Annotation of imach/src/imach.c, revision 1.345
1.345 ! brouard 1: /* $Id: imach.c,v 1.344 2022/09/14 19:33:30 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.345 ! brouard 4: Revision 1.344 2022/09/14 19:33:30 brouard
! 5: Summary: version 0.99r40
! 6:
! 7: * imach.c (Module): Fixing names of variables in T_ (thanks to Feinuo)
! 8:
1.344 brouard 9: Revision 1.343 2022/09/14 14:22:16 brouard
10: Summary: version 0.99r39
11:
12: * imach.c (Module): Version 0.99r39 with colored dummy covariates
13: (fixed or time varying), using new last columns of
14: ILK_parameter.txt file.
15:
1.343 brouard 16: Revision 1.342 2022/09/11 19:54:09 brouard
17: Summary: 0.99r38
18:
19: * imach.c (Module): Adding timevarying products of any kinds,
20: should work before shifting cotvar from ncovcol+nqv columns in
21: order to have a correspondance between the column of cotvar and
22: the id of column.
23: (Module): Some cleaning and adding covariates in ILK.txt
24:
1.342 brouard 25: Revision 1.341 2022/09/11 07:58:42 brouard
26: Summary: Version 0.99r38
27:
28: After adding change in cotvar.
29:
1.341 brouard 30: Revision 1.340 2022/09/11 07:53:11 brouard
31: Summary: Version imach 0.99r37
32:
33: * imach.c (Module): Adding timevarying products of any kinds,
34: should work before shifting cotvar from ncovcol+nqv columns in
35: order to have a correspondance between the column of cotvar and
36: the id of column.
37:
1.340 brouard 38: Revision 1.339 2022/09/09 17:55:22 brouard
39: Summary: version 0.99r37
40:
41: * imach.c (Module): Many improvements for fixing products of fixed
42: timevarying as well as fixed * fixed, and test with quantitative
43: covariate.
44:
1.339 brouard 45: Revision 1.338 2022/09/04 17:40:33 brouard
46: Summary: 0.99r36
47:
48: * imach.c (Module): Now the easy runs i.e. without result or
49: model=1+age only did not work. The defautl combination should be 1
50: and not 0 because everything hasn't been tranformed yet.
51:
1.338 brouard 52: Revision 1.337 2022/09/02 14:26:02 brouard
53: Summary: version 0.99r35
54:
55: * src/imach.c: Version 0.99r35 because it outputs same results with
56: 1+age+V1+V1*age for females and 1+age for females only
57: (education=1 noweight)
58:
1.337 brouard 59: Revision 1.336 2022/08/31 09:52:36 brouard
60: *** empty log message ***
61:
1.336 brouard 62: Revision 1.335 2022/08/31 08:23:16 brouard
63: Summary: improvements...
64:
1.335 brouard 65: Revision 1.334 2022/08/25 09:08:41 brouard
66: Summary: In progress for quantitative
67:
1.334 brouard 68: Revision 1.333 2022/08/21 09:10:30 brouard
69: * src/imach.c (Module): Version 0.99r33 A lot of changes in
70: reassigning covariates: my first idea was that people will always
71: use the first covariate V1 into the model but in fact they are
72: producing data with many covariates and can use an equation model
73: with some of the covariate; it means that in a model V2+V3 instead
74: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
75: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
76: the equation model is restricted to two variables only (V2, V3)
77: and the combination for V2 should be codtabm(k,1) instead of
78: (codtabm(k,2), and the code should be
79: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
80: made. All of these should be simplified once a day like we did in
81: hpxij() for example by using precov[nres] which is computed in
82: decoderesult for each nres of each resultline. Loop should be done
83: on the equation model globally by distinguishing only product with
84: age (which are changing with age) and no more on type of
85: covariates, single dummies, single covariates.
86:
1.333 brouard 87: Revision 1.332 2022/08/21 09:06:25 brouard
88: Summary: Version 0.99r33
89:
90: * src/imach.c (Module): Version 0.99r33 A lot of changes in
91: reassigning covariates: my first idea was that people will always
92: use the first covariate V1 into the model but in fact they are
93: producing data with many covariates and can use an equation model
94: with some of the covariate; it means that in a model V2+V3 instead
95: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
96: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
97: the equation model is restricted to two variables only (V2, V3)
98: and the combination for V2 should be codtabm(k,1) instead of
99: (codtabm(k,2), and the code should be
100: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
101: made. All of these should be simplified once a day like we did in
102: hpxij() for example by using precov[nres] which is computed in
103: decoderesult for each nres of each resultline. Loop should be done
104: on the equation model globally by distinguishing only product with
105: age (which are changing with age) and no more on type of
106: covariates, single dummies, single covariates.
107:
1.332 brouard 108: Revision 1.331 2022/08/07 05:40:09 brouard
109: *** empty log message ***
110:
1.331 brouard 111: Revision 1.330 2022/08/06 07:18:25 brouard
112: Summary: last 0.99r31
113:
114: * imach.c (Module): Version of imach using partly decoderesult to rebuild xpxij function
115:
1.330 brouard 116: Revision 1.329 2022/08/03 17:29:54 brouard
117: * imach.c (Module): Many errors in graphs fixed with Vn*age covariates.
118:
1.329 brouard 119: Revision 1.328 2022/07/27 17:40:48 brouard
120: Summary: valgrind bug fixed by initializing to zero DummyV as well as Tage
121:
1.328 brouard 122: Revision 1.327 2022/07/27 14:47:35 brouard
123: Summary: Still a problem for one-step probabilities in case of quantitative variables
124:
1.327 brouard 125: Revision 1.326 2022/07/26 17:33:55 brouard
126: Summary: some test with nres=1
127:
1.326 brouard 128: Revision 1.325 2022/07/25 14:27:23 brouard
129: Summary: r30
130:
131: * imach.c (Module): Error cptcovn instead of nsd in bmij (was
132: coredumped, revealed by Feiuno, thank you.
133:
1.325 brouard 134: Revision 1.324 2022/07/23 17:44:26 brouard
135: *** empty log message ***
136:
1.324 brouard 137: Revision 1.323 2022/07/22 12:30:08 brouard
138: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
139:
1.323 brouard 140: Revision 1.322 2022/07/22 12:27:48 brouard
141: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
142:
1.322 brouard 143: Revision 1.321 2022/07/22 12:04:24 brouard
144: Summary: r28
145:
146: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
147:
1.321 brouard 148: Revision 1.320 2022/06/02 05:10:11 brouard
149: *** empty log message ***
150:
1.320 brouard 151: Revision 1.319 2022/06/02 04:45:11 brouard
152: * imach.c (Module): Adding the Wald tests from the log to the main
153: htm for better display of the maximum likelihood estimators.
154:
1.319 brouard 155: Revision 1.318 2022/05/24 08:10:59 brouard
156: * imach.c (Module): Some attempts to find a bug of wrong estimates
157: of confidencce intervals with product in the equation modelC
158:
1.318 brouard 159: Revision 1.317 2022/05/15 15:06:23 brouard
160: * imach.c (Module): Some minor improvements
161:
1.317 brouard 162: Revision 1.316 2022/05/11 15:11:31 brouard
163: Summary: r27
164:
1.316 brouard 165: Revision 1.315 2022/05/11 15:06:32 brouard
166: *** empty log message ***
167:
1.315 brouard 168: Revision 1.314 2022/04/13 17:43:09 brouard
169: * imach.c (Module): Adding link to text data files
170:
1.314 brouard 171: Revision 1.313 2022/04/11 15:57:42 brouard
172: * imach.c (Module): Error in rewriting the 'r' file with yearsfproj or yearsbproj fixed
173:
1.313 brouard 174: Revision 1.312 2022/04/05 21:24:39 brouard
175: *** empty log message ***
176:
1.312 brouard 177: Revision 1.311 2022/04/05 21:03:51 brouard
178: Summary: Fixed quantitative covariates
179:
180: Fixed covariates (dummy or quantitative)
181: with missing values have never been allowed but are ERRORS and
182: program quits. Standard deviations of fixed covariates were
183: wrongly computed. Mean and standard deviations of time varying
184: covariates are still not computed.
185:
1.311 brouard 186: Revision 1.310 2022/03/17 08:45:53 brouard
187: Summary: 99r25
188:
189: Improving detection of errors: result lines should be compatible with
190: the model.
191:
1.310 brouard 192: Revision 1.309 2021/05/20 12:39:14 brouard
193: Summary: Version 0.99r24
194:
1.309 brouard 195: Revision 1.308 2021/03/31 13:11:57 brouard
196: Summary: Version 0.99r23
197:
198:
199: * imach.c (Module): Still bugs in the result loop. Thank to Holly Benett
200:
1.308 brouard 201: Revision 1.307 2021/03/08 18:11:32 brouard
202: Summary: 0.99r22 fixed bug on result:
203:
1.307 brouard 204: Revision 1.306 2021/02/20 15:44:02 brouard
205: Summary: Version 0.99r21
206:
207: * imach.c (Module): Fix bug on quitting after result lines!
208: (Module): Version 0.99r21
209:
1.306 brouard 210: Revision 1.305 2021/02/20 15:28:30 brouard
211: * imach.c (Module): Fix bug on quitting after result lines!
212:
1.305 brouard 213: Revision 1.304 2021/02/12 11:34:20 brouard
214: * imach.c (Module): The use of a Windows BOM (huge) file is now an error
215:
1.304 brouard 216: Revision 1.303 2021/02/11 19:50:15 brouard
217: * (Module): imach.c Someone entered 'results:' instead of 'result:'. Now it is an error which is printed.
218:
1.303 brouard 219: Revision 1.302 2020/02/22 21:00:05 brouard
220: * (Module): imach.c Update mle=-3 (for computing Life expectancy
221: and life table from the data without any state)
222:
1.302 brouard 223: Revision 1.301 2019/06/04 13:51:20 brouard
224: Summary: Error in 'r'parameter file backcast yearsbproj instead of yearsfproj
225:
1.301 brouard 226: Revision 1.300 2019/05/22 19:09:45 brouard
227: Summary: version 0.99r19 of May 2019
228:
1.300 brouard 229: Revision 1.299 2019/05/22 18:37:08 brouard
230: Summary: Cleaned 0.99r19
231:
1.299 brouard 232: Revision 1.298 2019/05/22 18:19:56 brouard
233: *** empty log message ***
234:
1.298 brouard 235: Revision 1.297 2019/05/22 17:56:10 brouard
236: Summary: Fix bug by moving date2dmy and nhstepm which gaefin=-1
237:
1.297 brouard 238: Revision 1.296 2019/05/20 13:03:18 brouard
239: Summary: Projection syntax simplified
240:
241:
242: We can now start projections, forward or backward, from the mean date
243: of inteviews up to or down to a number of years of projection:
244: prevforecast=1 yearsfproj=15.3 mobil_average=0
245: or
246: prevforecast=1 starting-proj-date=1/1/2007 final-proj-date=12/31/2017 mobil_average=0
247: or
248: prevbackcast=1 yearsbproj=12.3 mobil_average=1
249: or
250: prevbackcast=1 starting-back-date=1/10/1999 final-back-date=1/1/1985 mobil_average=1
251:
1.296 brouard 252: Revision 1.295 2019/05/18 09:52:50 brouard
253: Summary: doxygen tex bug
254:
1.295 brouard 255: Revision 1.294 2019/05/16 14:54:33 brouard
256: Summary: There was some wrong lines added
257:
1.294 brouard 258: Revision 1.293 2019/05/09 15:17:34 brouard
259: *** empty log message ***
260:
1.293 brouard 261: Revision 1.292 2019/05/09 14:17:20 brouard
262: Summary: Some updates
263:
1.292 brouard 264: Revision 1.291 2019/05/09 13:44:18 brouard
265: Summary: Before ncovmax
266:
1.291 brouard 267: Revision 1.290 2019/05/09 13:39:37 brouard
268: Summary: 0.99r18 unlimited number of individuals
269:
270: 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.
271:
1.290 brouard 272: Revision 1.289 2018/12/13 09:16:26 brouard
273: Summary: Bug for young ages (<-30) will be in r17
274:
1.289 brouard 275: Revision 1.288 2018/05/02 20:58:27 brouard
276: Summary: Some bugs fixed
277:
1.288 brouard 278: Revision 1.287 2018/05/01 17:57:25 brouard
279: Summary: Bug fixed by providing frequencies only for non missing covariates
280:
1.287 brouard 281: Revision 1.286 2018/04/27 14:27:04 brouard
282: Summary: some minor bugs
283:
1.286 brouard 284: Revision 1.285 2018/04/21 21:02:16 brouard
285: Summary: Some bugs fixed, valgrind tested
286:
1.285 brouard 287: Revision 1.284 2018/04/20 05:22:13 brouard
288: Summary: Computing mean and stdeviation of fixed quantitative variables
289:
1.284 brouard 290: Revision 1.283 2018/04/19 14:49:16 brouard
291: Summary: Some minor bugs fixed
292:
1.283 brouard 293: Revision 1.282 2018/02/27 22:50:02 brouard
294: *** empty log message ***
295:
1.282 brouard 296: Revision 1.281 2018/02/27 19:25:23 brouard
297: Summary: Adding second argument for quitting
298:
1.281 brouard 299: Revision 1.280 2018/02/21 07:58:13 brouard
300: Summary: 0.99r15
301:
302: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
303:
1.280 brouard 304: Revision 1.279 2017/07/20 13:35:01 brouard
305: Summary: temporary working
306:
1.279 brouard 307: Revision 1.278 2017/07/19 14:09:02 brouard
308: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
309:
1.278 brouard 310: Revision 1.277 2017/07/17 08:53:49 brouard
311: Summary: BOM files can be read now
312:
1.277 brouard 313: Revision 1.276 2017/06/30 15:48:31 brouard
314: Summary: Graphs improvements
315:
1.276 brouard 316: Revision 1.275 2017/06/30 13:39:33 brouard
317: Summary: Saito's color
318:
1.275 brouard 319: Revision 1.274 2017/06/29 09:47:08 brouard
320: Summary: Version 0.99r14
321:
1.274 brouard 322: Revision 1.273 2017/06/27 11:06:02 brouard
323: Summary: More documentation on projections
324:
1.273 brouard 325: Revision 1.272 2017/06/27 10:22:40 brouard
326: Summary: Color of backprojection changed from 6 to 5(yellow)
327:
1.272 brouard 328: Revision 1.271 2017/06/27 10:17:50 brouard
329: Summary: Some bug with rint
330:
1.271 brouard 331: Revision 1.270 2017/05/24 05:45:29 brouard
332: *** empty log message ***
333:
1.270 brouard 334: Revision 1.269 2017/05/23 08:39:25 brouard
335: Summary: Code into subroutine, cleanings
336:
1.269 brouard 337: Revision 1.268 2017/05/18 20:09:32 brouard
338: Summary: backprojection and confidence intervals of backprevalence
339:
1.268 brouard 340: Revision 1.267 2017/05/13 10:25:05 brouard
341: Summary: temporary save for backprojection
342:
1.267 brouard 343: Revision 1.266 2017/05/13 07:26:12 brouard
344: Summary: Version 0.99r13 (improvements and bugs fixed)
345:
1.266 brouard 346: Revision 1.265 2017/04/26 16:22:11 brouard
347: Summary: imach 0.99r13 Some bugs fixed
348:
1.265 brouard 349: Revision 1.264 2017/04/26 06:01:29 brouard
350: Summary: Labels in graphs
351:
1.264 brouard 352: Revision 1.263 2017/04/24 15:23:15 brouard
353: Summary: to save
354:
1.263 brouard 355: Revision 1.262 2017/04/18 16:48:12 brouard
356: *** empty log message ***
357:
1.262 brouard 358: Revision 1.261 2017/04/05 10:14:09 brouard
359: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
360:
1.261 brouard 361: Revision 1.260 2017/04/04 17:46:59 brouard
362: Summary: Gnuplot indexations fixed (humm)
363:
1.260 brouard 364: Revision 1.259 2017/04/04 13:01:16 brouard
365: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
366:
1.259 brouard 367: Revision 1.258 2017/04/03 10:17:47 brouard
368: Summary: Version 0.99r12
369:
370: Some cleanings, conformed with updated documentation.
371:
1.258 brouard 372: Revision 1.257 2017/03/29 16:53:30 brouard
373: Summary: Temp
374:
1.257 brouard 375: Revision 1.256 2017/03/27 05:50:23 brouard
376: Summary: Temporary
377:
1.256 brouard 378: Revision 1.255 2017/03/08 16:02:28 brouard
379: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
380:
1.255 brouard 381: Revision 1.254 2017/03/08 07:13:00 brouard
382: Summary: Fixing data parameter line
383:
1.254 brouard 384: Revision 1.253 2016/12/15 11:59:41 brouard
385: Summary: 0.99 in progress
386:
1.253 brouard 387: Revision 1.252 2016/09/15 21:15:37 brouard
388: *** empty log message ***
389:
1.252 brouard 390: Revision 1.251 2016/09/15 15:01:13 brouard
391: Summary: not working
392:
1.251 brouard 393: Revision 1.250 2016/09/08 16:07:27 brouard
394: Summary: continue
395:
1.250 brouard 396: Revision 1.249 2016/09/07 17:14:18 brouard
397: Summary: Starting values from frequencies
398:
1.249 brouard 399: Revision 1.248 2016/09/07 14:10:18 brouard
400: *** empty log message ***
401:
1.248 brouard 402: Revision 1.247 2016/09/02 11:11:21 brouard
403: *** empty log message ***
404:
1.247 brouard 405: Revision 1.246 2016/09/02 08:49:22 brouard
406: *** empty log message ***
407:
1.246 brouard 408: Revision 1.245 2016/09/02 07:25:01 brouard
409: *** empty log message ***
410:
1.245 brouard 411: Revision 1.244 2016/09/02 07:17:34 brouard
412: *** empty log message ***
413:
1.244 brouard 414: Revision 1.243 2016/09/02 06:45:35 brouard
415: *** empty log message ***
416:
1.243 brouard 417: Revision 1.242 2016/08/30 15:01:20 brouard
418: Summary: Fixing a lots
419:
1.242 brouard 420: Revision 1.241 2016/08/29 17:17:25 brouard
421: Summary: gnuplot problem in Back projection to fix
422:
1.241 brouard 423: Revision 1.240 2016/08/29 07:53:18 brouard
424: Summary: Better
425:
1.240 brouard 426: Revision 1.239 2016/08/26 15:51:03 brouard
427: Summary: Improvement in Powell output in order to copy and paste
428:
429: Author:
430:
1.239 brouard 431: Revision 1.238 2016/08/26 14:23:35 brouard
432: Summary: Starting tests of 0.99
433:
1.238 brouard 434: Revision 1.237 2016/08/26 09:20:19 brouard
435: Summary: to valgrind
436:
1.237 brouard 437: Revision 1.236 2016/08/25 10:50:18 brouard
438: *** empty log message ***
439:
1.236 brouard 440: Revision 1.235 2016/08/25 06:59:23 brouard
441: *** empty log message ***
442:
1.235 brouard 443: Revision 1.234 2016/08/23 16:51:20 brouard
444: *** empty log message ***
445:
1.234 brouard 446: Revision 1.233 2016/08/23 07:40:50 brouard
447: Summary: not working
448:
1.233 brouard 449: Revision 1.232 2016/08/22 14:20:21 brouard
450: Summary: not working
451:
1.232 brouard 452: Revision 1.231 2016/08/22 07:17:15 brouard
453: Summary: not working
454:
1.231 brouard 455: Revision 1.230 2016/08/22 06:55:53 brouard
456: Summary: Not working
457:
1.230 brouard 458: Revision 1.229 2016/07/23 09:45:53 brouard
459: Summary: Completing for func too
460:
1.229 brouard 461: Revision 1.228 2016/07/22 17:45:30 brouard
462: Summary: Fixing some arrays, still debugging
463:
1.227 brouard 464: Revision 1.226 2016/07/12 18:42:34 brouard
465: Summary: temp
466:
1.226 brouard 467: Revision 1.225 2016/07/12 08:40:03 brouard
468: Summary: saving but not running
469:
1.225 brouard 470: Revision 1.224 2016/07/01 13:16:01 brouard
471: Summary: Fixes
472:
1.224 brouard 473: Revision 1.223 2016/02/19 09:23:35 brouard
474: Summary: temporary
475:
1.223 brouard 476: Revision 1.222 2016/02/17 08:14:50 brouard
477: Summary: Probably last 0.98 stable version 0.98r6
478:
1.222 brouard 479: Revision 1.221 2016/02/15 23:35:36 brouard
480: Summary: minor bug
481:
1.220 brouard 482: Revision 1.219 2016/02/15 00:48:12 brouard
483: *** empty log message ***
484:
1.219 brouard 485: Revision 1.218 2016/02/12 11:29:23 brouard
486: Summary: 0.99 Back projections
487:
1.218 brouard 488: Revision 1.217 2015/12/23 17:18:31 brouard
489: Summary: Experimental backcast
490:
1.217 brouard 491: Revision 1.216 2015/12/18 17:32:11 brouard
492: Summary: 0.98r4 Warning and status=-2
493:
494: Version 0.98r4 is now:
495: - displaying an error when status is -1, date of interview unknown and date of death known;
496: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
497: Older changes concerning s=-2, dating from 2005 have been supersed.
498:
1.216 brouard 499: Revision 1.215 2015/12/16 08:52:24 brouard
500: Summary: 0.98r4 working
501:
1.215 brouard 502: Revision 1.214 2015/12/16 06:57:54 brouard
503: Summary: temporary not working
504:
1.214 brouard 505: Revision 1.213 2015/12/11 18:22:17 brouard
506: Summary: 0.98r4
507:
1.213 brouard 508: Revision 1.212 2015/11/21 12:47:24 brouard
509: Summary: minor typo
510:
1.212 brouard 511: Revision 1.211 2015/11/21 12:41:11 brouard
512: Summary: 0.98r3 with some graph of projected cross-sectional
513:
514: Author: Nicolas Brouard
515:
1.211 brouard 516: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 517: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 518: Summary: Adding ftolpl parameter
519: Author: N Brouard
520:
521: We had difficulties to get smoothed confidence intervals. It was due
522: to the period prevalence which wasn't computed accurately. The inner
523: parameter ftolpl is now an outer parameter of the .imach parameter
524: file after estepm. If ftolpl is small 1.e-4 and estepm too,
525: computation are long.
526:
1.209 brouard 527: Revision 1.208 2015/11/17 14:31:57 brouard
528: Summary: temporary
529:
1.208 brouard 530: Revision 1.207 2015/10/27 17:36:57 brouard
531: *** empty log message ***
532:
1.207 brouard 533: Revision 1.206 2015/10/24 07:14:11 brouard
534: *** empty log message ***
535:
1.206 brouard 536: Revision 1.205 2015/10/23 15:50:53 brouard
537: Summary: 0.98r3 some clarification for graphs on likelihood contributions
538:
1.205 brouard 539: Revision 1.204 2015/10/01 16:20:26 brouard
540: Summary: Some new graphs of contribution to likelihood
541:
1.204 brouard 542: Revision 1.203 2015/09/30 17:45:14 brouard
543: Summary: looking at better estimation of the hessian
544:
545: Also a better criteria for convergence to the period prevalence And
546: therefore adding the number of years needed to converge. (The
547: prevalence in any alive state shold sum to one
548:
1.203 brouard 549: Revision 1.202 2015/09/22 19:45:16 brouard
550: Summary: Adding some overall graph on contribution to likelihood. Might change
551:
1.202 brouard 552: Revision 1.201 2015/09/15 17:34:58 brouard
553: Summary: 0.98r0
554:
555: - Some new graphs like suvival functions
556: - Some bugs fixed like model=1+age+V2.
557:
1.201 brouard 558: Revision 1.200 2015/09/09 16:53:55 brouard
559: Summary: Big bug thanks to Flavia
560:
561: Even model=1+age+V2. did not work anymore
562:
1.200 brouard 563: Revision 1.199 2015/09/07 14:09:23 brouard
564: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
565:
1.199 brouard 566: Revision 1.198 2015/09/03 07:14:39 brouard
567: Summary: 0.98q5 Flavia
568:
1.198 brouard 569: Revision 1.197 2015/09/01 18:24:39 brouard
570: *** empty log message ***
571:
1.197 brouard 572: Revision 1.196 2015/08/18 23:17:52 brouard
573: Summary: 0.98q5
574:
1.196 brouard 575: Revision 1.195 2015/08/18 16:28:39 brouard
576: Summary: Adding a hack for testing purpose
577:
578: After reading the title, ftol and model lines, if the comment line has
579: a q, starting with #q, the answer at the end of the run is quit. It
580: permits to run test files in batch with ctest. The former workaround was
581: $ echo q | imach foo.imach
582:
1.195 brouard 583: Revision 1.194 2015/08/18 13:32:00 brouard
584: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
585:
1.194 brouard 586: Revision 1.193 2015/08/04 07:17:42 brouard
587: Summary: 0.98q4
588:
1.193 brouard 589: Revision 1.192 2015/07/16 16:49:02 brouard
590: Summary: Fixing some outputs
591:
1.192 brouard 592: Revision 1.191 2015/07/14 10:00:33 brouard
593: Summary: Some fixes
594:
1.191 brouard 595: Revision 1.190 2015/05/05 08:51:13 brouard
596: Summary: Adding digits in output parameters (7 digits instead of 6)
597:
598: Fix 1+age+.
599:
1.190 brouard 600: Revision 1.189 2015/04/30 14:45:16 brouard
601: Summary: 0.98q2
602:
1.189 brouard 603: Revision 1.188 2015/04/30 08:27:53 brouard
604: *** empty log message ***
605:
1.188 brouard 606: Revision 1.187 2015/04/29 09:11:15 brouard
607: *** empty log message ***
608:
1.187 brouard 609: Revision 1.186 2015/04/23 12:01:52 brouard
610: Summary: V1*age is working now, version 0.98q1
611:
612: Some codes had been disabled in order to simplify and Vn*age was
613: working in the optimization phase, ie, giving correct MLE parameters,
614: but, as usual, outputs were not correct and program core dumped.
615:
1.186 brouard 616: Revision 1.185 2015/03/11 13:26:42 brouard
617: Summary: Inclusion of compile and links command line for Intel Compiler
618:
1.185 brouard 619: Revision 1.184 2015/03/11 11:52:39 brouard
620: Summary: Back from Windows 8. Intel Compiler
621:
1.184 brouard 622: Revision 1.183 2015/03/10 20:34:32 brouard
623: Summary: 0.98q0, trying with directest, mnbrak fixed
624:
625: We use directest instead of original Powell test; probably no
626: incidence on the results, but better justifications;
627: We fixed Numerical Recipes mnbrak routine which was wrong and gave
628: wrong results.
629:
1.183 brouard 630: Revision 1.182 2015/02/12 08:19:57 brouard
631: Summary: Trying to keep directest which seems simpler and more general
632: Author: Nicolas Brouard
633:
1.182 brouard 634: Revision 1.181 2015/02/11 23:22:24 brouard
635: Summary: Comments on Powell added
636:
637: Author:
638:
1.181 brouard 639: Revision 1.180 2015/02/11 17:33:45 brouard
640: Summary: Finishing move from main to function (hpijx and prevalence_limit)
641:
1.180 brouard 642: Revision 1.179 2015/01/04 09:57:06 brouard
643: Summary: back to OS/X
644:
1.179 brouard 645: Revision 1.178 2015/01/04 09:35:48 brouard
646: *** empty log message ***
647:
1.178 brouard 648: Revision 1.177 2015/01/03 18:40:56 brouard
649: Summary: Still testing ilc32 on OSX
650:
1.177 brouard 651: Revision 1.176 2015/01/03 16:45:04 brouard
652: *** empty log message ***
653:
1.176 brouard 654: Revision 1.175 2015/01/03 16:33:42 brouard
655: *** empty log message ***
656:
1.175 brouard 657: Revision 1.174 2015/01/03 16:15:49 brouard
658: Summary: Still in cross-compilation
659:
1.174 brouard 660: Revision 1.173 2015/01/03 12:06:26 brouard
661: Summary: trying to detect cross-compilation
662:
1.173 brouard 663: Revision 1.172 2014/12/27 12:07:47 brouard
664: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
665:
1.172 brouard 666: Revision 1.171 2014/12/23 13:26:59 brouard
667: Summary: Back from Visual C
668:
669: Still problem with utsname.h on Windows
670:
1.171 brouard 671: Revision 1.170 2014/12/23 11:17:12 brouard
672: Summary: Cleaning some \%% back to %%
673:
674: The escape was mandatory for a specific compiler (which one?), but too many warnings.
675:
1.170 brouard 676: Revision 1.169 2014/12/22 23:08:31 brouard
677: Summary: 0.98p
678:
679: Outputs some informations on compiler used, OS etc. Testing on different platforms.
680:
1.169 brouard 681: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 682: Summary: update
1.169 brouard 683:
1.168 brouard 684: Revision 1.167 2014/12/22 13:50:56 brouard
685: Summary: Testing uname and compiler version and if compiled 32 or 64
686:
687: Testing on Linux 64
688:
1.167 brouard 689: Revision 1.166 2014/12/22 11:40:47 brouard
690: *** empty log message ***
691:
1.166 brouard 692: Revision 1.165 2014/12/16 11:20:36 brouard
693: Summary: After compiling on Visual C
694:
695: * imach.c (Module): Merging 1.61 to 1.162
696:
1.165 brouard 697: Revision 1.164 2014/12/16 10:52:11 brouard
698: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
699:
700: * imach.c (Module): Merging 1.61 to 1.162
701:
1.164 brouard 702: Revision 1.163 2014/12/16 10:30:11 brouard
703: * imach.c (Module): Merging 1.61 to 1.162
704:
1.163 brouard 705: Revision 1.162 2014/09/25 11:43:39 brouard
706: Summary: temporary backup 0.99!
707:
1.162 brouard 708: Revision 1.1 2014/09/16 11:06:58 brouard
709: Summary: With some code (wrong) for nlopt
710:
711: Author:
712:
713: Revision 1.161 2014/09/15 20:41:41 brouard
714: Summary: Problem with macro SQR on Intel compiler
715:
1.161 brouard 716: Revision 1.160 2014/09/02 09:24:05 brouard
717: *** empty log message ***
718:
1.160 brouard 719: Revision 1.159 2014/09/01 10:34:10 brouard
720: Summary: WIN32
721: Author: Brouard
722:
1.159 brouard 723: Revision 1.158 2014/08/27 17:11:51 brouard
724: *** empty log message ***
725:
1.158 brouard 726: Revision 1.157 2014/08/27 16:26:55 brouard
727: Summary: Preparing windows Visual studio version
728: Author: Brouard
729:
730: In order to compile on Visual studio, time.h is now correct and time_t
731: and tm struct should be used. difftime should be used but sometimes I
732: just make the differences in raw time format (time(&now).
733: Trying to suppress #ifdef LINUX
734: Add xdg-open for __linux in order to open default browser.
735:
1.157 brouard 736: Revision 1.156 2014/08/25 20:10:10 brouard
737: *** empty log message ***
738:
1.156 brouard 739: Revision 1.155 2014/08/25 18:32:34 brouard
740: Summary: New compile, minor changes
741: Author: Brouard
742:
1.155 brouard 743: Revision 1.154 2014/06/20 17:32:08 brouard
744: Summary: Outputs now all graphs of convergence to period prevalence
745:
1.154 brouard 746: Revision 1.153 2014/06/20 16:45:46 brouard
747: Summary: If 3 live state, convergence to period prevalence on same graph
748: Author: Brouard
749:
1.153 brouard 750: Revision 1.152 2014/06/18 17:54:09 brouard
751: Summary: open browser, use gnuplot on same dir than imach if not found in the path
752:
1.152 brouard 753: Revision 1.151 2014/06/18 16:43:30 brouard
754: *** empty log message ***
755:
1.151 brouard 756: Revision 1.150 2014/06/18 16:42:35 brouard
757: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
758: Author: brouard
759:
1.150 brouard 760: Revision 1.149 2014/06/18 15:51:14 brouard
761: Summary: Some fixes in parameter files errors
762: Author: Nicolas Brouard
763:
1.149 brouard 764: Revision 1.148 2014/06/17 17:38:48 brouard
765: Summary: Nothing new
766: Author: Brouard
767:
768: Just a new packaging for OS/X version 0.98nS
769:
1.148 brouard 770: Revision 1.147 2014/06/16 10:33:11 brouard
771: *** empty log message ***
772:
1.147 brouard 773: Revision 1.146 2014/06/16 10:20:28 brouard
774: Summary: Merge
775: Author: Brouard
776:
777: Merge, before building revised version.
778:
1.146 brouard 779: Revision 1.145 2014/06/10 21:23:15 brouard
780: Summary: Debugging with valgrind
781: Author: Nicolas Brouard
782:
783: Lot of changes in order to output the results with some covariates
784: After the Edimburgh REVES conference 2014, it seems mandatory to
785: improve the code.
786: No more memory valgrind error but a lot has to be done in order to
787: continue the work of splitting the code into subroutines.
788: Also, decodemodel has been improved. Tricode is still not
789: optimal. nbcode should be improved. Documentation has been added in
790: the source code.
791:
1.144 brouard 792: Revision 1.143 2014/01/26 09:45:38 brouard
793: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
794:
795: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
796: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
797:
1.143 brouard 798: Revision 1.142 2014/01/26 03:57:36 brouard
799: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
800:
801: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
802:
1.142 brouard 803: Revision 1.141 2014/01/26 02:42:01 brouard
804: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
805:
1.141 brouard 806: Revision 1.140 2011/09/02 10:37:54 brouard
807: Summary: times.h is ok with mingw32 now.
808:
1.140 brouard 809: Revision 1.139 2010/06/14 07:50:17 brouard
810: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
811: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
812:
1.139 brouard 813: Revision 1.138 2010/04/30 18:19:40 brouard
814: *** empty log message ***
815:
1.138 brouard 816: Revision 1.137 2010/04/29 18:11:38 brouard
817: (Module): Checking covariates for more complex models
818: than V1+V2. A lot of change to be done. Unstable.
819:
1.137 brouard 820: Revision 1.136 2010/04/26 20:30:53 brouard
821: (Module): merging some libgsl code. Fixing computation
822: of likelione (using inter/intrapolation if mle = 0) in order to
823: get same likelihood as if mle=1.
824: Some cleaning of code and comments added.
825:
1.136 brouard 826: Revision 1.135 2009/10/29 15:33:14 brouard
827: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
828:
1.135 brouard 829: Revision 1.134 2009/10/29 13:18:53 brouard
830: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
831:
1.134 brouard 832: Revision 1.133 2009/07/06 10:21:25 brouard
833: just nforces
834:
1.133 brouard 835: Revision 1.132 2009/07/06 08:22:05 brouard
836: Many tings
837:
1.132 brouard 838: Revision 1.131 2009/06/20 16:22:47 brouard
839: Some dimensions resccaled
840:
1.131 brouard 841: Revision 1.130 2009/05/26 06:44:34 brouard
842: (Module): Max Covariate is now set to 20 instead of 8. A
843: lot of cleaning with variables initialized to 0. Trying to make
844: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
845:
1.130 brouard 846: Revision 1.129 2007/08/31 13:49:27 lievre
847: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
848:
1.129 lievre 849: Revision 1.128 2006/06/30 13:02:05 brouard
850: (Module): Clarifications on computing e.j
851:
1.128 brouard 852: Revision 1.127 2006/04/28 18:11:50 brouard
853: (Module): Yes the sum of survivors was wrong since
854: imach-114 because nhstepm was no more computed in the age
855: loop. Now we define nhstepma in the age loop.
856: (Module): In order to speed up (in case of numerous covariates) we
857: compute health expectancies (without variances) in a first step
858: and then all the health expectancies with variances or standard
859: deviation (needs data from the Hessian matrices) which slows the
860: computation.
861: In the future we should be able to stop the program is only health
862: expectancies and graph are needed without standard deviations.
863:
1.127 brouard 864: Revision 1.126 2006/04/28 17:23:28 brouard
865: (Module): Yes the sum of survivors was wrong since
866: imach-114 because nhstepm was no more computed in the age
867: loop. Now we define nhstepma in the age loop.
868: Version 0.98h
869:
1.126 brouard 870: Revision 1.125 2006/04/04 15:20:31 lievre
871: Errors in calculation of health expectancies. Age was not initialized.
872: Forecasting file added.
873:
874: Revision 1.124 2006/03/22 17:13:53 lievre
875: Parameters are printed with %lf instead of %f (more numbers after the comma).
876: The log-likelihood is printed in the log file
877:
878: Revision 1.123 2006/03/20 10:52:43 brouard
879: * imach.c (Module): <title> changed, corresponds to .htm file
880: name. <head> headers where missing.
881:
882: * imach.c (Module): Weights can have a decimal point as for
883: English (a comma might work with a correct LC_NUMERIC environment,
884: otherwise the weight is truncated).
885: Modification of warning when the covariates values are not 0 or
886: 1.
887: Version 0.98g
888:
889: Revision 1.122 2006/03/20 09:45:41 brouard
890: (Module): Weights can have a decimal point as for
891: English (a comma might work with a correct LC_NUMERIC environment,
892: otherwise the weight is truncated).
893: Modification of warning when the covariates values are not 0 or
894: 1.
895: Version 0.98g
896:
897: Revision 1.121 2006/03/16 17:45:01 lievre
898: * imach.c (Module): Comments concerning covariates added
899:
900: * imach.c (Module): refinements in the computation of lli if
901: status=-2 in order to have more reliable computation if stepm is
902: not 1 month. Version 0.98f
903:
904: Revision 1.120 2006/03/16 15:10:38 lievre
905: (Module): refinements in the computation of lli if
906: status=-2 in order to have more reliable computation if stepm is
907: not 1 month. Version 0.98f
908:
909: Revision 1.119 2006/03/15 17:42:26 brouard
910: (Module): Bug if status = -2, the loglikelihood was
911: computed as likelihood omitting the logarithm. Version O.98e
912:
913: Revision 1.118 2006/03/14 18:20:07 brouard
914: (Module): varevsij Comments added explaining the second
915: table of variances if popbased=1 .
916: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
917: (Module): Function pstamp added
918: (Module): Version 0.98d
919:
920: Revision 1.117 2006/03/14 17:16:22 brouard
921: (Module): varevsij Comments added explaining the second
922: table of variances if popbased=1 .
923: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
924: (Module): Function pstamp added
925: (Module): Version 0.98d
926:
927: Revision 1.116 2006/03/06 10:29:27 brouard
928: (Module): Variance-covariance wrong links and
929: varian-covariance of ej. is needed (Saito).
930:
931: Revision 1.115 2006/02/27 12:17:45 brouard
932: (Module): One freematrix added in mlikeli! 0.98c
933:
934: Revision 1.114 2006/02/26 12:57:58 brouard
935: (Module): Some improvements in processing parameter
936: filename with strsep.
937:
938: Revision 1.113 2006/02/24 14:20:24 brouard
939: (Module): Memory leaks checks with valgrind and:
940: datafile was not closed, some imatrix were not freed and on matrix
941: allocation too.
942:
943: Revision 1.112 2006/01/30 09:55:26 brouard
944: (Module): Back to gnuplot.exe instead of wgnuplot.exe
945:
946: Revision 1.111 2006/01/25 20:38:18 brouard
947: (Module): Lots of cleaning and bugs added (Gompertz)
948: (Module): Comments can be added in data file. Missing date values
949: can be a simple dot '.'.
950:
951: Revision 1.110 2006/01/25 00:51:50 brouard
952: (Module): Lots of cleaning and bugs added (Gompertz)
953:
954: Revision 1.109 2006/01/24 19:37:15 brouard
955: (Module): Comments (lines starting with a #) are allowed in data.
956:
957: Revision 1.108 2006/01/19 18:05:42 lievre
958: Gnuplot problem appeared...
959: To be fixed
960:
961: Revision 1.107 2006/01/19 16:20:37 brouard
962: Test existence of gnuplot in imach path
963:
964: Revision 1.106 2006/01/19 13:24:36 brouard
965: Some cleaning and links added in html output
966:
967: Revision 1.105 2006/01/05 20:23:19 lievre
968: *** empty log message ***
969:
970: Revision 1.104 2005/09/30 16:11:43 lievre
971: (Module): sump fixed, loop imx fixed, and simplifications.
972: (Module): If the status is missing at the last wave but we know
973: that the person is alive, then we can code his/her status as -2
974: (instead of missing=-1 in earlier versions) and his/her
975: contributions to the likelihood is 1 - Prob of dying from last
976: health status (= 1-p13= p11+p12 in the easiest case of somebody in
977: the healthy state at last known wave). Version is 0.98
978:
979: Revision 1.103 2005/09/30 15:54:49 lievre
980: (Module): sump fixed, loop imx fixed, and simplifications.
981:
982: Revision 1.102 2004/09/15 17:31:30 brouard
983: Add the possibility to read data file including tab characters.
984:
985: Revision 1.101 2004/09/15 10:38:38 brouard
986: Fix on curr_time
987:
988: Revision 1.100 2004/07/12 18:29:06 brouard
989: Add version for Mac OS X. Just define UNIX in Makefile
990:
991: Revision 1.99 2004/06/05 08:57:40 brouard
992: *** empty log message ***
993:
994: Revision 1.98 2004/05/16 15:05:56 brouard
995: New version 0.97 . First attempt to estimate force of mortality
996: directly from the data i.e. without the need of knowing the health
997: state at each age, but using a Gompertz model: log u =a + b*age .
998: This is the basic analysis of mortality and should be done before any
999: other analysis, in order to test if the mortality estimated from the
1000: cross-longitudinal survey is different from the mortality estimated
1001: from other sources like vital statistic data.
1002:
1003: The same imach parameter file can be used but the option for mle should be -3.
1004:
1.324 brouard 1005: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 1006: former routines in order to include the new code within the former code.
1007:
1008: The output is very simple: only an estimate of the intercept and of
1009: the slope with 95% confident intervals.
1010:
1011: Current limitations:
1012: A) Even if you enter covariates, i.e. with the
1013: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
1014: B) There is no computation of Life Expectancy nor Life Table.
1015:
1016: Revision 1.97 2004/02/20 13:25:42 lievre
1017: Version 0.96d. Population forecasting command line is (temporarily)
1018: suppressed.
1019:
1020: Revision 1.96 2003/07/15 15:38:55 brouard
1021: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
1022: rewritten within the same printf. Workaround: many printfs.
1023:
1024: Revision 1.95 2003/07/08 07:54:34 brouard
1025: * imach.c (Repository):
1026: (Repository): Using imachwizard code to output a more meaningful covariance
1027: matrix (cov(a12,c31) instead of numbers.
1028:
1029: Revision 1.94 2003/06/27 13:00:02 brouard
1030: Just cleaning
1031:
1032: Revision 1.93 2003/06/25 16:33:55 brouard
1033: (Module): On windows (cygwin) function asctime_r doesn't
1034: exist so I changed back to asctime which exists.
1035: (Module): Version 0.96b
1036:
1037: Revision 1.92 2003/06/25 16:30:45 brouard
1038: (Module): On windows (cygwin) function asctime_r doesn't
1039: exist so I changed back to asctime which exists.
1040:
1041: Revision 1.91 2003/06/25 15:30:29 brouard
1042: * imach.c (Repository): Duplicated warning errors corrected.
1043: (Repository): Elapsed time after each iteration is now output. It
1044: helps to forecast when convergence will be reached. Elapsed time
1045: is stamped in powell. We created a new html file for the graphs
1046: concerning matrix of covariance. It has extension -cov.htm.
1047:
1048: Revision 1.90 2003/06/24 12:34:15 brouard
1049: (Module): Some bugs corrected for windows. Also, when
1050: mle=-1 a template is output in file "or"mypar.txt with the design
1051: of the covariance matrix to be input.
1052:
1053: Revision 1.89 2003/06/24 12:30:52 brouard
1054: (Module): Some bugs corrected for windows. Also, when
1055: mle=-1 a template is output in file "or"mypar.txt with the design
1056: of the covariance matrix to be input.
1057:
1058: Revision 1.88 2003/06/23 17:54:56 brouard
1059: * 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.
1060:
1061: Revision 1.87 2003/06/18 12:26:01 brouard
1062: Version 0.96
1063:
1064: Revision 1.86 2003/06/17 20:04:08 brouard
1065: (Module): Change position of html and gnuplot routines and added
1066: routine fileappend.
1067:
1068: Revision 1.85 2003/06/17 13:12:43 brouard
1069: * imach.c (Repository): Check when date of death was earlier that
1070: current date of interview. It may happen when the death was just
1071: prior to the death. In this case, dh was negative and likelihood
1072: was wrong (infinity). We still send an "Error" but patch by
1073: assuming that the date of death was just one stepm after the
1074: interview.
1075: (Repository): Because some people have very long ID (first column)
1076: we changed int to long in num[] and we added a new lvector for
1077: memory allocation. But we also truncated to 8 characters (left
1078: truncation)
1079: (Repository): No more line truncation errors.
1080:
1081: Revision 1.84 2003/06/13 21:44:43 brouard
1082: * imach.c (Repository): Replace "freqsummary" at a correct
1083: place. It differs from routine "prevalence" which may be called
1084: many times. Probs is memory consuming and must be used with
1085: parcimony.
1086: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
1087:
1088: Revision 1.83 2003/06/10 13:39:11 lievre
1089: *** empty log message ***
1090:
1091: Revision 1.82 2003/06/05 15:57:20 brouard
1092: Add log in imach.c and fullversion number is now printed.
1093:
1094: */
1095: /*
1096: Interpolated Markov Chain
1097:
1098: Short summary of the programme:
1099:
1.227 brouard 1100: This program computes Healthy Life Expectancies or State-specific
1101: (if states aren't health statuses) Expectancies from
1102: cross-longitudinal data. Cross-longitudinal data consist in:
1103:
1104: -1- a first survey ("cross") where individuals from different ages
1105: are interviewed on their health status or degree of disability (in
1106: the case of a health survey which is our main interest)
1107:
1108: -2- at least a second wave of interviews ("longitudinal") which
1109: measure each change (if any) in individual health status. Health
1110: expectancies are computed from the time spent in each health state
1111: according to a model. More health states you consider, more time is
1112: necessary to reach the Maximum Likelihood of the parameters involved
1113: in the model. The simplest model is the multinomial logistic model
1114: where pij is the probability to be observed in state j at the second
1115: wave conditional to be observed in state i at the first
1116: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
1117: etc , where 'age' is age and 'sex' is a covariate. If you want to
1118: have a more complex model than "constant and age", you should modify
1119: the program where the markup *Covariates have to be included here
1120: again* invites you to do it. More covariates you add, slower the
1.126 brouard 1121: convergence.
1122:
1123: The advantage of this computer programme, compared to a simple
1124: multinomial logistic model, is clear when the delay between waves is not
1125: identical for each individual. Also, if a individual missed an
1126: intermediate interview, the information is lost, but taken into
1127: account using an interpolation or extrapolation.
1128:
1129: hPijx is the probability to be observed in state i at age x+h
1130: conditional to the observed state i at age x. The delay 'h' can be
1131: split into an exact number (nh*stepm) of unobserved intermediate
1132: states. This elementary transition (by month, quarter,
1133: semester or year) is modelled as a multinomial logistic. The hPx
1134: matrix is simply the matrix product of nh*stepm elementary matrices
1135: and the contribution of each individual to the likelihood is simply
1136: hPijx.
1137:
1138: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 1139: of the life expectancies. It also computes the period (stable) prevalence.
1140:
1141: Back prevalence and projections:
1.227 brouard 1142:
1143: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
1144: double agemaxpar, double ftolpl, int *ncvyearp, double
1145: dateprev1,double dateprev2, int firstpass, int lastpass, int
1146: mobilavproj)
1147:
1148: Computes the back prevalence limit for any combination of
1149: covariate values k at any age between ageminpar and agemaxpar and
1150: returns it in **bprlim. In the loops,
1151:
1152: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
1153: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
1154:
1155: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 1156: Computes for any combination of covariates k and any age between bage and fage
1157: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
1158: oldm=oldms;savm=savms;
1.227 brouard 1159:
1.267 brouard 1160: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 1161: Computes the transition matrix starting at age 'age' over
1162: 'nhstepm*hstepm*stepm' months (i.e. until
1163: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 1164: nhstepm*hstepm matrices.
1165:
1166: Returns p3mat[i][j][h] after calling
1167: p3mat[i][j][h]=matprod2(newm,
1168: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
1169: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
1170: oldm);
1.226 brouard 1171:
1172: Important routines
1173:
1174: - func (or funcone), computes logit (pij) distinguishing
1175: o fixed variables (single or product dummies or quantitative);
1176: o varying variables by:
1177: (1) wave (single, product dummies, quantitative),
1178: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
1179: % fixed dummy (treated) or quantitative (not done because time-consuming);
1180: % varying dummy (not done) or quantitative (not done);
1181: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
1182: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
1183: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
1.325 brouard 1184: o There are 2**cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
1.226 brouard 1185: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 1186:
1.226 brouard 1187:
1188:
1.324 brouard 1189: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
1190: Institut national d'études démographiques, Paris.
1.126 brouard 1191: This software have been partly granted by Euro-REVES, a concerted action
1192: from the European Union.
1193: It is copyrighted identically to a GNU software product, ie programme and
1194: software can be distributed freely for non commercial use. Latest version
1195: can be accessed at http://euroreves.ined.fr/imach .
1196:
1197: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
1198: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
1199:
1200: **********************************************************************/
1201: /*
1202: main
1203: read parameterfile
1204: read datafile
1205: concatwav
1206: freqsummary
1207: if (mle >= 1)
1208: mlikeli
1209: print results files
1210: if mle==1
1211: computes hessian
1212: read end of parameter file: agemin, agemax, bage, fage, estepm
1213: begin-prev-date,...
1214: open gnuplot file
1215: open html file
1.145 brouard 1216: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
1217: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
1218: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
1219: freexexit2 possible for memory heap.
1220:
1221: h Pij x | pij_nom ficrestpij
1222: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
1223: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
1224: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
1225:
1226: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
1227: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
1228: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
1229: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
1230: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
1231:
1.126 brouard 1232: forecasting if prevfcast==1 prevforecast call prevalence()
1233: health expectancies
1234: Variance-covariance of DFLE
1235: prevalence()
1236: movingaverage()
1237: varevsij()
1238: if popbased==1 varevsij(,popbased)
1239: total life expectancies
1240: Variance of period (stable) prevalence
1241: end
1242: */
1243:
1.187 brouard 1244: /* #define DEBUG */
1245: /* #define DEBUGBRENT */
1.203 brouard 1246: /* #define DEBUGLINMIN */
1247: /* #define DEBUGHESS */
1248: #define DEBUGHESSIJ
1.224 brouard 1249: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 1250: #define POWELL /* Instead of NLOPT */
1.224 brouard 1251: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 1252: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
1253: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.319 brouard 1254: /* #define FLATSUP *//* Suppresses directions where likelihood is flat */
1.126 brouard 1255:
1256: #include <math.h>
1257: #include <stdio.h>
1258: #include <stdlib.h>
1259: #include <string.h>
1.226 brouard 1260: #include <ctype.h>
1.159 brouard 1261:
1262: #ifdef _WIN32
1263: #include <io.h>
1.172 brouard 1264: #include <windows.h>
1265: #include <tchar.h>
1.159 brouard 1266: #else
1.126 brouard 1267: #include <unistd.h>
1.159 brouard 1268: #endif
1.126 brouard 1269:
1270: #include <limits.h>
1271: #include <sys/types.h>
1.171 brouard 1272:
1273: #if defined(__GNUC__)
1274: #include <sys/utsname.h> /* Doesn't work on Windows */
1275: #endif
1276:
1.126 brouard 1277: #include <sys/stat.h>
1278: #include <errno.h>
1.159 brouard 1279: /* extern int errno; */
1.126 brouard 1280:
1.157 brouard 1281: /* #ifdef LINUX */
1282: /* #include <time.h> */
1283: /* #include "timeval.h" */
1284: /* #else */
1285: /* #include <sys/time.h> */
1286: /* #endif */
1287:
1.126 brouard 1288: #include <time.h>
1289:
1.136 brouard 1290: #ifdef GSL
1291: #include <gsl/gsl_errno.h>
1292: #include <gsl/gsl_multimin.h>
1293: #endif
1294:
1.167 brouard 1295:
1.162 brouard 1296: #ifdef NLOPT
1297: #include <nlopt.h>
1298: typedef struct {
1299: double (* function)(double [] );
1300: } myfunc_data ;
1301: #endif
1302:
1.126 brouard 1303: /* #include <libintl.h> */
1304: /* #define _(String) gettext (String) */
1305:
1.251 brouard 1306: #define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1307:
1308: #define GNUPLOTPROGRAM "gnuplot"
1.343 brouard 1309: #define GNUPLOTVERSION 5.1
1310: double gnuplotversion=GNUPLOTVERSION;
1.126 brouard 1311: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1.329 brouard 1312: #define FILENAMELENGTH 256
1.126 brouard 1313:
1314: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1315: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1316:
1.144 brouard 1317: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
1318: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1319:
1320: #define NINTERVMAX 8
1.144 brouard 1321: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1322: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.325 brouard 1323: #define NCOVMAX 30 /**< Maximum number of covariates used in the model, including generated covariates V1*V2 or V1*age */
1.197 brouard 1324: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1325: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1326: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1327: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1328: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1329: /* #define AGESUP 130 */
1.288 brouard 1330: /* #define AGESUP 150 */
1331: #define AGESUP 200
1.268 brouard 1332: #define AGEINF 0
1.218 brouard 1333: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1334: #define AGEBASE 40
1.194 brouard 1335: #define AGEOVERFLOW 1.e20
1.164 brouard 1336: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1337: #ifdef _WIN32
1338: #define DIRSEPARATOR '\\'
1339: #define CHARSEPARATOR "\\"
1340: #define ODIRSEPARATOR '/'
1341: #else
1.126 brouard 1342: #define DIRSEPARATOR '/'
1343: #define CHARSEPARATOR "/"
1344: #define ODIRSEPARATOR '\\'
1345: #endif
1346:
1.345 ! brouard 1347: /* $Id: imach.c,v 1.344 2022/09/14 19:33:30 brouard Exp $ */
1.126 brouard 1348: /* $State: Exp $ */
1.196 brouard 1349: #include "version.h"
1350: char version[]=__IMACH_VERSION__;
1.337 brouard 1351: 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";
1.345 ! brouard 1352: char fullversion[]="$Revision: 1.344 $ $Date: 2022/09/14 19:33:30 $";
1.126 brouard 1353: char strstart[80];
1354: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1355: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.342 brouard 1356: int debugILK=0; /* debugILK is set by a #d in a comment line */
1.187 brouard 1357: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.330 brouard 1358: /* Number of covariates model (1)=V2+V1+ V3*age+V2*V4 */
1359: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
1.335 brouard 1360: 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 1361: 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 1362: int cptcovs=0; /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
1363: int cptcovsnq=0; /**< cptcovsnq number of SIMPLE covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1364: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1365: int cptcovprodnoage=0; /**< Number of covariate products without age */
1.335 brouard 1366: 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 1367: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1368: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.339 brouard 1369: int ncovvt=0; /* Total number of effective (wave) varying covariates (dummy or quantitative or products [without age]) in the model */
1.232 brouard 1370: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 1371: int nsd=0; /**< Total number of single dummy variables (output) */
1372: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1373: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1374: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1375: int ntveff=0; /**< ntveff number of effective time varying variables */
1376: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1377: int cptcov=0; /* Working variable */
1.334 brouard 1378: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs+1 declared globally ;*/
1.290 brouard 1379: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1380: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.302 brouard 1381: int npar=NPARMAX; /* Number of parameters (nlstate+ndeath-1)*nlstate*ncovmodel; */
1.126 brouard 1382: int nlstate=2; /* Number of live states */
1383: int ndeath=1; /* Number of dead states */
1.130 brouard 1384: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.339 brouard 1385: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable*/
1386: int ncovcolt=0; /* ncovcolt=ncovcol+nqv+ntv+nqtv; total of covariates in the data, not in the model equation*/
1.126 brouard 1387: int popbased=0;
1388:
1389: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1390: int maxwav=0; /* Maxim number of waves */
1391: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1392: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1393: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1394: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1395: int mle=1, weightopt=0;
1.126 brouard 1396: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1397: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1398: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1399: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1400: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1401: int selected(int kvar); /* Is covariate kvar selected for printing results */
1402:
1.130 brouard 1403: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1404: double **matprod2(); /* test */
1.126 brouard 1405: double **oldm, **newm, **savm; /* Working pointers to matrices */
1406: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1407: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1408:
1.136 brouard 1409: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1410: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1411: FILE *ficlog, *ficrespow;
1.130 brouard 1412: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1413: double fretone; /* Only one call to likelihood */
1.130 brouard 1414: long ipmx=0; /* Number of contributions */
1.126 brouard 1415: double sw; /* Sum of weights */
1416: char filerespow[FILENAMELENGTH];
1417: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1418: FILE *ficresilk;
1419: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1420: FILE *ficresprobmorprev;
1421: FILE *fichtm, *fichtmcov; /* Html File */
1422: FILE *ficreseij;
1423: char filerese[FILENAMELENGTH];
1424: FILE *ficresstdeij;
1425: char fileresstde[FILENAMELENGTH];
1426: FILE *ficrescveij;
1427: char filerescve[FILENAMELENGTH];
1428: FILE *ficresvij;
1429: char fileresv[FILENAMELENGTH];
1.269 brouard 1430:
1.126 brouard 1431: char title[MAXLINE];
1.234 brouard 1432: char model[MAXLINE]; /**< The model line */
1.217 brouard 1433: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1434: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1435: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1436: char command[FILENAMELENGTH];
1437: int outcmd=0;
1438:
1.217 brouard 1439: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1440: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1441: char filelog[FILENAMELENGTH]; /* Log file */
1442: char filerest[FILENAMELENGTH];
1443: char fileregp[FILENAMELENGTH];
1444: char popfile[FILENAMELENGTH];
1445:
1446: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1447:
1.157 brouard 1448: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1449: /* struct timezone tzp; */
1450: /* extern int gettimeofday(); */
1451: struct tm tml, *gmtime(), *localtime();
1452:
1453: extern time_t time();
1454:
1455: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1456: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1457: struct tm tm;
1458:
1.126 brouard 1459: char strcurr[80], strfor[80];
1460:
1461: char *endptr;
1462: long lval;
1463: double dval;
1464:
1465: #define NR_END 1
1466: #define FREE_ARG char*
1467: #define FTOL 1.0e-10
1468:
1469: #define NRANSI
1.240 brouard 1470: #define ITMAX 200
1471: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1472:
1473: #define TOL 2.0e-4
1474:
1475: #define CGOLD 0.3819660
1476: #define ZEPS 1.0e-10
1477: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1478:
1479: #define GOLD 1.618034
1480: #define GLIMIT 100.0
1481: #define TINY 1.0e-20
1482:
1483: static double maxarg1,maxarg2;
1484: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1485: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1486:
1487: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1488: #define rint(a) floor(a+0.5)
1.166 brouard 1489: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1490: #define mytinydouble 1.0e-16
1.166 brouard 1491: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1492: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1493: /* static double dsqrarg; */
1494: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1495: static double sqrarg;
1496: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1497: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1498: int agegomp= AGEGOMP;
1499:
1500: int imx;
1501: int stepm=1;
1502: /* Stepm, step in month: minimum step interpolation*/
1503:
1504: int estepm;
1505: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1506:
1507: int m,nb;
1508: long *num;
1.197 brouard 1509: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1510: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1511: covariate for which somebody answered excluding
1512: undefined. Usually 2: 0 and 1. */
1513: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1514: covariate for which somebody answered including
1515: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1516: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1517: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1518: double ***mobaverage, ***mobaverages; /* New global variable */
1.332 brouard 1519: 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 1520: double *ageexmed,*agecens;
1521: double dateintmean=0;
1.296 brouard 1522: double anprojd, mprojd, jprojd; /* For eventual projections */
1523: double anprojf, mprojf, jprojf;
1.126 brouard 1524:
1.296 brouard 1525: double anbackd, mbackd, jbackd; /* For eventual backprojections */
1526: double anbackf, mbackf, jbackf;
1527: double jintmean,mintmean,aintmean;
1.126 brouard 1528: double *weight;
1529: int **s; /* Status */
1.141 brouard 1530: double *agedc;
1.145 brouard 1531: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1532: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1533: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1534: double **coqvar; /* Fixed quantitative covariate nqv */
1.341 brouard 1535: double ***cotvar; /* Time varying covariate start at ncovcol + nqv + (1 to ntv) */
1.225 brouard 1536: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1537: double idx;
1538: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.319 brouard 1539: /* Some documentation */
1540: /* Design original data
1541: * V1 V2 V3 V4 V5 V6 V7 V8 Weight ddb ddth d1st s1 V9 V10 V11 V12 s2 V9 V10 V11 V12
1542: * < ncovcol=6 > nqv=2 (V7 V8) dv dv dv qtv dv dv dvv qtv
1543: * ntv=3 nqtv=1
1.330 brouard 1544: * cptcovn number of covariates (not including constant and age or age*age) = number of plus sign + 1 = 10+1=11
1.319 brouard 1545: * For time varying covariate, quanti or dummies
1546: * cotqvar[wav][iv(1 to nqtv)][i]= [1][12][i]=(V12) quanti
1.341 brouard 1547: * cotvar[wav][ncovcol+nqv+ iv(1 to nqtv)][i]= [(1 to nqtv)][i]=(V12) quanti
1.319 brouard 1548: * cotvar[wav][iv(1 to ntv)][i]= [1][1][i]=(V9) dummies at wav 1
1549: * cotvar[wav][iv(1 to ntv)][i]= [1][2][i]=(V10) dummies at wav 1
1.332 brouard 1550: * covar[Vk,i], value of the Vkth fixed covariate dummy or quanti for individual i:
1.319 brouard 1551: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
1552: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 + V9 + V9*age + V10
1553: * k= 1 2 3 4 5 6 7 8 9 10 11
1554: */
1555: /* According to the model, more columns can be added to covar by the product of covariates */
1.318 brouard 1556: /* 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
1557: # States 1=Coresidence, 2 Living alone, 3 Institution
1558: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1559: */
1.343 brouard 1560: /* V5+V4+ V3+V4*V3 +V5*age+V2 +V1*V2+V1*age+V1 */
1561: /* kmodel 1 2 3 4 5 6 7 8 9 */
1.319 brouard 1562: /*Typevar[k]= 0 0 0 2 1 0 2 1 0 *//*0 for simple covariate (dummy, quantitative,*/
1563: /* fixed or varying), 1 for age product, 2 for*/
1564: /* product */
1565: /*Dummy[k]= 1 0 0 1 3 1 1 2 0 *//*Dummy[k] 0=dummy (0 1), 1 quantitative */
1566: /*(single or product without age), 2 dummy*/
1567: /* with age product, 3 quant with age product*/
1568: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1569: /* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */
1.330 brouard 1570: /*TnsdVar[Tvar] 1 2 3 */
1.337 brouard 1571: /*Tvaraff[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1.319 brouard 1572: /*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1.338 brouard 1573: /*TvarsDind[nsd] 2 3 9 */ /* position K of single dummy cova */
1.319 brouard 1574: /* nsq 1 2 */ /* Counting single quantit tv */
1575: /* TvarsQ[k] 5 2 */ /* Number of single quantitative cova */
1576: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1577: /* Tprod[i]=k 1 2 */ /* Position in model of the ith prod without age */
1578: /* cptcovage 1 2 */ /* Counting cov*age in the model equation */
1579: /* Tage[cptcovage]=k 5 8 */ /* Position in the model of ith cov*age */
1580: /* Tvard[1][1]@4={4,3,1,2} V4*V3 V1*V2 */ /* Position in model of the ith prod without age */
1.330 brouard 1581: /* 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 1582: /* 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 1583: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.234 brouard 1584: /* Type */
1585: /* V 1 2 3 4 5 */
1586: /* F F V V V */
1587: /* D Q D D Q */
1588: /* */
1589: int *TvarsD;
1.330 brouard 1590: int *TnsdVar;
1.234 brouard 1591: int *TvarsDind;
1592: int *TvarsQ;
1593: int *TvarsQind;
1594:
1.318 brouard 1595: #define MAXRESULTLINESPONE 10+1
1.235 brouard 1596: int nresult=0;
1.258 brouard 1597: int parameterline=0; /* # of the parameter (type) line */
1.334 brouard 1598: int TKresult[MAXRESULTLINESPONE]; /* TKresult[nres]=k for each resultline nres give the corresponding combination of dummies */
1599: int resultmodel[MAXRESULTLINESPONE][NCOVMAX];/* resultmodel[k1]=k3: k1th position in the model corresponds to the k3 position in the resultline */
1600: int modelresult[MAXRESULTLINESPONE][NCOVMAX];/* modelresult[k3]=k1: k1th position in the model corresponds to the k3 position in the resultline */
1601: int Tresult[MAXRESULTLINESPONE][NCOVMAX];/* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1602: int Tinvresult[MAXRESULTLINESPONE][NCOVMAX];/* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1603: double TinvDoQresult[MAXRESULTLINESPONE][NCOVMAX];/* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.334 brouard 1604: int Tvresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1605: double Tqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.318 brouard 1606: double Tqinvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
1.332 brouard 1607: int Tvqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.318 brouard 1608:
1609: /* 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
1610: # States 1=Coresidence, 2 Living alone, 3 Institution
1611: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1612: */
1.234 brouard 1613: /* 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 1614: 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 */
1615: 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 */
1616: 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 */
1617: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1618: 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 */
1619: 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 1620: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1621: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1622: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1623: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1624: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1625: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1626: 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 */
1627: 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 1628: int *TvarVV; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1629: int *TvarVVind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1630: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
1631: /* model V1+V3+age*V1+age*V3+V1*V3 */
1632: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
1633: /* TvarVV={3,1,3}, for V3 and then the product V1*V3 is decomposed into V1 and V3 */
1634: /* TvarVVind={2,5,5}, for V3 and then the product V1*V3 is decomposed into V1 and V3 */
1.230 brouard 1635: int *Tvarsel; /**< Selected covariates for output */
1636: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1637: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1638: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1639: 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 1640: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1641: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1642: int *Tage;
1.227 brouard 1643: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1644: 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 1645: 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*/
1646: 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 1647: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1648: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1649: int **Tvard;
1.330 brouard 1650: int **Tvardk;
1.227 brouard 1651: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1652: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1653: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1654: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1655: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1656: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1657: double *lsurv, *lpop, *tpop;
1658:
1.231 brouard 1659: #define FD 1; /* Fixed dummy covariate */
1660: #define FQ 2; /* Fixed quantitative covariate */
1661: #define FP 3; /* Fixed product covariate */
1662: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1663: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1664: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1665: #define VD 10; /* Varying dummy covariate */
1666: #define VQ 11; /* Varying quantitative covariate */
1667: #define VP 12; /* Varying product covariate */
1668: #define VPDD 13; /* Varying product dummy*dummy covariate */
1669: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1670: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1671: #define APFD 16; /* Age product * fixed dummy covariate */
1672: #define APFQ 17; /* Age product * fixed quantitative covariate */
1673: #define APVD 18; /* Age product * varying dummy covariate */
1674: #define APVQ 19; /* Age product * varying quantitative covariate */
1675:
1676: #define FTYPE 1; /* Fixed covariate */
1677: #define VTYPE 2; /* Varying covariate (loop in wave) */
1678: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1679:
1680: struct kmodel{
1681: int maintype; /* main type */
1682: int subtype; /* subtype */
1683: };
1684: struct kmodel modell[NCOVMAX];
1685:
1.143 brouard 1686: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1687: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1688:
1689: /**************** split *************************/
1690: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1691: {
1692: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1693: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1694: */
1695: char *ss; /* pointer */
1.186 brouard 1696: int l1=0, l2=0; /* length counters */
1.126 brouard 1697:
1698: l1 = strlen(path ); /* length of path */
1699: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1700: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1701: if ( ss == NULL ) { /* no directory, so determine current directory */
1702: strcpy( name, path ); /* we got the fullname name because no directory */
1703: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1704: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1705: /* get current working directory */
1706: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1707: #ifdef WIN32
1708: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1709: #else
1710: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1711: #endif
1.126 brouard 1712: return( GLOCK_ERROR_GETCWD );
1713: }
1714: /* got dirc from getcwd*/
1715: printf(" DIRC = %s \n",dirc);
1.205 brouard 1716: } else { /* strip directory from path */
1.126 brouard 1717: ss++; /* after this, the filename */
1718: l2 = strlen( ss ); /* length of filename */
1719: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1720: strcpy( name, ss ); /* save file name */
1721: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1722: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1723: printf(" DIRC2 = %s \n",dirc);
1724: }
1725: /* We add a separator at the end of dirc if not exists */
1726: l1 = strlen( dirc ); /* length of directory */
1727: if( dirc[l1-1] != DIRSEPARATOR ){
1728: dirc[l1] = DIRSEPARATOR;
1729: dirc[l1+1] = 0;
1730: printf(" DIRC3 = %s \n",dirc);
1731: }
1732: ss = strrchr( name, '.' ); /* find last / */
1733: if (ss >0){
1734: ss++;
1735: strcpy(ext,ss); /* save extension */
1736: l1= strlen( name);
1737: l2= strlen(ss)+1;
1738: strncpy( finame, name, l1-l2);
1739: finame[l1-l2]= 0;
1740: }
1741:
1742: return( 0 ); /* we're done */
1743: }
1744:
1745:
1746: /******************************************/
1747:
1748: void replace_back_to_slash(char *s, char*t)
1749: {
1750: int i;
1751: int lg=0;
1752: i=0;
1753: lg=strlen(t);
1754: for(i=0; i<= lg; i++) {
1755: (s[i] = t[i]);
1756: if (t[i]== '\\') s[i]='/';
1757: }
1758: }
1759:
1.132 brouard 1760: char *trimbb(char *out, char *in)
1.137 brouard 1761: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1762: char *s;
1763: s=out;
1764: while (*in != '\0'){
1.137 brouard 1765: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1766: in++;
1767: }
1768: *out++ = *in++;
1769: }
1770: *out='\0';
1771: return s;
1772: }
1773:
1.187 brouard 1774: /* char *substrchaine(char *out, char *in, char *chain) */
1775: /* { */
1776: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1777: /* char *s, *t; */
1778: /* t=in;s=out; */
1779: /* while ((*in != *chain) && (*in != '\0')){ */
1780: /* *out++ = *in++; */
1781: /* } */
1782:
1783: /* /\* *in matches *chain *\/ */
1784: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1785: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1786: /* } */
1787: /* in--; chain--; */
1788: /* while ( (*in != '\0')){ */
1789: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1790: /* *out++ = *in++; */
1791: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1792: /* } */
1793: /* *out='\0'; */
1794: /* out=s; */
1795: /* return out; */
1796: /* } */
1797: char *substrchaine(char *out, char *in, char *chain)
1798: {
1799: /* Substract chain 'chain' from 'in', return and output 'out' */
1800: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1801:
1802: char *strloc;
1803:
1804: strcpy (out, in);
1805: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1806: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1807: if(strloc != NULL){
1808: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1809: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1810: /* strcpy (strloc, strloc +strlen(chain));*/
1811: }
1812: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1813: return out;
1814: }
1815:
1816:
1.145 brouard 1817: char *cutl(char *blocc, char *alocc, char *in, char occ)
1818: {
1.187 brouard 1819: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1820: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.310 brouard 1821: gives alocc="abcdef" and blocc="ghi2j".
1.145 brouard 1822: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1823: */
1.160 brouard 1824: char *s, *t;
1.145 brouard 1825: t=in;s=in;
1826: while ((*in != occ) && (*in != '\0')){
1827: *alocc++ = *in++;
1828: }
1829: if( *in == occ){
1830: *(alocc)='\0';
1831: s=++in;
1832: }
1833:
1834: if (s == t) {/* occ not found */
1835: *(alocc-(in-s))='\0';
1836: in=s;
1837: }
1838: while ( *in != '\0'){
1839: *blocc++ = *in++;
1840: }
1841:
1842: *blocc='\0';
1843: return t;
1844: }
1.137 brouard 1845: char *cutv(char *blocc, char *alocc, char *in, char occ)
1846: {
1.187 brouard 1847: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1848: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1849: gives blocc="abcdef2ghi" and alocc="j".
1850: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1851: */
1852: char *s, *t;
1853: t=in;s=in;
1854: while (*in != '\0'){
1855: while( *in == occ){
1856: *blocc++ = *in++;
1857: s=in;
1858: }
1859: *blocc++ = *in++;
1860: }
1861: if (s == t) /* occ not found */
1862: *(blocc-(in-s))='\0';
1863: else
1864: *(blocc-(in-s)-1)='\0';
1865: in=s;
1866: while ( *in != '\0'){
1867: *alocc++ = *in++;
1868: }
1869:
1870: *alocc='\0';
1871: return s;
1872: }
1873:
1.126 brouard 1874: int nbocc(char *s, char occ)
1875: {
1876: int i,j=0;
1877: int lg=20;
1878: i=0;
1879: lg=strlen(s);
1880: for(i=0; i<= lg; i++) {
1.234 brouard 1881: if (s[i] == occ ) j++;
1.126 brouard 1882: }
1883: return j;
1884: }
1885:
1.137 brouard 1886: /* void cutv(char *u,char *v, char*t, char occ) */
1887: /* { */
1888: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1889: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1890: /* gives u="abcdef2ghi" and v="j" *\/ */
1891: /* int i,lg,j,p=0; */
1892: /* i=0; */
1893: /* lg=strlen(t); */
1894: /* for(j=0; j<=lg-1; j++) { */
1895: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1896: /* } */
1.126 brouard 1897:
1.137 brouard 1898: /* for(j=0; j<p; j++) { */
1899: /* (u[j] = t[j]); */
1900: /* } */
1901: /* u[p]='\0'; */
1.126 brouard 1902:
1.137 brouard 1903: /* for(j=0; j<= lg; j++) { */
1904: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1905: /* } */
1906: /* } */
1.126 brouard 1907:
1.160 brouard 1908: #ifdef _WIN32
1909: char * strsep(char **pp, const char *delim)
1910: {
1911: char *p, *q;
1912:
1913: if ((p = *pp) == NULL)
1914: return 0;
1915: if ((q = strpbrk (p, delim)) != NULL)
1916: {
1917: *pp = q + 1;
1918: *q = '\0';
1919: }
1920: else
1921: *pp = 0;
1922: return p;
1923: }
1924: #endif
1925:
1.126 brouard 1926: /********************** nrerror ********************/
1927:
1928: void nrerror(char error_text[])
1929: {
1930: fprintf(stderr,"ERREUR ...\n");
1931: fprintf(stderr,"%s\n",error_text);
1932: exit(EXIT_FAILURE);
1933: }
1934: /*********************** vector *******************/
1935: double *vector(int nl, int nh)
1936: {
1937: double *v;
1938: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1939: if (!v) nrerror("allocation failure in vector");
1940: return v-nl+NR_END;
1941: }
1942:
1943: /************************ free vector ******************/
1944: void free_vector(double*v, int nl, int nh)
1945: {
1946: free((FREE_ARG)(v+nl-NR_END));
1947: }
1948:
1949: /************************ivector *******************************/
1950: int *ivector(long nl,long nh)
1951: {
1952: int *v;
1953: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1954: if (!v) nrerror("allocation failure in ivector");
1955: return v-nl+NR_END;
1956: }
1957:
1958: /******************free ivector **************************/
1959: void free_ivector(int *v, long nl, long nh)
1960: {
1961: free((FREE_ARG)(v+nl-NR_END));
1962: }
1963:
1964: /************************lvector *******************************/
1965: long *lvector(long nl,long nh)
1966: {
1967: long *v;
1968: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1969: if (!v) nrerror("allocation failure in ivector");
1970: return v-nl+NR_END;
1971: }
1972:
1973: /******************free lvector **************************/
1974: void free_lvector(long *v, long nl, long nh)
1975: {
1976: free((FREE_ARG)(v+nl-NR_END));
1977: }
1978:
1979: /******************* imatrix *******************************/
1980: int **imatrix(long nrl, long nrh, long ncl, long nch)
1981: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1982: {
1983: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1984: int **m;
1985:
1986: /* allocate pointers to rows */
1987: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1988: if (!m) nrerror("allocation failure 1 in matrix()");
1989: m += NR_END;
1990: m -= nrl;
1991:
1992:
1993: /* allocate rows and set pointers to them */
1994: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
1995: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1996: m[nrl] += NR_END;
1997: m[nrl] -= ncl;
1998:
1999: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
2000:
2001: /* return pointer to array of pointers to rows */
2002: return m;
2003: }
2004:
2005: /****************** free_imatrix *************************/
2006: void free_imatrix(m,nrl,nrh,ncl,nch)
2007: int **m;
2008: long nch,ncl,nrh,nrl;
2009: /* free an int matrix allocated by imatrix() */
2010: {
2011: free((FREE_ARG) (m[nrl]+ncl-NR_END));
2012: free((FREE_ARG) (m+nrl-NR_END));
2013: }
2014:
2015: /******************* matrix *******************************/
2016: double **matrix(long nrl, long nrh, long ncl, long nch)
2017: {
2018: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
2019: double **m;
2020:
2021: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
2022: if (!m) nrerror("allocation failure 1 in matrix()");
2023: m += NR_END;
2024: m -= nrl;
2025:
2026: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
2027: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2028: m[nrl] += NR_END;
2029: m[nrl] -= ncl;
2030:
2031: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2032: return m;
1.145 brouard 2033: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
2034: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
2035: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 2036: */
2037: }
2038:
2039: /*************************free matrix ************************/
2040: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
2041: {
2042: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2043: free((FREE_ARG)(m+nrl-NR_END));
2044: }
2045:
2046: /******************* ma3x *******************************/
2047: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
2048: {
2049: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
2050: double ***m;
2051:
2052: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
2053: if (!m) nrerror("allocation failure 1 in matrix()");
2054: m += NR_END;
2055: m -= nrl;
2056:
2057: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
2058: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2059: m[nrl] += NR_END;
2060: m[nrl] -= ncl;
2061:
2062: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2063:
2064: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
2065: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
2066: m[nrl][ncl] += NR_END;
2067: m[nrl][ncl] -= nll;
2068: for (j=ncl+1; j<=nch; j++)
2069: m[nrl][j]=m[nrl][j-1]+nlay;
2070:
2071: for (i=nrl+1; i<=nrh; i++) {
2072: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
2073: for (j=ncl+1; j<=nch; j++)
2074: m[i][j]=m[i][j-1]+nlay;
2075: }
2076: return m;
2077: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
2078: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
2079: */
2080: }
2081:
2082: /*************************free ma3x ************************/
2083: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
2084: {
2085: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
2086: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2087: free((FREE_ARG)(m+nrl-NR_END));
2088: }
2089:
2090: /*************** function subdirf ***********/
2091: char *subdirf(char fileres[])
2092: {
2093: /* Caution optionfilefiname is hidden */
2094: strcpy(tmpout,optionfilefiname);
2095: strcat(tmpout,"/"); /* Add to the right */
2096: strcat(tmpout,fileres);
2097: return tmpout;
2098: }
2099:
2100: /*************** function subdirf2 ***********/
2101: char *subdirf2(char fileres[], char *preop)
2102: {
1.314 brouard 2103: /* Example subdirf2(optionfilefiname,"FB_") with optionfilefiname="texte", result="texte/FB_texte"
2104: Errors in subdirf, 2, 3 while printing tmpout is
1.315 brouard 2105: rewritten within the same printf. Workaround: many printfs */
1.126 brouard 2106: /* Caution optionfilefiname is hidden */
2107: strcpy(tmpout,optionfilefiname);
2108: strcat(tmpout,"/");
2109: strcat(tmpout,preop);
2110: strcat(tmpout,fileres);
2111: return tmpout;
2112: }
2113:
2114: /*************** function subdirf3 ***********/
2115: char *subdirf3(char fileres[], char *preop, char *preop2)
2116: {
2117:
2118: /* Caution optionfilefiname is hidden */
2119: strcpy(tmpout,optionfilefiname);
2120: strcat(tmpout,"/");
2121: strcat(tmpout,preop);
2122: strcat(tmpout,preop2);
2123: strcat(tmpout,fileres);
2124: return tmpout;
2125: }
1.213 brouard 2126:
2127: /*************** function subdirfext ***********/
2128: char *subdirfext(char fileres[], char *preop, char *postop)
2129: {
2130:
2131: strcpy(tmpout,preop);
2132: strcat(tmpout,fileres);
2133: strcat(tmpout,postop);
2134: return tmpout;
2135: }
1.126 brouard 2136:
1.213 brouard 2137: /*************** function subdirfext3 ***********/
2138: char *subdirfext3(char fileres[], char *preop, char *postop)
2139: {
2140:
2141: /* Caution optionfilefiname is hidden */
2142: strcpy(tmpout,optionfilefiname);
2143: strcat(tmpout,"/");
2144: strcat(tmpout,preop);
2145: strcat(tmpout,fileres);
2146: strcat(tmpout,postop);
2147: return tmpout;
2148: }
2149:
1.162 brouard 2150: char *asc_diff_time(long time_sec, char ascdiff[])
2151: {
2152: long sec_left, days, hours, minutes;
2153: days = (time_sec) / (60*60*24);
2154: sec_left = (time_sec) % (60*60*24);
2155: hours = (sec_left) / (60*60) ;
2156: sec_left = (sec_left) %(60*60);
2157: minutes = (sec_left) /60;
2158: sec_left = (sec_left) % (60);
2159: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
2160: return ascdiff;
2161: }
2162:
1.126 brouard 2163: /***************** f1dim *************************/
2164: extern int ncom;
2165: extern double *pcom,*xicom;
2166: extern double (*nrfunc)(double []);
2167:
2168: double f1dim(double x)
2169: {
2170: int j;
2171: double f;
2172: double *xt;
2173:
2174: xt=vector(1,ncom);
2175: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
2176: f=(*nrfunc)(xt);
2177: free_vector(xt,1,ncom);
2178: return f;
2179: }
2180:
2181: /*****************brent *************************/
2182: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 2183: {
2184: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
2185: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
2186: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
2187: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
2188: * returned function value.
2189: */
1.126 brouard 2190: int iter;
2191: double a,b,d,etemp;
1.159 brouard 2192: double fu=0,fv,fw,fx;
1.164 brouard 2193: double ftemp=0.;
1.126 brouard 2194: double p,q,r,tol1,tol2,u,v,w,x,xm;
2195: double e=0.0;
2196:
2197: a=(ax < cx ? ax : cx);
2198: b=(ax > cx ? ax : cx);
2199: x=w=v=bx;
2200: fw=fv=fx=(*f)(x);
2201: for (iter=1;iter<=ITMAX;iter++) {
2202: xm=0.5*(a+b);
2203: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
2204: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
2205: printf(".");fflush(stdout);
2206: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 2207: #ifdef DEBUGBRENT
1.126 brouard 2208: 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);
2209: 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);
2210: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
2211: #endif
2212: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
2213: *xmin=x;
2214: return fx;
2215: }
2216: ftemp=fu;
2217: if (fabs(e) > tol1) {
2218: r=(x-w)*(fx-fv);
2219: q=(x-v)*(fx-fw);
2220: p=(x-v)*q-(x-w)*r;
2221: q=2.0*(q-r);
2222: if (q > 0.0) p = -p;
2223: q=fabs(q);
2224: etemp=e;
2225: e=d;
2226: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 2227: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 2228: else {
1.224 brouard 2229: d=p/q;
2230: u=x+d;
2231: if (u-a < tol2 || b-u < tol2)
2232: d=SIGN(tol1,xm-x);
1.126 brouard 2233: }
2234: } else {
2235: d=CGOLD*(e=(x >= xm ? a-x : b-x));
2236: }
2237: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
2238: fu=(*f)(u);
2239: if (fu <= fx) {
2240: if (u >= x) a=x; else b=x;
2241: SHFT(v,w,x,u)
1.183 brouard 2242: SHFT(fv,fw,fx,fu)
2243: } else {
2244: if (u < x) a=u; else b=u;
2245: if (fu <= fw || w == x) {
1.224 brouard 2246: v=w;
2247: w=u;
2248: fv=fw;
2249: fw=fu;
1.183 brouard 2250: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 2251: v=u;
2252: fv=fu;
1.183 brouard 2253: }
2254: }
1.126 brouard 2255: }
2256: nrerror("Too many iterations in brent");
2257: *xmin=x;
2258: return fx;
2259: }
2260:
2261: /****************** mnbrak ***********************/
2262:
2263: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
2264: double (*func)(double))
1.183 brouard 2265: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
2266: the downhill direction (defined by the function as evaluated at the initial points) and returns
2267: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
2268: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
2269: */
1.126 brouard 2270: double ulim,u,r,q, dum;
2271: double fu;
1.187 brouard 2272:
2273: double scale=10.;
2274: int iterscale=0;
2275:
2276: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
2277: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
2278:
2279:
2280: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
2281: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
2282: /* *bx = *ax - (*ax - *bx)/scale; */
2283: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
2284: /* } */
2285:
1.126 brouard 2286: if (*fb > *fa) {
2287: SHFT(dum,*ax,*bx,dum)
1.183 brouard 2288: SHFT(dum,*fb,*fa,dum)
2289: }
1.126 brouard 2290: *cx=(*bx)+GOLD*(*bx-*ax);
2291: *fc=(*func)(*cx);
1.183 brouard 2292: #ifdef DEBUG
1.224 brouard 2293: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
2294: 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 2295: #endif
1.224 brouard 2296: 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 2297: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 2298: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 2299: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 2300: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
2301: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
2302: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 2303: fu=(*func)(u);
1.163 brouard 2304: #ifdef DEBUG
2305: /* f(x)=A(x-u)**2+f(u) */
2306: double A, fparabu;
2307: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2308: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 2309: 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);
2310: 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 2311: /* And thus,it can be that fu > *fc even if fparabu < *fc */
2312: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
2313: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
2314: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 2315: #endif
1.184 brouard 2316: #ifdef MNBRAKORIGINAL
1.183 brouard 2317: #else
1.191 brouard 2318: /* if (fu > *fc) { */
2319: /* #ifdef DEBUG */
2320: /* printf("mnbrak4 fu > fc \n"); */
2321: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
2322: /* #endif */
2323: /* /\* 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 *\\/ *\/ */
2324: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2325: /* dum=u; /\* Shifting c and u *\/ */
2326: /* u = *cx; */
2327: /* *cx = dum; */
2328: /* dum = fu; */
2329: /* fu = *fc; */
2330: /* *fc =dum; */
2331: /* } else { /\* end *\/ */
2332: /* #ifdef DEBUG */
2333: /* printf("mnbrak3 fu < fc \n"); */
2334: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2335: /* #endif */
2336: /* dum=u; /\* Shifting c and u *\/ */
2337: /* u = *cx; */
2338: /* *cx = dum; */
2339: /* dum = fu; */
2340: /* fu = *fc; */
2341: /* *fc =dum; */
2342: /* } */
1.224 brouard 2343: #ifdef DEBUGMNBRAK
2344: double A, fparabu;
2345: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2346: fparabu= *fa - A*(*ax-u)*(*ax-u);
2347: 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);
2348: 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 2349: #endif
1.191 brouard 2350: dum=u; /* Shifting c and u */
2351: u = *cx;
2352: *cx = dum;
2353: dum = fu;
2354: fu = *fc;
2355: *fc =dum;
1.183 brouard 2356: #endif
1.162 brouard 2357: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2358: #ifdef DEBUG
1.224 brouard 2359: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2360: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2361: #endif
1.126 brouard 2362: fu=(*func)(u);
2363: if (fu < *fc) {
1.183 brouard 2364: #ifdef DEBUG
1.224 brouard 2365: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2366: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2367: #endif
2368: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2369: SHFT(*fb,*fc,fu,(*func)(u))
2370: #ifdef DEBUG
2371: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2372: #endif
2373: }
1.162 brouard 2374: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2375: #ifdef DEBUG
1.224 brouard 2376: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2377: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2378: #endif
1.126 brouard 2379: u=ulim;
2380: fu=(*func)(u);
1.183 brouard 2381: } else { /* u could be left to b (if r > q parabola has a maximum) */
2382: #ifdef DEBUG
1.224 brouard 2383: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2384: 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 2385: #endif
1.126 brouard 2386: u=(*cx)+GOLD*(*cx-*bx);
2387: fu=(*func)(u);
1.224 brouard 2388: #ifdef DEBUG
2389: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2390: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2391: #endif
1.183 brouard 2392: } /* end tests */
1.126 brouard 2393: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2394: SHFT(*fa,*fb,*fc,fu)
2395: #ifdef DEBUG
1.224 brouard 2396: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2397: 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 2398: #endif
2399: } /* 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 2400: }
2401:
2402: /*************** linmin ************************/
1.162 brouard 2403: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2404: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2405: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2406: the value of func at the returned location p . This is actually all accomplished by calling the
2407: routines mnbrak and brent .*/
1.126 brouard 2408: int ncom;
2409: double *pcom,*xicom;
2410: double (*nrfunc)(double []);
2411:
1.224 brouard 2412: #ifdef LINMINORIGINAL
1.126 brouard 2413: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2414: #else
2415: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2416: #endif
1.126 brouard 2417: {
2418: double brent(double ax, double bx, double cx,
2419: double (*f)(double), double tol, double *xmin);
2420: double f1dim(double x);
2421: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2422: double *fc, double (*func)(double));
2423: int j;
2424: double xx,xmin,bx,ax;
2425: double fx,fb,fa;
1.187 brouard 2426:
1.203 brouard 2427: #ifdef LINMINORIGINAL
2428: #else
2429: double scale=10., axs, xxs; /* Scale added for infinity */
2430: #endif
2431:
1.126 brouard 2432: ncom=n;
2433: pcom=vector(1,n);
2434: xicom=vector(1,n);
2435: nrfunc=func;
2436: for (j=1;j<=n;j++) {
2437: pcom[j]=p[j];
1.202 brouard 2438: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2439: }
1.187 brouard 2440:
1.203 brouard 2441: #ifdef LINMINORIGINAL
2442: xx=1.;
2443: #else
2444: axs=0.0;
2445: xxs=1.;
2446: do{
2447: xx= xxs;
2448: #endif
1.187 brouard 2449: ax=0.;
2450: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2451: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2452: /* 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)) */
2453: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2454: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2455: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2456: /* 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 2457: #ifdef LINMINORIGINAL
2458: #else
2459: if (fx != fx){
1.224 brouard 2460: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2461: printf("|");
2462: fprintf(ficlog,"|");
1.203 brouard 2463: #ifdef DEBUGLINMIN
1.224 brouard 2464: 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 2465: #endif
2466: }
1.224 brouard 2467: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2468: #endif
2469:
1.191 brouard 2470: #ifdef DEBUGLINMIN
2471: 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 2472: 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 2473: #endif
1.224 brouard 2474: #ifdef LINMINORIGINAL
2475: #else
1.317 brouard 2476: if(fb == fx){ /* Flat function in the direction */
2477: xmin=xx;
1.224 brouard 2478: *flat=1;
1.317 brouard 2479: }else{
1.224 brouard 2480: *flat=0;
2481: #endif
2482: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2483: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2484: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2485: /* fmin = f(p[j] + xmin * xi[j]) */
2486: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2487: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2488: #ifdef DEBUG
1.224 brouard 2489: 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);
2490: 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);
2491: #endif
2492: #ifdef LINMINORIGINAL
2493: #else
2494: }
1.126 brouard 2495: #endif
1.191 brouard 2496: #ifdef DEBUGLINMIN
2497: printf("linmin end ");
1.202 brouard 2498: fprintf(ficlog,"linmin end ");
1.191 brouard 2499: #endif
1.126 brouard 2500: for (j=1;j<=n;j++) {
1.203 brouard 2501: #ifdef LINMINORIGINAL
2502: xi[j] *= xmin;
2503: #else
2504: #ifdef DEBUGLINMIN
2505: if(xxs <1.0)
2506: printf(" before xi[%d]=%12.8f", j,xi[j]);
2507: #endif
2508: 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) */
2509: #ifdef DEBUGLINMIN
2510: if(xxs <1.0)
2511: 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 );
2512: #endif
2513: #endif
1.187 brouard 2514: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2515: }
1.191 brouard 2516: #ifdef DEBUGLINMIN
1.203 brouard 2517: printf("\n");
1.191 brouard 2518: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2519: 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 2520: for (j=1;j<=n;j++) {
1.202 brouard 2521: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2522: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2523: if(j % ncovmodel == 0){
1.191 brouard 2524: printf("\n");
1.202 brouard 2525: fprintf(ficlog,"\n");
2526: }
1.191 brouard 2527: }
1.203 brouard 2528: #else
1.191 brouard 2529: #endif
1.126 brouard 2530: free_vector(xicom,1,n);
2531: free_vector(pcom,1,n);
2532: }
2533:
2534:
2535: /*************** powell ************************/
1.162 brouard 2536: /*
1.317 brouard 2537: Minimization of a function func of n variables. Input consists in an initial starting point
2538: p[1..n] ; an initial matrix xi[1..n][1..n] whose columns contain the initial set of di-
2539: rections (usually the n unit vectors); and ftol, the fractional tolerance in the function value
2540: such that failure to decrease by more than this amount in one iteration signals doneness. On
1.162 brouard 2541: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2542: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2543: */
1.224 brouard 2544: #ifdef LINMINORIGINAL
2545: #else
2546: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2547: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2548: #endif
1.126 brouard 2549: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2550: double (*func)(double []))
2551: {
1.224 brouard 2552: #ifdef LINMINORIGINAL
2553: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2554: double (*func)(double []));
1.224 brouard 2555: #else
1.241 brouard 2556: void linmin(double p[], double xi[], int n, double *fret,
2557: double (*func)(double []),int *flat);
1.224 brouard 2558: #endif
1.239 brouard 2559: int i,ibig,j,jk,k;
1.126 brouard 2560: double del,t,*pt,*ptt,*xit;
1.181 brouard 2561: double directest;
1.126 brouard 2562: double fp,fptt;
2563: double *xits;
2564: int niterf, itmp;
2565:
2566: pt=vector(1,n);
2567: ptt=vector(1,n);
2568: xit=vector(1,n);
2569: xits=vector(1,n);
2570: *fret=(*func)(p);
2571: for (j=1;j<=n;j++) pt[j]=p[j];
1.338 brouard 2572: rcurr_time = time(NULL);
2573: fp=(*fret); /* Initialisation */
1.126 brouard 2574: for (*iter=1;;++(*iter)) {
2575: ibig=0;
2576: del=0.0;
1.157 brouard 2577: rlast_time=rcurr_time;
2578: /* (void) gettimeofday(&curr_time,&tzp); */
2579: rcurr_time = time(NULL);
2580: curr_time = *localtime(&rcurr_time);
1.337 brouard 2581: /* 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); */
2582: /* 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); */
2583: 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);
2584: 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 2585: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.324 brouard 2586: fp=(*fret); /* From former iteration or initial value */
1.192 brouard 2587: for (i=1;i<=n;i++) {
1.126 brouard 2588: fprintf(ficrespow," %.12lf", p[i]);
2589: }
1.239 brouard 2590: fprintf(ficrespow,"\n");fflush(ficrespow);
2591: printf("\n#model= 1 + age ");
2592: fprintf(ficlog,"\n#model= 1 + age ");
2593: if(nagesqr==1){
1.241 brouard 2594: printf(" + age*age ");
2595: fprintf(ficlog," + age*age ");
1.239 brouard 2596: }
2597: for(j=1;j <=ncovmodel-2;j++){
2598: if(Typevar[j]==0) {
2599: printf(" + V%d ",Tvar[j]);
2600: fprintf(ficlog," + V%d ",Tvar[j]);
2601: }else if(Typevar[j]==1) {
2602: printf(" + V%d*age ",Tvar[j]);
2603: fprintf(ficlog," + V%d*age ",Tvar[j]);
2604: }else if(Typevar[j]==2) {
2605: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2606: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2607: }
2608: }
1.126 brouard 2609: printf("\n");
1.239 brouard 2610: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2611: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2612: fprintf(ficlog,"\n");
1.239 brouard 2613: for(i=1,jk=1; i <=nlstate; i++){
2614: for(k=1; k <=(nlstate+ndeath); k++){
2615: if (k != i) {
2616: printf("%d%d ",i,k);
2617: fprintf(ficlog,"%d%d ",i,k);
2618: for(j=1; j <=ncovmodel; j++){
2619: printf("%12.7f ",p[jk]);
2620: fprintf(ficlog,"%12.7f ",p[jk]);
2621: jk++;
2622: }
2623: printf("\n");
2624: fprintf(ficlog,"\n");
2625: }
2626: }
2627: }
1.241 brouard 2628: if(*iter <=3 && *iter >1){
1.157 brouard 2629: tml = *localtime(&rcurr_time);
2630: strcpy(strcurr,asctime(&tml));
2631: rforecast_time=rcurr_time;
1.126 brouard 2632: itmp = strlen(strcurr);
2633: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2634: strcurr[itmp-1]='\0';
1.162 brouard 2635: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2636: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2637: for(niterf=10;niterf<=30;niterf+=10){
1.241 brouard 2638: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2639: forecast_time = *localtime(&rforecast_time);
2640: strcpy(strfor,asctime(&forecast_time));
2641: itmp = strlen(strfor);
2642: if(strfor[itmp-1]=='\n')
2643: strfor[itmp-1]='\0';
2644: 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);
2645: 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 2646: }
2647: }
1.187 brouard 2648: for (i=1;i<=n;i++) { /* For each direction i */
2649: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2650: fptt=(*fret);
2651: #ifdef DEBUG
1.203 brouard 2652: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2653: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2654: #endif
1.203 brouard 2655: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2656: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2657: #ifdef LINMINORIGINAL
1.188 brouard 2658: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2659: #else
2660: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2661: flatdir[i]=flat; /* Function is vanishing in that direction i */
2662: #endif
2663: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2664: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2665: /* because that direction will be replaced unless the gain del is small */
2666: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2667: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2668: /* with the new direction. */
2669: del=fabs(fptt-(*fret));
2670: ibig=i;
1.126 brouard 2671: }
2672: #ifdef DEBUG
2673: printf("%d %.12e",i,(*fret));
2674: fprintf(ficlog,"%d %.12e",i,(*fret));
2675: for (j=1;j<=n;j++) {
1.224 brouard 2676: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2677: printf(" x(%d)=%.12e",j,xit[j]);
2678: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2679: }
2680: for(j=1;j<=n;j++) {
1.225 brouard 2681: printf(" p(%d)=%.12e",j,p[j]);
2682: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2683: }
2684: printf("\n");
2685: fprintf(ficlog,"\n");
2686: #endif
1.187 brouard 2687: } /* end loop on each direction i */
2688: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2689: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2690: /* New value of last point Pn is not computed, P(n-1) */
1.319 brouard 2691: for(j=1;j<=n;j++) {
2692: if(flatdir[j] >0){
2693: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2694: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
1.302 brouard 2695: }
1.319 brouard 2696: /* printf("\n"); */
2697: /* fprintf(ficlog,"\n"); */
2698: }
1.243 brouard 2699: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2700: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2701: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2702: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2703: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2704: /* decreased of more than 3.84 */
2705: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2706: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2707: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2708:
1.188 brouard 2709: /* Starting the program with initial values given by a former maximization will simply change */
2710: /* the scales of the directions and the directions, because the are reset to canonical directions */
2711: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2712: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2713: #ifdef DEBUG
2714: int k[2],l;
2715: k[0]=1;
2716: k[1]=-1;
2717: printf("Max: %.12e",(*func)(p));
2718: fprintf(ficlog,"Max: %.12e",(*func)(p));
2719: for (j=1;j<=n;j++) {
2720: printf(" %.12e",p[j]);
2721: fprintf(ficlog," %.12e",p[j]);
2722: }
2723: printf("\n");
2724: fprintf(ficlog,"\n");
2725: for(l=0;l<=1;l++) {
2726: for (j=1;j<=n;j++) {
2727: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2728: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2729: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2730: }
2731: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2732: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2733: }
2734: #endif
2735:
2736: free_vector(xit,1,n);
2737: free_vector(xits,1,n);
2738: free_vector(ptt,1,n);
2739: free_vector(pt,1,n);
2740: return;
1.192 brouard 2741: } /* enough precision */
1.240 brouard 2742: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2743: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2744: ptt[j]=2.0*p[j]-pt[j];
2745: xit[j]=p[j]-pt[j];
2746: pt[j]=p[j];
2747: }
1.181 brouard 2748: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2749: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2750: if (*iter <=4) {
1.225 brouard 2751: #else
2752: #endif
1.224 brouard 2753: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2754: #else
1.161 brouard 2755: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2756: #endif
1.162 brouard 2757: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2758: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2759: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2760: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2761: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2762: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2763: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2764: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2765: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2766: /* Even if f3 <f1, directest can be negative and t >0 */
2767: /* mu² and del² are equal when f3=f1 */
2768: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2769: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2770: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2771: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2772: #ifdef NRCORIGINAL
2773: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2774: #else
2775: 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 2776: t= t- del*SQR(fp-fptt);
1.183 brouard 2777: #endif
1.202 brouard 2778: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2779: #ifdef DEBUG
1.181 brouard 2780: 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);
2781: 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 2782: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2783: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2784: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2785: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2786: 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);
2787: 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);
2788: #endif
1.183 brouard 2789: #ifdef POWELLORIGINAL
2790: if (t < 0.0) { /* Then we use it for new direction */
2791: #else
1.182 brouard 2792: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2793: 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 2794: 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 2795: 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 2796: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2797: }
1.181 brouard 2798: if (directest < 0.0) { /* Then we use it for new direction */
2799: #endif
1.191 brouard 2800: #ifdef DEBUGLINMIN
1.234 brouard 2801: printf("Before linmin in direction P%d-P0\n",n);
2802: for (j=1;j<=n;j++) {
2803: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2804: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2805: if(j % ncovmodel == 0){
2806: printf("\n");
2807: fprintf(ficlog,"\n");
2808: }
2809: }
1.224 brouard 2810: #endif
2811: #ifdef LINMINORIGINAL
1.234 brouard 2812: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2813: #else
1.234 brouard 2814: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2815: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2816: #endif
1.234 brouard 2817:
1.191 brouard 2818: #ifdef DEBUGLINMIN
1.234 brouard 2819: for (j=1;j<=n;j++) {
2820: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2821: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2822: if(j % ncovmodel == 0){
2823: printf("\n");
2824: fprintf(ficlog,"\n");
2825: }
2826: }
1.224 brouard 2827: #endif
1.234 brouard 2828: for (j=1;j<=n;j++) {
2829: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2830: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2831: }
1.224 brouard 2832: #ifdef LINMINORIGINAL
2833: #else
1.234 brouard 2834: for (j=1, flatd=0;j<=n;j++) {
2835: if(flatdir[j]>0)
2836: flatd++;
2837: }
2838: if(flatd >0){
1.255 brouard 2839: printf("%d flat directions: ",flatd);
2840: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2841: for (j=1;j<=n;j++) {
2842: if(flatdir[j]>0){
2843: printf("%d ",j);
2844: fprintf(ficlog,"%d ",j);
2845: }
2846: }
2847: printf("\n");
2848: fprintf(ficlog,"\n");
1.319 brouard 2849: #ifdef FLATSUP
2850: free_vector(xit,1,n);
2851: free_vector(xits,1,n);
2852: free_vector(ptt,1,n);
2853: free_vector(pt,1,n);
2854: return;
2855: #endif
1.234 brouard 2856: }
1.191 brouard 2857: #endif
1.234 brouard 2858: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2859: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2860:
1.126 brouard 2861: #ifdef DEBUG
1.234 brouard 2862: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2863: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2864: for(j=1;j<=n;j++){
2865: printf(" %lf",xit[j]);
2866: fprintf(ficlog," %lf",xit[j]);
2867: }
2868: printf("\n");
2869: fprintf(ficlog,"\n");
1.126 brouard 2870: #endif
1.192 brouard 2871: } /* end of t or directest negative */
1.224 brouard 2872: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2873: #else
1.234 brouard 2874: } /* end if (fptt < fp) */
1.192 brouard 2875: #endif
1.225 brouard 2876: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2877: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2878: #else
1.224 brouard 2879: #endif
1.234 brouard 2880: } /* loop iteration */
1.126 brouard 2881: }
1.234 brouard 2882:
1.126 brouard 2883: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2884:
1.235 brouard 2885: 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 2886: {
1.338 brouard 2887: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij . Nicely done
1.279 brouard 2888: * (and selected quantitative values in nres)
2889: * by left multiplying the unit
2890: * matrix by transitions matrix until convergence is reached with precision ftolpl
2891: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2892: * Wx is row vector: population in state 1, population in state 2, population dead
2893: * or prevalence in state 1, prevalence in state 2, 0
2894: * newm is the matrix after multiplications, its rows are identical at a factor.
2895: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2896: * Output is prlim.
2897: * Initial matrix pimij
2898: */
1.206 brouard 2899: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2900: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2901: /* 0, 0 , 1} */
2902: /*
2903: * and after some iteration: */
2904: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2905: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2906: /* 0, 0 , 1} */
2907: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2908: /* {0.51571254859325999, 0.4842874514067399, */
2909: /* 0.51326036147820708, 0.48673963852179264} */
2910: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2911:
1.332 brouard 2912: int i, ii,j,k, k1;
1.209 brouard 2913: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2914: /* double **matprod2(); */ /* test */
1.218 brouard 2915: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2916: double **newm;
1.209 brouard 2917: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2918: int ncvloop=0;
1.288 brouard 2919: int first=0;
1.169 brouard 2920:
1.209 brouard 2921: min=vector(1,nlstate);
2922: max=vector(1,nlstate);
2923: meandiff=vector(1,nlstate);
2924:
1.218 brouard 2925: /* Starting with matrix unity */
1.126 brouard 2926: for (ii=1;ii<=nlstate+ndeath;ii++)
2927: for (j=1;j<=nlstate+ndeath;j++){
2928: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2929: }
1.169 brouard 2930:
2931: cov[1]=1.;
2932:
2933: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2934: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2935: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2936: ncvloop++;
1.126 brouard 2937: newm=savm;
2938: /* Covariates have to be included here again */
1.138 brouard 2939: cov[2]=agefin;
1.319 brouard 2940: if(nagesqr==1){
2941: cov[3]= agefin*agefin;
2942: }
1.332 brouard 2943: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
2944: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
2945: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
2946: if(Typevar[k1]==1){ /* A product with age */
2947: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
2948: }else{
2949: cov[2+nagesqr+k1]=precov[nres][k1];
2950: }
2951: }/* End of loop on model equation */
2952:
2953: /* Start of old code (replaced by a loop on position in the model equation */
2954: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only of the model *\/ */
2955: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
2956: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; *\/ */
2957: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TnsdVar[TvarsD[k]])]; */
2958: /* /\* model = 1 +age + V1*V3 + age*V1 + V2 + V1 + age*V2 + V3 + V3*age + V1*V2 */
2959: /* * k 1 2 3 4 5 6 7 8 */
2960: /* *cov[] 1 2 3 4 5 6 7 8 9 10 */
2961: /* *TypeVar[k] 2 1 0 0 1 0 1 2 */
2962: /* *Dummy[k] 0 2 0 0 2 0 2 0 */
2963: /* *Tvar[k] 4 1 2 1 2 3 3 5 */
2964: /* *nsd=3 (1) (2) (3) */
2965: /* *TvarsD[nsd] [1]=2 1 3 */
2966: /* *TnsdVar [2]=2 [1]=1 [3]=3 */
2967: /* *TvarsDind[nsd](=k) [1]=3 [2]=4 [3]=6 */
2968: /* *Tage[] [1]=1 [2]=2 [3]=3 */
2969: /* *Tvard[] [1][1]=1 [2][1]=1 */
2970: /* * [1][2]=3 [2][2]=2 */
2971: /* *Tprod[](=k) [1]=1 [2]=8 */
2972: /* *TvarsDp(=Tvar) [1]=1 [2]=2 [3]=3 [4]=5 */
2973: /* *TvarD (=k) [1]=1 [2]=3 [3]=4 [3]=6 [4]=6 */
2974: /* *TvarsDpType */
2975: /* *si model= 1 + age + V3 + V2*age + V2 + V3*age */
2976: /* * nsd=1 (1) (2) */
2977: /* *TvarsD[nsd] 3 2 */
2978: /* *TnsdVar (3)=1 (2)=2 */
2979: /* *TvarsDind[nsd](=k) [1]=1 [2]=3 */
2980: /* *Tage[] [1]=2 [2]= 3 */
2981: /* *\/ */
2982: /* /\* cov[++k1]=nbcode[TvarsD[k]][codtabm(ij,k)]; *\/ */
2983: /* /\* 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)); *\/ */
2984: /* } */
2985: /* for (k=1; k<=nsq;k++) { /\* For single quantitative varying covariates only of the model *\/ */
2986: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
2987: /* /\* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline *\/ */
2988: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
2989: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][resultmodel[nres][k1]] */
2990: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
2991: /* /\* 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]); *\/ */
2992: /* } */
2993: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
2994: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
2995: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
2996: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
2997: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
2998: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
2999: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
3000: /* } */
3001: /* /\* 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]); *\/ */
3002: /* } */
3003: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
3004: /* /\* 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]); *\/ */
3005: /* if(Dummy[Tvard[k][1]]==0){ */
3006: /* if(Dummy[Tvard[k][2]]==0){ */
3007: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3008: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3009: /* }else{ */
3010: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3011: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
3012: /* } */
3013: /* }else{ */
3014: /* if(Dummy[Tvard[k][2]]==0){ */
3015: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3016: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
3017: /* }else{ */
3018: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3019: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
3020: /* } */
3021: /* } */
3022: /* } /\* End product without age *\/ */
3023: /* ENd of old code */
1.138 brouard 3024: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
3025: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
3026: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 3027: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3028: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.319 brouard 3029: /* age and covariate values of ij are in 'cov' */
1.142 brouard 3030: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 3031:
1.126 brouard 3032: savm=oldm;
3033: oldm=newm;
1.209 brouard 3034:
3035: for(j=1; j<=nlstate; j++){
3036: max[j]=0.;
3037: min[j]=1.;
3038: }
3039: for(i=1;i<=nlstate;i++){
3040: sumnew=0;
3041: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
3042: for(j=1; j<=nlstate; j++){
3043: prlim[i][j]= newm[i][j]/(1-sumnew);
3044: max[j]=FMAX(max[j],prlim[i][j]);
3045: min[j]=FMIN(min[j],prlim[i][j]);
3046: }
3047: }
3048:
1.126 brouard 3049: maxmax=0.;
1.209 brouard 3050: for(j=1; j<=nlstate; j++){
3051: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
3052: maxmax=FMAX(maxmax,meandiff[j]);
3053: /* 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 3054: } /* j loop */
1.203 brouard 3055: *ncvyear= (int)age- (int)agefin;
1.208 brouard 3056: /* 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 3057: if(maxmax < ftolpl){
1.209 brouard 3058: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
3059: free_vector(min,1,nlstate);
3060: free_vector(max,1,nlstate);
3061: free_vector(meandiff,1,nlstate);
1.126 brouard 3062: return prlim;
3063: }
1.288 brouard 3064: } /* agefin loop */
1.208 brouard 3065: /* After some age loop it doesn't converge */
1.288 brouard 3066: if(!first){
3067: first=1;
3068: 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 3069: 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);
3070: }else if (first >=1 && first <10){
3071: 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);
3072: first++;
3073: }else if (first ==10){
3074: 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);
3075: 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");
3076: fprintf(ficlog,"Warning: the stable prevalence no convergence; too many cases, giving up noticing, even in log file\n");
3077: first++;
1.288 brouard 3078: }
3079:
1.209 brouard 3080: /* 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); */
3081: free_vector(min,1,nlstate);
3082: free_vector(max,1,nlstate);
3083: free_vector(meandiff,1,nlstate);
1.208 brouard 3084:
1.169 brouard 3085: return prlim; /* should not reach here */
1.126 brouard 3086: }
3087:
1.217 brouard 3088:
3089: /**** Back Prevalence limit (stable or period prevalence) ****************/
3090:
1.218 brouard 3091: /* 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) */
3092: /* 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 3093: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 3094: {
1.264 brouard 3095: /* 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 3096: matrix by transitions matrix until convergence is reached with precision ftolpl */
3097: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
3098: /* Wx is row vector: population in state 1, population in state 2, population dead */
3099: /* or prevalence in state 1, prevalence in state 2, 0 */
3100: /* newm is the matrix after multiplications, its rows are identical at a factor */
3101: /* Initial matrix pimij */
3102: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
3103: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
3104: /* 0, 0 , 1} */
3105: /*
3106: * and after some iteration: */
3107: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
3108: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
3109: /* 0, 0 , 1} */
3110: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
3111: /* {0.51571254859325999, 0.4842874514067399, */
3112: /* 0.51326036147820708, 0.48673963852179264} */
3113: /* If we start from prlim again, prlim tends to a constant matrix */
3114:
1.332 brouard 3115: int i, ii,j,k, k1;
1.247 brouard 3116: int first=0;
1.217 brouard 3117: double *min, *max, *meandiff, maxmax,sumnew=0.;
3118: /* double **matprod2(); */ /* test */
3119: double **out, cov[NCOVMAX+1], **bmij();
3120: double **newm;
1.218 brouard 3121: double **dnewm, **doldm, **dsavm; /* for use */
3122: double **oldm, **savm; /* for use */
3123:
1.217 brouard 3124: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
3125: int ncvloop=0;
3126:
3127: min=vector(1,nlstate);
3128: max=vector(1,nlstate);
3129: meandiff=vector(1,nlstate);
3130:
1.266 brouard 3131: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
3132: oldm=oldms; savm=savms;
3133:
3134: /* Starting with matrix unity */
3135: for (ii=1;ii<=nlstate+ndeath;ii++)
3136: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 3137: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3138: }
3139:
3140: cov[1]=1.;
3141:
3142: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3143: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 3144: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 3145: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
3146: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 3147: ncvloop++;
1.218 brouard 3148: newm=savm; /* oldm should be kept from previous iteration or unity at start */
3149: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 3150: /* Covariates have to be included here again */
3151: cov[2]=agefin;
1.319 brouard 3152: if(nagesqr==1){
1.217 brouard 3153: cov[3]= agefin*agefin;;
1.319 brouard 3154: }
1.332 brouard 3155: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
3156: if(Typevar[k1]==1){ /* A product with age */
3157: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.242 brouard 3158: }else{
1.332 brouard 3159: cov[2+nagesqr+k1]=precov[nres][k1];
1.242 brouard 3160: }
1.332 brouard 3161: }/* End of loop on model equation */
3162:
3163: /* Old code */
3164:
3165: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
3166: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
3167: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; */
3168: /* /\* 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)); *\/ */
3169: /* } */
3170: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
3171: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
3172: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
3173: /* /\* /\\* 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])]); *\\/ *\/ */
3174: /* /\* } *\/ */
3175: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
3176: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3177: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
3178: /* /\* 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]); *\/ */
3179: /* } */
3180: /* /\* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; *\/ */
3181: /* /\* for (k=1; k<=cptcovprod;k++) /\\* Useless *\\/ *\/ */
3182: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\\/ *\/ */
3183: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3184: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
3185: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age *\\/ ERROR ???*\/ */
3186: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
3187: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3188: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
3189: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3190: /* } */
3191: /* /\* 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]); *\/ */
3192: /* } */
3193: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
3194: /* /\* 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]); *\/ */
3195: /* if(Dummy[Tvard[k][1]]==0){ */
3196: /* if(Dummy[Tvard[k][2]]==0){ */
3197: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3198: /* }else{ */
3199: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3200: /* } */
3201: /* }else{ */
3202: /* if(Dummy[Tvard[k][2]]==0){ */
3203: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3204: /* }else{ */
3205: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3206: /* } */
3207: /* } */
3208: /* } */
1.217 brouard 3209:
3210: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
3211: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
3212: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
3213: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3214: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 3215: /* ij should be linked to the correct index of cov */
3216: /* age and covariate values ij are in 'cov', but we need to pass
3217: * ij for the observed prevalence at age and status and covariate
3218: * number: prevacurrent[(int)agefin][ii][ij]
3219: */
3220: /* 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 *\/ */
3221: /* 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 *\/ */
3222: 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 3223: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 3224: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
3225: /* for(i=1; i<=nlstate+ndeath; i++) { */
3226: /* printf("%d newm= ",i); */
3227: /* for(j=1;j<=nlstate+ndeath;j++) { */
3228: /* printf("%f ",newm[i][j]); */
3229: /* } */
3230: /* printf("oldm * "); */
3231: /* for(j=1;j<=nlstate+ndeath;j++) { */
3232: /* printf("%f ",oldm[i][j]); */
3233: /* } */
1.268 brouard 3234: /* printf(" bmmij "); */
1.266 brouard 3235: /* for(j=1;j<=nlstate+ndeath;j++) { */
3236: /* printf("%f ",pmmij[i][j]); */
3237: /* } */
3238: /* printf("\n"); */
3239: /* } */
3240: /* } */
1.217 brouard 3241: savm=oldm;
3242: oldm=newm;
1.266 brouard 3243:
1.217 brouard 3244: for(j=1; j<=nlstate; j++){
3245: max[j]=0.;
3246: min[j]=1.;
3247: }
3248: for(j=1; j<=nlstate; j++){
3249: for(i=1;i<=nlstate;i++){
1.234 brouard 3250: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
3251: bprlim[i][j]= newm[i][j];
3252: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
3253: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 3254: }
3255: }
1.218 brouard 3256:
1.217 brouard 3257: maxmax=0.;
3258: for(i=1; i<=nlstate; i++){
1.318 brouard 3259: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column, could be nan! */
1.217 brouard 3260: maxmax=FMAX(maxmax,meandiff[i]);
3261: /* 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 3262: } /* i loop */
1.217 brouard 3263: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 3264: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3265: if(maxmax < ftolpl){
1.220 brouard 3266: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3267: free_vector(min,1,nlstate);
3268: free_vector(max,1,nlstate);
3269: free_vector(meandiff,1,nlstate);
3270: return bprlim;
3271: }
1.288 brouard 3272: } /* agefin loop */
1.217 brouard 3273: /* After some age loop it doesn't converge */
1.288 brouard 3274: if(!first){
1.247 brouard 3275: first=1;
3276: 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\
3277: 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);
3278: }
3279: 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 3280: 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);
3281: /* 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); */
3282: free_vector(min,1,nlstate);
3283: free_vector(max,1,nlstate);
3284: free_vector(meandiff,1,nlstate);
3285:
3286: return bprlim; /* should not reach here */
3287: }
3288:
1.126 brouard 3289: /*************** transition probabilities ***************/
3290:
3291: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
3292: {
1.138 brouard 3293: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 3294: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 3295: model to the ncovmodel covariates (including constant and age).
3296: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3297: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3298: ncth covariate in the global vector x is given by the formula:
3299: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3300: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3301: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3302: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 3303: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 3304: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 3305: Sum on j ps[i][j] should equal to 1.
1.138 brouard 3306: */
3307: double s1, lnpijopii;
1.126 brouard 3308: /*double t34;*/
1.164 brouard 3309: int i,j, nc, ii, jj;
1.126 brouard 3310:
1.223 brouard 3311: for(i=1; i<= nlstate; i++){
3312: for(j=1; j<i;j++){
3313: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3314: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3315: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3316: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3317: }
3318: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3319: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3320: }
3321: for(j=i+1; j<=nlstate+ndeath;j++){
3322: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3323: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3324: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3325: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3326: }
3327: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3328: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3329: }
3330: }
1.218 brouard 3331:
1.223 brouard 3332: for(i=1; i<= nlstate; i++){
3333: s1=0;
3334: for(j=1; j<i; j++){
1.339 brouard 3335: /* printf("debug1 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 3336: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3337: }
3338: for(j=i+1; j<=nlstate+ndeath; j++){
1.339 brouard 3339: /* printf("debug2 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 3340: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3341: }
3342: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3343: ps[i][i]=1./(s1+1.);
3344: /* Computing other pijs */
3345: for(j=1; j<i; j++)
1.325 brouard 3346: ps[i][j]= exp(ps[i][j])*ps[i][i];/* Bug valgrind */
1.223 brouard 3347: for(j=i+1; j<=nlstate+ndeath; j++)
3348: ps[i][j]= exp(ps[i][j])*ps[i][i];
3349: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3350: } /* end i */
1.218 brouard 3351:
1.223 brouard 3352: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3353: for(jj=1; jj<= nlstate+ndeath; jj++){
3354: ps[ii][jj]=0;
3355: ps[ii][ii]=1;
3356: }
3357: }
1.294 brouard 3358:
3359:
1.223 brouard 3360: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3361: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3362: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3363: /* } */
3364: /* printf("\n "); */
3365: /* } */
3366: /* printf("\n ");printf("%lf ",cov[2]);*/
3367: /*
3368: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 3369: goto end;*/
1.266 brouard 3370: return ps; /* Pointer is unchanged since its call */
1.126 brouard 3371: }
3372:
1.218 brouard 3373: /*************** backward transition probabilities ***************/
3374:
3375: /* 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 ) */
3376: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
3377: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
3378: {
1.302 brouard 3379: /* 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 3380: * 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 3381: */
1.218 brouard 3382: int i, ii, j,k;
1.222 brouard 3383:
3384: double **out, **pmij();
3385: double sumnew=0.;
1.218 brouard 3386: double agefin;
1.292 brouard 3387: 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 3388: double **dnewm, **dsavm, **doldm;
3389: double **bbmij;
3390:
1.218 brouard 3391: doldm=ddoldms; /* global pointers */
1.222 brouard 3392: dnewm=ddnewms;
3393: dsavm=ddsavms;
1.318 brouard 3394:
3395: /* Debug */
3396: /* printf("Bmij ij=%d, cov[2}=%f\n", ij, cov[2]); */
1.222 brouard 3397: agefin=cov[2];
1.268 brouard 3398: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 3399: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 3400: the observed prevalence (with this covariate ij) at beginning of transition */
3401: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 3402:
3403: /* P_x */
1.325 brouard 3404: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm *//* Bug valgrind */
1.268 brouard 3405: /* outputs pmmij which is a stochastic matrix in row */
3406:
3407: /* Diag(w_x) */
1.292 brouard 3408: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 3409: sumnew=0.;
1.269 brouard 3410: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 3411: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.297 brouard 3412: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 3413: sumnew+=prevacurrent[(int)agefin][ii][ij];
3414: }
3415: if(sumnew >0.01){ /* At least some value in the prevalence */
3416: for (ii=1;ii<=nlstate+ndeath;ii++){
3417: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 3418: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 3419: }
3420: }else{
3421: for (ii=1;ii<=nlstate+ndeath;ii++){
3422: for (j=1;j<=nlstate+ndeath;j++)
3423: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
3424: }
3425: /* if(sumnew <0.9){ */
3426: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3427: /* } */
3428: }
3429: k3=0.0; /* We put the last diagonal to 0 */
3430: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3431: doldm[ii][ii]= k3;
3432: }
3433: /* End doldm, At the end doldm is diag[(w_i)] */
3434:
1.292 brouard 3435: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
3436: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 3437:
1.292 brouard 3438: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 3439: /* 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 3440: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3441: sumnew=0.;
1.222 brouard 3442: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3443: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3444: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3445: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3446: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3447: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3448: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3449: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3450: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3451: /* }else */
1.268 brouard 3452: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3453: } /*End ii */
3454: } /* 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 */
3455:
1.292 brouard 3456: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 3457: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3458: /* end bmij */
1.266 brouard 3459: return ps; /*pointer is unchanged */
1.218 brouard 3460: }
1.217 brouard 3461: /*************** transition probabilities ***************/
3462:
1.218 brouard 3463: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3464: {
3465: /* According to parameters values stored in x and the covariate's values stored in cov,
3466: computes the probability to be observed in state j being in state i by appying the
3467: model to the ncovmodel covariates (including constant and age).
3468: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3469: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3470: ncth covariate in the global vector x is given by the formula:
3471: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3472: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3473: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3474: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3475: Outputs ps[i][j] the probability to be observed in j being in j according to
3476: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3477: */
3478: double s1, lnpijopii;
3479: /*double t34;*/
3480: int i,j, nc, ii, jj;
3481:
1.234 brouard 3482: for(i=1; i<= nlstate; i++){
3483: for(j=1; j<i;j++){
3484: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3485: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3486: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3487: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3488: }
3489: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3490: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3491: }
3492: for(j=i+1; j<=nlstate+ndeath;j++){
3493: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3494: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3495: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3496: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3497: }
3498: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3499: }
3500: }
3501:
3502: for(i=1; i<= nlstate; i++){
3503: s1=0;
3504: for(j=1; j<i; j++){
3505: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3506: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3507: }
3508: for(j=i+1; j<=nlstate+ndeath; j++){
3509: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3510: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3511: }
3512: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3513: ps[i][i]=1./(s1+1.);
3514: /* Computing other pijs */
3515: for(j=1; j<i; j++)
3516: ps[i][j]= exp(ps[i][j])*ps[i][i];
3517: for(j=i+1; j<=nlstate+ndeath; j++)
3518: ps[i][j]= exp(ps[i][j])*ps[i][i];
3519: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3520: } /* end i */
3521:
3522: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3523: for(jj=1; jj<= nlstate+ndeath; jj++){
3524: ps[ii][jj]=0;
3525: ps[ii][ii]=1;
3526: }
3527: }
1.296 brouard 3528: /* Added for prevbcast */ /* Transposed matrix too */
1.234 brouard 3529: for(jj=1; jj<= nlstate+ndeath; jj++){
3530: s1=0.;
3531: for(ii=1; ii<= nlstate+ndeath; ii++){
3532: s1+=ps[ii][jj];
3533: }
3534: for(ii=1; ii<= nlstate; ii++){
3535: ps[ii][jj]=ps[ii][jj]/s1;
3536: }
3537: }
3538: /* Transposition */
3539: for(jj=1; jj<= nlstate+ndeath; jj++){
3540: for(ii=jj; ii<= nlstate+ndeath; ii++){
3541: s1=ps[ii][jj];
3542: ps[ii][jj]=ps[jj][ii];
3543: ps[jj][ii]=s1;
3544: }
3545: }
3546: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3547: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3548: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3549: /* } */
3550: /* printf("\n "); */
3551: /* } */
3552: /* printf("\n ");printf("%lf ",cov[2]);*/
3553: /*
3554: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3555: goto end;*/
3556: return ps;
1.217 brouard 3557: }
3558:
3559:
1.126 brouard 3560: /**************** Product of 2 matrices ******************/
3561:
1.145 brouard 3562: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3563: {
3564: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3565: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3566: /* in, b, out are matrice of pointers which should have been initialized
3567: before: only the contents of out is modified. The function returns
3568: a pointer to pointers identical to out */
1.145 brouard 3569: int i, j, k;
1.126 brouard 3570: for(i=nrl; i<= nrh; i++)
1.145 brouard 3571: for(k=ncolol; k<=ncoloh; k++){
3572: out[i][k]=0.;
3573: for(j=ncl; j<=nch; j++)
3574: out[i][k] +=in[i][j]*b[j][k];
3575: }
1.126 brouard 3576: return out;
3577: }
3578:
3579:
3580: /************* Higher Matrix Product ***************/
3581:
1.235 brouard 3582: 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 3583: {
1.336 brouard 3584: /* Already optimized with precov.
3585: 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 3586: 'nhstepm*hstepm*stepm' months (i.e. until
3587: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3588: nhstepm*hstepm matrices.
3589: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3590: (typically every 2 years instead of every month which is too big
3591: for the memory).
3592: Model is determined by parameters x and covariates have to be
3593: included manually here.
3594:
3595: */
3596:
1.330 brouard 3597: int i, j, d, h, k, k1;
1.131 brouard 3598: double **out, cov[NCOVMAX+1];
1.126 brouard 3599: double **newm;
1.187 brouard 3600: double agexact;
1.214 brouard 3601: double agebegin, ageend;
1.126 brouard 3602:
3603: /* Hstepm could be zero and should return the unit matrix */
3604: for (i=1;i<=nlstate+ndeath;i++)
3605: for (j=1;j<=nlstate+ndeath;j++){
3606: oldm[i][j]=(i==j ? 1.0 : 0.0);
3607: po[i][j][0]=(i==j ? 1.0 : 0.0);
3608: }
3609: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3610: for(h=1; h <=nhstepm; h++){
3611: for(d=1; d <=hstepm; d++){
3612: newm=savm;
3613: /* Covariates have to be included here again */
3614: cov[1]=1.;
1.214 brouard 3615: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3616: cov[2]=agexact;
1.319 brouard 3617: if(nagesqr==1){
1.227 brouard 3618: cov[3]= agexact*agexact;
1.319 brouard 3619: }
1.330 brouard 3620: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
3621: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
3622: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.332 brouard 3623: if(Typevar[k1]==1){ /* A product with age */
3624: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
3625: }else{
3626: cov[2+nagesqr+k1]=precov[nres][k1];
3627: }
3628: }/* End of loop on model equation */
3629: /* Old code */
3630: /* if( Dummy[k1]==0 && Typevar[k1]==0 ){ /\* Single dummy *\/ */
3631: /* /\* V(Tvarsel)=Tvalsel=Tresult[nres][pos](value); V(Tvresult[nres][pos] (variable): V(variable)=value) *\/ */
3632: /* /\* for (k=1; k<=nsd;k++) { /\\* For single dummy covariates only *\\/ *\/ */
3633: /* /\* /\\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\\/ *\/ */
3634: /* /\* codtabm(ij,k) (1 & (ij-1) >> (k-1))+1 *\/ */
3635: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3636: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3637: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
3638: /* /\* nsd 1 2 3 *\/ /\* Counting single dummies covar fixed or tv *\/ */
3639: /* /\*TvarsD[nsd] 4 3 1 *\/ /\* ID of single dummy cova fixed or timevary*\/ */
3640: /* /\*TvarsDind[k] 2 3 9 *\/ /\* position K of single dummy cova *\/ */
3641: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];or [codtabm(ij,TnsdVar[TvarsD[k]] *\/ */
3642: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
3643: /* /\* 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]])); *\/ */
3644: /* 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); */
3645: /* printf("hpxij new Dummy precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3646: /* }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /\* Single quantitative variables *\/ */
3647: /* /\* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline *\/ */
3648: /* cov[2+nagesqr+k1]=Tqresult[nres][resultmodel[nres][k1]]; */
3649: /* /\* for (k=1; k<=nsq;k++) { /\\* For single varying covariates only *\\/ *\/ */
3650: /* /\* /\\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\\/ *\/ */
3651: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
3652: /* 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]]); */
3653: /* printf("hpxij new Quanti precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3654: /* }else if( Dummy[k1]==2 ){ /\* For dummy with age product *\/ */
3655: /* /\* Tvar[k1] Variable in the age product age*V1 is 1 *\/ */
3656: /* /\* [Tinvresult[nres][V1] is its value in the resultline nres *\/ */
3657: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvar[k1]]*cov[2]; */
3658: /* 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]); */
3659: /* printf("hpxij new Dummy with age product precov[nres=%d][k1=%d]=%.4f * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
3660:
3661: /* /\* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; *\/ */
3662: /* /\* for (k=1; k<=cptcovage;k++){ /\\* For product with age V1+V1*age +V4 +age*V3 *\\/ *\/ */
3663: /* /\* 1+2 Tage[1]=2 TVar[2]=1 Dummy[2]=2, Tage[2]=4 TVar[4]=3 Dummy[4]=3 quant*\/ */
3664: /* /\* *\/ */
1.330 brouard 3665: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3666: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3667: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
1.332 brouard 3668: /* /\*cptcovage=2 1 2 *\/ */
3669: /* /\*Tage[k]= 5 8 *\/ */
3670: /* }else if( Dummy[k1]==3 ){ /\* For quant with age product *\/ */
3671: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
3672: /* 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]]); */
3673: /* printf("hpxij new Quanti with age product precov[nres=%d][k1=%d] * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
3674: /* /\* if(Dummy[Tage[k]]== 2){ /\\* dummy with age *\\/ *\/ */
3675: /* /\* /\\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\\* dummy with age *\\\/ *\\/ *\/ */
3676: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\\/ *\/ */
3677: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\\/ *\/ */
3678: /* /\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\/ */
3679: /* /\* 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); *\/ */
3680: /* /\* } else if(Dummy[Tage[k]]== 3){ /\\* quantitative with age *\\/ *\/ */
3681: /* /\* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; *\/ */
3682: /* /\* } *\/ */
3683: /* /\* 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]); *\/ */
3684: /* }else if(Typevar[k1]==2 ){ /\* For product (not with age) *\/ */
3685: /* /\* for (k=1; k<=cptcovprod;k++){ /\\* For product without age *\\/ *\/ */
3686: /* /\* /\\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\\/ *\/ */
3687: /* /\* /\\* k 1 2 3 4 5 6 7 8 9 *\\/ *\/ */
3688: /* /\* /\\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\\/ *\/ */
3689: /* /\* /\\*cptcovprod=1 1 2 *\\/ *\/ */
3690: /* /\* /\\*Tprod[]= 4 7 *\\/ *\/ */
3691: /* /\* /\\*Tvard[][1] 4 1 *\\/ *\/ */
3692: /* /\* /\\*Tvard[][2] 3 2 *\\/ *\/ */
1.330 brouard 3693:
1.332 brouard 3694: /* /\* 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])]); *\/ */
3695: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3696: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]]; */
3697: /* 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]]); */
3698: /* printf("hpxij new Product no age product precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3699:
3700: /* /\* if(Dummy[Tvardk[k1][1]]==0){ *\/ */
3701: /* /\* if(Dummy[Tvardk[k1][2]]==0){ /\\* Product of dummies *\\/ *\/ */
3702: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3703: /* /\* cov[2+nagesqr+k1]=Tinvresult[nres][Tvardk[k1][1]] * Tinvresult[nres][Tvardk[k1][2]]; *\/ */
3704: /* /\* 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]])]; *\/ */
3705: /* /\* }else{ /\\* Product of dummy by quantitative *\\/ *\/ */
3706: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,TnsdVar[Tvard[k][1]])] * Tqresult[nres][k]; *\/ */
3707: /* /\* cov[2+nagesqr+k1]=Tresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]]; *\/ */
3708: /* /\* } *\/ */
3709: /* /\* }else{ /\\* Product of quantitative by...*\\/ *\/ */
3710: /* /\* if(Dummy[Tvard[k][2]]==0){ /\\* quant by dummy *\\/ *\/ */
3711: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][Tvard[k][1]]; *\\/ *\/ */
3712: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
3713: /* /\* }else{ /\\* Product of two quant *\\/ *\/ */
3714: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\\/ *\/ */
3715: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
3716: /* /\* } *\/ */
3717: /* /\* }/\\*end of products quantitative *\\/ *\/ */
3718: /* }/\*end of products *\/ */
3719: /* } /\* End of loop on model equation *\/ */
1.235 brouard 3720: /* for (k=1; k<=cptcovn;k++) */
3721: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3722: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3723: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3724: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3725: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3726:
3727:
1.126 brouard 3728: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3729: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.319 brouard 3730: /* right multiplication of oldm by the current matrix */
1.126 brouard 3731: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3732: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3733: /* if((int)age == 70){ */
3734: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3735: /* for(i=1; i<=nlstate+ndeath; i++) { */
3736: /* printf("%d pmmij ",i); */
3737: /* for(j=1;j<=nlstate+ndeath;j++) { */
3738: /* printf("%f ",pmmij[i][j]); */
3739: /* } */
3740: /* printf(" oldm "); */
3741: /* for(j=1;j<=nlstate+ndeath;j++) { */
3742: /* printf("%f ",oldm[i][j]); */
3743: /* } */
3744: /* printf("\n"); */
3745: /* } */
3746: /* } */
1.126 brouard 3747: savm=oldm;
3748: oldm=newm;
3749: }
3750: for(i=1; i<=nlstate+ndeath; i++)
3751: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3752: po[i][j][h]=newm[i][j];
3753: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3754: }
1.128 brouard 3755: /*printf("h=%d ",h);*/
1.126 brouard 3756: } /* end h */
1.267 brouard 3757: /* printf("\n H=%d \n",h); */
1.126 brouard 3758: return po;
3759: }
3760:
1.217 brouard 3761: /************* Higher Back Matrix Product ***************/
1.218 brouard 3762: /* 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 3763: 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 3764: {
1.332 brouard 3765: /* For dummy covariates given in each resultline (for historical, computes the corresponding combination ij),
3766: computes the transition matrix starting at age 'age' over
1.217 brouard 3767: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3768: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3769: nhstepm*hstepm matrices.
3770: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3771: (typically every 2 years instead of every month which is too big
1.217 brouard 3772: for the memory).
1.218 brouard 3773: Model is determined by parameters x and covariates have to be
1.266 brouard 3774: included manually here. Then we use a call to bmij(x and cov)
3775: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3776: */
1.217 brouard 3777:
1.332 brouard 3778: int i, j, d, h, k, k1;
1.266 brouard 3779: double **out, cov[NCOVMAX+1], **bmij();
3780: double **newm, ***newmm;
1.217 brouard 3781: double agexact;
3782: double agebegin, ageend;
1.222 brouard 3783: double **oldm, **savm;
1.217 brouard 3784:
1.266 brouard 3785: newmm=po; /* To be saved */
3786: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3787: /* Hstepm could be zero and should return the unit matrix */
3788: for (i=1;i<=nlstate+ndeath;i++)
3789: for (j=1;j<=nlstate+ndeath;j++){
3790: oldm[i][j]=(i==j ? 1.0 : 0.0);
3791: po[i][j][0]=(i==j ? 1.0 : 0.0);
3792: }
3793: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3794: for(h=1; h <=nhstepm; h++){
3795: for(d=1; d <=hstepm; d++){
3796: newm=savm;
3797: /* Covariates have to be included here again */
3798: cov[1]=1.;
1.271 brouard 3799: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3800: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
1.318 brouard 3801: /* Debug */
3802: /* printf("hBxij age=%lf, agexact=%lf\n", age, agexact); */
1.217 brouard 3803: cov[2]=agexact;
1.332 brouard 3804: if(nagesqr==1){
1.222 brouard 3805: cov[3]= agexact*agexact;
1.332 brouard 3806: }
3807: /** New code */
3808: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
3809: if(Typevar[k1]==1){ /* A product with age */
3810: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.325 brouard 3811: }else{
1.332 brouard 3812: cov[2+nagesqr+k1]=precov[nres][k1];
1.325 brouard 3813: }
1.332 brouard 3814: }/* End of loop on model equation */
3815: /** End of new code */
3816: /** This was old code */
3817: /* for (k=1; k<=nsd;k++){ /\* For single dummy covariates only *\//\* cptcovn error *\/ */
3818: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
3819: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
3820: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])];/\* Bug valgrind *\/ */
3821: /* /\* 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)); *\/ */
3822: /* } */
3823: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
3824: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3825: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
3826: /* /\* 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]); *\/ */
3827: /* } */
3828: /* for (k=1; k<=cptcovage;k++){ /\* Should start at cptcovn+1 *\//\* For product with age *\/ */
3829: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age error!!!*\\/ *\/ */
3830: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
3831: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3832: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
3833: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3834: /* } */
3835: /* /\* 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]); *\/ */
3836: /* } */
3837: /* for (k=1; k<=cptcovprod;k++){ /\* Useless because included in cptcovn *\/ */
3838: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])]*nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3839: /* if(Dummy[Tvard[k][1]]==0){ */
3840: /* if(Dummy[Tvard[k][2]]==0){ */
3841: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][1])]; */
3842: /* }else{ */
3843: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3844: /* } */
3845: /* }else{ */
3846: /* if(Dummy[Tvard[k][2]]==0){ */
3847: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3848: /* }else{ */
3849: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3850: /* } */
3851: /* } */
3852: /* } */
3853: /* /\*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*\/ */
3854: /* /\*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*\/ */
3855: /** End of old code */
3856:
1.218 brouard 3857: /* Careful transposed matrix */
1.266 brouard 3858: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3859: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3860: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3861: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.325 brouard 3862: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);/* Bug valgrind */
1.217 brouard 3863: /* if((int)age == 70){ */
3864: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3865: /* for(i=1; i<=nlstate+ndeath; i++) { */
3866: /* printf("%d pmmij ",i); */
3867: /* for(j=1;j<=nlstate+ndeath;j++) { */
3868: /* printf("%f ",pmmij[i][j]); */
3869: /* } */
3870: /* printf(" oldm "); */
3871: /* for(j=1;j<=nlstate+ndeath;j++) { */
3872: /* printf("%f ",oldm[i][j]); */
3873: /* } */
3874: /* printf("\n"); */
3875: /* } */
3876: /* } */
3877: savm=oldm;
3878: oldm=newm;
3879: }
3880: for(i=1; i<=nlstate+ndeath; i++)
3881: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3882: po[i][j][h]=newm[i][j];
1.268 brouard 3883: /* if(h==nhstepm) */
3884: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3885: }
1.268 brouard 3886: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3887: } /* end h */
1.268 brouard 3888: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3889: return po;
3890: }
3891:
3892:
1.162 brouard 3893: #ifdef NLOPT
3894: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3895: double fret;
3896: double *xt;
3897: int j;
3898: myfunc_data *d2 = (myfunc_data *) pd;
3899: /* xt = (p1-1); */
3900: xt=vector(1,n);
3901: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3902:
3903: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3904: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3905: printf("Function = %.12lf ",fret);
3906: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3907: printf("\n");
3908: free_vector(xt,1,n);
3909: return fret;
3910: }
3911: #endif
1.126 brouard 3912:
3913: /*************** log-likelihood *************/
3914: double func( double *x)
3915: {
1.336 brouard 3916: int i, ii, j, k, mi, d, kk, kf=0;
1.226 brouard 3917: int ioffset=0;
1.339 brouard 3918: int ipos=0,iposold=0,ncovv=0;
3919:
1.340 brouard 3920: double cotvarv, cotvarvold;
1.226 brouard 3921: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3922: double **out;
3923: double lli; /* Individual log likelihood */
3924: int s1, s2;
1.228 brouard 3925: 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 3926:
1.226 brouard 3927: double bbh, survp;
3928: double agexact;
1.336 brouard 3929: double agebegin, ageend;
1.226 brouard 3930: /*extern weight */
3931: /* We are differentiating ll according to initial status */
3932: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3933: /*for(i=1;i<imx;i++)
3934: printf(" %d\n",s[4][i]);
3935: */
1.162 brouard 3936:
1.226 brouard 3937: ++countcallfunc;
1.162 brouard 3938:
1.226 brouard 3939: cov[1]=1.;
1.126 brouard 3940:
1.226 brouard 3941: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3942: ioffset=0;
1.226 brouard 3943: if(mle==1){
3944: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3945: /* Computes the values of the ncovmodel covariates of the model
3946: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3947: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3948: to be observed in j being in i according to the model.
3949: */
1.243 brouard 3950: ioffset=2+nagesqr ;
1.233 brouard 3951: /* Fixed */
1.345 ! brouard 3952: for (kf=1; kf<=ncovf;kf++){ /* For each fixed covariate dummy or quant or prod */
1.319 brouard 3953: /* # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi */
3954: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
3955: /* 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 3956: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.336 brouard 3957: 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 3958: /* V1*V2 (7) TvarFind[2]=7, TvarFind[3]=9 */
1.234 brouard 3959: }
1.226 brouard 3960: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
1.319 brouard 3961: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
1.226 brouard 3962: has been calculated etc */
3963: /* For an individual i, wav[i] gives the number of effective waves */
3964: /* We compute the contribution to Likelihood of each effective transition
3965: mw[mi][i] is real wave of the mi th effectve wave */
3966: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3967: s2=s[mw[mi+1][i]][i];
1.341 brouard 3968: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i] because now is moved after nvocol+nqv
1.226 brouard 3969: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3970: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3971: */
1.336 brouard 3972: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
3973: /* Wave varying (but not age varying) */
1.339 brouard 3974: /* 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*\/ */
3975: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; but where is the crossproduct? *\/ */
3976: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
3977: /* } */
1.340 brouard 3978: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age )*/
3979: itv=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
3980: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
1.345 ! brouard 3981: if(FixedV[itv]!=0){ /* Not a fixed covariate */
1.341 brouard 3982: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]][i]; /* cotvar[wav][ncovcol+nqv+iv][i] */
1.340 brouard 3983: }else{ /* fixed covariate */
1.345 ! brouard 3984: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
1.340 brouard 3985: }
1.339 brouard 3986: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 brouard 3987: cotvarvold=cotvarv;
3988: }else{ /* A second product */
3989: cotvarv=cotvarv*cotvarvold;
1.339 brouard 3990: }
3991: iposold=ipos;
1.340 brouard 3992: cov[ioffset+ipos]=cotvarv;
1.234 brouard 3993: }
1.339 brouard 3994: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
3995: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3996: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
3997: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
3998: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
3999: /* 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]); */
4000: /* } */
4001: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
4002: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4003: /* /\* 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]); *\/ */
4004: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
4005: /* } */
4006: /* for products of time varying to be done */
1.234 brouard 4007: for (ii=1;ii<=nlstate+ndeath;ii++)
4008: for (j=1;j<=nlstate+ndeath;j++){
4009: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4010: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4011: }
1.336 brouard 4012:
4013: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4014: 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 4015: for(d=0; d<dh[mi][i]; d++){
4016: newm=savm;
4017: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4018: cov[2]=agexact;
4019: if(nagesqr==1)
4020: cov[3]= agexact*agexact; /* Should be changed here */
4021: for (kk=1; kk<=cptcovage;kk++) {
1.318 brouard 4022: if(!FixedV[Tvar[Tage[kk]]])
4023: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
4024: else
1.341 brouard 4025: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]*agexact; /* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
1.234 brouard 4026: }
4027: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4028: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4029: savm=oldm;
4030: oldm=newm;
4031: } /* end mult */
4032:
4033: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
4034: /* But now since version 0.9 we anticipate for bias at large stepm.
4035: * If stepm is larger than one month (smallest stepm) and if the exact delay
4036: * (in months) between two waves is not a multiple of stepm, we rounded to
4037: * the nearest (and in case of equal distance, to the lowest) interval but now
4038: * we keep into memory the bias bh[mi][i] and also the previous matrix product
4039: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
4040: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 4041: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
4042: * -stepm/2 to stepm/2 .
4043: * For stepm=1 the results are the same as for previous versions of Imach.
4044: * For stepm > 1 the results are less biased than in previous versions.
4045: */
1.234 brouard 4046: s1=s[mw[mi][i]][i];
4047: s2=s[mw[mi+1][i]][i];
4048: bbh=(double)bh[mi][i]/(double)stepm;
4049: /* bias bh is positive if real duration
4050: * is higher than the multiple of stepm and negative otherwise.
4051: */
4052: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
4053: if( s2 > nlstate){
4054: /* i.e. if s2 is a death state and if the date of death is known
4055: then the contribution to the likelihood is the probability to
4056: die between last step unit time and current step unit time,
4057: which is also equal to probability to die before dh
4058: minus probability to die before dh-stepm .
4059: In version up to 0.92 likelihood was computed
4060: as if date of death was unknown. Death was treated as any other
4061: health state: the date of the interview describes the actual state
4062: and not the date of a change in health state. The former idea was
4063: to consider that at each interview the state was recorded
4064: (healthy, disable or death) and IMaCh was corrected; but when we
4065: introduced the exact date of death then we should have modified
4066: the contribution of an exact death to the likelihood. This new
4067: contribution is smaller and very dependent of the step unit
4068: stepm. It is no more the probability to die between last interview
4069: and month of death but the probability to survive from last
4070: interview up to one month before death multiplied by the
4071: probability to die within a month. Thanks to Chris
4072: Jackson for correcting this bug. Former versions increased
4073: mortality artificially. The bad side is that we add another loop
4074: which slows down the processing. The difference can be up to 10%
4075: lower mortality.
4076: */
4077: /* If, at the beginning of the maximization mostly, the
4078: cumulative probability or probability to be dead is
4079: constant (ie = 1) over time d, the difference is equal to
4080: 0. out[s1][3] = savm[s1][3]: probability, being at state
4081: s1 at precedent wave, to be dead a month before current
4082: wave is equal to probability, being at state s1 at
4083: precedent wave, to be dead at mont of the current
4084: wave. Then the observed probability (that this person died)
4085: is null according to current estimated parameter. In fact,
4086: it should be very low but not zero otherwise the log go to
4087: infinity.
4088: */
1.183 brouard 4089: /* #ifdef INFINITYORIGINAL */
4090: /* lli=log(out[s1][s2] - savm[s1][s2]); */
4091: /* #else */
4092: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
4093: /* lli=log(mytinydouble); */
4094: /* else */
4095: /* lli=log(out[s1][s2] - savm[s1][s2]); */
4096: /* #endif */
1.226 brouard 4097: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4098:
1.226 brouard 4099: } else if ( s2==-1 ) { /* alive */
4100: for (j=1,survp=0. ; j<=nlstate; j++)
4101: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4102: /*survp += out[s1][j]; */
4103: lli= log(survp);
4104: }
1.336 brouard 4105: /* else if (s2==-4) { */
4106: /* for (j=3,survp=0. ; j<=nlstate; j++) */
4107: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
4108: /* lli= log(survp); */
4109: /* } */
4110: /* else if (s2==-5) { */
4111: /* for (j=1,survp=0. ; j<=2; j++) */
4112: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
4113: /* lli= log(survp); */
4114: /* } */
1.226 brouard 4115: else{
4116: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4117: /* 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 */
4118: }
4119: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
4120: /*if(lli ==000.0)*/
1.340 brouard 4121: /* printf("num[i], i=%d, bbh= %f lli=%f savm=%f out=%f %d\n",bbh,lli,savm[s1][s2], out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]],i); */
1.226 brouard 4122: ipmx +=1;
4123: sw += weight[i];
4124: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4125: /* if (lli < log(mytinydouble)){ */
4126: /* 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); */
4127: /* 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]); */
4128: /* } */
4129: } /* end of wave */
4130: } /* end of individual */
4131: } else if(mle==2){
4132: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.319 brouard 4133: ioffset=2+nagesqr ;
4134: for (k=1; k<=ncovf;k++)
4135: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];
1.226 brouard 4136: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 4137: for(k=1; k <= ncovv ; k++){
1.341 brouard 4138: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; /* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
1.319 brouard 4139: }
1.226 brouard 4140: for (ii=1;ii<=nlstate+ndeath;ii++)
4141: for (j=1;j<=nlstate+ndeath;j++){
4142: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4143: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4144: }
4145: for(d=0; d<=dh[mi][i]; d++){
4146: newm=savm;
4147: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4148: cov[2]=agexact;
4149: if(nagesqr==1)
4150: cov[3]= agexact*agexact;
4151: for (kk=1; kk<=cptcovage;kk++) {
4152: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4153: }
4154: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4155: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4156: savm=oldm;
4157: oldm=newm;
4158: } /* end mult */
4159:
4160: s1=s[mw[mi][i]][i];
4161: s2=s[mw[mi+1][i]][i];
4162: bbh=(double)bh[mi][i]/(double)stepm;
4163: 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 */
4164: ipmx +=1;
4165: sw += weight[i];
4166: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4167: } /* end of wave */
4168: } /* end of individual */
4169: } else if(mle==3){ /* exponential inter-extrapolation */
4170: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4171: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4172: for(mi=1; mi<= wav[i]-1; mi++){
4173: for (ii=1;ii<=nlstate+ndeath;ii++)
4174: for (j=1;j<=nlstate+ndeath;j++){
4175: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4176: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4177: }
4178: for(d=0; d<dh[mi][i]; d++){
4179: newm=savm;
4180: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4181: cov[2]=agexact;
4182: if(nagesqr==1)
4183: cov[3]= agexact*agexact;
4184: for (kk=1; kk<=cptcovage;kk++) {
1.340 brouard 4185: if(!FixedV[Tvar[Tage[kk]]])
4186: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
4187: else
1.341 brouard 4188: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]*agexact; /* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
1.226 brouard 4189: }
4190: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4191: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4192: savm=oldm;
4193: oldm=newm;
4194: } /* end mult */
4195:
4196: s1=s[mw[mi][i]][i];
4197: s2=s[mw[mi+1][i]][i];
4198: bbh=(double)bh[mi][i]/(double)stepm;
4199: 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 */
4200: ipmx +=1;
4201: sw += weight[i];
4202: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4203: } /* end of wave */
4204: } /* end of individual */
4205: }else if (mle==4){ /* ml=4 no inter-extrapolation */
4206: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4207: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4208: for(mi=1; mi<= wav[i]-1; mi++){
4209: for (ii=1;ii<=nlstate+ndeath;ii++)
4210: for (j=1;j<=nlstate+ndeath;j++){
4211: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4212: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4213: }
4214: for(d=0; d<dh[mi][i]; d++){
4215: newm=savm;
4216: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4217: cov[2]=agexact;
4218: if(nagesqr==1)
4219: cov[3]= agexact*agexact;
4220: for (kk=1; kk<=cptcovage;kk++) {
4221: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4222: }
1.126 brouard 4223:
1.226 brouard 4224: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4225: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4226: savm=oldm;
4227: oldm=newm;
4228: } /* end mult */
4229:
4230: s1=s[mw[mi][i]][i];
4231: s2=s[mw[mi+1][i]][i];
4232: if( s2 > nlstate){
4233: lli=log(out[s1][s2] - savm[s1][s2]);
4234: } else if ( s2==-1 ) { /* alive */
4235: for (j=1,survp=0. ; j<=nlstate; j++)
4236: survp += out[s1][j];
4237: lli= log(survp);
4238: }else{
4239: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4240: }
4241: ipmx +=1;
4242: sw += weight[i];
4243: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.343 brouard 4244: /* printf("num[i]=%09ld, i=%6d s1=%1d s2=%1d mi=%1d mw=%1d dh=%3d prob=%10.6f w=%6.4f out=%10.6f sav=%10.6f\n",num[i],i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2])); */
1.226 brouard 4245: } /* end of wave */
4246: } /* end of individual */
4247: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
4248: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4249: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4250: for(mi=1; mi<= wav[i]-1; mi++){
4251: for (ii=1;ii<=nlstate+ndeath;ii++)
4252: for (j=1;j<=nlstate+ndeath;j++){
4253: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4254: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4255: }
4256: for(d=0; d<dh[mi][i]; d++){
4257: newm=savm;
4258: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4259: cov[2]=agexact;
4260: if(nagesqr==1)
4261: cov[3]= agexact*agexact;
4262: for (kk=1; kk<=cptcovage;kk++) {
1.340 brouard 4263: if(!FixedV[Tvar[Tage[kk]]])
4264: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
4265: else
1.341 brouard 4266: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]*agexact; /* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
1.226 brouard 4267: }
1.126 brouard 4268:
1.226 brouard 4269: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4270: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4271: savm=oldm;
4272: oldm=newm;
4273: } /* end mult */
4274:
4275: s1=s[mw[mi][i]][i];
4276: s2=s[mw[mi+1][i]][i];
4277: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4278: ipmx +=1;
4279: sw += weight[i];
4280: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4281: /*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]);*/
4282: } /* end of wave */
4283: } /* end of individual */
4284: } /* End of if */
4285: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
4286: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
4287: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4288: return -l;
1.126 brouard 4289: }
4290:
4291: /*************** log-likelihood *************/
4292: double funcone( double *x)
4293: {
1.228 brouard 4294: /* Same as func but slower because of a lot of printf and if */
1.335 brouard 4295: int i, ii, j, k, mi, d, kk, kf=0;
1.228 brouard 4296: int ioffset=0;
1.339 brouard 4297: int ipos=0,iposold=0,ncovv=0;
4298:
1.340 brouard 4299: double cotvarv, cotvarvold;
1.131 brouard 4300: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 4301: double **out;
4302: double lli; /* Individual log likelihood */
4303: double llt;
4304: int s1, s2;
1.228 brouard 4305: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
4306:
1.126 brouard 4307: double bbh, survp;
1.187 brouard 4308: double agexact;
1.214 brouard 4309: double agebegin, ageend;
1.126 brouard 4310: /*extern weight */
4311: /* We are differentiating ll according to initial status */
4312: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
4313: /*for(i=1;i<imx;i++)
4314: printf(" %d\n",s[4][i]);
4315: */
4316: cov[1]=1.;
4317:
4318: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 4319: ioffset=0;
4320: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.336 brouard 4321: /* Computes the values of the ncovmodel covariates of the model
4322: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
4323: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
4324: to be observed in j being in i according to the model.
4325: */
1.243 brouard 4326: /* ioffset=2+nagesqr+cptcovage; */
4327: ioffset=2+nagesqr;
1.232 brouard 4328: /* Fixed */
1.224 brouard 4329: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 4330: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
1.335 brouard 4331: 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 4332: /* printf("Debug3 TvarFind[%d]=%d",kf, TvarFind[kf]); */
4333: /* printf(" Tvar[TvarFind[kf]]=%d", Tvar[TvarFind[kf]]); */
4334: /* printf(" i=%d covar[Tvar[TvarFind[kf]]][i]=%f\n",i,covar[Tvar[TvarFind[kf]]][i]); */
1.335 brouard 4335: 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 4336: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
4337: /* cov[2+6]=covar[Tvar[6]][i]; */
4338: /* cov[2+6]=covar[2][i]; V2 */
4339: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
4340: /* cov[2+7]=covar[Tvar[7]][i]; */
4341: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
4342: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
4343: /* cov[2+9]=covar[Tvar[9]][i]; */
4344: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 4345: }
1.336 brouard 4346: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
4347: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
4348: has been calculated etc */
4349: /* For an individual i, wav[i] gives the number of effective waves */
4350: /* We compute the contribution to Likelihood of each effective transition
4351: mw[mi][i] is real wave of the mi th effectve wave */
4352: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
4353: s2=s[mw[mi+1][i]][i];
1.341 brouard 4354: And the iv th varying covariate in the DATA is the cotvar[mw[mi+1][i]][ncovcol+nqv+iv][i]
1.336 brouard 4355: */
4356: /* This part may be useless now because everythin should be in covar */
1.232 brouard 4357: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
4358: /* 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?)*\/ */
4359: /* } */
1.231 brouard 4360: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
4361: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
4362: /* } */
1.225 brouard 4363:
1.233 brouard 4364:
4365: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.339 brouard 4366: /* 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 */
4367: /* for(k=1; k <= ncovv ; k++){ /\* Varying covariates (single and product but no age )*\/ */
4368: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; *\/ */
4369: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
4370: /* } */
4371:
4372: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
4373: /* model V1+V3+age*V1+age*V3+V1*V3 */
4374: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
4375: /* TvarVV[1]=V3 (first time varying in the model equation, TvarVV[2]=V1 (in V1*V3) TvarVV[3]=3(V3) */
4376: /* We need the position of the time varying or product in the model */
4377: /* 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 */
4378: /* TvarVV gives the variable name */
1.340 brouard 4379: /* Other example V1 + V3 + V5 + age*V1 + age*V3 + age*V5 + V1*V3 + V3*V5 + V1*V5
4380: * k= 1 2 3 4 5 6 7 8 9
4381: * varying 1 2 3 4 5
4382: * ncovv 1 2 3 4 5 6 7 8
1.343 brouard 4383: * TvarVV[ncovv] V3 5 1 3 3 5 1 5
1.340 brouard 4384: * TvarVVind 2 3 7 7 8 8 9 9
4385: * TvarFind[k] 1 0 0 0 0 0 0 0 0
4386: */
1.345 ! brouard 4387: /* Other model ncovcol=5 nqv=0 ntv=3 nqtv=0 nlstate=3
! 4388: /* V2 V3 V4 are fixed V6 V7 are timevarying so V8 and V5 are not in the model and product column will start at 9 Tvar[4]=6
! 4389: * FixedV[ncovcol+qv+ntv+nqtv] V5
! 4390: * V1 V2 V3 V4 V5 V6 V7 V8
! 4391: * 0 0 0 0 0 1 1 1
! 4392: * model= V2 + V3 + V4 + V6 + V7 + V6*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
! 4393: * kmodel 1 2 3 4 5 6 7 8 9 10 11
! 4394: * ncovf 1 2 3
! 4395: * ncovvt=14 1 2 3 4 5 6 7 8 9 10 11 12 13 14
! 4396: * TvarVV[1]@14 = itv {6, 7, 6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
! 4397: * TvarVVind[1]@14= {4, 5, 6, 6, 7, 7, 8, 8, 9, 9, 10, 10, 11, 11}
! 4398: * TvarFind[1]@14= {1, 2, 3, 0 <repeats 12 times>}
! 4399: * Tvar[1]@20= {2, 3, 4, 6, 7, 9, 10, 11, 12, 13, 14}
! 4400: * TvarFind[itv] 0 0 0
! 4401: * FixedV[itv] 1 1 1 0 1 0 1 0 1 0 0
! 4402: * Tvar[TvarFind[ncovf]]=[1]=2 [2]=3 [4]=4
! 4403: * Tvar[TvarFind[itv]] [0]=? ?ncovv 1 à ncovvt]
! 4404: * Not a fixed cotvar[mw][itv][i] 6 7 6 2 7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
! 4405: * fixed covar[itv] [6] [7] [6][2]
! 4406: */
! 4407:
1.340 brouard 4408: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age) including individual from products */
1.345 ! brouard 4409: itv=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product */
1.340 brouard 4410: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
1.345 ! brouard 4411: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
! 4412: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
! 4413: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
1.340 brouard 4414: }else{ /* fixed covariate */
1.345 ! brouard 4415: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
! 4416: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
1.340 brouard 4417: }
1.339 brouard 4418: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 brouard 4419: cotvarvold=cotvarv;
4420: }else{ /* A second product */
4421: cotvarv=cotvarv*cotvarvold;
1.339 brouard 4422: }
4423: iposold=ipos;
1.340 brouard 4424: cov[ioffset+ipos]=cotvarv;
1.339 brouard 4425: /* For products */
4426: }
4427: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates single *\/ */
4428: /* iv=TvarVDind[itv]; /\* iv, position in the model equation of time varying covariate itv *\/ */
4429: /* /\* "V1+V3+age*V1+age*V3+V1*V3" with V3 time varying *\/ */
4430: /* /\* 1 2 3 4 5 *\/ */
4431: /* /\*itv 1 *\/ */
4432: /* /\* TvarVInd[1]= 2 *\/ */
4433: /* /\* iv= Tvar[Tmodelind[itv]]-ncovcol-nqv; /\\* Counting the # varying covariate from 1 to ntveff *\\/ *\/ */
4434: /* /\* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; *\/ */
4435: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; *\/ */
4436: /* /\* k=ioffset-2-nagesqr-cptcovage+itv; /\\* position in simple model *\\/ *\/ */
4437: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; *\/ */
4438: /* cov[ioffset+iv]=cotvar[mw[mi][i]][itv][i]; */
4439: /* /\* 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]); *\/ */
4440: /* } */
1.232 brouard 4441: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 4442: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4443: /* /\* 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]); *\/ */
4444: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 4445: /* } */
1.126 brouard 4446: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 4447: for (j=1;j<=nlstate+ndeath;j++){
4448: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4449: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4450: }
1.214 brouard 4451:
4452: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4453: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
4454: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 4455: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 4456: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
4457: and mw[mi+1][i]. dh depends on stepm.*/
4458: newm=savm;
1.247 brouard 4459: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 4460: cov[2]=agexact;
4461: if(nagesqr==1)
4462: cov[3]= agexact*agexact;
4463: for (kk=1; kk<=cptcovage;kk++) {
4464: if(!FixedV[Tvar[Tage[kk]]])
4465: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4466: else
1.341 brouard 4467: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]*agexact; /* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
1.242 brouard 4468: }
4469: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
4470: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
4471: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4472: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4473: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
4474: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
4475: savm=oldm;
4476: oldm=newm;
1.126 brouard 4477: } /* end mult */
1.336 brouard 4478: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
4479: /* But now since version 0.9 we anticipate for bias at large stepm.
4480: * If stepm is larger than one month (smallest stepm) and if the exact delay
4481: * (in months) between two waves is not a multiple of stepm, we rounded to
4482: * the nearest (and in case of equal distance, to the lowest) interval but now
4483: * we keep into memory the bias bh[mi][i] and also the previous matrix product
4484: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
4485: * probability in order to take into account the bias as a fraction of the way
4486: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
4487: * -stepm/2 to stepm/2 .
4488: * For stepm=1 the results are the same as for previous versions of Imach.
4489: * For stepm > 1 the results are less biased than in previous versions.
4490: */
1.126 brouard 4491: s1=s[mw[mi][i]][i];
4492: s2=s[mw[mi+1][i]][i];
1.217 brouard 4493: /* if(s2==-1){ */
1.268 brouard 4494: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 4495: /* /\* exit(1); *\/ */
4496: /* } */
1.126 brouard 4497: bbh=(double)bh[mi][i]/(double)stepm;
4498: /* bias is positive if real duration
4499: * is higher than the multiple of stepm and negative otherwise.
4500: */
4501: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 4502: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4503: } else if ( s2==-1 ) { /* alive */
1.242 brouard 4504: for (j=1,survp=0. ; j<=nlstate; j++)
4505: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4506: lli= log(survp);
1.126 brouard 4507: }else if (mle==1){
1.242 brouard 4508: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 4509: } else if(mle==2){
1.242 brouard 4510: 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 4511: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 4512: 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 4513: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 4514: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 4515: } else{ /* mle=0 back to 1 */
1.242 brouard 4516: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4517: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 4518: } /* End of if */
4519: ipmx +=1;
4520: sw += weight[i];
4521: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.342 brouard 4522: /* Printing covariates values for each contribution for checking */
1.343 brouard 4523: /* printf("num[i]=%09ld, i=%6d s1=%1d s2=%1d mi=%1d mw=%1d dh=%3d prob=%10.6f w=%6.4f out=%10.6f sav=%10.6f\n",num[i],i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2])); */
1.126 brouard 4524: if(globpr){
1.246 brouard 4525: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 4526: %11.6f %11.6f %11.6f ", \
1.242 brouard 4527: 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 4528: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.343 brouard 4529: /* printf("%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\ */
4530: /* %11.6f %11.6f %11.6f ", \ */
4531: /* num[i], agebegin, ageend, i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],weight[i]*gipmx/gsw, */
4532: /* 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2])); */
1.242 brouard 4533: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
4534: llt +=ll[k]*gipmx/gsw;
4535: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
1.335 brouard 4536: /* printf(" %10.6f",-ll[k]*gipmx/gsw); */
1.242 brouard 4537: }
1.343 brouard 4538: fprintf(ficresilk," %10.6f ", -llt);
1.335 brouard 4539: /* printf(" %10.6f\n", -llt); */
1.342 brouard 4540: /* if(debugILK){ /\* debugILK is set by a #d in a comment line *\/ */
1.343 brouard 4541: /* fprintf(ficresilk,"%09ld ", num[i]); */ /* not necessary */
4542: for (kf=1; kf<=ncovf;kf++){ /* Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */
4543: fprintf(ficresilk," %g",covar[Tvar[TvarFind[kf]]][i]);
4544: }
4545: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age) including individual from products */
4546: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4547: if(ipos!=iposold){ /* Not a product or first of a product */
4548: fprintf(ficresilk," %g",cov[ioffset+ipos]);
4549: /* printf(" %g",cov[ioffset+ipos]); */
4550: }else{
4551: fprintf(ficresilk,"*");
4552: /* printf("*"); */
1.342 brouard 4553: }
1.343 brouard 4554: iposold=ipos;
4555: }
4556: for (kk=1; kk<=cptcovage;kk++) {
4557: if(!FixedV[Tvar[Tage[kk]]]){
4558: fprintf(ficresilk," %g*age",covar[Tvar[Tage[kk]]][i]);
4559: /* printf(" %g*age",covar[Tvar[Tage[kk]]][i]); */
4560: }else{
4561: fprintf(ficresilk," %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
4562: /* printf(" %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */
1.342 brouard 4563: }
1.343 brouard 4564: }
4565: /* printf("\n"); */
1.342 brouard 4566: /* } /\* End debugILK *\/ */
4567: fprintf(ficresilk,"\n");
4568: } /* End if globpr */
1.335 brouard 4569: } /* end of wave */
4570: } /* end of individual */
4571: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
1.232 brouard 4572: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
1.335 brouard 4573: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4574: if(globpr==0){ /* First time we count the contributions and weights */
4575: gipmx=ipmx;
4576: gsw=sw;
4577: }
1.343 brouard 4578: return -l;
1.126 brouard 4579: }
4580:
4581:
4582: /*************** function likelione ***********/
1.292 brouard 4583: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 4584: {
4585: /* This routine should help understanding what is done with
4586: the selection of individuals/waves and
4587: to check the exact contribution to the likelihood.
4588: Plotting could be done.
1.342 brouard 4589: */
4590: void pstamp(FILE *ficres);
1.343 brouard 4591: int k, kf, kk, kvar, ncovv, iposold, ipos;
1.126 brouard 4592:
4593: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 4594: strcpy(fileresilk,"ILK_");
1.202 brouard 4595: strcat(fileresilk,fileresu);
1.126 brouard 4596: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
4597: printf("Problem with resultfile: %s\n", fileresilk);
4598: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
4599: }
1.342 brouard 4600: pstamp(ficresilk);fprintf(ficresilk,"# model=1+age+%s\n",model);
1.214 brouard 4601: 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");
4602: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 4603: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
4604: for(k=1; k<=nlstate; k++)
4605: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
1.342 brouard 4606: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total) ");
4607:
4608: /* if(debugILK){ /\* debugILK is set by a #d in a comment line *\/ */
4609: for(kf=1;kf <= ncovf; kf++){
4610: fprintf(ficresilk,"V%d",Tvar[TvarFind[kf]]);
4611: /* printf("V%d",Tvar[TvarFind[kf]]); */
4612: }
4613: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){
1.343 brouard 4614: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
1.342 brouard 4615: if(ipos!=iposold){ /* Not a product or first of a product */
4616: /* printf(" %d",ipos); */
4617: fprintf(ficresilk," V%d",TvarVV[ncovv]);
4618: }else{
4619: /* printf("*"); */
4620: fprintf(ficresilk,"*");
1.343 brouard 4621: }
1.342 brouard 4622: iposold=ipos;
4623: }
4624: for (kk=1; kk<=cptcovage;kk++) {
4625: if(!FixedV[Tvar[Tage[kk]]]){
4626: /* printf(" %d*age(Fixed)",Tvar[Tage[kk]]); */
4627: fprintf(ficresilk," %d*age(Fixed)",Tvar[Tage[kk]]);
4628: }else{
4629: fprintf(ficresilk," %d*age(Varying)",Tvar[Tage[kk]]);/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
4630: /* printf(" %d*age(Varying)",Tvar[Tage[kk]]);/\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */
4631: }
4632: }
4633: /* } /\* End if debugILK *\/ */
4634: /* printf("\n"); */
4635: fprintf(ficresilk,"\n");
4636: } /* End glogpri */
1.126 brouard 4637:
1.292 brouard 4638: *fretone=(*func)(p);
1.126 brouard 4639: if(*globpri !=0){
4640: fclose(ficresilk);
1.205 brouard 4641: if (mle ==0)
4642: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
4643: else if(mle >=1)
4644: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
4645: 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 4646: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 4647:
1.207 brouard 4648: fprintf(fichtm,"<br>- The function drawn is -2Log(L) in Log scale: by state of origin <a href=\"%s-ori.png\">%s-ori.png</a><br> \
1.343 brouard 4649: <img src=\"%s-ori.png\">\n",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4650: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.343 brouard 4651: <img src=\"%s-dest.png\">\n",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
4652:
4653: for (k=1; k<= nlstate ; k++) {
4654: fprintf(fichtm,"<br>- Probability p<sub>%dj</sub> by origin %d and destination j. Dot's sizes are related to corresponding weight: <a href=\"%s-p%dj.png\">%s-p%dj.png</a><br>\n \
4655: <img src=\"%s-p%dj.png\">\n",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
4656: for(kf=1; kf <= ncovf; kf++){ /* For each simple dummy covariate of the model */
4657: /* kvar=Tvar[TvarFind[kf]]; */ /* variable */
4658: fprintf(fichtm,"<br>- Probability p<sub>%dj</sub> by origin %d and destination j with colored covariate V%d. Same dot size of all points but with a different color for transitions with dummy variable V%d=1 at beginning of transition (keeping former color for V%d=0): <a href=\"%s-p%dj.png\">%s-p%dj.png</a><br> \
4659: <img src=\"%s-p%dj-%d.png\">",k,k,Tvar[TvarFind[kf]],Tvar[TvarFind[kf]],Tvar[TvarFind[kf]],subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,Tvar[TvarFind[kf]]);
4660: }
4661: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Loop on the time varying extended covariates (with extension of Vn*Vm */
4662: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
4663: kvar=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
4664: /* printf("DebugILK fichtm ncovv=%d, kvar=TvarVV[ncovv]=V%d, ipos=TvarVVind[ncovv]=%d, Dummy[ipos]=%d, Typevar[ipos]=%d\n", ncovv,kvar,ipos,Dummy[ipos],Typevar[ipos]); */
4665: if(ipos!=iposold){ /* Not a product or first of a product */
4666: /* fprintf(ficresilk," V%d",TvarVV[ncovv]); */
4667: /* printf(" DebugILK fichtm ipos=%d != iposold=%d\n", ipos, iposold); */
4668: if(Dummy[ipos]==0 && Typevar[ipos]==0){ /* Only if dummy time varying: Dummy(0, 1=quant singor prod without age,2 dummy*age, 3quant*age) Typevar (0 single, 1=*age,2=Vn*vm) */
4669: fprintf(fichtm,"<br>- Probability p<sub>%dj</sub> by origin %d and destination j with colored time varying dummy covariate V%d. Same dot size of all points but with a different color for transitions with dummy variable V%d=1 at beginning of transition (keeping former color for V%d=0): <a href=\"%s-p%dj.png\">%s-p%dj.png</a><br> \
4670: <img src=\"%s-p%dj-%d.png\">",k,k,kvar,kvar,kvar,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,kvar);
4671: } /* End only for dummies time varying (single?) */
4672: }else{ /* Useless product */
4673: /* printf("*"); */
4674: /* fprintf(ficresilk,"*"); */
4675: }
4676: iposold=ipos;
4677: } /* For each time varying covariate */
4678: } /* End loop on states */
4679:
4680: /* if(debugILK){ */
4681: /* for(kf=1; kf <= ncovf; kf++){ /\* For each simple dummy covariate of the model *\/ */
4682: /* /\* kvar=Tvar[TvarFind[kf]]; *\/ /\* variable *\/ */
4683: /* for (k=1; k<= nlstate ; k++) { */
4684: /* fprintf(fichtm,"<br>- Probability p<sub>%dj</sub> by origin %d and destination j with colored covariate V%. Same dot size of all points but with a different color for transitions with dummy variable V%d=1 at beginning of transition (keeping former color for V%d=0): <a href=\"%s-p%dj.png\">%s-p%dj.png</a><br> \ */
4685: /* <img src=\"%s-p%dj-%d.png\">",k,k,Tvar[TvarFind[kf]],Tvar[TvarFind[kf]],Tvar[TvarFind[kf]],subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,Tvar[TvarFind[kf]]); */
4686: /* } */
4687: /* } */
4688: /* for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /\* Loop on the time varying extended covariates (with extension of Vn*Vm *\/ */
4689: /* ipos=TvarVVind[ncovv]; /\* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate *\/ */
4690: /* kvar=TvarVV[ncovv]; /\* TvarVV={3, 1, 3} gives the name of each varying covariate *\/ */
4691: /* /\* printf("DebugILK fichtm ncovv=%d, kvar=TvarVV[ncovv]=V%d, ipos=TvarVVind[ncovv]=%d, Dummy[ipos]=%d, Typevar[ipos]=%d\n", ncovv,kvar,ipos,Dummy[ipos],Typevar[ipos]); *\/ */
4692: /* if(ipos!=iposold){ /\* Not a product or first of a product *\/ */
4693: /* /\* fprintf(ficresilk," V%d",TvarVV[ncovv]); *\/ */
4694: /* /\* printf(" DebugILK fichtm ipos=%d != iposold=%d\n", ipos, iposold); *\/ */
4695: /* if(Dummy[ipos]==0 && Typevar[ipos]==0){ /\* Only if dummy time varying: Dummy(0, 1=quant singor prod without age,2 dummy*age, 3quant*age) Typevar (0 single, 1=*age,2=Vn*vm) *\/ */
4696: /* for (k=1; k<= nlstate ; k++) { */
4697: /* fprintf(fichtm,"<br>- Probability p<sub>%dj</sub> by origin %d and destination j. Same dot size of all points but with a different color for transitions with dummy variable V%d=1 at beginning of transition (keeping former color for V%d=0): <a href=\"%s-p%dj.png\">%s-p%dj.png</a><br> \ */
4698: /* <img src=\"%s-p%dj-%d.png\">",k,k,kvar,kvar,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,kvar); */
4699: /* } /\* End state *\/ */
4700: /* } /\* End only for dummies time varying (single?) *\/ */
4701: /* }else{ /\* Useless product *\/ */
4702: /* /\* printf("*"); *\/ */
4703: /* /\* fprintf(ficresilk,"*"); *\/ */
4704: /* } */
4705: /* iposold=ipos; */
4706: /* } /\* For each time varying covariate *\/ */
4707: /* }/\* End debugILK *\/ */
1.207 brouard 4708: fflush(fichtm);
1.343 brouard 4709: }/* End globpri */
1.126 brouard 4710: return;
4711: }
4712:
4713:
4714: /*********** Maximum Likelihood Estimation ***************/
4715:
4716: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
4717: {
1.319 brouard 4718: int i,j,k, jk, jkk=0, iter=0;
1.126 brouard 4719: double **xi;
4720: double fret;
4721: double fretone; /* Only one call to likelihood */
4722: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 4723:
4724: #ifdef NLOPT
4725: int creturn;
4726: nlopt_opt opt;
4727: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
4728: double *lb;
4729: double minf; /* the minimum objective value, upon return */
4730: double * p1; /* Shifted parameters from 0 instead of 1 */
4731: myfunc_data dinst, *d = &dinst;
4732: #endif
4733:
4734:
1.126 brouard 4735: xi=matrix(1,npar,1,npar);
4736: for (i=1;i<=npar;i++)
4737: for (j=1;j<=npar;j++)
4738: xi[i][j]=(i==j ? 1.0 : 0.0);
4739: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 4740: strcpy(filerespow,"POW_");
1.126 brouard 4741: strcat(filerespow,fileres);
4742: if((ficrespow=fopen(filerespow,"w"))==NULL) {
4743: printf("Problem with resultfile: %s\n", filerespow);
4744: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
4745: }
4746: fprintf(ficrespow,"# Powell\n# iter -2*LL");
4747: for (i=1;i<=nlstate;i++)
4748: for(j=1;j<=nlstate+ndeath;j++)
4749: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
4750: fprintf(ficrespow,"\n");
1.162 brouard 4751: #ifdef POWELL
1.319 brouard 4752: #ifdef LINMINORIGINAL
4753: #else /* LINMINORIGINAL */
4754:
4755: flatdir=ivector(1,npar);
4756: for (j=1;j<=npar;j++) flatdir[j]=0;
4757: #endif /*LINMINORIGINAL */
4758:
4759: #ifdef FLATSUP
4760: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4761: /* reorganizing p by suppressing flat directions */
4762: for(i=1, jk=1; i <=nlstate; i++){
4763: for(k=1; k <=(nlstate+ndeath); k++){
4764: if (k != i) {
4765: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4766: if(flatdir[jk]==1){
4767: printf(" To be skipped %d%d flatdir[%d]=%d ",i,k,jk, flatdir[jk]);
4768: }
4769: for(j=1; j <=ncovmodel; j++){
4770: printf("%12.7f ",p[jk]);
4771: jk++;
4772: }
4773: printf("\n");
4774: }
4775: }
4776: }
4777: /* skipping */
4778: /* for(i=1, jk=1, jkk=1;(flatdir[jk]==0)&& (i <=nlstate); i++){ */
4779: for(i=1, jk=1, jkk=1;i <=nlstate; i++){
4780: for(k=1; k <=(nlstate+ndeath); k++){
4781: if (k != i) {
4782: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4783: if(flatdir[jk]==1){
4784: printf(" To be skipped %d%d flatdir[%d]=%d jk=%d p[%d] ",i,k,jk, flatdir[jk],jk, jk);
4785: for(j=1; j <=ncovmodel; jk++,j++){
4786: printf(" p[%d]=%12.7f",jk, p[jk]);
4787: /*q[jjk]=p[jk];*/
4788: }
4789: }else{
4790: printf(" To be kept %d%d flatdir[%d]=%d jk=%d q[%d]=p[%d] ",i,k,jk, flatdir[jk],jk, jkk, jk);
4791: for(j=1; j <=ncovmodel; jk++,jkk++,j++){
4792: printf(" p[%d]=%12.7f=q[%d]",jk, p[jk],jkk);
4793: /*q[jjk]=p[jk];*/
4794: }
4795: }
4796: printf("\n");
4797: }
4798: fflush(stdout);
4799: }
4800: }
4801: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4802: #else /* FLATSUP */
1.126 brouard 4803: powell(p,xi,npar,ftol,&iter,&fret,func);
1.319 brouard 4804: #endif /* FLATSUP */
4805:
4806: #ifdef LINMINORIGINAL
4807: #else
4808: free_ivector(flatdir,1,npar);
4809: #endif /* LINMINORIGINAL*/
4810: #endif /* POWELL */
1.126 brouard 4811:
1.162 brouard 4812: #ifdef NLOPT
4813: #ifdef NEWUOA
4814: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
4815: #else
4816: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
4817: #endif
4818: lb=vector(0,npar-1);
4819: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
4820: nlopt_set_lower_bounds(opt, lb);
4821: nlopt_set_initial_step1(opt, 0.1);
4822:
4823: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
4824: d->function = func;
4825: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
4826: nlopt_set_min_objective(opt, myfunc, d);
4827: nlopt_set_xtol_rel(opt, ftol);
4828: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
4829: printf("nlopt failed! %d\n",creturn);
4830: }
4831: else {
4832: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
4833: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
4834: iter=1; /* not equal */
4835: }
4836: nlopt_destroy(opt);
4837: #endif
1.319 brouard 4838: #ifdef FLATSUP
4839: /* npared = npar -flatd/ncovmodel; */
4840: /* xired= matrix(1,npared,1,npared); */
4841: /* paramred= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); */
4842: /* powell(pred,xired,npared,ftol,&iter,&fret,flatdir,func); */
4843: /* free_matrix(xire,1,npared,1,npared); */
4844: #else /* FLATSUP */
4845: #endif /* FLATSUP */
1.126 brouard 4846: free_matrix(xi,1,npar,1,npar);
4847: fclose(ficrespow);
1.203 brouard 4848: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
4849: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 4850: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 4851:
4852: }
4853:
4854: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 4855: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 4856: {
4857: double **a,**y,*x,pd;
1.203 brouard 4858: /* double **hess; */
1.164 brouard 4859: int i, j;
1.126 brouard 4860: int *indx;
4861:
4862: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 4863: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 4864: void lubksb(double **a, int npar, int *indx, double b[]) ;
4865: void ludcmp(double **a, int npar, int *indx, double *d) ;
4866: double gompertz(double p[]);
1.203 brouard 4867: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 4868:
4869: printf("\nCalculation of the hessian matrix. Wait...\n");
4870: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
4871: for (i=1;i<=npar;i++){
1.203 brouard 4872: printf("%d-",i);fflush(stdout);
4873: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 4874:
4875: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
4876:
4877: /* printf(" %f ",p[i]);
4878: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
4879: }
4880:
4881: for (i=1;i<=npar;i++) {
4882: for (j=1;j<=npar;j++) {
4883: if (j>i) {
1.203 brouard 4884: printf(".%d-%d",i,j);fflush(stdout);
4885: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
4886: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 4887:
4888: hess[j][i]=hess[i][j];
4889: /*printf(" %lf ",hess[i][j]);*/
4890: }
4891: }
4892: }
4893: printf("\n");
4894: fprintf(ficlog,"\n");
4895:
4896: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
4897: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
4898:
4899: a=matrix(1,npar,1,npar);
4900: y=matrix(1,npar,1,npar);
4901: x=vector(1,npar);
4902: indx=ivector(1,npar);
4903: for (i=1;i<=npar;i++)
4904: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
4905: ludcmp(a,npar,indx,&pd);
4906:
4907: for (j=1;j<=npar;j++) {
4908: for (i=1;i<=npar;i++) x[i]=0;
4909: x[j]=1;
4910: lubksb(a,npar,indx,x);
4911: for (i=1;i<=npar;i++){
4912: matcov[i][j]=x[i];
4913: }
4914: }
4915:
4916: printf("\n#Hessian matrix#\n");
4917: fprintf(ficlog,"\n#Hessian matrix#\n");
4918: for (i=1;i<=npar;i++) {
4919: for (j=1;j<=npar;j++) {
1.203 brouard 4920: printf("%.6e ",hess[i][j]);
4921: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 4922: }
4923: printf("\n");
4924: fprintf(ficlog,"\n");
4925: }
4926:
1.203 brouard 4927: /* printf("\n#Covariance matrix#\n"); */
4928: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
4929: /* for (i=1;i<=npar;i++) { */
4930: /* for (j=1;j<=npar;j++) { */
4931: /* printf("%.6e ",matcov[i][j]); */
4932: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
4933: /* } */
4934: /* printf("\n"); */
4935: /* fprintf(ficlog,"\n"); */
4936: /* } */
4937:
1.126 brouard 4938: /* Recompute Inverse */
1.203 brouard 4939: /* for (i=1;i<=npar;i++) */
4940: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
4941: /* ludcmp(a,npar,indx,&pd); */
4942:
4943: /* printf("\n#Hessian matrix recomputed#\n"); */
4944:
4945: /* for (j=1;j<=npar;j++) { */
4946: /* for (i=1;i<=npar;i++) x[i]=0; */
4947: /* x[j]=1; */
4948: /* lubksb(a,npar,indx,x); */
4949: /* for (i=1;i<=npar;i++){ */
4950: /* y[i][j]=x[i]; */
4951: /* printf("%.3e ",y[i][j]); */
4952: /* fprintf(ficlog,"%.3e ",y[i][j]); */
4953: /* } */
4954: /* printf("\n"); */
4955: /* fprintf(ficlog,"\n"); */
4956: /* } */
4957:
4958: /* Verifying the inverse matrix */
4959: #ifdef DEBUGHESS
4960: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 4961:
1.203 brouard 4962: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
4963: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 4964:
4965: for (j=1;j<=npar;j++) {
4966: for (i=1;i<=npar;i++){
1.203 brouard 4967: printf("%.2f ",y[i][j]);
4968: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 4969: }
4970: printf("\n");
4971: fprintf(ficlog,"\n");
4972: }
1.203 brouard 4973: #endif
1.126 brouard 4974:
4975: free_matrix(a,1,npar,1,npar);
4976: free_matrix(y,1,npar,1,npar);
4977: free_vector(x,1,npar);
4978: free_ivector(indx,1,npar);
1.203 brouard 4979: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 4980:
4981:
4982: }
4983:
4984: /*************** hessian matrix ****************/
4985: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 4986: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 4987: int i;
4988: int l=1, lmax=20;
1.203 brouard 4989: double k1,k2, res, fx;
1.132 brouard 4990: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 4991: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
4992: int k=0,kmax=10;
4993: double l1;
4994:
4995: fx=func(x);
4996: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 4997: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 4998: l1=pow(10,l);
4999: delts=delt;
5000: for(k=1 ; k <kmax; k=k+1){
5001: delt = delta*(l1*k);
5002: p2[theta]=x[theta] +delt;
1.145 brouard 5003: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 5004: p2[theta]=x[theta]-delt;
5005: k2=func(p2)-fx;
5006: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 5007: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 5008:
1.203 brouard 5009: #ifdef DEBUGHESSII
1.126 brouard 5010: 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);
5011: 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);
5012: #endif
5013: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
5014: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
5015: k=kmax;
5016: }
5017: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 5018: k=kmax; l=lmax*10;
1.126 brouard 5019: }
5020: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
5021: delts=delt;
5022: }
1.203 brouard 5023: } /* End loop k */
1.126 brouard 5024: }
5025: delti[theta]=delts;
5026: return res;
5027:
5028: }
5029:
1.203 brouard 5030: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 5031: {
5032: int i;
1.164 brouard 5033: int l=1, lmax=20;
1.126 brouard 5034: double k1,k2,k3,k4,res,fx;
1.132 brouard 5035: double p2[MAXPARM+1];
1.203 brouard 5036: int k, kmax=1;
5037: double v1, v2, cv12, lc1, lc2;
1.208 brouard 5038:
5039: int firstime=0;
1.203 brouard 5040:
1.126 brouard 5041: fx=func(x);
1.203 brouard 5042: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 5043: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 5044: p2[thetai]=x[thetai]+delti[thetai]*k;
5045: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 5046: k1=func(p2)-fx;
5047:
1.203 brouard 5048: p2[thetai]=x[thetai]+delti[thetai]*k;
5049: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 5050: k2=func(p2)-fx;
5051:
1.203 brouard 5052: p2[thetai]=x[thetai]-delti[thetai]*k;
5053: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 5054: k3=func(p2)-fx;
5055:
1.203 brouard 5056: p2[thetai]=x[thetai]-delti[thetai]*k;
5057: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 5058: k4=func(p2)-fx;
1.203 brouard 5059: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
5060: if(k1*k2*k3*k4 <0.){
1.208 brouard 5061: firstime=1;
1.203 brouard 5062: kmax=kmax+10;
1.208 brouard 5063: }
5064: if(kmax >=10 || firstime ==1){
1.246 brouard 5065: 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);
5066: 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 5067: 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);
5068: 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);
5069: }
5070: #ifdef DEBUGHESSIJ
5071: v1=hess[thetai][thetai];
5072: v2=hess[thetaj][thetaj];
5073: cv12=res;
5074: /* Computing eigen value of Hessian matrix */
5075: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
5076: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
5077: if ((lc2 <0) || (lc1 <0) ){
5078: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
5079: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
5080: 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);
5081: 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);
5082: }
1.126 brouard 5083: #endif
5084: }
5085: return res;
5086: }
5087:
1.203 brouard 5088: /* Not done yet: Was supposed to fix if not exactly at the maximum */
5089: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
5090: /* { */
5091: /* int i; */
5092: /* int l=1, lmax=20; */
5093: /* double k1,k2,k3,k4,res,fx; */
5094: /* double p2[MAXPARM+1]; */
5095: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
5096: /* int k=0,kmax=10; */
5097: /* double l1; */
5098:
5099: /* fx=func(x); */
5100: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
5101: /* l1=pow(10,l); */
5102: /* delts=delt; */
5103: /* for(k=1 ; k <kmax; k=k+1){ */
5104: /* delt = delti*(l1*k); */
5105: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
5106: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
5107: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
5108: /* k1=func(p2)-fx; */
5109:
5110: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
5111: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
5112: /* k2=func(p2)-fx; */
5113:
5114: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
5115: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
5116: /* k3=func(p2)-fx; */
5117:
5118: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
5119: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
5120: /* k4=func(p2)-fx; */
5121: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
5122: /* #ifdef DEBUGHESSIJ */
5123: /* 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); */
5124: /* 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); */
5125: /* #endif */
5126: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
5127: /* k=kmax; */
5128: /* } */
5129: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
5130: /* k=kmax; l=lmax*10; */
5131: /* } */
5132: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
5133: /* delts=delt; */
5134: /* } */
5135: /* } /\* End loop k *\/ */
5136: /* } */
5137: /* delti[theta]=delts; */
5138: /* return res; */
5139: /* } */
5140:
5141:
1.126 brouard 5142: /************** Inverse of matrix **************/
5143: void ludcmp(double **a, int n, int *indx, double *d)
5144: {
5145: int i,imax,j,k;
5146: double big,dum,sum,temp;
5147: double *vv;
5148:
5149: vv=vector(1,n);
5150: *d=1.0;
5151: for (i=1;i<=n;i++) {
5152: big=0.0;
5153: for (j=1;j<=n;j++)
5154: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 5155: if (big == 0.0){
5156: printf(" Singular Hessian matrix at row %d:\n",i);
5157: for (j=1;j<=n;j++) {
5158: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
5159: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
5160: }
5161: fflush(ficlog);
5162: fclose(ficlog);
5163: nrerror("Singular matrix in routine ludcmp");
5164: }
1.126 brouard 5165: vv[i]=1.0/big;
5166: }
5167: for (j=1;j<=n;j++) {
5168: for (i=1;i<j;i++) {
5169: sum=a[i][j];
5170: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
5171: a[i][j]=sum;
5172: }
5173: big=0.0;
5174: for (i=j;i<=n;i++) {
5175: sum=a[i][j];
5176: for (k=1;k<j;k++)
5177: sum -= a[i][k]*a[k][j];
5178: a[i][j]=sum;
5179: if ( (dum=vv[i]*fabs(sum)) >= big) {
5180: big=dum;
5181: imax=i;
5182: }
5183: }
5184: if (j != imax) {
5185: for (k=1;k<=n;k++) {
5186: dum=a[imax][k];
5187: a[imax][k]=a[j][k];
5188: a[j][k]=dum;
5189: }
5190: *d = -(*d);
5191: vv[imax]=vv[j];
5192: }
5193: indx[j]=imax;
5194: if (a[j][j] == 0.0) a[j][j]=TINY;
5195: if (j != n) {
5196: dum=1.0/(a[j][j]);
5197: for (i=j+1;i<=n;i++) a[i][j] *= dum;
5198: }
5199: }
5200: free_vector(vv,1,n); /* Doesn't work */
5201: ;
5202: }
5203:
5204: void lubksb(double **a, int n, int *indx, double b[])
5205: {
5206: int i,ii=0,ip,j;
5207: double sum;
5208:
5209: for (i=1;i<=n;i++) {
5210: ip=indx[i];
5211: sum=b[ip];
5212: b[ip]=b[i];
5213: if (ii)
5214: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
5215: else if (sum) ii=i;
5216: b[i]=sum;
5217: }
5218: for (i=n;i>=1;i--) {
5219: sum=b[i];
5220: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
5221: b[i]=sum/a[i][i];
5222: }
5223: }
5224:
5225: void pstamp(FILE *fichier)
5226: {
1.196 brouard 5227: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 5228: }
5229:
1.297 brouard 5230: void date2dmy(double date,double *day, double *month, double *year){
5231: double yp=0., yp1=0., yp2=0.;
5232:
5233: yp1=modf(date,&yp);/* extracts integral of date in yp and
5234: fractional in yp1 */
5235: *year=yp;
5236: yp2=modf((yp1*12),&yp);
5237: *month=yp;
5238: yp1=modf((yp2*30.5),&yp);
5239: *day=yp;
5240: if(*day==0) *day=1;
5241: if(*month==0) *month=1;
5242: }
5243:
1.253 brouard 5244:
5245:
1.126 brouard 5246: /************ Frequencies ********************/
1.251 brouard 5247: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 5248: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
5249: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 5250: { /* Some frequencies as well as proposing some starting values */
1.332 brouard 5251: /* Frequencies of any combination of dummy covariate used in the model equation */
1.265 brouard 5252: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 5253: int iind=0, iage=0;
5254: int mi; /* Effective wave */
5255: int first;
5256: double ***freq; /* Frequencies */
1.268 brouard 5257: 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 */
5258: 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 5259: double *meanq, *stdq, *idq;
1.226 brouard 5260: double **meanqt;
5261: double *pp, **prop, *posprop, *pospropt;
5262: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
5263: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
5264: double agebegin, ageend;
5265:
5266: pp=vector(1,nlstate);
1.251 brouard 5267: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 5268: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
5269: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
5270: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
5271: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 5272: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 5273: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 5274: meanqt=matrix(1,lastpass,1,nqtveff);
5275: strcpy(fileresp,"P_");
5276: strcat(fileresp,fileresu);
5277: /*strcat(fileresphtm,fileresu);*/
5278: if((ficresp=fopen(fileresp,"w"))==NULL) {
5279: printf("Problem with prevalence resultfile: %s\n", fileresp);
5280: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
5281: exit(0);
5282: }
1.240 brouard 5283:
1.226 brouard 5284: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
5285: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
5286: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
5287: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
5288: fflush(ficlog);
5289: exit(70);
5290: }
5291: else{
5292: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 5293: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 5294: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 5295: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
5296: }
1.319 brouard 5297: 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 5298:
1.226 brouard 5299: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
5300: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
5301: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
5302: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
5303: fflush(ficlog);
5304: exit(70);
1.240 brouard 5305: } else{
1.226 brouard 5306: 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 5307: ,<hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 5308: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 5309: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
5310: }
1.319 brouard 5311: 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 5312:
1.253 brouard 5313: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
5314: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 5315: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 5316: j1=0;
1.126 brouard 5317:
1.227 brouard 5318: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
1.335 brouard 5319: j=cptcoveff; /* Only simple dummy covariates used in the model */
1.330 brouard 5320: /* j=cptcovn; /\* Only dummy covariates of the model *\/ */
1.226 brouard 5321: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 5322:
5323:
1.226 brouard 5324: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
5325: reference=low_education V1=0,V2=0
5326: med_educ V1=1 V2=0,
5327: high_educ V1=0 V2=1
1.330 brouard 5328: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcovn
1.226 brouard 5329: */
1.249 brouard 5330: dateintsum=0;
5331: k2cpt=0;
5332:
1.253 brouard 5333: if(cptcoveff == 0 )
1.265 brouard 5334: nl=1; /* Constant and age model only */
1.253 brouard 5335: else
5336: nl=2;
1.265 brouard 5337:
5338: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
5339: /* Loop on nj=1 or 2 if dummy covariates j!=0
1.335 brouard 5340: * Loop on j1(1 to 2**cptcoveff) covariate combination
1.265 brouard 5341: * freq[s1][s2][iage] =0.
5342: * Loop on iind
5343: * ++freq[s1][s2][iage] weighted
5344: * end iind
5345: * if covariate and j!0
5346: * headers Variable on one line
5347: * endif cov j!=0
5348: * header of frequency table by age
5349: * Loop on age
5350: * pp[s1]+=freq[s1][s2][iage] weighted
5351: * pos+=freq[s1][s2][iage] weighted
5352: * Loop on s1 initial state
5353: * fprintf(ficresp
5354: * end s1
5355: * end age
5356: * if j!=0 computes starting values
5357: * end compute starting values
5358: * end j1
5359: * end nl
5360: */
1.253 brouard 5361: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
5362: if(nj==1)
5363: j=0; /* First pass for the constant */
1.265 brouard 5364: else{
1.335 brouard 5365: 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 5366: }
1.251 brouard 5367: first=1;
1.332 brouard 5368: 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 5369: posproptt=0.;
1.330 brouard 5370: /*printf("cptcovn=%d Tvaraff=%d", cptcovn,Tvaraff[1]);
1.251 brouard 5371: scanf("%d", i);*/
5372: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 5373: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 5374: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 5375: freq[i][s2][m]=0;
1.251 brouard 5376:
5377: for (i=1; i<=nlstate; i++) {
1.240 brouard 5378: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 5379: prop[i][m]=0;
5380: posprop[i]=0;
5381: pospropt[i]=0;
5382: }
1.283 brouard 5383: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 5384: idq[z1]=0.;
5385: meanq[z1]=0.;
5386: stdq[z1]=0.;
1.283 brouard 5387: }
5388: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 5389: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 5390: /* meanqt[m][z1]=0.; */
5391: /* } */
5392: /* } */
1.251 brouard 5393: /* dateintsum=0; */
5394: /* k2cpt=0; */
5395:
1.265 brouard 5396: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 5397: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
5398: bool=1;
5399: if(j !=0){
5400: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
1.335 brouard 5401: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
5402: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
1.251 brouard 5403: /* if(Tvaraff[z1] ==-20){ */
5404: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
5405: /* }else if(Tvaraff[z1] ==-10){ */
5406: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
1.330 brouard 5407: /* }else */ /* TODO TODO codtabm(j1,z1) or codtabm(j1,Tvaraff[z1]]z1)*/
1.335 brouard 5408: /* 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); */
5409: if(Tvaraff[z1]<1 || Tvaraff[z1]>=NCOVMAX)
1.338 brouard 5410: printf("Error Tvaraff[z1]=%d<1 or >=%d, cptcoveff=%d model=1+age+%s\n",Tvaraff[z1],NCOVMAX, cptcoveff, model);
1.332 brouard 5411: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]){ /* for combination j1 of covariates */
1.265 brouard 5412: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 5413: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
1.332 brouard 5414: /* 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", */
5415: /* bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),*/
5416: /* j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
1.251 brouard 5417: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
5418: } /* Onlyf fixed */
5419: } /* end z1 */
1.335 brouard 5420: } /* cptcoveff > 0 */
1.251 brouard 5421: } /* end any */
5422: }/* end j==0 */
1.265 brouard 5423: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 5424: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 5425: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 5426: m=mw[mi][iind];
5427: if(j!=0){
5428: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
1.335 brouard 5429: for (z1=1; z1<=cptcoveff; z1++) {
1.251 brouard 5430: if( Fixed[Tmodelind[z1]]==1){
1.341 brouard 5431: /* iv= Tvar[Tmodelind[z1]]-ncovcol-nqv; /\* Good *\/ */
5432: iv= Tvar[Tmodelind[z1]]; /* Good *//* because cotvar starts now at first at ncovcol+nqv+ntv */
1.332 brouard 5433: 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 5434: value is -1, we don't select. It differs from the
5435: constant and age model which counts them. */
5436: bool=0; /* not selected */
5437: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
1.334 brouard 5438: /* i1=Tvaraff[z1]; */
5439: /* i2=TnsdVar[i1]; */
5440: /* i3=nbcode[i1][i2]; */
5441: /* i4=covar[i1][iind]; */
5442: /* if(i4 != i3){ */
5443: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) { /* Bug valgrind */
1.251 brouard 5444: bool=0;
5445: }
5446: }
5447: }
5448: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
5449: } /* end j==0 */
5450: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 5451: if(bool==1){ /*Selected */
1.251 brouard 5452: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
5453: and mw[mi+1][iind]. dh depends on stepm. */
5454: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
5455: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
5456: if(m >=firstpass && m <=lastpass){
5457: k2=anint[m][iind]+(mint[m][iind]/12.);
5458: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
5459: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
5460: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
5461: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
5462: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
5463: if (m<lastpass) {
5464: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
5465: /* 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]); */
5466: if(s[m][iind]==-1)
5467: 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.));
5468: 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 5469: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean on known values only */
5470: if(!isnan(covar[ncovcol+z1][iind])){
1.332 brouard 5471: idq[z1]=idq[z1]+weight[iind];
5472: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
5473: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; *//*error*/
5474: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
1.311 brouard 5475: }
1.284 brouard 5476: }
1.251 brouard 5477: /* if((int)agev[m][iind] == 55) */
5478: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
5479: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
5480: 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 5481: }
1.251 brouard 5482: } /* end if between passes */
5483: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
5484: dateintsum=dateintsum+k2; /* on all covariates ?*/
5485: k2cpt++;
5486: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 5487: }
1.251 brouard 5488: }else{
5489: bool=1;
5490: }/* end bool 2 */
5491: } /* end m */
1.284 brouard 5492: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
5493: /* idq[z1]=idq[z1]+weight[iind]; */
5494: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
5495: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
5496: /* } */
1.251 brouard 5497: } /* end bool */
5498: } /* end iind = 1 to imx */
1.319 brouard 5499: /* prop[s][age] is fed for any initial and valid live state as well as
1.251 brouard 5500: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
5501:
5502:
5503: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.335 brouard 5504: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
1.265 brouard 5505: pstamp(ficresp);
1.335 brouard 5506: if (cptcoveff>0 && j!=0){
1.265 brouard 5507: pstamp(ficresp);
1.251 brouard 5508: printf( "\n#********** Variable ");
5509: fprintf(ficresp, "\n#********** Variable ");
5510: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
5511: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
5512: fprintf(ficlog, "\n#********** Variable ");
1.340 brouard 5513: for (z1=1; z1<=cptcoveff; z1++){
1.251 brouard 5514: if(!FixedV[Tvaraff[z1]]){
1.330 brouard 5515: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5516: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5517: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5518: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5519: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.250 brouard 5520: }else{
1.330 brouard 5521: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5522: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5523: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5524: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5525: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.251 brouard 5526: }
5527: }
5528: printf( "**********\n#");
5529: fprintf(ficresp, "**********\n#");
5530: fprintf(ficresphtm, "**********</h3>\n");
5531: fprintf(ficresphtmfr, "**********</h3>\n");
5532: fprintf(ficlog, "**********\n");
5533: }
1.284 brouard 5534: /*
5535: Printing means of quantitative variables if any
5536: */
5537: for (z1=1; z1<= nqfveff; z1++) {
1.311 brouard 5538: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.3g (weighted) individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.312 brouard 5539: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
1.284 brouard 5540: if(weightopt==1){
5541: printf(" Weighted mean and standard deviation of");
5542: fprintf(ficlog," Weighted mean and standard deviation of");
5543: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
5544: }
1.311 brouard 5545: /* mu = \frac{w x}{\sum w}
5546: var = \frac{\sum w (x-mu)^2}{\sum w} = \frac{w x^2}{\sum w} - mu^2
5547: */
5548: 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]));
5549: 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]));
5550: 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 5551: }
5552: /* for (z1=1; z1<= nqtveff; z1++) { */
5553: /* for(m=1;m<=lastpass;m++){ */
5554: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
5555: /* } */
5556: /* } */
1.283 brouard 5557:
1.251 brouard 5558: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.335 brouard 5559: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
1.265 brouard 5560: fprintf(ficresp, " Age");
1.335 brouard 5561: if(nj==2) for (z1=1; z1<=cptcoveff; z1++) {
5562: 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]]);
5563: fprintf(ficresp, " V%d=%d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5564: }
1.251 brouard 5565: for(i=1; i<=nlstate;i++) {
1.335 brouard 5566: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 5567: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
5568: }
1.335 brouard 5569: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 5570: fprintf(ficresphtm, "\n");
5571:
5572: /* Header of frequency table by age */
5573: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
5574: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 5575: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 5576: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5577: if(s2!=0 && m!=0)
5578: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 5579: }
1.226 brouard 5580: }
1.251 brouard 5581: fprintf(ficresphtmfr, "\n");
5582:
5583: /* For each age */
5584: for(iage=iagemin; iage <= iagemax+3; iage++){
5585: fprintf(ficresphtm,"<tr>");
5586: if(iage==iagemax+1){
5587: fprintf(ficlog,"1");
5588: fprintf(ficresphtmfr,"<tr><th>0</th> ");
5589: }else if(iage==iagemax+2){
5590: fprintf(ficlog,"0");
5591: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
5592: }else if(iage==iagemax+3){
5593: fprintf(ficlog,"Total");
5594: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
5595: }else{
1.240 brouard 5596: if(first==1){
1.251 brouard 5597: first=0;
5598: printf("See log file for details...\n");
5599: }
5600: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
5601: fprintf(ficlog,"Age %d", iage);
5602: }
1.265 brouard 5603: for(s1=1; s1 <=nlstate ; s1++){
5604: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
5605: pp[s1] += freq[s1][m][iage];
1.251 brouard 5606: }
1.265 brouard 5607: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5608: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 5609: pos += freq[s1][m][iage];
5610: if(pp[s1]>=1.e-10){
1.251 brouard 5611: if(first==1){
1.265 brouard 5612: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5613: }
1.265 brouard 5614: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5615: }else{
5616: if(first==1)
1.265 brouard 5617: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
5618: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 5619: }
5620: }
5621:
1.265 brouard 5622: for(s1=1; s1 <=nlstate ; s1++){
5623: /* posprop[s1]=0; */
5624: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
5625: pp[s1] += freq[s1][m][iage];
5626: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
5627:
5628: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
5629: pos += pp[s1]; /* pos is the total number of transitions until this age */
5630: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
5631: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5632: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
5633: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5634: }
5635:
5636: /* Writing ficresp */
1.335 brouard 5637: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5638: if( iage <= iagemax){
5639: fprintf(ficresp," %d",iage);
5640: }
5641: }else if( nj==2){
5642: if( iage <= iagemax){
5643: fprintf(ficresp," %d",iage);
1.335 brouard 5644: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.265 brouard 5645: }
1.240 brouard 5646: }
1.265 brouard 5647: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 5648: if(pos>=1.e-5){
1.251 brouard 5649: if(first==1)
1.265 brouard 5650: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
5651: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 5652: }else{
5653: if(first==1)
1.265 brouard 5654: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
5655: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 5656: }
5657: if( iage <= iagemax){
5658: if(pos>=1.e-5){
1.335 brouard 5659: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5660: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5661: }else if( nj==2){
5662: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5663: }
5664: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5665: /*probs[iage][s1][j1]= pp[s1]/pos;*/
5666: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
5667: } else{
1.335 brouard 5668: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
1.265 brouard 5669: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 5670: }
1.240 brouard 5671: }
1.265 brouard 5672: pospropt[s1] +=posprop[s1];
5673: } /* end loop s1 */
1.251 brouard 5674: /* pospropt=0.; */
1.265 brouard 5675: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 5676: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5677: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 5678: if(first==1){
1.265 brouard 5679: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5680: }
1.265 brouard 5681: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
5682: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5683: }
1.265 brouard 5684: if(s1!=0 && m!=0)
5685: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 5686: }
1.265 brouard 5687: } /* end loop s1 */
1.251 brouard 5688: posproptt=0.;
1.265 brouard 5689: for(s1=1; s1 <=nlstate; s1++){
5690: posproptt += pospropt[s1];
1.251 brouard 5691: }
5692: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 5693: fprintf(ficresphtm,"</tr>\n");
1.335 brouard 5694: if((cptcoveff==0 && nj==1)|| nj==2 ) {
1.265 brouard 5695: if(iage <= iagemax)
5696: fprintf(ficresp,"\n");
1.240 brouard 5697: }
1.251 brouard 5698: if(first==1)
5699: printf("Others in log...\n");
5700: fprintf(ficlog,"\n");
5701: } /* end loop age iage */
1.265 brouard 5702:
1.251 brouard 5703: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 5704: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5705: if(posproptt < 1.e-5){
1.265 brouard 5706: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 5707: }else{
1.265 brouard 5708: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 5709: }
1.226 brouard 5710: }
1.251 brouard 5711: fprintf(ficresphtm,"</tr>\n");
5712: fprintf(ficresphtm,"</table>\n");
5713: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 5714: if(posproptt < 1.e-5){
1.251 brouard 5715: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
5716: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 5717: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
5718: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 5719: invalidvarcomb[j1]=1;
1.226 brouard 5720: }else{
1.338 brouard 5721: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced (or no resultline).</p>",j1);
1.251 brouard 5722: invalidvarcomb[j1]=0;
1.226 brouard 5723: }
1.251 brouard 5724: fprintf(ficresphtmfr,"</table>\n");
5725: fprintf(ficlog,"\n");
5726: if(j!=0){
5727: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 5728: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5729: for(k=1; k <=(nlstate+ndeath); k++){
5730: if (k != i) {
1.265 brouard 5731: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 5732: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 5733: if(j1==1){ /* All dummy covariates to zero */
5734: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
5735: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 5736: printf("%d%d ",i,k);
5737: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5738: 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]));
5739: 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]));
5740: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 5741: }
1.253 brouard 5742: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
5743: for(iage=iagemin; iage <= iagemax+3; iage++){
5744: x[iage]= (double)iage;
5745: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 5746: /* 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 5747: }
1.268 brouard 5748: /* Some are not finite, but linreg will ignore these ages */
5749: no=0;
1.253 brouard 5750: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 5751: pstart[s1]=b;
5752: pstart[s1-1]=a;
1.252 brouard 5753: }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 */
5754: 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]);
5755: 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 5756: 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 5757: printf("%d%d ",i,k);
5758: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5759: 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 5760: }else{ /* Other cases, like quantitative fixed or varying covariates */
5761: ;
5762: }
5763: /* printf("%12.7f )", param[i][jj][k]); */
5764: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5765: s1++;
1.251 brouard 5766: } /* end jj */
5767: } /* end k!= i */
5768: } /* end k */
1.265 brouard 5769: } /* end i, s1 */
1.251 brouard 5770: } /* end j !=0 */
5771: } /* end selected combination of covariate j1 */
5772: if(j==0){ /* We can estimate starting values from the occurences in each case */
5773: printf("#Freqsummary: Starting values for the constants:\n");
5774: fprintf(ficlog,"\n");
1.265 brouard 5775: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5776: for(k=1; k <=(nlstate+ndeath); k++){
5777: if (k != i) {
5778: printf("%d%d ",i,k);
5779: fprintf(ficlog,"%d%d ",i,k);
5780: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 5781: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 5782: if(jj==1){ /* Age has to be done */
1.265 brouard 5783: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
5784: 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]));
5785: 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 5786: }
5787: /* printf("%12.7f )", param[i][jj][k]); */
5788: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5789: s1++;
1.250 brouard 5790: }
1.251 brouard 5791: printf("\n");
5792: fprintf(ficlog,"\n");
1.250 brouard 5793: }
5794: }
1.284 brouard 5795: } /* end of state i */
1.251 brouard 5796: printf("#Freqsummary\n");
5797: fprintf(ficlog,"\n");
1.265 brouard 5798: for(s1=-1; s1 <=nlstate+ndeath; s1++){
5799: for(s2=-1; s2 <=nlstate+ndeath; s2++){
5800: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
5801: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5802: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5803: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
5804: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
5805: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 5806: /* } */
5807: }
1.265 brouard 5808: } /* end loop s1 */
1.251 brouard 5809:
5810: printf("\n");
5811: fprintf(ficlog,"\n");
5812: } /* end j=0 */
1.249 brouard 5813: } /* end j */
1.252 brouard 5814:
1.253 brouard 5815: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 5816: for(i=1, jk=1; i <=nlstate; i++){
5817: for(j=1; j <=nlstate+ndeath; j++){
5818: if(j!=i){
5819: /*ca[0]= k+'a'-1;ca[1]='\0';*/
5820: printf("%1d%1d",i,j);
5821: fprintf(ficparo,"%1d%1d",i,j);
5822: for(k=1; k<=ncovmodel;k++){
5823: /* printf(" %lf",param[i][j][k]); */
5824: /* fprintf(ficparo," %lf",param[i][j][k]); */
5825: p[jk]=pstart[jk];
5826: printf(" %f ",pstart[jk]);
5827: fprintf(ficparo," %f ",pstart[jk]);
5828: jk++;
5829: }
5830: printf("\n");
5831: fprintf(ficparo,"\n");
5832: }
5833: }
5834: }
5835: } /* end mle=-2 */
1.226 brouard 5836: dateintmean=dateintsum/k2cpt;
1.296 brouard 5837: date2dmy(dateintmean,&jintmean,&mintmean,&aintmean);
1.240 brouard 5838:
1.226 brouard 5839: fclose(ficresp);
5840: fclose(ficresphtm);
5841: fclose(ficresphtmfr);
1.283 brouard 5842: free_vector(idq,1,nqfveff);
1.226 brouard 5843: free_vector(meanq,1,nqfveff);
1.284 brouard 5844: free_vector(stdq,1,nqfveff);
1.226 brouard 5845: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 5846: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
5847: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 5848: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5849: free_vector(pospropt,1,nlstate);
5850: free_vector(posprop,1,nlstate);
1.251 brouard 5851: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5852: free_vector(pp,1,nlstate);
5853: /* End of freqsummary */
5854: }
1.126 brouard 5855:
1.268 brouard 5856: /* Simple linear regression */
5857: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
5858:
5859: /* y=a+bx regression */
5860: double sumx = 0.0; /* sum of x */
5861: double sumx2 = 0.0; /* sum of x**2 */
5862: double sumxy = 0.0; /* sum of x * y */
5863: double sumy = 0.0; /* sum of y */
5864: double sumy2 = 0.0; /* sum of y**2 */
5865: double sume2 = 0.0; /* sum of square or residuals */
5866: double yhat;
5867:
5868: double denom=0;
5869: int i;
5870: int ne=*no;
5871:
5872: for ( i=ifi, ne=0;i<=ila;i++) {
5873: if(!isfinite(x[i]) || !isfinite(y[i])){
5874: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5875: continue;
5876: }
5877: ne=ne+1;
5878: sumx += x[i];
5879: sumx2 += x[i]*x[i];
5880: sumxy += x[i] * y[i];
5881: sumy += y[i];
5882: sumy2 += y[i]*y[i];
5883: denom = (ne * sumx2 - sumx*sumx);
5884: /* 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); */
5885: }
5886:
5887: denom = (ne * sumx2 - sumx*sumx);
5888: if (denom == 0) {
5889: // vertical, slope m is infinity
5890: *b = INFINITY;
5891: *a = 0;
5892: if (r) *r = 0;
5893: return 1;
5894: }
5895:
5896: *b = (ne * sumxy - sumx * sumy) / denom;
5897: *a = (sumy * sumx2 - sumx * sumxy) / denom;
5898: if (r!=NULL) {
5899: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
5900: sqrt((sumx2 - sumx*sumx/ne) *
5901: (sumy2 - sumy*sumy/ne));
5902: }
5903: *no=ne;
5904: for ( i=ifi, ne=0;i<=ila;i++) {
5905: if(!isfinite(x[i]) || !isfinite(y[i])){
5906: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5907: continue;
5908: }
5909: ne=ne+1;
5910: yhat = y[i] - *a -*b* x[i];
5911: sume2 += yhat * yhat ;
5912:
5913: denom = (ne * sumx2 - sumx*sumx);
5914: /* 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); */
5915: }
5916: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
5917: *sa= *sb * sqrt(sumx2/ne);
5918:
5919: return 0;
5920: }
5921:
1.126 brouard 5922: /************ Prevalence ********************/
1.227 brouard 5923: 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)
5924: {
5925: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
5926: in each health status at the date of interview (if between dateprev1 and dateprev2).
5927: We still use firstpass and lastpass as another selection.
5928: */
1.126 brouard 5929:
1.227 brouard 5930: int i, m, jk, j1, bool, z1,j, iv;
5931: int mi; /* Effective wave */
5932: int iage;
5933: double agebegin, ageend;
5934:
5935: double **prop;
5936: double posprop;
5937: double y2; /* in fractional years */
5938: int iagemin, iagemax;
5939: int first; /** to stop verbosity which is redirected to log file */
5940:
5941: iagemin= (int) agemin;
5942: iagemax= (int) agemax;
5943: /*pp=vector(1,nlstate);*/
1.251 brouard 5944: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5945: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
5946: j1=0;
1.222 brouard 5947:
1.227 brouard 5948: /*j=cptcoveff;*/
5949: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 5950:
1.288 brouard 5951: first=0;
1.335 brouard 5952: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of simple dummy covariates */
1.227 brouard 5953: for (i=1; i<=nlstate; i++)
1.251 brouard 5954: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 5955: prop[i][iage]=0.0;
5956: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
5957: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
5958: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
5959:
5960: for (i=1; i<=imx; i++) { /* Each individual */
5961: bool=1;
5962: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
5963: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
5964: m=mw[mi][i];
5965: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
5966: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
5967: for (z1=1; z1<=cptcoveff; z1++){
5968: if( Fixed[Tmodelind[z1]]==1){
1.341 brouard 5969: iv= Tvar[Tmodelind[z1]];/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
1.332 brouard 5970: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) /* iv=1 to ntv, right modality */
1.227 brouard 5971: bool=0;
5972: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
1.332 brouard 5973: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) {
1.227 brouard 5974: bool=0;
5975: }
5976: }
5977: if(bool==1){ /* Otherwise we skip that wave/person */
5978: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
5979: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
5980: if(m >=firstpass && m <=lastpass){
5981: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
5982: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
5983: if(agev[m][i]==0) agev[m][i]=iagemax+1;
5984: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 5985: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 5986: 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);
5987: exit(1);
5988: }
5989: if (s[m][i]>0 && s[m][i]<=nlstate) {
5990: /*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]]);*/
5991: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
5992: prop[s[m][i]][iagemax+3] += weight[i];
5993: } /* end valid statuses */
5994: } /* end selection of dates */
5995: } /* end selection of waves */
5996: } /* end bool */
5997: } /* end wave */
5998: } /* end individual */
5999: for(i=iagemin; i <= iagemax+3; i++){
6000: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
6001: posprop += prop[jk][i];
6002: }
6003:
6004: for(jk=1; jk <=nlstate ; jk++){
6005: if( i <= iagemax){
6006: if(posprop>=1.e-5){
6007: probs[i][jk][j1]= prop[jk][i]/posprop;
6008: } else{
1.288 brouard 6009: if(!first){
6010: first=1;
1.266 brouard 6011: 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]);
6012: }else{
1.288 brouard 6013: 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 6014: }
6015: }
6016: }
6017: }/* end jk */
6018: }/* end i */
1.222 brouard 6019: /*} *//* end i1 */
1.227 brouard 6020: } /* end j1 */
1.222 brouard 6021:
1.227 brouard 6022: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
6023: /*free_vector(pp,1,nlstate);*/
1.251 brouard 6024: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 6025: } /* End of prevalence */
1.126 brouard 6026:
6027: /************* Waves Concatenation ***************/
6028:
6029: 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)
6030: {
1.298 brouard 6031: /* 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 6032: Death is a valid wave (if date is known).
6033: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
6034: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
1.298 brouard 6035: and mw[mi+1][i]. dh depends on stepm. s[m][i] exists for any wave from firstpass to lastpass
1.227 brouard 6036: */
1.126 brouard 6037:
1.224 brouard 6038: int i=0, mi=0, m=0, mli=0;
1.126 brouard 6039: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
6040: double sum=0., jmean=0.;*/
1.224 brouard 6041: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 6042: int j, k=0,jk, ju, jl;
6043: double sum=0.;
6044: first=0;
1.214 brouard 6045: firstwo=0;
1.217 brouard 6046: firsthree=0;
1.218 brouard 6047: firstfour=0;
1.164 brouard 6048: jmin=100000;
1.126 brouard 6049: jmax=-1;
6050: jmean=0.;
1.224 brouard 6051:
6052: /* Treating live states */
1.214 brouard 6053: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 6054: mi=0; /* First valid wave */
1.227 brouard 6055: mli=0; /* Last valid wave */
1.309 brouard 6056: m=firstpass; /* Loop on waves */
6057: while(s[m][i] <= nlstate){ /* a live state or unknown state */
1.227 brouard 6058: 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 */
6059: mli=m-1;/* mw[++mi][i]=m-1; */
6060: }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 6061: 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 6062: mli=m;
1.224 brouard 6063: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
6064: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 6065: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 6066: }
1.309 brouard 6067: else{ /* m = lastpass, eventual special issue with warning */
1.224 brouard 6068: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 6069: break;
1.224 brouard 6070: #else
1.317 brouard 6071: 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 6072: if(firsthree == 0){
1.302 brouard 6073: 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 6074: firsthree=1;
1.317 brouard 6075: }else if(firsthree >=1 && firsthree < 10){
6076: 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);
6077: firsthree++;
6078: }else if(firsthree == 10){
6079: printf("Information, too many Information flags: no more reported to log either\n");
6080: fprintf(ficlog,"Information, too many Information flags: no more reported to log either\n");
6081: firsthree++;
6082: }else{
6083: firsthree++;
1.227 brouard 6084: }
1.309 brouard 6085: mw[++mi][i]=m; /* Valid transition with unknown status */
1.227 brouard 6086: mli=m;
6087: }
6088: if(s[m][i]==-2){ /* Vital status is really unknown */
6089: nbwarn++;
1.309 brouard 6090: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified?not a transition */
1.227 brouard 6091: 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);
6092: 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);
6093: }
6094: break;
6095: }
6096: break;
1.224 brouard 6097: #endif
1.227 brouard 6098: }/* End m >= lastpass */
1.126 brouard 6099: }/* end while */
1.224 brouard 6100:
1.227 brouard 6101: /* 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 6102: /* After last pass */
1.224 brouard 6103: /* Treating death states */
1.214 brouard 6104: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 6105: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
6106: /* } */
1.126 brouard 6107: mi++; /* Death is another wave */
6108: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 6109: /* Only death is a correct wave */
1.126 brouard 6110: mw[mi][i]=m;
1.257 brouard 6111: } /* else not in a death state */
1.224 brouard 6112: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 6113: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 6114: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.309 brouard 6115: 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 6116: nbwarn++;
6117: if(firstfiv==0){
1.309 brouard 6118: 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 6119: firstfiv=1;
6120: }else{
1.309 brouard 6121: 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 6122: }
1.309 brouard 6123: s[m][i]=nlstate+1; /* Fixing the status as death. Be careful if multiple death states */
6124: }else{ /* Month of Death occured afer last wave month, potential bias */
1.227 brouard 6125: nberr++;
6126: if(firstwo==0){
1.309 brouard 6127: 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 6128: firstwo=1;
6129: }
1.309 brouard 6130: 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 6131: }
1.257 brouard 6132: }else{ /* if date of interview is unknown */
1.227 brouard 6133: /* death is known but not confirmed by death status at any wave */
6134: if(firstfour==0){
1.309 brouard 6135: 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 6136: firstfour=1;
6137: }
1.309 brouard 6138: 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 6139: }
1.224 brouard 6140: } /* end if date of death is known */
6141: #endif
1.309 brouard 6142: wav[i]=mi; /* mi should be the last effective wave (or mli), */
6143: /* wav[i]=mw[mi][i]; */
1.126 brouard 6144: if(mi==0){
6145: nbwarn++;
6146: if(first==0){
1.227 brouard 6147: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
6148: first=1;
1.126 brouard 6149: }
6150: if(first==1){
1.227 brouard 6151: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 6152: }
6153: } /* end mi==0 */
6154: } /* End individuals */
1.214 brouard 6155: /* wav and mw are no more changed */
1.223 brouard 6156:
1.317 brouard 6157: printf("Information, you have to check %d informations which haven't been logged!\n",firsthree);
6158: fprintf(ficlog,"Information, you have to check %d informations which haven't been logged!\n",firsthree);
6159:
6160:
1.126 brouard 6161: for(i=1; i<=imx; i++){
6162: for(mi=1; mi<wav[i];mi++){
6163: if (stepm <=0)
1.227 brouard 6164: dh[mi][i]=1;
1.126 brouard 6165: else{
1.260 brouard 6166: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 6167: if (agedc[i] < 2*AGESUP) {
6168: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
6169: if(j==0) j=1; /* Survives at least one month after exam */
6170: else if(j<0){
6171: nberr++;
6172: 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]);
6173: j=1; /* Temporary Dangerous patch */
6174: 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);
6175: 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]);
6176: 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);
6177: }
6178: k=k+1;
6179: if (j >= jmax){
6180: jmax=j;
6181: ijmax=i;
6182: }
6183: if (j <= jmin){
6184: jmin=j;
6185: ijmin=i;
6186: }
6187: sum=sum+j;
6188: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
6189: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
6190: }
6191: }
6192: else{
6193: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 6194: /* 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 6195:
1.227 brouard 6196: k=k+1;
6197: if (j >= jmax) {
6198: jmax=j;
6199: ijmax=i;
6200: }
6201: else if (j <= jmin){
6202: jmin=j;
6203: ijmin=i;
6204: }
6205: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
6206: /*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]);*/
6207: if(j<0){
6208: nberr++;
6209: 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]);
6210: 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]);
6211: }
6212: sum=sum+j;
6213: }
6214: jk= j/stepm;
6215: jl= j -jk*stepm;
6216: ju= j -(jk+1)*stepm;
6217: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
6218: if(jl==0){
6219: dh[mi][i]=jk;
6220: bh[mi][i]=0;
6221: }else{ /* We want a negative bias in order to only have interpolation ie
6222: * to avoid the price of an extra matrix product in likelihood */
6223: dh[mi][i]=jk+1;
6224: bh[mi][i]=ju;
6225: }
6226: }else{
6227: if(jl <= -ju){
6228: dh[mi][i]=jk;
6229: bh[mi][i]=jl; /* bias is positive if real duration
6230: * is higher than the multiple of stepm and negative otherwise.
6231: */
6232: }
6233: else{
6234: dh[mi][i]=jk+1;
6235: bh[mi][i]=ju;
6236: }
6237: if(dh[mi][i]==0){
6238: dh[mi][i]=1; /* At least one step */
6239: bh[mi][i]=ju; /* At least one step */
6240: /* 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);*/
6241: }
6242: } /* end if mle */
1.126 brouard 6243: }
6244: } /* end wave */
6245: }
6246: jmean=sum/k;
6247: 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 6248: 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 6249: }
1.126 brouard 6250:
6251: /*********** Tricode ****************************/
1.220 brouard 6252: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 6253: {
6254: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
6255: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
6256: * Boring subroutine which should only output nbcode[Tvar[j]][k]
6257: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
6258: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
6259: */
1.130 brouard 6260:
1.242 brouard 6261: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
6262: int modmaxcovj=0; /* Modality max of covariates j */
6263: int cptcode=0; /* Modality max of covariates j */
6264: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 6265:
6266:
1.242 brouard 6267: /* cptcoveff=0; */
6268: /* *cptcov=0; */
1.126 brouard 6269:
1.242 brouard 6270: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 6271: for (k=1; k <= maxncov; k++)
6272: for(j=1; j<=2; j++)
6273: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 6274:
1.242 brouard 6275: /* Loop on covariates without age and products and no quantitative variable */
1.335 brouard 6276: 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 6277: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
1.343 brouard 6278: /* printf("Testing k=%d, cptcovt=%d\n",k, cptcovt); */
1.339 brouard 6279: if(Dummy[k]==0 && Typevar[k] !=1 && Typevar[k] != 2){ /* Dummy covariate and not age product nor fixed product */
1.242 brouard 6280: switch(Fixed[k]) {
6281: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
1.311 brouard 6282: modmaxcovj=0;
6283: modmincovj=0;
1.242 brouard 6284: 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 6285: /* 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 6286: ij=(int)(covar[Tvar[k]][i]);
6287: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
6288: * If product of Vn*Vm, still boolean *:
6289: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
6290: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
6291: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
6292: modality of the nth covariate of individual i. */
6293: if (ij > modmaxcovj)
6294: modmaxcovj=ij;
6295: else if (ij < modmincovj)
6296: modmincovj=ij;
1.287 brouard 6297: if (ij <0 || ij >1 ){
1.311 brouard 6298: printf("ERROR, IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
6299: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
6300: fflush(ficlog);
6301: exit(1);
1.287 brouard 6302: }
6303: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 6304: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
6305: exit(1);
6306: }else
6307: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
6308: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
6309: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
6310: /* getting the maximum value of the modality of the covariate
6311: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
6312: female ies 1, then modmaxcovj=1.
6313: */
6314: } /* end for loop on individuals i */
6315: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
6316: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
6317: cptcode=modmaxcovj;
6318: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
6319: /*for (i=0; i<=cptcode; i++) {*/
6320: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
6321: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
6322: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
6323: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
6324: if( j != -1){
6325: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
6326: covariate for which somebody answered excluding
6327: undefined. Usually 2: 0 and 1. */
6328: }
6329: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
6330: covariate for which somebody answered including
6331: undefined. Usually 3: -1, 0 and 1. */
6332: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
6333: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
6334: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 6335:
1.242 brouard 6336: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
6337: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
6338: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
6339: /* modmincovj=3; modmaxcovj = 7; */
6340: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
6341: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
6342: /* defining two dummy variables: variables V1_1 and V1_2.*/
6343: /* nbcode[Tvar[j]][ij]=k; */
6344: /* nbcode[Tvar[j]][1]=0; */
6345: /* nbcode[Tvar[j]][2]=1; */
6346: /* nbcode[Tvar[j]][3]=2; */
6347: /* To be continued (not working yet). */
6348: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 6349:
6350: /* 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*/
6351: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
6352: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
6353: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
6354: /*, could be restored in the future */
6355: 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 6356: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
6357: break;
6358: }
6359: ij++;
1.287 brouard 6360: 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 6361: cptcode = ij; /* New max modality for covar j */
6362: } /* end of loop on modality i=-1 to 1 or more */
6363: break;
6364: case 1: /* Testing on varying covariate, could be simple and
6365: * should look at waves or product of fixed *
6366: * varying. No time to test -1, assuming 0 and 1 only */
6367: ij=0;
6368: for(i=0; i<=1;i++){
6369: nbcode[Tvar[k]][++ij]=i;
6370: }
6371: break;
6372: default:
6373: break;
6374: } /* end switch */
6375: } /* end dummy test */
1.342 brouard 6376: if(Dummy[k]==1 && Typevar[k] !=1 && Fixed ==0){ /* Fixed Quantitative covariate and not age product */
1.311 brouard 6377: 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 6378: if(Tvar[k]<=0 || Tvar[k]>=NCOVMAX){
6379: printf("Error k=%d \n",k);
6380: exit(1);
6381: }
1.311 brouard 6382: if(isnan(covar[Tvar[k]][i])){
6383: printf("ERROR, IMaCh doesn't treat fixed quantitative covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
6384: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
6385: fflush(ficlog);
6386: exit(1);
6387: }
6388: }
1.335 brouard 6389: } /* end Quanti */
1.287 brouard 6390: } /* 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 6391:
6392: for (k=-1; k< maxncov; k++) Ndum[k]=0;
6393: /* Look at fixed dummy (single or product) covariates to check empty modalities */
6394: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
6395: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
6396: 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 */
6397: 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 */
6398: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
6399: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
6400:
6401: ij=0;
6402: /* 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 6403: 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 */
6404: /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
1.242 brouard 6405: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
6406: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
1.335 brouard 6407: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy simple and non empty in the model */
6408: /* Typevar[k] =0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
6409: /* 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 6410: /* If product not in single variable we don't print results */
6411: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
1.335 brouard 6412: ++ij;/* V5 + V4 + V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V1, *//* V5 quanti, V2 quanti, V4, V3, V1 dummies */
6413: /* k= 1 2 3 4 5 6 7 8 9 */
6414: /* Tvar[k]= 5 4 3 6 5 2 7 1 1 */
6415: /* ij 1 2 3 */
6416: /* Tvaraff[ij]= 4 3 1 */
6417: /* Tmodelind[ij]=2 3 9 */
6418: /* TmodelInvind[ij]=2 1 1 */
1.242 brouard 6419: 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*/
6420: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
6421: 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 */
6422: if(Fixed[k]!=0)
6423: anyvaryingduminmodel=1;
6424: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
6425: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
6426: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
6427: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
6428: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
6429: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
6430: }
6431: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
6432: /* ij--; */
6433: /* cptcoveff=ij; /\*Number of total covariates*\/ */
1.335 brouard 6434: *cptcov=ij; /* cptcov= Number of total real effective simple dummies (fixed or time arying) effective (used as cptcoveff in other functions)
1.242 brouard 6435: * because they can be excluded from the model and real
6436: * if in the model but excluded because missing values, but how to get k from ij?*/
6437: for(j=ij+1; j<= cptcovt; j++){
6438: Tvaraff[j]=0;
6439: Tmodelind[j]=0;
6440: }
6441: for(j=ntveff+1; j<= cptcovt; j++){
6442: TmodelInvind[j]=0;
6443: }
6444: /* To be sorted */
6445: ;
6446: }
1.126 brouard 6447:
1.145 brouard 6448:
1.126 brouard 6449: /*********** Health Expectancies ****************/
6450:
1.235 brouard 6451: 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 6452:
6453: {
6454: /* Health expectancies, no variances */
1.329 brouard 6455: /* cij is the combination in the list of combination of dummy covariates */
6456: /* strstart is a string of time at start of computing */
1.164 brouard 6457: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 6458: int nhstepma, nstepma; /* Decreasing with age */
6459: double age, agelim, hf;
6460: double ***p3mat;
6461: double eip;
6462:
1.238 brouard 6463: /* pstamp(ficreseij); */
1.126 brouard 6464: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
6465: fprintf(ficreseij,"# Age");
6466: for(i=1; i<=nlstate;i++){
6467: for(j=1; j<=nlstate;j++){
6468: fprintf(ficreseij," e%1d%1d ",i,j);
6469: }
6470: fprintf(ficreseij," e%1d. ",i);
6471: }
6472: fprintf(ficreseij,"\n");
6473:
6474:
6475: if(estepm < stepm){
6476: printf ("Problem %d lower than %d\n",estepm, stepm);
6477: }
6478: else hstepm=estepm;
6479: /* We compute the life expectancy from trapezoids spaced every estepm months
6480: * This is mainly to measure the difference between two models: for example
6481: * if stepm=24 months pijx are given only every 2 years and by summing them
6482: * we are calculating an estimate of the Life Expectancy assuming a linear
6483: * progression in between and thus overestimating or underestimating according
6484: * to the curvature of the survival function. If, for the same date, we
6485: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6486: * to compare the new estimate of Life expectancy with the same linear
6487: * hypothesis. A more precise result, taking into account a more precise
6488: * curvature will be obtained if estepm is as small as stepm. */
6489:
6490: /* For example we decided to compute the life expectancy with the smallest unit */
6491: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6492: nhstepm is the number of hstepm from age to agelim
6493: nstepm is the number of stepm from age to agelin.
1.270 brouard 6494: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 6495: and note for a fixed period like estepm months */
6496: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6497: survival function given by stepm (the optimization length). Unfortunately it
6498: means that if the survival funtion is printed only each two years of age and if
6499: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6500: results. So we changed our mind and took the option of the best precision.
6501: */
6502: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6503:
6504: agelim=AGESUP;
6505: /* If stepm=6 months */
6506: /* Computed by stepm unit matrices, product of hstepm matrices, stored
6507: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
6508:
6509: /* nhstepm age range expressed in number of stepm */
6510: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6511: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6512: /* if (stepm >= YEARM) hstepm=1;*/
6513: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6514: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6515:
6516: for (age=bage; age<=fage; age ++){
6517: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6518: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6519: /* if (stepm >= YEARM) hstepm=1;*/
6520: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
6521:
6522: /* If stepm=6 months */
6523: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6524: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
1.330 brouard 6525: /* 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 6526: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 6527:
6528: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6529:
6530: printf("%d|",(int)age);fflush(stdout);
6531: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6532:
6533: /* Computing expectancies */
6534: for(i=1; i<=nlstate;i++)
6535: for(j=1; j<=nlstate;j++)
6536: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6537: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
6538:
6539: /* 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]);*/
6540:
6541: }
6542:
6543: fprintf(ficreseij,"%3.0f",age );
6544: for(i=1; i<=nlstate;i++){
6545: eip=0;
6546: for(j=1; j<=nlstate;j++){
6547: eip +=eij[i][j][(int)age];
6548: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
6549: }
6550: fprintf(ficreseij,"%9.4f", eip );
6551: }
6552: fprintf(ficreseij,"\n");
6553:
6554: }
6555: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6556: printf("\n");
6557: fprintf(ficlog,"\n");
6558:
6559: }
6560:
1.235 brouard 6561: 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 6562:
6563: {
6564: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 6565: to initial status i, ei. .
1.126 brouard 6566: */
1.336 brouard 6567: /* Very time consuming function, but already optimized with precov */
1.126 brouard 6568: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
6569: int nhstepma, nstepma; /* Decreasing with age */
6570: double age, agelim, hf;
6571: double ***p3matp, ***p3matm, ***varhe;
6572: double **dnewm,**doldm;
6573: double *xp, *xm;
6574: double **gp, **gm;
6575: double ***gradg, ***trgradg;
6576: int theta;
6577:
6578: double eip, vip;
6579:
6580: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
6581: xp=vector(1,npar);
6582: xm=vector(1,npar);
6583: dnewm=matrix(1,nlstate*nlstate,1,npar);
6584: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
6585:
6586: pstamp(ficresstdeij);
6587: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
6588: fprintf(ficresstdeij,"# Age");
6589: for(i=1; i<=nlstate;i++){
6590: for(j=1; j<=nlstate;j++)
6591: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
6592: fprintf(ficresstdeij," e%1d. ",i);
6593: }
6594: fprintf(ficresstdeij,"\n");
6595:
6596: pstamp(ficrescveij);
6597: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
6598: fprintf(ficrescveij,"# Age");
6599: for(i=1; i<=nlstate;i++)
6600: for(j=1; j<=nlstate;j++){
6601: cptj= (j-1)*nlstate+i;
6602: for(i2=1; i2<=nlstate;i2++)
6603: for(j2=1; j2<=nlstate;j2++){
6604: cptj2= (j2-1)*nlstate+i2;
6605: if(cptj2 <= cptj)
6606: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
6607: }
6608: }
6609: fprintf(ficrescveij,"\n");
6610:
6611: if(estepm < stepm){
6612: printf ("Problem %d lower than %d\n",estepm, stepm);
6613: }
6614: else hstepm=estepm;
6615: /* We compute the life expectancy from trapezoids spaced every estepm months
6616: * This is mainly to measure the difference between two models: for example
6617: * if stepm=24 months pijx are given only every 2 years and by summing them
6618: * we are calculating an estimate of the Life Expectancy assuming a linear
6619: * progression in between and thus overestimating or underestimating according
6620: * to the curvature of the survival function. If, for the same date, we
6621: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6622: * to compare the new estimate of Life expectancy with the same linear
6623: * hypothesis. A more precise result, taking into account a more precise
6624: * curvature will be obtained if estepm is as small as stepm. */
6625:
6626: /* For example we decided to compute the life expectancy with the smallest unit */
6627: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6628: nhstepm is the number of hstepm from age to agelim
6629: nstepm is the number of stepm from age to agelin.
6630: Look at hpijx to understand the reason of that which relies in memory size
6631: and note for a fixed period like estepm months */
6632: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6633: survival function given by stepm (the optimization length). Unfortunately it
6634: means that if the survival funtion is printed only each two years of age and if
6635: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6636: results. So we changed our mind and took the option of the best precision.
6637: */
6638: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6639:
6640: /* If stepm=6 months */
6641: /* nhstepm age range expressed in number of stepm */
6642: agelim=AGESUP;
6643: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
6644: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6645: /* if (stepm >= YEARM) hstepm=1;*/
6646: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6647:
6648: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6649: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6650: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
6651: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
6652: gp=matrix(0,nhstepm,1,nlstate*nlstate);
6653: gm=matrix(0,nhstepm,1,nlstate*nlstate);
6654:
6655: for (age=bage; age<=fage; age ++){
6656: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6657: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6658: /* if (stepm >= YEARM) hstepm=1;*/
6659: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 6660:
1.126 brouard 6661: /* If stepm=6 months */
6662: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6663: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
6664:
6665: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 6666:
1.126 brouard 6667: /* Computing Variances of health expectancies */
6668: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
6669: decrease memory allocation */
6670: for(theta=1; theta <=npar; theta++){
6671: for(i=1; i<=npar; i++){
1.222 brouard 6672: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6673: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 6674: }
1.235 brouard 6675: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
6676: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 6677:
1.126 brouard 6678: for(j=1; j<= nlstate; j++){
1.222 brouard 6679: for(i=1; i<=nlstate; i++){
6680: for(h=0; h<=nhstepm-1; h++){
6681: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
6682: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
6683: }
6684: }
1.126 brouard 6685: }
1.218 brouard 6686:
1.126 brouard 6687: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 6688: for(h=0; h<=nhstepm-1; h++){
6689: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
6690: }
1.126 brouard 6691: }/* End theta */
6692:
6693:
6694: for(h=0; h<=nhstepm-1; h++)
6695: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 6696: for(theta=1; theta <=npar; theta++)
6697: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 6698:
1.218 brouard 6699:
1.222 brouard 6700: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 6701: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 6702: varhe[ij][ji][(int)age] =0.;
1.218 brouard 6703:
1.222 brouard 6704: printf("%d|",(int)age);fflush(stdout);
6705: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6706: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 6707: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 6708: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
6709: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
6710: for(ij=1;ij<=nlstate*nlstate;ij++)
6711: for(ji=1;ji<=nlstate*nlstate;ji++)
6712: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 6713: }
6714: }
1.320 brouard 6715: /* if((int)age ==50){ */
6716: /* printf(" age=%d cij=%d nres=%d varhe[%d][%d]=%f ",(int)age, cij, nres, 1,2,varhe[1][2]); */
6717: /* } */
1.126 brouard 6718: /* Computing expectancies */
1.235 brouard 6719: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 6720: for(i=1; i<=nlstate;i++)
6721: for(j=1; j<=nlstate;j++)
1.222 brouard 6722: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6723: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 6724:
1.222 brouard 6725: /* 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 6726:
1.222 brouard 6727: }
1.269 brouard 6728:
6729: /* Standard deviation of expectancies ij */
1.126 brouard 6730: fprintf(ficresstdeij,"%3.0f",age );
6731: for(i=1; i<=nlstate;i++){
6732: eip=0.;
6733: vip=0.;
6734: for(j=1; j<=nlstate;j++){
1.222 brouard 6735: eip += eij[i][j][(int)age];
6736: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
6737: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
6738: 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 6739: }
6740: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
6741: }
6742: fprintf(ficresstdeij,"\n");
1.218 brouard 6743:
1.269 brouard 6744: /* Variance of expectancies ij */
1.126 brouard 6745: fprintf(ficrescveij,"%3.0f",age );
6746: for(i=1; i<=nlstate;i++)
6747: for(j=1; j<=nlstate;j++){
1.222 brouard 6748: cptj= (j-1)*nlstate+i;
6749: for(i2=1; i2<=nlstate;i2++)
6750: for(j2=1; j2<=nlstate;j2++){
6751: cptj2= (j2-1)*nlstate+i2;
6752: if(cptj2 <= cptj)
6753: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
6754: }
1.126 brouard 6755: }
6756: fprintf(ficrescveij,"\n");
1.218 brouard 6757:
1.126 brouard 6758: }
6759: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
6760: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
6761: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
6762: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
6763: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6764: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6765: printf("\n");
6766: fprintf(ficlog,"\n");
1.218 brouard 6767:
1.126 brouard 6768: free_vector(xm,1,npar);
6769: free_vector(xp,1,npar);
6770: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
6771: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
6772: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
6773: }
1.218 brouard 6774:
1.126 brouard 6775: /************ Variance ******************/
1.235 brouard 6776: 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 6777: {
1.279 brouard 6778: /** Variance of health expectancies
6779: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
6780: * double **newm;
6781: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
6782: */
1.218 brouard 6783:
6784: /* int movingaverage(); */
6785: double **dnewm,**doldm;
6786: double **dnewmp,**doldmp;
6787: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 6788: int first=0;
1.218 brouard 6789: int k;
6790: double *xp;
1.279 brouard 6791: double **gp, **gm; /**< for var eij */
6792: double ***gradg, ***trgradg; /**< for var eij */
6793: double **gradgp, **trgradgp; /**< for var p point j */
6794: double *gpp, *gmp; /**< for var p point j */
6795: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 6796: double ***p3mat;
6797: double age,agelim, hf;
6798: /* double ***mobaverage; */
6799: int theta;
6800: char digit[4];
6801: char digitp[25];
6802:
6803: char fileresprobmorprev[FILENAMELENGTH];
6804:
6805: if(popbased==1){
6806: if(mobilav!=0)
6807: strcpy(digitp,"-POPULBASED-MOBILAV_");
6808: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
6809: }
6810: else
6811: strcpy(digitp,"-STABLBASED_");
1.126 brouard 6812:
1.218 brouard 6813: /* if (mobilav!=0) { */
6814: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6815: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
6816: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
6817: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
6818: /* } */
6819: /* } */
6820:
6821: strcpy(fileresprobmorprev,"PRMORPREV-");
6822: sprintf(digit,"%-d",ij);
6823: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
6824: strcat(fileresprobmorprev,digit); /* Tvar to be done */
6825: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
6826: strcat(fileresprobmorprev,fileresu);
6827: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
6828: printf("Problem with resultfile: %s\n", fileresprobmorprev);
6829: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
6830: }
6831: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
6832: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
6833: pstamp(ficresprobmorprev);
6834: 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 6835: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
1.337 brouard 6836:
6837: /* We use TinvDoQresult[nres][resultmodel[nres][j] we sort according to the equation model and the resultline: it is a choice */
6838: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ /\* To be done*\/ */
6839: /* fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
6840: /* } */
6841: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */ /* To be done*/
1.344 brouard 6842: /* fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); */
1.337 brouard 6843: fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 6844: }
1.337 brouard 6845: /* for(j=1;j<=cptcoveff;j++) */
6846: /* fprintf(ficresprobmorprev," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,TnsdVar[Tvaraff[j]])]); */
1.238 brouard 6847: fprintf(ficresprobmorprev,"\n");
6848:
1.218 brouard 6849: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
6850: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6851: fprintf(ficresprobmorprev," p.%-d SE",j);
6852: for(i=1; i<=nlstate;i++)
6853: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
6854: }
6855: fprintf(ficresprobmorprev,"\n");
6856:
6857: fprintf(ficgp,"\n# Routine varevsij");
6858: fprintf(ficgp,"\nunset title \n");
6859: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
6860: 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");
6861: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 6862:
1.218 brouard 6863: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6864: pstamp(ficresvij);
6865: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
6866: if(popbased==1)
6867: 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);
6868: else
6869: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
6870: fprintf(ficresvij,"# Age");
6871: for(i=1; i<=nlstate;i++)
6872: for(j=1; j<=nlstate;j++)
6873: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
6874: fprintf(ficresvij,"\n");
6875:
6876: xp=vector(1,npar);
6877: dnewm=matrix(1,nlstate,1,npar);
6878: doldm=matrix(1,nlstate,1,nlstate);
6879: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
6880: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6881:
6882: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
6883: gpp=vector(nlstate+1,nlstate+ndeath);
6884: gmp=vector(nlstate+1,nlstate+ndeath);
6885: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 6886:
1.218 brouard 6887: if(estepm < stepm){
6888: printf ("Problem %d lower than %d\n",estepm, stepm);
6889: }
6890: else hstepm=estepm;
6891: /* For example we decided to compute the life expectancy with the smallest unit */
6892: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6893: nhstepm is the number of hstepm from age to agelim
6894: nstepm is the number of stepm from age to agelim.
6895: Look at function hpijx to understand why because of memory size limitations,
6896: we decided (b) to get a life expectancy respecting the most precise curvature of the
6897: survival function given by stepm (the optimization length). Unfortunately it
6898: means that if the survival funtion is printed every two years of age and if
6899: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6900: results. So we changed our mind and took the option of the best precision.
6901: */
6902: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6903: agelim = AGESUP;
6904: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6905: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6906: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6907: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6908: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
6909: gp=matrix(0,nhstepm,1,nlstate);
6910: gm=matrix(0,nhstepm,1,nlstate);
6911:
6912:
6913: for(theta=1; theta <=npar; theta++){
6914: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
6915: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6916: }
1.279 brouard 6917: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
6918: * returns into prlim .
1.288 brouard 6919: */
1.242 brouard 6920: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 6921:
6922: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 6923: if (popbased==1) {
6924: if(mobilav ==0){
6925: for(i=1; i<=nlstate;i++)
6926: prlim[i][i]=probs[(int)age][i][ij];
6927: }else{ /* mobilav */
6928: for(i=1; i<=nlstate;i++)
6929: prlim[i][i]=mobaverage[(int)age][i][ij];
6930: }
6931: }
1.295 brouard 6932: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h.
1.279 brouard 6933: */
6934: 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 6935: /**< 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 6936: * at horizon h in state j including mortality.
6937: */
1.218 brouard 6938: for(j=1; j<= nlstate; j++){
6939: for(h=0; h<=nhstepm; h++){
6940: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
6941: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
6942: }
6943: }
1.279 brouard 6944: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 6945: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 6946: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 6947: */
6948: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6949: for(i=1,gpp[j]=0.; i<= nlstate; i++)
6950: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 6951: }
6952:
6953: /* Again with minus shift */
1.218 brouard 6954:
6955: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
6956: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6957:
1.242 brouard 6958: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 6959:
6960: if (popbased==1) {
6961: if(mobilav ==0){
6962: for(i=1; i<=nlstate;i++)
6963: prlim[i][i]=probs[(int)age][i][ij];
6964: }else{ /* mobilav */
6965: for(i=1; i<=nlstate;i++)
6966: prlim[i][i]=mobaverage[(int)age][i][ij];
6967: }
6968: }
6969:
1.235 brouard 6970: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 6971:
6972: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
6973: for(h=0; h<=nhstepm; h++){
6974: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
6975: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
6976: }
6977: }
6978: /* This for computing probability of death (h=1 means
6979: computed over hstepm matrices product = hstepm*stepm months)
6980: as a weighted average of prlim.
6981: */
6982: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6983: for(i=1,gmp[j]=0.; i<= nlstate; i++)
6984: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6985: }
1.279 brouard 6986: /* end shifting computations */
6987:
6988: /**< Computing gradient matrix at horizon h
6989: */
1.218 brouard 6990: for(j=1; j<= nlstate; j++) /* vareij */
6991: for(h=0; h<=nhstepm; h++){
6992: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
6993: }
1.279 brouard 6994: /**< Gradient of overall mortality p.3 (or p.j)
6995: */
6996: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 6997: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
6998: }
6999:
7000: } /* End theta */
1.279 brouard 7001:
7002: /* We got the gradient matrix for each theta and state j */
1.218 brouard 7003: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
7004:
7005: for(h=0; h<=nhstepm; h++) /* veij */
7006: for(j=1; j<=nlstate;j++)
7007: for(theta=1; theta <=npar; theta++)
7008: trgradg[h][j][theta]=gradg[h][theta][j];
7009:
7010: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
7011: for(theta=1; theta <=npar; theta++)
7012: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 7013: /**< as well as its transposed matrix
7014: */
1.218 brouard 7015:
7016: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
7017: for(i=1;i<=nlstate;i++)
7018: for(j=1;j<=nlstate;j++)
7019: vareij[i][j][(int)age] =0.;
1.279 brouard 7020:
7021: /* Computing trgradg by matcov by gradg at age and summing over h
7022: * and k (nhstepm) formula 15 of article
7023: * Lievre-Brouard-Heathcote
7024: */
7025:
1.218 brouard 7026: for(h=0;h<=nhstepm;h++){
7027: for(k=0;k<=nhstepm;k++){
7028: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
7029: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
7030: for(i=1;i<=nlstate;i++)
7031: for(j=1;j<=nlstate;j++)
7032: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
7033: }
7034: }
7035:
1.279 brouard 7036: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
7037: * p.j overall mortality formula 49 but computed directly because
7038: * we compute the grad (wix pijx) instead of grad (pijx),even if
7039: * wix is independent of theta.
7040: */
1.218 brouard 7041: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
7042: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
7043: for(j=nlstate+1;j<=nlstate+ndeath;j++)
7044: for(i=nlstate+1;i<=nlstate+ndeath;i++)
7045: varppt[j][i]=doldmp[j][i];
7046: /* end ppptj */
7047: /* x centered again */
7048:
1.242 brouard 7049: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 7050:
7051: if (popbased==1) {
7052: if(mobilav ==0){
7053: for(i=1; i<=nlstate;i++)
7054: prlim[i][i]=probs[(int)age][i][ij];
7055: }else{ /* mobilav */
7056: for(i=1; i<=nlstate;i++)
7057: prlim[i][i]=mobaverage[(int)age][i][ij];
7058: }
7059: }
7060:
7061: /* This for computing probability of death (h=1 means
7062: computed over hstepm (estepm) matrices product = hstepm*stepm months)
7063: as a weighted average of prlim.
7064: */
1.235 brouard 7065: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 7066: for(j=nlstate+1;j<=nlstate+ndeath;j++){
7067: for(i=1,gmp[j]=0.;i<= nlstate; i++)
7068: gmp[j] += prlim[i][i]*p3mat[i][j][1];
7069: }
7070: /* end probability of death */
7071:
7072: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
7073: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
7074: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
7075: for(i=1; i<=nlstate;i++){
7076: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
7077: }
7078: }
7079: fprintf(ficresprobmorprev,"\n");
7080:
7081: fprintf(ficresvij,"%.0f ",age );
7082: for(i=1; i<=nlstate;i++)
7083: for(j=1; j<=nlstate;j++){
7084: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
7085: }
7086: fprintf(ficresvij,"\n");
7087: free_matrix(gp,0,nhstepm,1,nlstate);
7088: free_matrix(gm,0,nhstepm,1,nlstate);
7089: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
7090: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
7091: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
7092: } /* End age */
7093: free_vector(gpp,nlstate+1,nlstate+ndeath);
7094: free_vector(gmp,nlstate+1,nlstate+ndeath);
7095: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
7096: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
7097: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
7098: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
7099: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
7100: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
7101: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
7102: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
7103: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
7104: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
7105: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
7106: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
7107: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
7108: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
7109: 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);
7110: /* 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 7111: */
1.218 brouard 7112: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
7113: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 7114:
1.218 brouard 7115: free_vector(xp,1,npar);
7116: free_matrix(doldm,1,nlstate,1,nlstate);
7117: free_matrix(dnewm,1,nlstate,1,npar);
7118: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7119: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
7120: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7121: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
7122: fclose(ficresprobmorprev);
7123: fflush(ficgp);
7124: fflush(fichtm);
7125: } /* end varevsij */
1.126 brouard 7126:
7127: /************ Variance of prevlim ******************/
1.269 brouard 7128: 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 7129: {
1.205 brouard 7130: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 7131: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 7132:
1.268 brouard 7133: double **dnewmpar,**doldm;
1.126 brouard 7134: int i, j, nhstepm, hstepm;
7135: double *xp;
7136: double *gp, *gm;
7137: double **gradg, **trgradg;
1.208 brouard 7138: double **mgm, **mgp;
1.126 brouard 7139: double age,agelim;
7140: int theta;
7141:
7142: pstamp(ficresvpl);
1.288 brouard 7143: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 7144: fprintf(ficresvpl,"# Age ");
7145: if(nresult >=1)
7146: fprintf(ficresvpl," Result# ");
1.126 brouard 7147: for(i=1; i<=nlstate;i++)
7148: fprintf(ficresvpl," %1d-%1d",i,i);
7149: fprintf(ficresvpl,"\n");
7150:
7151: xp=vector(1,npar);
1.268 brouard 7152: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 7153: doldm=matrix(1,nlstate,1,nlstate);
7154:
7155: hstepm=1*YEARM; /* Every year of age */
7156: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
7157: agelim = AGESUP;
7158: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
7159: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7160: if (stepm >= YEARM) hstepm=1;
7161: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
7162: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 7163: mgp=matrix(1,npar,1,nlstate);
7164: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 7165: gp=vector(1,nlstate);
7166: gm=vector(1,nlstate);
7167:
7168: for(theta=1; theta <=npar; theta++){
7169: for(i=1; i<=npar; i++){ /* Computes gradient */
7170: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7171: }
1.288 brouard 7172: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
7173: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
7174: /* else */
7175: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 7176: for(i=1;i<=nlstate;i++){
1.126 brouard 7177: gp[i] = prlim[i][i];
1.208 brouard 7178: mgp[theta][i] = prlim[i][i];
7179: }
1.126 brouard 7180: for(i=1; i<=npar; i++) /* Computes gradient */
7181: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 7182: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
7183: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
7184: /* else */
7185: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 7186: for(i=1;i<=nlstate;i++){
1.126 brouard 7187: gm[i] = prlim[i][i];
1.208 brouard 7188: mgm[theta][i] = prlim[i][i];
7189: }
1.126 brouard 7190: for(i=1;i<=nlstate;i++)
7191: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 7192: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 7193: } /* End theta */
7194:
7195: trgradg =matrix(1,nlstate,1,npar);
7196:
7197: for(j=1; j<=nlstate;j++)
7198: for(theta=1; theta <=npar; theta++)
7199: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 7200: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7201: /* printf("\nmgm mgp %d ",(int)age); */
7202: /* for(j=1; j<=nlstate;j++){ */
7203: /* printf(" %d ",j); */
7204: /* for(theta=1; theta <=npar; theta++) */
7205: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
7206: /* printf("\n "); */
7207: /* } */
7208: /* } */
7209: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7210: /* printf("\n gradg %d ",(int)age); */
7211: /* for(j=1; j<=nlstate;j++){ */
7212: /* printf("%d ",j); */
7213: /* for(theta=1; theta <=npar; theta++) */
7214: /* printf("%d %lf ",theta,gradg[theta][j]); */
7215: /* printf("\n "); */
7216: /* } */
7217: /* } */
1.126 brouard 7218:
7219: for(i=1;i<=nlstate;i++)
7220: varpl[i][(int)age] =0.;
1.209 brouard 7221: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 7222: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7223: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 7224: }else{
1.268 brouard 7225: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7226: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 7227: }
1.126 brouard 7228: for(i=1;i<=nlstate;i++)
7229: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
7230:
7231: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 7232: if(nresult >=1)
7233: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 7234: for(i=1; i<=nlstate;i++){
1.126 brouard 7235: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 7236: /* for(j=1;j<=nlstate;j++) */
7237: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
7238: }
1.126 brouard 7239: fprintf(ficresvpl,"\n");
7240: free_vector(gp,1,nlstate);
7241: free_vector(gm,1,nlstate);
1.208 brouard 7242: free_matrix(mgm,1,npar,1,nlstate);
7243: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 7244: free_matrix(gradg,1,npar,1,nlstate);
7245: free_matrix(trgradg,1,nlstate,1,npar);
7246: } /* End age */
7247:
7248: free_vector(xp,1,npar);
7249: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 7250: free_matrix(dnewmpar,1,nlstate,1,nlstate);
7251:
7252: }
7253:
7254:
7255: /************ Variance of backprevalence limit ******************/
1.269 brouard 7256: 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 7257: {
7258: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
7259: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
7260:
7261: double **dnewmpar,**doldm;
7262: int i, j, nhstepm, hstepm;
7263: double *xp;
7264: double *gp, *gm;
7265: double **gradg, **trgradg;
7266: double **mgm, **mgp;
7267: double age,agelim;
7268: int theta;
7269:
7270: pstamp(ficresvbl);
7271: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
7272: fprintf(ficresvbl,"# Age ");
7273: if(nresult >=1)
7274: fprintf(ficresvbl," Result# ");
7275: for(i=1; i<=nlstate;i++)
7276: fprintf(ficresvbl," %1d-%1d",i,i);
7277: fprintf(ficresvbl,"\n");
7278:
7279: xp=vector(1,npar);
7280: dnewmpar=matrix(1,nlstate,1,npar);
7281: doldm=matrix(1,nlstate,1,nlstate);
7282:
7283: hstepm=1*YEARM; /* Every year of age */
7284: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
7285: agelim = AGEINF;
7286: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
7287: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7288: if (stepm >= YEARM) hstepm=1;
7289: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
7290: gradg=matrix(1,npar,1,nlstate);
7291: mgp=matrix(1,npar,1,nlstate);
7292: mgm=matrix(1,npar,1,nlstate);
7293: gp=vector(1,nlstate);
7294: gm=vector(1,nlstate);
7295:
7296: for(theta=1; theta <=npar; theta++){
7297: for(i=1; i<=npar; i++){ /* Computes gradient */
7298: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7299: }
7300: if(mobilavproj > 0 )
7301: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7302: else
7303: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7304: for(i=1;i<=nlstate;i++){
7305: gp[i] = bprlim[i][i];
7306: mgp[theta][i] = bprlim[i][i];
7307: }
7308: for(i=1; i<=npar; i++) /* Computes gradient */
7309: xp[i] = x[i] - (i==theta ?delti[theta]:0);
7310: if(mobilavproj > 0 )
7311: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7312: else
7313: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7314: for(i=1;i<=nlstate;i++){
7315: gm[i] = bprlim[i][i];
7316: mgm[theta][i] = bprlim[i][i];
7317: }
7318: for(i=1;i<=nlstate;i++)
7319: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
7320: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
7321: } /* End theta */
7322:
7323: trgradg =matrix(1,nlstate,1,npar);
7324:
7325: for(j=1; j<=nlstate;j++)
7326: for(theta=1; theta <=npar; theta++)
7327: trgradg[j][theta]=gradg[theta][j];
7328: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7329: /* printf("\nmgm mgp %d ",(int)age); */
7330: /* for(j=1; j<=nlstate;j++){ */
7331: /* printf(" %d ",j); */
7332: /* for(theta=1; theta <=npar; theta++) */
7333: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
7334: /* printf("\n "); */
7335: /* } */
7336: /* } */
7337: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7338: /* printf("\n gradg %d ",(int)age); */
7339: /* for(j=1; j<=nlstate;j++){ */
7340: /* printf("%d ",j); */
7341: /* for(theta=1; theta <=npar; theta++) */
7342: /* printf("%d %lf ",theta,gradg[theta][j]); */
7343: /* printf("\n "); */
7344: /* } */
7345: /* } */
7346:
7347: for(i=1;i<=nlstate;i++)
7348: varbpl[i][(int)age] =0.;
7349: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
7350: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7351: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
7352: }else{
7353: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7354: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
7355: }
7356: for(i=1;i<=nlstate;i++)
7357: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
7358:
7359: fprintf(ficresvbl,"%.0f ",age );
7360: if(nresult >=1)
7361: fprintf(ficresvbl,"%d ",nres );
7362: for(i=1; i<=nlstate;i++)
7363: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
7364: fprintf(ficresvbl,"\n");
7365: free_vector(gp,1,nlstate);
7366: free_vector(gm,1,nlstate);
7367: free_matrix(mgm,1,npar,1,nlstate);
7368: free_matrix(mgp,1,npar,1,nlstate);
7369: free_matrix(gradg,1,npar,1,nlstate);
7370: free_matrix(trgradg,1,nlstate,1,npar);
7371: } /* End age */
7372:
7373: free_vector(xp,1,npar);
7374: free_matrix(doldm,1,nlstate,1,npar);
7375: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 7376:
7377: }
7378:
7379: /************ Variance of one-step probabilities ******************/
7380: 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 7381: {
7382: int i, j=0, k1, l1, tj;
7383: int k2, l2, j1, z1;
7384: int k=0, l;
7385: int first=1, first1, first2;
1.326 brouard 7386: int nres=0; /* New */
1.222 brouard 7387: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
7388: double **dnewm,**doldm;
7389: double *xp;
7390: double *gp, *gm;
7391: double **gradg, **trgradg;
7392: double **mu;
7393: double age, cov[NCOVMAX+1];
7394: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
7395: int theta;
7396: char fileresprob[FILENAMELENGTH];
7397: char fileresprobcov[FILENAMELENGTH];
7398: char fileresprobcor[FILENAMELENGTH];
7399: double ***varpij;
7400:
7401: strcpy(fileresprob,"PROB_");
7402: strcat(fileresprob,fileres);
7403: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
7404: printf("Problem with resultfile: %s\n", fileresprob);
7405: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
7406: }
7407: strcpy(fileresprobcov,"PROBCOV_");
7408: strcat(fileresprobcov,fileresu);
7409: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
7410: printf("Problem with resultfile: %s\n", fileresprobcov);
7411: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
7412: }
7413: strcpy(fileresprobcor,"PROBCOR_");
7414: strcat(fileresprobcor,fileresu);
7415: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
7416: printf("Problem with resultfile: %s\n", fileresprobcor);
7417: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
7418: }
7419: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7420: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7421: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7422: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7423: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7424: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7425: pstamp(ficresprob);
7426: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
7427: fprintf(ficresprob,"# Age");
7428: pstamp(ficresprobcov);
7429: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
7430: fprintf(ficresprobcov,"# Age");
7431: pstamp(ficresprobcor);
7432: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
7433: fprintf(ficresprobcor,"# Age");
1.126 brouard 7434:
7435:
1.222 brouard 7436: for(i=1; i<=nlstate;i++)
7437: for(j=1; j<=(nlstate+ndeath);j++){
7438: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
7439: fprintf(ficresprobcov," p%1d-%1d ",i,j);
7440: fprintf(ficresprobcor," p%1d-%1d ",i,j);
7441: }
7442: /* fprintf(ficresprob,"\n");
7443: fprintf(ficresprobcov,"\n");
7444: fprintf(ficresprobcor,"\n");
7445: */
7446: xp=vector(1,npar);
7447: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7448: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
7449: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
7450: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
7451: first=1;
7452: fprintf(ficgp,"\n# Routine varprob");
7453: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
7454: fprintf(fichtm,"\n");
7455:
1.288 brouard 7456: 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 7457: 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);
7458: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 7459: and drawn. It helps understanding how is the covariance between two incidences.\
7460: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 7461: 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 7462: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
7463: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
7464: standard deviations wide on each axis. <br>\
7465: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
7466: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
7467: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
7468:
1.222 brouard 7469: cov[1]=1;
7470: /* tj=cptcoveff; */
1.225 brouard 7471: tj = (int) pow(2,cptcoveff);
1.222 brouard 7472: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
7473: j1=0;
1.332 brouard 7474:
7475: for(nres=1;nres <=nresult; nres++){ /* For each resultline */
7476: for(j1=1; j1<=tj;j1++){ /* For any combination of dummy covariates, fixed and varying */
1.342 brouard 7477: /* 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 7478: if(tj != 1 && TKresult[nres]!= j1)
7479: continue;
7480:
7481: /* for(j1=1; j1<=tj;j1++){ /\* For each valid combination of covariates or only once*\/ */
7482: /* for(nres=1;nres <=1; nres++){ /\* For each resultline *\/ */
7483: /* /\* for(nres=1;nres <=nresult; nres++){ /\\* For each resultline *\\/ *\/ */
1.222 brouard 7484: if (cptcovn>0) {
1.334 brouard 7485: fprintf(ficresprob, "\n#********** Variable ");
7486: fprintf(ficresprobcov, "\n#********** Variable ");
7487: fprintf(ficgp, "\n#********** Variable ");
7488: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
7489: fprintf(ficresprobcor, "\n#********** Variable ");
7490:
7491: /* Including quantitative variables of the resultline to be done */
7492: for (z1=1; z1<=cptcovs; z1++){ /* Loop on each variable of this resultline */
1.343 brouard 7493: /* printf("Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model); */
1.338 brouard 7494: fprintf(ficlog,"Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model);
7495: /* 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 7496: if(Dummy[modelresult[nres][z1]]==0){/* Dummy variable of the variable in position modelresult in the model corresponding to z1 in resultline */
7497: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed referenced to model equation */
7498: 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 */
7499: 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 */
7500: 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 */
7501: 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 */
7502: 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 */
7503: fprintf(ficresprob,"fixed ");
7504: fprintf(ficresprobcov,"fixed ");
7505: fprintf(ficgp,"fixed ");
7506: fprintf(fichtmcov,"fixed ");
7507: fprintf(ficresprobcor,"fixed ");
7508: }else{
7509: fprintf(ficresprob,"varyi ");
7510: fprintf(ficresprobcov,"varyi ");
7511: fprintf(ficgp,"varyi ");
7512: fprintf(fichtmcov,"varyi ");
7513: fprintf(ficresprobcor,"varyi ");
7514: }
7515: }else if(Dummy[modelresult[nres][z1]]==1){ /* Quanti variable */
7516: /* For each selected (single) quantitative value */
1.337 brouard 7517: fprintf(ficresprob," V%d=%lg ",Tvqresult[nres][z1],Tqresult[nres][z1]);
1.334 brouard 7518: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed */
7519: fprintf(ficresprob,"fixed ");
7520: fprintf(ficresprobcov,"fixed ");
7521: fprintf(ficgp,"fixed ");
7522: fprintf(fichtmcov,"fixed ");
7523: fprintf(ficresprobcor,"fixed ");
7524: }else{
7525: fprintf(ficresprob,"varyi ");
7526: fprintf(ficresprobcov,"varyi ");
7527: fprintf(ficgp,"varyi ");
7528: fprintf(fichtmcov,"varyi ");
7529: fprintf(ficresprobcor,"varyi ");
7530: }
7531: }else{
7532: 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 */
7533: 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 */
7534: exit(1);
7535: }
7536: } /* End loop on variable of this resultline */
7537: /* for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]); */
1.222 brouard 7538: fprintf(ficresprob, "**********\n#\n");
7539: fprintf(ficresprobcov, "**********\n#\n");
7540: fprintf(ficgp, "**********\n#\n");
7541: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
7542: fprintf(ficresprobcor, "**********\n#");
7543: if(invalidvarcomb[j1]){
7544: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
7545: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
7546: continue;
7547: }
7548: }
7549: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
7550: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7551: gp=vector(1,(nlstate)*(nlstate+ndeath));
7552: gm=vector(1,(nlstate)*(nlstate+ndeath));
1.334 brouard 7553: for (age=bage; age<=fage; age ++){ /* Fo each age we feed the model equation with covariates, using precov as in hpxij() ? */
1.222 brouard 7554: cov[2]=age;
7555: if(nagesqr==1)
7556: cov[3]= age*age;
1.334 brouard 7557: /* New code end of combination but for each resultline */
7558: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
7559: if(Typevar[k1]==1){ /* A product with age */
7560: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.326 brouard 7561: }else{
1.334 brouard 7562: cov[2+nagesqr+k1]=precov[nres][k1];
1.326 brouard 7563: }
1.334 brouard 7564: }/* End of loop on model equation */
7565: /* Old code */
7566: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
7567: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)]; *\/ */
7568: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
7569: /* /\* Here comes the value of the covariate 'j1' after renumbering k with single dummy covariates *\/ */
7570: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(j1,TnsdVar[TvarsD[k]])]; */
7571: /* /\*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*\//\* j1 1 2 3 4 */
7572: /* * 1 1 1 1 1 */
7573: /* * 2 2 1 1 1 */
7574: /* * 3 1 2 1 1 */
7575: /* *\/ */
7576: /* /\* nbcode[1][1]=0 nbcode[1][2]=1;*\/ */
7577: /* } */
7578: /* /\* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
7579: /* /\* ) p nbcode[Tvar[Tage[k]]][(1 & (ij-1) >> (k-1))+1] *\/ */
7580: /* /\*for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; *\/ */
7581: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
7582: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
7583: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(j1,TnsdVar[Tvar[Tage[k]]])]*cov[2]; */
7584: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
7585: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
7586: /* 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]); */
7587: /* /\* cov[2+nagesqr+Tage[k]]=meanq[k]/idq[k]*cov[2];/\\* Using the mean of quantitative variable Tvar[Tage[k]] /\\* Tqresult[nres][k]; *\\/ *\/ */
7588: /* /\* exit(1); *\/ */
7589: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
7590: /* } */
7591: /* /\* cov[2+Tage[k]+nagesqr]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
7592: /* } */
7593: /* for (k=1; k<=cptcovprod;k++){/\* For product without age *\/ */
7594: /* if(Dummy[Tvard[k][1]]==0){ */
7595: /* if(Dummy[Tvard[k][2]]==0){ */
7596: /* 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]])]; */
7597: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
7598: /* }else{ /\* Should we use the mean of the quantitative variables? *\/ */
7599: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(j1,TnsdVar[Tvard[k][1]])] * Tqresult[nres][resultmodel[nres][k]]; */
7600: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
7601: /* } */
7602: /* }else{ */
7603: /* if(Dummy[Tvard[k][2]]==0){ */
7604: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(j1,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][TnsdVar[Tvard[k][1]]]; */
7605: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
7606: /* }else{ */
7607: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][TnsdVar[Tvard[k][1]]]* Tqinvresult[nres][TnsdVar[Tvard[k][2]]]; */
7608: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
7609: /* } */
7610: /* } */
7611: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
7612: /* } */
1.326 brouard 7613: /* For each age and combination of dummy covariates we slightly move the parameters of delti in order to get the gradient*/
1.222 brouard 7614: for(theta=1; theta <=npar; theta++){
7615: for(i=1; i<=npar; i++)
7616: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 7617:
1.222 brouard 7618: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 7619:
1.222 brouard 7620: k=0;
7621: for(i=1; i<= (nlstate); i++){
7622: for(j=1; j<=(nlstate+ndeath);j++){
7623: k=k+1;
7624: gp[k]=pmmij[i][j];
7625: }
7626: }
1.220 brouard 7627:
1.222 brouard 7628: for(i=1; i<=npar; i++)
7629: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 7630:
1.222 brouard 7631: pmij(pmmij,cov,ncovmodel,xp,nlstate);
7632: k=0;
7633: for(i=1; i<=(nlstate); i++){
7634: for(j=1; j<=(nlstate+ndeath);j++){
7635: k=k+1;
7636: gm[k]=pmmij[i][j];
7637: }
7638: }
1.220 brouard 7639:
1.222 brouard 7640: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
7641: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
7642: }
1.126 brouard 7643:
1.222 brouard 7644: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
7645: for(theta=1; theta <=npar; theta++)
7646: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 7647:
1.222 brouard 7648: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
7649: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 7650:
1.222 brouard 7651: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 7652:
1.222 brouard 7653: k=0;
7654: for(i=1; i<=(nlstate); i++){
7655: for(j=1; j<=(nlstate+ndeath);j++){
7656: k=k+1;
7657: mu[k][(int) age]=pmmij[i][j];
7658: }
7659: }
7660: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
7661: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
7662: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 7663:
1.222 brouard 7664: /*printf("\n%d ",(int)age);
7665: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7666: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7667: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7668: }*/
1.220 brouard 7669:
1.222 brouard 7670: fprintf(ficresprob,"\n%d ",(int)age);
7671: fprintf(ficresprobcov,"\n%d ",(int)age);
7672: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 7673:
1.222 brouard 7674: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
7675: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
7676: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7677: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
7678: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
7679: }
7680: i=0;
7681: for (k=1; k<=(nlstate);k++){
7682: for (l=1; l<=(nlstate+ndeath);l++){
7683: i++;
7684: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
7685: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
7686: for (j=1; j<=i;j++){
7687: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
7688: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
7689: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
7690: }
7691: }
7692: }/* end of loop for state */
7693: } /* end of loop for age */
7694: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
7695: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
7696: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7697: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7698:
7699: /* Confidence intervalle of pij */
7700: /*
7701: fprintf(ficgp,"\nunset parametric;unset label");
7702: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
7703: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
7704: 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);
7705: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
7706: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
7707: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
7708: */
7709:
7710: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
7711: first1=1;first2=2;
7712: for (k2=1; k2<=(nlstate);k2++){
7713: for (l2=1; l2<=(nlstate+ndeath);l2++){
7714: if(l2==k2) continue;
7715: j=(k2-1)*(nlstate+ndeath)+l2;
7716: for (k1=1; k1<=(nlstate);k1++){
7717: for (l1=1; l1<=(nlstate+ndeath);l1++){
7718: if(l1==k1) continue;
7719: i=(k1-1)*(nlstate+ndeath)+l1;
7720: if(i<=j) continue;
7721: for (age=bage; age<=fage; age ++){
7722: if ((int)age %5==0){
7723: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
7724: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
7725: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
7726: mu1=mu[i][(int) age]/stepm*YEARM ;
7727: mu2=mu[j][(int) age]/stepm*YEARM;
7728: c12=cv12/sqrt(v1*v2);
7729: /* Computing eigen value of matrix of covariance */
7730: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7731: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7732: if ((lc2 <0) || (lc1 <0) ){
7733: if(first2==1){
7734: first1=0;
7735: 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);
7736: }
7737: 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);
7738: /* lc1=fabs(lc1); */ /* If we want to have them positive */
7739: /* lc2=fabs(lc2); */
7740: }
1.220 brouard 7741:
1.222 brouard 7742: /* Eigen vectors */
1.280 brouard 7743: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
7744: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7745: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7746: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
7747: }else
7748: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 7749: /*v21=sqrt(1.-v11*v11); *//* error */
7750: v21=(lc1-v1)/cv12*v11;
7751: v12=-v21;
7752: v22=v11;
7753: tnalp=v21/v11;
7754: if(first1==1){
7755: first1=0;
7756: 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);
7757: }
7758: 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);
7759: /*printf(fignu*/
7760: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
7761: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
7762: if(first==1){
7763: first=0;
7764: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
7765: fprintf(ficgp,"\nset parametric;unset label");
7766: 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);
7767: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 7768: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 7769: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 7770: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 7771: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
7772: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7773: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7774: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
7775: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7776: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7777: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7778: 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 7779: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
7780: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 7781: }else{
7782: first=0;
7783: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
7784: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7785: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7786: 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 7787: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
7788: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 7789: }/* if first */
7790: } /* age mod 5 */
7791: } /* end loop age */
7792: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7793: first=1;
7794: } /*l12 */
7795: } /* k12 */
7796: } /*l1 */
7797: }/* k1 */
1.332 brouard 7798: } /* loop on combination of covariates j1 */
1.326 brouard 7799: } /* loop on nres */
1.222 brouard 7800: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
7801: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
7802: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
7803: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
7804: free_vector(xp,1,npar);
7805: fclose(ficresprob);
7806: fclose(ficresprobcov);
7807: fclose(ficresprobcor);
7808: fflush(ficgp);
7809: fflush(fichtmcov);
7810: }
1.126 brouard 7811:
7812:
7813: /******************* Printing html file ***********/
1.201 brouard 7814: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 7815: int lastpass, int stepm, int weightopt, char model[],\
7816: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.296 brouard 7817: int popforecast, int mobilav, int prevfcast, int mobilavproj, int prevbcast, int estepm , \
7818: double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \
7819: double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){
1.237 brouard 7820: int jj1, k1, i1, cpt, k4, nres;
1.319 brouard 7821: /* In fact some results are already printed in fichtm which is open */
1.126 brouard 7822: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
7823: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
7824: </ul>");
1.319 brouard 7825: /* fprintf(fichtm,"<ul><li> model=1+age+%s\n \ */
7826: /* </ul>", model); */
1.214 brouard 7827: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
7828: 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",
7829: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
1.332 brouard 7830: 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 7831: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
7832: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 7833: fprintf(fichtm,"\
7834: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 7835: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 7836: fprintf(fichtm,"\
1.217 brouard 7837: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
7838: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
7839: fprintf(fichtm,"\
1.288 brouard 7840: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 7841: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 7842: fprintf(fichtm,"\
1.288 brouard 7843: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 7844: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
7845: fprintf(fichtm,"\
1.211 brouard 7846: - (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 7847: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 7848: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 7849: if(prevfcast==1){
7850: fprintf(fichtm,"\
7851: - Prevalence projections by age and states: \
1.201 brouard 7852: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 7853: }
1.126 brouard 7854:
7855:
1.225 brouard 7856: m=pow(2,cptcoveff);
1.222 brouard 7857: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7858:
1.317 brouard 7859: fprintf(fichtm," \n<ul><li><b>Graphs (first order)</b></li><p>");
1.264 brouard 7860:
7861: jj1=0;
7862:
7863: fprintf(fichtm," \n<ul>");
1.337 brouard 7864: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
7865: /* k1=nres; */
1.338 brouard 7866: k1=TKresult[nres];
7867: if(TKresult[nres]==0)k1=1; /* To be checked for no result */
1.337 brouard 7868: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
7869: /* if(m != 1 && TKresult[nres]!= k1) */
7870: /* continue; */
1.264 brouard 7871: jj1++;
7872: if (cptcovn > 0) {
7873: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
1.337 brouard 7874: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
7875: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 7876: }
1.337 brouard 7877: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
7878: /* fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
7879: /* } */
7880: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
7881: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
7882: /* } */
1.264 brouard 7883: fprintf(fichtm,"\">");
7884:
7885: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
7886: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 7887: for (cpt=1; cpt<=cptcovs;cpt++){
7888: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 7889: }
1.337 brouard 7890: /* fprintf(fichtm,"************ Results for covariates"); */
7891: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
7892: /* fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
7893: /* } */
7894: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
7895: /* fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
7896: /* } */
1.264 brouard 7897: if(invalidvarcomb[k1]){
7898: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
7899: continue;
7900: }
7901: fprintf(fichtm,"</a></li>");
7902: } /* cptcovn >0 */
7903: }
1.317 brouard 7904: fprintf(fichtm," \n</ul>");
1.264 brouard 7905:
1.222 brouard 7906: jj1=0;
1.237 brouard 7907:
1.337 brouard 7908: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
7909: /* k1=nres; */
1.338 brouard 7910: k1=TKresult[nres];
7911: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 7912: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
7913: /* if(m != 1 && TKresult[nres]!= k1) */
7914: /* continue; */
1.220 brouard 7915:
1.222 brouard 7916: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7917: jj1++;
7918: if (cptcovn > 0) {
1.264 brouard 7919: fprintf(fichtm,"\n<p><a name=\"rescov");
1.337 brouard 7920: for (cpt=1; cpt<=cptcovs;cpt++){
7921: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 7922: }
1.337 brouard 7923: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
7924: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
7925: /* } */
1.264 brouard 7926: fprintf(fichtm,"\"</a>");
7927:
1.222 brouard 7928: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 7929: for (cpt=1; cpt<=cptcovs;cpt++){
7930: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
7931: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 7932: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
7933: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 7934: }
1.230 brouard 7935: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.338 brouard 7936: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.222 brouard 7937: if(invalidvarcomb[k1]){
7938: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
7939: printf("\nCombination (%d) ignored because no cases \n",k1);
7940: continue;
7941: }
7942: }
7943: /* aij, bij */
1.259 brouard 7944: 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 7945: <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 7946: /* Pij */
1.241 brouard 7947: 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> \
7948: <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 7949: /* Quasi-incidences */
7950: 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 7951: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 7952: 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 7953: 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> \
7954: <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 7955: /* Survival functions (period) in state j */
7956: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 7957: 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);
7958: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
7959: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.222 brouard 7960: }
7961: /* State specific survival functions (period) */
7962: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 7963: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
7964: And probability to be observed in various states (up to %d) being in state %d at different ages. \
1.329 brouard 7965: <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);
7966: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
7967: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.222 brouard 7968: }
1.288 brouard 7969: /* Period (forward stable) prevalence in each health state */
1.222 brouard 7970: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 7971: 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 7972: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
1.329 brouard 7973: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.222 brouard 7974: }
1.296 brouard 7975: if(prevbcast==1){
1.288 brouard 7976: /* Backward prevalence in each health state */
1.222 brouard 7977: for(cpt=1; cpt<=nlstate;cpt++){
1.338 brouard 7978: 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);
7979: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJB_"),subdirf2(optionfilefiname,"PIJB_"));
7980: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.222 brouard 7981: }
1.217 brouard 7982: }
1.222 brouard 7983: if(prevfcast==1){
1.288 brouard 7984: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 7985: for(cpt=1; cpt<=nlstate;cpt++){
1.314 brouard 7986: 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);
7987: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"F_"),subdirf2(optionfilefiname,"F_"));
7988: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",
7989: subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 7990: }
7991: }
1.296 brouard 7992: if(prevbcast==1){
1.268 brouard 7993: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
7994: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 7995: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
7996: 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 \
7997: 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 7998: 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);
7999: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"FB_"),subdirf2(optionfilefiname,"FB_"));
8000: fprintf(fichtm," <img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
1.268 brouard 8001: }
8002: }
1.220 brouard 8003:
1.222 brouard 8004: for(cpt=1; cpt<=nlstate;cpt++) {
1.314 brouard 8005: 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);
8006: fprintf(fichtm," (data from text file <a href=\"%s.txt\"> %s.txt</a>)\n<br>",subdirf2(optionfilefiname,"E_"),subdirf2(optionfilefiname,"E_"));
8007: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres );
1.222 brouard 8008: }
8009: /* } /\* end i1 *\/ */
1.337 brouard 8010: }/* End k1=nres */
1.222 brouard 8011: fprintf(fichtm,"</ul>");
1.126 brouard 8012:
1.222 brouard 8013: fprintf(fichtm,"\
1.126 brouard 8014: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 8015: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 8016: - 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 8017: But because parameters are usually highly correlated (a higher incidence of disability \
8018: and a higher incidence of recovery can give very close observed transition) it might \
8019: be very useful to look not only at linear confidence intervals estimated from the \
8020: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
8021: (parameters) of the logistic regression, it might be more meaningful to visualize the \
8022: covariance matrix of the one-step probabilities. \
8023: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 8024:
1.222 brouard 8025: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
8026: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
8027: fprintf(fichtm,"\
1.126 brouard 8028: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 8029: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 8030:
1.222 brouard 8031: fprintf(fichtm,"\
1.126 brouard 8032: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 8033: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
8034: fprintf(fichtm,"\
1.126 brouard 8035: - 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): \
8036: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 8037: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 8038: fprintf(fichtm,"\
1.126 brouard 8039: - (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): \
8040: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 8041: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 8042: fprintf(fichtm,"\
1.288 brouard 8043: - 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 8044: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
8045: fprintf(fichtm,"\
1.128 brouard 8046: - 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 8047: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
8048: fprintf(fichtm,"\
1.288 brouard 8049: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 8050: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 8051:
8052: /* if(popforecast==1) fprintf(fichtm,"\n */
8053: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
8054: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
8055: /* <br>",fileres,fileres,fileres,fileres); */
8056: /* else */
1.338 brouard 8057: /* 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 8058: fflush(fichtm);
1.126 brouard 8059:
1.225 brouard 8060: m=pow(2,cptcoveff);
1.222 brouard 8061: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 8062:
1.317 brouard 8063: fprintf(fichtm," <ul><li><b>Graphs (second order)</b></li><p>");
8064:
8065: jj1=0;
8066:
8067: fprintf(fichtm," \n<ul>");
1.337 brouard 8068: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8069: /* k1=nres; */
1.338 brouard 8070: k1=TKresult[nres];
1.337 brouard 8071: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
8072: /* if(m != 1 && TKresult[nres]!= k1) */
8073: /* continue; */
1.317 brouard 8074: jj1++;
8075: if (cptcovn > 0) {
8076: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescovsecond");
1.337 brouard 8077: for (cpt=1; cpt<=cptcovs;cpt++){
8078: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8079: }
8080: fprintf(fichtm,"\">");
8081:
8082: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
8083: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 8084: for (cpt=1; cpt<=cptcovs;cpt++){
8085: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8086: }
8087: if(invalidvarcomb[k1]){
8088: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
8089: continue;
8090: }
8091: fprintf(fichtm,"</a></li>");
8092: } /* cptcovn >0 */
1.337 brouard 8093: } /* End nres */
1.317 brouard 8094: fprintf(fichtm," \n</ul>");
8095:
1.222 brouard 8096: jj1=0;
1.237 brouard 8097:
1.241 brouard 8098: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8099: /* k1=nres; */
1.338 brouard 8100: k1=TKresult[nres];
8101: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8102: /* for(k1=1; k1<=m;k1++){ */
8103: /* if(m != 1 && TKresult[nres]!= k1) */
8104: /* continue; */
1.222 brouard 8105: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
8106: jj1++;
1.126 brouard 8107: if (cptcovn > 0) {
1.317 brouard 8108: fprintf(fichtm,"\n<p><a name=\"rescovsecond");
1.337 brouard 8109: for (cpt=1; cpt<=cptcovs;cpt++){
8110: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8111: }
8112: fprintf(fichtm,"\"</a>");
8113:
1.126 brouard 8114: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 8115: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcoveff number of variables */
8116: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
8117: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 8118: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
1.317 brouard 8119: }
1.237 brouard 8120:
1.338 brouard 8121: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.220 brouard 8122:
1.222 brouard 8123: if(invalidvarcomb[k1]){
8124: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
8125: continue;
8126: }
1.337 brouard 8127: } /* If cptcovn >0 */
1.126 brouard 8128: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 8129: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.314 brouard 8130: 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);
8131: fprintf(fichtm," (data from text file <a href=\"%s\">%s</a>)\n <br>",subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
8132: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"V_"), cpt,k1,nres);
1.126 brouard 8133: }
8134: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.314 brouard 8135: health expectancies in each live states (1 to %d). If popbased=1 the smooth (due to the model) \
1.128 brouard 8136: true period expectancies (those weighted with period prevalences are also\
8137: drawn in addition to the population based expectancies computed using\
1.314 brouard 8138: 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);
8139: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>) \n<br>",subdirf2(optionfilefiname,"T_"),subdirf2(optionfilefiname,"T_"));
8140: fprintf(fichtm,"<img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 8141: /* } /\* end i1 *\/ */
1.241 brouard 8142: }/* End nres */
1.222 brouard 8143: fprintf(fichtm,"</ul>");
8144: fflush(fichtm);
1.126 brouard 8145: }
8146:
8147: /******************* Gnuplot file **************/
1.296 brouard 8148: 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 8149:
8150: char dirfileres[132],optfileres[132];
1.264 brouard 8151: char gplotcondition[132], gplotlabel[132];
1.343 brouard 8152: int cpt=0,k1=0,i=0,k=0,j=0,jk=0,k2=0,k3=0,k4=0,kf=0,kvar=0,kk=0,ipos=0,iposold=0,ij=0, ijp=0, l=0;
1.211 brouard 8153: int lv=0, vlv=0, kl=0;
1.130 brouard 8154: int ng=0;
1.201 brouard 8155: int vpopbased;
1.223 brouard 8156: int ioffset; /* variable offset for columns */
1.270 brouard 8157: int iyearc=1; /* variable column for year of projection */
8158: int iagec=1; /* variable column for age of projection */
1.235 brouard 8159: int nres=0; /* Index of resultline */
1.266 brouard 8160: int istart=1; /* For starting graphs in projections */
1.219 brouard 8161:
1.126 brouard 8162: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
8163: /* printf("Problem with file %s",optionfilegnuplot); */
8164: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
8165: /* } */
8166:
8167: /*#ifdef windows */
8168: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 8169: /*#endif */
1.225 brouard 8170: m=pow(2,cptcoveff);
1.126 brouard 8171:
1.274 brouard 8172: /* diagram of the model */
8173: fprintf(ficgp,"\n#Diagram of the model \n");
8174: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
8175: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
8176: 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);
8177:
1.343 brouard 8178: fprintf(ficgp,"\n#Centripete arrows (turning in other direction (1-i) instead of (i-1)) \nset for [i=1:%d] for [j=1:%d] arrow (%d+1)*10+i from cos(pi*((1-(%d/2)*2./%d)/2+(1-i)*2./%d))-(i!=j?(i-j)/abs(i-j)*delta:0), yoff +sin(pi*((1-(%d/2)*2./%d)/2+(1-i)*2./%d)) + (i!=j?(i-j)/abs(i-j)*delta:0) rto -0.80*(cos(pi*((1-(%d/2)*2./%d)/2+(1-i)*2./%d))+(i!=j?(i-j)/abs(i-j)*delta:0) ), -0.80*(sin(pi*((1-(%d/2)*2./%d)/2+(1-i)*2./%d)) + (i!=j?(i-j)/abs(i-j)*delta:0) + yoff ) ls 4\n",nlstate, nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate);
1.274 brouard 8179: fprintf(ficgp,"\n#show arrow\nunset label\n");
8180: 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);
8181: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
8182: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
8183: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
8184: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
8185:
1.202 brouard 8186: /* Contribution to likelihood */
8187: /* Plot the probability implied in the likelihood */
1.223 brouard 8188: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
8189: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
8190: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
8191: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 8192: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 8193: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
8194: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 8195: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
8196: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
8197: 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));
8198: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
8199: 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));
8200: for (i=1; i<= nlstate ; i ++) {
8201: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
8202: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
8203: 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);
8204: for (j=2; j<= nlstate+ndeath ; j ++) {
8205: 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);
8206: }
8207: fprintf(ficgp,";\nset out; unset ylabel;\n");
8208: }
8209: /* 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 */
8210: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
8211: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
8212: fprintf(ficgp,"\nset out;unset log\n");
8213: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 8214:
1.343 brouard 8215: /* Plot the probability implied in the likelihood by covariate value */
8216: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
8217: /* if(debugILK==1){ */
8218: for(kf=1; kf <= ncovf; kf++){ /* For each simple dummy covariate of the model */
8219: kvar=Tvar[TvarFind[kf]]; /* variable */
8220: k=18+Tvar[TvarFind[kf]];/*offset because there are 18 columns in the ILK_ file */
8221: for (i=1; i<= nlstate ; i ++) {
8222: fprintf(ficgp,"\nset out \"%s-p%dj-%d.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i,kvar);
8223: fprintf(ficgp,"unset log;\n# For each simple dummy covariate of the model \n plot \"%s\"",subdirf(fileresilk));
8224: fprintf(ficgp," u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? 7 : 9):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt variable ps 0.4 lc variable \\\n",i,1,k,k,i,1,kvar);
8225: for (j=2; j<= nlstate+ndeath ; j ++) {
8226: fprintf(ficgp,",\\\n \"\" u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? 7 : 9):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt variable ps 0.4 lc variable ",i,j,k,k,i,j,kvar);
8227: }
8228: fprintf(ficgp,";\nset out; unset ylabel;\n");
8229: }
8230: } /* End of each covariate dummy */
8231: for(ncovv=1, iposold=0, kk=0; ncovv <= ncovvt ; ncovv++){
8232: /* Other example V1 + V3 + V5 + age*V1 + age*V3 + age*V5 + V1*V3 + V3*V5 + V1*V5
8233: * kmodel = 1 2 3 4 5 6 7 8 9
8234: * varying 1 2 3 4 5
8235: * ncovv 1 2 3 4 5 6 7 8
8236: * TvarVV[ncovv] V3 5 1 3 3 5 1 5
8237: * TvarVVind[ncovv]=kmodel 2 3 7 7 8 8 9 9
8238: * TvarFind[kmodel] 1 0 0 0 0 0 0 0 0
8239: * kdata ncovcol=[V1 V2] nqv=0 ntv=[V3 V4] nqtv=V5
8240: * Dummy[kmodel] 0 0 1 2 2 3 1 1 1
8241: */
8242: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
8243: kvar=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
8244: /* printf("DebugILK ficgp ncovv=%d, kvar=TvarVV[ncovv]=%d, ipos=TvarVVind[ncovv]=%d, Dummy[ipos]=%d, Typevar[ipos]=%d\n", ncovv,kvar,ipos,Dummy[ipos],Typevar[ipos]); */
8245: if(ipos!=iposold){ /* Not a product or first of a product */
8246: /* printf(" %d",ipos); */
8247: /* fprintf(ficresilk," V%d",TvarVV[ncovv]); */
8248: /* printf(" DebugILK ficgp suite ipos=%d != iposold=%d\n", ipos, iposold); */
8249: kk++; /* Position of the ncovv column in ILK_ */
8250: k=18+ncovf+kk; /*offset because there are 18 columns in the ILK_ file plus ncovf fixed covariate */
8251: if(Dummy[ipos]==0 && Typevar[ipos]==0){ /* Only if dummy time varying: Dummy(0, 1=quant singor prod without age,2 dummy*age, 3quant*age) Typevar (0 single, 1=*age,2=Vn*vm) */
8252: for (i=1; i<= nlstate ; i ++) {
8253: fprintf(ficgp,"\nset out \"%s-p%dj-%d.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i,kvar);
8254: fprintf(ficgp,"unset log;\n# For each simple dummy covariate of the model \n plot \"%s\"",subdirf(fileresilk));
8255:
8256: if(gnuplotversion >=5.2){ /* Former gnuplot versions do not have variable pointsize!! */
8257: /* printf("DebugILK gnuplotversion=%g >=5.2\n",gnuplotversion); */
8258: fprintf(ficgp," u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? 7 : 9):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt variable ps 0.4 lc variable \\\n",i,1,k,k,i,1,kvar);
8259: for (j=2; j<= nlstate+ndeath ; j ++) {
8260: fprintf(ficgp,",\\\n \"\" u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? 7 : 9):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt variable ps 0.4 lc variable ",i,j,k,k,i,j,kvar);
8261: }
8262: }else{
8263: /* printf("DebugILK gnuplotversion=%g <5.2\n",gnuplotversion); */
8264: fprintf(ficgp," u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt 7 ps 0.4 lc variable \\\n",i,1,k,i,1,kvar);
8265: for (j=2; j<= nlstate+ndeath ; j ++) {
8266: fprintf(ficgp,",\\\n \"\" u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt 7 ps 0.4 lc variable ",i,j,k,i,j,kvar);
8267: }
8268: }
8269: fprintf(ficgp,";\nset out; unset ylabel;\n");
8270: }
8271: }/* End if dummy varying */
8272: }else{ /*Product */
8273: /* printf("*"); */
8274: /* fprintf(ficresilk,"*"); */
8275: }
8276: iposold=ipos;
8277: } /* For each time varying covariate */
8278: /* } /\* debugILK==1 *\/ */
8279: /* 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 */
8280: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
8281: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
8282: fprintf(ficgp,"\nset out;unset log\n");
8283: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
8284:
8285:
8286:
1.126 brouard 8287: strcpy(dirfileres,optionfilefiname);
8288: strcpy(optfileres,"vpl");
1.223 brouard 8289: /* 1eme*/
1.238 brouard 8290: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
1.337 brouard 8291: /* for (k1=1; k1<= m ; k1 ++){ /\* For each valid combination of covariate *\/ */
1.236 brouard 8292: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8293: k1=TKresult[nres];
1.338 brouard 8294: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.238 brouard 8295: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.337 brouard 8296: /* if(m != 1 && TKresult[nres]!= k1) */
8297: /* continue; */
1.238 brouard 8298: /* We are interested in selected combination by the resultline */
1.246 brouard 8299: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 8300: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 8301: strcpy(gplotlabel,"(");
1.337 brouard 8302: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8303: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8304: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8305:
8306: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate k get corresponding value lv for combination k1 *\/ */
8307: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the value of the covariate corresponding to k1 combination *\\/ *\/ */
8308: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8309: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8310: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8311: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8312: /* vlv= nbcode[Tvaraff[k]][lv]; /\* vlv is the value of the covariate lv, 0 or 1 *\/ */
8313: /* /\* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv *\/ */
8314: /* /\* printf(" V%d=%d ",Tvaraff[k],vlv); *\/ */
8315: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8316: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8317: /* } */
8318: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8319: /* /\* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); *\/ */
8320: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8321: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.264 brouard 8322: }
8323: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 8324: /* printf("\n#\n"); */
1.238 brouard 8325: fprintf(ficgp,"\n#\n");
8326: if(invalidvarcomb[k1]){
1.260 brouard 8327: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 8328: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8329: continue;
8330: }
1.235 brouard 8331:
1.241 brouard 8332: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
8333: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 8334: /* 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 8335: fprintf(ficgp,"set title \"Alive state %d %s model=1+age+%s\" font \"Helvetica,12\"\n",cpt,gplotlabel,model);
1.260 brouard 8336: 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);
8337: /* 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); */
8338: /* k1-1 error should be nres-1*/
1.238 brouard 8339: for (i=1; i<= nlstate ; i ++) {
8340: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8341: else fprintf(ficgp," %%*lf (%%*lf)");
8342: }
1.288 brouard 8343: 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 8344: for (i=1; i<= nlstate ; i ++) {
8345: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8346: else fprintf(ficgp," %%*lf (%%*lf)");
8347: }
1.260 brouard 8348: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 8349: for (i=1; i<= nlstate ; i ++) {
8350: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8351: else fprintf(ficgp," %%*lf (%%*lf)");
8352: }
1.265 brouard 8353: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
8354:
8355: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
8356: if(cptcoveff ==0){
1.271 brouard 8357: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 8358: }else{
8359: kl=0;
8360: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 8361: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
8362: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.265 brouard 8363: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8364: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8365: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8366: vlv= nbcode[Tvaraff[k]][lv];
8367: kl++;
8368: /* 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 *\/ */
8369: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8370: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8371: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
8372: if(k==cptcoveff){
8373: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
8374: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
8375: }else{
8376: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
8377: kl++;
8378: }
8379: } /* end covariate */
8380: } /* end if no covariate */
8381:
1.296 brouard 8382: if(prevbcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
1.238 brouard 8383: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 8384: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 8385: if(cptcoveff ==0){
1.245 brouard 8386: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 8387: }else{
8388: kl=0;
8389: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 8390: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
8391: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.238 brouard 8392: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8393: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8394: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 8395: /* vlv= nbcode[Tvaraff[k]][lv]; */
8396: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.223 brouard 8397: kl++;
1.238 brouard 8398: /* 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 *\/ */
8399: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8400: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8401: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
8402: if(k==cptcoveff){
1.245 brouard 8403: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 8404: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 8405: }else{
1.332 brouard 8406: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]);
1.238 brouard 8407: kl++;
8408: }
8409: } /* end covariate */
8410: } /* end if no covariate */
1.296 brouard 8411: if(prevbcast == 1){
1.268 brouard 8412: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
8413: /* k1-1 error should be nres-1*/
8414: for (i=1; i<= nlstate ; i ++) {
8415: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8416: else fprintf(ficgp," %%*lf (%%*lf)");
8417: }
1.271 brouard 8418: 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 8419: for (i=1; i<= nlstate ; i ++) {
8420: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8421: else fprintf(ficgp," %%*lf (%%*lf)");
8422: }
1.276 brouard 8423: 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 8424: for (i=1; i<= nlstate ; i ++) {
8425: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8426: else fprintf(ficgp," %%*lf (%%*lf)");
8427: }
1.274 brouard 8428: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 8429: } /* end if backprojcast */
1.296 brouard 8430: } /* end if prevbcast */
1.276 brouard 8431: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
8432: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 8433: } /* nres */
1.337 brouard 8434: /* } /\* k1 *\/ */
1.201 brouard 8435: } /* cpt */
1.235 brouard 8436:
8437:
1.126 brouard 8438: /*2 eme*/
1.337 brouard 8439: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 8440: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8441: k1=TKresult[nres];
1.338 brouard 8442: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8443: /* if(m != 1 && TKresult[nres]!= k1) */
8444: /* continue; */
1.238 brouard 8445: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 8446: strcpy(gplotlabel,"(");
1.337 brouard 8447: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8448: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8449: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8450: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8451: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8452: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8453: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8454: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8455: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8456: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8457: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8458: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8459: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8460: /* } */
8461: /* /\* for(k=1; k <= ncovds; k++){ *\/ */
8462: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8463: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8464: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8465: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 8466: }
1.264 brouard 8467: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8468: fprintf(ficgp,"\n#\n");
1.223 brouard 8469: if(invalidvarcomb[k1]){
8470: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8471: continue;
8472: }
1.219 brouard 8473:
1.241 brouard 8474: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 8475: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 8476: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
8477: if(vpopbased==0){
1.238 brouard 8478: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 8479: }else
1.238 brouard 8480: fprintf(ficgp,"\nreplot ");
8481: for (i=1; i<= nlstate+1 ; i ++) {
8482: k=2*i;
1.261 brouard 8483: 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 8484: for (j=1; j<= nlstate+1 ; j ++) {
8485: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8486: else fprintf(ficgp," %%*lf (%%*lf)");
8487: }
8488: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
8489: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 8490: 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 8491: for (j=1; j<= nlstate+1 ; j ++) {
8492: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8493: else fprintf(ficgp," %%*lf (%%*lf)");
8494: }
8495: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 8496: 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 8497: for (j=1; j<= nlstate+1 ; j ++) {
8498: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8499: else fprintf(ficgp," %%*lf (%%*lf)");
8500: }
8501: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
8502: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
8503: } /* state */
8504: } /* vpopbased */
1.264 brouard 8505: 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 8506: } /* end nres */
1.337 brouard 8507: /* } /\* k1 end 2 eme*\/ */
1.238 brouard 8508:
8509:
8510: /*3eme*/
1.337 brouard 8511: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 8512: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8513: k1=TKresult[nres];
1.338 brouard 8514: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8515: /* if(m != 1 && TKresult[nres]!= k1) */
8516: /* continue; */
1.238 brouard 8517:
1.332 brouard 8518: for (cpt=1; cpt<= nlstate ; cpt ++) { /* Fragile no verification of covariate values */
1.261 brouard 8519: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 8520: strcpy(gplotlabel,"(");
1.337 brouard 8521: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8522: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8523: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8524: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8525: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8526: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8527: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8528: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8529: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8530: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8531: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8532: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8533: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8534: /* } */
8535: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8536: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
8537: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
8538: }
1.264 brouard 8539: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8540: fprintf(ficgp,"\n#\n");
8541: if(invalidvarcomb[k1]){
8542: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8543: continue;
8544: }
8545:
8546: /* k=2+nlstate*(2*cpt-2); */
8547: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 8548: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 8549: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 8550: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 8551: 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 8552: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8553: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8554: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
8555: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8556: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8557: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 8558:
1.238 brouard 8559: */
8560: for (i=1; i< nlstate ; i ++) {
1.261 brouard 8561: 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 8562: /* 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 8563:
1.238 brouard 8564: }
1.261 brouard 8565: 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 8566: }
1.264 brouard 8567: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 8568: } /* end nres */
1.337 brouard 8569: /* } /\* end kl 3eme *\/ */
1.126 brouard 8570:
1.223 brouard 8571: /* 4eme */
1.201 brouard 8572: /* Survival functions (period) from state i in state j by initial state i */
1.337 brouard 8573: /* for (k1=1; k1<=m; k1++){ /\* For each covariate and each value *\/ */
1.238 brouard 8574: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8575: k1=TKresult[nres];
1.338 brouard 8576: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8577: /* if(m != 1 && TKresult[nres]!= k1) */
8578: /* continue; */
1.238 brouard 8579: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 8580: strcpy(gplotlabel,"(");
1.337 brouard 8581: fprintf(ficgp,"\n#\n#\n# Survival functions in state %d : 'LIJ_' files, cov=%d state=%d", cpt, k1, cpt);
8582: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8583: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8584: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8585: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8586: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8587: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8588: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8589: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8590: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8591: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8592: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8593: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8594: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8595: /* } */
8596: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8597: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8598: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 8599: }
1.264 brouard 8600: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8601: fprintf(ficgp,"\n#\n");
8602: if(invalidvarcomb[k1]){
8603: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8604: continue;
1.223 brouard 8605: }
1.238 brouard 8606:
1.241 brouard 8607: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 8608: 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 8609: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8610: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8611: k=3;
8612: for (i=1; i<= nlstate ; i ++){
8613: if(i==1){
8614: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8615: }else{
8616: fprintf(ficgp,", '' ");
8617: }
8618: l=(nlstate+ndeath)*(i-1)+1;
8619: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8620: for (j=2; j<= nlstate+ndeath ; j ++)
8621: fprintf(ficgp,"+$%d",k+l+j-1);
8622: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
8623: } /* nlstate */
1.264 brouard 8624: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8625: } /* end cpt state*/
8626: } /* end nres */
1.337 brouard 8627: /* } /\* end covariate k1 *\/ */
1.238 brouard 8628:
1.220 brouard 8629: /* 5eme */
1.201 brouard 8630: /* Survival functions (period) from state i in state j by final state j */
1.337 brouard 8631: /* for (k1=1; k1<= m ; k1++){ /\* For each covariate combination if any *\/ */
1.238 brouard 8632: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8633: k1=TKresult[nres];
1.338 brouard 8634: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8635: /* if(m != 1 && TKresult[nres]!= k1) */
8636: /* continue; */
1.238 brouard 8637: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 8638: strcpy(gplotlabel,"(");
1.238 brouard 8639: 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 8640: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8641: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8642: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8643: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8644: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8645: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8646: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8647: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8648: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8649: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8650: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8651: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8652: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8653: /* } */
8654: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8655: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8656: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 8657: }
1.264 brouard 8658: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8659: fprintf(ficgp,"\n#\n");
8660: if(invalidvarcomb[k1]){
8661: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8662: continue;
8663: }
1.227 brouard 8664:
1.241 brouard 8665: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 8666: 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 8667: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8668: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8669: k=3;
8670: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8671: if(j==1)
8672: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8673: else
8674: fprintf(ficgp,", '' ");
8675: l=(nlstate+ndeath)*(cpt-1) +j;
8676: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
8677: /* for (i=2; i<= nlstate+ndeath ; i ++) */
8678: /* fprintf(ficgp,"+$%d",k+l+i-1); */
8679: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
8680: } /* nlstate */
8681: fprintf(ficgp,", '' ");
8682: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
8683: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8684: l=(nlstate+ndeath)*(cpt-1) +j;
8685: if(j < nlstate)
8686: fprintf(ficgp,"$%d +",k+l);
8687: else
8688: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
8689: }
1.264 brouard 8690: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8691: } /* end cpt state*/
1.337 brouard 8692: /* } /\* end covariate *\/ */
1.238 brouard 8693: } /* end nres */
1.227 brouard 8694:
1.220 brouard 8695: /* 6eme */
1.202 brouard 8696: /* CV preval stable (period) for each covariate */
1.337 brouard 8697: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8698: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8699: k1=TKresult[nres];
1.338 brouard 8700: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8701: /* if(m != 1 && TKresult[nres]!= k1) */
8702: /* continue; */
1.255 brouard 8703: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 8704: strcpy(gplotlabel,"(");
1.288 brouard 8705: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 8706: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8707: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8708: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8709: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8710: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8711: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8712: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8713: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8714: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8715: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8716: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8717: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8718: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8719: /* } */
8720: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8721: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8722: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 8723: }
1.264 brouard 8724: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8725: fprintf(ficgp,"\n#\n");
1.223 brouard 8726: if(invalidvarcomb[k1]){
1.227 brouard 8727: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8728: continue;
1.223 brouard 8729: }
1.227 brouard 8730:
1.241 brouard 8731: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 8732: 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 8733: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 8734: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 8735: k=3; /* Offset */
1.255 brouard 8736: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 8737: if(i==1)
8738: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8739: else
8740: fprintf(ficgp,", '' ");
1.255 brouard 8741: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 8742: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8743: for (j=2; j<= nlstate ; j ++)
8744: fprintf(ficgp,"+$%d",k+l+j-1);
8745: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 8746: } /* nlstate */
1.264 brouard 8747: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 8748: } /* end cpt state*/
8749: } /* end covariate */
1.227 brouard 8750:
8751:
1.220 brouard 8752: /* 7eme */
1.296 brouard 8753: if(prevbcast == 1){
1.288 brouard 8754: /* CV backward prevalence for each covariate */
1.337 brouard 8755: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8756: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8757: k1=TKresult[nres];
1.338 brouard 8758: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8759: /* if(m != 1 && TKresult[nres]!= k1) */
8760: /* continue; */
1.268 brouard 8761: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 8762: strcpy(gplotlabel,"(");
1.288 brouard 8763: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 8764: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8765: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8766: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8767: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8768: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8769: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8770: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8771: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8772: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8773: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8774: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8775: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8776: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8777: /* } */
8778: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8779: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8780: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 8781: }
1.264 brouard 8782: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 8783: fprintf(ficgp,"\n#\n");
8784: if(invalidvarcomb[k1]){
8785: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8786: continue;
8787: }
8788:
1.241 brouard 8789: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 8790: 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 8791: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 8792: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 8793: k=3; /* Offset */
1.268 brouard 8794: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 8795: if(i==1)
8796: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
8797: else
8798: fprintf(ficgp,", '' ");
8799: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 8800: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.324 brouard 8801: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
8802: /* 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 8803: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 8804: /* for (j=2; j<= nlstate ; j ++) */
8805: /* fprintf(ficgp,"+$%d",k+l+j-1); */
8806: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 8807: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 8808: } /* nlstate */
1.264 brouard 8809: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 8810: } /* end cpt state*/
8811: } /* end covariate */
1.296 brouard 8812: } /* End if prevbcast */
1.218 brouard 8813:
1.223 brouard 8814: /* 8eme */
1.218 brouard 8815: if(prevfcast==1){
1.288 brouard 8816: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 8817:
1.337 brouard 8818: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8819: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8820: k1=TKresult[nres];
1.338 brouard 8821: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8822: /* if(m != 1 && TKresult[nres]!= k1) */
8823: /* continue; */
1.211 brouard 8824: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 8825: strcpy(gplotlabel,"(");
1.288 brouard 8826: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 8827: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8828: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8829: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8830: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
8831: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
8832: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8833: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8834: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8835: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8836: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8837: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8838: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8839: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8840: /* } */
8841: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8842: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8843: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 8844: }
1.264 brouard 8845: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 8846: fprintf(ficgp,"\n#\n");
8847: if(invalidvarcomb[k1]){
8848: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8849: continue;
8850: }
8851:
8852: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 8853: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 8854: 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 8855: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 8856: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 8857:
8858: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
8859: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
8860: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
8861: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 8862: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8863: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8864: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8865: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 8866: if(i==istart){
1.227 brouard 8867: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
8868: }else{
8869: fprintf(ficgp,",\\\n '' ");
8870: }
8871: if(cptcoveff ==0){ /* No covariate */
8872: ioffset=2; /* Age is in 2 */
8873: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8874: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8875: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8876: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8877: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 8878: if(i==nlstate+1){
1.270 brouard 8879: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 8880: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
8881: fprintf(ficgp,",\\\n '' ");
8882: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 8883: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 8884: offyear, \
1.268 brouard 8885: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 8886: }else
1.227 brouard 8887: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
8888: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
8889: }else{ /* more than 2 covariates */
1.270 brouard 8890: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
8891: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8892: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8893: iyearc=ioffset-1;
8894: iagec=ioffset;
1.227 brouard 8895: fprintf(ficgp," u %d:(",ioffset);
8896: kl=0;
8897: strcpy(gplotcondition,"(");
8898: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
1.332 brouard 8899: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8900: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.227 brouard 8901: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8902: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8903: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 8904: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
8905: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.227 brouard 8906: kl++;
8907: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
8908: kl++;
8909: if(k <cptcoveff && cptcoveff>1)
8910: sprintf(gplotcondition+strlen(gplotcondition)," && ");
8911: }
8912: strcpy(gplotcondition+strlen(gplotcondition),")");
8913: /* 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 *\/ */
8914: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8915: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8916: /* '' 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*/
8917: if(i==nlstate+1){
1.270 brouard 8918: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
8919: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 8920: fprintf(ficgp,",\\\n '' ");
1.270 brouard 8921: fprintf(ficgp," u %d:(",iagec);
8922: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
8923: iyearc, iagec, offyear, \
8924: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 8925: /* '' 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 8926: }else{
8927: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
8928: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
8929: }
8930: } /* end if covariate */
8931: } /* nlstate */
1.264 brouard 8932: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 8933: } /* end cpt state*/
8934: } /* end covariate */
8935: } /* End if prevfcast */
1.227 brouard 8936:
1.296 brouard 8937: if(prevbcast==1){
1.268 brouard 8938: /* Back projection from cross-sectional to stable (mixed) for each covariate */
8939:
1.337 brouard 8940: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.268 brouard 8941: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8942: k1=TKresult[nres];
1.338 brouard 8943: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8944: /* if(m != 1 && TKresult[nres]!= k1) */
8945: /* continue; */
1.268 brouard 8946: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
8947: strcpy(gplotlabel,"(");
8948: 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 8949: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8950: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8951: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8952: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
8953: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
8954: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8955: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8956: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8957: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8958: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8959: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8960: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8961: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8962: /* } */
8963: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8964: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8965: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.268 brouard 8966: }
8967: strcpy(gplotlabel+strlen(gplotlabel),")");
8968: fprintf(ficgp,"\n#\n");
8969: if(invalidvarcomb[k1]){
8970: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8971: continue;
8972: }
8973:
8974: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
8975: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
8976: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
8977: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
8978: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8979:
8980: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
8981: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
8982: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
8983: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
8984: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8985: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8986: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8987: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8988: if(i==istart){
8989: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
8990: }else{
8991: fprintf(ficgp,",\\\n '' ");
8992: }
8993: if(cptcoveff ==0){ /* No covariate */
8994: ioffset=2; /* Age is in 2 */
8995: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8996: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8997: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8998: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8999: fprintf(ficgp," u %d:(", ioffset);
9000: if(i==nlstate+1){
1.270 brouard 9001: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 9002: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
9003: fprintf(ficgp,",\\\n '' ");
9004: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 9005: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 9006: offbyear, \
9007: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
9008: }else
9009: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
9010: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
9011: }else{ /* more than 2 covariates */
1.270 brouard 9012: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
9013: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9014: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9015: iyearc=ioffset-1;
9016: iagec=ioffset;
1.268 brouard 9017: fprintf(ficgp," u %d:(",ioffset);
9018: kl=0;
9019: strcpy(gplotcondition,"(");
1.337 brouard 9020: for (k=1; k<=cptcovs; k++){ /* For each covariate k of the resultline, get corresponding value lv for combination k1 */
1.338 brouard 9021: if(Dummy[modelresult[nres][k]]==0){ /* To be verified */
1.337 brouard 9022: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate writing the chain of conditions *\/ */
9023: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9024: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9025: lv=Tvresult[nres][k];
9026: vlv=TinvDoQresult[nres][Tvresult[nres][k]];
9027: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
9028: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
9029: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
9030: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
9031: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9032: kl++;
9033: /* sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); */
9034: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%lg " ,kl,Tvresult[nres][k], kl+1,TinvDoQresult[nres][Tvresult[nres][k]]);
9035: kl++;
1.338 brouard 9036: if(k <cptcovs && cptcovs>1)
1.337 brouard 9037: sprintf(gplotcondition+strlen(gplotcondition)," && ");
9038: }
1.268 brouard 9039: }
9040: strcpy(gplotcondition+strlen(gplotcondition),")");
9041: /* 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 *\/ */
9042: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
9043: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
9044: /* '' 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*/
9045: if(i==nlstate+1){
1.270 brouard 9046: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
9047: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 9048: fprintf(ficgp,",\\\n '' ");
1.270 brouard 9049: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 9050: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 9051: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
9052: iyearc,iagec,offbyear, \
9053: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 9054: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
9055: }else{
9056: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
9057: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
9058: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
9059: }
9060: } /* end if covariate */
9061: } /* nlstate */
9062: fprintf(ficgp,"\nset out; unset label;\n");
9063: } /* end cpt state*/
9064: } /* end covariate */
1.296 brouard 9065: } /* End if prevbcast */
1.268 brouard 9066:
1.227 brouard 9067:
1.238 brouard 9068: /* 9eme writing MLE parameters */
9069: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 9070: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 9071: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 9072: for(k=1; k <=(nlstate+ndeath); k++){
9073: if (k != i) {
1.227 brouard 9074: fprintf(ficgp,"# current state %d\n",k);
9075: for(j=1; j <=ncovmodel; j++){
9076: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
9077: jk++;
9078: }
9079: fprintf(ficgp,"\n");
1.126 brouard 9080: }
9081: }
1.223 brouard 9082: }
1.187 brouard 9083: fprintf(ficgp,"##############\n#\n");
1.227 brouard 9084:
1.145 brouard 9085: /*goto avoid;*/
1.238 brouard 9086: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
9087: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 9088: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
9089: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
9090: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
9091: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
9092: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
9093: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
9094: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
9095: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
9096: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
9097: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
9098: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
9099: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
9100: fprintf(ficgp,"#\n");
1.223 brouard 9101: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 9102: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.338 brouard 9103: fprintf(ficgp,"#model=1+age+%s \n",model);
1.238 brouard 9104: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 brouard 9105: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
1.337 brouard 9106: /* for(k1=1; k1 <=m; k1++) /\* For each combination of covariate *\/ */
1.237 brouard 9107: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9108: /* k1=nres; */
1.338 brouard 9109: k1=TKresult[nres];
9110: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9111: fprintf(ficgp,"\n\n# Resultline k1=%d ",k1);
1.264 brouard 9112: strcpy(gplotlabel,"(");
1.276 brouard 9113: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.337 brouard 9114: for (k=1; k<=cptcovs; k++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
9115: /* for each resultline nres, and position k, Tvresult[nres][k] gives the name of the variable and
9116: TinvDoQresult[nres][Tvresult[nres][k]] gives its value double or integer) */
9117: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9118: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9119: }
9120: /* if(m != 1 && TKresult[nres]!= k1) */
9121: /* continue; */
9122: /* fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1); */
9123: /* strcpy(gplotlabel,"("); */
9124: /* /\*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*\/ */
9125: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
9126: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
9127: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9128: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9129: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9130: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9131: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9132: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9133: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9134: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9135: /* } */
9136: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9137: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9138: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9139: /* } */
1.264 brouard 9140: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 9141: fprintf(ficgp,"\n#\n");
1.264 brouard 9142: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 9143: fprintf(ficgp,"\nset key outside ");
9144: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
9145: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 9146: fprintf(ficgp,"\nset ter svg size 640, 480 ");
9147: if (ng==1){
9148: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
9149: fprintf(ficgp,"\nunset log y");
9150: }else if (ng==2){
9151: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
9152: fprintf(ficgp,"\nset log y");
9153: }else if (ng==3){
9154: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
9155: fprintf(ficgp,"\nset log y");
9156: }else
9157: fprintf(ficgp,"\nunset title ");
9158: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
9159: i=1;
9160: for(k2=1; k2<=nlstate; k2++) {
9161: k3=i;
9162: for(k=1; k<=(nlstate+ndeath); k++) {
9163: if (k != k2){
9164: switch( ng) {
9165: case 1:
9166: if(nagesqr==0)
9167: fprintf(ficgp," p%d+p%d*x",i,i+1);
9168: else /* nagesqr =1 */
9169: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
9170: break;
9171: case 2: /* ng=2 */
9172: if(nagesqr==0)
9173: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
9174: else /* nagesqr =1 */
9175: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
9176: break;
9177: case 3:
9178: if(nagesqr==0)
9179: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
9180: else /* nagesqr =1 */
9181: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
9182: break;
9183: }
9184: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 9185: ijp=1; /* product no age */
9186: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
9187: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 9188: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.329 brouard 9189: switch(Typevar[j]){
9190: case 1:
9191: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
9192: if(j==Tage[ij]) { /* Product by age To be looked at!!*//* Bug valgrind */
9193: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
9194: if(DummyV[j]==0){/* Bug valgrind */
9195: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
9196: }else{ /* quantitative */
9197: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
9198: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9199: }
9200: ij++;
1.268 brouard 9201: }
1.237 brouard 9202: }
1.329 brouard 9203: }
9204: break;
9205: case 2:
9206: if(cptcovprod >0){
9207: if(j==Tprod[ijp]) { /* */
9208: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9209: if(ijp <=cptcovprod) { /* Product */
9210: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
9211: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
9212: /* 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)]); */
9213: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9214: }else{ /* Vn is dummy and Vm is quanti */
9215: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
9216: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9217: }
9218: }else{ /* Vn*Vm Vn is quanti */
9219: if(DummyV[Tvard[ijp][2]]==0){
9220: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
9221: }else{ /* Both quanti */
9222: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9223: }
1.268 brouard 9224: }
1.329 brouard 9225: ijp++;
1.237 brouard 9226: }
1.329 brouard 9227: } /* end Tprod */
9228: }
9229: break;
9230: case 0:
9231: /* simple covariate */
1.264 brouard 9232: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 9233: if(Dummy[j]==0){
9234: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
9235: }else{ /* quantitative */
9236: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 9237: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 9238: }
1.329 brouard 9239: /* end simple */
9240: break;
9241: default:
9242: break;
9243: } /* end switch */
1.237 brouard 9244: } /* end j */
1.329 brouard 9245: }else{ /* k=k2 */
9246: if(ng !=1 ){ /* For logit formula of log p11 is more difficult to get */
9247: fprintf(ficgp," (1.");i=i-ncovmodel;
9248: }else
9249: i=i-ncovmodel;
1.223 brouard 9250: }
1.227 brouard 9251:
1.223 brouard 9252: if(ng != 1){
9253: fprintf(ficgp,")/(1");
1.227 brouard 9254:
1.264 brouard 9255: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 9256: if(nagesqr==0)
1.264 brouard 9257: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 9258: else /* nagesqr =1 */
1.264 brouard 9259: 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 9260:
1.223 brouard 9261: ij=1;
1.329 brouard 9262: ijp=1;
9263: /* for(j=3; j <=ncovmodel-nagesqr; j++){ */
9264: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
9265: switch(Typevar[j]){
9266: case 1:
9267: if(cptcovage >0){
9268: if(j==Tage[ij]) { /* Bug valgrind */
9269: if(ij <=cptcovage) { /* Bug valgrind */
9270: if(DummyV[j]==0){/* Bug valgrind */
9271: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]); */
9272: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,nbcode[Tvar[j]][codtabm(k1,j)]); */
9273: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]);
9274: /* fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);; */
9275: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9276: }else{ /* quantitative */
9277: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
9278: fprintf(ficgp,"+p%d*%f*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
9279: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
9280: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9281: }
9282: ij++;
9283: }
9284: }
9285: }
9286: break;
9287: case 2:
9288: if(cptcovprod >0){
9289: if(j==Tprod[ijp]) { /* */
9290: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9291: if(ijp <=cptcovprod) { /* Product */
9292: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
9293: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
9294: /* 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)]); */
9295: fprintf(ficgp,"+p%d*%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9296: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
9297: }else{ /* Vn is dummy and Vm is quanti */
9298: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
9299: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9300: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9301: }
9302: }else{ /* Vn*Vm Vn is quanti */
9303: if(DummyV[Tvard[ijp][2]]==0){
9304: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
9305: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
9306: }else{ /* Both quanti */
9307: fprintf(ficgp,"+p%d*%f*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9308: /* fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9309: }
9310: }
9311: ijp++;
9312: }
9313: } /* end Tprod */
9314: } /* end if */
9315: break;
9316: case 0:
9317: /* simple covariate */
9318: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
9319: if(Dummy[j]==0){
9320: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
9321: fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]); /* */
9322: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
9323: }else{ /* quantitative */
9324: fprintf(ficgp,"+p%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* */
9325: /* fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* *\/ */
9326: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9327: }
9328: /* end simple */
9329: /* fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);/\* Valgrind bug nbcode *\/ */
9330: break;
9331: default:
9332: break;
9333: } /* end switch */
1.223 brouard 9334: }
9335: fprintf(ficgp,")");
9336: }
9337: fprintf(ficgp,")");
9338: if(ng ==2)
1.276 brouard 9339: 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 9340: else /* ng= 3 */
1.276 brouard 9341: 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 9342: }else{ /* end ng <> 1 */
1.223 brouard 9343: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 9344: 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 9345: }
9346: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
9347: fprintf(ficgp,",");
9348: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
9349: fprintf(ficgp,",");
9350: i=i+ncovmodel;
9351: } /* end k */
9352: } /* end k2 */
1.276 brouard 9353: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
9354: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.337 brouard 9355: } /* end resultline */
1.223 brouard 9356: } /* end ng */
9357: /* avoid: */
9358: fflush(ficgp);
1.126 brouard 9359: } /* end gnuplot */
9360:
9361:
9362: /*************** Moving average **************/
1.219 brouard 9363: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 9364: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 9365:
1.222 brouard 9366: int i, cpt, cptcod;
9367: int modcovmax =1;
9368: int mobilavrange, mob;
9369: int iage=0;
1.288 brouard 9370: int firstA1=0, firstA2=0;
1.222 brouard 9371:
1.266 brouard 9372: double sum=0., sumr=0.;
1.222 brouard 9373: double age;
1.266 brouard 9374: double *sumnewp, *sumnewm, *sumnewmr;
9375: double *agemingood, *agemaxgood;
9376: double *agemingoodr, *agemaxgoodr;
1.222 brouard 9377:
9378:
1.278 brouard 9379: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
9380: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 9381:
9382: sumnewp = vector(1,ncovcombmax);
9383: sumnewm = vector(1,ncovcombmax);
1.266 brouard 9384: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 9385: agemingood = vector(1,ncovcombmax);
1.266 brouard 9386: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 9387: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 9388: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 9389:
9390: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 9391: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 9392: sumnewp[cptcod]=0.;
1.266 brouard 9393: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
9394: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 9395: }
9396: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
9397:
1.266 brouard 9398: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
9399: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 9400: else mobilavrange=mobilav;
9401: for (age=bage; age<=fage; age++)
9402: for (i=1; i<=nlstate;i++)
9403: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
9404: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9405: /* We keep the original values on the extreme ages bage, fage and for
9406: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
9407: we use a 5 terms etc. until the borders are no more concerned.
9408: */
9409: for (mob=3;mob <=mobilavrange;mob=mob+2){
9410: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 9411: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
9412: sumnewm[cptcod]=0.;
9413: for (i=1; i<=nlstate;i++){
1.222 brouard 9414: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
9415: for (cpt=1;cpt<=(mob-1)/2;cpt++){
9416: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
9417: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
9418: }
9419: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 9420: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9421: } /* end i */
9422: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
9423: } /* end cptcod */
1.222 brouard 9424: }/* end age */
9425: }/* end mob */
1.266 brouard 9426: }else{
9427: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 9428: return -1;
1.266 brouard 9429: }
9430:
9431: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 9432: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
9433: if(invalidvarcomb[cptcod]){
9434: printf("\nCombination (%d) ignored because no cases \n",cptcod);
9435: continue;
9436: }
1.219 brouard 9437:
1.266 brouard 9438: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
9439: sumnewm[cptcod]=0.;
9440: sumnewmr[cptcod]=0.;
9441: for (i=1; i<=nlstate;i++){
9442: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9443: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9444: }
9445: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9446: agemingoodr[cptcod]=age;
9447: }
9448: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9449: agemingood[cptcod]=age;
9450: }
9451: } /* age */
9452: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 9453: sumnewm[cptcod]=0.;
1.266 brouard 9454: sumnewmr[cptcod]=0.;
1.222 brouard 9455: for (i=1; i<=nlstate;i++){
9456: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 9457: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9458: }
9459: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9460: agemaxgoodr[cptcod]=age;
1.222 brouard 9461: }
9462: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 9463: agemaxgood[cptcod]=age;
9464: }
9465: } /* age */
9466: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
9467: /* but they will change */
1.288 brouard 9468: firstA1=0;firstA2=0;
1.266 brouard 9469: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
9470: sumnewm[cptcod]=0.;
9471: sumnewmr[cptcod]=0.;
9472: for (i=1; i<=nlstate;i++){
9473: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9474: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9475: }
9476: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
9477: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9478: agemaxgoodr[cptcod]=age; /* age min */
9479: for (i=1; i<=nlstate;i++)
9480: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9481: }else{ /* bad we change the value with the values of good ages */
9482: for (i=1; i<=nlstate;i++){
9483: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
9484: } /* i */
9485: } /* end bad */
9486: }else{
9487: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9488: agemaxgood[cptcod]=age;
9489: }else{ /* bad we change the value with the values of good ages */
9490: for (i=1; i<=nlstate;i++){
9491: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
9492: } /* i */
9493: } /* end bad */
9494: }/* end else */
9495: sum=0.;sumr=0.;
9496: for (i=1; i<=nlstate;i++){
9497: sum+=mobaverage[(int)age][i][cptcod];
9498: sumr+=probs[(int)age][i][cptcod];
9499: }
9500: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 9501: if(!firstA1){
9502: firstA1=1;
9503: 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);
9504: }
9505: 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 9506: } /* end bad */
9507: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
9508: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 9509: if(!firstA2){
9510: firstA2=1;
9511: 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);
9512: }
9513: 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 9514: } /* end bad */
9515: }/* age */
1.266 brouard 9516:
9517: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 9518: sumnewm[cptcod]=0.;
1.266 brouard 9519: sumnewmr[cptcod]=0.;
1.222 brouard 9520: for (i=1; i<=nlstate;i++){
9521: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 9522: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9523: }
9524: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
9525: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
9526: agemingoodr[cptcod]=age;
9527: for (i=1; i<=nlstate;i++)
9528: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9529: }else{ /* bad we change the value with the values of good ages */
9530: for (i=1; i<=nlstate;i++){
9531: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
9532: } /* i */
9533: } /* end bad */
9534: }else{
9535: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9536: agemingood[cptcod]=age;
9537: }else{ /* bad */
9538: for (i=1; i<=nlstate;i++){
9539: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
9540: } /* i */
9541: } /* end bad */
9542: }/* end else */
9543: sum=0.;sumr=0.;
9544: for (i=1; i<=nlstate;i++){
9545: sum+=mobaverage[(int)age][i][cptcod];
9546: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 9547: }
1.266 brouard 9548: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 9549: 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 9550: } /* end bad */
9551: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
9552: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 9553: 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 9554: } /* end bad */
9555: }/* age */
1.266 brouard 9556:
1.222 brouard 9557:
9558: for (age=bage; age<=fage; age++){
1.235 brouard 9559: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 9560: sumnewp[cptcod]=0.;
9561: sumnewm[cptcod]=0.;
9562: for (i=1; i<=nlstate;i++){
9563: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
9564: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9565: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
9566: }
9567: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
9568: }
9569: /* printf("\n"); */
9570: /* } */
1.266 brouard 9571:
1.222 brouard 9572: /* brutal averaging */
1.266 brouard 9573: /* for (i=1; i<=nlstate;i++){ */
9574: /* for (age=1; age<=bage; age++){ */
9575: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
9576: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
9577: /* } */
9578: /* for (age=fage; age<=AGESUP; age++){ */
9579: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
9580: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
9581: /* } */
9582: /* } /\* end i status *\/ */
9583: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
9584: /* for (age=1; age<=AGESUP; age++){ */
9585: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
9586: /* mobaverage[(int)age][i][cptcod]=0.; */
9587: /* } */
9588: /* } */
1.222 brouard 9589: }/* end cptcod */
1.266 brouard 9590: free_vector(agemaxgoodr,1, ncovcombmax);
9591: free_vector(agemaxgood,1, ncovcombmax);
9592: free_vector(agemingood,1, ncovcombmax);
9593: free_vector(agemingoodr,1, ncovcombmax);
9594: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 9595: free_vector(sumnewm,1, ncovcombmax);
9596: free_vector(sumnewp,1, ncovcombmax);
9597: return 0;
9598: }/* End movingaverage */
1.218 brouard 9599:
1.126 brouard 9600:
1.296 brouard 9601:
1.126 brouard 9602: /************** Forecasting ******************/
1.296 brouard 9603: /* 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)*/
9604: 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){
9605: /* dateintemean, mean date of interviews
9606: dateprojd, year, month, day of starting projection
9607: dateprojf date of end of projection;year of end of projection (same day and month as proj1).
1.126 brouard 9608: agemin, agemax range of age
9609: dateprev1 dateprev2 range of dates during which prevalence is computed
9610: */
1.296 brouard 9611: /* double anprojd, mprojd, jprojd; */
9612: /* double anprojf, mprojf, jprojf; */
1.267 brouard 9613: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 9614: double agec; /* generic age */
1.296 brouard 9615: double agelim, ppij, yp,yp1,yp2;
1.126 brouard 9616: double *popeffectif,*popcount;
9617: double ***p3mat;
1.218 brouard 9618: /* double ***mobaverage; */
1.126 brouard 9619: char fileresf[FILENAMELENGTH];
9620:
9621: agelim=AGESUP;
1.211 brouard 9622: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
9623: in each health status at the date of interview (if between dateprev1 and dateprev2).
9624: We still use firstpass and lastpass as another selection.
9625: */
1.214 brouard 9626: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
9627: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 9628:
1.201 brouard 9629: strcpy(fileresf,"F_");
9630: strcat(fileresf,fileresu);
1.126 brouard 9631: if((ficresf=fopen(fileresf,"w"))==NULL) {
9632: printf("Problem with forecast resultfile: %s\n", fileresf);
9633: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
9634: }
1.235 brouard 9635: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
9636: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 9637:
1.225 brouard 9638: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 9639:
9640:
9641: stepsize=(int) (stepm+YEARM-1)/YEARM;
9642: if (stepm<=12) stepsize=1;
9643: if(estepm < stepm){
9644: printf ("Problem %d lower than %d\n",estepm, stepm);
9645: }
1.270 brouard 9646: else{
9647: hstepm=estepm;
9648: }
9649: if(estepm > stepm){ /* Yes every two year */
9650: stepsize=2;
9651: }
1.296 brouard 9652: hstepm=hstepm/stepm;
1.126 brouard 9653:
1.296 brouard 9654:
9655: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
9656: /* fractional in yp1 *\/ */
9657: /* aintmean=yp; */
9658: /* yp2=modf((yp1*12),&yp); */
9659: /* mintmean=yp; */
9660: /* yp1=modf((yp2*30.5),&yp); */
9661: /* jintmean=yp; */
9662: /* if(jintmean==0) jintmean=1; */
9663: /* if(mintmean==0) mintmean=1; */
1.126 brouard 9664:
1.296 brouard 9665:
9666: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */
9667: /* date2dmy(dateprojd,&jprojd, &mprojd, &anprojd); */
9668: /* date2dmy(dateprojf,&jprojf, &mprojf, &anprojf); */
1.227 brouard 9669: i1=pow(2,cptcoveff);
1.126 brouard 9670: if (cptcovn < 1){i1=1;}
9671:
1.296 brouard 9672: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.126 brouard 9673:
9674: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 9675:
1.126 brouard 9676: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 9677: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.332 brouard 9678: 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 9679: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 9680: continue;
1.227 brouard 9681: if(invalidvarcomb[k]){
9682: printf("\nCombination (%d) projection ignored because no cases \n",k);
9683: continue;
9684: }
9685: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
9686: for(j=1;j<=cptcoveff;j++) {
1.332 brouard 9687: /* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); */
9688: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.227 brouard 9689: }
1.235 brouard 9690: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 9691: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 9692: }
1.227 brouard 9693: fprintf(ficresf," yearproj age");
9694: for(j=1; j<=nlstate+ndeath;j++){
9695: for(i=1; i<=nlstate;i++)
9696: fprintf(ficresf," p%d%d",i,j);
9697: fprintf(ficresf," wp.%d",j);
9698: }
1.296 brouard 9699: for (yearp=0; yearp<=(anprojf-anprojd);yearp +=stepsize) {
1.227 brouard 9700: fprintf(ficresf,"\n");
1.296 brouard 9701: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jprojd,mprojd,anprojd+yearp);
1.270 brouard 9702: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
9703: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 9704: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
9705: nhstepm = nhstepm/hstepm;
9706: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9707: oldm=oldms;savm=savms;
1.268 brouard 9708: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 9709: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 9710: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 9711: for (h=0; h<=nhstepm; h++){
9712: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 9713: break;
9714: }
9715: }
9716: fprintf(ficresf,"\n");
9717: for(j=1;j<=cptcoveff;j++)
1.332 brouard 9718: /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Tvaraff not correct *\/ */
9719: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /* TnsdVar[Tvaraff] correct */
1.296 brouard 9720: fprintf(ficresf,"%.f %.f ",anprojd+yearp,agec+h*hstepm/YEARM*stepm);
1.268 brouard 9721:
9722: for(j=1; j<=nlstate+ndeath;j++) {
9723: ppij=0.;
9724: for(i=1; i<=nlstate;i++) {
1.278 brouard 9725: if (mobilav>=1)
9726: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
9727: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
9728: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
9729: }
1.268 brouard 9730: fprintf(ficresf," %.3f", p3mat[i][j][h]);
9731: } /* end i */
9732: fprintf(ficresf," %.3f", ppij);
9733: }/* end j */
1.227 brouard 9734: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9735: } /* end agec */
1.266 brouard 9736: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
9737: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 9738: } /* end yearp */
9739: } /* end k */
1.219 brouard 9740:
1.126 brouard 9741: fclose(ficresf);
1.215 brouard 9742: printf("End of Computing forecasting \n");
9743: fprintf(ficlog,"End of Computing forecasting\n");
9744:
1.126 brouard 9745: }
9746:
1.269 brouard 9747: /************** Back Forecasting ******************/
1.296 brouard 9748: /* 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){ */
9749: 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){
9750: /* back1, year, month, day of starting backprojection
1.267 brouard 9751: agemin, agemax range of age
9752: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 9753: anback2 year of end of backprojection (same day and month as back1).
9754: prevacurrent and prev are prevalences.
1.267 brouard 9755: */
9756: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
9757: double agec; /* generic age */
1.302 brouard 9758: double agelim, ppij, ppi, yp,yp1,yp2; /* ,jintmean,mintmean,aintmean;*/
1.267 brouard 9759: double *popeffectif,*popcount;
9760: double ***p3mat;
9761: /* double ***mobaverage; */
9762: char fileresfb[FILENAMELENGTH];
9763:
1.268 brouard 9764: agelim=AGEINF;
1.267 brouard 9765: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
9766: in each health status at the date of interview (if between dateprev1 and dateprev2).
9767: We still use firstpass and lastpass as another selection.
9768: */
9769: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
9770: /* firstpass, lastpass, stepm, weightopt, model); */
9771:
9772: /*Do we need to compute prevalence again?*/
9773:
9774: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
9775:
9776: strcpy(fileresfb,"FB_");
9777: strcat(fileresfb,fileresu);
9778: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
9779: printf("Problem with back forecast resultfile: %s\n", fileresfb);
9780: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
9781: }
9782: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
9783: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
9784:
9785: if (cptcoveff==0) ncodemax[cptcoveff]=1;
9786:
9787:
9788: stepsize=(int) (stepm+YEARM-1)/YEARM;
9789: if (stepm<=12) stepsize=1;
9790: if(estepm < stepm){
9791: printf ("Problem %d lower than %d\n",estepm, stepm);
9792: }
1.270 brouard 9793: else{
9794: hstepm=estepm;
9795: }
9796: if(estepm >= stepm){ /* Yes every two year */
9797: stepsize=2;
9798: }
1.267 brouard 9799:
9800: hstepm=hstepm/stepm;
1.296 brouard 9801: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
9802: /* fractional in yp1 *\/ */
9803: /* aintmean=yp; */
9804: /* yp2=modf((yp1*12),&yp); */
9805: /* mintmean=yp; */
9806: /* yp1=modf((yp2*30.5),&yp); */
9807: /* jintmean=yp; */
9808: /* if(jintmean==0) jintmean=1; */
9809: /* if(mintmean==0) jintmean=1; */
1.267 brouard 9810:
9811: i1=pow(2,cptcoveff);
9812: if (cptcovn < 1){i1=1;}
9813:
1.296 brouard 9814: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
9815: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 9816:
9817: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
9818:
9819: for(nres=1; nres <= nresult; nres++) /* For each resultline */
9820: for(k=1; k<=i1;k++){
9821: if(i1 != 1 && TKresult[nres]!= k)
9822: continue;
9823: if(invalidvarcomb[k]){
9824: printf("\nCombination (%d) projection ignored because no cases \n",k);
9825: continue;
9826: }
1.268 brouard 9827: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.267 brouard 9828: for(j=1;j<=cptcoveff;j++) {
1.332 brouard 9829: fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.267 brouard 9830: }
9831: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
9832: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
9833: }
9834: fprintf(ficresfb," yearbproj age");
9835: for(j=1; j<=nlstate+ndeath;j++){
9836: for(i=1; i<=nlstate;i++)
1.268 brouard 9837: fprintf(ficresfb," b%d%d",i,j);
9838: fprintf(ficresfb," b.%d",j);
1.267 brouard 9839: }
1.296 brouard 9840: for (yearp=0; yearp>=(anbackf-anbackd);yearp -=stepsize) {
1.267 brouard 9841: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
9842: fprintf(ficresfb,"\n");
1.296 brouard 9843: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jbackd,mbackd,anbackd+yearp);
1.273 brouard 9844: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 9845: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
9846: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 9847: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 9848: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 9849: nhstepm = nhstepm/hstepm;
9850: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9851: oldm=oldms;savm=savms;
1.268 brouard 9852: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 9853: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 9854: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 9855: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
9856: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
9857: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 9858: for (h=0; h<=nhstepm; h++){
1.268 brouard 9859: if (h*hstepm/YEARM*stepm ==-yearp) {
9860: break;
9861: }
9862: }
9863: fprintf(ficresfb,"\n");
9864: for(j=1;j<=cptcoveff;j++)
1.332 brouard 9865: fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.296 brouard 9866: fprintf(ficresfb,"%.f %.f ",anbackd+yearp,agec-h*hstepm/YEARM*stepm);
1.268 brouard 9867: for(i=1; i<=nlstate+ndeath;i++) {
9868: ppij=0.;ppi=0.;
9869: for(j=1; j<=nlstate;j++) {
9870: /* if (mobilav==1) */
1.269 brouard 9871: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
9872: ppi=ppi+prevacurrent[(int)agec][j][k];
9873: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
9874: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 9875: /* else { */
9876: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
9877: /* } */
1.268 brouard 9878: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
9879: } /* end j */
9880: if(ppi <0.99){
9881: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
9882: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
9883: }
9884: fprintf(ficresfb," %.3f", ppij);
9885: }/* end j */
1.267 brouard 9886: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9887: } /* end agec */
9888: } /* end yearp */
9889: } /* end k */
1.217 brouard 9890:
1.267 brouard 9891: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 9892:
1.267 brouard 9893: fclose(ficresfb);
9894: printf("End of Computing Back forecasting \n");
9895: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 9896:
1.267 brouard 9897: }
1.217 brouard 9898:
1.269 brouard 9899: /* Variance of prevalence limit: varprlim */
9900: 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 9901: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 9902:
9903: char fileresvpl[FILENAMELENGTH];
9904: FILE *ficresvpl;
9905: double **oldm, **savm;
9906: double **varpl; /* Variances of prevalence limits by age */
9907: int i1, k, nres, j ;
9908:
9909: strcpy(fileresvpl,"VPL_");
9910: strcat(fileresvpl,fileresu);
9911: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 9912: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 9913: exit(0);
9914: }
1.288 brouard 9915: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
9916: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 9917:
9918: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
9919: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
9920:
9921: i1=pow(2,cptcoveff);
9922: if (cptcovn < 1){i1=1;}
9923:
1.337 brouard 9924: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
9925: k=TKresult[nres];
1.338 brouard 9926: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 9927: /* for(k=1; k<=i1;k++){ /\* We find the combination equivalent to result line values of dummies *\/ */
1.269 brouard 9928: if(i1 != 1 && TKresult[nres]!= k)
9929: continue;
9930: fprintf(ficresvpl,"\n#****** ");
9931: printf("\n#****** ");
9932: fprintf(ficlog,"\n#****** ");
1.337 brouard 9933: for(j=1;j<=cptcovs;j++) {
9934: fprintf(ficresvpl,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
9935: fprintf(ficlog,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
9936: printf("V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
9937: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
9938: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.269 brouard 9939: }
1.337 brouard 9940: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
9941: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
9942: /* fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
9943: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
9944: /* } */
1.269 brouard 9945: fprintf(ficresvpl,"******\n");
9946: printf("******\n");
9947: fprintf(ficlog,"******\n");
9948:
9949: varpl=matrix(1,nlstate,(int) bage, (int) fage);
9950: oldm=oldms;savm=savms;
9951: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
9952: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
9953: /*}*/
9954: }
9955:
9956: fclose(ficresvpl);
1.288 brouard 9957: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
9958: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 9959:
9960: }
9961: /* Variance of back prevalence: varbprlim */
9962: 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){
9963: /*------- Variance of back (stable) prevalence------*/
9964:
9965: char fileresvbl[FILENAMELENGTH];
9966: FILE *ficresvbl;
9967:
9968: double **oldm, **savm;
9969: double **varbpl; /* Variances of back prevalence limits by age */
9970: int i1, k, nres, j ;
9971:
9972: strcpy(fileresvbl,"VBL_");
9973: strcat(fileresvbl,fileresu);
9974: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
9975: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
9976: exit(0);
9977: }
9978: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
9979: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
9980:
9981:
9982: i1=pow(2,cptcoveff);
9983: if (cptcovn < 1){i1=1;}
9984:
1.337 brouard 9985: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
9986: k=TKresult[nres];
1.338 brouard 9987: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 9988: /* for(k=1; k<=i1;k++){ */
9989: /* if(i1 != 1 && TKresult[nres]!= k) */
9990: /* continue; */
1.269 brouard 9991: fprintf(ficresvbl,"\n#****** ");
9992: printf("\n#****** ");
9993: fprintf(ficlog,"\n#****** ");
1.337 brouard 9994: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */
1.338 brouard 9995: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
9996: fprintf(ficresvbl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
9997: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
1.337 brouard 9998: /* for(j=1;j<=cptcoveff;j++) { */
9999: /* fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10000: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10001: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10002: /* } */
10003: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
10004: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10005: /* fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10006: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
1.269 brouard 10007: }
10008: fprintf(ficresvbl,"******\n");
10009: printf("******\n");
10010: fprintf(ficlog,"******\n");
10011:
10012: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
10013: oldm=oldms;savm=savms;
10014:
10015: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
10016: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
10017: /*}*/
10018: }
10019:
10020: fclose(ficresvbl);
10021: printf("done variance-covariance of back prevalence\n");fflush(stdout);
10022: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
10023:
10024: } /* End of varbprlim */
10025:
1.126 brouard 10026: /************** Forecasting *****not tested NB*************/
1.227 brouard 10027: /* 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 10028:
1.227 brouard 10029: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
10030: /* int *popage; */
10031: /* double calagedatem, agelim, kk1, kk2; */
10032: /* double *popeffectif,*popcount; */
10033: /* double ***p3mat,***tabpop,***tabpopprev; */
10034: /* /\* double ***mobaverage; *\/ */
10035: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 10036:
1.227 brouard 10037: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10038: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10039: /* agelim=AGESUP; */
10040: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 10041:
1.227 brouard 10042: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 10043:
10044:
1.227 brouard 10045: /* strcpy(filerespop,"POP_"); */
10046: /* strcat(filerespop,fileresu); */
10047: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
10048: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
10049: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
10050: /* } */
10051: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
10052: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 10053:
1.227 brouard 10054: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 10055:
1.227 brouard 10056: /* /\* if (mobilav!=0) { *\/ */
10057: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
10058: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
10059: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
10060: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
10061: /* /\* } *\/ */
10062: /* /\* } *\/ */
1.126 brouard 10063:
1.227 brouard 10064: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
10065: /* if (stepm<=12) stepsize=1; */
1.126 brouard 10066:
1.227 brouard 10067: /* agelim=AGESUP; */
1.126 brouard 10068:
1.227 brouard 10069: /* hstepm=1; */
10070: /* hstepm=hstepm/stepm; */
1.218 brouard 10071:
1.227 brouard 10072: /* if (popforecast==1) { */
10073: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
10074: /* printf("Problem with population file : %s\n",popfile);exit(0); */
10075: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
10076: /* } */
10077: /* popage=ivector(0,AGESUP); */
10078: /* popeffectif=vector(0,AGESUP); */
10079: /* popcount=vector(0,AGESUP); */
1.126 brouard 10080:
1.227 brouard 10081: /* i=1; */
10082: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 10083:
1.227 brouard 10084: /* imx=i; */
10085: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
10086: /* } */
1.218 brouard 10087:
1.227 brouard 10088: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
10089: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
10090: /* k=k+1; */
10091: /* fprintf(ficrespop,"\n#******"); */
10092: /* for(j=1;j<=cptcoveff;j++) { */
10093: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
10094: /* } */
10095: /* fprintf(ficrespop,"******\n"); */
10096: /* fprintf(ficrespop,"# Age"); */
10097: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
10098: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 10099:
1.227 brouard 10100: /* for (cpt=0; cpt<=0;cpt++) { */
10101: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 10102:
1.227 brouard 10103: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
10104: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
10105: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 10106:
1.227 brouard 10107: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10108: /* oldm=oldms;savm=savms; */
10109: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 10110:
1.227 brouard 10111: /* for (h=0; h<=nhstepm; h++){ */
10112: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
10113: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
10114: /* } */
10115: /* for(j=1; j<=nlstate+ndeath;j++) { */
10116: /* kk1=0.;kk2=0; */
10117: /* for(i=1; i<=nlstate;i++) { */
10118: /* if (mobilav==1) */
10119: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
10120: /* else { */
10121: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
10122: /* } */
10123: /* } */
10124: /* if (h==(int)(calagedatem+12*cpt)){ */
10125: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
10126: /* /\*fprintf(ficrespop," %.3f", kk1); */
10127: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
10128: /* } */
10129: /* } */
10130: /* for(i=1; i<=nlstate;i++){ */
10131: /* kk1=0.; */
10132: /* for(j=1; j<=nlstate;j++){ */
10133: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
10134: /* } */
10135: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
10136: /* } */
1.218 brouard 10137:
1.227 brouard 10138: /* if (h==(int)(calagedatem+12*cpt)) */
10139: /* for(j=1; j<=nlstate;j++) */
10140: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
10141: /* } */
10142: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10143: /* } */
10144: /* } */
1.218 brouard 10145:
1.227 brouard 10146: /* /\******\/ */
1.218 brouard 10147:
1.227 brouard 10148: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
10149: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
10150: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
10151: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
10152: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 10153:
1.227 brouard 10154: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10155: /* oldm=oldms;savm=savms; */
10156: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
10157: /* for (h=0; h<=nhstepm; h++){ */
10158: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
10159: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
10160: /* } */
10161: /* for(j=1; j<=nlstate+ndeath;j++) { */
10162: /* kk1=0.;kk2=0; */
10163: /* for(i=1; i<=nlstate;i++) { */
10164: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
10165: /* } */
10166: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
10167: /* } */
10168: /* } */
10169: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10170: /* } */
10171: /* } */
10172: /* } */
10173: /* } */
1.218 brouard 10174:
1.227 brouard 10175: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 10176:
1.227 brouard 10177: /* if (popforecast==1) { */
10178: /* free_ivector(popage,0,AGESUP); */
10179: /* free_vector(popeffectif,0,AGESUP); */
10180: /* free_vector(popcount,0,AGESUP); */
10181: /* } */
10182: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10183: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10184: /* fclose(ficrespop); */
10185: /* } /\* End of popforecast *\/ */
1.218 brouard 10186:
1.126 brouard 10187: int fileappend(FILE *fichier, char *optionfich)
10188: {
10189: if((fichier=fopen(optionfich,"a"))==NULL) {
10190: printf("Problem with file: %s\n", optionfich);
10191: fprintf(ficlog,"Problem with file: %s\n", optionfich);
10192: return (0);
10193: }
10194: fflush(fichier);
10195: return (1);
10196: }
10197:
10198:
10199: /**************** function prwizard **********************/
10200: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
10201: {
10202:
10203: /* Wizard to print covariance matrix template */
10204:
1.164 brouard 10205: char ca[32], cb[32];
10206: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 10207: int numlinepar;
10208:
10209: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
10210: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
10211: for(i=1; i <=nlstate; i++){
10212: jj=0;
10213: for(j=1; j <=nlstate+ndeath; j++){
10214: if(j==i) continue;
10215: jj++;
10216: /*ca[0]= k+'a'-1;ca[1]='\0';*/
10217: printf("%1d%1d",i,j);
10218: fprintf(ficparo,"%1d%1d",i,j);
10219: for(k=1; k<=ncovmodel;k++){
10220: /* printf(" %lf",param[i][j][k]); */
10221: /* fprintf(ficparo," %lf",param[i][j][k]); */
10222: printf(" 0.");
10223: fprintf(ficparo," 0.");
10224: }
10225: printf("\n");
10226: fprintf(ficparo,"\n");
10227: }
10228: }
10229: printf("# Scales (for hessian or gradient estimation)\n");
10230: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
10231: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
10232: for(i=1; i <=nlstate; i++){
10233: jj=0;
10234: for(j=1; j <=nlstate+ndeath; j++){
10235: if(j==i) continue;
10236: jj++;
10237: fprintf(ficparo,"%1d%1d",i,j);
10238: printf("%1d%1d",i,j);
10239: fflush(stdout);
10240: for(k=1; k<=ncovmodel;k++){
10241: /* printf(" %le",delti3[i][j][k]); */
10242: /* fprintf(ficparo," %le",delti3[i][j][k]); */
10243: printf(" 0.");
10244: fprintf(ficparo," 0.");
10245: }
10246: numlinepar++;
10247: printf("\n");
10248: fprintf(ficparo,"\n");
10249: }
10250: }
10251: printf("# Covariance matrix\n");
10252: /* # 121 Var(a12)\n\ */
10253: /* # 122 Cov(b12,a12) Var(b12)\n\ */
10254: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
10255: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
10256: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
10257: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
10258: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
10259: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
10260: fflush(stdout);
10261: fprintf(ficparo,"# Covariance matrix\n");
10262: /* # 121 Var(a12)\n\ */
10263: /* # 122 Cov(b12,a12) Var(b12)\n\ */
10264: /* # ...\n\ */
10265: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
10266:
10267: for(itimes=1;itimes<=2;itimes++){
10268: jj=0;
10269: for(i=1; i <=nlstate; i++){
10270: for(j=1; j <=nlstate+ndeath; j++){
10271: if(j==i) continue;
10272: for(k=1; k<=ncovmodel;k++){
10273: jj++;
10274: ca[0]= k+'a'-1;ca[1]='\0';
10275: if(itimes==1){
10276: printf("#%1d%1d%d",i,j,k);
10277: fprintf(ficparo,"#%1d%1d%d",i,j,k);
10278: }else{
10279: printf("%1d%1d%d",i,j,k);
10280: fprintf(ficparo,"%1d%1d%d",i,j,k);
10281: /* printf(" %.5le",matcov[i][j]); */
10282: }
10283: ll=0;
10284: for(li=1;li <=nlstate; li++){
10285: for(lj=1;lj <=nlstate+ndeath; lj++){
10286: if(lj==li) continue;
10287: for(lk=1;lk<=ncovmodel;lk++){
10288: ll++;
10289: if(ll<=jj){
10290: cb[0]= lk +'a'-1;cb[1]='\0';
10291: if(ll<jj){
10292: if(itimes==1){
10293: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10294: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10295: }else{
10296: printf(" 0.");
10297: fprintf(ficparo," 0.");
10298: }
10299: }else{
10300: if(itimes==1){
10301: printf(" Var(%s%1d%1d)",ca,i,j);
10302: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
10303: }else{
10304: printf(" 0.");
10305: fprintf(ficparo," 0.");
10306: }
10307: }
10308: }
10309: } /* end lk */
10310: } /* end lj */
10311: } /* end li */
10312: printf("\n");
10313: fprintf(ficparo,"\n");
10314: numlinepar++;
10315: } /* end k*/
10316: } /*end j */
10317: } /* end i */
10318: } /* end itimes */
10319:
10320: } /* end of prwizard */
10321: /******************* Gompertz Likelihood ******************************/
10322: double gompertz(double x[])
10323: {
1.302 brouard 10324: double A=0.0,B=0.,L=0.0,sump=0.,num=0.;
1.126 brouard 10325: int i,n=0; /* n is the size of the sample */
10326:
1.220 brouard 10327: for (i=1;i<=imx ; i++) {
1.126 brouard 10328: sump=sump+weight[i];
10329: /* sump=sump+1;*/
10330: num=num+1;
10331: }
1.302 brouard 10332: L=0.0;
10333: /* agegomp=AGEGOMP; */
1.126 brouard 10334: /* for (i=0; i<=imx; i++)
10335: 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]);*/
10336:
1.302 brouard 10337: for (i=1;i<=imx ; i++) {
10338: /* mu(a)=mu(agecomp)*exp(teta*(age-agegomp))
10339: mu(a)=x[1]*exp(x[2]*(age-agegomp)); x[1] and x[2] are per year.
10340: * L= Product mu(agedeces)exp(-\int_ageexam^agedc mu(u) du ) for a death between agedc (in month)
10341: * and agedc +1 month, cens[i]=0: log(x[1]/YEARM)
10342: * +
10343: * exp(-\int_ageexam^agecens mu(u) du ) when censored, cens[i]=1
10344: */
10345: if (wav[i] > 1 || agedc[i] < AGESUP) {
10346: if (cens[i] == 1){
10347: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
10348: } else if (cens[i] == 0){
1.126 brouard 10349: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
1.302 brouard 10350: +log(x[1]/YEARM) +x[2]*(agedc[i]-agegomp)+log(YEARM);
10351: } else
10352: printf("Gompertz cens[%d] neither 1 nor 0\n",i);
1.126 brouard 10353: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
1.302 brouard 10354: L=L+A*weight[i];
1.126 brouard 10355: /* 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 10356: }
10357: }
1.126 brouard 10358:
1.302 brouard 10359: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
1.126 brouard 10360:
10361: return -2*L*num/sump;
10362: }
10363:
1.136 brouard 10364: #ifdef GSL
10365: /******************* Gompertz_f Likelihood ******************************/
10366: double gompertz_f(const gsl_vector *v, void *params)
10367: {
1.302 brouard 10368: double A=0.,B=0.,LL=0.0,sump=0.,num=0.;
1.136 brouard 10369: double *x= (double *) v->data;
10370: int i,n=0; /* n is the size of the sample */
10371:
10372: for (i=0;i<=imx-1 ; i++) {
10373: sump=sump+weight[i];
10374: /* sump=sump+1;*/
10375: num=num+1;
10376: }
10377:
10378:
10379: /* for (i=0; i<=imx; i++)
10380: 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]);*/
10381: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
10382: for (i=1;i<=imx ; i++)
10383: {
10384: if (cens[i] == 1 && wav[i]>1)
10385: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
10386:
10387: if (cens[i] == 0 && wav[i]>1)
10388: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
10389: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
10390:
10391: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
10392: if (wav[i] > 1 ) { /* ??? */
10393: LL=LL+A*weight[i];
10394: /* 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]);*/
10395: }
10396: }
10397:
10398: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
10399: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
10400:
10401: return -2*LL*num/sump;
10402: }
10403: #endif
10404:
1.126 brouard 10405: /******************* Printing html file ***********/
1.201 brouard 10406: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 10407: int lastpass, int stepm, int weightopt, char model[],\
10408: int imx, double p[],double **matcov,double agemortsup){
10409: int i,k;
10410:
10411: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
10412: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
10413: for (i=1;i<=2;i++)
10414: 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 10415: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 10416: fprintf(fichtm,"</ul>");
10417:
10418: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
10419:
10420: 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>");
10421:
10422: for (k=agegomp;k<(agemortsup-2);k++)
10423: 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]);
10424:
10425:
10426: fflush(fichtm);
10427: }
10428:
10429: /******************* Gnuplot file **************/
1.201 brouard 10430: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 10431:
10432: char dirfileres[132],optfileres[132];
1.164 brouard 10433:
1.126 brouard 10434: int ng;
10435:
10436:
10437: /*#ifdef windows */
10438: fprintf(ficgp,"cd \"%s\" \n",pathc);
10439: /*#endif */
10440:
10441:
10442: strcpy(dirfileres,optionfilefiname);
10443: strcpy(optfileres,"vpl");
1.199 brouard 10444: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 10445: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 10446: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 10447: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 10448: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
10449:
10450: }
10451:
1.136 brouard 10452: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
10453: {
1.126 brouard 10454:
1.136 brouard 10455: /*-------- data file ----------*/
10456: FILE *fic;
10457: char dummy[]=" ";
1.240 brouard 10458: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 10459: int lstra;
1.136 brouard 10460: int linei, month, year,iout;
1.302 brouard 10461: int noffset=0; /* This is the offset if BOM data file */
1.136 brouard 10462: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 10463: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 10464: char *stratrunc;
1.223 brouard 10465:
1.240 brouard 10466: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
10467: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.328 brouard 10468: for(v=1;v<NCOVMAX;v++){
10469: DummyV[v]=0;
10470: FixedV[v]=0;
10471: }
1.126 brouard 10472:
1.240 brouard 10473: for(v=1; v <=ncovcol;v++){
10474: DummyV[v]=0;
10475: FixedV[v]=0;
10476: }
10477: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
10478: DummyV[v]=1;
10479: FixedV[v]=0;
10480: }
10481: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
10482: DummyV[v]=0;
10483: FixedV[v]=1;
10484: }
10485: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
10486: DummyV[v]=1;
10487: FixedV[v]=1;
10488: }
10489: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
10490: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
10491: 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]);
10492: }
1.339 brouard 10493:
10494: ncovcolt=ncovcol+nqv+ntv+nqtv; /* total of covariates in the data, not in the model equation */
10495:
1.136 brouard 10496: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 10497: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
10498: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 10499: }
1.126 brouard 10500:
1.302 brouard 10501: /* Is it a BOM UTF-8 Windows file? */
10502: /* First data line */
10503: linei=0;
10504: while(fgets(line, MAXLINE, fic)) {
10505: noffset=0;
10506: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
10507: {
10508: noffset=noffset+3;
10509: printf("# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);fflush(stdout);
10510: fprintf(ficlog,"# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);
10511: fflush(ficlog); return 1;
10512: }
10513: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
10514: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
10515: {
10516: noffset=noffset+2;
1.304 brouard 10517: 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);
10518: 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 10519: fflush(ficlog); return 1;
10520: }
10521: else if( line[0] == 0 && line[1] == 0)
10522: {
10523: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
10524: noffset=noffset+4;
1.304 brouard 10525: 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);
10526: 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 10527: fflush(ficlog); return 1;
10528: }
10529: } else{
10530: ;/*printf(" Not a BOM file\n");*/
10531: }
10532: /* If line starts with a # it is a comment */
10533: if (line[noffset] == '#') {
10534: linei=linei+1;
10535: break;
10536: }else{
10537: break;
10538: }
10539: }
10540: fclose(fic);
10541: if((fic=fopen(datafile,"r"))==NULL) {
10542: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
10543: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
10544: }
10545: /* Not a Bom file */
10546:
1.136 brouard 10547: i=1;
10548: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
10549: linei=linei+1;
10550: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
10551: if(line[j] == '\t')
10552: line[j] = ' ';
10553: }
10554: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
10555: ;
10556: };
10557: line[j+1]=0; /* Trims blanks at end of line */
10558: if(line[0]=='#'){
10559: fprintf(ficlog,"Comment line\n%s\n",line);
10560: printf("Comment line\n%s\n",line);
10561: continue;
10562: }
10563: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 10564: strcpy(line, linetmp);
1.223 brouard 10565:
10566: /* Loops on waves */
10567: for (j=maxwav;j>=1;j--){
10568: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 10569: cutv(stra, strb, line, ' ');
10570: if(strb[0]=='.') { /* Missing value */
10571: lval=-1;
10572: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
1.341 brouard 10573: cotvar[j][ncovcol+nqv+ntv+iv][i]=-1; /* For performance reasons */
1.238 brouard 10574: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
10575: 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);
10576: 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);
10577: return 1;
10578: }
10579: }else{
10580: errno=0;
10581: /* what_kind_of_number(strb); */
10582: dval=strtod(strb,&endptr);
10583: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
10584: /* if(strb != endptr && *endptr == '\0') */
10585: /* dval=dlval; */
10586: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
10587: if( strb[0]=='\0' || (*endptr != '\0')){
10588: 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);
10589: 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);
10590: return 1;
10591: }
10592: cotqvar[j][iv][i]=dval;
1.341 brouard 10593: cotvar[j][ncovcol+nqv+ntv+iv][i]=dval; /* because cotvar starts now at first ntv */
1.238 brouard 10594: }
10595: strcpy(line,stra);
1.223 brouard 10596: }/* end loop ntqv */
1.225 brouard 10597:
1.223 brouard 10598: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 10599: cutv(stra, strb, line, ' ');
10600: if(strb[0]=='.') { /* Missing value */
10601: lval=-1;
10602: }else{
10603: errno=0;
10604: lval=strtol(strb,&endptr,10);
10605: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
10606: if( strb[0]=='\0' || (*endptr != '\0')){
10607: 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);
10608: 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);
10609: return 1;
10610: }
10611: }
10612: if(lval <-1 || lval >1){
10613: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10614: 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 10615: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10616: For example, for multinomial values like 1, 2 and 3,\n \
10617: build V1=0 V2=0 for the reference value (1),\n \
10618: V1=1 V2=0 for (2) \n \
1.223 brouard 10619: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10620: output of IMaCh is often meaningless.\n \
1.319 brouard 10621: Exiting.\n",lval,linei, i,line,iv,j);
1.238 brouard 10622: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10623: 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 10624: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10625: For example, for multinomial values like 1, 2 and 3,\n \
10626: build V1=0 V2=0 for the reference value (1),\n \
10627: V1=1 V2=0 for (2) \n \
1.223 brouard 10628: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10629: output of IMaCh is often meaningless.\n \
1.319 brouard 10630: Exiting.\n",lval,linei, i,line,iv,j);fflush(ficlog);
1.238 brouard 10631: return 1;
10632: }
1.341 brouard 10633: cotvar[j][ncovcol+nqv+iv][i]=(double)(lval);
1.238 brouard 10634: strcpy(line,stra);
1.223 brouard 10635: }/* end loop ntv */
1.225 brouard 10636:
1.223 brouard 10637: /* Statuses at wave */
1.137 brouard 10638: cutv(stra, strb, line, ' ');
1.223 brouard 10639: if(strb[0]=='.') { /* Missing value */
1.238 brouard 10640: lval=-1;
1.136 brouard 10641: }else{
1.238 brouard 10642: errno=0;
10643: lval=strtol(strb,&endptr,10);
10644: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
10645: if( strb[0]=='\0' || (*endptr != '\0')){
10646: 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);
10647: 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);
10648: return 1;
10649: }
1.136 brouard 10650: }
1.225 brouard 10651:
1.136 brouard 10652: s[j][i]=lval;
1.225 brouard 10653:
1.223 brouard 10654: /* Date of Interview */
1.136 brouard 10655: strcpy(line,stra);
10656: cutv(stra, strb,line,' ');
1.169 brouard 10657: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10658: }
1.169 brouard 10659: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 10660: month=99;
10661: year=9999;
1.136 brouard 10662: }else{
1.225 brouard 10663: 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);
10664: 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);
10665: return 1;
1.136 brouard 10666: }
10667: anint[j][i]= (double) year;
1.302 brouard 10668: mint[j][i]= (double)month;
10669: /* if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){ */
10670: /* 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]); */
10671: /* 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]); */
10672: /* } */
1.136 brouard 10673: strcpy(line,stra);
1.223 brouard 10674: } /* End loop on waves */
1.225 brouard 10675:
1.223 brouard 10676: /* Date of death */
1.136 brouard 10677: cutv(stra, strb,line,' ');
1.169 brouard 10678: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10679: }
1.169 brouard 10680: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 10681: month=99;
10682: year=9999;
10683: }else{
1.141 brouard 10684: 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 10685: 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);
10686: return 1;
1.136 brouard 10687: }
10688: andc[i]=(double) year;
10689: moisdc[i]=(double) month;
10690: strcpy(line,stra);
10691:
1.223 brouard 10692: /* Date of birth */
1.136 brouard 10693: cutv(stra, strb,line,' ');
1.169 brouard 10694: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10695: }
1.169 brouard 10696: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 10697: month=99;
10698: year=9999;
10699: }else{
1.141 brouard 10700: 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);
10701: 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 10702: return 1;
1.136 brouard 10703: }
10704: if (year==9999) {
1.141 brouard 10705: 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);
10706: 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 10707: return 1;
10708:
1.136 brouard 10709: }
10710: annais[i]=(double)(year);
1.302 brouard 10711: moisnais[i]=(double)(month);
10712: for (j=1;j<=maxwav;j++){
10713: if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){
10714: 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]);
10715: 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]);
10716: }
10717: }
10718:
1.136 brouard 10719: strcpy(line,stra);
1.225 brouard 10720:
1.223 brouard 10721: /* Sample weight */
1.136 brouard 10722: cutv(stra, strb,line,' ');
10723: errno=0;
10724: dval=strtod(strb,&endptr);
10725: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 10726: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
10727: 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 10728: fflush(ficlog);
10729: return 1;
10730: }
10731: weight[i]=dval;
10732: strcpy(line,stra);
1.225 brouard 10733:
1.223 brouard 10734: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
10735: cutv(stra, strb, line, ' ');
10736: if(strb[0]=='.') { /* Missing value */
1.225 brouard 10737: lval=-1;
1.311 brouard 10738: coqvar[iv][i]=NAN;
10739: covar[ncovcol+iv][i]=NAN; /* including qvar in standard covar for performance reasons */
1.223 brouard 10740: }else{
1.225 brouard 10741: errno=0;
10742: /* what_kind_of_number(strb); */
10743: dval=strtod(strb,&endptr);
10744: /* if(strb != endptr && *endptr == '\0') */
10745: /* dval=dlval; */
10746: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
10747: if( strb[0]=='\0' || (*endptr != '\0')){
10748: 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);
10749: 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);
10750: return 1;
10751: }
10752: coqvar[iv][i]=dval;
1.226 brouard 10753: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 10754: }
10755: strcpy(line,stra);
10756: }/* end loop nqv */
1.136 brouard 10757:
1.223 brouard 10758: /* Covariate values */
1.136 brouard 10759: for (j=ncovcol;j>=1;j--){
10760: cutv(stra, strb,line,' ');
1.223 brouard 10761: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 10762: lval=-1;
1.136 brouard 10763: }else{
1.225 brouard 10764: errno=0;
10765: lval=strtol(strb,&endptr,10);
10766: if( strb[0]=='\0' || (*endptr != '\0')){
10767: 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);
10768: 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);
10769: return 1;
10770: }
1.136 brouard 10771: }
10772: if(lval <-1 || lval >1){
1.225 brouard 10773: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 10774: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
10775: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 10776: For example, for multinomial values like 1, 2 and 3,\n \
10777: build V1=0 V2=0 for the reference value (1),\n \
10778: V1=1 V2=0 for (2) \n \
1.136 brouard 10779: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 10780: output of IMaCh is often meaningless.\n \
1.136 brouard 10781: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 10782: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 10783: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
10784: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 10785: For example, for multinomial values like 1, 2 and 3,\n \
10786: build V1=0 V2=0 for the reference value (1),\n \
10787: V1=1 V2=0 for (2) \n \
1.136 brouard 10788: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 10789: output of IMaCh is often meaningless.\n \
1.136 brouard 10790: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 10791: return 1;
1.136 brouard 10792: }
10793: covar[j][i]=(double)(lval);
10794: strcpy(line,stra);
10795: }
10796: lstra=strlen(stra);
1.225 brouard 10797:
1.136 brouard 10798: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
10799: stratrunc = &(stra[lstra-9]);
10800: num[i]=atol(stratrunc);
10801: }
10802: else
10803: num[i]=atol(stra);
10804: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
10805: 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;}*/
10806:
10807: i=i+1;
10808: } /* End loop reading data */
1.225 brouard 10809:
1.136 brouard 10810: *imax=i-1; /* Number of individuals */
10811: fclose(fic);
1.225 brouard 10812:
1.136 brouard 10813: return (0);
1.164 brouard 10814: /* endread: */
1.225 brouard 10815: printf("Exiting readdata: ");
10816: fclose(fic);
10817: return (1);
1.223 brouard 10818: }
1.126 brouard 10819:
1.234 brouard 10820: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 10821: char *p1 = *stri, *p2 = *stri;
1.235 brouard 10822: while (*p2 == ' ')
1.234 brouard 10823: p2++;
10824: /* while ((*p1++ = *p2++) !=0) */
10825: /* ; */
10826: /* do */
10827: /* while (*p2 == ' ') */
10828: /* p2++; */
10829: /* while (*p1++ == *p2++); */
10830: *stri=p2;
1.145 brouard 10831: }
10832:
1.330 brouard 10833: int decoderesult( char resultline[], int nres)
1.230 brouard 10834: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
10835: {
1.235 brouard 10836: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 10837: char resultsav[MAXLINE];
1.330 brouard 10838: /* int resultmodel[MAXLINE]; */
1.334 brouard 10839: /* int modelresult[MAXLINE]; */
1.230 brouard 10840: char stra[80], strb[80], strc[80], strd[80],stre[80];
10841:
1.234 brouard 10842: removefirstspace(&resultline);
1.332 brouard 10843: printf("decoderesult:%s\n",resultline);
1.230 brouard 10844:
1.332 brouard 10845: strcpy(resultsav,resultline);
1.342 brouard 10846: /* printf("Decoderesult resultsav=\"%s\" resultline=\"%s\"\n", resultsav, resultline); */
1.230 brouard 10847: if (strlen(resultsav) >1){
1.334 brouard 10848: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' in this resultline */
1.230 brouard 10849: }
1.253 brouard 10850: if(j == 0){ /* Resultline but no = */
10851: TKresult[nres]=0; /* Combination for the nresult and the model */
10852: return (0);
10853: }
1.234 brouard 10854: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
1.334 brouard 10855: 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);
10856: 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 10857: /* return 1;*/
1.234 brouard 10858: }
1.334 brouard 10859: for(k=1; k<=j;k++){ /* Loop on any covariate of the RESULT LINE */
1.234 brouard 10860: if(nbocc(resultsav,'=') >1){
1.318 brouard 10861: 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 10862: /* 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 10863: cutl(strc,strd,strb,'='); /* strb:"V4=1" strc="1" strd="V4" */
1.332 brouard 10864: /* If a blank, then strc="V4=" and strd='\0' */
10865: if(strc[0]=='\0'){
10866: printf("Error in resultline, probably a blank after the \"%s\", \"result:%s\", stra=\"%s\" resultsav=\"%s\"\n",strb,resultline, stra, resultsav);
10867: fprintf(ficlog,"Error in resultline, probably a blank after the \"V%s=\", resultline=%s\n",strb,resultline);
10868: return 1;
10869: }
1.234 brouard 10870: }else
10871: cutl(strc,strd,resultsav,'=');
1.318 brouard 10872: Tvalsel[k]=atof(strc); /* 1 */ /* Tvalsel of k is the float value of the kth covariate appearing in this result line */
1.234 brouard 10873:
1.230 brouard 10874: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
1.318 brouard 10875: 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 10876: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
10877: /* cptcovsel++; */
10878: if (nbocc(stra,'=') >0)
10879: strcpy(resultsav,stra); /* and analyzes it */
10880: }
1.235 brouard 10881: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 10882: /* 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 10883: 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 10884: if(Typevar[k1]==0){ /* Single covariate in model */
10885: /* 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.234 brouard 10886: match=0;
1.318 brouard 10887: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
10888: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 10889: modelresult[nres][k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.318 brouard 10890: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
1.234 brouard 10891: break;
10892: }
10893: }
10894: if(match == 0){
1.338 brouard 10895: 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]);
10896: 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 10897: return 1;
1.234 brouard 10898: }
1.332 brouard 10899: }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*/
10900: /* We feed resultmodel[k1]=k2; */
10901: match=0;
10902: 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 */
10903: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 10904: 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 10905: resultmodel[nres][k1]=k2; /* Added here */
1.342 brouard 10906: /* printf("Decoderesult first modelresult[k2=%d]=%d (k1) V%d*AGE\n",k2,k1,Tvar[k1]); */
1.332 brouard 10907: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
10908: break;
10909: }
10910: }
10911: if(match == 0){
1.338 brouard 10912: 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]);
10913: 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 10914: return 1;
10915: }
10916: }else if(Typevar[k1]==2){ /* Product No age We want to get the position in the resultline of the product in the model line*/
10917: /* resultmodel[nres][of such a Vn * Vm product k1] is not unique, so can't exist, we feed Tvard[k1][1] and [2] */
10918: match=0;
1.342 brouard 10919: /* printf("Decoderesult very first Product Tvardk[k1=%d][1]=%d Tvardk[k1=%d][2]=%d V%d * V%d\n",k1,Tvardk[k1][1],k1,Tvardk[k1][2],Tvardk[k1][1],Tvardk[k1][2]); */
1.332 brouard 10920: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
10921: if(Tvardk[k1][1]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
10922: /* modelresult[k2]=k1; */
1.342 brouard 10923: /* printf("Decoderesult first Product modelresult[k2=%d]=%d (k1) V%d * \n",k2,k1,Tvarsel[k2]); */
1.332 brouard 10924: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
10925: }
10926: }
10927: if(match == 0){
1.338 brouard 10928: 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);
10929: 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 10930: return 1;
10931: }
10932: match=0;
10933: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
10934: if(Tvardk[k1][2]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
10935: /* modelresult[k2]=k1;*/
1.342 brouard 10936: /* printf("Decoderesult second Product modelresult[k2=%d]=%d (k1) * V%d \n ",k2,k1,Tvarsel[k2]); */
1.332 brouard 10937: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
10938: break;
10939: }
10940: }
10941: if(match == 0){
1.338 brouard 10942: 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);
10943: 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 10944: return 1;
10945: }
10946: }/* End of testing */
1.333 brouard 10947: }/* End loop cptcovt */
1.235 brouard 10948: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 10949: /* Feeds resultmodel[nres][k1]=k2 for single covariate (k1) in the model equation */
1.334 brouard 10950: 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)
10951: * Loop on resultline variables: result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 10952: match=0;
1.318 brouard 10953: 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 10954: if(Typevar[k1]==0){ /* Single only */
1.237 brouard 10955: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.330 brouard 10956: 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 10957: 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 10958: ++match;
10959: }
10960: }
10961: }
10962: if(match == 0){
1.338 brouard 10963: printf("Error in result line: variable V%d is missing in model; result: %s, model=1+age+%s\n",Tvarsel[k2], resultline, model);
10964: 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 10965: return 1;
1.234 brouard 10966: }else if(match > 1){
1.338 brouard 10967: printf("Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
10968: fprintf(ficlog,"Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
1.310 brouard 10969: return 1;
1.234 brouard 10970: }
10971: }
1.334 brouard 10972: /* cptcovres=j /\* Number of variables in the resultline is equal to cptcovs and thus useless *\/ */
1.234 brouard 10973: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 10974: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.330 brouard 10975: /* nres=1st result line: V4=1 V5=25.1 V3=0 V2=8 V1=1 */
10976: /* 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*/
10977: /* nres=2nd result line: V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.235 brouard 10978: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
10979: /* 1 0 0 0 */
10980: /* 2 1 0 0 */
10981: /* 3 0 1 0 */
1.330 brouard 10982: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 (nres=2)*/
1.235 brouard 10983: /* 5 0 0 1 */
1.330 brouard 10984: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 (nres=1)*/
1.235 brouard 10985: /* 7 0 1 1 */
10986: /* 8 1 1 1 */
1.237 brouard 10987: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
10988: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
10989: /* V5*age V5 known which value for nres? */
10990: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.334 brouard 10991: 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.
10992: * loop on position k1 in the MODEL LINE */
1.331 brouard 10993: /* k counting number of combination of single dummies in the equation model */
10994: /* k4 counting single dummies in the equation model */
10995: /* k4q counting single quantitatives in the equation model */
1.344 brouard 10996: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Dummy and Single, fixed or timevarying, k1 is sorting according to MODEL, but k3 to resultline */
1.334 brouard 10997: /* 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 10998: /* 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 10999: /* Value in the (current nres) resultline of the variable at the k1th position in the model equation resultmodel[nres][k1]= k3 */
1.332 brouard 11000: /* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline */
11001: /* k3 is the position in the nres result line of the k1th variable of the model equation */
11002: /* Tvarsel[k3]: Name of the variable at the k3th position in the result line. */
11003: /* Tvalsel[k3]: Value of the variable at the k3th position in the result line. */
11004: /* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.334 brouard 11005: /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 11006: /* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1.330 brouard 11007: /* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.332 brouard 11008: k3= resultmodel[nres][k1]; /* From position k1 in model get position k3 in result line */
11009: /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
11010: 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 11011: 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 11012: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][Name]=Value; stores the value into the name of the variable. */
1.332 brouard 11013: /* Tinvresult[nres][4]=1 */
1.334 brouard 11014: /* Tresult[nres][k4+1]=Tvalsel[k3];/\* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) *\/ */
11015: Tresult[nres][k3]=Tvalsel[k3];/* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) */
11016: /* Tvresult[nres][k4+1]=(int)Tvarsel[k3];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
11017: Tvresult[nres][k3]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
1.237 brouard 11018: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.334 brouard 11019: precov[nres][k1]=Tvalsel[k3]; /* Value from resultline of the variable at the k1 position in the model */
1.342 brouard 11020: /* 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 11021: k4++;;
1.331 brouard 11022: }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Quantitative and single */
1.330 brouard 11023: /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.332 brouard 11024: /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.330 brouard 11025: /* Tqinvresult[nres][Name of a quantitative variable]= value of the variable in the result line */
1.332 brouard 11026: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 5 =k3q */
11027: k2q=(int)Tvarsel[k3q]; /* Name of variable at k3q th position in the resultline */
11028: /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.334 brouard 11029: /* Tqresult[nres][k4q+1]=Tvalsel[k3q]; /\* Tqresult[nres][1]=25.1 *\/ */
11030: /* Tvresult[nres][k4q+1]=(int)Tvarsel[k3q];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
11031: /* Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /\* Tvqresult[nres][1]=5 *\/ */
11032: Tqresult[nres][k3q]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
11033: Tvresult[nres][k3q]=(int)Tvarsel[k3q];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
11034: Tvqresult[nres][k3q]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
1.237 brouard 11035: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.330 brouard 11036: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.332 brouard 11037: precov[nres][k1]=Tvalsel[k3q];
1.342 brouard 11038: /* 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 11039: k4q++;;
1.331 brouard 11040: }else if( Dummy[k1]==2 ){ /* For dummy with age product */
11041: /* Tvar[k1]; */ /* Age variable */
1.332 brouard 11042: /* Wrong we want the value of variable name Tvar[k1] */
11043:
11044: k3= resultmodel[nres][k1]; /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
1.331 brouard 11045: 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 11046: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][4]=1 */
1.332 brouard 11047: precov[nres][k1]=Tvalsel[k3];
1.342 brouard 11048: /* 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 11049: }else if( Dummy[k1]==3 ){ /* For quant with age product */
1.332 brouard 11050: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 25.1=k3q */
1.331 brouard 11051: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.334 brouard 11052: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* TinvDoQresult[nres][5]=25.1 */
1.332 brouard 11053: precov[nres][k1]=Tvalsel[k3q];
1.342 brouard 11054: /* 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 11055: }else if(Typevar[k1]==2 ){ /* For product quant or dummy (not with age) */
1.332 brouard 11056: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
1.342 brouard 11057: /* 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 11058: }else{
1.332 brouard 11059: printf("Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
11060: fprintf(ficlog,"Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
1.235 brouard 11061: }
11062: }
1.234 brouard 11063:
1.334 brouard 11064: TKresult[nres]=++k; /* Number of combinations of dummies for the nresult and the model =Tvalsel[k3]*pow(2,k4) + 1*/
1.230 brouard 11065: return (0);
11066: }
1.235 brouard 11067:
1.230 brouard 11068: int decodemodel( char model[], int lastobs)
11069: /**< This routine decodes the model and returns:
1.224 brouard 11070: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
11071: * - nagesqr = 1 if age*age in the model, otherwise 0.
11072: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
11073: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
11074: * - cptcovage number of covariates with age*products =2
11075: * - cptcovs number of simple covariates
1.339 brouard 11076: * ncovcolt=ncovcol+nqv+ntv+nqtv total of covariates in the data, not in the model equation
1.224 brouard 11077: * - 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 11078: * which is a new column after the 9 (ncovcol+nqv+ntv+nqtv) variables.
1.319 brouard 11079: * - if k is a product Vn*Vm, covar[k][i] is filled with correct values for each individual
1.224 brouard 11080: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
11081: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
11082: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
11083: */
1.319 brouard 11084: /* 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 11085: {
1.238 brouard 11086: int i, j, k, ks, v;
1.227 brouard 11087: int j1, k1, k2, k3, k4;
1.136 brouard 11088: char modelsav[80];
1.145 brouard 11089: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 11090: char *strpt;
1.136 brouard 11091:
1.145 brouard 11092: /*removespace(model);*/
1.136 brouard 11093: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 11094: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 11095: if (strstr(model,"AGE") !=0){
1.192 brouard 11096: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
11097: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 11098: return 1;
11099: }
1.141 brouard 11100: if (strstr(model,"v") !=0){
1.338 brouard 11101: printf("Error. 'v' must be in upper case 'V' model=1+age+%s ",model);
11102: fprintf(ficlog,"Error. 'v' must be in upper case model=1+age+%s ",model);fflush(ficlog);
1.141 brouard 11103: return 1;
11104: }
1.187 brouard 11105: strcpy(modelsav,model);
11106: if ((strpt=strstr(model,"age*age")) !=0){
1.338 brouard 11107: printf(" strpt=%s, model=1+age+%s\n",strpt, model);
1.187 brouard 11108: if(strpt != model){
1.338 brouard 11109: printf("Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 11110: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 11111: corresponding column of parameters.\n",model);
1.338 brouard 11112: fprintf(ficlog,"Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 11113: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 11114: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 11115: return 1;
1.225 brouard 11116: }
1.187 brouard 11117: nagesqr=1;
11118: if (strstr(model,"+age*age") !=0)
1.234 brouard 11119: substrchaine(modelsav, model, "+age*age");
1.187 brouard 11120: else if (strstr(model,"age*age+") !=0)
1.234 brouard 11121: substrchaine(modelsav, model, "age*age+");
1.187 brouard 11122: else
1.234 brouard 11123: substrchaine(modelsav, model, "age*age");
1.187 brouard 11124: }else
11125: nagesqr=0;
11126: if (strlen(modelsav) >1){
11127: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
11128: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 11129: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 11130: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 11131: * cst, age and age*age
11132: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
11133: /* including age products which are counted in cptcovage.
11134: * but the covariates which are products must be treated
11135: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 11136: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
11137: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 11138:
11139:
1.187 brouard 11140: /* Design
11141: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
11142: * < ncovcol=8 >
11143: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
11144: * k= 1 2 3 4 5 6 7 8
11145: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
1.345 ! brouard 11146: * covar[k,i], are for fixed covariates, value of kth covariate if not including age for individual i:
1.224 brouard 11147: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
11148: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 11149: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
11150: * Tage[++cptcovage]=k
1.345 ! brouard 11151: * if products, new covar are created after ncovcol + nqv (quanti fixed) with k1
1.187 brouard 11152: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
11153: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
11154: * 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
11155: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
11156: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
11157: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
1.345 ! brouard 11158: * < ncovcol=8 8 fixed covariate. Additional starts at 9 (V5*V6) and 10(V7*V8) >
1.187 brouard 11159: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
11160: * k= 1 2 3 4 5 6 7 8 9 10 11 12
1.345 ! brouard 11161: * Tvard[k]= 2 1 3 3 10 11 8 8 5 6 7 8
! 11162: * p Tvar[1]@12={2, 1, 3, 3, 9, 10, 8, 8}
1.187 brouard 11163: * p Tprod[1]@2={ 6, 5}
11164: *p Tvard[1][1]@4= {7, 8, 5, 6}
11165: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
11166: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
1.319 brouard 11167: *How to reorganize? Tvars(orted)
1.187 brouard 11168: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
11169: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
11170: * {2, 1, 4, 8, 5, 6, 3, 7}
11171: * Struct []
11172: */
1.225 brouard 11173:
1.187 brouard 11174: /* This loop fills the array Tvar from the string 'model'.*/
11175: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
11176: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
11177: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
11178: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
11179: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
11180: /* k=1 Tvar[1]=2 (from V2) */
11181: /* k=5 Tvar[5] */
11182: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 11183: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 11184: /* } */
1.198 brouard 11185: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 11186: /*
11187: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 11188: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
11189: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
11190: }
1.187 brouard 11191: cptcovage=0;
1.319 brouard 11192: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model line */
11193: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+' cutl from left to right
11194: 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" */
11195: if (nbocc(modelsav,'+')==0)
11196: strcpy(strb,modelsav); /* and analyzes it */
1.234 brouard 11197: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
11198: /*scanf("%d",i);*/
1.319 brouard 11199: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V5*age+ V4+V3*age strb=V3*age */
11200: 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 11201: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
11202: /* covar is not filled and then is empty */
11203: cptcovprod--;
11204: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
1.319 brouard 11205: 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 11206: Typevar[k]=1; /* 1 for age product */
1.319 brouard 11207: cptcovage++; /* Counts the number of covariates which include age as a product */
11208: 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 11209: /*printf("stre=%s ", stre);*/
11210: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
11211: cptcovprod--;
11212: cutl(stre,strb,strc,'V');
11213: Tvar[k]=atoi(stre);
11214: Typevar[k]=1; /* 1 for age product */
11215: cptcovage++;
11216: Tage[cptcovage]=k;
11217: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
11218: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
11219: cptcovn++;
11220: cptcovprodnoage++;k1++;
11221: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
1.339 brouard 11222: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* ncovcolt+k1; For model-covariate k tells which data-covariate to use but
1.234 brouard 11223: because this model-covariate is a construction we invent a new column
11224: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
1.335 brouard 11225: If already ncovcol=4 and model= V2 + V1 + V1*V4 + age*V3 + V3*V2
1.319 brouard 11226: thus after V4 we invent V5 and V6 because age*V3 will be computed in 4
1.339 brouard 11227: Tvar[3=V1*V4]=4+1=5 Tvar[5=V3*V2]=4 + 2= 6, Tvar[4=age*V3]=3 etc */
1.335 brouard 11228: /* Please remark that the new variables are model dependent */
11229: /* If we have 4 variable but the model uses only 3, like in
11230: * model= V1 + age*V1 + V2 + V3 + age*V2 + age*V3 + V1*V2 + V1*V3
11231: * k= 1 2 3 4 5 6 7 8
11232: * Tvar[k]=1 1 2 3 2 3 (5 6) (and not 4 5 because of V4 missing)
11233: * Tage[kk] [1]= 2 [2]=5 [3]=6 kk=1 to cptcovage=3
11234: * Tvar[Tage[kk]][1]=2 [2]=2 [3]=3
11235: */
1.339 brouard 11236: Typevar[k]=2; /* 2 for product */
1.234 brouard 11237: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
11238: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
1.319 brouard 11239: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 */
1.234 brouard 11240: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
1.330 brouard 11241: Tvardk[k][1] =atoi(strc); /* m 1 for V1*/
1.234 brouard 11242: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
1.330 brouard 11243: Tvardk[k][2] =atoi(stre); /* n 4 for V4*/
1.234 brouard 11244: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
11245: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
11246: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 11247: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 11248: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
1.339 brouard 11249: 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 */
11250: for (i=1; i<=lastobs;i++){/* For fixed product */
1.234 brouard 11251: /* Computes the new covariate which is a product of
11252: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
1.339 brouard 11253: covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
11254: }
11255: } /*End of FixedV */
1.234 brouard 11256: } /* End age is not in the model */
11257: } /* End if model includes a product */
1.319 brouard 11258: else { /* not a product */
1.234 brouard 11259: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
11260: /* scanf("%d",i);*/
11261: cutl(strd,strc,strb,'V');
11262: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
11263: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
11264: Tvar[k]=atoi(strd);
11265: Typevar[k]=0; /* 0 for simple covariates */
11266: }
11267: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 11268: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 11269: scanf("%d",i);*/
1.187 brouard 11270: } /* end of loop + on total covariates */
11271: } /* end if strlen(modelsave == 0) age*age might exist */
11272: } /* end if strlen(model == 0) */
1.136 brouard 11273:
11274: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
11275: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 11276:
1.136 brouard 11277: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 11278: printf("cptcovprod=%d ", cptcovprod);
11279: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
11280: scanf("%d ",i);*/
11281:
11282:
1.230 brouard 11283: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
11284: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 11285: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
11286: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
11287: k = 1 2 3 4 5 6 7 8 9
11288: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
1.319 brouard 11289: Typevar[k]= 0 0 0 2 1 0 2 1 0
1.227 brouard 11290: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
11291: Dummy[k] 1 0 0 0 3 1 1 2 3
11292: Tmodelind[combination of covar]=k;
1.225 brouard 11293: */
11294: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 11295: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 11296: /* 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 11297: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.318 brouard 11298: printf("Model=1+age+%s\n\
1.227 brouard 11299: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
11300: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
11301: 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 11302: fprintf(ficlog,"Model=1+age+%s\n\
1.227 brouard 11303: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
11304: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
11305: Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product\n",model);
1.342 brouard 11306: for(k=-1;k<=NCOVMAX; k++){ Fixed[k]=0; Dummy[k]=0;}
11307: for(k=1;k<=NCOVMAX; k++){TvarFind[k]=0; TvarVind[k]=0;}
1.343 brouard 11308: 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 loop on k from model */
1.234 brouard 11309: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 11310: Fixed[k]= 0;
11311: Dummy[k]= 0;
1.225 brouard 11312: ncoveff++;
1.232 brouard 11313: ncovf++;
1.234 brouard 11314: nsd++;
11315: modell[k].maintype= FTYPE;
11316: TvarsD[nsd]=Tvar[k];
11317: TvarsDind[nsd]=k;
1.330 brouard 11318: TnsdVar[Tvar[k]]=nsd;
1.234 brouard 11319: TvarF[ncovf]=Tvar[k];
11320: TvarFind[ncovf]=k;
11321: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
11322: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.339 brouard 11323: /* }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /\* Product of fixed dummy (<=ncovcol) covariates For a fixed product k is higher than ncovcol *\/ */
11324: }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 11325: Fixed[k]= 0;
11326: Dummy[k]= 0;
11327: ncoveff++;
11328: ncovf++;
11329: modell[k].maintype= FTYPE;
11330: TvarF[ncovf]=Tvar[k];
1.330 brouard 11331: /* TnsdVar[Tvar[k]]=nsd; */ /* To be done */
1.234 brouard 11332: TvarFind[ncovf]=k;
1.230 brouard 11333: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 11334: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.240 brouard 11335: }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 11336: Fixed[k]= 0;
11337: Dummy[k]= 1;
1.230 brouard 11338: nqfveff++;
1.234 brouard 11339: modell[k].maintype= FTYPE;
11340: modell[k].subtype= FQ;
11341: nsq++;
1.334 brouard 11342: TvarsQ[nsq]=Tvar[k]; /* Gives the variable name (extended to products) of first nsq simple quantitative covariates (fixed or time vary see below */
11343: TvarsQind[nsq]=k; /* Gives the position in the model equation of the first nsq simple quantitative covariates (fixed or time vary) */
1.232 brouard 11344: ncovf++;
1.234 brouard 11345: TvarF[ncovf]=Tvar[k];
11346: TvarFind[ncovf]=k;
1.231 brouard 11347: 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 11348: 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 11349: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.339 brouard 11350: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11351: /* model V1+V3+age*V1+age*V3+V1*V3 */
11352: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11353: ncovvt++;
11354: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
11355: TvarVVind[ncovvt]=k; /* TvarVVind[1]=2 (second position in the model equation */
11356:
1.227 brouard 11357: Fixed[k]= 1;
11358: Dummy[k]= 0;
1.225 brouard 11359: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 11360: modell[k].maintype= VTYPE;
11361: modell[k].subtype= VD;
11362: nsd++;
11363: TvarsD[nsd]=Tvar[k];
11364: TvarsDind[nsd]=k;
1.330 brouard 11365: TnsdVar[Tvar[k]]=nsd; /* To be verified */
1.234 brouard 11366: ncovv++; /* Only simple time varying variables */
11367: TvarV[ncovv]=Tvar[k];
1.242 brouard 11368: 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 11369: 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 */
11370: 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 11371: 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);
11372: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 11373: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.339 brouard 11374: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11375: /* model V1+V3+age*V1+age*V3+V1*V3 */
11376: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11377: ncovvt++;
11378: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
11379: TvarVVind[ncovvt]=k; /* TvarVV[1]=V3 (first time varying in the model equation */
11380:
1.234 brouard 11381: Fixed[k]= 1;
11382: Dummy[k]= 1;
11383: nqtveff++;
11384: modell[k].maintype= VTYPE;
11385: modell[k].subtype= VQ;
11386: ncovv++; /* Only simple time varying variables */
11387: nsq++;
1.334 brouard 11388: 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) */
11389: 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 11390: TvarV[ncovv]=Tvar[k];
1.242 brouard 11391: 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 11392: 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 */
11393: 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 11394: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
11395: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
1.342 brouard 11396: /* 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); */
11397: /* printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv); */
1.227 brouard 11398: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 11399: ncova++;
11400: TvarA[ncova]=Tvar[k];
11401: TvarAind[ncova]=k;
1.231 brouard 11402: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 11403: Fixed[k]= 2;
11404: Dummy[k]= 2;
11405: modell[k].maintype= ATYPE;
11406: modell[k].subtype= APFD;
11407: /* ncoveff++; */
1.227 brouard 11408: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 11409: Fixed[k]= 2;
11410: Dummy[k]= 3;
11411: modell[k].maintype= ATYPE;
11412: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
11413: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 11414: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 11415: Fixed[k]= 3;
11416: Dummy[k]= 2;
11417: modell[k].maintype= ATYPE;
11418: modell[k].subtype= APVD; /* Product age * varying dummy */
11419: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 11420: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 11421: Fixed[k]= 3;
11422: Dummy[k]= 3;
11423: modell[k].maintype= ATYPE;
11424: modell[k].subtype= APVQ; /* Product age * varying quantitative */
11425: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 11426: }
1.339 brouard 11427: }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 */
11428: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11429: /* model V1+V3+age*V1+age*V3+V1*V3 */
11430: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11431: 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 */
11432: ncovvt++;
11433: TvarVV[ncovvt]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */
11434: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
11435: ncovvt++;
11436: TvarVV[ncovvt]=Tvard[k1][2]; /* TvarVV[3]=V3 */
11437: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
11438:
11439:
11440: if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */
11441: if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */
1.240 brouard 11442: Fixed[k]= 1;
11443: Dummy[k]= 0;
11444: modell[k].maintype= FTYPE;
11445: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
11446: ncovf++; /* Fixed variables without age */
11447: TvarF[ncovf]=Tvar[k];
11448: TvarFind[ncovf]=k;
1.339 brouard 11449: }else if(Tvard[k1][2] <=ncovcol+nqv){ /* Vm is quanti fixed */
11450: Fixed[k]= 0; /* Fixed product */
1.240 brouard 11451: Dummy[k]= 1;
11452: modell[k].maintype= FTYPE;
11453: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
11454: ncovf++; /* Varying variables without age */
11455: TvarF[ncovf]=Tvar[k];
11456: TvarFind[ncovf]=k;
1.339 brouard 11457: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is a time varying dummy covariate */
1.240 brouard 11458: Fixed[k]= 1;
11459: Dummy[k]= 0;
11460: modell[k].maintype= VTYPE;
11461: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
11462: ncovv++; /* Varying variables without age */
1.339 brouard 11463: TvarV[ncovv]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */
11464: TvarVind[ncovv]=k;/* TvarVind[1]=5 */
11465: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */
1.240 brouard 11466: Fixed[k]= 1;
11467: Dummy[k]= 1;
11468: modell[k].maintype= VTYPE;
11469: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
11470: ncovv++; /* Varying variables without age */
11471: TvarV[ncovv]=Tvar[k];
11472: TvarVind[ncovv]=k;
11473: }
1.339 brouard 11474: }else if(Tvard[k1][1] <=ncovcol+nqv){ /* Vn is fixed quanti */
11475: if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */
11476: Fixed[k]= 0; /* Fixed product */
1.240 brouard 11477: Dummy[k]= 1;
11478: modell[k].maintype= FTYPE;
11479: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
11480: ncovf++; /* Fixed variables without age */
11481: TvarF[ncovf]=Tvar[k];
11482: TvarFind[ncovf]=k;
1.339 brouard 11483: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is time varying */
1.240 brouard 11484: Fixed[k]= 1;
11485: Dummy[k]= 1;
11486: modell[k].maintype= VTYPE;
11487: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
11488: ncovv++; /* Varying variables without age */
11489: TvarV[ncovv]=Tvar[k];
11490: TvarVind[ncovv]=k;
1.339 brouard 11491: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is time varying quanti */
1.240 brouard 11492: Fixed[k]= 1;
11493: Dummy[k]= 1;
11494: modell[k].maintype= VTYPE;
11495: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
11496: ncovv++; /* Varying variables without age */
11497: TvarV[ncovv]=Tvar[k];
11498: TvarVind[ncovv]=k;
11499: ncovv++; /* Varying variables without age */
11500: TvarV[ncovv]=Tvar[k];
11501: TvarVind[ncovv]=k;
11502: }
1.339 brouard 11503: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ /* Vn is time varying dummy */
1.240 brouard 11504: if(Tvard[k1][2] <=ncovcol){
11505: Fixed[k]= 1;
11506: Dummy[k]= 1;
11507: modell[k].maintype= VTYPE;
11508: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
11509: ncovv++; /* Varying variables without age */
11510: TvarV[ncovv]=Tvar[k];
11511: TvarVind[ncovv]=k;
11512: }else if(Tvard[k1][2] <=ncovcol+nqv){
11513: Fixed[k]= 1;
11514: Dummy[k]= 1;
11515: modell[k].maintype= VTYPE;
11516: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
11517: ncovv++; /* Varying variables without age */
11518: TvarV[ncovv]=Tvar[k];
11519: TvarVind[ncovv]=k;
11520: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
11521: Fixed[k]= 1;
11522: Dummy[k]= 0;
11523: modell[k].maintype= VTYPE;
11524: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
11525: ncovv++; /* Varying variables without age */
11526: TvarV[ncovv]=Tvar[k];
11527: TvarVind[ncovv]=k;
11528: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
11529: Fixed[k]= 1;
11530: Dummy[k]= 1;
11531: modell[k].maintype= VTYPE;
11532: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
11533: ncovv++; /* Varying variables without age */
11534: TvarV[ncovv]=Tvar[k];
11535: TvarVind[ncovv]=k;
11536: }
1.339 brouard 11537: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ /* Vn is time varying quanti */
1.240 brouard 11538: if(Tvard[k1][2] <=ncovcol){
11539: Fixed[k]= 1;
11540: Dummy[k]= 1;
11541: modell[k].maintype= VTYPE;
11542: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
11543: ncovv++; /* Varying variables without age */
11544: TvarV[ncovv]=Tvar[k];
11545: TvarVind[ncovv]=k;
11546: }else if(Tvard[k1][2] <=ncovcol+nqv){
11547: Fixed[k]= 1;
11548: Dummy[k]= 1;
11549: modell[k].maintype= VTYPE;
11550: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
11551: ncovv++; /* Varying variables without age */
11552: TvarV[ncovv]=Tvar[k];
11553: TvarVind[ncovv]=k;
11554: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
11555: Fixed[k]= 1;
11556: Dummy[k]= 1;
11557: modell[k].maintype= VTYPE;
11558: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
11559: ncovv++; /* Varying variables without age */
11560: TvarV[ncovv]=Tvar[k];
11561: TvarVind[ncovv]=k;
11562: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
11563: Fixed[k]= 1;
11564: Dummy[k]= 1;
11565: modell[k].maintype= VTYPE;
11566: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
11567: ncovv++; /* Varying variables without age */
11568: TvarV[ncovv]=Tvar[k];
11569: TvarVind[ncovv]=k;
11570: }
1.227 brouard 11571: }else{
1.240 brouard 11572: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
11573: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
11574: } /*end k1*/
1.225 brouard 11575: }else{
1.226 brouard 11576: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
11577: 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 11578: }
1.342 brouard 11579: /* 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]); */
11580: /* printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype); */
1.227 brouard 11581: 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]);
11582: }
11583: /* Searching for doublons in the model */
11584: for(k1=1; k1<= cptcovt;k1++){
11585: for(k2=1; k2 <k1;k2++){
1.285 brouard 11586: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
11587: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 11588: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
11589: if(Tvar[k1]==Tvar[k2]){
1.338 brouard 11590: 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]);
11591: 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 11592: return(1);
11593: }
11594: }else if (Typevar[k1] ==2){
11595: k3=Tposprod[k1];
11596: k4=Tposprod[k2];
11597: 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 11598: 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]]);
11599: 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 11600: return(1);
11601: }
11602: }
1.227 brouard 11603: }
11604: }
1.225 brouard 11605: }
11606: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
11607: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 11608: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
11609: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 11610: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 11611: /*endread:*/
1.225 brouard 11612: printf("Exiting decodemodel: ");
11613: return (1);
1.136 brouard 11614: }
11615:
1.169 brouard 11616: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 11617: {/* Check ages at death */
1.136 brouard 11618: int i, m;
1.218 brouard 11619: int firstone=0;
11620:
1.136 brouard 11621: for (i=1; i<=imx; i++) {
11622: for(m=2; (m<= maxwav); m++) {
11623: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
11624: anint[m][i]=9999;
1.216 brouard 11625: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
11626: s[m][i]=-1;
1.136 brouard 11627: }
11628: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 11629: *nberr = *nberr + 1;
1.218 brouard 11630: if(firstone == 0){
11631: firstone=1;
1.260 brouard 11632: 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 11633: }
1.262 brouard 11634: 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 11635: s[m][i]=-1; /* Droping the death status */
1.136 brouard 11636: }
11637: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 11638: (*nberr)++;
1.259 brouard 11639: 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 11640: 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 11641: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 11642: }
11643: }
11644: }
11645:
11646: for (i=1; i<=imx; i++) {
11647: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
11648: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 11649: 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 11650: if (s[m][i] >= nlstate+1) {
1.169 brouard 11651: if(agedc[i]>0){
11652: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 11653: agev[m][i]=agedc[i];
1.214 brouard 11654: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 11655: }else {
1.136 brouard 11656: if ((int)andc[i]!=9999){
11657: nbwarn++;
11658: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
11659: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
11660: agev[m][i]=-1;
11661: }
11662: }
1.169 brouard 11663: } /* agedc > 0 */
1.214 brouard 11664: } /* end if */
1.136 brouard 11665: else if(s[m][i] !=9){ /* Standard case, age in fractional
11666: years but with the precision of a month */
11667: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
11668: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
11669: agev[m][i]=1;
11670: else if(agev[m][i] < *agemin){
11671: *agemin=agev[m][i];
11672: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
11673: }
11674: else if(agev[m][i] >*agemax){
11675: *agemax=agev[m][i];
1.156 brouard 11676: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 11677: }
11678: /*agev[m][i]=anint[m][i]-annais[i];*/
11679: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 11680: } /* en if 9*/
1.136 brouard 11681: else { /* =9 */
1.214 brouard 11682: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 11683: agev[m][i]=1;
11684: s[m][i]=-1;
11685: }
11686: }
1.214 brouard 11687: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 11688: agev[m][i]=1;
1.214 brouard 11689: else{
11690: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
11691: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
11692: agev[m][i]=0;
11693: }
11694: } /* End for lastpass */
11695: }
1.136 brouard 11696:
11697: for (i=1; i<=imx; i++) {
11698: for(m=firstpass; (m<=lastpass); m++){
11699: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 11700: (*nberr)++;
1.136 brouard 11701: 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);
11702: 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);
11703: return 1;
11704: }
11705: }
11706: }
11707:
11708: /*for (i=1; i<=imx; i++){
11709: for (m=firstpass; (m<lastpass); m++){
11710: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
11711: }
11712:
11713: }*/
11714:
11715:
1.139 brouard 11716: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
11717: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 11718:
11719: return (0);
1.164 brouard 11720: /* endread:*/
1.136 brouard 11721: printf("Exiting calandcheckages: ");
11722: return (1);
11723: }
11724:
1.172 brouard 11725: #if defined(_MSC_VER)
11726: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
11727: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
11728: //#include "stdafx.h"
11729: //#include <stdio.h>
11730: //#include <tchar.h>
11731: //#include <windows.h>
11732: //#include <iostream>
11733: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
11734:
11735: LPFN_ISWOW64PROCESS fnIsWow64Process;
11736:
11737: BOOL IsWow64()
11738: {
11739: BOOL bIsWow64 = FALSE;
11740:
11741: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
11742: // (HANDLE, PBOOL);
11743:
11744: //LPFN_ISWOW64PROCESS fnIsWow64Process;
11745:
11746: HMODULE module = GetModuleHandle(_T("kernel32"));
11747: const char funcName[] = "IsWow64Process";
11748: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
11749: GetProcAddress(module, funcName);
11750:
11751: if (NULL != fnIsWow64Process)
11752: {
11753: if (!fnIsWow64Process(GetCurrentProcess(),
11754: &bIsWow64))
11755: //throw std::exception("Unknown error");
11756: printf("Unknown error\n");
11757: }
11758: return bIsWow64 != FALSE;
11759: }
11760: #endif
1.177 brouard 11761:
1.191 brouard 11762: void syscompilerinfo(int logged)
1.292 brouard 11763: {
11764: #include <stdint.h>
11765:
11766: /* #include "syscompilerinfo.h"*/
1.185 brouard 11767: /* command line Intel compiler 32bit windows, XP compatible:*/
11768: /* /GS /W3 /Gy
11769: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
11770: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
11771: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 11772: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
11773: */
11774: /* 64 bits */
1.185 brouard 11775: /*
11776: /GS /W3 /Gy
11777: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
11778: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
11779: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
11780: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
11781: /* Optimization are useless and O3 is slower than O2 */
11782: /*
11783: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
11784: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
11785: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
11786: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
11787: */
1.186 brouard 11788: /* Link is */ /* /OUT:"visual studio
1.185 brouard 11789: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
11790: /PDB:"visual studio
11791: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
11792: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
11793: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
11794: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
11795: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
11796: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
11797: uiAccess='false'"
11798: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
11799: /NOLOGO /TLBID:1
11800: */
1.292 brouard 11801:
11802:
1.177 brouard 11803: #if defined __INTEL_COMPILER
1.178 brouard 11804: #if defined(__GNUC__)
11805: struct utsname sysInfo; /* For Intel on Linux and OS/X */
11806: #endif
1.177 brouard 11807: #elif defined(__GNUC__)
1.179 brouard 11808: #ifndef __APPLE__
1.174 brouard 11809: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 11810: #endif
1.177 brouard 11811: struct utsname sysInfo;
1.178 brouard 11812: int cross = CROSS;
11813: if (cross){
11814: printf("Cross-");
1.191 brouard 11815: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 11816: }
1.174 brouard 11817: #endif
11818:
1.191 brouard 11819: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 11820: #if defined(__clang__)
1.191 brouard 11821: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 11822: #endif
11823: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 11824: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 11825: #endif
11826: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 11827: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 11828: #endif
11829: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 11830: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 11831: #endif
11832: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 11833: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 11834: #endif
11835: #if defined(_MSC_VER)
1.191 brouard 11836: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 11837: #endif
11838: #if defined(__PGI)
1.191 brouard 11839: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 11840: #endif
11841: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 11842: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 11843: #endif
1.191 brouard 11844: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 11845:
1.167 brouard 11846: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
11847: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
11848: // Windows (x64 and x86)
1.191 brouard 11849: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 11850: #elif __unix__ // all unices, not all compilers
11851: // Unix
1.191 brouard 11852: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 11853: #elif __linux__
11854: // linux
1.191 brouard 11855: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 11856: #elif __APPLE__
1.174 brouard 11857: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 11858: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 11859: #endif
11860:
11861: /* __MINGW32__ */
11862: /* __CYGWIN__ */
11863: /* __MINGW64__ */
11864: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
11865: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
11866: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
11867: /* _WIN64 // Defined for applications for Win64. */
11868: /* _M_X64 // Defined for compilations that target x64 processors. */
11869: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 11870:
1.167 brouard 11871: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 11872: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 11873: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 11874: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 11875: #else
1.191 brouard 11876: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 11877: #endif
11878:
1.169 brouard 11879: #if defined(__GNUC__)
11880: # if defined(__GNUC_PATCHLEVEL__)
11881: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
11882: + __GNUC_MINOR__ * 100 \
11883: + __GNUC_PATCHLEVEL__)
11884: # else
11885: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
11886: + __GNUC_MINOR__ * 100)
11887: # endif
1.174 brouard 11888: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 11889: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 11890:
11891: if (uname(&sysInfo) != -1) {
11892: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 11893: 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 11894: }
11895: else
11896: perror("uname() error");
1.179 brouard 11897: //#ifndef __INTEL_COMPILER
11898: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 11899: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 11900: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 11901: #endif
1.169 brouard 11902: #endif
1.172 brouard 11903:
1.286 brouard 11904: // void main ()
1.172 brouard 11905: // {
1.169 brouard 11906: #if defined(_MSC_VER)
1.174 brouard 11907: if (IsWow64()){
1.191 brouard 11908: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
11909: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 11910: }
11911: else{
1.191 brouard 11912: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
11913: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 11914: }
1.172 brouard 11915: // printf("\nPress Enter to continue...");
11916: // getchar();
11917: // }
11918:
1.169 brouard 11919: #endif
11920:
1.167 brouard 11921:
1.219 brouard 11922: }
1.136 brouard 11923:
1.219 brouard 11924: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 11925: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.332 brouard 11926: /* Computes the prevalence limit for each combination of the dummy covariates */
1.235 brouard 11927: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 11928: /* double ftolpl = 1.e-10; */
1.180 brouard 11929: double age, agebase, agelim;
1.203 brouard 11930: double tot;
1.180 brouard 11931:
1.202 brouard 11932: strcpy(filerespl,"PL_");
11933: strcat(filerespl,fileresu);
11934: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 11935: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
11936: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 11937: }
1.288 brouard 11938: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
11939: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 11940: pstamp(ficrespl);
1.288 brouard 11941: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 11942: fprintf(ficrespl,"#Age ");
11943: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
11944: fprintf(ficrespl,"\n");
1.180 brouard 11945:
1.219 brouard 11946: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 11947:
1.219 brouard 11948: agebase=ageminpar;
11949: agelim=agemaxpar;
1.180 brouard 11950:
1.227 brouard 11951: /* i1=pow(2,ncoveff); */
1.234 brouard 11952: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 11953: if (cptcovn < 1){i1=1;}
1.180 brouard 11954:
1.337 brouard 11955: /* for(k=1; k<=i1;k++){ /\* For each combination k of dummy covariates in the model *\/ */
1.238 brouard 11956: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 11957: k=TKresult[nres];
1.338 brouard 11958: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 11959: /* if(i1 != 1 && TKresult[nres]!= k) /\* We found the combination k corresponding to the resultline value of dummies *\/ */
11960: /* continue; */
1.235 brouard 11961:
1.238 brouard 11962: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
11963: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
11964: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
11965: /* k=k+1; */
11966: /* to clean */
1.332 brouard 11967: /*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*/
1.238 brouard 11968: fprintf(ficrespl,"#******");
11969: printf("#******");
11970: fprintf(ficlog,"#******");
1.337 brouard 11971: 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 11972: /* fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Here problem for varying dummy*\/ */
1.337 brouard 11973: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11974: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11975: fprintf(ficrespl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11976: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11977: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11978: }
11979: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
11980: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
11981: /* fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
11982: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
11983: /* } */
1.238 brouard 11984: fprintf(ficrespl,"******\n");
11985: printf("******\n");
11986: fprintf(ficlog,"******\n");
11987: if(invalidvarcomb[k]){
11988: printf("\nCombination (%d) ignored because no case \n",k);
11989: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
11990: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
11991: continue;
11992: }
1.219 brouard 11993:
1.238 brouard 11994: fprintf(ficrespl,"#Age ");
1.337 brouard 11995: /* for(j=1;j<=cptcoveff;j++) { */
11996: /* fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11997: /* } */
11998: for(j=1;j<=cptcovs;j++) { /* New the quanti variable is added */
11999: fprintf(ficrespl,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12000: }
12001: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
12002: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 12003:
1.238 brouard 12004: for (age=agebase; age<=agelim; age++){
12005: /* for (age=agebase; age<=agebase; age++){ */
1.337 brouard 12006: /**< Computes the prevalence limit in each live state at age x and for covariate combination (k and) nres */
12007: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres); /* Nicely done */
1.238 brouard 12008: fprintf(ficrespl,"%.0f ",age );
1.337 brouard 12009: /* for(j=1;j<=cptcoveff;j++) */
12010: /* fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12011: for(j=1;j<=cptcovs;j++)
12012: fprintf(ficrespl,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12013: tot=0.;
12014: for(i=1; i<=nlstate;i++){
12015: tot += prlim[i][i];
12016: fprintf(ficrespl," %.5f", prlim[i][i]);
12017: }
12018: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
12019: } /* Age */
12020: /* was end of cptcod */
1.337 brouard 12021: } /* nres */
12022: /* } /\* for each combination *\/ */
1.219 brouard 12023: return 0;
1.180 brouard 12024: }
12025:
1.218 brouard 12026: 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 12027: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 12028:
12029: /* Computes the back prevalence limit for any combination of covariate values
12030: * at any age between ageminpar and agemaxpar
12031: */
1.235 brouard 12032: int i, j, k, i1, nres=0 ;
1.217 brouard 12033: /* double ftolpl = 1.e-10; */
12034: double age, agebase, agelim;
12035: double tot;
1.218 brouard 12036: /* double ***mobaverage; */
12037: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 12038:
12039: strcpy(fileresplb,"PLB_");
12040: strcat(fileresplb,fileresu);
12041: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 12042: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
12043: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 12044: }
1.288 brouard 12045: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
12046: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 12047: pstamp(ficresplb);
1.288 brouard 12048: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 12049: fprintf(ficresplb,"#Age ");
12050: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
12051: fprintf(ficresplb,"\n");
12052:
1.218 brouard 12053:
12054: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
12055:
12056: agebase=ageminpar;
12057: agelim=agemaxpar;
12058:
12059:
1.227 brouard 12060: i1=pow(2,cptcoveff);
1.218 brouard 12061: if (cptcovn < 1){i1=1;}
1.227 brouard 12062:
1.238 brouard 12063: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.338 brouard 12064: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
12065: k=TKresult[nres];
12066: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
12067: /* if(i1 != 1 && TKresult[nres]!= k) */
12068: /* continue; */
12069: /* /\*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*\/ */
1.238 brouard 12070: fprintf(ficresplb,"#******");
12071: printf("#******");
12072: fprintf(ficlog,"#******");
1.338 brouard 12073: 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) */
12074: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12075: fprintf(ficresplb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12076: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12077: }
1.338 brouard 12078: /* for(j=1;j<=cptcoveff ;j++) {/\* all covariates *\/ */
12079: /* fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12080: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12081: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12082: /* } */
12083: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
12084: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12085: /* fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12086: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12087: /* } */
1.238 brouard 12088: fprintf(ficresplb,"******\n");
12089: printf("******\n");
12090: fprintf(ficlog,"******\n");
12091: if(invalidvarcomb[k]){
12092: printf("\nCombination (%d) ignored because no cases \n",k);
12093: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
12094: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
12095: continue;
12096: }
1.218 brouard 12097:
1.238 brouard 12098: fprintf(ficresplb,"#Age ");
1.338 brouard 12099: for(j=1;j<=cptcovs;j++) {
12100: fprintf(ficresplb,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12101: }
12102: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
12103: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 12104:
12105:
1.238 brouard 12106: for (age=agebase; age<=agelim; age++){
12107: /* for (age=agebase; age<=agebase; age++){ */
12108: if(mobilavproj > 0){
12109: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
12110: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 12111: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 12112: }else if (mobilavproj == 0){
12113: 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);
12114: 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);
12115: exit(1);
12116: }else{
12117: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 12118: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 12119: /* printf("TOTOT\n"); */
12120: /* exit(1); */
1.238 brouard 12121: }
12122: fprintf(ficresplb,"%.0f ",age );
1.338 brouard 12123: for(j=1;j<=cptcovs;j++)
12124: fprintf(ficresplb,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12125: tot=0.;
12126: for(i=1; i<=nlstate;i++){
12127: tot += bprlim[i][i];
12128: fprintf(ficresplb," %.5f", bprlim[i][i]);
12129: }
12130: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
12131: } /* Age */
12132: /* was end of cptcod */
1.255 brouard 12133: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.338 brouard 12134: /* } /\* end of any combination *\/ */
1.238 brouard 12135: } /* end of nres */
1.218 brouard 12136: /* hBijx(p, bage, fage); */
12137: /* fclose(ficrespijb); */
12138:
12139: return 0;
1.217 brouard 12140: }
1.218 brouard 12141:
1.180 brouard 12142: int hPijx(double *p, int bage, int fage){
12143: /*------------- h Pij x at various ages ------------*/
1.336 brouard 12144: /* to be optimized with precov */
1.180 brouard 12145: int stepsize;
12146: int agelim;
12147: int hstepm;
12148: int nhstepm;
1.235 brouard 12149: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 12150:
12151: double agedeb;
12152: double ***p3mat;
12153:
1.337 brouard 12154: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
12155: if((ficrespij=fopen(filerespij,"w"))==NULL) {
12156: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
12157: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
12158: }
12159: printf("Computing pij: result on file '%s' \n", filerespij);
12160: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
12161:
12162: stepsize=(int) (stepm+YEARM-1)/YEARM;
12163: /*if (stepm<=24) stepsize=2;*/
12164:
12165: agelim=AGESUP;
12166: hstepm=stepsize*YEARM; /* Every year of age */
12167: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
12168:
12169: /* hstepm=1; aff par mois*/
12170: pstamp(ficrespij);
12171: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
12172: i1= pow(2,cptcoveff);
12173: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12174: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
12175: /* k=k+1; */
12176: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
12177: k=TKresult[nres];
1.338 brouard 12178: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12179: /* for(k=1; k<=i1;k++){ */
12180: /* if(i1 != 1 && TKresult[nres]!= k) */
12181: /* continue; */
12182: fprintf(ficrespij,"\n#****** ");
12183: for(j=1;j<=cptcovs;j++){
12184: fprintf(ficrespij," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12185: /* fprintf(ficrespij,"@wV%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12186: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
12187: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12188: /* fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12189: }
12190: fprintf(ficrespij,"******\n");
12191:
12192: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
12193: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
12194: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
12195:
12196: /* nhstepm=nhstepm*YEARM; aff par mois*/
12197:
12198: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12199: oldm=oldms;savm=savms;
12200: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
12201: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
12202: for(i=1; i<=nlstate;i++)
12203: for(j=1; j<=nlstate+ndeath;j++)
12204: fprintf(ficrespij," %1d-%1d",i,j);
12205: fprintf(ficrespij,"\n");
12206: for (h=0; h<=nhstepm; h++){
12207: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
12208: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.183 brouard 12209: for(i=1; i<=nlstate;i++)
12210: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 12211: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.183 brouard 12212: fprintf(ficrespij,"\n");
12213: }
1.337 brouard 12214: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12215: fprintf(ficrespij,"\n");
1.180 brouard 12216: }
1.337 brouard 12217: }
12218: /*}*/
12219: return 0;
1.180 brouard 12220: }
1.218 brouard 12221:
12222: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 12223: /*------------- h Bij x at various ages ------------*/
1.336 brouard 12224: /* To be optimized with precov */
1.217 brouard 12225: int stepsize;
1.218 brouard 12226: /* int agelim; */
12227: int ageminl;
1.217 brouard 12228: int hstepm;
12229: int nhstepm;
1.238 brouard 12230: int h, i, i1, j, k, nres;
1.218 brouard 12231:
1.217 brouard 12232: double agedeb;
12233: double ***p3mat;
1.218 brouard 12234:
12235: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
12236: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
12237: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
12238: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
12239: }
12240: printf("Computing pij back: result on file '%s' \n", filerespijb);
12241: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
12242:
12243: stepsize=(int) (stepm+YEARM-1)/YEARM;
12244: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 12245:
1.218 brouard 12246: /* agelim=AGESUP; */
1.289 brouard 12247: ageminl=AGEINF; /* was 30 */
1.218 brouard 12248: hstepm=stepsize*YEARM; /* Every year of age */
12249: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
12250:
12251: /* hstepm=1; aff par mois*/
12252: pstamp(ficrespijb);
1.255 brouard 12253: 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 12254: i1= pow(2,cptcoveff);
1.218 brouard 12255: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12256: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
12257: /* k=k+1; */
1.238 brouard 12258: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 12259: k=TKresult[nres];
1.338 brouard 12260: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12261: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
12262: /* if(i1 != 1 && TKresult[nres]!= k) */
12263: /* continue; */
12264: fprintf(ficrespijb,"\n#****** ");
12265: for(j=1;j<=cptcovs;j++){
1.338 brouard 12266: fprintf(ficrespijb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.337 brouard 12267: /* for(j=1;j<=cptcoveff;j++) */
12268: /* fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12269: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
12270: /* fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12271: }
12272: fprintf(ficrespijb,"******\n");
12273: if(invalidvarcomb[k]){ /* Is it necessary here? */
12274: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
12275: continue;
12276: }
12277:
12278: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
12279: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
12280: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
12281: 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 */
12282: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 or 28*/
12283:
12284: /* nhstepm=nhstepm*YEARM; aff par mois*/
12285:
12286: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
12287: /* and memory limitations if stepm is small */
12288:
12289: /* oldm=oldms;savm=savms; */
12290: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
12291: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);/* Bug valgrind */
12292: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
12293: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
12294: for(i=1; i<=nlstate;i++)
12295: for(j=1; j<=nlstate+ndeath;j++)
12296: fprintf(ficrespijb," %1d-%1d",i,j);
12297: fprintf(ficrespijb,"\n");
12298: for (h=0; h<=nhstepm; h++){
12299: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
12300: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
12301: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
1.217 brouard 12302: for(i=1; i<=nlstate;i++)
12303: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 12304: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);/* Bug valgrind */
1.217 brouard 12305: fprintf(ficrespijb,"\n");
1.337 brouard 12306: }
12307: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12308: fprintf(ficrespijb,"\n");
12309: } /* end age deb */
12310: /* } /\* end combination *\/ */
1.238 brouard 12311: } /* end nres */
1.218 brouard 12312: return 0;
12313: } /* hBijx */
1.217 brouard 12314:
1.180 brouard 12315:
1.136 brouard 12316: /***********************************************/
12317: /**************** Main Program *****************/
12318: /***********************************************/
12319:
12320: int main(int argc, char *argv[])
12321: {
12322: #ifdef GSL
12323: const gsl_multimin_fminimizer_type *T;
12324: size_t iteri = 0, it;
12325: int rval = GSL_CONTINUE;
12326: int status = GSL_SUCCESS;
12327: double ssval;
12328: #endif
12329: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 12330: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
12331: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 12332: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 12333: int jj, ll, li, lj, lk;
1.136 brouard 12334: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 12335: int num_filled;
1.136 brouard 12336: int itimes;
12337: int NDIM=2;
12338: int vpopbased=0;
1.235 brouard 12339: int nres=0;
1.258 brouard 12340: int endishere=0;
1.277 brouard 12341: int noffset=0;
1.274 brouard 12342: int ncurrv=0; /* Temporary variable */
12343:
1.164 brouard 12344: char ca[32], cb[32];
1.136 brouard 12345: /* FILE *fichtm; *//* Html File */
12346: /* FILE *ficgp;*/ /*Gnuplot File */
12347: struct stat info;
1.191 brouard 12348: double agedeb=0.;
1.194 brouard 12349:
12350: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 12351: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 12352:
1.165 brouard 12353: double fret;
1.191 brouard 12354: double dum=0.; /* Dummy variable */
1.136 brouard 12355: double ***p3mat;
1.218 brouard 12356: /* double ***mobaverage; */
1.319 brouard 12357: double wald;
1.164 brouard 12358:
12359: char line[MAXLINE];
1.197 brouard 12360: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
12361:
1.234 brouard 12362: char modeltemp[MAXLINE];
1.332 brouard 12363: char resultline[MAXLINE], resultlineori[MAXLINE];
1.230 brouard 12364:
1.136 brouard 12365: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 12366: char *tok, *val; /* pathtot */
1.334 brouard 12367: /* int firstobs=1, lastobs=10; /\* nobs = lastobs-firstobs declared globally ;*\/ */
1.195 brouard 12368: int c, h , cpt, c2;
1.191 brouard 12369: int jl=0;
12370: int i1, j1, jk, stepsize=0;
1.194 brouard 12371: int count=0;
12372:
1.164 brouard 12373: int *tab;
1.136 brouard 12374: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.296 brouard 12375: /* double anprojd, mprojd, jprojd; /\* For eventual projections *\/ */
12376: /* double anprojf, mprojf, jprojf; */
12377: /* double jintmean,mintmean,aintmean; */
12378: int prvforecast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
12379: int prvbackcast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
12380: double yrfproj= 10.0; /* Number of years of forward projections */
12381: double yrbproj= 10.0; /* Number of years of backward projections */
12382: int prevbcast=0; /* defined as global for mlikeli and mle, replacing backcast */
1.136 brouard 12383: int mobilav=0,popforecast=0;
1.191 brouard 12384: int hstepm=0, nhstepm=0;
1.136 brouard 12385: int agemortsup;
12386: float sumlpop=0.;
12387: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
12388: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
12389:
1.191 brouard 12390: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 12391: double ftolpl=FTOL;
12392: double **prlim;
1.217 brouard 12393: double **bprlim;
1.317 brouard 12394: double ***param; /* Matrix of parameters, param[i][j][k] param=ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel)
12395: state of origin, state of destination including death, for each covariate: constante, age, and V1 V2 etc. */
1.251 brouard 12396: double ***paramstart; /* Matrix of starting parameter values */
12397: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 12398: double **matcov; /* Matrix of covariance */
1.203 brouard 12399: double **hess; /* Hessian matrix */
1.136 brouard 12400: double ***delti3; /* Scale */
12401: double *delti; /* Scale */
12402: double ***eij, ***vareij;
12403: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 12404:
1.136 brouard 12405: double *epj, vepp;
1.164 brouard 12406:
1.273 brouard 12407: double dateprev1, dateprev2;
1.296 brouard 12408: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0, dateprojd=0, dateprojf=0;
12409: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0, datebackd=0, datebackf=0;
12410:
1.217 brouard 12411:
1.136 brouard 12412: double **ximort;
1.145 brouard 12413: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 12414: int *dcwave;
12415:
1.164 brouard 12416: char z[1]="c";
1.136 brouard 12417:
12418: /*char *strt;*/
12419: char strtend[80];
1.126 brouard 12420:
1.164 brouard 12421:
1.126 brouard 12422: /* setlocale (LC_ALL, ""); */
12423: /* bindtextdomain (PACKAGE, LOCALEDIR); */
12424: /* textdomain (PACKAGE); */
12425: /* setlocale (LC_CTYPE, ""); */
12426: /* setlocale (LC_MESSAGES, ""); */
12427:
12428: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 12429: rstart_time = time(NULL);
12430: /* (void) gettimeofday(&start_time,&tzp);*/
12431: start_time = *localtime(&rstart_time);
1.126 brouard 12432: curr_time=start_time;
1.157 brouard 12433: /*tml = *localtime(&start_time.tm_sec);*/
12434: /* strcpy(strstart,asctime(&tml)); */
12435: strcpy(strstart,asctime(&start_time));
1.126 brouard 12436:
12437: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 12438: /* tp.tm_sec = tp.tm_sec +86400; */
12439: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 12440: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
12441: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
12442: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 12443: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 12444: /* strt=asctime(&tmg); */
12445: /* printf("Time(after) =%s",strstart); */
12446: /* (void) time (&time_value);
12447: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
12448: * tm = *localtime(&time_value);
12449: * strstart=asctime(&tm);
12450: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
12451: */
12452:
12453: nberr=0; /* Number of errors and warnings */
12454: nbwarn=0;
1.184 brouard 12455: #ifdef WIN32
12456: _getcwd(pathcd, size);
12457: #else
1.126 brouard 12458: getcwd(pathcd, size);
1.184 brouard 12459: #endif
1.191 brouard 12460: syscompilerinfo(0);
1.196 brouard 12461: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 12462: if(argc <=1){
12463: printf("\nEnter the parameter file name: ");
1.205 brouard 12464: if(!fgets(pathr,FILENAMELENGTH,stdin)){
12465: printf("ERROR Empty parameter file name\n");
12466: goto end;
12467: }
1.126 brouard 12468: i=strlen(pathr);
12469: if(pathr[i-1]=='\n')
12470: pathr[i-1]='\0';
1.156 brouard 12471: i=strlen(pathr);
1.205 brouard 12472: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 12473: pathr[i-1]='\0';
1.205 brouard 12474: }
12475: i=strlen(pathr);
12476: if( i==0 ){
12477: printf("ERROR Empty parameter file name\n");
12478: goto end;
12479: }
12480: for (tok = pathr; tok != NULL; ){
1.126 brouard 12481: printf("Pathr |%s|\n",pathr);
12482: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
12483: printf("val= |%s| pathr=%s\n",val,pathr);
12484: strcpy (pathtot, val);
12485: if(pathr[0] == '\0') break; /* Dirty */
12486: }
12487: }
1.281 brouard 12488: else if (argc<=2){
12489: strcpy(pathtot,argv[1]);
12490: }
1.126 brouard 12491: else{
12492: strcpy(pathtot,argv[1]);
1.281 brouard 12493: strcpy(z,argv[2]);
12494: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 12495: }
12496: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
12497: /*cygwin_split_path(pathtot,path,optionfile);
12498: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
12499: /* cutv(path,optionfile,pathtot,'\\');*/
12500:
12501: /* Split argv[0], imach program to get pathimach */
12502: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
12503: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
12504: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
12505: /* strcpy(pathimach,argv[0]); */
12506: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
12507: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
12508: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 12509: #ifdef WIN32
12510: _chdir(path); /* Can be a relative path */
12511: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
12512: #else
1.126 brouard 12513: chdir(path); /* Can be a relative path */
1.184 brouard 12514: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
12515: #endif
12516: printf("Current directory %s!\n",pathcd);
1.126 brouard 12517: strcpy(command,"mkdir ");
12518: strcat(command,optionfilefiname);
12519: if((outcmd=system(command)) != 0){
1.169 brouard 12520: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 12521: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
12522: /* fclose(ficlog); */
12523: /* exit(1); */
12524: }
12525: /* if((imk=mkdir(optionfilefiname))<0){ */
12526: /* perror("mkdir"); */
12527: /* } */
12528:
12529: /*-------- arguments in the command line --------*/
12530:
1.186 brouard 12531: /* Main Log file */
1.126 brouard 12532: strcat(filelog, optionfilefiname);
12533: strcat(filelog,".log"); /* */
12534: if((ficlog=fopen(filelog,"w"))==NULL) {
12535: printf("Problem with logfile %s\n",filelog);
12536: goto end;
12537: }
12538: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 12539: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 12540: fprintf(ficlog,"\nEnter the parameter file name: \n");
12541: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
12542: path=%s \n\
12543: optionfile=%s\n\
12544: optionfilext=%s\n\
1.156 brouard 12545: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 12546:
1.197 brouard 12547: syscompilerinfo(1);
1.167 brouard 12548:
1.126 brouard 12549: printf("Local time (at start):%s",strstart);
12550: fprintf(ficlog,"Local time (at start): %s",strstart);
12551: fflush(ficlog);
12552: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 12553: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 12554:
12555: /* */
12556: strcpy(fileres,"r");
12557: strcat(fileres, optionfilefiname);
1.201 brouard 12558: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 12559: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 12560: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 12561:
1.186 brouard 12562: /* Main ---------arguments file --------*/
1.126 brouard 12563:
12564: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 12565: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
12566: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 12567: fflush(ficlog);
1.149 brouard 12568: /* goto end; */
12569: exit(70);
1.126 brouard 12570: }
12571:
12572: strcpy(filereso,"o");
1.201 brouard 12573: strcat(filereso,fileresu);
1.126 brouard 12574: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
12575: printf("Problem with Output resultfile: %s\n", filereso);
12576: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
12577: fflush(ficlog);
12578: goto end;
12579: }
1.278 brouard 12580: /*-------- Rewriting parameter file ----------*/
12581: strcpy(rfileres,"r"); /* "Rparameterfile */
12582: strcat(rfileres,optionfilefiname); /* Parameter file first name */
12583: strcat(rfileres,"."); /* */
12584: strcat(rfileres,optionfilext); /* Other files have txt extension */
12585: if((ficres =fopen(rfileres,"w"))==NULL) {
12586: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
12587: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
12588: fflush(ficlog);
12589: goto end;
12590: }
12591: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 12592:
1.278 brouard 12593:
1.126 brouard 12594: /* Reads comments: lines beginning with '#' */
12595: numlinepar=0;
1.277 brouard 12596: /* Is it a BOM UTF-8 Windows file? */
12597: /* First parameter line */
1.197 brouard 12598: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 12599: noffset=0;
12600: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
12601: {
12602: noffset=noffset+3;
12603: printf("# File is an UTF8 Bom.\n"); // 0xBF
12604: }
1.302 brouard 12605: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
12606: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
1.277 brouard 12607: {
12608: noffset=noffset+2;
12609: printf("# File is an UTF16BE BOM file\n");
12610: }
12611: else if( line[0] == 0 && line[1] == 0)
12612: {
12613: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
12614: noffset=noffset+4;
12615: printf("# File is an UTF16BE BOM file\n");
12616: }
12617: } else{
12618: ;/*printf(" Not a BOM file\n");*/
12619: }
12620:
1.197 brouard 12621: /* If line starts with a # it is a comment */
1.277 brouard 12622: if (line[noffset] == '#') {
1.197 brouard 12623: numlinepar++;
12624: fputs(line,stdout);
12625: fputs(line,ficparo);
1.278 brouard 12626: fputs(line,ficres);
1.197 brouard 12627: fputs(line,ficlog);
12628: continue;
12629: }else
12630: break;
12631: }
12632: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
12633: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
12634: if (num_filled != 5) {
12635: printf("Should be 5 parameters\n");
1.283 brouard 12636: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 12637: }
1.126 brouard 12638: numlinepar++;
1.197 brouard 12639: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 12640: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
12641: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
12642: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 12643: }
12644: /* Second parameter line */
12645: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 12646: /* while(fscanf(ficpar,"%[^\n]", line)) { */
12647: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 12648: if (line[0] == '#') {
12649: numlinepar++;
1.283 brouard 12650: printf("%s",line);
12651: fprintf(ficres,"%s",line);
12652: fprintf(ficparo,"%s",line);
12653: fprintf(ficlog,"%s",line);
1.197 brouard 12654: continue;
12655: }else
12656: break;
12657: }
1.223 brouard 12658: 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", \
12659: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
12660: if (num_filled != 11) {
12661: 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 12662: printf("but line=%s\n",line);
1.283 brouard 12663: 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");
12664: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 12665: }
1.286 brouard 12666: if( lastpass > maxwav){
12667: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
12668: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
12669: fflush(ficlog);
12670: goto end;
12671: }
12672: 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 12673: 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 12674: 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 12675: 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 12676: }
1.203 brouard 12677: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 12678: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 12679: /* Third parameter line */
12680: while(fgets(line, MAXLINE, ficpar)) {
12681: /* If line starts with a # it is a comment */
12682: if (line[0] == '#') {
12683: numlinepar++;
1.283 brouard 12684: printf("%s",line);
12685: fprintf(ficres,"%s",line);
12686: fprintf(ficparo,"%s",line);
12687: fprintf(ficlog,"%s",line);
1.197 brouard 12688: continue;
12689: }else
12690: break;
12691: }
1.201 brouard 12692: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.279 brouard 12693: if (num_filled != 1){
1.302 brouard 12694: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
12695: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
1.197 brouard 12696: model[0]='\0';
12697: goto end;
12698: }
12699: else{
12700: if (model[0]=='+'){
12701: for(i=1; i<=strlen(model);i++)
12702: modeltemp[i-1]=model[i];
1.201 brouard 12703: strcpy(model,modeltemp);
1.197 brouard 12704: }
12705: }
1.338 brouard 12706: /* printf(" model=1+age%s modeltemp= %s, model=1+age+%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 12707: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 12708: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
12709: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
12710: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 12711: }
12712: /* 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); */
12713: /* numlinepar=numlinepar+3; /\* In general *\/ */
12714: /* 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 12715: /* 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); */
12716: /* 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 12717: fflush(ficlog);
1.190 brouard 12718: /* if(model[0]=='#'|| model[0]== '\0'){ */
12719: if(model[0]=='#'){
1.279 brouard 12720: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
12721: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
12722: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 12723: if(mle != -1){
1.279 brouard 12724: 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 12725: exit(1);
12726: }
12727: }
1.126 brouard 12728: while((c=getc(ficpar))=='#' && c!= EOF){
12729: ungetc(c,ficpar);
12730: fgets(line, MAXLINE, ficpar);
12731: numlinepar++;
1.195 brouard 12732: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
12733: z[0]=line[1];
1.342 brouard 12734: }else if(line[1]=='d'){ /* For debugging individual values of covariates in ficresilk */
1.343 brouard 12735: debugILK=1;printf("DebugILK\n");
1.195 brouard 12736: }
12737: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 12738: fputs(line, stdout);
12739: //puts(line);
1.126 brouard 12740: fputs(line,ficparo);
12741: fputs(line,ficlog);
12742: }
12743: ungetc(c,ficpar);
12744:
12745:
1.290 brouard 12746: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
12747: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
12748: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
1.341 brouard 12749: /* if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /\**< Time varying covariate (dummy and quantitative)*\/ */
12750: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs); /**< Might be better */
1.136 brouard 12751: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
12752: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
12753: v1+v2*age+v2*v3 makes cptcovn = 3
12754: */
12755: if (strlen(model)>1)
1.187 brouard 12756: 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 12757: else
1.187 brouard 12758: ncovmodel=2; /* Constant and age */
1.133 brouard 12759: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
12760: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 12761: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
12762: 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);
12763: 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);
12764: fflush(stdout);
12765: fclose (ficlog);
12766: goto end;
12767: }
1.126 brouard 12768: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
12769: delti=delti3[1][1];
12770: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
12771: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 12772: /* We could also provide initial parameters values giving by simple logistic regression
12773: * only one way, that is without matrix product. We will have nlstate maximizations */
12774: /* for(i=1;i<nlstate;i++){ */
12775: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
12776: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
12777: /* } */
1.126 brouard 12778: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 12779: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
12780: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 12781: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12782: fclose (ficparo);
12783: fclose (ficlog);
12784: goto end;
12785: exit(0);
1.220 brouard 12786: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 12787: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 12788: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
12789: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 12790: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
12791: matcov=matrix(1,npar,1,npar);
1.203 brouard 12792: hess=matrix(1,npar,1,npar);
1.220 brouard 12793: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 12794: /* Read guessed parameters */
1.126 brouard 12795: /* Reads comments: lines beginning with '#' */
12796: while((c=getc(ficpar))=='#' && c!= EOF){
12797: ungetc(c,ficpar);
12798: fgets(line, MAXLINE, ficpar);
12799: numlinepar++;
1.141 brouard 12800: fputs(line,stdout);
1.126 brouard 12801: fputs(line,ficparo);
12802: fputs(line,ficlog);
12803: }
12804: ungetc(c,ficpar);
12805:
12806: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 12807: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 12808: for(i=1; i <=nlstate; i++){
1.234 brouard 12809: j=0;
1.126 brouard 12810: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 12811: if(jj==i) continue;
12812: j++;
1.292 brouard 12813: while((c=getc(ficpar))=='#' && c!= EOF){
12814: ungetc(c,ficpar);
12815: fgets(line, MAXLINE, ficpar);
12816: numlinepar++;
12817: fputs(line,stdout);
12818: fputs(line,ficparo);
12819: fputs(line,ficlog);
12820: }
12821: ungetc(c,ficpar);
1.234 brouard 12822: fscanf(ficpar,"%1d%1d",&i1,&j1);
12823: if ((i1 != i) || (j1 != jj)){
12824: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 12825: It might be a problem of design; if ncovcol and the model are correct\n \
12826: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 12827: exit(1);
12828: }
12829: fprintf(ficparo,"%1d%1d",i1,j1);
12830: if(mle==1)
12831: printf("%1d%1d",i,jj);
12832: fprintf(ficlog,"%1d%1d",i,jj);
12833: for(k=1; k<=ncovmodel;k++){
12834: fscanf(ficpar," %lf",¶m[i][j][k]);
12835: if(mle==1){
12836: printf(" %lf",param[i][j][k]);
12837: fprintf(ficlog," %lf",param[i][j][k]);
12838: }
12839: else
12840: fprintf(ficlog," %lf",param[i][j][k]);
12841: fprintf(ficparo," %lf",param[i][j][k]);
12842: }
12843: fscanf(ficpar,"\n");
12844: numlinepar++;
12845: if(mle==1)
12846: printf("\n");
12847: fprintf(ficlog,"\n");
12848: fprintf(ficparo,"\n");
1.126 brouard 12849: }
12850: }
12851: fflush(ficlog);
1.234 brouard 12852:
1.251 brouard 12853: /* Reads parameters values */
1.126 brouard 12854: p=param[1][1];
1.251 brouard 12855: pstart=paramstart[1][1];
1.126 brouard 12856:
12857: /* Reads comments: lines beginning with '#' */
12858: while((c=getc(ficpar))=='#' && c!= EOF){
12859: ungetc(c,ficpar);
12860: fgets(line, MAXLINE, ficpar);
12861: numlinepar++;
1.141 brouard 12862: fputs(line,stdout);
1.126 brouard 12863: fputs(line,ficparo);
12864: fputs(line,ficlog);
12865: }
12866: ungetc(c,ficpar);
12867:
12868: for(i=1; i <=nlstate; i++){
12869: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 12870: fscanf(ficpar,"%1d%1d",&i1,&j1);
12871: if ( (i1-i) * (j1-j) != 0){
12872: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
12873: exit(1);
12874: }
12875: printf("%1d%1d",i,j);
12876: fprintf(ficparo,"%1d%1d",i1,j1);
12877: fprintf(ficlog,"%1d%1d",i1,j1);
12878: for(k=1; k<=ncovmodel;k++){
12879: fscanf(ficpar,"%le",&delti3[i][j][k]);
12880: printf(" %le",delti3[i][j][k]);
12881: fprintf(ficparo," %le",delti3[i][j][k]);
12882: fprintf(ficlog," %le",delti3[i][j][k]);
12883: }
12884: fscanf(ficpar,"\n");
12885: numlinepar++;
12886: printf("\n");
12887: fprintf(ficparo,"\n");
12888: fprintf(ficlog,"\n");
1.126 brouard 12889: }
12890: }
12891: fflush(ficlog);
1.234 brouard 12892:
1.145 brouard 12893: /* Reads covariance matrix */
1.126 brouard 12894: delti=delti3[1][1];
1.220 brouard 12895:
12896:
1.126 brouard 12897: /* 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 12898:
1.126 brouard 12899: /* Reads comments: lines beginning with '#' */
12900: while((c=getc(ficpar))=='#' && c!= EOF){
12901: ungetc(c,ficpar);
12902: fgets(line, MAXLINE, ficpar);
12903: numlinepar++;
1.141 brouard 12904: fputs(line,stdout);
1.126 brouard 12905: fputs(line,ficparo);
12906: fputs(line,ficlog);
12907: }
12908: ungetc(c,ficpar);
1.220 brouard 12909:
1.126 brouard 12910: matcov=matrix(1,npar,1,npar);
1.203 brouard 12911: hess=matrix(1,npar,1,npar);
1.131 brouard 12912: for(i=1; i <=npar; i++)
12913: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 12914:
1.194 brouard 12915: /* Scans npar lines */
1.126 brouard 12916: for(i=1; i <=npar; i++){
1.226 brouard 12917: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 12918: if(count != 3){
1.226 brouard 12919: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 12920: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
12921: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 12922: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 12923: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
12924: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 12925: exit(1);
1.220 brouard 12926: }else{
1.226 brouard 12927: if(mle==1)
12928: printf("%1d%1d%d",i1,j1,jk);
12929: }
12930: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
12931: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 12932: for(j=1; j <=i; j++){
1.226 brouard 12933: fscanf(ficpar," %le",&matcov[i][j]);
12934: if(mle==1){
12935: printf(" %.5le",matcov[i][j]);
12936: }
12937: fprintf(ficlog," %.5le",matcov[i][j]);
12938: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 12939: }
12940: fscanf(ficpar,"\n");
12941: numlinepar++;
12942: if(mle==1)
1.220 brouard 12943: printf("\n");
1.126 brouard 12944: fprintf(ficlog,"\n");
12945: fprintf(ficparo,"\n");
12946: }
1.194 brouard 12947: /* End of read covariance matrix npar lines */
1.126 brouard 12948: for(i=1; i <=npar; i++)
12949: for(j=i+1;j<=npar;j++)
1.226 brouard 12950: matcov[i][j]=matcov[j][i];
1.126 brouard 12951:
12952: if(mle==1)
12953: printf("\n");
12954: fprintf(ficlog,"\n");
12955:
12956: fflush(ficlog);
12957:
12958: } /* End of mle != -3 */
1.218 brouard 12959:
1.186 brouard 12960: /* Main data
12961: */
1.290 brouard 12962: nobs=lastobs-firstobs+1; /* was = lastobs;*/
12963: /* num=lvector(1,n); */
12964: /* moisnais=vector(1,n); */
12965: /* annais=vector(1,n); */
12966: /* moisdc=vector(1,n); */
12967: /* andc=vector(1,n); */
12968: /* weight=vector(1,n); */
12969: /* agedc=vector(1,n); */
12970: /* cod=ivector(1,n); */
12971: /* for(i=1;i<=n;i++){ */
12972: num=lvector(firstobs,lastobs);
12973: moisnais=vector(firstobs,lastobs);
12974: annais=vector(firstobs,lastobs);
12975: moisdc=vector(firstobs,lastobs);
12976: andc=vector(firstobs,lastobs);
12977: weight=vector(firstobs,lastobs);
12978: agedc=vector(firstobs,lastobs);
12979: cod=ivector(firstobs,lastobs);
12980: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 12981: num[i]=0;
12982: moisnais[i]=0;
12983: annais[i]=0;
12984: moisdc[i]=0;
12985: andc[i]=0;
12986: agedc[i]=0;
12987: cod[i]=0;
12988: weight[i]=1.0; /* Equal weights, 1 by default */
12989: }
1.290 brouard 12990: mint=matrix(1,maxwav,firstobs,lastobs);
12991: anint=matrix(1,maxwav,firstobs,lastobs);
1.325 brouard 12992: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
1.336 brouard 12993: /* printf("BUG ncovmodel=%d NCOVMAX=%d 2**ncovmodel=%f BUG\n",ncovmodel,NCOVMAX,pow(2,ncovmodel)); */
1.126 brouard 12994: tab=ivector(1,NCOVMAX);
1.144 brouard 12995: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 12996: 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 12997:
1.136 brouard 12998: /* Reads data from file datafile */
12999: if (readdata(datafile, firstobs, lastobs, &imx)==1)
13000: goto end;
13001:
13002: /* Calculation of the number of parameters from char model */
1.234 brouard 13003: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 13004: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
13005: k=3 V4 Tvar[k=3]= 4 (from V4)
13006: k=2 V1 Tvar[k=2]= 1 (from V1)
13007: k=1 Tvar[1]=2 (from V2)
1.234 brouard 13008: */
13009:
13010: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
13011: TvarsDind=ivector(1,NCOVMAX); /* */
1.330 brouard 13012: TnsdVar=ivector(1,NCOVMAX); /* */
1.335 brouard 13013: /* for(i=1; i<=NCOVMAX;i++) TnsdVar[i]=3; */
1.234 brouard 13014: TvarsD=ivector(1,NCOVMAX); /* */
13015: TvarsQind=ivector(1,NCOVMAX); /* */
13016: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 13017: TvarF=ivector(1,NCOVMAX); /* */
13018: TvarFind=ivector(1,NCOVMAX); /* */
13019: TvarV=ivector(1,NCOVMAX); /* */
13020: TvarVind=ivector(1,NCOVMAX); /* */
13021: TvarA=ivector(1,NCOVMAX); /* */
13022: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 13023: TvarFD=ivector(1,NCOVMAX); /* */
13024: TvarFDind=ivector(1,NCOVMAX); /* */
13025: TvarFQ=ivector(1,NCOVMAX); /* */
13026: TvarFQind=ivector(1,NCOVMAX); /* */
13027: TvarVD=ivector(1,NCOVMAX); /* */
13028: TvarVDind=ivector(1,NCOVMAX); /* */
13029: TvarVQ=ivector(1,NCOVMAX); /* */
13030: TvarVQind=ivector(1,NCOVMAX); /* */
1.339 brouard 13031: TvarVV=ivector(1,NCOVMAX); /* */
13032: TvarVVind=ivector(1,NCOVMAX); /* */
1.231 brouard 13033:
1.230 brouard 13034: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 13035: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 13036: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
13037: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
13038: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.137 brouard 13039: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
13040: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
13041: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
13042: */
13043: /* For model-covariate k tells which data-covariate to use but
13044: because this model-covariate is a construction we invent a new column
13045: ncovcol + k1
13046: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
13047: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 13048: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
13049: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 13050: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
13051: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 13052: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 13053: */
1.145 brouard 13054: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
13055: 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 13056: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
13057: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.330 brouard 13058: Tvardk=imatrix(1,NCOVMAX,1,2);
1.145 brouard 13059: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 13060: 4 covariates (3 plus signs)
13061: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
1.328 brouard 13062: */
13063: for(i=1;i<NCOVMAX;i++)
13064: Tage[i]=0;
1.230 brouard 13065: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 13066: * individual dummy, fixed or varying:
13067: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
13068: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 13069: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
13070: * V1 df, V2 qf, V3 & V4 dv, V5 qv
13071: * Tmodelind[1]@9={9,0,3,2,}*/
13072: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
13073: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 13074: * individual quantitative, fixed or varying:
13075: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
13076: * 3, 1, 0, 0, 0, 0, 0, 0},
13077: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 13078: /* Main decodemodel */
13079:
1.187 brouard 13080:
1.223 brouard 13081: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 13082: goto end;
13083:
1.137 brouard 13084: if((double)(lastobs-imx)/(double)imx > 1.10){
13085: nbwarn++;
13086: 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);
13087: 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);
13088: }
1.136 brouard 13089: /* if(mle==1){*/
1.137 brouard 13090: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
13091: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 13092: }
13093:
13094: /*-calculation of age at interview from date of interview and age at death -*/
13095: agev=matrix(1,maxwav,1,imx);
13096:
13097: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
13098: goto end;
13099:
1.126 brouard 13100:
1.136 brouard 13101: agegomp=(int)agemin;
1.290 brouard 13102: free_vector(moisnais,firstobs,lastobs);
13103: free_vector(annais,firstobs,lastobs);
1.126 brouard 13104: /* free_matrix(mint,1,maxwav,1,n);
13105: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 13106: /* free_vector(moisdc,1,n); */
13107: /* free_vector(andc,1,n); */
1.145 brouard 13108: /* */
13109:
1.126 brouard 13110: wav=ivector(1,imx);
1.214 brouard 13111: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
13112: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
13113: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
13114: 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.*/
13115: bh=imatrix(1,lastpass-firstpass+2,1,imx);
13116: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 13117:
13118: /* Concatenates waves */
1.214 brouard 13119: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
13120: Death is a valid wave (if date is known).
13121: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
13122: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
13123: and mw[mi+1][i]. dh depends on stepm.
13124: */
13125:
1.126 brouard 13126: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 13127: /* Concatenates waves */
1.145 brouard 13128:
1.290 brouard 13129: free_vector(moisdc,firstobs,lastobs);
13130: free_vector(andc,firstobs,lastobs);
1.215 brouard 13131:
1.126 brouard 13132: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
13133: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
13134: ncodemax[1]=1;
1.145 brouard 13135: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 13136: cptcoveff=0;
1.220 brouard 13137: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
1.335 brouard 13138: 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 13139: }
13140:
13141: ncovcombmax=pow(2,cptcoveff);
1.338 brouard 13142: invalidvarcomb=ivector(0, ncovcombmax);
13143: for(i=0;i<ncovcombmax;i++)
1.227 brouard 13144: invalidvarcomb[i]=0;
13145:
1.211 brouard 13146: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 13147: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 13148: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 13149:
1.200 brouard 13150: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 13151: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 13152: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 13153: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
13154: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
13155: * (currently 0 or 1) in the data.
13156: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
13157: * corresponding modality (h,j).
13158: */
13159:
1.145 brouard 13160: h=0;
13161: /*if (cptcovn > 0) */
1.126 brouard 13162: m=pow(2,cptcoveff);
13163:
1.144 brouard 13164: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 13165: * For k=4 covariates, h goes from 1 to m=2**k
13166: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
13167: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.329 brouard 13168: * h\k 1 2 3 4 * h-1\k-1 4 3 2 1
13169: *______________________________ *______________________
13170: * 1 i=1 1 i=1 1 i=1 1 i=1 1 * 0 0 0 0 0
13171: * 2 2 1 1 1 * 1 0 0 0 1
13172: * 3 i=2 1 2 1 1 * 2 0 0 1 0
13173: * 4 2 2 1 1 * 3 0 0 1 1
13174: * 5 i=3 1 i=2 1 2 1 * 4 0 1 0 0
13175: * 6 2 1 2 1 * 5 0 1 0 1
13176: * 7 i=4 1 2 2 1 * 6 0 1 1 0
13177: * 8 2 2 2 1 * 7 0 1 1 1
13178: * 9 i=5 1 i=3 1 i=2 1 2 * 8 1 0 0 0
13179: * 10 2 1 1 2 * 9 1 0 0 1
13180: * 11 i=6 1 2 1 2 * 10 1 0 1 0
13181: * 12 2 2 1 2 * 11 1 0 1 1
13182: * 13 i=7 1 i=4 1 2 2 * 12 1 1 0 0
13183: * 14 2 1 2 2 * 13 1 1 0 1
13184: * 15 i=8 1 2 2 2 * 14 1 1 1 0
13185: * 16 2 2 2 2 * 15 1 1 1 1
13186: */
1.212 brouard 13187: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 13188: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
13189: * and the value of each covariate?
13190: * V1=1, V2=1, V3=2, V4=1 ?
13191: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
13192: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
13193: * In order to get the real value in the data, we use nbcode
13194: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
13195: * We are keeping this crazy system in order to be able (in the future?)
13196: * to have more than 2 values (0 or 1) for a covariate.
13197: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
13198: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
13199: * bbbbbbbb
13200: * 76543210
13201: * h-1 00000101 (6-1=5)
1.219 brouard 13202: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 13203: * &
13204: * 1 00000001 (1)
1.219 brouard 13205: * 00000000 = 1 & ((h-1) >> (k-1))
13206: * +1= 00000001 =1
1.211 brouard 13207: *
13208: * h=14, k=3 => h'=h-1=13, k'=k-1=2
13209: * h' 1101 =2^3+2^2+0x2^1+2^0
13210: * >>k' 11
13211: * & 00000001
13212: * = 00000001
13213: * +1 = 00000010=2 = codtabm(14,3)
13214: * Reverse h=6 and m=16?
13215: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
13216: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
13217: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
13218: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
13219: * V3=decodtabm(14,3,2**4)=2
13220: * h'=13 1101 =2^3+2^2+0x2^1+2^0
13221: *(h-1) >> (j-1) 0011 =13 >> 2
13222: * &1 000000001
13223: * = 000000001
13224: * +1= 000000010 =2
13225: * 2211
13226: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
13227: * V3=2
1.220 brouard 13228: * codtabm and decodtabm are identical
1.211 brouard 13229: */
13230:
1.145 brouard 13231:
13232: free_ivector(Ndum,-1,NCOVMAX);
13233:
13234:
1.126 brouard 13235:
1.186 brouard 13236: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 13237: strcpy(optionfilegnuplot,optionfilefiname);
13238: if(mle==-3)
1.201 brouard 13239: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 13240: strcat(optionfilegnuplot,".gp");
13241:
13242: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
13243: printf("Problem with file %s",optionfilegnuplot);
13244: }
13245: else{
1.204 brouard 13246: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 13247: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 13248: //fprintf(ficgp,"set missing 'NaNq'\n");
13249: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 13250: }
13251: /* fclose(ficgp);*/
1.186 brouard 13252:
13253:
13254: /* Initialisation of --------- index.htm --------*/
1.126 brouard 13255:
13256: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
13257: if(mle==-3)
1.201 brouard 13258: strcat(optionfilehtm,"-MORT_");
1.126 brouard 13259: strcat(optionfilehtm,".htm");
13260: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 13261: printf("Problem with %s \n",optionfilehtm);
13262: exit(0);
1.126 brouard 13263: }
13264:
13265: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
13266: strcat(optionfilehtmcov,"-cov.htm");
13267: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
13268: printf("Problem with %s \n",optionfilehtmcov), exit(0);
13269: }
13270: else{
13271: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
13272: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 13273: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 13274: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
13275: }
13276:
1.335 brouard 13277: fprintf(fichtm,"<html><head>\n<meta charset=\"utf-8\"/><meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n\
13278: <title>IMaCh %s</title></head>\n\
13279: <body><font size=\"7\"><a href=http:/euroreves.ined.fr/imach>IMaCh for Interpolated Markov Chain</a> </font><br>\n\
13280: <font size=\"3\">Sponsored by Copyright (C) 2002-2015 <a href=http://www.ined.fr>INED</a>\
13281: -EUROREVES-Institut de longévité-2013-2022-Japan Society for the Promotion of Sciences 日本学術振興会 \
13282: (<a href=https://www.jsps.go.jp/english/e-grants/>Grant-in-Aid for Scientific Research 25293121</a>) - \
13283: <a href=https://software.intel.com/en-us>Intel Software 2015-2018</a></font><br> \n", optionfilehtm);
13284:
13285: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 13286: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 13287: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.337 brouard 13288: 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 13289: \n\
13290: <hr size=\"2\" color=\"#EC5E5E\">\
13291: <ul><li><h4>Parameter files</h4>\n\
13292: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
13293: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
13294: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
13295: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
13296: - Date and time at start: %s</ul>\n",\
1.335 brouard 13297: version,fullversion,optionfilehtm,optionfilehtm,title,datafile,datafile,firstpass,lastpass,stepm, weightopt, model, \
1.126 brouard 13298: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
13299: fileres,fileres,\
13300: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
13301: fflush(fichtm);
13302:
13303: strcpy(pathr,path);
13304: strcat(pathr,optionfilefiname);
1.184 brouard 13305: #ifdef WIN32
13306: _chdir(optionfilefiname); /* Move to directory named optionfile */
13307: #else
1.126 brouard 13308: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 13309: #endif
13310:
1.126 brouard 13311:
1.220 brouard 13312: /* Calculates basic frequencies. Computes observed prevalence at single age
13313: and for any valid combination of covariates
1.126 brouard 13314: and prints on file fileres'p'. */
1.251 brouard 13315: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 13316: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 13317:
13318: fprintf(fichtm,"\n");
1.286 brouard 13319: 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 13320: ftol, stepm);
13321: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
13322: ncurrv=1;
13323: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
13324: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
13325: ncurrv=i;
13326: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 13327: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 13328: ncurrv=i;
13329: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 13330: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 13331: ncurrv=i;
13332: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
13333: 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", \
13334: nlstate, ndeath, maxwav, mle, weightopt);
13335:
13336: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
13337: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
13338:
13339:
1.317 brouard 13340: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Number of (used) observations=%d <br>\n\
1.126 brouard 13341: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
13342: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 13343: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 13344: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 13345: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
13346: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
13347: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
13348: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 13349:
1.126 brouard 13350: /* For Powell, parameters are in a vector p[] starting at p[1]
13351: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
13352: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
13353:
13354: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 13355: /* For mortality only */
1.126 brouard 13356: if (mle==-3){
1.136 brouard 13357: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 13358: for(i=1;i<=NDIM;i++)
13359: for(j=1;j<=NDIM;j++)
13360: ximort[i][j]=0.;
1.186 brouard 13361: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 13362: cens=ivector(firstobs,lastobs);
13363: ageexmed=vector(firstobs,lastobs);
13364: agecens=vector(firstobs,lastobs);
13365: dcwave=ivector(firstobs,lastobs);
1.223 brouard 13366:
1.126 brouard 13367: for (i=1; i<=imx; i++){
13368: dcwave[i]=-1;
13369: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 13370: if (s[m][i]>nlstate) {
13371: dcwave[i]=m;
13372: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
13373: break;
13374: }
1.126 brouard 13375: }
1.226 brouard 13376:
1.126 brouard 13377: for (i=1; i<=imx; i++) {
13378: if (wav[i]>0){
1.226 brouard 13379: ageexmed[i]=agev[mw[1][i]][i];
13380: j=wav[i];
13381: agecens[i]=1.;
13382:
13383: if (ageexmed[i]> 1 && wav[i] > 0){
13384: agecens[i]=agev[mw[j][i]][i];
13385: cens[i]= 1;
13386: }else if (ageexmed[i]< 1)
13387: cens[i]= -1;
13388: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
13389: cens[i]=0 ;
1.126 brouard 13390: }
13391: else cens[i]=-1;
13392: }
13393:
13394: for (i=1;i<=NDIM;i++) {
13395: for (j=1;j<=NDIM;j++)
1.226 brouard 13396: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 13397: }
13398:
1.302 brouard 13399: p[1]=0.0268; p[NDIM]=0.083;
13400: /* printf("%lf %lf", p[1], p[2]); */
1.126 brouard 13401:
13402:
1.136 brouard 13403: #ifdef GSL
13404: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 13405: #else
1.126 brouard 13406: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 13407: #endif
1.201 brouard 13408: strcpy(filerespow,"POW-MORT_");
13409: strcat(filerespow,fileresu);
1.126 brouard 13410: if((ficrespow=fopen(filerespow,"w"))==NULL) {
13411: printf("Problem with resultfile: %s\n", filerespow);
13412: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
13413: }
1.136 brouard 13414: #ifdef GSL
13415: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 13416: #else
1.126 brouard 13417: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 13418: #endif
1.126 brouard 13419: /* for (i=1;i<=nlstate;i++)
13420: for(j=1;j<=nlstate+ndeath;j++)
13421: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
13422: */
13423: fprintf(ficrespow,"\n");
1.136 brouard 13424: #ifdef GSL
13425: /* gsl starts here */
13426: T = gsl_multimin_fminimizer_nmsimplex;
13427: gsl_multimin_fminimizer *sfm = NULL;
13428: gsl_vector *ss, *x;
13429: gsl_multimin_function minex_func;
13430:
13431: /* Initial vertex size vector */
13432: ss = gsl_vector_alloc (NDIM);
13433:
13434: if (ss == NULL){
13435: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
13436: }
13437: /* Set all step sizes to 1 */
13438: gsl_vector_set_all (ss, 0.001);
13439:
13440: /* Starting point */
1.126 brouard 13441:
1.136 brouard 13442: x = gsl_vector_alloc (NDIM);
13443:
13444: if (x == NULL){
13445: gsl_vector_free(ss);
13446: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
13447: }
13448:
13449: /* Initialize method and iterate */
13450: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 13451: /* gsl_vector_set(x, 0, 0.0268); */
13452: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 13453: gsl_vector_set(x, 0, p[1]);
13454: gsl_vector_set(x, 1, p[2]);
13455:
13456: minex_func.f = &gompertz_f;
13457: minex_func.n = NDIM;
13458: minex_func.params = (void *)&p; /* ??? */
13459:
13460: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
13461: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
13462:
13463: printf("Iterations beginning .....\n\n");
13464: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
13465:
13466: iteri=0;
13467: while (rval == GSL_CONTINUE){
13468: iteri++;
13469: status = gsl_multimin_fminimizer_iterate(sfm);
13470:
13471: if (status) printf("error: %s\n", gsl_strerror (status));
13472: fflush(0);
13473:
13474: if (status)
13475: break;
13476:
13477: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
13478: ssval = gsl_multimin_fminimizer_size (sfm);
13479:
13480: if (rval == GSL_SUCCESS)
13481: printf ("converged to a local maximum at\n");
13482:
13483: printf("%5d ", iteri);
13484: for (it = 0; it < NDIM; it++){
13485: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
13486: }
13487: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
13488: }
13489:
13490: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
13491:
13492: gsl_vector_free(x); /* initial values */
13493: gsl_vector_free(ss); /* inital step size */
13494: for (it=0; it<NDIM; it++){
13495: p[it+1]=gsl_vector_get(sfm->x,it);
13496: fprintf(ficrespow," %.12lf", p[it]);
13497: }
13498: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
13499: #endif
13500: #ifdef POWELL
13501: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
13502: #endif
1.126 brouard 13503: fclose(ficrespow);
13504:
1.203 brouard 13505: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 13506:
13507: for(i=1; i <=NDIM; i++)
13508: for(j=i+1;j<=NDIM;j++)
1.220 brouard 13509: matcov[i][j]=matcov[j][i];
1.126 brouard 13510:
13511: printf("\nCovariance matrix\n ");
1.203 brouard 13512: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 13513: for(i=1; i <=NDIM; i++) {
13514: for(j=1;j<=NDIM;j++){
1.220 brouard 13515: printf("%f ",matcov[i][j]);
13516: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 13517: }
1.203 brouard 13518: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 13519: }
13520:
13521: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 13522: for (i=1;i<=NDIM;i++) {
1.126 brouard 13523: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 13524: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
13525: }
1.302 brouard 13526: lsurv=vector(agegomp,AGESUP);
13527: lpop=vector(agegomp,AGESUP);
13528: tpop=vector(agegomp,AGESUP);
1.126 brouard 13529: lsurv[agegomp]=100000;
13530:
13531: for (k=agegomp;k<=AGESUP;k++) {
13532: agemortsup=k;
13533: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
13534: }
13535:
13536: for (k=agegomp;k<agemortsup;k++)
13537: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
13538:
13539: for (k=agegomp;k<agemortsup;k++){
13540: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
13541: sumlpop=sumlpop+lpop[k];
13542: }
13543:
13544: tpop[agegomp]=sumlpop;
13545: for (k=agegomp;k<(agemortsup-3);k++){
13546: /* tpop[k+1]=2;*/
13547: tpop[k+1]=tpop[k]-lpop[k];
13548: }
13549:
13550:
13551: printf("\nAge lx qx dx Lx Tx e(x)\n");
13552: for (k=agegomp;k<(agemortsup-2);k++)
13553: 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]);
13554:
13555:
13556: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 13557: ageminpar=50;
13558: agemaxpar=100;
1.194 brouard 13559: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
13560: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
13561: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
13562: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
13563: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
13564: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
13565: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 13566: }else{
13567: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
13568: 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 13569: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 13570: }
1.201 brouard 13571: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 13572: stepm, weightopt,\
13573: model,imx,p,matcov,agemortsup);
13574:
1.302 brouard 13575: free_vector(lsurv,agegomp,AGESUP);
13576: free_vector(lpop,agegomp,AGESUP);
13577: free_vector(tpop,agegomp,AGESUP);
1.220 brouard 13578: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 13579: free_ivector(dcwave,firstobs,lastobs);
13580: free_vector(agecens,firstobs,lastobs);
13581: free_vector(ageexmed,firstobs,lastobs);
13582: free_ivector(cens,firstobs,lastobs);
1.220 brouard 13583: #ifdef GSL
1.136 brouard 13584: #endif
1.186 brouard 13585: } /* Endof if mle==-3 mortality only */
1.205 brouard 13586: /* Standard */
13587: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
13588: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
13589: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 13590: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 13591: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
13592: for (k=1; k<=npar;k++)
13593: printf(" %d %8.5f",k,p[k]);
13594: printf("\n");
1.205 brouard 13595: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
13596: /* mlikeli uses func not funcone */
1.247 brouard 13597: /* for(i=1;i<nlstate;i++){ */
13598: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
13599: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
13600: /* } */
1.205 brouard 13601: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
13602: }
13603: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
13604: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
13605: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
13606: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
13607: }
13608: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 13609: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
13610: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
1.335 brouard 13611: /* exit(0); */
1.126 brouard 13612: for (k=1; k<=npar;k++)
13613: printf(" %d %8.5f",k,p[k]);
13614: printf("\n");
13615:
13616: /*--------- results files --------------*/
1.283 brouard 13617: /* 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 13618:
13619:
13620: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 13621: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); /* Printing model equation */
1.126 brouard 13622: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 13623:
13624: printf("#model= 1 + age ");
13625: fprintf(ficres,"#model= 1 + age ");
13626: fprintf(ficlog,"#model= 1 + age ");
13627: fprintf(fichtm,"\n<ul><li> model=1+age+%s\n \
13628: </ul>", model);
13629:
13630: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">\n");
13631: fprintf(fichtm, "<tr><th>Model=</th><th>1</th><th>+ age</th>");
13632: if(nagesqr==1){
13633: printf(" + age*age ");
13634: fprintf(ficres," + age*age ");
13635: fprintf(ficlog," + age*age ");
13636: fprintf(fichtm, "<th>+ age*age</th>");
13637: }
13638: for(j=1;j <=ncovmodel-2;j++){
13639: if(Typevar[j]==0) {
13640: printf(" + V%d ",Tvar[j]);
13641: fprintf(ficres," + V%d ",Tvar[j]);
13642: fprintf(ficlog," + V%d ",Tvar[j]);
13643: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
13644: }else if(Typevar[j]==1) {
13645: printf(" + V%d*age ",Tvar[j]);
13646: fprintf(ficres," + V%d*age ",Tvar[j]);
13647: fprintf(ficlog," + V%d*age ",Tvar[j]);
13648: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
13649: }else if(Typevar[j]==2) {
13650: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13651: fprintf(ficres," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13652: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13653: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13654: }
13655: }
13656: printf("\n");
13657: fprintf(ficres,"\n");
13658: fprintf(ficlog,"\n");
13659: fprintf(fichtm, "</tr>");
13660: fprintf(fichtm, "\n");
13661:
13662:
1.126 brouard 13663: for(i=1,jk=1; i <=nlstate; i++){
13664: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 13665: if (k != i) {
1.319 brouard 13666: fprintf(fichtm, "<tr>");
1.225 brouard 13667: printf("%d%d ",i,k);
13668: fprintf(ficlog,"%d%d ",i,k);
13669: fprintf(ficres,"%1d%1d ",i,k);
1.319 brouard 13670: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 13671: for(j=1; j <=ncovmodel; j++){
13672: printf("%12.7f ",p[jk]);
13673: fprintf(ficlog,"%12.7f ",p[jk]);
13674: fprintf(ficres,"%12.7f ",p[jk]);
1.319 brouard 13675: fprintf(fichtm, "<td>%12.7f</td>",p[jk]);
1.225 brouard 13676: jk++;
13677: }
13678: printf("\n");
13679: fprintf(ficlog,"\n");
13680: fprintf(ficres,"\n");
1.319 brouard 13681: fprintf(fichtm, "</tr>\n");
1.225 brouard 13682: }
1.126 brouard 13683: }
13684: }
1.319 brouard 13685: /* fprintf(fichtm,"</tr>\n"); */
13686: fprintf(fichtm,"</table>\n");
13687: fprintf(fichtm, "\n");
13688:
1.203 brouard 13689: if(mle != 0){
13690: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 13691: ftolhess=ftol; /* Usually correct */
1.203 brouard 13692: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
13693: 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");
13694: 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 13695: 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 13696: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">");
13697: fprintf(fichtm, "\n<tr><th>Model=</th><th>1</th><th>+ age</th>");
13698: if(nagesqr==1){
13699: printf(" + age*age ");
13700: fprintf(ficres," + age*age ");
13701: fprintf(ficlog," + age*age ");
13702: fprintf(fichtm, "<th>+ age*age</th>");
13703: }
13704: for(j=1;j <=ncovmodel-2;j++){
13705: if(Typevar[j]==0) {
13706: printf(" + V%d ",Tvar[j]);
13707: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
13708: }else if(Typevar[j]==1) {
13709: printf(" + V%d*age ",Tvar[j]);
13710: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
13711: }else if(Typevar[j]==2) {
13712: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13713: }
13714: }
13715: fprintf(fichtm, "</tr>\n");
13716:
1.203 brouard 13717: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 13718: for(k=1; k <=(nlstate+ndeath); k++){
13719: if (k != i) {
1.319 brouard 13720: fprintf(fichtm, "<tr valign=top>");
1.225 brouard 13721: printf("%d%d ",i,k);
13722: fprintf(ficlog,"%d%d ",i,k);
1.319 brouard 13723: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 13724: for(j=1; j <=ncovmodel; j++){
1.319 brouard 13725: wald=p[jk]/sqrt(matcov[jk][jk]);
1.324 brouard 13726: 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]));
13727: 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 13728: if(fabs(wald) > 1.96){
1.321 brouard 13729: fprintf(fichtm, "<td><b>%12.7f</b></br> (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
1.319 brouard 13730: }else{
13731: fprintf(fichtm, "<td>%12.7f (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
13732: }
1.324 brouard 13733: fprintf(fichtm,"W=%8.3f</br>",wald);
1.319 brouard 13734: 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 13735: jk++;
13736: }
13737: printf("\n");
13738: fprintf(ficlog,"\n");
1.319 brouard 13739: fprintf(fichtm, "</tr>\n");
1.225 brouard 13740: }
13741: }
1.193 brouard 13742: }
1.203 brouard 13743: } /* end of hesscov and Wald tests */
1.319 brouard 13744: fprintf(fichtm,"</table>\n");
1.225 brouard 13745:
1.203 brouard 13746: /* */
1.126 brouard 13747: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
13748: printf("# Scales (for hessian or gradient estimation)\n");
13749: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
13750: for(i=1,jk=1; i <=nlstate; i++){
13751: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 13752: if (j!=i) {
13753: fprintf(ficres,"%1d%1d",i,j);
13754: printf("%1d%1d",i,j);
13755: fprintf(ficlog,"%1d%1d",i,j);
13756: for(k=1; k<=ncovmodel;k++){
13757: printf(" %.5e",delti[jk]);
13758: fprintf(ficlog," %.5e",delti[jk]);
13759: fprintf(ficres," %.5e",delti[jk]);
13760: jk++;
13761: }
13762: printf("\n");
13763: fprintf(ficlog,"\n");
13764: fprintf(ficres,"\n");
13765: }
1.126 brouard 13766: }
13767: }
13768:
13769: 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 13770: if(mle >= 1) /* To big for the screen */
1.126 brouard 13771: 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");
13772: 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");
13773: /* # 121 Var(a12)\n\ */
13774: /* # 122 Cov(b12,a12) Var(b12)\n\ */
13775: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
13776: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
13777: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
13778: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
13779: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
13780: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
13781:
13782:
13783: /* Just to have a covariance matrix which will be more understandable
13784: even is we still don't want to manage dictionary of variables
13785: */
13786: for(itimes=1;itimes<=2;itimes++){
13787: jj=0;
13788: for(i=1; i <=nlstate; i++){
1.225 brouard 13789: for(j=1; j <=nlstate+ndeath; j++){
13790: if(j==i) continue;
13791: for(k=1; k<=ncovmodel;k++){
13792: jj++;
13793: ca[0]= k+'a'-1;ca[1]='\0';
13794: if(itimes==1){
13795: if(mle>=1)
13796: printf("#%1d%1d%d",i,j,k);
13797: fprintf(ficlog,"#%1d%1d%d",i,j,k);
13798: fprintf(ficres,"#%1d%1d%d",i,j,k);
13799: }else{
13800: if(mle>=1)
13801: printf("%1d%1d%d",i,j,k);
13802: fprintf(ficlog,"%1d%1d%d",i,j,k);
13803: fprintf(ficres,"%1d%1d%d",i,j,k);
13804: }
13805: ll=0;
13806: for(li=1;li <=nlstate; li++){
13807: for(lj=1;lj <=nlstate+ndeath; lj++){
13808: if(lj==li) continue;
13809: for(lk=1;lk<=ncovmodel;lk++){
13810: ll++;
13811: if(ll<=jj){
13812: cb[0]= lk +'a'-1;cb[1]='\0';
13813: if(ll<jj){
13814: if(itimes==1){
13815: if(mle>=1)
13816: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
13817: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
13818: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
13819: }else{
13820: if(mle>=1)
13821: printf(" %.5e",matcov[jj][ll]);
13822: fprintf(ficlog," %.5e",matcov[jj][ll]);
13823: fprintf(ficres," %.5e",matcov[jj][ll]);
13824: }
13825: }else{
13826: if(itimes==1){
13827: if(mle>=1)
13828: printf(" Var(%s%1d%1d)",ca,i,j);
13829: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
13830: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
13831: }else{
13832: if(mle>=1)
13833: printf(" %.7e",matcov[jj][ll]);
13834: fprintf(ficlog," %.7e",matcov[jj][ll]);
13835: fprintf(ficres," %.7e",matcov[jj][ll]);
13836: }
13837: }
13838: }
13839: } /* end lk */
13840: } /* end lj */
13841: } /* end li */
13842: if(mle>=1)
13843: printf("\n");
13844: fprintf(ficlog,"\n");
13845: fprintf(ficres,"\n");
13846: numlinepar++;
13847: } /* end k*/
13848: } /*end j */
1.126 brouard 13849: } /* end i */
13850: } /* end itimes */
13851:
13852: fflush(ficlog);
13853: fflush(ficres);
1.225 brouard 13854: while(fgets(line, MAXLINE, ficpar)) {
13855: /* If line starts with a # it is a comment */
13856: if (line[0] == '#') {
13857: numlinepar++;
13858: fputs(line,stdout);
13859: fputs(line,ficparo);
13860: fputs(line,ficlog);
1.299 brouard 13861: fputs(line,ficres);
1.225 brouard 13862: continue;
13863: }else
13864: break;
13865: }
13866:
1.209 brouard 13867: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
13868: /* ungetc(c,ficpar); */
13869: /* fgets(line, MAXLINE, ficpar); */
13870: /* fputs(line,stdout); */
13871: /* fputs(line,ficparo); */
13872: /* } */
13873: /* ungetc(c,ficpar); */
1.126 brouard 13874:
13875: estepm=0;
1.209 brouard 13876: 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 13877:
13878: if (num_filled != 6) {
13879: 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);
13880: 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);
13881: goto end;
13882: }
13883: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
13884: }
13885: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
13886: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
13887:
1.209 brouard 13888: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 13889: if (estepm==0 || estepm < stepm) estepm=stepm;
13890: if (fage <= 2) {
13891: bage = ageminpar;
13892: fage = agemaxpar;
13893: }
13894:
13895: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 13896: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
13897: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 13898:
1.186 brouard 13899: /* Other stuffs, more or less useful */
1.254 brouard 13900: while(fgets(line, MAXLINE, ficpar)) {
13901: /* If line starts with a # it is a comment */
13902: if (line[0] == '#') {
13903: numlinepar++;
13904: fputs(line,stdout);
13905: fputs(line,ficparo);
13906: fputs(line,ficlog);
1.299 brouard 13907: fputs(line,ficres);
1.254 brouard 13908: continue;
13909: }else
13910: break;
13911: }
13912:
13913: 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){
13914:
13915: if (num_filled != 7) {
13916: 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);
13917: 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);
13918: goto end;
13919: }
13920: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
13921: 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);
13922: 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);
13923: 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 13924: }
1.254 brouard 13925:
13926: while(fgets(line, MAXLINE, ficpar)) {
13927: /* If line starts with a # it is a comment */
13928: if (line[0] == '#') {
13929: numlinepar++;
13930: fputs(line,stdout);
13931: fputs(line,ficparo);
13932: fputs(line,ficlog);
1.299 brouard 13933: fputs(line,ficres);
1.254 brouard 13934: continue;
13935: }else
13936: break;
1.126 brouard 13937: }
13938:
13939:
13940: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
13941: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
13942:
1.254 brouard 13943: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
13944: if (num_filled != 1) {
13945: 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);
13946: 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);
13947: goto end;
13948: }
13949: printf("pop_based=%d\n",popbased);
13950: fprintf(ficlog,"pop_based=%d\n",popbased);
13951: fprintf(ficparo,"pop_based=%d\n",popbased);
13952: fprintf(ficres,"pop_based=%d\n",popbased);
13953: }
13954:
1.258 brouard 13955: /* Results */
1.332 brouard 13956: /* Value of covariate in each resultine will be compututed (if product) and sorted according to model rank */
13957: /* It is precov[] because we need the varying age in order to compute the real cov[] of the model equation */
13958: precov=matrix(1,MAXRESULTLINESPONE,1,NCOVMAX+1);
1.307 brouard 13959: endishere=0;
1.258 brouard 13960: nresult=0;
1.308 brouard 13961: parameterline=0;
1.258 brouard 13962: do{
13963: if(!fgets(line, MAXLINE, ficpar)){
13964: endishere=1;
1.308 brouard 13965: parameterline=15;
1.258 brouard 13966: }else if (line[0] == '#') {
13967: /* If line starts with a # it is a comment */
1.254 brouard 13968: numlinepar++;
13969: fputs(line,stdout);
13970: fputs(line,ficparo);
13971: fputs(line,ficlog);
1.299 brouard 13972: fputs(line,ficres);
1.254 brouard 13973: continue;
1.258 brouard 13974: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
13975: parameterline=11;
1.296 brouard 13976: else if(sscanf(line,"prevbackcast=%[^\n]\n",modeltemp))
1.258 brouard 13977: parameterline=12;
1.307 brouard 13978: else if(sscanf(line,"result:%[^\n]\n",modeltemp)){
1.258 brouard 13979: parameterline=13;
1.307 brouard 13980: }
1.258 brouard 13981: else{
13982: parameterline=14;
1.254 brouard 13983: }
1.308 brouard 13984: switch (parameterline){ /* =0 only if only comments */
1.258 brouard 13985: case 11:
1.296 brouard 13986: 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)){
13987: 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 13988: 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);
13989: 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);
13990: 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);
13991: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 13992: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
13993: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
1.296 brouard 13994: prvforecast = 1;
13995: }
13996: else if((num_filled=sscanf(line,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",&prevfcast,&yrfproj,&mobilavproj)) !=EOF){/* && (num_filled == 3))*/
1.313 brouard 13997: printf("prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
13998: fprintf(ficlog,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
13999: fprintf(ficres,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
1.296 brouard 14000: prvforecast = 2;
14001: }
14002: else {
14003: 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);
14004: 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);
14005: goto end;
1.258 brouard 14006: }
1.254 brouard 14007: break;
1.258 brouard 14008: case 12:
1.296 brouard 14009: 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)){
14010: 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);
14011: 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);
14012: 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);
14013: 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);
14014: /* day and month of back2 are not used but only year anback2.*/
1.273 brouard 14015: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
14016: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.296 brouard 14017: prvbackcast = 1;
14018: }
14019: else if((num_filled=sscanf(line,"prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",&prevbcast,&yrbproj,&mobilavproj)) ==3){/* && (num_filled == 3))*/
1.313 brouard 14020: printf("prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
14021: fprintf(ficlog,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
14022: fprintf(ficres,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
1.296 brouard 14023: prvbackcast = 2;
14024: }
14025: else {
14026: 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);
14027: 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);
14028: goto end;
1.258 brouard 14029: }
1.230 brouard 14030: break;
1.258 brouard 14031: case 13:
1.332 brouard 14032: num_filled=sscanf(line,"result:%[^\n]\n",resultlineori);
1.307 brouard 14033: nresult++; /* Sum of resultlines */
1.342 brouard 14034: /* printf("Result %d: result:%s\n",nresult, resultlineori); */
1.332 brouard 14035: /* removefirstspace(&resultlineori); */
14036:
14037: if(strstr(resultlineori,"v") !=0){
14038: printf("Error. 'v' must be in upper case 'V' result: %s ",resultlineori);
14039: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultlineori);fflush(ficlog);
14040: return 1;
14041: }
14042: trimbb(resultline, resultlineori); /* Suppressing double blank in the resultline */
1.342 brouard 14043: /* printf("Decoderesult resultline=\"%s\" resultlineori=\"%s\"\n", resultline, resultlineori); */
1.318 brouard 14044: if(nresult > MAXRESULTLINESPONE-1){
14045: 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);
14046: 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 14047: goto end;
14048: }
1.332 brouard 14049:
1.310 brouard 14050: if(!decoderesult(resultline, nresult)){ /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
1.314 brouard 14051: fprintf(ficparo,"result: %s\n",resultline);
14052: fprintf(ficres,"result: %s\n",resultline);
14053: fprintf(ficlog,"result: %s\n",resultline);
1.310 brouard 14054: } else
14055: goto end;
1.307 brouard 14056: break;
14057: case 14:
14058: printf("Error: Unknown command '%s'\n",line);
14059: fprintf(ficlog,"Error: Unknown command '%s'\n",line);
1.314 brouard 14060: if(line[0] == ' ' || line[0] == '\n'){
14061: printf("It should not be an empty line '%s'\n",line);
14062: fprintf(ficlog,"It should not be an empty line '%s'\n",line);
14063: }
1.307 brouard 14064: if(ncovmodel >=2 && nresult==0 ){
14065: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
14066: fprintf(ficlog,"ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 14067: }
1.307 brouard 14068: /* goto end; */
14069: break;
1.308 brouard 14070: case 15:
14071: printf("End of resultlines.\n");
14072: fprintf(ficlog,"End of resultlines.\n");
14073: break;
14074: default: /* parameterline =0 */
1.307 brouard 14075: nresult=1;
14076: decoderesult(".",nresult ); /* No covariate */
1.258 brouard 14077: } /* End switch parameterline */
14078: }while(endishere==0); /* End do */
1.126 brouard 14079:
1.230 brouard 14080: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 14081: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 14082:
14083: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 14084: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 14085: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 14086: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14087: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 14088: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 14089: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14090: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 14091: }else{
1.270 brouard 14092: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
1.296 brouard 14093: /* It seems that anprojd which is computed from the mean year at interview which is known yet because of freqsummary */
14094: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */ /* Done in freqsummary */
14095: if(prvforecast==1){
14096: dateprojd=(jproj1+12*mproj1+365*anproj1)/365;
14097: jprojd=jproj1;
14098: mprojd=mproj1;
14099: anprojd=anproj1;
14100: dateprojf=(jproj2+12*mproj2+365*anproj2)/365;
14101: jprojf=jproj2;
14102: mprojf=mproj2;
14103: anprojf=anproj2;
14104: } else if(prvforecast == 2){
14105: dateprojd=dateintmean;
14106: date2dmy(dateprojd,&jprojd, &mprojd, &anprojd);
14107: dateprojf=dateintmean+yrfproj;
14108: date2dmy(dateprojf,&jprojf, &mprojf, &anprojf);
14109: }
14110: if(prvbackcast==1){
14111: datebackd=(jback1+12*mback1+365*anback1)/365;
14112: jbackd=jback1;
14113: mbackd=mback1;
14114: anbackd=anback1;
14115: datebackf=(jback2+12*mback2+365*anback2)/365;
14116: jbackf=jback2;
14117: mbackf=mback2;
14118: anbackf=anback2;
14119: } else if(prvbackcast == 2){
14120: datebackd=dateintmean;
14121: date2dmy(datebackd,&jbackd, &mbackd, &anbackd);
14122: datebackf=dateintmean-yrbproj;
14123: date2dmy(datebackf,&jbackf, &mbackf, &anbackf);
14124: }
14125:
14126: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage);
1.220 brouard 14127: }
14128: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.296 brouard 14129: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,prevbcast, estepm, \
14130: jprev1,mprev1,anprev1,dateprev1, dateprojd, datebackd,jprev2,mprev2,anprev2,dateprev2,dateprojf, datebackf);
1.220 brouard 14131:
1.225 brouard 14132: /*------------ free_vector -------------*/
14133: /* chdir(path); */
1.220 brouard 14134:
1.215 brouard 14135: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
14136: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
14137: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
14138: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 14139: free_lvector(num,firstobs,lastobs);
14140: free_vector(agedc,firstobs,lastobs);
1.126 brouard 14141: /*free_matrix(covar,0,NCOVMAX,1,n);*/
14142: /*free_matrix(covar,1,NCOVMAX,1,n);*/
14143: fclose(ficparo);
14144: fclose(ficres);
1.220 brouard 14145:
14146:
1.186 brouard 14147: /* Other results (useful)*/
1.220 brouard 14148:
14149:
1.126 brouard 14150: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 14151: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
14152: prlim=matrix(1,nlstate,1,nlstate);
1.332 brouard 14153: /* Computes the prevalence limit for each combination k of the dummy covariates by calling prevalim(k) */
1.209 brouard 14154: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 14155: fclose(ficrespl);
14156:
14157: /*------------- h Pij x at various ages ------------*/
1.180 brouard 14158: /*#include "hpijx.h"*/
1.332 brouard 14159: /** 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?*/
14160: /* calls hpxij with combination k */
1.180 brouard 14161: hPijx(p, bage, fage);
1.145 brouard 14162: fclose(ficrespij);
1.227 brouard 14163:
1.220 brouard 14164: /* ncovcombmax= pow(2,cptcoveff); */
1.332 brouard 14165: /*-------------- Variance of one-step probabilities for a combination ij or for nres ?---*/
1.145 brouard 14166: k=1;
1.126 brouard 14167: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 14168:
1.269 brouard 14169: /* Prevalence for each covariate combination in probs[age][status][cov] */
14170: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
14171: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 14172: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 14173: for(k=1;k<=ncovcombmax;k++)
14174: probs[i][j][k]=0.;
1.269 brouard 14175: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
14176: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 14177: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 14178: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
14179: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 14180: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 14181: for(k=1;k<=ncovcombmax;k++)
14182: mobaverages[i][j][k]=0.;
1.219 brouard 14183: mobaverage=mobaverages;
14184: if (mobilav!=0) {
1.235 brouard 14185: printf("Movingaveraging observed prevalence\n");
1.258 brouard 14186: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 14187: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
14188: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
14189: printf(" Error in movingaverage mobilav=%d\n",mobilav);
14190: }
1.269 brouard 14191: } else if (mobilavproj !=0) {
1.235 brouard 14192: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 14193: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 14194: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
14195: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
14196: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
14197: }
1.269 brouard 14198: }else{
14199: printf("Internal error moving average\n");
14200: fflush(stdout);
14201: exit(1);
1.219 brouard 14202: }
14203: }/* end if moving average */
1.227 brouard 14204:
1.126 brouard 14205: /*---------- Forecasting ------------------*/
1.296 brouard 14206: if(prevfcast==1){
14207: /* /\* if(stepm ==1){*\/ */
14208: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
14209: /*This done previously after freqsummary.*/
14210: /* dateprojd=(jproj1+12*mproj1+365*anproj1)/365; */
14211: /* dateprojf=(jproj2+12*mproj2+365*anproj2)/365; */
14212:
14213: /* } else if (prvforecast==2){ */
14214: /* /\* if(stepm ==1){*\/ */
14215: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
14216: /* } */
14217: /*prevforecast(fileresu, dateintmean, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);*/
14218: prevforecast(fileresu,dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, p, cptcoveff);
1.126 brouard 14219: }
1.269 brouard 14220:
1.296 brouard 14221: /* Prevbcasting */
14222: if(prevbcast==1){
1.219 brouard 14223: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14224: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14225: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14226:
14227: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
14228:
14229: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 14230:
1.219 brouard 14231: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
14232: fclose(ficresplb);
14233:
1.222 brouard 14234: hBijx(p, bage, fage, mobaverage);
14235: fclose(ficrespijb);
1.219 brouard 14236:
1.296 brouard 14237: /* /\* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, *\/ */
14238: /* /\* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); *\/ */
14239: /* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, */
14240: /* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
14241: prevbackforecast(fileresu, mobaverage, dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2,
14242: mobilavproj, bage, fage, firstpass, lastpass, p, cptcoveff);
14243:
14244:
1.269 brouard 14245: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 14246:
14247:
1.269 brouard 14248: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 14249: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
14250: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
14251: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.296 brouard 14252: } /* end Prevbcasting */
1.268 brouard 14253:
1.186 brouard 14254:
14255: /* ------ Other prevalence ratios------------ */
1.126 brouard 14256:
1.215 brouard 14257: free_ivector(wav,1,imx);
14258: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
14259: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
14260: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 14261:
14262:
1.127 brouard 14263: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 14264:
1.201 brouard 14265: strcpy(filerese,"E_");
14266: strcat(filerese,fileresu);
1.126 brouard 14267: if((ficreseij=fopen(filerese,"w"))==NULL) {
14268: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
14269: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
14270: }
1.208 brouard 14271: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
14272: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 14273:
14274: pstamp(ficreseij);
1.219 brouard 14275:
1.235 brouard 14276: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
14277: if (cptcovn < 1){i1=1;}
14278:
14279: for(nres=1; nres <= nresult; nres++) /* For each resultline */
14280: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 14281: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 14282: continue;
1.219 brouard 14283: fprintf(ficreseij,"\n#****** ");
1.235 brouard 14284: printf("\n#****** ");
1.225 brouard 14285: for(j=1;j<=cptcoveff;j++) {
1.332 brouard 14286: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
14287: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.235 brouard 14288: }
14289: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.337 brouard 14290: printf(" V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]); /* TvarsQ[j] gives the name of the jth quantitative (fixed or time v) */
14291: fprintf(ficreseij,"V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]);
1.219 brouard 14292: }
14293: fprintf(ficreseij,"******\n");
1.235 brouard 14294: printf("******\n");
1.219 brouard 14295:
14296: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
14297: oldm=oldms;savm=savms;
1.330 brouard 14298: /* 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 14299: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 14300:
1.219 brouard 14301: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 14302: }
14303: fclose(ficreseij);
1.208 brouard 14304: printf("done evsij\n");fflush(stdout);
14305: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 14306:
1.218 brouard 14307:
1.227 brouard 14308: /*---------- State-specific expectancies and variances ------------*/
1.336 brouard 14309: /* Should be moved in a function */
1.201 brouard 14310: strcpy(filerest,"T_");
14311: strcat(filerest,fileresu);
1.127 brouard 14312: if((ficrest=fopen(filerest,"w"))==NULL) {
14313: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
14314: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
14315: }
1.208 brouard 14316: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
14317: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 14318: strcpy(fileresstde,"STDE_");
14319: strcat(fileresstde,fileresu);
1.126 brouard 14320: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 14321: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
14322: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 14323: }
1.227 brouard 14324: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
14325: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 14326:
1.201 brouard 14327: strcpy(filerescve,"CVE_");
14328: strcat(filerescve,fileresu);
1.126 brouard 14329: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 14330: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
14331: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 14332: }
1.227 brouard 14333: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
14334: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 14335:
1.201 brouard 14336: strcpy(fileresv,"V_");
14337: strcat(fileresv,fileresu);
1.126 brouard 14338: if((ficresvij=fopen(fileresv,"w"))==NULL) {
14339: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
14340: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
14341: }
1.227 brouard 14342: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
14343: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 14344:
1.235 brouard 14345: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
14346: if (cptcovn < 1){i1=1;}
14347:
1.334 brouard 14348: for(nres=1; nres <= nresult; nres++) /* For each resultline, find the combination and output results according to the values of dummies and then quanti. */
14349: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying. For each nres and each value at position k
14350: * we know Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline
14351: * Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline
14352: * and Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
14353: /* */
14354: 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 14355: continue;
1.321 brouard 14356: printf("\n# model %s \n#****** Result for:", model);
14357: fprintf(ficrest,"\n# model %s \n#****** Result for:", model);
14358: fprintf(ficlog,"\n# model %s \n#****** Result for:", model);
1.334 brouard 14359: /* It might not be a good idea to mix dummies and quantitative */
14360: /* 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 *\/ */
14361: 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 */
14362: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /\* Output by variables in the resultline *\/ */
14363: /* Tvaraff[j] is the name of the dummy variable in position j in the equation model:
14364: * Tvaraff[1]@9={4, 3, 0, 0, 0, 0, 0, 0, 0}, in model=V5+V4+V3+V4*V3+V5*age
14365: * (V5 is quanti) V4 and V3 are dummies
14366: * TnsdVar[4] is the position 1 and TnsdVar[3]=2 in codtabm(k,l)(V4 V3)=V4 V3
14367: * l=1 l=2
14368: * k=1 1 1 0 0
14369: * k=2 2 1 1 0
14370: * k=3 [1] [2] 0 1
14371: * k=4 2 2 1 1
14372: * If nres=1 result: V3=1 V4=0 then k=3 and outputs
14373: * If nres=2 result: V4=1 V3=0 then k=2 and outputs
14374: * nres=1 =>k=3 j=1 V4= nbcode[4][codtabm(3,1)=1)=0; j=2 V3= nbcode[3][codtabm(3,2)=2]=1
14375: * nres=2 =>k=2 j=1 V4= nbcode[4][codtabm(2,1)=2)=1; j=2 V3= nbcode[3][codtabm(2,2)=1]=0
14376: */
14377: /* Tvresult[nres][j] Name of the variable at position j in this resultline */
14378: /* Tresult[nres][j] Value of this variable at position j could be a float if quantitative */
14379: /* We give up with the combinations!! */
1.342 brouard 14380: /* if(debugILK) */
14381: /* printf("\n j=%d In computing T_ Dummy[modelresult[%d][%d]]=%d, modelresult[%d][%d]=%d cptcovs=%d, cptcoveff=%d Fixed[modelresult[nres][j]]=%d\n", j, nres, j, Dummy[modelresult[nres][j]],nres,j,modelresult[nres][j],cptcovs, cptcoveff,Fixed[modelresult[nres][j]]); /\* end if dummy or quanti *\/ */
1.334 brouard 14382:
14383: if(Dummy[modelresult[nres][j]]==0){/* Dummy variable of the variable in position modelresult in the model corresponding to j in resultline */
1.344 brouard 14384: /* printf("V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][j]); /\* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline *\/ */ /* TinvDoQresult[nres][Name of the variable] */
14385: printf("V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); /* Output of each value for the combination TKresult[nres], ordered by the covariate values in the resultline */
14386: fprintf(ficlog,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
14387: fprintf(ficrest,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
1.334 brouard 14388: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
14389: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
14390: }else{
14391: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
14392: }
14393: /* fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14394: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14395: }else if(Dummy[modelresult[nres][j]]==1){ /* Quanti variable */
14396: /* For each selected (single) quantitative value */
1.337 brouard 14397: printf(" V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
14398: fprintf(ficlog," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
14399: fprintf(ficrest," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
1.334 brouard 14400: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
14401: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
14402: }else{
14403: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
14404: }
14405: }else{
14406: 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 */
14407: 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 */
14408: exit(1);
14409: }
1.335 brouard 14410: } /* End loop for each variable in the resultline */
1.334 brouard 14411: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
14412: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /\* Wrong j is not in the equation model *\/ */
14413: /* fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
14414: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
14415: /* } */
1.208 brouard 14416: fprintf(ficrest,"******\n");
1.227 brouard 14417: fprintf(ficlog,"******\n");
14418: printf("******\n");
1.208 brouard 14419:
14420: fprintf(ficresstdeij,"\n#****** ");
14421: fprintf(ficrescveij,"\n#****** ");
1.337 brouard 14422: /* It could have been: for(j=1;j<=cptcoveff;j++) {printf("V=%d=%lg",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);} */
14423: /* But it won't be sorted and depends on how the resultline is ordered */
1.225 brouard 14424: for(j=1;j<=cptcoveff;j++) {
1.334 brouard 14425: fprintf(ficresstdeij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
14426: /* fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14427: /* fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14428: }
14429: 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 14430: fprintf(ficresstdeij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
14431: fprintf(ficrescveij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
1.235 brouard 14432: }
1.208 brouard 14433: fprintf(ficresstdeij,"******\n");
14434: fprintf(ficrescveij,"******\n");
14435:
14436: fprintf(ficresvij,"\n#****** ");
1.238 brouard 14437: /* pstamp(ficresvij); */
1.225 brouard 14438: for(j=1;j<=cptcoveff;j++)
1.335 brouard 14439: fprintf(ficresvij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
14440: /* fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[TnsdVar[Tvaraff[j]]])]); */
1.235 brouard 14441: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.332 brouard 14442: /* fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); /\* To solve *\/ */
1.337 brouard 14443: fprintf(ficresvij," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /* Solved */
1.235 brouard 14444: }
1.208 brouard 14445: fprintf(ficresvij,"******\n");
14446:
14447: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
14448: oldm=oldms;savm=savms;
1.235 brouard 14449: printf(" cvevsij ");
14450: fprintf(ficlog, " cvevsij ");
14451: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 14452: printf(" end cvevsij \n ");
14453: fprintf(ficlog, " end cvevsij \n ");
14454:
14455: /*
14456: */
14457: /* goto endfree; */
14458:
14459: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
14460: pstamp(ficrest);
14461:
1.269 brouard 14462: epj=vector(1,nlstate+1);
1.208 brouard 14463: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 14464: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
14465: cptcod= 0; /* To be deleted */
14466: printf("varevsij vpopbased=%d \n",vpopbased);
14467: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 14468: 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 14469: 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 ");
14470: if(vpopbased==1)
14471: 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);
14472: else
1.288 brouard 14473: fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n");
1.335 brouard 14474: fprintf(ficrest,"# Age popbased mobilav e.. (std) "); /* Adding covariate values? */
1.227 brouard 14475: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
14476: fprintf(ficrest,"\n");
14477: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 14478: printf("Computing age specific forward period (stable) prevalences in each health state \n");
14479: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 14480: for(age=bage; age <=fage ;age++){
1.235 brouard 14481: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 14482: if (vpopbased==1) {
14483: if(mobilav ==0){
14484: for(i=1; i<=nlstate;i++)
14485: prlim[i][i]=probs[(int)age][i][k];
14486: }else{ /* mobilav */
14487: for(i=1; i<=nlstate;i++)
14488: prlim[i][i]=mobaverage[(int)age][i][k];
14489: }
14490: }
1.219 brouard 14491:
1.227 brouard 14492: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
14493: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
14494: /* printf(" age %4.0f ",age); */
14495: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
14496: for(i=1, epj[j]=0.;i <=nlstate;i++) {
14497: epj[j] += prlim[i][i]*eij[i][j][(int)age];
14498: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
14499: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
14500: }
14501: epj[nlstate+1] +=epj[j];
14502: }
14503: /* printf(" age %4.0f \n",age); */
1.219 brouard 14504:
1.227 brouard 14505: for(i=1, vepp=0.;i <=nlstate;i++)
14506: for(j=1;j <=nlstate;j++)
14507: vepp += vareij[i][j][(int)age];
14508: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
14509: for(j=1;j <=nlstate;j++){
14510: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
14511: }
14512: fprintf(ficrest,"\n");
14513: }
1.208 brouard 14514: } /* End vpopbased */
1.269 brouard 14515: free_vector(epj,1,nlstate+1);
1.208 brouard 14516: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
14517: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 14518: printf("done selection\n");fflush(stdout);
14519: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 14520:
1.335 brouard 14521: } /* End k selection or end covariate selection for nres */
1.227 brouard 14522:
14523: printf("done State-specific expectancies\n");fflush(stdout);
14524: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
14525:
1.335 brouard 14526: /* variance-covariance of forward period prevalence */
1.269 brouard 14527: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 14528:
1.227 brouard 14529:
1.290 brouard 14530: free_vector(weight,firstobs,lastobs);
1.330 brouard 14531: free_imatrix(Tvardk,1,NCOVMAX,1,2);
1.227 brouard 14532: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 14533: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
14534: free_matrix(anint,1,maxwav,firstobs,lastobs);
14535: free_matrix(mint,1,maxwav,firstobs,lastobs);
14536: free_ivector(cod,firstobs,lastobs);
1.227 brouard 14537: free_ivector(tab,1,NCOVMAX);
14538: fclose(ficresstdeij);
14539: fclose(ficrescveij);
14540: fclose(ficresvij);
14541: fclose(ficrest);
14542: fclose(ficpar);
14543:
14544:
1.126 brouard 14545: /*---------- End : free ----------------*/
1.219 brouard 14546: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 14547: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
14548: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 14549: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
14550: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 14551: } /* mle==-3 arrives here for freeing */
1.227 brouard 14552: /* endfree:*/
14553: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
14554: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
14555: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.341 brouard 14556: /* if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs); */
14557: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs);
1.290 brouard 14558: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
14559: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
14560: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 14561: free_matrix(matcov,1,npar,1,npar);
14562: free_matrix(hess,1,npar,1,npar);
14563: /*free_vector(delti,1,npar);*/
14564: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
14565: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 14566: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 14567: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
14568:
14569: free_ivector(ncodemax,1,NCOVMAX);
14570: free_ivector(ncodemaxwundef,1,NCOVMAX);
14571: free_ivector(Dummy,-1,NCOVMAX);
14572: free_ivector(Fixed,-1,NCOVMAX);
1.238 brouard 14573: free_ivector(DummyV,1,NCOVMAX);
14574: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 14575: free_ivector(Typevar,-1,NCOVMAX);
14576: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 14577: free_ivector(TvarsQ,1,NCOVMAX);
14578: free_ivector(TvarsQind,1,NCOVMAX);
14579: free_ivector(TvarsD,1,NCOVMAX);
1.330 brouard 14580: free_ivector(TnsdVar,1,NCOVMAX);
1.234 brouard 14581: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 14582: free_ivector(TvarFD,1,NCOVMAX);
14583: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 14584: free_ivector(TvarF,1,NCOVMAX);
14585: free_ivector(TvarFind,1,NCOVMAX);
14586: free_ivector(TvarV,1,NCOVMAX);
14587: free_ivector(TvarVind,1,NCOVMAX);
14588: free_ivector(TvarA,1,NCOVMAX);
14589: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 14590: free_ivector(TvarFQ,1,NCOVMAX);
14591: free_ivector(TvarFQind,1,NCOVMAX);
14592: free_ivector(TvarVD,1,NCOVMAX);
14593: free_ivector(TvarVDind,1,NCOVMAX);
14594: free_ivector(TvarVQ,1,NCOVMAX);
14595: free_ivector(TvarVQind,1,NCOVMAX);
1.339 brouard 14596: free_ivector(TvarVV,1,NCOVMAX);
14597: free_ivector(TvarVVind,1,NCOVMAX);
14598:
1.230 brouard 14599: free_ivector(Tvarsel,1,NCOVMAX);
14600: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 14601: free_ivector(Tposprod,1,NCOVMAX);
14602: free_ivector(Tprod,1,NCOVMAX);
14603: free_ivector(Tvaraff,1,NCOVMAX);
1.338 brouard 14604: free_ivector(invalidvarcomb,0,ncovcombmax);
1.227 brouard 14605: free_ivector(Tage,1,NCOVMAX);
14606: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 14607: free_ivector(TmodelInvind,1,NCOVMAX);
14608: free_ivector(TmodelInvQind,1,NCOVMAX);
1.332 brouard 14609:
14610: free_matrix(precov, 1,MAXRESULTLINESPONE,1,NCOVMAX+1); /* Could be elsewhere ?*/
14611:
1.227 brouard 14612: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
14613: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 14614: fflush(fichtm);
14615: fflush(ficgp);
14616:
1.227 brouard 14617:
1.126 brouard 14618: if((nberr >0) || (nbwarn>0)){
1.216 brouard 14619: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
14620: 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 14621: }else{
14622: printf("End of Imach\n");
14623: fprintf(ficlog,"End of Imach\n");
14624: }
14625: printf("See log file on %s\n",filelog);
14626: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 14627: /*(void) gettimeofday(&end_time,&tzp);*/
14628: rend_time = time(NULL);
14629: end_time = *localtime(&rend_time);
14630: /* tml = *localtime(&end_time.tm_sec); */
14631: strcpy(strtend,asctime(&end_time));
1.126 brouard 14632: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
14633: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 14634: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 14635:
1.157 brouard 14636: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
14637: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
14638: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 14639: /* printf("Total time was %d uSec.\n", total_usecs);*/
14640: /* if(fileappend(fichtm,optionfilehtm)){ */
14641: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
14642: fclose(fichtm);
14643: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
14644: fclose(fichtmcov);
14645: fclose(ficgp);
14646: fclose(ficlog);
14647: /*------ End -----------*/
1.227 brouard 14648:
1.281 brouard 14649:
14650: /* Executes gnuplot */
1.227 brouard 14651:
14652: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 14653: #ifdef WIN32
1.227 brouard 14654: if (_chdir(pathcd) != 0)
14655: printf("Can't move to directory %s!\n",path);
14656: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 14657: #else
1.227 brouard 14658: if(chdir(pathcd) != 0)
14659: printf("Can't move to directory %s!\n", path);
14660: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 14661: #endif
1.126 brouard 14662: printf("Current directory %s!\n",pathcd);
14663: /*strcat(plotcmd,CHARSEPARATOR);*/
14664: sprintf(plotcmd,"gnuplot");
1.157 brouard 14665: #ifdef _WIN32
1.126 brouard 14666: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
14667: #endif
14668: if(!stat(plotcmd,&info)){
1.158 brouard 14669: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 14670: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 14671: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 14672: }else
14673: strcpy(pplotcmd,plotcmd);
1.157 brouard 14674: #ifdef __unix
1.126 brouard 14675: strcpy(plotcmd,GNUPLOTPROGRAM);
14676: if(!stat(plotcmd,&info)){
1.158 brouard 14677: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 14678: }else
14679: strcpy(pplotcmd,plotcmd);
14680: #endif
14681: }else
14682: strcpy(pplotcmd,plotcmd);
14683:
14684: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 14685: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 brouard 14686: strcpy(pplotcmd,plotcmd);
1.227 brouard 14687:
1.126 brouard 14688: if((outcmd=system(plotcmd)) != 0){
1.292 brouard 14689: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 14690: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 14691: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 brouard 14692: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 14693: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 brouard 14694: strcpy(plotcmd,pplotcmd);
14695: }
1.126 brouard 14696: }
1.158 brouard 14697: printf(" Successful, please wait...");
1.126 brouard 14698: while (z[0] != 'q') {
14699: /* chdir(path); */
1.154 brouard 14700: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 14701: scanf("%s",z);
14702: /* if (z[0] == 'c') system("./imach"); */
14703: if (z[0] == 'e') {
1.158 brouard 14704: #ifdef __APPLE__
1.152 brouard 14705: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 14706: #elif __linux
14707: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 14708: #else
1.152 brouard 14709: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 14710: #endif
14711: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
14712: system(pplotcmd);
1.126 brouard 14713: }
14714: else if (z[0] == 'g') system(plotcmd);
14715: else if (z[0] == 'q') exit(0);
14716: }
1.227 brouard 14717: end:
1.126 brouard 14718: while (z[0] != 'q') {
1.195 brouard 14719: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 14720: scanf("%s",z);
14721: }
1.283 brouard 14722: printf("End\n");
1.282 brouard 14723: exit(0);
1.126 brouard 14724: }
FreeBSD-CVSweb <freebsd-cvsweb@FreeBSD.org>
![[BACK]](/icons/small/back.gif){kind=icon}
Return to imach.c CVS log ![[TXT]](/icons/small/text.gif){kind=icon}
![[DIR]](/icons/small/dir.gif){kind=icon}
Up to [Local Repository] / imach / src