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][2], resultline, model);
10683: fprintf(ficlog,"Error in result line (Product without age second variable): V%d is missing in result : %s according to model=1+age+%s\n",Tvardk[k1][2], resultline, model);
1.332 brouard 10684: return 1;
10685: }
10686: }/* End of testing */
1.333 brouard 10687: }/* End loop cptcovt */
1.235 brouard 10688: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 10689: /* Feeds resultmodel[nres][k1]=k2 for single covariate (k1) in the model equation */
1.334 brouard 10690: 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)
10691: * Loop on resultline variables: result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 10692: match=0;
1.318 brouard 10693: 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 10694: if(Typevar[k1]==0){ /* Single only */
1.237 brouard 10695: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.330 brouard 10696: 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 10697: 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 10698: ++match;
10699: }
10700: }
10701: }
10702: if(match == 0){
1.338 brouard 10703: printf("Error in result line: variable V%d is missing in model; result: %s, model=1+age+%s\n",Tvarsel[k2], resultline, model);
10704: fprintf(ficlog,"Error in result line: variable V%d is missing in model; result: %s, model=1+age+%s\n",Tvarsel[k2], resultline, model);
1.310 brouard 10705: return 1;
1.234 brouard 10706: }else if(match > 1){
1.338 brouard 10707: printf("Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
10708: fprintf(ficlog,"Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
1.310 brouard 10709: return 1;
1.234 brouard 10710: }
10711: }
1.334 brouard 10712: /* cptcovres=j /\* Number of variables in the resultline is equal to cptcovs and thus useless *\/ */
1.234 brouard 10713: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 10714: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.330 brouard 10715: /* nres=1st result line: V4=1 V5=25.1 V3=0 V2=8 V1=1 */
10716: /* 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*/
10717: /* nres=2nd result line: V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.235 brouard 10718: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
10719: /* 1 0 0 0 */
10720: /* 2 1 0 0 */
10721: /* 3 0 1 0 */
1.330 brouard 10722: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 (nres=2)*/
1.235 brouard 10723: /* 5 0 0 1 */
1.330 brouard 10724: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 (nres=1)*/
1.235 brouard 10725: /* 7 0 1 1 */
10726: /* 8 1 1 1 */
1.237 brouard 10727: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
10728: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
10729: /* V5*age V5 known which value for nres? */
10730: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.334 brouard 10731: 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.
10732: * loop on position k1 in the MODEL LINE */
1.331 brouard 10733: /* k counting number of combination of single dummies in the equation model */
10734: /* k4 counting single dummies in the equation model */
10735: /* k4q counting single quantitatives in the equation model */
1.334 brouard 10736: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Dummy and Single, k1 is sorting according to MODEL, but k3 to resultline */
10737: /* 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 10738: /* 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 10739: /* Value in the (current nres) resultline of the variable at the k1th position in the model equation resultmodel[nres][k1]= k3 */
1.332 brouard 10740: /* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline */
10741: /* k3 is the position in the nres result line of the k1th variable of the model equation */
10742: /* Tvarsel[k3]: Name of the variable at the k3th position in the result line. */
10743: /* Tvalsel[k3]: Value of the variable at the k3th position in the result line. */
10744: /* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.334 brouard 10745: /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 10746: /* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1.330 brouard 10747: /* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.332 brouard 10748: k3= resultmodel[nres][k1]; /* From position k1 in model get position k3 in result line */
10749: /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
10750: 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 10751: 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 10752: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][Name]=Value; stores the value into the name of the variable. */
1.332 brouard 10753: /* Tinvresult[nres][4]=1 */
1.334 brouard 10754: /* Tresult[nres][k4+1]=Tvalsel[k3];/\* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) *\/ */
10755: Tresult[nres][k3]=Tvalsel[k3];/* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) */
10756: /* Tvresult[nres][k4+1]=(int)Tvarsel[k3];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
10757: Tvresult[nres][k3]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
1.237 brouard 10758: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.334 brouard 10759: precov[nres][k1]=Tvalsel[k3]; /* Value from resultline of the variable at the k1 position in the model */
1.332 brouard 10760: 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 10761: k4++;;
1.331 brouard 10762: }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Quantitative and single */
1.330 brouard 10763: /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.332 brouard 10764: /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.330 brouard 10765: /* Tqinvresult[nres][Name of a quantitative variable]= value of the variable in the result line */
1.332 brouard 10766: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 5 =k3q */
10767: k2q=(int)Tvarsel[k3q]; /* Name of variable at k3q th position in the resultline */
10768: /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.334 brouard 10769: /* Tqresult[nres][k4q+1]=Tvalsel[k3q]; /\* Tqresult[nres][1]=25.1 *\/ */
10770: /* Tvresult[nres][k4q+1]=(int)Tvarsel[k3q];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
10771: /* Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /\* Tvqresult[nres][1]=5 *\/ */
10772: Tqresult[nres][k3q]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
10773: Tvresult[nres][k3q]=(int)Tvarsel[k3q];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
10774: Tvqresult[nres][k3q]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
1.237 brouard 10775: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.330 brouard 10776: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.332 brouard 10777: precov[nres][k1]=Tvalsel[k3q];
10778: 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 10779: k4q++;;
1.331 brouard 10780: }else if( Dummy[k1]==2 ){ /* For dummy with age product */
10781: /* Tvar[k1]; */ /* Age variable */
1.332 brouard 10782: /* Wrong we want the value of variable name Tvar[k1] */
10783:
10784: k3= resultmodel[nres][k1]; /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
1.331 brouard 10785: 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 10786: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][4]=1 */
1.332 brouard 10787: precov[nres][k1]=Tvalsel[k3];
10788: 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 10789: }else if( Dummy[k1]==3 ){ /* For quant with age product */
1.332 brouard 10790: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 25.1=k3q */
1.331 brouard 10791: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.334 brouard 10792: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* TinvDoQresult[nres][5]=25.1 */
1.332 brouard 10793: precov[nres][k1]=Tvalsel[k3q];
1.334 brouard 10794: 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 10795: }else if(Typevar[k1]==2 ){ /* For product quant or dummy (not with age) */
1.332 brouard 10796: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
10797: 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 10798: }else{
1.332 brouard 10799: printf("Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
10800: fprintf(ficlog,"Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
1.235 brouard 10801: }
10802: }
1.234 brouard 10803:
1.334 brouard 10804: TKresult[nres]=++k; /* Number of combinations of dummies for the nresult and the model =Tvalsel[k3]*pow(2,k4) + 1*/
1.230 brouard 10805: return (0);
10806: }
1.235 brouard 10807:
1.230 brouard 10808: int decodemodel( char model[], int lastobs)
10809: /**< This routine decodes the model and returns:
1.224 brouard 10810: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
10811: * - nagesqr = 1 if age*age in the model, otherwise 0.
10812: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
10813: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
10814: * - cptcovage number of covariates with age*products =2
10815: * - cptcovs number of simple covariates
1.339 ! brouard 10816: * ncovcolt=ncovcol+nqv+ntv+nqtv total of covariates in the data, not in the model equation
1.224 brouard 10817: * - Tvar[k] is the id of the kth covariate Tvar[1]@12 {1, 2, 3, 8, 10, 11, 8, 3, 7, 8, 5, 6}, thus Tvar[5=V7*V8]=10
1.339 ! brouard 10818: * which is a new column after the 9 (ncovcol+nqv+ntv+nqtv) variables.
1.319 brouard 10819: * - if k is a product Vn*Vm, covar[k][i] is filled with correct values for each individual
1.224 brouard 10820: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
10821: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
10822: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
10823: */
1.319 brouard 10824: /* 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 10825: {
1.238 brouard 10826: int i, j, k, ks, v;
1.227 brouard 10827: int j1, k1, k2, k3, k4;
1.136 brouard 10828: char modelsav[80];
1.145 brouard 10829: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 10830: char *strpt;
1.136 brouard 10831:
1.145 brouard 10832: /*removespace(model);*/
1.136 brouard 10833: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 10834: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 10835: if (strstr(model,"AGE") !=0){
1.192 brouard 10836: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
10837: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 10838: return 1;
10839: }
1.141 brouard 10840: if (strstr(model,"v") !=0){
1.338 brouard 10841: printf("Error. 'v' must be in upper case 'V' model=1+age+%s ",model);
10842: fprintf(ficlog,"Error. 'v' must be in upper case model=1+age+%s ",model);fflush(ficlog);
1.141 brouard 10843: return 1;
10844: }
1.187 brouard 10845: strcpy(modelsav,model);
10846: if ((strpt=strstr(model,"age*age")) !=0){
1.338 brouard 10847: printf(" strpt=%s, model=1+age+%s\n",strpt, model);
1.187 brouard 10848: if(strpt != model){
1.338 brouard 10849: printf("Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 10850: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 10851: corresponding column of parameters.\n",model);
1.338 brouard 10852: fprintf(ficlog,"Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 10853: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 10854: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 10855: return 1;
1.225 brouard 10856: }
1.187 brouard 10857: nagesqr=1;
10858: if (strstr(model,"+age*age") !=0)
1.234 brouard 10859: substrchaine(modelsav, model, "+age*age");
1.187 brouard 10860: else if (strstr(model,"age*age+") !=0)
1.234 brouard 10861: substrchaine(modelsav, model, "age*age+");
1.187 brouard 10862: else
1.234 brouard 10863: substrchaine(modelsav, model, "age*age");
1.187 brouard 10864: }else
10865: nagesqr=0;
10866: if (strlen(modelsav) >1){
10867: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
10868: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 10869: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 10870: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 10871: * cst, age and age*age
10872: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
10873: /* including age products which are counted in cptcovage.
10874: * but the covariates which are products must be treated
10875: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 10876: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
10877: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 10878:
10879:
1.187 brouard 10880: /* Design
10881: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
10882: * < ncovcol=8 >
10883: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
10884: * k= 1 2 3 4 5 6 7 8
10885: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
10886: * covar[k,i], value of kth covariate if not including age for individual i:
1.224 brouard 10887: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
10888: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 10889: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
10890: * Tage[++cptcovage]=k
10891: * if products, new covar are created after ncovcol with k1
10892: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
10893: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
10894: * 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
10895: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
10896: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
10897: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
10898: * < ncovcol=8 >
10899: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
10900: * k= 1 2 3 4 5 6 7 8 9 10 11 12
10901: * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8
1.319 brouard 10902: * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
1.187 brouard 10903: * p Tprod[1]@2={ 6, 5}
10904: *p Tvard[1][1]@4= {7, 8, 5, 6}
10905: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
10906: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
1.319 brouard 10907: *How to reorganize? Tvars(orted)
1.187 brouard 10908: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
10909: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
10910: * {2, 1, 4, 8, 5, 6, 3, 7}
10911: * Struct []
10912: */
1.225 brouard 10913:
1.187 brouard 10914: /* This loop fills the array Tvar from the string 'model'.*/
10915: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
10916: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
10917: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
10918: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
10919: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
10920: /* k=1 Tvar[1]=2 (from V2) */
10921: /* k=5 Tvar[5] */
10922: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 10923: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 10924: /* } */
1.198 brouard 10925: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 10926: /*
10927: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 10928: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
10929: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
10930: }
1.187 brouard 10931: cptcovage=0;
1.319 brouard 10932: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model line */
10933: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+' cutl from left to right
10934: 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" */
10935: if (nbocc(modelsav,'+')==0)
10936: strcpy(strb,modelsav); /* and analyzes it */
1.234 brouard 10937: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
10938: /*scanf("%d",i);*/
1.319 brouard 10939: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V5*age+ V4+V3*age strb=V3*age */
10940: 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 10941: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
10942: /* covar is not filled and then is empty */
10943: cptcovprod--;
10944: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
1.319 brouard 10945: 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 10946: Typevar[k]=1; /* 1 for age product */
1.319 brouard 10947: cptcovage++; /* Counts the number of covariates which include age as a product */
10948: 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 10949: /*printf("stre=%s ", stre);*/
10950: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
10951: cptcovprod--;
10952: cutl(stre,strb,strc,'V');
10953: Tvar[k]=atoi(stre);
10954: Typevar[k]=1; /* 1 for age product */
10955: cptcovage++;
10956: Tage[cptcovage]=k;
10957: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
10958: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
10959: cptcovn++;
10960: cptcovprodnoage++;k1++;
10961: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
1.339 ! brouard 10962: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* ncovcolt+k1; For model-covariate k tells which data-covariate to use but
1.234 brouard 10963: because this model-covariate is a construction we invent a new column
10964: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
1.335 brouard 10965: If already ncovcol=4 and model= V2 + V1 + V1*V4 + age*V3 + V3*V2
1.319 brouard 10966: thus after V4 we invent V5 and V6 because age*V3 will be computed in 4
1.339 ! brouard 10967: Tvar[3=V1*V4]=4+1=5 Tvar[5=V3*V2]=4 + 2= 6, Tvar[4=age*V3]=3 etc */
1.335 brouard 10968: /* Please remark that the new variables are model dependent */
10969: /* If we have 4 variable but the model uses only 3, like in
10970: * model= V1 + age*V1 + V2 + V3 + age*V2 + age*V3 + V1*V2 + V1*V3
10971: * k= 1 2 3 4 5 6 7 8
10972: * Tvar[k]=1 1 2 3 2 3 (5 6) (and not 4 5 because of V4 missing)
10973: * Tage[kk] [1]= 2 [2]=5 [3]=6 kk=1 to cptcovage=3
10974: * Tvar[Tage[kk]][1]=2 [2]=2 [3]=3
10975: */
1.339 ! brouard 10976: Typevar[k]=2; /* 2 for product */
1.234 brouard 10977: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
10978: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
1.319 brouard 10979: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 */
1.234 brouard 10980: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
1.330 brouard 10981: Tvardk[k][1] =atoi(strc); /* m 1 for V1*/
1.234 brouard 10982: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
1.330 brouard 10983: Tvardk[k][2] =atoi(stre); /* n 4 for V4*/
1.234 brouard 10984: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
10985: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
10986: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 10987: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 10988: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
1.339 ! brouard 10989: if( FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){ /* If the product is a fixed covariate then we feed the new column with Vn*Vm */
! 10990: for (i=1; i<=lastobs;i++){/* For fixed product */
1.234 brouard 10991: /* Computes the new covariate which is a product of
10992: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
1.339 ! brouard 10993: covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
! 10994: }
! 10995: } /*End of FixedV */
1.234 brouard 10996: } /* End age is not in the model */
10997: } /* End if model includes a product */
1.319 brouard 10998: else { /* not a product */
1.234 brouard 10999: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
11000: /* scanf("%d",i);*/
11001: cutl(strd,strc,strb,'V');
11002: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
11003: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
11004: Tvar[k]=atoi(strd);
11005: Typevar[k]=0; /* 0 for simple covariates */
11006: }
11007: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 11008: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 11009: scanf("%d",i);*/
1.187 brouard 11010: } /* end of loop + on total covariates */
11011: } /* end if strlen(modelsave == 0) age*age might exist */
11012: } /* end if strlen(model == 0) */
1.136 brouard 11013:
11014: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
11015: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 11016:
1.136 brouard 11017: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 11018: printf("cptcovprod=%d ", cptcovprod);
11019: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
11020: scanf("%d ",i);*/
11021:
11022:
1.230 brouard 11023: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
11024: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 11025: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
11026: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
11027: k = 1 2 3 4 5 6 7 8 9
11028: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
1.319 brouard 11029: Typevar[k]= 0 0 0 2 1 0 2 1 0
1.227 brouard 11030: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
11031: Dummy[k] 1 0 0 0 3 1 1 2 3
11032: Tmodelind[combination of covar]=k;
1.225 brouard 11033: */
11034: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 11035: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 11036: /* 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 11037: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.318 brouard 11038: printf("Model=1+age+%s\n\
1.227 brouard 11039: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
11040: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
11041: 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 11042: fprintf(ficlog,"Model=1+age+%s\n\
1.227 brouard 11043: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
11044: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
11045: 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 11046: for(k=-1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;}
1.339 ! brouard 11047: for(k=1, ncovf=0, nsd=0, nsq=0, ncovv=0, ncova=0, ncoveff=0, nqfveff=0, ntveff=0, nqtveff=0, ncovvt=0;k<=cptcovt; k++){ /* or cptocvt */
1.234 brouard 11048: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 11049: Fixed[k]= 0;
11050: Dummy[k]= 0;
1.225 brouard 11051: ncoveff++;
1.232 brouard 11052: ncovf++;
1.234 brouard 11053: nsd++;
11054: modell[k].maintype= FTYPE;
11055: TvarsD[nsd]=Tvar[k];
11056: TvarsDind[nsd]=k;
1.330 brouard 11057: TnsdVar[Tvar[k]]=nsd;
1.234 brouard 11058: TvarF[ncovf]=Tvar[k];
11059: TvarFind[ncovf]=k;
11060: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
11061: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.339 ! brouard 11062: /* }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /\* Product of fixed dummy (<=ncovcol) covariates For a fixed product k is higher than ncovcol *\/ */
! 11063: }else if( Tposprod[k]>0 && Typevar[k]==2 && FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){ /* Needs a fixed product Product of fixed dummy (<=ncovcol) covariates For a fixed product k is higher than ncovcol */
1.234 brouard 11064: Fixed[k]= 0;
11065: Dummy[k]= 0;
11066: ncoveff++;
11067: ncovf++;
11068: modell[k].maintype= FTYPE;
11069: TvarF[ncovf]=Tvar[k];
1.330 brouard 11070: /* TnsdVar[Tvar[k]]=nsd; */ /* To be done */
1.234 brouard 11071: TvarFind[ncovf]=k;
1.230 brouard 11072: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 11073: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.240 brouard 11074: }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 11075: Fixed[k]= 0;
11076: Dummy[k]= 1;
1.230 brouard 11077: nqfveff++;
1.234 brouard 11078: modell[k].maintype= FTYPE;
11079: modell[k].subtype= FQ;
11080: nsq++;
1.334 brouard 11081: TvarsQ[nsq]=Tvar[k]; /* Gives the variable name (extended to products) of first nsq simple quantitative covariates (fixed or time vary see below */
11082: TvarsQind[nsq]=k; /* Gives the position in the model equation of the first nsq simple quantitative covariates (fixed or time vary) */
1.232 brouard 11083: ncovf++;
1.234 brouard 11084: TvarF[ncovf]=Tvar[k];
11085: TvarFind[ncovf]=k;
1.231 brouard 11086: 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 11087: 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 11088: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.339 ! brouard 11089: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
! 11090: /* model V1+V3+age*V1+age*V3+V1*V3 */
! 11091: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
! 11092: ncovvt++;
! 11093: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
! 11094: TvarVVind[ncovvt]=k; /* TvarVVind[1]=2 (second position in the model equation */
! 11095:
1.227 brouard 11096: Fixed[k]= 1;
11097: Dummy[k]= 0;
1.225 brouard 11098: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 11099: modell[k].maintype= VTYPE;
11100: modell[k].subtype= VD;
11101: nsd++;
11102: TvarsD[nsd]=Tvar[k];
11103: TvarsDind[nsd]=k;
1.330 brouard 11104: TnsdVar[Tvar[k]]=nsd; /* To be verified */
1.234 brouard 11105: ncovv++; /* Only simple time varying variables */
11106: TvarV[ncovv]=Tvar[k];
1.242 brouard 11107: 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 11108: 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 */
11109: 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 11110: 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);
11111: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 11112: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.339 ! brouard 11113: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
! 11114: /* model V1+V3+age*V1+age*V3+V1*V3 */
! 11115: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
! 11116: ncovvt++;
! 11117: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
! 11118: TvarVVind[ncovvt]=k; /* TvarVV[1]=V3 (first time varying in the model equation */
! 11119:
1.234 brouard 11120: Fixed[k]= 1;
11121: Dummy[k]= 1;
11122: nqtveff++;
11123: modell[k].maintype= VTYPE;
11124: modell[k].subtype= VQ;
11125: ncovv++; /* Only simple time varying variables */
11126: nsq++;
1.334 brouard 11127: 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) */
11128: 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 11129: TvarV[ncovv]=Tvar[k];
1.242 brouard 11130: 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 11131: 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 */
11132: 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 11133: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
11134: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
11135: 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 11136: printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv);
1.227 brouard 11137: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 11138: ncova++;
11139: TvarA[ncova]=Tvar[k];
11140: TvarAind[ncova]=k;
1.231 brouard 11141: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 11142: Fixed[k]= 2;
11143: Dummy[k]= 2;
11144: modell[k].maintype= ATYPE;
11145: modell[k].subtype= APFD;
11146: /* ncoveff++; */
1.227 brouard 11147: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 11148: Fixed[k]= 2;
11149: Dummy[k]= 3;
11150: modell[k].maintype= ATYPE;
11151: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
11152: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 11153: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 11154: Fixed[k]= 3;
11155: Dummy[k]= 2;
11156: modell[k].maintype= ATYPE;
11157: modell[k].subtype= APVD; /* Product age * varying dummy */
11158: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 11159: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 11160: Fixed[k]= 3;
11161: Dummy[k]= 3;
11162: modell[k].maintype= ATYPE;
11163: modell[k].subtype= APVQ; /* Product age * varying quantitative */
11164: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 11165: }
1.339 ! brouard 11166: }else if (Typevar[k] == 2) { /* product Vn * Vm without age, V1+V3+age*V1+age*V3+V1*V3 looking at V1*V3, Typevar={0, 0, 1, 1, 2}, k=5, V1 is fixed, V3 is timevary, V5 is a product */
! 11167: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
! 11168: /* model V1+V3+age*V1+age*V3+V1*V3 */
! 11169: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
! 11170: k1=Tposprod[k]; /* Position in the products of product k, Tposprod={0, 0, 0, 0, 1} k1=1 first product but second time varying because of V3 */
! 11171: ncovvt++;
! 11172: TvarVV[ncovvt]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */
! 11173: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
! 11174: ncovvt++;
! 11175: TvarVV[ncovvt]=Tvard[k1][2]; /* TvarVV[3]=V3 */
! 11176: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
! 11177:
! 11178:
! 11179: if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */
! 11180: if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */
1.240 brouard 11181: Fixed[k]= 1;
11182: Dummy[k]= 0;
11183: modell[k].maintype= FTYPE;
11184: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
11185: ncovf++; /* Fixed variables without age */
11186: TvarF[ncovf]=Tvar[k];
11187: TvarFind[ncovf]=k;
1.339 ! brouard 11188: }else if(Tvard[k1][2] <=ncovcol+nqv){ /* Vm is quanti fixed */
! 11189: Fixed[k]= 0; /* Fixed product */
1.240 brouard 11190: Dummy[k]= 1;
11191: modell[k].maintype= FTYPE;
11192: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
11193: ncovf++; /* Varying variables without age */
11194: TvarF[ncovf]=Tvar[k];
11195: TvarFind[ncovf]=k;
1.339 ! brouard 11196: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is a time varying dummy covariate */
1.240 brouard 11197: Fixed[k]= 1;
11198: Dummy[k]= 0;
11199: modell[k].maintype= VTYPE;
11200: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
11201: ncovv++; /* Varying variables without age */
1.339 ! brouard 11202: TvarV[ncovv]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */
! 11203: TvarVind[ncovv]=k;/* TvarVind[1]=5 */
! 11204: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */
1.240 brouard 11205: Fixed[k]= 1;
11206: Dummy[k]= 1;
11207: modell[k].maintype= VTYPE;
11208: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
11209: ncovv++; /* Varying variables without age */
11210: TvarV[ncovv]=Tvar[k];
11211: TvarVind[ncovv]=k;
11212: }
1.339 ! brouard 11213: }else if(Tvard[k1][1] <=ncovcol+nqv){ /* Vn is fixed quanti */
! 11214: if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */
! 11215: Fixed[k]= 0; /* Fixed product */
1.240 brouard 11216: Dummy[k]= 1;
11217: modell[k].maintype= FTYPE;
11218: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
11219: ncovf++; /* Fixed variables without age */
11220: TvarF[ncovf]=Tvar[k];
11221: TvarFind[ncovf]=k;
1.339 ! brouard 11222: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is time varying */
1.240 brouard 11223: Fixed[k]= 1;
11224: Dummy[k]= 1;
11225: modell[k].maintype= VTYPE;
11226: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
11227: ncovv++; /* Varying variables without age */
11228: TvarV[ncovv]=Tvar[k];
11229: TvarVind[ncovv]=k;
1.339 ! brouard 11230: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is time varying quanti */
1.240 brouard 11231: Fixed[k]= 1;
11232: Dummy[k]= 1;
11233: modell[k].maintype= VTYPE;
11234: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
11235: ncovv++; /* Varying variables without age */
11236: TvarV[ncovv]=Tvar[k];
11237: TvarVind[ncovv]=k;
11238: ncovv++; /* Varying variables without age */
11239: TvarV[ncovv]=Tvar[k];
11240: TvarVind[ncovv]=k;
11241: }
1.339 ! brouard 11242: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ /* Vn is time varying dummy */
1.240 brouard 11243: if(Tvard[k1][2] <=ncovcol){
11244: Fixed[k]= 1;
11245: Dummy[k]= 1;
11246: modell[k].maintype= VTYPE;
11247: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
11248: ncovv++; /* Varying variables without age */
11249: TvarV[ncovv]=Tvar[k];
11250: TvarVind[ncovv]=k;
11251: }else if(Tvard[k1][2] <=ncovcol+nqv){
11252: Fixed[k]= 1;
11253: Dummy[k]= 1;
11254: modell[k].maintype= VTYPE;
11255: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
11256: ncovv++; /* Varying variables without age */
11257: TvarV[ncovv]=Tvar[k];
11258: TvarVind[ncovv]=k;
11259: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
11260: Fixed[k]= 1;
11261: Dummy[k]= 0;
11262: modell[k].maintype= VTYPE;
11263: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
11264: ncovv++; /* Varying variables without age */
11265: TvarV[ncovv]=Tvar[k];
11266: TvarVind[ncovv]=k;
11267: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
11268: Fixed[k]= 1;
11269: Dummy[k]= 1;
11270: modell[k].maintype= VTYPE;
11271: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
11272: ncovv++; /* Varying variables without age */
11273: TvarV[ncovv]=Tvar[k];
11274: TvarVind[ncovv]=k;
11275: }
1.339 ! brouard 11276: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ /* Vn is time varying quanti */
1.240 brouard 11277: if(Tvard[k1][2] <=ncovcol){
11278: Fixed[k]= 1;
11279: Dummy[k]= 1;
11280: modell[k].maintype= VTYPE;
11281: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
11282: ncovv++; /* Varying variables without age */
11283: TvarV[ncovv]=Tvar[k];
11284: TvarVind[ncovv]=k;
11285: }else if(Tvard[k1][2] <=ncovcol+nqv){
11286: Fixed[k]= 1;
11287: Dummy[k]= 1;
11288: modell[k].maintype= VTYPE;
11289: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
11290: ncovv++; /* Varying variables without age */
11291: TvarV[ncovv]=Tvar[k];
11292: TvarVind[ncovv]=k;
11293: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
11294: Fixed[k]= 1;
11295: Dummy[k]= 1;
11296: modell[k].maintype= VTYPE;
11297: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
11298: ncovv++; /* Varying variables without age */
11299: TvarV[ncovv]=Tvar[k];
11300: TvarVind[ncovv]=k;
11301: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
11302: Fixed[k]= 1;
11303: Dummy[k]= 1;
11304: modell[k].maintype= VTYPE;
11305: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
11306: ncovv++; /* Varying variables without age */
11307: TvarV[ncovv]=Tvar[k];
11308: TvarVind[ncovv]=k;
11309: }
1.227 brouard 11310: }else{
1.240 brouard 11311: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
11312: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
11313: } /*end k1*/
1.225 brouard 11314: }else{
1.226 brouard 11315: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
11316: 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 11317: }
1.227 brouard 11318: 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 11319: printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype);
1.227 brouard 11320: 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]);
11321: }
11322: /* Searching for doublons in the model */
11323: for(k1=1; k1<= cptcovt;k1++){
11324: for(k2=1; k2 <k1;k2++){
1.285 brouard 11325: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
11326: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 11327: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
11328: if(Tvar[k1]==Tvar[k2]){
1.338 brouard 11329: printf("Error duplication in the model=1+age+%s at positions (+) %d and %d, Tvar[%d]=V%d, Tvar[%d]=V%d, Typevar=%d, Fixed=%d, Dummy=%d\n", model, k1,k2, k1, Tvar[k1], k2, Tvar[k2],Typevar[k1],Fixed[k1],Dummy[k1]);
11330: fprintf(ficlog,"Error duplication in the model=1+age+%s at positions (+) %d and %d, Tvar[%d]=V%d, Tvar[%d]=V%d, Typevar=%d, Fixed=%d, Dummy=%d\n", model, k1,k2, k1, Tvar[k1], k2, Tvar[k2],Typevar[k1],Fixed[k1],Dummy[k1]); fflush(ficlog);
1.234 brouard 11331: return(1);
11332: }
11333: }else if (Typevar[k1] ==2){
11334: k3=Tposprod[k1];
11335: k4=Tposprod[k2];
11336: if( ((Tvard[k3][1]== Tvard[k4][1])&&(Tvard[k3][2]== Tvard[k4][2])) || ((Tvard[k3][1]== Tvard[k4][2])&&(Tvard[k3][2]== Tvard[k4][1])) ){
1.338 brouard 11337: printf("Error duplication in the model=1+age+%s at positions (+) %d and %d, V%d*V%d, Typevar=%d, Fixed=%d, Dummy=%d\n",model, k1,k2, Tvard[k3][1], Tvard[k3][2],Typevar[k1],Fixed[Tvar[k1]],Dummy[Tvar[k1]]);
11338: fprintf(ficlog,"Error duplication in the model=1+age+%s at positions (+) %d and %d, V%d*V%d, Typevar=%d, Fixed=%d, Dummy=%d\n",model, k1,k2, Tvard[k3][1], Tvard[k3][2],Typevar[k1],Fixed[Tvar[k1]],Dummy[Tvar[k1]]); fflush(ficlog);
1.234 brouard 11339: return(1);
11340: }
11341: }
1.227 brouard 11342: }
11343: }
1.225 brouard 11344: }
11345: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
11346: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 11347: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
11348: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 11349: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 11350: /*endread:*/
1.225 brouard 11351: printf("Exiting decodemodel: ");
11352: return (1);
1.136 brouard 11353: }
11354:
1.169 brouard 11355: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 11356: {/* Check ages at death */
1.136 brouard 11357: int i, m;
1.218 brouard 11358: int firstone=0;
11359:
1.136 brouard 11360: for (i=1; i<=imx; i++) {
11361: for(m=2; (m<= maxwav); m++) {
11362: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
11363: anint[m][i]=9999;
1.216 brouard 11364: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
11365: s[m][i]=-1;
1.136 brouard 11366: }
11367: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 11368: *nberr = *nberr + 1;
1.218 brouard 11369: if(firstone == 0){
11370: firstone=1;
1.260 brouard 11371: 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 11372: }
1.262 brouard 11373: 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 11374: s[m][i]=-1; /* Droping the death status */
1.136 brouard 11375: }
11376: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 11377: (*nberr)++;
1.259 brouard 11378: 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 11379: 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 11380: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 11381: }
11382: }
11383: }
11384:
11385: for (i=1; i<=imx; i++) {
11386: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
11387: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 11388: 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 11389: if (s[m][i] >= nlstate+1) {
1.169 brouard 11390: if(agedc[i]>0){
11391: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 11392: agev[m][i]=agedc[i];
1.214 brouard 11393: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 11394: }else {
1.136 brouard 11395: if ((int)andc[i]!=9999){
11396: nbwarn++;
11397: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
11398: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
11399: agev[m][i]=-1;
11400: }
11401: }
1.169 brouard 11402: } /* agedc > 0 */
1.214 brouard 11403: } /* end if */
1.136 brouard 11404: else if(s[m][i] !=9){ /* Standard case, age in fractional
11405: years but with the precision of a month */
11406: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
11407: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
11408: agev[m][i]=1;
11409: else if(agev[m][i] < *agemin){
11410: *agemin=agev[m][i];
11411: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
11412: }
11413: else if(agev[m][i] >*agemax){
11414: *agemax=agev[m][i];
1.156 brouard 11415: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 11416: }
11417: /*agev[m][i]=anint[m][i]-annais[i];*/
11418: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 11419: } /* en if 9*/
1.136 brouard 11420: else { /* =9 */
1.214 brouard 11421: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 11422: agev[m][i]=1;
11423: s[m][i]=-1;
11424: }
11425: }
1.214 brouard 11426: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 11427: agev[m][i]=1;
1.214 brouard 11428: else{
11429: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
11430: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
11431: agev[m][i]=0;
11432: }
11433: } /* End for lastpass */
11434: }
1.136 brouard 11435:
11436: for (i=1; i<=imx; i++) {
11437: for(m=firstpass; (m<=lastpass); m++){
11438: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 11439: (*nberr)++;
1.136 brouard 11440: 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);
11441: 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);
11442: return 1;
11443: }
11444: }
11445: }
11446:
11447: /*for (i=1; i<=imx; i++){
11448: for (m=firstpass; (m<lastpass); m++){
11449: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
11450: }
11451:
11452: }*/
11453:
11454:
1.139 brouard 11455: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
11456: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 11457:
11458: return (0);
1.164 brouard 11459: /* endread:*/
1.136 brouard 11460: printf("Exiting calandcheckages: ");
11461: return (1);
11462: }
11463:
1.172 brouard 11464: #if defined(_MSC_VER)
11465: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
11466: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
11467: //#include "stdafx.h"
11468: //#include <stdio.h>
11469: //#include <tchar.h>
11470: //#include <windows.h>
11471: //#include <iostream>
11472: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
11473:
11474: LPFN_ISWOW64PROCESS fnIsWow64Process;
11475:
11476: BOOL IsWow64()
11477: {
11478: BOOL bIsWow64 = FALSE;
11479:
11480: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
11481: // (HANDLE, PBOOL);
11482:
11483: //LPFN_ISWOW64PROCESS fnIsWow64Process;
11484:
11485: HMODULE module = GetModuleHandle(_T("kernel32"));
11486: const char funcName[] = "IsWow64Process";
11487: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
11488: GetProcAddress(module, funcName);
11489:
11490: if (NULL != fnIsWow64Process)
11491: {
11492: if (!fnIsWow64Process(GetCurrentProcess(),
11493: &bIsWow64))
11494: //throw std::exception("Unknown error");
11495: printf("Unknown error\n");
11496: }
11497: return bIsWow64 != FALSE;
11498: }
11499: #endif
1.177 brouard 11500:
1.191 brouard 11501: void syscompilerinfo(int logged)
1.292 brouard 11502: {
11503: #include <stdint.h>
11504:
11505: /* #include "syscompilerinfo.h"*/
1.185 brouard 11506: /* command line Intel compiler 32bit windows, XP compatible:*/
11507: /* /GS /W3 /Gy
11508: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
11509: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
11510: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 11511: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
11512: */
11513: /* 64 bits */
1.185 brouard 11514: /*
11515: /GS /W3 /Gy
11516: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
11517: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
11518: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
11519: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
11520: /* Optimization are useless and O3 is slower than O2 */
11521: /*
11522: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
11523: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
11524: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
11525: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
11526: */
1.186 brouard 11527: /* Link is */ /* /OUT:"visual studio
1.185 brouard 11528: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
11529: /PDB:"visual studio
11530: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
11531: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
11532: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
11533: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
11534: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
11535: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
11536: uiAccess='false'"
11537: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
11538: /NOLOGO /TLBID:1
11539: */
1.292 brouard 11540:
11541:
1.177 brouard 11542: #if defined __INTEL_COMPILER
1.178 brouard 11543: #if defined(__GNUC__)
11544: struct utsname sysInfo; /* For Intel on Linux and OS/X */
11545: #endif
1.177 brouard 11546: #elif defined(__GNUC__)
1.179 brouard 11547: #ifndef __APPLE__
1.174 brouard 11548: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 11549: #endif
1.177 brouard 11550: struct utsname sysInfo;
1.178 brouard 11551: int cross = CROSS;
11552: if (cross){
11553: printf("Cross-");
1.191 brouard 11554: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 11555: }
1.174 brouard 11556: #endif
11557:
1.191 brouard 11558: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 11559: #if defined(__clang__)
1.191 brouard 11560: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 11561: #endif
11562: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 11563: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 11564: #endif
11565: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 11566: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 11567: #endif
11568: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 11569: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 11570: #endif
11571: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 11572: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 11573: #endif
11574: #if defined(_MSC_VER)
1.191 brouard 11575: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 11576: #endif
11577: #if defined(__PGI)
1.191 brouard 11578: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 11579: #endif
11580: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 11581: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 11582: #endif
1.191 brouard 11583: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 11584:
1.167 brouard 11585: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
11586: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
11587: // Windows (x64 and x86)
1.191 brouard 11588: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 11589: #elif __unix__ // all unices, not all compilers
11590: // Unix
1.191 brouard 11591: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 11592: #elif __linux__
11593: // linux
1.191 brouard 11594: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 11595: #elif __APPLE__
1.174 brouard 11596: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 11597: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 11598: #endif
11599:
11600: /* __MINGW32__ */
11601: /* __CYGWIN__ */
11602: /* __MINGW64__ */
11603: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
11604: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
11605: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
11606: /* _WIN64 // Defined for applications for Win64. */
11607: /* _M_X64 // Defined for compilations that target x64 processors. */
11608: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 11609:
1.167 brouard 11610: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 11611: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 11612: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 11613: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 11614: #else
1.191 brouard 11615: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 11616: #endif
11617:
1.169 brouard 11618: #if defined(__GNUC__)
11619: # if defined(__GNUC_PATCHLEVEL__)
11620: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
11621: + __GNUC_MINOR__ * 100 \
11622: + __GNUC_PATCHLEVEL__)
11623: # else
11624: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
11625: + __GNUC_MINOR__ * 100)
11626: # endif
1.174 brouard 11627: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 11628: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 11629:
11630: if (uname(&sysInfo) != -1) {
11631: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 11632: 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 11633: }
11634: else
11635: perror("uname() error");
1.179 brouard 11636: //#ifndef __INTEL_COMPILER
11637: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 11638: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 11639: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 11640: #endif
1.169 brouard 11641: #endif
1.172 brouard 11642:
1.286 brouard 11643: // void main ()
1.172 brouard 11644: // {
1.169 brouard 11645: #if defined(_MSC_VER)
1.174 brouard 11646: if (IsWow64()){
1.191 brouard 11647: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
11648: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 11649: }
11650: else{
1.191 brouard 11651: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
11652: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 11653: }
1.172 brouard 11654: // printf("\nPress Enter to continue...");
11655: // getchar();
11656: // }
11657:
1.169 brouard 11658: #endif
11659:
1.167 brouard 11660:
1.219 brouard 11661: }
1.136 brouard 11662:
1.219 brouard 11663: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 11664: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.332 brouard 11665: /* Computes the prevalence limit for each combination of the dummy covariates */
1.235 brouard 11666: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 11667: /* double ftolpl = 1.e-10; */
1.180 brouard 11668: double age, agebase, agelim;
1.203 brouard 11669: double tot;
1.180 brouard 11670:
1.202 brouard 11671: strcpy(filerespl,"PL_");
11672: strcat(filerespl,fileresu);
11673: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 11674: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
11675: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 11676: }
1.288 brouard 11677: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
11678: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 11679: pstamp(ficrespl);
1.288 brouard 11680: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 11681: fprintf(ficrespl,"#Age ");
11682: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
11683: fprintf(ficrespl,"\n");
1.180 brouard 11684:
1.219 brouard 11685: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 11686:
1.219 brouard 11687: agebase=ageminpar;
11688: agelim=agemaxpar;
1.180 brouard 11689:
1.227 brouard 11690: /* i1=pow(2,ncoveff); */
1.234 brouard 11691: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 11692: if (cptcovn < 1){i1=1;}
1.180 brouard 11693:
1.337 brouard 11694: /* for(k=1; k<=i1;k++){ /\* For each combination k of dummy covariates in the model *\/ */
1.238 brouard 11695: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 11696: k=TKresult[nres];
1.338 brouard 11697: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 11698: /* if(i1 != 1 && TKresult[nres]!= k) /\* We found the combination k corresponding to the resultline value of dummies *\/ */
11699: /* continue; */
1.235 brouard 11700:
1.238 brouard 11701: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
11702: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
11703: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
11704: /* k=k+1; */
11705: /* to clean */
1.332 brouard 11706: /*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*/
1.238 brouard 11707: fprintf(ficrespl,"#******");
11708: printf("#******");
11709: fprintf(ficlog,"#******");
1.337 brouard 11710: for(j=1;j<=cptcovs ;j++) {/**< cptcovs number of SIMPLE covariates in the model or resultline V2+V1 =2 (dummy or quantit or time varying) */
1.332 brouard 11711: /* fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Here problem for varying dummy*\/ */
1.337 brouard 11712: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11713: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11714: fprintf(ficrespl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11715: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11716: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11717: }
11718: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
11719: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
11720: /* fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
11721: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
11722: /* } */
1.238 brouard 11723: fprintf(ficrespl,"******\n");
11724: printf("******\n");
11725: fprintf(ficlog,"******\n");
11726: if(invalidvarcomb[k]){
11727: printf("\nCombination (%d) ignored because no case \n",k);
11728: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
11729: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
11730: continue;
11731: }
1.219 brouard 11732:
1.238 brouard 11733: fprintf(ficrespl,"#Age ");
1.337 brouard 11734: /* for(j=1;j<=cptcoveff;j++) { */
11735: /* fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11736: /* } */
11737: for(j=1;j<=cptcovs;j++) { /* New the quanti variable is added */
11738: fprintf(ficrespl,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 11739: }
11740: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
11741: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 11742:
1.238 brouard 11743: for (age=agebase; age<=agelim; age++){
11744: /* for (age=agebase; age<=agebase; age++){ */
1.337 brouard 11745: /**< Computes the prevalence limit in each live state at age x and for covariate combination (k and) nres */
11746: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres); /* Nicely done */
1.238 brouard 11747: fprintf(ficrespl,"%.0f ",age );
1.337 brouard 11748: /* for(j=1;j<=cptcoveff;j++) */
11749: /* fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11750: for(j=1;j<=cptcovs;j++)
11751: fprintf(ficrespl,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 11752: tot=0.;
11753: for(i=1; i<=nlstate;i++){
11754: tot += prlim[i][i];
11755: fprintf(ficrespl," %.5f", prlim[i][i]);
11756: }
11757: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
11758: } /* Age */
11759: /* was end of cptcod */
1.337 brouard 11760: } /* nres */
11761: /* } /\* for each combination *\/ */
1.219 brouard 11762: return 0;
1.180 brouard 11763: }
11764:
1.218 brouard 11765: 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 11766: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 11767:
11768: /* Computes the back prevalence limit for any combination of covariate values
11769: * at any age between ageminpar and agemaxpar
11770: */
1.235 brouard 11771: int i, j, k, i1, nres=0 ;
1.217 brouard 11772: /* double ftolpl = 1.e-10; */
11773: double age, agebase, agelim;
11774: double tot;
1.218 brouard 11775: /* double ***mobaverage; */
11776: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 11777:
11778: strcpy(fileresplb,"PLB_");
11779: strcat(fileresplb,fileresu);
11780: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 11781: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
11782: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 11783: }
1.288 brouard 11784: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
11785: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 11786: pstamp(ficresplb);
1.288 brouard 11787: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 11788: fprintf(ficresplb,"#Age ");
11789: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
11790: fprintf(ficresplb,"\n");
11791:
1.218 brouard 11792:
11793: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
11794:
11795: agebase=ageminpar;
11796: agelim=agemaxpar;
11797:
11798:
1.227 brouard 11799: i1=pow(2,cptcoveff);
1.218 brouard 11800: if (cptcovn < 1){i1=1;}
1.227 brouard 11801:
1.238 brouard 11802: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.338 brouard 11803: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
11804: k=TKresult[nres];
11805: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
11806: /* if(i1 != 1 && TKresult[nres]!= k) */
11807: /* continue; */
11808: /* /\*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*\/ */
1.238 brouard 11809: fprintf(ficresplb,"#******");
11810: printf("#******");
11811: fprintf(ficlog,"#******");
1.338 brouard 11812: for(j=1;j<=cptcovs ;j++) {/**< cptcovs number of SIMPLE covariates in the model or resultline V2+V1 =2 (dummy or quantit or time varying) */
11813: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11814: fprintf(ficresplb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11815: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 11816: }
1.338 brouard 11817: /* for(j=1;j<=cptcoveff ;j++) {/\* all covariates *\/ */
11818: /* fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11819: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11820: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11821: /* } */
11822: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
11823: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
11824: /* fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
11825: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
11826: /* } */
1.238 brouard 11827: fprintf(ficresplb,"******\n");
11828: printf("******\n");
11829: fprintf(ficlog,"******\n");
11830: if(invalidvarcomb[k]){
11831: printf("\nCombination (%d) ignored because no cases \n",k);
11832: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
11833: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
11834: continue;
11835: }
1.218 brouard 11836:
1.238 brouard 11837: fprintf(ficresplb,"#Age ");
1.338 brouard 11838: for(j=1;j<=cptcovs;j++) {
11839: fprintf(ficresplb,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 11840: }
11841: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
11842: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 11843:
11844:
1.238 brouard 11845: for (age=agebase; age<=agelim; age++){
11846: /* for (age=agebase; age<=agebase; age++){ */
11847: if(mobilavproj > 0){
11848: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
11849: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 11850: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 11851: }else if (mobilavproj == 0){
11852: 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);
11853: 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);
11854: exit(1);
11855: }else{
11856: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 11857: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 11858: /* printf("TOTOT\n"); */
11859: /* exit(1); */
1.238 brouard 11860: }
11861: fprintf(ficresplb,"%.0f ",age );
1.338 brouard 11862: for(j=1;j<=cptcovs;j++)
11863: fprintf(ficresplb,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 11864: tot=0.;
11865: for(i=1; i<=nlstate;i++){
11866: tot += bprlim[i][i];
11867: fprintf(ficresplb," %.5f", bprlim[i][i]);
11868: }
11869: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
11870: } /* Age */
11871: /* was end of cptcod */
1.255 brouard 11872: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.338 brouard 11873: /* } /\* end of any combination *\/ */
1.238 brouard 11874: } /* end of nres */
1.218 brouard 11875: /* hBijx(p, bage, fage); */
11876: /* fclose(ficrespijb); */
11877:
11878: return 0;
1.217 brouard 11879: }
1.218 brouard 11880:
1.180 brouard 11881: int hPijx(double *p, int bage, int fage){
11882: /*------------- h Pij x at various ages ------------*/
1.336 brouard 11883: /* to be optimized with precov */
1.180 brouard 11884: int stepsize;
11885: int agelim;
11886: int hstepm;
11887: int nhstepm;
1.235 brouard 11888: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 11889:
11890: double agedeb;
11891: double ***p3mat;
11892:
1.337 brouard 11893: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
11894: if((ficrespij=fopen(filerespij,"w"))==NULL) {
11895: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
11896: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
11897: }
11898: printf("Computing pij: result on file '%s' \n", filerespij);
11899: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
11900:
11901: stepsize=(int) (stepm+YEARM-1)/YEARM;
11902: /*if (stepm<=24) stepsize=2;*/
11903:
11904: agelim=AGESUP;
11905: hstepm=stepsize*YEARM; /* Every year of age */
11906: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
11907:
11908: /* hstepm=1; aff par mois*/
11909: pstamp(ficrespij);
11910: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
11911: i1= pow(2,cptcoveff);
11912: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
11913: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
11914: /* k=k+1; */
11915: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
11916: k=TKresult[nres];
1.338 brouard 11917: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 11918: /* for(k=1; k<=i1;k++){ */
11919: /* if(i1 != 1 && TKresult[nres]!= k) */
11920: /* continue; */
11921: fprintf(ficrespij,"\n#****** ");
11922: for(j=1;j<=cptcovs;j++){
11923: fprintf(ficrespij," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11924: /* fprintf(ficrespij,"@wV%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11925: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
11926: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
11927: /* fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
11928: }
11929: fprintf(ficrespij,"******\n");
11930:
11931: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
11932: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
11933: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
11934:
11935: /* nhstepm=nhstepm*YEARM; aff par mois*/
11936:
11937: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11938: oldm=oldms;savm=savms;
11939: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
11940: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
11941: for(i=1; i<=nlstate;i++)
11942: for(j=1; j<=nlstate+ndeath;j++)
11943: fprintf(ficrespij," %1d-%1d",i,j);
11944: fprintf(ficrespij,"\n");
11945: for (h=0; h<=nhstepm; h++){
11946: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
11947: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.183 brouard 11948: for(i=1; i<=nlstate;i++)
11949: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 11950: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.183 brouard 11951: fprintf(ficrespij,"\n");
11952: }
1.337 brouard 11953: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11954: fprintf(ficrespij,"\n");
1.180 brouard 11955: }
1.337 brouard 11956: }
11957: /*}*/
11958: return 0;
1.180 brouard 11959: }
1.218 brouard 11960:
11961: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 11962: /*------------- h Bij x at various ages ------------*/
1.336 brouard 11963: /* To be optimized with precov */
1.217 brouard 11964: int stepsize;
1.218 brouard 11965: /* int agelim; */
11966: int ageminl;
1.217 brouard 11967: int hstepm;
11968: int nhstepm;
1.238 brouard 11969: int h, i, i1, j, k, nres;
1.218 brouard 11970:
1.217 brouard 11971: double agedeb;
11972: double ***p3mat;
1.218 brouard 11973:
11974: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
11975: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
11976: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
11977: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
11978: }
11979: printf("Computing pij back: result on file '%s' \n", filerespijb);
11980: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
11981:
11982: stepsize=(int) (stepm+YEARM-1)/YEARM;
11983: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 11984:
1.218 brouard 11985: /* agelim=AGESUP; */
1.289 brouard 11986: ageminl=AGEINF; /* was 30 */
1.218 brouard 11987: hstepm=stepsize*YEARM; /* Every year of age */
11988: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
11989:
11990: /* hstepm=1; aff par mois*/
11991: pstamp(ficrespijb);
1.255 brouard 11992: 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 11993: i1= pow(2,cptcoveff);
1.218 brouard 11994: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
11995: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
11996: /* k=k+1; */
1.238 brouard 11997: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 11998: k=TKresult[nres];
1.338 brouard 11999: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12000: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
12001: /* if(i1 != 1 && TKresult[nres]!= k) */
12002: /* continue; */
12003: fprintf(ficrespijb,"\n#****** ");
12004: for(j=1;j<=cptcovs;j++){
1.338 brouard 12005: fprintf(ficrespijb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.337 brouard 12006: /* for(j=1;j<=cptcoveff;j++) */
12007: /* fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12008: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
12009: /* fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12010: }
12011: fprintf(ficrespijb,"******\n");
12012: if(invalidvarcomb[k]){ /* Is it necessary here? */
12013: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
12014: continue;
12015: }
12016:
12017: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
12018: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
12019: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
12020: 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 */
12021: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 or 28*/
12022:
12023: /* nhstepm=nhstepm*YEARM; aff par mois*/
12024:
12025: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
12026: /* and memory limitations if stepm is small */
12027:
12028: /* oldm=oldms;savm=savms; */
12029: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
12030: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);/* Bug valgrind */
12031: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
12032: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
12033: for(i=1; i<=nlstate;i++)
12034: for(j=1; j<=nlstate+ndeath;j++)
12035: fprintf(ficrespijb," %1d-%1d",i,j);
12036: fprintf(ficrespijb,"\n");
12037: for (h=0; h<=nhstepm; h++){
12038: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
12039: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
12040: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
1.217 brouard 12041: for(i=1; i<=nlstate;i++)
12042: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 12043: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);/* Bug valgrind */
1.217 brouard 12044: fprintf(ficrespijb,"\n");
1.337 brouard 12045: }
12046: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12047: fprintf(ficrespijb,"\n");
12048: } /* end age deb */
12049: /* } /\* end combination *\/ */
1.238 brouard 12050: } /* end nres */
1.218 brouard 12051: return 0;
12052: } /* hBijx */
1.217 brouard 12053:
1.180 brouard 12054:
1.136 brouard 12055: /***********************************************/
12056: /**************** Main Program *****************/
12057: /***********************************************/
12058:
12059: int main(int argc, char *argv[])
12060: {
12061: #ifdef GSL
12062: const gsl_multimin_fminimizer_type *T;
12063: size_t iteri = 0, it;
12064: int rval = GSL_CONTINUE;
12065: int status = GSL_SUCCESS;
12066: double ssval;
12067: #endif
12068: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 12069: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
12070: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 12071: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 12072: int jj, ll, li, lj, lk;
1.136 brouard 12073: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 12074: int num_filled;
1.136 brouard 12075: int itimes;
12076: int NDIM=2;
12077: int vpopbased=0;
1.235 brouard 12078: int nres=0;
1.258 brouard 12079: int endishere=0;
1.277 brouard 12080: int noffset=0;
1.274 brouard 12081: int ncurrv=0; /* Temporary variable */
12082:
1.164 brouard 12083: char ca[32], cb[32];
1.136 brouard 12084: /* FILE *fichtm; *//* Html File */
12085: /* FILE *ficgp;*/ /*Gnuplot File */
12086: struct stat info;
1.191 brouard 12087: double agedeb=0.;
1.194 brouard 12088:
12089: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 12090: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 12091:
1.165 brouard 12092: double fret;
1.191 brouard 12093: double dum=0.; /* Dummy variable */
1.136 brouard 12094: double ***p3mat;
1.218 brouard 12095: /* double ***mobaverage; */
1.319 brouard 12096: double wald;
1.164 brouard 12097:
12098: char line[MAXLINE];
1.197 brouard 12099: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
12100:
1.234 brouard 12101: char modeltemp[MAXLINE];
1.332 brouard 12102: char resultline[MAXLINE], resultlineori[MAXLINE];
1.230 brouard 12103:
1.136 brouard 12104: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 12105: char *tok, *val; /* pathtot */
1.334 brouard 12106: /* int firstobs=1, lastobs=10; /\* nobs = lastobs-firstobs declared globally ;*\/ */
1.195 brouard 12107: int c, h , cpt, c2;
1.191 brouard 12108: int jl=0;
12109: int i1, j1, jk, stepsize=0;
1.194 brouard 12110: int count=0;
12111:
1.164 brouard 12112: int *tab;
1.136 brouard 12113: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.296 brouard 12114: /* double anprojd, mprojd, jprojd; /\* For eventual projections *\/ */
12115: /* double anprojf, mprojf, jprojf; */
12116: /* double jintmean,mintmean,aintmean; */
12117: int prvforecast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
12118: int prvbackcast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
12119: double yrfproj= 10.0; /* Number of years of forward projections */
12120: double yrbproj= 10.0; /* Number of years of backward projections */
12121: int prevbcast=0; /* defined as global for mlikeli and mle, replacing backcast */
1.136 brouard 12122: int mobilav=0,popforecast=0;
1.191 brouard 12123: int hstepm=0, nhstepm=0;
1.136 brouard 12124: int agemortsup;
12125: float sumlpop=0.;
12126: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
12127: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
12128:
1.191 brouard 12129: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 12130: double ftolpl=FTOL;
12131: double **prlim;
1.217 brouard 12132: double **bprlim;
1.317 brouard 12133: double ***param; /* Matrix of parameters, param[i][j][k] param=ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel)
12134: state of origin, state of destination including death, for each covariate: constante, age, and V1 V2 etc. */
1.251 brouard 12135: double ***paramstart; /* Matrix of starting parameter values */
12136: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 12137: double **matcov; /* Matrix of covariance */
1.203 brouard 12138: double **hess; /* Hessian matrix */
1.136 brouard 12139: double ***delti3; /* Scale */
12140: double *delti; /* Scale */
12141: double ***eij, ***vareij;
12142: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 12143:
1.136 brouard 12144: double *epj, vepp;
1.164 brouard 12145:
1.273 brouard 12146: double dateprev1, dateprev2;
1.296 brouard 12147: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0, dateprojd=0, dateprojf=0;
12148: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0, datebackd=0, datebackf=0;
12149:
1.217 brouard 12150:
1.136 brouard 12151: double **ximort;
1.145 brouard 12152: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 12153: int *dcwave;
12154:
1.164 brouard 12155: char z[1]="c";
1.136 brouard 12156:
12157: /*char *strt;*/
12158: char strtend[80];
1.126 brouard 12159:
1.164 brouard 12160:
1.126 brouard 12161: /* setlocale (LC_ALL, ""); */
12162: /* bindtextdomain (PACKAGE, LOCALEDIR); */
12163: /* textdomain (PACKAGE); */
12164: /* setlocale (LC_CTYPE, ""); */
12165: /* setlocale (LC_MESSAGES, ""); */
12166:
12167: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 12168: rstart_time = time(NULL);
12169: /* (void) gettimeofday(&start_time,&tzp);*/
12170: start_time = *localtime(&rstart_time);
1.126 brouard 12171: curr_time=start_time;
1.157 brouard 12172: /*tml = *localtime(&start_time.tm_sec);*/
12173: /* strcpy(strstart,asctime(&tml)); */
12174: strcpy(strstart,asctime(&start_time));
1.126 brouard 12175:
12176: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 12177: /* tp.tm_sec = tp.tm_sec +86400; */
12178: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 12179: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
12180: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
12181: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 12182: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 12183: /* strt=asctime(&tmg); */
12184: /* printf("Time(after) =%s",strstart); */
12185: /* (void) time (&time_value);
12186: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
12187: * tm = *localtime(&time_value);
12188: * strstart=asctime(&tm);
12189: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
12190: */
12191:
12192: nberr=0; /* Number of errors and warnings */
12193: nbwarn=0;
1.184 brouard 12194: #ifdef WIN32
12195: _getcwd(pathcd, size);
12196: #else
1.126 brouard 12197: getcwd(pathcd, size);
1.184 brouard 12198: #endif
1.191 brouard 12199: syscompilerinfo(0);
1.196 brouard 12200: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 12201: if(argc <=1){
12202: printf("\nEnter the parameter file name: ");
1.205 brouard 12203: if(!fgets(pathr,FILENAMELENGTH,stdin)){
12204: printf("ERROR Empty parameter file name\n");
12205: goto end;
12206: }
1.126 brouard 12207: i=strlen(pathr);
12208: if(pathr[i-1]=='\n')
12209: pathr[i-1]='\0';
1.156 brouard 12210: i=strlen(pathr);
1.205 brouard 12211: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 12212: pathr[i-1]='\0';
1.205 brouard 12213: }
12214: i=strlen(pathr);
12215: if( i==0 ){
12216: printf("ERROR Empty parameter file name\n");
12217: goto end;
12218: }
12219: for (tok = pathr; tok != NULL; ){
1.126 brouard 12220: printf("Pathr |%s|\n",pathr);
12221: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
12222: printf("val= |%s| pathr=%s\n",val,pathr);
12223: strcpy (pathtot, val);
12224: if(pathr[0] == '\0') break; /* Dirty */
12225: }
12226: }
1.281 brouard 12227: else if (argc<=2){
12228: strcpy(pathtot,argv[1]);
12229: }
1.126 brouard 12230: else{
12231: strcpy(pathtot,argv[1]);
1.281 brouard 12232: strcpy(z,argv[2]);
12233: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 12234: }
12235: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
12236: /*cygwin_split_path(pathtot,path,optionfile);
12237: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
12238: /* cutv(path,optionfile,pathtot,'\\');*/
12239:
12240: /* Split argv[0], imach program to get pathimach */
12241: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
12242: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
12243: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
12244: /* strcpy(pathimach,argv[0]); */
12245: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
12246: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
12247: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 12248: #ifdef WIN32
12249: _chdir(path); /* Can be a relative path */
12250: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
12251: #else
1.126 brouard 12252: chdir(path); /* Can be a relative path */
1.184 brouard 12253: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
12254: #endif
12255: printf("Current directory %s!\n",pathcd);
1.126 brouard 12256: strcpy(command,"mkdir ");
12257: strcat(command,optionfilefiname);
12258: if((outcmd=system(command)) != 0){
1.169 brouard 12259: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 12260: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
12261: /* fclose(ficlog); */
12262: /* exit(1); */
12263: }
12264: /* if((imk=mkdir(optionfilefiname))<0){ */
12265: /* perror("mkdir"); */
12266: /* } */
12267:
12268: /*-------- arguments in the command line --------*/
12269:
1.186 brouard 12270: /* Main Log file */
1.126 brouard 12271: strcat(filelog, optionfilefiname);
12272: strcat(filelog,".log"); /* */
12273: if((ficlog=fopen(filelog,"w"))==NULL) {
12274: printf("Problem with logfile %s\n",filelog);
12275: goto end;
12276: }
12277: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 12278: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 12279: fprintf(ficlog,"\nEnter the parameter file name: \n");
12280: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
12281: path=%s \n\
12282: optionfile=%s\n\
12283: optionfilext=%s\n\
1.156 brouard 12284: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 12285:
1.197 brouard 12286: syscompilerinfo(1);
1.167 brouard 12287:
1.126 brouard 12288: printf("Local time (at start):%s",strstart);
12289: fprintf(ficlog,"Local time (at start): %s",strstart);
12290: fflush(ficlog);
12291: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 12292: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 12293:
12294: /* */
12295: strcpy(fileres,"r");
12296: strcat(fileres, optionfilefiname);
1.201 brouard 12297: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 12298: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 12299: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 12300:
1.186 brouard 12301: /* Main ---------arguments file --------*/
1.126 brouard 12302:
12303: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 12304: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
12305: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 12306: fflush(ficlog);
1.149 brouard 12307: /* goto end; */
12308: exit(70);
1.126 brouard 12309: }
12310:
12311: strcpy(filereso,"o");
1.201 brouard 12312: strcat(filereso,fileresu);
1.126 brouard 12313: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
12314: printf("Problem with Output resultfile: %s\n", filereso);
12315: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
12316: fflush(ficlog);
12317: goto end;
12318: }
1.278 brouard 12319: /*-------- Rewriting parameter file ----------*/
12320: strcpy(rfileres,"r"); /* "Rparameterfile */
12321: strcat(rfileres,optionfilefiname); /* Parameter file first name */
12322: strcat(rfileres,"."); /* */
12323: strcat(rfileres,optionfilext); /* Other files have txt extension */
12324: if((ficres =fopen(rfileres,"w"))==NULL) {
12325: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
12326: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
12327: fflush(ficlog);
12328: goto end;
12329: }
12330: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 12331:
1.278 brouard 12332:
1.126 brouard 12333: /* Reads comments: lines beginning with '#' */
12334: numlinepar=0;
1.277 brouard 12335: /* Is it a BOM UTF-8 Windows file? */
12336: /* First parameter line */
1.197 brouard 12337: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 12338: noffset=0;
12339: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
12340: {
12341: noffset=noffset+3;
12342: printf("# File is an UTF8 Bom.\n"); // 0xBF
12343: }
1.302 brouard 12344: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
12345: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
1.277 brouard 12346: {
12347: noffset=noffset+2;
12348: printf("# File is an UTF16BE BOM file\n");
12349: }
12350: else if( line[0] == 0 && line[1] == 0)
12351: {
12352: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
12353: noffset=noffset+4;
12354: printf("# File is an UTF16BE BOM file\n");
12355: }
12356: } else{
12357: ;/*printf(" Not a BOM file\n");*/
12358: }
12359:
1.197 brouard 12360: /* If line starts with a # it is a comment */
1.277 brouard 12361: if (line[noffset] == '#') {
1.197 brouard 12362: numlinepar++;
12363: fputs(line,stdout);
12364: fputs(line,ficparo);
1.278 brouard 12365: fputs(line,ficres);
1.197 brouard 12366: fputs(line,ficlog);
12367: continue;
12368: }else
12369: break;
12370: }
12371: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
12372: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
12373: if (num_filled != 5) {
12374: printf("Should be 5 parameters\n");
1.283 brouard 12375: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 12376: }
1.126 brouard 12377: numlinepar++;
1.197 brouard 12378: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 12379: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
12380: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
12381: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 12382: }
12383: /* Second parameter line */
12384: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 12385: /* while(fscanf(ficpar,"%[^\n]", line)) { */
12386: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 12387: if (line[0] == '#') {
12388: numlinepar++;
1.283 brouard 12389: printf("%s",line);
12390: fprintf(ficres,"%s",line);
12391: fprintf(ficparo,"%s",line);
12392: fprintf(ficlog,"%s",line);
1.197 brouard 12393: continue;
12394: }else
12395: break;
12396: }
1.223 brouard 12397: 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", \
12398: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
12399: if (num_filled != 11) {
12400: 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 12401: printf("but line=%s\n",line);
1.283 brouard 12402: 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");
12403: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 12404: }
1.286 brouard 12405: if( lastpass > maxwav){
12406: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
12407: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
12408: fflush(ficlog);
12409: goto end;
12410: }
12411: 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 12412: 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 12413: 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 12414: 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 12415: }
1.203 brouard 12416: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 12417: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 12418: /* Third parameter line */
12419: while(fgets(line, MAXLINE, ficpar)) {
12420: /* If line starts with a # it is a comment */
12421: if (line[0] == '#') {
12422: numlinepar++;
1.283 brouard 12423: printf("%s",line);
12424: fprintf(ficres,"%s",line);
12425: fprintf(ficparo,"%s",line);
12426: fprintf(ficlog,"%s",line);
1.197 brouard 12427: continue;
12428: }else
12429: break;
12430: }
1.201 brouard 12431: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.279 brouard 12432: if (num_filled != 1){
1.302 brouard 12433: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
12434: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
1.197 brouard 12435: model[0]='\0';
12436: goto end;
12437: }
12438: else{
12439: if (model[0]=='+'){
12440: for(i=1; i<=strlen(model);i++)
12441: modeltemp[i-1]=model[i];
1.201 brouard 12442: strcpy(model,modeltemp);
1.197 brouard 12443: }
12444: }
1.338 brouard 12445: /* printf(" model=1+age%s modeltemp= %s, model=1+age+%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 12446: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 12447: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
12448: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
12449: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 12450: }
12451: /* 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); */
12452: /* numlinepar=numlinepar+3; /\* In general *\/ */
12453: /* 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 12454: /* 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); */
12455: /* 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 12456: fflush(ficlog);
1.190 brouard 12457: /* if(model[0]=='#'|| model[0]== '\0'){ */
12458: if(model[0]=='#'){
1.279 brouard 12459: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
12460: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
12461: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 12462: if(mle != -1){
1.279 brouard 12463: 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 12464: exit(1);
12465: }
12466: }
1.126 brouard 12467: while((c=getc(ficpar))=='#' && c!= EOF){
12468: ungetc(c,ficpar);
12469: fgets(line, MAXLINE, ficpar);
12470: numlinepar++;
1.195 brouard 12471: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
12472: z[0]=line[1];
12473: }
12474: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 12475: fputs(line, stdout);
12476: //puts(line);
1.126 brouard 12477: fputs(line,ficparo);
12478: fputs(line,ficlog);
12479: }
12480: ungetc(c,ficpar);
12481:
12482:
1.290 brouard 12483: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
12484: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
12485: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
12486: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /**< Time varying covariate (dummy and quantitative)*/
1.136 brouard 12487: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
12488: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
12489: v1+v2*age+v2*v3 makes cptcovn = 3
12490: */
12491: if (strlen(model)>1)
1.187 brouard 12492: 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 12493: else
1.187 brouard 12494: ncovmodel=2; /* Constant and age */
1.133 brouard 12495: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
12496: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 12497: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
12498: 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);
12499: 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);
12500: fflush(stdout);
12501: fclose (ficlog);
12502: goto end;
12503: }
1.126 brouard 12504: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
12505: delti=delti3[1][1];
12506: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
12507: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 12508: /* We could also provide initial parameters values giving by simple logistic regression
12509: * only one way, that is without matrix product. We will have nlstate maximizations */
12510: /* for(i=1;i<nlstate;i++){ */
12511: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
12512: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
12513: /* } */
1.126 brouard 12514: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 12515: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
12516: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 12517: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12518: fclose (ficparo);
12519: fclose (ficlog);
12520: goto end;
12521: exit(0);
1.220 brouard 12522: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 12523: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 12524: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
12525: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 12526: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
12527: matcov=matrix(1,npar,1,npar);
1.203 brouard 12528: hess=matrix(1,npar,1,npar);
1.220 brouard 12529: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 12530: /* Read guessed parameters */
1.126 brouard 12531: /* Reads comments: lines beginning with '#' */
12532: while((c=getc(ficpar))=='#' && c!= EOF){
12533: ungetc(c,ficpar);
12534: fgets(line, MAXLINE, ficpar);
12535: numlinepar++;
1.141 brouard 12536: fputs(line,stdout);
1.126 brouard 12537: fputs(line,ficparo);
12538: fputs(line,ficlog);
12539: }
12540: ungetc(c,ficpar);
12541:
12542: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 12543: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 12544: for(i=1; i <=nlstate; i++){
1.234 brouard 12545: j=0;
1.126 brouard 12546: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 12547: if(jj==i) continue;
12548: j++;
1.292 brouard 12549: while((c=getc(ficpar))=='#' && c!= EOF){
12550: ungetc(c,ficpar);
12551: fgets(line, MAXLINE, ficpar);
12552: numlinepar++;
12553: fputs(line,stdout);
12554: fputs(line,ficparo);
12555: fputs(line,ficlog);
12556: }
12557: ungetc(c,ficpar);
1.234 brouard 12558: fscanf(ficpar,"%1d%1d",&i1,&j1);
12559: if ((i1 != i) || (j1 != jj)){
12560: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 12561: It might be a problem of design; if ncovcol and the model are correct\n \
12562: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 12563: exit(1);
12564: }
12565: fprintf(ficparo,"%1d%1d",i1,j1);
12566: if(mle==1)
12567: printf("%1d%1d",i,jj);
12568: fprintf(ficlog,"%1d%1d",i,jj);
12569: for(k=1; k<=ncovmodel;k++){
12570: fscanf(ficpar," %lf",¶m[i][j][k]);
12571: if(mle==1){
12572: printf(" %lf",param[i][j][k]);
12573: fprintf(ficlog," %lf",param[i][j][k]);
12574: }
12575: else
12576: fprintf(ficlog," %lf",param[i][j][k]);
12577: fprintf(ficparo," %lf",param[i][j][k]);
12578: }
12579: fscanf(ficpar,"\n");
12580: numlinepar++;
12581: if(mle==1)
12582: printf("\n");
12583: fprintf(ficlog,"\n");
12584: fprintf(ficparo,"\n");
1.126 brouard 12585: }
12586: }
12587: fflush(ficlog);
1.234 brouard 12588:
1.251 brouard 12589: /* Reads parameters values */
1.126 brouard 12590: p=param[1][1];
1.251 brouard 12591: pstart=paramstart[1][1];
1.126 brouard 12592:
12593: /* Reads comments: lines beginning with '#' */
12594: while((c=getc(ficpar))=='#' && c!= EOF){
12595: ungetc(c,ficpar);
12596: fgets(line, MAXLINE, ficpar);
12597: numlinepar++;
1.141 brouard 12598: fputs(line,stdout);
1.126 brouard 12599: fputs(line,ficparo);
12600: fputs(line,ficlog);
12601: }
12602: ungetc(c,ficpar);
12603:
12604: for(i=1; i <=nlstate; i++){
12605: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 12606: fscanf(ficpar,"%1d%1d",&i1,&j1);
12607: if ( (i1-i) * (j1-j) != 0){
12608: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
12609: exit(1);
12610: }
12611: printf("%1d%1d",i,j);
12612: fprintf(ficparo,"%1d%1d",i1,j1);
12613: fprintf(ficlog,"%1d%1d",i1,j1);
12614: for(k=1; k<=ncovmodel;k++){
12615: fscanf(ficpar,"%le",&delti3[i][j][k]);
12616: printf(" %le",delti3[i][j][k]);
12617: fprintf(ficparo," %le",delti3[i][j][k]);
12618: fprintf(ficlog," %le",delti3[i][j][k]);
12619: }
12620: fscanf(ficpar,"\n");
12621: numlinepar++;
12622: printf("\n");
12623: fprintf(ficparo,"\n");
12624: fprintf(ficlog,"\n");
1.126 brouard 12625: }
12626: }
12627: fflush(ficlog);
1.234 brouard 12628:
1.145 brouard 12629: /* Reads covariance matrix */
1.126 brouard 12630: delti=delti3[1][1];
1.220 brouard 12631:
12632:
1.126 brouard 12633: /* 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 12634:
1.126 brouard 12635: /* Reads comments: lines beginning with '#' */
12636: while((c=getc(ficpar))=='#' && c!= EOF){
12637: ungetc(c,ficpar);
12638: fgets(line, MAXLINE, ficpar);
12639: numlinepar++;
1.141 brouard 12640: fputs(line,stdout);
1.126 brouard 12641: fputs(line,ficparo);
12642: fputs(line,ficlog);
12643: }
12644: ungetc(c,ficpar);
1.220 brouard 12645:
1.126 brouard 12646: matcov=matrix(1,npar,1,npar);
1.203 brouard 12647: hess=matrix(1,npar,1,npar);
1.131 brouard 12648: for(i=1; i <=npar; i++)
12649: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 12650:
1.194 brouard 12651: /* Scans npar lines */
1.126 brouard 12652: for(i=1; i <=npar; i++){
1.226 brouard 12653: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 12654: if(count != 3){
1.226 brouard 12655: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 12656: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
12657: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 12658: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 12659: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
12660: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 12661: exit(1);
1.220 brouard 12662: }else{
1.226 brouard 12663: if(mle==1)
12664: printf("%1d%1d%d",i1,j1,jk);
12665: }
12666: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
12667: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 12668: for(j=1; j <=i; j++){
1.226 brouard 12669: fscanf(ficpar," %le",&matcov[i][j]);
12670: if(mle==1){
12671: printf(" %.5le",matcov[i][j]);
12672: }
12673: fprintf(ficlog," %.5le",matcov[i][j]);
12674: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 12675: }
12676: fscanf(ficpar,"\n");
12677: numlinepar++;
12678: if(mle==1)
1.220 brouard 12679: printf("\n");
1.126 brouard 12680: fprintf(ficlog,"\n");
12681: fprintf(ficparo,"\n");
12682: }
1.194 brouard 12683: /* End of read covariance matrix npar lines */
1.126 brouard 12684: for(i=1; i <=npar; i++)
12685: for(j=i+1;j<=npar;j++)
1.226 brouard 12686: matcov[i][j]=matcov[j][i];
1.126 brouard 12687:
12688: if(mle==1)
12689: printf("\n");
12690: fprintf(ficlog,"\n");
12691:
12692: fflush(ficlog);
12693:
12694: } /* End of mle != -3 */
1.218 brouard 12695:
1.186 brouard 12696: /* Main data
12697: */
1.290 brouard 12698: nobs=lastobs-firstobs+1; /* was = lastobs;*/
12699: /* num=lvector(1,n); */
12700: /* moisnais=vector(1,n); */
12701: /* annais=vector(1,n); */
12702: /* moisdc=vector(1,n); */
12703: /* andc=vector(1,n); */
12704: /* weight=vector(1,n); */
12705: /* agedc=vector(1,n); */
12706: /* cod=ivector(1,n); */
12707: /* for(i=1;i<=n;i++){ */
12708: num=lvector(firstobs,lastobs);
12709: moisnais=vector(firstobs,lastobs);
12710: annais=vector(firstobs,lastobs);
12711: moisdc=vector(firstobs,lastobs);
12712: andc=vector(firstobs,lastobs);
12713: weight=vector(firstobs,lastobs);
12714: agedc=vector(firstobs,lastobs);
12715: cod=ivector(firstobs,lastobs);
12716: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 12717: num[i]=0;
12718: moisnais[i]=0;
12719: annais[i]=0;
12720: moisdc[i]=0;
12721: andc[i]=0;
12722: agedc[i]=0;
12723: cod[i]=0;
12724: weight[i]=1.0; /* Equal weights, 1 by default */
12725: }
1.290 brouard 12726: mint=matrix(1,maxwav,firstobs,lastobs);
12727: anint=matrix(1,maxwav,firstobs,lastobs);
1.325 brouard 12728: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
1.336 brouard 12729: /* printf("BUG ncovmodel=%d NCOVMAX=%d 2**ncovmodel=%f BUG\n",ncovmodel,NCOVMAX,pow(2,ncovmodel)); */
1.126 brouard 12730: tab=ivector(1,NCOVMAX);
1.144 brouard 12731: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 12732: 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 12733:
1.136 brouard 12734: /* Reads data from file datafile */
12735: if (readdata(datafile, firstobs, lastobs, &imx)==1)
12736: goto end;
12737:
12738: /* Calculation of the number of parameters from char model */
1.234 brouard 12739: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 12740: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
12741: k=3 V4 Tvar[k=3]= 4 (from V4)
12742: k=2 V1 Tvar[k=2]= 1 (from V1)
12743: k=1 Tvar[1]=2 (from V2)
1.234 brouard 12744: */
12745:
12746: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
12747: TvarsDind=ivector(1,NCOVMAX); /* */
1.330 brouard 12748: TnsdVar=ivector(1,NCOVMAX); /* */
1.335 brouard 12749: /* for(i=1; i<=NCOVMAX;i++) TnsdVar[i]=3; */
1.234 brouard 12750: TvarsD=ivector(1,NCOVMAX); /* */
12751: TvarsQind=ivector(1,NCOVMAX); /* */
12752: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 12753: TvarF=ivector(1,NCOVMAX); /* */
12754: TvarFind=ivector(1,NCOVMAX); /* */
12755: TvarV=ivector(1,NCOVMAX); /* */
12756: TvarVind=ivector(1,NCOVMAX); /* */
12757: TvarA=ivector(1,NCOVMAX); /* */
12758: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 12759: TvarFD=ivector(1,NCOVMAX); /* */
12760: TvarFDind=ivector(1,NCOVMAX); /* */
12761: TvarFQ=ivector(1,NCOVMAX); /* */
12762: TvarFQind=ivector(1,NCOVMAX); /* */
12763: TvarVD=ivector(1,NCOVMAX); /* */
12764: TvarVDind=ivector(1,NCOVMAX); /* */
12765: TvarVQ=ivector(1,NCOVMAX); /* */
12766: TvarVQind=ivector(1,NCOVMAX); /* */
1.339 ! brouard 12767: TvarVV=ivector(1,NCOVMAX); /* */
! 12768: TvarVVind=ivector(1,NCOVMAX); /* */
1.231 brouard 12769:
1.230 brouard 12770: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 12771: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 12772: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
12773: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
12774: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.137 brouard 12775: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
12776: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
12777: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
12778: */
12779: /* For model-covariate k tells which data-covariate to use but
12780: because this model-covariate is a construction we invent a new column
12781: ncovcol + k1
12782: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
12783: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 12784: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
12785: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 12786: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
12787: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 12788: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 12789: */
1.145 brouard 12790: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
12791: 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 12792: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
12793: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.330 brouard 12794: Tvardk=imatrix(1,NCOVMAX,1,2);
1.145 brouard 12795: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 12796: 4 covariates (3 plus signs)
12797: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
1.328 brouard 12798: */
12799: for(i=1;i<NCOVMAX;i++)
12800: Tage[i]=0;
1.230 brouard 12801: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 12802: * individual dummy, fixed or varying:
12803: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
12804: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 12805: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
12806: * V1 df, V2 qf, V3 & V4 dv, V5 qv
12807: * Tmodelind[1]@9={9,0,3,2,}*/
12808: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
12809: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 12810: * individual quantitative, fixed or varying:
12811: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
12812: * 3, 1, 0, 0, 0, 0, 0, 0},
12813: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 12814: /* Main decodemodel */
12815:
1.187 brouard 12816:
1.223 brouard 12817: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 12818: goto end;
12819:
1.137 brouard 12820: if((double)(lastobs-imx)/(double)imx > 1.10){
12821: nbwarn++;
12822: 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);
12823: 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);
12824: }
1.136 brouard 12825: /* if(mle==1){*/
1.137 brouard 12826: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
12827: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 12828: }
12829:
12830: /*-calculation of age at interview from date of interview and age at death -*/
12831: agev=matrix(1,maxwav,1,imx);
12832:
12833: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
12834: goto end;
12835:
1.126 brouard 12836:
1.136 brouard 12837: agegomp=(int)agemin;
1.290 brouard 12838: free_vector(moisnais,firstobs,lastobs);
12839: free_vector(annais,firstobs,lastobs);
1.126 brouard 12840: /* free_matrix(mint,1,maxwav,1,n);
12841: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 12842: /* free_vector(moisdc,1,n); */
12843: /* free_vector(andc,1,n); */
1.145 brouard 12844: /* */
12845:
1.126 brouard 12846: wav=ivector(1,imx);
1.214 brouard 12847: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
12848: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
12849: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
12850: 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.*/
12851: bh=imatrix(1,lastpass-firstpass+2,1,imx);
12852: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 12853:
12854: /* Concatenates waves */
1.214 brouard 12855: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
12856: Death is a valid wave (if date is known).
12857: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
12858: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
12859: and mw[mi+1][i]. dh depends on stepm.
12860: */
12861:
1.126 brouard 12862: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 12863: /* Concatenates waves */
1.145 brouard 12864:
1.290 brouard 12865: free_vector(moisdc,firstobs,lastobs);
12866: free_vector(andc,firstobs,lastobs);
1.215 brouard 12867:
1.126 brouard 12868: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
12869: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
12870: ncodemax[1]=1;
1.145 brouard 12871: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 12872: cptcoveff=0;
1.220 brouard 12873: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
1.335 brouard 12874: tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; as well as calculate cptcoveff or number of total effective dummy covariates*/
1.227 brouard 12875: }
12876:
12877: ncovcombmax=pow(2,cptcoveff);
1.338 brouard 12878: invalidvarcomb=ivector(0, ncovcombmax);
12879: for(i=0;i<ncovcombmax;i++)
1.227 brouard 12880: invalidvarcomb[i]=0;
12881:
1.211 brouard 12882: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 12883: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 12884: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 12885:
1.200 brouard 12886: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 12887: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 12888: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 12889: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
12890: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
12891: * (currently 0 or 1) in the data.
12892: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
12893: * corresponding modality (h,j).
12894: */
12895:
1.145 brouard 12896: h=0;
12897: /*if (cptcovn > 0) */
1.126 brouard 12898: m=pow(2,cptcoveff);
12899:
1.144 brouard 12900: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 12901: * For k=4 covariates, h goes from 1 to m=2**k
12902: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
12903: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.329 brouard 12904: * h\k 1 2 3 4 * h-1\k-1 4 3 2 1
12905: *______________________________ *______________________
12906: * 1 i=1 1 i=1 1 i=1 1 i=1 1 * 0 0 0 0 0
12907: * 2 2 1 1 1 * 1 0 0 0 1
12908: * 3 i=2 1 2 1 1 * 2 0 0 1 0
12909: * 4 2 2 1 1 * 3 0 0 1 1
12910: * 5 i=3 1 i=2 1 2 1 * 4 0 1 0 0
12911: * 6 2 1 2 1 * 5 0 1 0 1
12912: * 7 i=4 1 2 2 1 * 6 0 1 1 0
12913: * 8 2 2 2 1 * 7 0 1 1 1
12914: * 9 i=5 1 i=3 1 i=2 1 2 * 8 1 0 0 0
12915: * 10 2 1 1 2 * 9 1 0 0 1
12916: * 11 i=6 1 2 1 2 * 10 1 0 1 0
12917: * 12 2 2 1 2 * 11 1 0 1 1
12918: * 13 i=7 1 i=4 1 2 2 * 12 1 1 0 0
12919: * 14 2 1 2 2 * 13 1 1 0 1
12920: * 15 i=8 1 2 2 2 * 14 1 1 1 0
12921: * 16 2 2 2 2 * 15 1 1 1 1
12922: */
1.212 brouard 12923: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 12924: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
12925: * and the value of each covariate?
12926: * V1=1, V2=1, V3=2, V4=1 ?
12927: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
12928: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
12929: * In order to get the real value in the data, we use nbcode
12930: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
12931: * We are keeping this crazy system in order to be able (in the future?)
12932: * to have more than 2 values (0 or 1) for a covariate.
12933: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
12934: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
12935: * bbbbbbbb
12936: * 76543210
12937: * h-1 00000101 (6-1=5)
1.219 brouard 12938: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 12939: * &
12940: * 1 00000001 (1)
1.219 brouard 12941: * 00000000 = 1 & ((h-1) >> (k-1))
12942: * +1= 00000001 =1
1.211 brouard 12943: *
12944: * h=14, k=3 => h'=h-1=13, k'=k-1=2
12945: * h' 1101 =2^3+2^2+0x2^1+2^0
12946: * >>k' 11
12947: * & 00000001
12948: * = 00000001
12949: * +1 = 00000010=2 = codtabm(14,3)
12950: * Reverse h=6 and m=16?
12951: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
12952: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
12953: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
12954: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
12955: * V3=decodtabm(14,3,2**4)=2
12956: * h'=13 1101 =2^3+2^2+0x2^1+2^0
12957: *(h-1) >> (j-1) 0011 =13 >> 2
12958: * &1 000000001
12959: * = 000000001
12960: * +1= 000000010 =2
12961: * 2211
12962: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
12963: * V3=2
1.220 brouard 12964: * codtabm and decodtabm are identical
1.211 brouard 12965: */
12966:
1.145 brouard 12967:
12968: free_ivector(Ndum,-1,NCOVMAX);
12969:
12970:
1.126 brouard 12971:
1.186 brouard 12972: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 12973: strcpy(optionfilegnuplot,optionfilefiname);
12974: if(mle==-3)
1.201 brouard 12975: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 12976: strcat(optionfilegnuplot,".gp");
12977:
12978: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
12979: printf("Problem with file %s",optionfilegnuplot);
12980: }
12981: else{
1.204 brouard 12982: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 12983: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 12984: //fprintf(ficgp,"set missing 'NaNq'\n");
12985: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 12986: }
12987: /* fclose(ficgp);*/
1.186 brouard 12988:
12989:
12990: /* Initialisation of --------- index.htm --------*/
1.126 brouard 12991:
12992: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
12993: if(mle==-3)
1.201 brouard 12994: strcat(optionfilehtm,"-MORT_");
1.126 brouard 12995: strcat(optionfilehtm,".htm");
12996: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 12997: printf("Problem with %s \n",optionfilehtm);
12998: exit(0);
1.126 brouard 12999: }
13000:
13001: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
13002: strcat(optionfilehtmcov,"-cov.htm");
13003: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
13004: printf("Problem with %s \n",optionfilehtmcov), exit(0);
13005: }
13006: else{
13007: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
13008: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 13009: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 13010: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
13011: }
13012:
1.335 brouard 13013: fprintf(fichtm,"<html><head>\n<meta charset=\"utf-8\"/><meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n\
13014: <title>IMaCh %s</title></head>\n\
13015: <body><font size=\"7\"><a href=http:/euroreves.ined.fr/imach>IMaCh for Interpolated Markov Chain</a> </font><br>\n\
13016: <font size=\"3\">Sponsored by Copyright (C) 2002-2015 <a href=http://www.ined.fr>INED</a>\
13017: -EUROREVES-Institut de longévité-2013-2022-Japan Society for the Promotion of Sciences 日本学術振興会 \
13018: (<a href=https://www.jsps.go.jp/english/e-grants/>Grant-in-Aid for Scientific Research 25293121</a>) - \
13019: <a href=https://software.intel.com/en-us>Intel Software 2015-2018</a></font><br> \n", optionfilehtm);
13020:
13021: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 13022: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 13023: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.337 brouard 13024: This file: <a href=\"%s\">%s</a></br>Title=%s <br>Datafile=<a href=\"%s\">%s</a> Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\
1.126 brouard 13025: \n\
13026: <hr size=\"2\" color=\"#EC5E5E\">\
13027: <ul><li><h4>Parameter files</h4>\n\
13028: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
13029: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
13030: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
13031: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
13032: - Date and time at start: %s</ul>\n",\
1.335 brouard 13033: version,fullversion,optionfilehtm,optionfilehtm,title,datafile,datafile,firstpass,lastpass,stepm, weightopt, model, \
1.126 brouard 13034: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
13035: fileres,fileres,\
13036: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
13037: fflush(fichtm);
13038:
13039: strcpy(pathr,path);
13040: strcat(pathr,optionfilefiname);
1.184 brouard 13041: #ifdef WIN32
13042: _chdir(optionfilefiname); /* Move to directory named optionfile */
13043: #else
1.126 brouard 13044: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 13045: #endif
13046:
1.126 brouard 13047:
1.220 brouard 13048: /* Calculates basic frequencies. Computes observed prevalence at single age
13049: and for any valid combination of covariates
1.126 brouard 13050: and prints on file fileres'p'. */
1.251 brouard 13051: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 13052: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 13053:
13054: fprintf(fichtm,"\n");
1.286 brouard 13055: 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 13056: ftol, stepm);
13057: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
13058: ncurrv=1;
13059: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
13060: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
13061: ncurrv=i;
13062: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 13063: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 13064: ncurrv=i;
13065: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 13066: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 13067: ncurrv=i;
13068: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
13069: 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", \
13070: nlstate, ndeath, maxwav, mle, weightopt);
13071:
13072: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
13073: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
13074:
13075:
1.317 brouard 13076: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Number of (used) observations=%d <br>\n\
1.126 brouard 13077: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
13078: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 13079: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 13080: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 13081: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
13082: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
13083: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
13084: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 13085:
1.126 brouard 13086: /* For Powell, parameters are in a vector p[] starting at p[1]
13087: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
13088: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
13089:
13090: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 13091: /* For mortality only */
1.126 brouard 13092: if (mle==-3){
1.136 brouard 13093: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 13094: for(i=1;i<=NDIM;i++)
13095: for(j=1;j<=NDIM;j++)
13096: ximort[i][j]=0.;
1.186 brouard 13097: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 13098: cens=ivector(firstobs,lastobs);
13099: ageexmed=vector(firstobs,lastobs);
13100: agecens=vector(firstobs,lastobs);
13101: dcwave=ivector(firstobs,lastobs);
1.223 brouard 13102:
1.126 brouard 13103: for (i=1; i<=imx; i++){
13104: dcwave[i]=-1;
13105: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 13106: if (s[m][i]>nlstate) {
13107: dcwave[i]=m;
13108: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
13109: break;
13110: }
1.126 brouard 13111: }
1.226 brouard 13112:
1.126 brouard 13113: for (i=1; i<=imx; i++) {
13114: if (wav[i]>0){
1.226 brouard 13115: ageexmed[i]=agev[mw[1][i]][i];
13116: j=wav[i];
13117: agecens[i]=1.;
13118:
13119: if (ageexmed[i]> 1 && wav[i] > 0){
13120: agecens[i]=agev[mw[j][i]][i];
13121: cens[i]= 1;
13122: }else if (ageexmed[i]< 1)
13123: cens[i]= -1;
13124: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
13125: cens[i]=0 ;
1.126 brouard 13126: }
13127: else cens[i]=-1;
13128: }
13129:
13130: for (i=1;i<=NDIM;i++) {
13131: for (j=1;j<=NDIM;j++)
1.226 brouard 13132: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 13133: }
13134:
1.302 brouard 13135: p[1]=0.0268; p[NDIM]=0.083;
13136: /* printf("%lf %lf", p[1], p[2]); */
1.126 brouard 13137:
13138:
1.136 brouard 13139: #ifdef GSL
13140: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 13141: #else
1.126 brouard 13142: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 13143: #endif
1.201 brouard 13144: strcpy(filerespow,"POW-MORT_");
13145: strcat(filerespow,fileresu);
1.126 brouard 13146: if((ficrespow=fopen(filerespow,"w"))==NULL) {
13147: printf("Problem with resultfile: %s\n", filerespow);
13148: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
13149: }
1.136 brouard 13150: #ifdef GSL
13151: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 13152: #else
1.126 brouard 13153: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 13154: #endif
1.126 brouard 13155: /* for (i=1;i<=nlstate;i++)
13156: for(j=1;j<=nlstate+ndeath;j++)
13157: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
13158: */
13159: fprintf(ficrespow,"\n");
1.136 brouard 13160: #ifdef GSL
13161: /* gsl starts here */
13162: T = gsl_multimin_fminimizer_nmsimplex;
13163: gsl_multimin_fminimizer *sfm = NULL;
13164: gsl_vector *ss, *x;
13165: gsl_multimin_function minex_func;
13166:
13167: /* Initial vertex size vector */
13168: ss = gsl_vector_alloc (NDIM);
13169:
13170: if (ss == NULL){
13171: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
13172: }
13173: /* Set all step sizes to 1 */
13174: gsl_vector_set_all (ss, 0.001);
13175:
13176: /* Starting point */
1.126 brouard 13177:
1.136 brouard 13178: x = gsl_vector_alloc (NDIM);
13179:
13180: if (x == NULL){
13181: gsl_vector_free(ss);
13182: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
13183: }
13184:
13185: /* Initialize method and iterate */
13186: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 13187: /* gsl_vector_set(x, 0, 0.0268); */
13188: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 13189: gsl_vector_set(x, 0, p[1]);
13190: gsl_vector_set(x, 1, p[2]);
13191:
13192: minex_func.f = &gompertz_f;
13193: minex_func.n = NDIM;
13194: minex_func.params = (void *)&p; /* ??? */
13195:
13196: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
13197: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
13198:
13199: printf("Iterations beginning .....\n\n");
13200: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
13201:
13202: iteri=0;
13203: while (rval == GSL_CONTINUE){
13204: iteri++;
13205: status = gsl_multimin_fminimizer_iterate(sfm);
13206:
13207: if (status) printf("error: %s\n", gsl_strerror (status));
13208: fflush(0);
13209:
13210: if (status)
13211: break;
13212:
13213: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
13214: ssval = gsl_multimin_fminimizer_size (sfm);
13215:
13216: if (rval == GSL_SUCCESS)
13217: printf ("converged to a local maximum at\n");
13218:
13219: printf("%5d ", iteri);
13220: for (it = 0; it < NDIM; it++){
13221: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
13222: }
13223: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
13224: }
13225:
13226: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
13227:
13228: gsl_vector_free(x); /* initial values */
13229: gsl_vector_free(ss); /* inital step size */
13230: for (it=0; it<NDIM; it++){
13231: p[it+1]=gsl_vector_get(sfm->x,it);
13232: fprintf(ficrespow," %.12lf", p[it]);
13233: }
13234: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
13235: #endif
13236: #ifdef POWELL
13237: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
13238: #endif
1.126 brouard 13239: fclose(ficrespow);
13240:
1.203 brouard 13241: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 13242:
13243: for(i=1; i <=NDIM; i++)
13244: for(j=i+1;j<=NDIM;j++)
1.220 brouard 13245: matcov[i][j]=matcov[j][i];
1.126 brouard 13246:
13247: printf("\nCovariance matrix\n ");
1.203 brouard 13248: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 13249: for(i=1; i <=NDIM; i++) {
13250: for(j=1;j<=NDIM;j++){
1.220 brouard 13251: printf("%f ",matcov[i][j]);
13252: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 13253: }
1.203 brouard 13254: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 13255: }
13256:
13257: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 13258: for (i=1;i<=NDIM;i++) {
1.126 brouard 13259: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 13260: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
13261: }
1.302 brouard 13262: lsurv=vector(agegomp,AGESUP);
13263: lpop=vector(agegomp,AGESUP);
13264: tpop=vector(agegomp,AGESUP);
1.126 brouard 13265: lsurv[agegomp]=100000;
13266:
13267: for (k=agegomp;k<=AGESUP;k++) {
13268: agemortsup=k;
13269: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
13270: }
13271:
13272: for (k=agegomp;k<agemortsup;k++)
13273: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
13274:
13275: for (k=agegomp;k<agemortsup;k++){
13276: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
13277: sumlpop=sumlpop+lpop[k];
13278: }
13279:
13280: tpop[agegomp]=sumlpop;
13281: for (k=agegomp;k<(agemortsup-3);k++){
13282: /* tpop[k+1]=2;*/
13283: tpop[k+1]=tpop[k]-lpop[k];
13284: }
13285:
13286:
13287: printf("\nAge lx qx dx Lx Tx e(x)\n");
13288: for (k=agegomp;k<(agemortsup-2);k++)
13289: 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]);
13290:
13291:
13292: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 13293: ageminpar=50;
13294: agemaxpar=100;
1.194 brouard 13295: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
13296: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
13297: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
13298: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
13299: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
13300: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
13301: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 13302: }else{
13303: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
13304: 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 13305: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 13306: }
1.201 brouard 13307: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 13308: stepm, weightopt,\
13309: model,imx,p,matcov,agemortsup);
13310:
1.302 brouard 13311: free_vector(lsurv,agegomp,AGESUP);
13312: free_vector(lpop,agegomp,AGESUP);
13313: free_vector(tpop,agegomp,AGESUP);
1.220 brouard 13314: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 13315: free_ivector(dcwave,firstobs,lastobs);
13316: free_vector(agecens,firstobs,lastobs);
13317: free_vector(ageexmed,firstobs,lastobs);
13318: free_ivector(cens,firstobs,lastobs);
1.220 brouard 13319: #ifdef GSL
1.136 brouard 13320: #endif
1.186 brouard 13321: } /* Endof if mle==-3 mortality only */
1.205 brouard 13322: /* Standard */
13323: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
13324: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
13325: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 13326: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 13327: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
13328: for (k=1; k<=npar;k++)
13329: printf(" %d %8.5f",k,p[k]);
13330: printf("\n");
1.205 brouard 13331: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
13332: /* mlikeli uses func not funcone */
1.247 brouard 13333: /* for(i=1;i<nlstate;i++){ */
13334: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
13335: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
13336: /* } */
1.205 brouard 13337: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
13338: }
13339: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
13340: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
13341: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
13342: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
13343: }
13344: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 13345: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
13346: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
1.335 brouard 13347: /* exit(0); */
1.126 brouard 13348: for (k=1; k<=npar;k++)
13349: printf(" %d %8.5f",k,p[k]);
13350: printf("\n");
13351:
13352: /*--------- results files --------------*/
1.283 brouard 13353: /* 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 13354:
13355:
13356: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 13357: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); /* Printing model equation */
1.126 brouard 13358: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 13359:
13360: printf("#model= 1 + age ");
13361: fprintf(ficres,"#model= 1 + age ");
13362: fprintf(ficlog,"#model= 1 + age ");
13363: fprintf(fichtm,"\n<ul><li> model=1+age+%s\n \
13364: </ul>", model);
13365:
13366: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">\n");
13367: fprintf(fichtm, "<tr><th>Model=</th><th>1</th><th>+ age</th>");
13368: if(nagesqr==1){
13369: printf(" + age*age ");
13370: fprintf(ficres," + age*age ");
13371: fprintf(ficlog," + age*age ");
13372: fprintf(fichtm, "<th>+ age*age</th>");
13373: }
13374: for(j=1;j <=ncovmodel-2;j++){
13375: if(Typevar[j]==0) {
13376: printf(" + V%d ",Tvar[j]);
13377: fprintf(ficres," + V%d ",Tvar[j]);
13378: fprintf(ficlog," + V%d ",Tvar[j]);
13379: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
13380: }else if(Typevar[j]==1) {
13381: printf(" + V%d*age ",Tvar[j]);
13382: fprintf(ficres," + V%d*age ",Tvar[j]);
13383: fprintf(ficlog," + V%d*age ",Tvar[j]);
13384: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
13385: }else if(Typevar[j]==2) {
13386: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13387: fprintf(ficres," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13388: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13389: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13390: }
13391: }
13392: printf("\n");
13393: fprintf(ficres,"\n");
13394: fprintf(ficlog,"\n");
13395: fprintf(fichtm, "</tr>");
13396: fprintf(fichtm, "\n");
13397:
13398:
1.126 brouard 13399: for(i=1,jk=1; i <=nlstate; i++){
13400: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 13401: if (k != i) {
1.319 brouard 13402: fprintf(fichtm, "<tr>");
1.225 brouard 13403: printf("%d%d ",i,k);
13404: fprintf(ficlog,"%d%d ",i,k);
13405: fprintf(ficres,"%1d%1d ",i,k);
1.319 brouard 13406: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 13407: for(j=1; j <=ncovmodel; j++){
13408: printf("%12.7f ",p[jk]);
13409: fprintf(ficlog,"%12.7f ",p[jk]);
13410: fprintf(ficres,"%12.7f ",p[jk]);
1.319 brouard 13411: fprintf(fichtm, "<td>%12.7f</td>",p[jk]);
1.225 brouard 13412: jk++;
13413: }
13414: printf("\n");
13415: fprintf(ficlog,"\n");
13416: fprintf(ficres,"\n");
1.319 brouard 13417: fprintf(fichtm, "</tr>\n");
1.225 brouard 13418: }
1.126 brouard 13419: }
13420: }
1.319 brouard 13421: /* fprintf(fichtm,"</tr>\n"); */
13422: fprintf(fichtm,"</table>\n");
13423: fprintf(fichtm, "\n");
13424:
1.203 brouard 13425: if(mle != 0){
13426: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 13427: ftolhess=ftol; /* Usually correct */
1.203 brouard 13428: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
13429: 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");
13430: 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 13431: 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 13432: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">");
13433: fprintf(fichtm, "\n<tr><th>Model=</th><th>1</th><th>+ age</th>");
13434: if(nagesqr==1){
13435: printf(" + age*age ");
13436: fprintf(ficres," + age*age ");
13437: fprintf(ficlog," + age*age ");
13438: fprintf(fichtm, "<th>+ age*age</th>");
13439: }
13440: for(j=1;j <=ncovmodel-2;j++){
13441: if(Typevar[j]==0) {
13442: printf(" + V%d ",Tvar[j]);
13443: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
13444: }else if(Typevar[j]==1) {
13445: printf(" + V%d*age ",Tvar[j]);
13446: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
13447: }else if(Typevar[j]==2) {
13448: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13449: }
13450: }
13451: fprintf(fichtm, "</tr>\n");
13452:
1.203 brouard 13453: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 13454: for(k=1; k <=(nlstate+ndeath); k++){
13455: if (k != i) {
1.319 brouard 13456: fprintf(fichtm, "<tr valign=top>");
1.225 brouard 13457: printf("%d%d ",i,k);
13458: fprintf(ficlog,"%d%d ",i,k);
1.319 brouard 13459: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 13460: for(j=1; j <=ncovmodel; j++){
1.319 brouard 13461: wald=p[jk]/sqrt(matcov[jk][jk]);
1.324 brouard 13462: 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]));
13463: 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 13464: if(fabs(wald) > 1.96){
1.321 brouard 13465: fprintf(fichtm, "<td><b>%12.7f</b></br> (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
1.319 brouard 13466: }else{
13467: fprintf(fichtm, "<td>%12.7f (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
13468: }
1.324 brouard 13469: fprintf(fichtm,"W=%8.3f</br>",wald);
1.319 brouard 13470: 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 13471: jk++;
13472: }
13473: printf("\n");
13474: fprintf(ficlog,"\n");
1.319 brouard 13475: fprintf(fichtm, "</tr>\n");
1.225 brouard 13476: }
13477: }
1.193 brouard 13478: }
1.203 brouard 13479: } /* end of hesscov and Wald tests */
1.319 brouard 13480: fprintf(fichtm,"</table>\n");
1.225 brouard 13481:
1.203 brouard 13482: /* */
1.126 brouard 13483: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
13484: printf("# Scales (for hessian or gradient estimation)\n");
13485: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
13486: for(i=1,jk=1; i <=nlstate; i++){
13487: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 13488: if (j!=i) {
13489: fprintf(ficres,"%1d%1d",i,j);
13490: printf("%1d%1d",i,j);
13491: fprintf(ficlog,"%1d%1d",i,j);
13492: for(k=1; k<=ncovmodel;k++){
13493: printf(" %.5e",delti[jk]);
13494: fprintf(ficlog," %.5e",delti[jk]);
13495: fprintf(ficres," %.5e",delti[jk]);
13496: jk++;
13497: }
13498: printf("\n");
13499: fprintf(ficlog,"\n");
13500: fprintf(ficres,"\n");
13501: }
1.126 brouard 13502: }
13503: }
13504:
13505: 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 13506: if(mle >= 1) /* To big for the screen */
1.126 brouard 13507: 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");
13508: 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");
13509: /* # 121 Var(a12)\n\ */
13510: /* # 122 Cov(b12,a12) Var(b12)\n\ */
13511: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
13512: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
13513: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
13514: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
13515: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
13516: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
13517:
13518:
13519: /* Just to have a covariance matrix which will be more understandable
13520: even is we still don't want to manage dictionary of variables
13521: */
13522: for(itimes=1;itimes<=2;itimes++){
13523: jj=0;
13524: for(i=1; i <=nlstate; i++){
1.225 brouard 13525: for(j=1; j <=nlstate+ndeath; j++){
13526: if(j==i) continue;
13527: for(k=1; k<=ncovmodel;k++){
13528: jj++;
13529: ca[0]= k+'a'-1;ca[1]='\0';
13530: if(itimes==1){
13531: if(mle>=1)
13532: printf("#%1d%1d%d",i,j,k);
13533: fprintf(ficlog,"#%1d%1d%d",i,j,k);
13534: fprintf(ficres,"#%1d%1d%d",i,j,k);
13535: }else{
13536: if(mle>=1)
13537: printf("%1d%1d%d",i,j,k);
13538: fprintf(ficlog,"%1d%1d%d",i,j,k);
13539: fprintf(ficres,"%1d%1d%d",i,j,k);
13540: }
13541: ll=0;
13542: for(li=1;li <=nlstate; li++){
13543: for(lj=1;lj <=nlstate+ndeath; lj++){
13544: if(lj==li) continue;
13545: for(lk=1;lk<=ncovmodel;lk++){
13546: ll++;
13547: if(ll<=jj){
13548: cb[0]= lk +'a'-1;cb[1]='\0';
13549: if(ll<jj){
13550: if(itimes==1){
13551: if(mle>=1)
13552: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
13553: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
13554: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
13555: }else{
13556: if(mle>=1)
13557: printf(" %.5e",matcov[jj][ll]);
13558: fprintf(ficlog," %.5e",matcov[jj][ll]);
13559: fprintf(ficres," %.5e",matcov[jj][ll]);
13560: }
13561: }else{
13562: if(itimes==1){
13563: if(mle>=1)
13564: printf(" Var(%s%1d%1d)",ca,i,j);
13565: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
13566: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
13567: }else{
13568: if(mle>=1)
13569: printf(" %.7e",matcov[jj][ll]);
13570: fprintf(ficlog," %.7e",matcov[jj][ll]);
13571: fprintf(ficres," %.7e",matcov[jj][ll]);
13572: }
13573: }
13574: }
13575: } /* end lk */
13576: } /* end lj */
13577: } /* end li */
13578: if(mle>=1)
13579: printf("\n");
13580: fprintf(ficlog,"\n");
13581: fprintf(ficres,"\n");
13582: numlinepar++;
13583: } /* end k*/
13584: } /*end j */
1.126 brouard 13585: } /* end i */
13586: } /* end itimes */
13587:
13588: fflush(ficlog);
13589: fflush(ficres);
1.225 brouard 13590: while(fgets(line, MAXLINE, ficpar)) {
13591: /* If line starts with a # it is a comment */
13592: if (line[0] == '#') {
13593: numlinepar++;
13594: fputs(line,stdout);
13595: fputs(line,ficparo);
13596: fputs(line,ficlog);
1.299 brouard 13597: fputs(line,ficres);
1.225 brouard 13598: continue;
13599: }else
13600: break;
13601: }
13602:
1.209 brouard 13603: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
13604: /* ungetc(c,ficpar); */
13605: /* fgets(line, MAXLINE, ficpar); */
13606: /* fputs(line,stdout); */
13607: /* fputs(line,ficparo); */
13608: /* } */
13609: /* ungetc(c,ficpar); */
1.126 brouard 13610:
13611: estepm=0;
1.209 brouard 13612: 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 13613:
13614: if (num_filled != 6) {
13615: 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);
13616: 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);
13617: goto end;
13618: }
13619: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
13620: }
13621: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
13622: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
13623:
1.209 brouard 13624: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 13625: if (estepm==0 || estepm < stepm) estepm=stepm;
13626: if (fage <= 2) {
13627: bage = ageminpar;
13628: fage = agemaxpar;
13629: }
13630:
13631: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 13632: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
13633: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 13634:
1.186 brouard 13635: /* Other stuffs, more or less useful */
1.254 brouard 13636: while(fgets(line, MAXLINE, ficpar)) {
13637: /* If line starts with a # it is a comment */
13638: if (line[0] == '#') {
13639: numlinepar++;
13640: fputs(line,stdout);
13641: fputs(line,ficparo);
13642: fputs(line,ficlog);
1.299 brouard 13643: fputs(line,ficres);
1.254 brouard 13644: continue;
13645: }else
13646: break;
13647: }
13648:
13649: 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){
13650:
13651: if (num_filled != 7) {
13652: 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);
13653: 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);
13654: goto end;
13655: }
13656: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
13657: 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);
13658: 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);
13659: 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 13660: }
1.254 brouard 13661:
13662: while(fgets(line, MAXLINE, ficpar)) {
13663: /* If line starts with a # it is a comment */
13664: if (line[0] == '#') {
13665: numlinepar++;
13666: fputs(line,stdout);
13667: fputs(line,ficparo);
13668: fputs(line,ficlog);
1.299 brouard 13669: fputs(line,ficres);
1.254 brouard 13670: continue;
13671: }else
13672: break;
1.126 brouard 13673: }
13674:
13675:
13676: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
13677: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
13678:
1.254 brouard 13679: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
13680: if (num_filled != 1) {
13681: 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);
13682: 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);
13683: goto end;
13684: }
13685: printf("pop_based=%d\n",popbased);
13686: fprintf(ficlog,"pop_based=%d\n",popbased);
13687: fprintf(ficparo,"pop_based=%d\n",popbased);
13688: fprintf(ficres,"pop_based=%d\n",popbased);
13689: }
13690:
1.258 brouard 13691: /* Results */
1.332 brouard 13692: /* Value of covariate in each resultine will be compututed (if product) and sorted according to model rank */
13693: /* It is precov[] because we need the varying age in order to compute the real cov[] of the model equation */
13694: precov=matrix(1,MAXRESULTLINESPONE,1,NCOVMAX+1);
1.307 brouard 13695: endishere=0;
1.258 brouard 13696: nresult=0;
1.308 brouard 13697: parameterline=0;
1.258 brouard 13698: do{
13699: if(!fgets(line, MAXLINE, ficpar)){
13700: endishere=1;
1.308 brouard 13701: parameterline=15;
1.258 brouard 13702: }else if (line[0] == '#') {
13703: /* If line starts with a # it is a comment */
1.254 brouard 13704: numlinepar++;
13705: fputs(line,stdout);
13706: fputs(line,ficparo);
13707: fputs(line,ficlog);
1.299 brouard 13708: fputs(line,ficres);
1.254 brouard 13709: continue;
1.258 brouard 13710: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
13711: parameterline=11;
1.296 brouard 13712: else if(sscanf(line,"prevbackcast=%[^\n]\n",modeltemp))
1.258 brouard 13713: parameterline=12;
1.307 brouard 13714: else if(sscanf(line,"result:%[^\n]\n",modeltemp)){
1.258 brouard 13715: parameterline=13;
1.307 brouard 13716: }
1.258 brouard 13717: else{
13718: parameterline=14;
1.254 brouard 13719: }
1.308 brouard 13720: switch (parameterline){ /* =0 only if only comments */
1.258 brouard 13721: case 11:
1.296 brouard 13722: 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)){
13723: 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 13724: 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);
13725: 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);
13726: 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);
13727: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 13728: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
13729: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
1.296 brouard 13730: prvforecast = 1;
13731: }
13732: else if((num_filled=sscanf(line,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",&prevfcast,&yrfproj,&mobilavproj)) !=EOF){/* && (num_filled == 3))*/
1.313 brouard 13733: printf("prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
13734: fprintf(ficlog,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
13735: fprintf(ficres,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
1.296 brouard 13736: prvforecast = 2;
13737: }
13738: else {
13739: 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);
13740: 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);
13741: goto end;
1.258 brouard 13742: }
1.254 brouard 13743: break;
1.258 brouard 13744: case 12:
1.296 brouard 13745: 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)){
13746: 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);
13747: 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);
13748: 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);
13749: 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);
13750: /* day and month of back2 are not used but only year anback2.*/
1.273 brouard 13751: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
13752: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.296 brouard 13753: prvbackcast = 1;
13754: }
13755: else if((num_filled=sscanf(line,"prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",&prevbcast,&yrbproj,&mobilavproj)) ==3){/* && (num_filled == 3))*/
1.313 brouard 13756: printf("prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
13757: fprintf(ficlog,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
13758: fprintf(ficres,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
1.296 brouard 13759: prvbackcast = 2;
13760: }
13761: else {
13762: 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);
13763: 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);
13764: goto end;
1.258 brouard 13765: }
1.230 brouard 13766: break;
1.258 brouard 13767: case 13:
1.332 brouard 13768: num_filled=sscanf(line,"result:%[^\n]\n",resultlineori);
1.307 brouard 13769: nresult++; /* Sum of resultlines */
1.332 brouard 13770: printf("Result %d: result:%s\n",nresult, resultlineori);
13771: /* removefirstspace(&resultlineori); */
13772:
13773: if(strstr(resultlineori,"v") !=0){
13774: printf("Error. 'v' must be in upper case 'V' result: %s ",resultlineori);
13775: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultlineori);fflush(ficlog);
13776: return 1;
13777: }
13778: trimbb(resultline, resultlineori); /* Suppressing double blank in the resultline */
13779: printf("Decoderesult resultline=\"%s\" resultlineori=\"%s\"\n", resultline, resultlineori);
1.318 brouard 13780: if(nresult > MAXRESULTLINESPONE-1){
13781: 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);
13782: 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 13783: goto end;
13784: }
1.332 brouard 13785:
1.310 brouard 13786: if(!decoderesult(resultline, nresult)){ /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
1.314 brouard 13787: fprintf(ficparo,"result: %s\n",resultline);
13788: fprintf(ficres,"result: %s\n",resultline);
13789: fprintf(ficlog,"result: %s\n",resultline);
1.310 brouard 13790: } else
13791: goto end;
1.307 brouard 13792: break;
13793: case 14:
13794: printf("Error: Unknown command '%s'\n",line);
13795: fprintf(ficlog,"Error: Unknown command '%s'\n",line);
1.314 brouard 13796: if(line[0] == ' ' || line[0] == '\n'){
13797: printf("It should not be an empty line '%s'\n",line);
13798: fprintf(ficlog,"It should not be an empty line '%s'\n",line);
13799: }
1.307 brouard 13800: if(ncovmodel >=2 && nresult==0 ){
13801: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
13802: fprintf(ficlog,"ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 13803: }
1.307 brouard 13804: /* goto end; */
13805: break;
1.308 brouard 13806: case 15:
13807: printf("End of resultlines.\n");
13808: fprintf(ficlog,"End of resultlines.\n");
13809: break;
13810: default: /* parameterline =0 */
1.307 brouard 13811: nresult=1;
13812: decoderesult(".",nresult ); /* No covariate */
1.258 brouard 13813: } /* End switch parameterline */
13814: }while(endishere==0); /* End do */
1.126 brouard 13815:
1.230 brouard 13816: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 13817: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 13818:
13819: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 13820: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 13821: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 13822: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
13823: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 13824: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 13825: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
13826: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 13827: }else{
1.270 brouard 13828: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
1.296 brouard 13829: /* It seems that anprojd which is computed from the mean year at interview which is known yet because of freqsummary */
13830: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */ /* Done in freqsummary */
13831: if(prvforecast==1){
13832: dateprojd=(jproj1+12*mproj1+365*anproj1)/365;
13833: jprojd=jproj1;
13834: mprojd=mproj1;
13835: anprojd=anproj1;
13836: dateprojf=(jproj2+12*mproj2+365*anproj2)/365;
13837: jprojf=jproj2;
13838: mprojf=mproj2;
13839: anprojf=anproj2;
13840: } else if(prvforecast == 2){
13841: dateprojd=dateintmean;
13842: date2dmy(dateprojd,&jprojd, &mprojd, &anprojd);
13843: dateprojf=dateintmean+yrfproj;
13844: date2dmy(dateprojf,&jprojf, &mprojf, &anprojf);
13845: }
13846: if(prvbackcast==1){
13847: datebackd=(jback1+12*mback1+365*anback1)/365;
13848: jbackd=jback1;
13849: mbackd=mback1;
13850: anbackd=anback1;
13851: datebackf=(jback2+12*mback2+365*anback2)/365;
13852: jbackf=jback2;
13853: mbackf=mback2;
13854: anbackf=anback2;
13855: } else if(prvbackcast == 2){
13856: datebackd=dateintmean;
13857: date2dmy(datebackd,&jbackd, &mbackd, &anbackd);
13858: datebackf=dateintmean-yrbproj;
13859: date2dmy(datebackf,&jbackf, &mbackf, &anbackf);
13860: }
13861:
13862: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage);
1.220 brouard 13863: }
13864: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.296 brouard 13865: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,prevbcast, estepm, \
13866: jprev1,mprev1,anprev1,dateprev1, dateprojd, datebackd,jprev2,mprev2,anprev2,dateprev2,dateprojf, datebackf);
1.220 brouard 13867:
1.225 brouard 13868: /*------------ free_vector -------------*/
13869: /* chdir(path); */
1.220 brouard 13870:
1.215 brouard 13871: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
13872: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
13873: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
13874: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 13875: free_lvector(num,firstobs,lastobs);
13876: free_vector(agedc,firstobs,lastobs);
1.126 brouard 13877: /*free_matrix(covar,0,NCOVMAX,1,n);*/
13878: /*free_matrix(covar,1,NCOVMAX,1,n);*/
13879: fclose(ficparo);
13880: fclose(ficres);
1.220 brouard 13881:
13882:
1.186 brouard 13883: /* Other results (useful)*/
1.220 brouard 13884:
13885:
1.126 brouard 13886: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 13887: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
13888: prlim=matrix(1,nlstate,1,nlstate);
1.332 brouard 13889: /* Computes the prevalence limit for each combination k of the dummy covariates by calling prevalim(k) */
1.209 brouard 13890: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 13891: fclose(ficrespl);
13892:
13893: /*------------- h Pij x at various ages ------------*/
1.180 brouard 13894: /*#include "hpijx.h"*/
1.332 brouard 13895: /** 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?*/
13896: /* calls hpxij with combination k */
1.180 brouard 13897: hPijx(p, bage, fage);
1.145 brouard 13898: fclose(ficrespij);
1.227 brouard 13899:
1.220 brouard 13900: /* ncovcombmax= pow(2,cptcoveff); */
1.332 brouard 13901: /*-------------- Variance of one-step probabilities for a combination ij or for nres ?---*/
1.145 brouard 13902: k=1;
1.126 brouard 13903: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 13904:
1.269 brouard 13905: /* Prevalence for each covariate combination in probs[age][status][cov] */
13906: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
13907: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 13908: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 13909: for(k=1;k<=ncovcombmax;k++)
13910: probs[i][j][k]=0.;
1.269 brouard 13911: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
13912: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 13913: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 13914: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
13915: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 13916: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 13917: for(k=1;k<=ncovcombmax;k++)
13918: mobaverages[i][j][k]=0.;
1.219 brouard 13919: mobaverage=mobaverages;
13920: if (mobilav!=0) {
1.235 brouard 13921: printf("Movingaveraging observed prevalence\n");
1.258 brouard 13922: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 13923: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
13924: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
13925: printf(" Error in movingaverage mobilav=%d\n",mobilav);
13926: }
1.269 brouard 13927: } else if (mobilavproj !=0) {
1.235 brouard 13928: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 13929: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 13930: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
13931: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
13932: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
13933: }
1.269 brouard 13934: }else{
13935: printf("Internal error moving average\n");
13936: fflush(stdout);
13937: exit(1);
1.219 brouard 13938: }
13939: }/* end if moving average */
1.227 brouard 13940:
1.126 brouard 13941: /*---------- Forecasting ------------------*/
1.296 brouard 13942: if(prevfcast==1){
13943: /* /\* if(stepm ==1){*\/ */
13944: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
13945: /*This done previously after freqsummary.*/
13946: /* dateprojd=(jproj1+12*mproj1+365*anproj1)/365; */
13947: /* dateprojf=(jproj2+12*mproj2+365*anproj2)/365; */
13948:
13949: /* } else if (prvforecast==2){ */
13950: /* /\* if(stepm ==1){*\/ */
13951: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
13952: /* } */
13953: /*prevforecast(fileresu, dateintmean, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);*/
13954: prevforecast(fileresu,dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, p, cptcoveff);
1.126 brouard 13955: }
1.269 brouard 13956:
1.296 brouard 13957: /* Prevbcasting */
13958: if(prevbcast==1){
1.219 brouard 13959: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
13960: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
13961: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
13962:
13963: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
13964:
13965: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 13966:
1.219 brouard 13967: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
13968: fclose(ficresplb);
13969:
1.222 brouard 13970: hBijx(p, bage, fage, mobaverage);
13971: fclose(ficrespijb);
1.219 brouard 13972:
1.296 brouard 13973: /* /\* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, *\/ */
13974: /* /\* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); *\/ */
13975: /* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, */
13976: /* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
13977: prevbackforecast(fileresu, mobaverage, dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2,
13978: mobilavproj, bage, fage, firstpass, lastpass, p, cptcoveff);
13979:
13980:
1.269 brouard 13981: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 13982:
13983:
1.269 brouard 13984: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 13985: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
13986: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
13987: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.296 brouard 13988: } /* end Prevbcasting */
1.268 brouard 13989:
1.186 brouard 13990:
13991: /* ------ Other prevalence ratios------------ */
1.126 brouard 13992:
1.215 brouard 13993: free_ivector(wav,1,imx);
13994: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
13995: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
13996: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 13997:
13998:
1.127 brouard 13999: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 14000:
1.201 brouard 14001: strcpy(filerese,"E_");
14002: strcat(filerese,fileresu);
1.126 brouard 14003: if((ficreseij=fopen(filerese,"w"))==NULL) {
14004: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
14005: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
14006: }
1.208 brouard 14007: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
14008: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 14009:
14010: pstamp(ficreseij);
1.219 brouard 14011:
1.235 brouard 14012: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
14013: if (cptcovn < 1){i1=1;}
14014:
14015: for(nres=1; nres <= nresult; nres++) /* For each resultline */
14016: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 14017: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 14018: continue;
1.219 brouard 14019: fprintf(ficreseij,"\n#****** ");
1.235 brouard 14020: printf("\n#****** ");
1.225 brouard 14021: for(j=1;j<=cptcoveff;j++) {
1.332 brouard 14022: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
14023: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.235 brouard 14024: }
14025: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.337 brouard 14026: printf(" V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]); /* TvarsQ[j] gives the name of the jth quantitative (fixed or time v) */
14027: fprintf(ficreseij,"V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]);
1.219 brouard 14028: }
14029: fprintf(ficreseij,"******\n");
1.235 brouard 14030: printf("******\n");
1.219 brouard 14031:
14032: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
14033: oldm=oldms;savm=savms;
1.330 brouard 14034: /* 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 14035: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 14036:
1.219 brouard 14037: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 14038: }
14039: fclose(ficreseij);
1.208 brouard 14040: printf("done evsij\n");fflush(stdout);
14041: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 14042:
1.218 brouard 14043:
1.227 brouard 14044: /*---------- State-specific expectancies and variances ------------*/
1.336 brouard 14045: /* Should be moved in a function */
1.201 brouard 14046: strcpy(filerest,"T_");
14047: strcat(filerest,fileresu);
1.127 brouard 14048: if((ficrest=fopen(filerest,"w"))==NULL) {
14049: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
14050: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
14051: }
1.208 brouard 14052: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
14053: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 14054: strcpy(fileresstde,"STDE_");
14055: strcat(fileresstde,fileresu);
1.126 brouard 14056: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 14057: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
14058: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 14059: }
1.227 brouard 14060: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
14061: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 14062:
1.201 brouard 14063: strcpy(filerescve,"CVE_");
14064: strcat(filerescve,fileresu);
1.126 brouard 14065: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 14066: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
14067: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 14068: }
1.227 brouard 14069: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
14070: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 14071:
1.201 brouard 14072: strcpy(fileresv,"V_");
14073: strcat(fileresv,fileresu);
1.126 brouard 14074: if((ficresvij=fopen(fileresv,"w"))==NULL) {
14075: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
14076: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
14077: }
1.227 brouard 14078: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
14079: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 14080:
1.235 brouard 14081: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
14082: if (cptcovn < 1){i1=1;}
14083:
1.334 brouard 14084: for(nres=1; nres <= nresult; nres++) /* For each resultline, find the combination and output results according to the values of dummies and then quanti. */
14085: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying. For each nres and each value at position k
14086: * we know Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline
14087: * Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline
14088: * and Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
14089: /* */
14090: 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 14091: continue;
1.321 brouard 14092: printf("\n# model %s \n#****** Result for:", model);
14093: fprintf(ficrest,"\n# model %s \n#****** Result for:", model);
14094: fprintf(ficlog,"\n# model %s \n#****** Result for:", model);
1.334 brouard 14095: /* It might not be a good idea to mix dummies and quantitative */
14096: /* 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 *\/ */
14097: 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 */
14098: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /\* Output by variables in the resultline *\/ */
14099: /* Tvaraff[j] is the name of the dummy variable in position j in the equation model:
14100: * Tvaraff[1]@9={4, 3, 0, 0, 0, 0, 0, 0, 0}, in model=V5+V4+V3+V4*V3+V5*age
14101: * (V5 is quanti) V4 and V3 are dummies
14102: * TnsdVar[4] is the position 1 and TnsdVar[3]=2 in codtabm(k,l)(V4 V3)=V4 V3
14103: * l=1 l=2
14104: * k=1 1 1 0 0
14105: * k=2 2 1 1 0
14106: * k=3 [1] [2] 0 1
14107: * k=4 2 2 1 1
14108: * If nres=1 result: V3=1 V4=0 then k=3 and outputs
14109: * If nres=2 result: V4=1 V3=0 then k=2 and outputs
14110: * nres=1 =>k=3 j=1 V4= nbcode[4][codtabm(3,1)=1)=0; j=2 V3= nbcode[3][codtabm(3,2)=2]=1
14111: * nres=2 =>k=2 j=1 V4= nbcode[4][codtabm(2,1)=2)=1; j=2 V3= nbcode[3][codtabm(2,2)=1]=0
14112: */
14113: /* Tvresult[nres][j] Name of the variable at position j in this resultline */
14114: /* Tresult[nres][j] Value of this variable at position j could be a float if quantitative */
14115: /* We give up with the combinations!! */
14116: 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 */
14117:
14118: if(Dummy[modelresult[nres][j]]==0){/* Dummy variable of the variable in position modelresult in the model corresponding to j in resultline */
1.337 brouard 14119: printf("V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][j]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
14120: fprintf(ficlog,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][j]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
14121: fprintf(ficrest,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][j]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
1.334 brouard 14122: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
14123: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
14124: }else{
14125: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
14126: }
14127: /* fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14128: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14129: }else if(Dummy[modelresult[nres][j]]==1){ /* Quanti variable */
14130: /* For each selected (single) quantitative value */
1.337 brouard 14131: printf(" V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
14132: fprintf(ficlog," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
14133: fprintf(ficrest," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
1.334 brouard 14134: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
14135: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
14136: }else{
14137: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
14138: }
14139: }else{
14140: 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 */
14141: 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 */
14142: exit(1);
14143: }
1.335 brouard 14144: } /* End loop for each variable in the resultline */
1.334 brouard 14145: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
14146: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /\* Wrong j is not in the equation model *\/ */
14147: /* fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
14148: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
14149: /* } */
1.208 brouard 14150: fprintf(ficrest,"******\n");
1.227 brouard 14151: fprintf(ficlog,"******\n");
14152: printf("******\n");
1.208 brouard 14153:
14154: fprintf(ficresstdeij,"\n#****** ");
14155: fprintf(ficrescveij,"\n#****** ");
1.337 brouard 14156: /* It could have been: for(j=1;j<=cptcoveff;j++) {printf("V=%d=%lg",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);} */
14157: /* But it won't be sorted and depends on how the resultline is ordered */
1.225 brouard 14158: for(j=1;j<=cptcoveff;j++) {
1.334 brouard 14159: fprintf(ficresstdeij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
14160: /* fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14161: /* fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14162: }
14163: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value, TvarsQind gives the position of a quantitative in model equation */
1.337 brouard 14164: fprintf(ficresstdeij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
14165: fprintf(ficrescveij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
1.235 brouard 14166: }
1.208 brouard 14167: fprintf(ficresstdeij,"******\n");
14168: fprintf(ficrescveij,"******\n");
14169:
14170: fprintf(ficresvij,"\n#****** ");
1.238 brouard 14171: /* pstamp(ficresvij); */
1.225 brouard 14172: for(j=1;j<=cptcoveff;j++)
1.335 brouard 14173: fprintf(ficresvij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
14174: /* fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[TnsdVar[Tvaraff[j]]])]); */
1.235 brouard 14175: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.332 brouard 14176: /* fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); /\* To solve *\/ */
1.337 brouard 14177: fprintf(ficresvij," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /* Solved */
1.235 brouard 14178: }
1.208 brouard 14179: fprintf(ficresvij,"******\n");
14180:
14181: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
14182: oldm=oldms;savm=savms;
1.235 brouard 14183: printf(" cvevsij ");
14184: fprintf(ficlog, " cvevsij ");
14185: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 14186: printf(" end cvevsij \n ");
14187: fprintf(ficlog, " end cvevsij \n ");
14188:
14189: /*
14190: */
14191: /* goto endfree; */
14192:
14193: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
14194: pstamp(ficrest);
14195:
1.269 brouard 14196: epj=vector(1,nlstate+1);
1.208 brouard 14197: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 14198: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
14199: cptcod= 0; /* To be deleted */
14200: printf("varevsij vpopbased=%d \n",vpopbased);
14201: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 14202: 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 14203: 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 ");
14204: if(vpopbased==1)
14205: 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);
14206: else
1.288 brouard 14207: fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n");
1.335 brouard 14208: fprintf(ficrest,"# Age popbased mobilav e.. (std) "); /* Adding covariate values? */
1.227 brouard 14209: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
14210: fprintf(ficrest,"\n");
14211: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 14212: printf("Computing age specific forward period (stable) prevalences in each health state \n");
14213: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 14214: for(age=bage; age <=fage ;age++){
1.235 brouard 14215: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 14216: if (vpopbased==1) {
14217: if(mobilav ==0){
14218: for(i=1; i<=nlstate;i++)
14219: prlim[i][i]=probs[(int)age][i][k];
14220: }else{ /* mobilav */
14221: for(i=1; i<=nlstate;i++)
14222: prlim[i][i]=mobaverage[(int)age][i][k];
14223: }
14224: }
1.219 brouard 14225:
1.227 brouard 14226: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
14227: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
14228: /* printf(" age %4.0f ",age); */
14229: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
14230: for(i=1, epj[j]=0.;i <=nlstate;i++) {
14231: epj[j] += prlim[i][i]*eij[i][j][(int)age];
14232: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
14233: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
14234: }
14235: epj[nlstate+1] +=epj[j];
14236: }
14237: /* printf(" age %4.0f \n",age); */
1.219 brouard 14238:
1.227 brouard 14239: for(i=1, vepp=0.;i <=nlstate;i++)
14240: for(j=1;j <=nlstate;j++)
14241: vepp += vareij[i][j][(int)age];
14242: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
14243: for(j=1;j <=nlstate;j++){
14244: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
14245: }
14246: fprintf(ficrest,"\n");
14247: }
1.208 brouard 14248: } /* End vpopbased */
1.269 brouard 14249: free_vector(epj,1,nlstate+1);
1.208 brouard 14250: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
14251: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 14252: printf("done selection\n");fflush(stdout);
14253: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 14254:
1.335 brouard 14255: } /* End k selection or end covariate selection for nres */
1.227 brouard 14256:
14257: printf("done State-specific expectancies\n");fflush(stdout);
14258: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
14259:
1.335 brouard 14260: /* variance-covariance of forward period prevalence */
1.269 brouard 14261: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 14262:
1.227 brouard 14263:
1.290 brouard 14264: free_vector(weight,firstobs,lastobs);
1.330 brouard 14265: free_imatrix(Tvardk,1,NCOVMAX,1,2);
1.227 brouard 14266: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 14267: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
14268: free_matrix(anint,1,maxwav,firstobs,lastobs);
14269: free_matrix(mint,1,maxwav,firstobs,lastobs);
14270: free_ivector(cod,firstobs,lastobs);
1.227 brouard 14271: free_ivector(tab,1,NCOVMAX);
14272: fclose(ficresstdeij);
14273: fclose(ficrescveij);
14274: fclose(ficresvij);
14275: fclose(ficrest);
14276: fclose(ficpar);
14277:
14278:
1.126 brouard 14279: /*---------- End : free ----------------*/
1.219 brouard 14280: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 14281: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
14282: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 14283: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
14284: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 14285: } /* mle==-3 arrives here for freeing */
1.227 brouard 14286: /* endfree:*/
14287: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
14288: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
14289: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.290 brouard 14290: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs);
14291: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
14292: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
14293: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 14294: free_matrix(matcov,1,npar,1,npar);
14295: free_matrix(hess,1,npar,1,npar);
14296: /*free_vector(delti,1,npar);*/
14297: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
14298: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 14299: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 14300: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
14301:
14302: free_ivector(ncodemax,1,NCOVMAX);
14303: free_ivector(ncodemaxwundef,1,NCOVMAX);
14304: free_ivector(Dummy,-1,NCOVMAX);
14305: free_ivector(Fixed,-1,NCOVMAX);
1.238 brouard 14306: free_ivector(DummyV,1,NCOVMAX);
14307: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 14308: free_ivector(Typevar,-1,NCOVMAX);
14309: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 14310: free_ivector(TvarsQ,1,NCOVMAX);
14311: free_ivector(TvarsQind,1,NCOVMAX);
14312: free_ivector(TvarsD,1,NCOVMAX);
1.330 brouard 14313: free_ivector(TnsdVar,1,NCOVMAX);
1.234 brouard 14314: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 14315: free_ivector(TvarFD,1,NCOVMAX);
14316: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 14317: free_ivector(TvarF,1,NCOVMAX);
14318: free_ivector(TvarFind,1,NCOVMAX);
14319: free_ivector(TvarV,1,NCOVMAX);
14320: free_ivector(TvarVind,1,NCOVMAX);
14321: free_ivector(TvarA,1,NCOVMAX);
14322: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 14323: free_ivector(TvarFQ,1,NCOVMAX);
14324: free_ivector(TvarFQind,1,NCOVMAX);
14325: free_ivector(TvarVD,1,NCOVMAX);
14326: free_ivector(TvarVDind,1,NCOVMAX);
14327: free_ivector(TvarVQ,1,NCOVMAX);
14328: free_ivector(TvarVQind,1,NCOVMAX);
1.339 ! brouard 14329: free_ivector(TvarVV,1,NCOVMAX);
! 14330: free_ivector(TvarVVind,1,NCOVMAX);
! 14331:
1.230 brouard 14332: free_ivector(Tvarsel,1,NCOVMAX);
14333: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 14334: free_ivector(Tposprod,1,NCOVMAX);
14335: free_ivector(Tprod,1,NCOVMAX);
14336: free_ivector(Tvaraff,1,NCOVMAX);
1.338 brouard 14337: free_ivector(invalidvarcomb,0,ncovcombmax);
1.227 brouard 14338: free_ivector(Tage,1,NCOVMAX);
14339: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 14340: free_ivector(TmodelInvind,1,NCOVMAX);
14341: free_ivector(TmodelInvQind,1,NCOVMAX);
1.332 brouard 14342:
14343: free_matrix(precov, 1,MAXRESULTLINESPONE,1,NCOVMAX+1); /* Could be elsewhere ?*/
14344:
1.227 brouard 14345: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
14346: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 14347: fflush(fichtm);
14348: fflush(ficgp);
14349:
1.227 brouard 14350:
1.126 brouard 14351: if((nberr >0) || (nbwarn>0)){
1.216 brouard 14352: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
14353: 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 14354: }else{
14355: printf("End of Imach\n");
14356: fprintf(ficlog,"End of Imach\n");
14357: }
14358: printf("See log file on %s\n",filelog);
14359: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 14360: /*(void) gettimeofday(&end_time,&tzp);*/
14361: rend_time = time(NULL);
14362: end_time = *localtime(&rend_time);
14363: /* tml = *localtime(&end_time.tm_sec); */
14364: strcpy(strtend,asctime(&end_time));
1.126 brouard 14365: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
14366: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 14367: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 14368:
1.157 brouard 14369: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
14370: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
14371: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 14372: /* printf("Total time was %d uSec.\n", total_usecs);*/
14373: /* if(fileappend(fichtm,optionfilehtm)){ */
14374: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
14375: fclose(fichtm);
14376: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
14377: fclose(fichtmcov);
14378: fclose(ficgp);
14379: fclose(ficlog);
14380: /*------ End -----------*/
1.227 brouard 14381:
1.281 brouard 14382:
14383: /* Executes gnuplot */
1.227 brouard 14384:
14385: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 14386: #ifdef WIN32
1.227 brouard 14387: if (_chdir(pathcd) != 0)
14388: printf("Can't move to directory %s!\n",path);
14389: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 14390: #else
1.227 brouard 14391: if(chdir(pathcd) != 0)
14392: printf("Can't move to directory %s!\n", path);
14393: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 14394: #endif
1.126 brouard 14395: printf("Current directory %s!\n",pathcd);
14396: /*strcat(plotcmd,CHARSEPARATOR);*/
14397: sprintf(plotcmd,"gnuplot");
1.157 brouard 14398: #ifdef _WIN32
1.126 brouard 14399: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
14400: #endif
14401: if(!stat(plotcmd,&info)){
1.158 brouard 14402: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 14403: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 14404: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 14405: }else
14406: strcpy(pplotcmd,plotcmd);
1.157 brouard 14407: #ifdef __unix
1.126 brouard 14408: strcpy(plotcmd,GNUPLOTPROGRAM);
14409: if(!stat(plotcmd,&info)){
1.158 brouard 14410: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 14411: }else
14412: strcpy(pplotcmd,plotcmd);
14413: #endif
14414: }else
14415: strcpy(pplotcmd,plotcmd);
14416:
14417: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 14418: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 brouard 14419: strcpy(pplotcmd,plotcmd);
1.227 brouard 14420:
1.126 brouard 14421: if((outcmd=system(plotcmd)) != 0){
1.292 brouard 14422: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 14423: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 14424: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 brouard 14425: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 14426: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 brouard 14427: strcpy(plotcmd,pplotcmd);
14428: }
1.126 brouard 14429: }
1.158 brouard 14430: printf(" Successful, please wait...");
1.126 brouard 14431: while (z[0] != 'q') {
14432: /* chdir(path); */
1.154 brouard 14433: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 14434: scanf("%s",z);
14435: /* if (z[0] == 'c') system("./imach"); */
14436: if (z[0] == 'e') {
1.158 brouard 14437: #ifdef __APPLE__
1.152 brouard 14438: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 14439: #elif __linux
14440: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 14441: #else
1.152 brouard 14442: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 14443: #endif
14444: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
14445: system(pplotcmd);
1.126 brouard 14446: }
14447: else if (z[0] == 'g') system(plotcmd);
14448: else if (z[0] == 'q') exit(0);
14449: }
1.227 brouard 14450: end:
1.126 brouard 14451: while (z[0] != 'q') {
1.195 brouard 14452: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 14453: scanf("%s",z);
14454: }
1.283 brouard 14455: printf("End\n");
1.282 brouard 14456: exit(0);
1.126 brouard 14457: }
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