Annotation of imach/src/imach.c, revision 1.349
1.348 brouard 1: /* $Id: imach.c,v 1.347 2022/09/18 14:36:44 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.348 brouard 4: Revision 1.347 2022/09/18 14:36:44 brouard
5: Summary: version 0.99r42
6:
1.347 brouard 7: Revision 1.346 2022/09/16 13:52:36 brouard
8: * src/imach.c (Module): 0.99r41 Was an error when product of timevarying and fixed. Using FixedV[of name] now. Thank you Feinuo
9:
1.346 brouard 10: Revision 1.345 2022/09/16 13:40:11 brouard
11: Summary: Version 0.99r41
12:
13: * imach.c (Module): 0.99r41 Was an error when product of timevarying and fixed. Using FixedV[of name] now. Thank you Feinuo
14:
1.345 brouard 15: Revision 1.344 2022/09/14 19:33:30 brouard
16: Summary: version 0.99r40
17:
18: * imach.c (Module): Fixing names of variables in T_ (thanks to Feinuo)
19:
1.344 brouard 20: Revision 1.343 2022/09/14 14:22:16 brouard
21: Summary: version 0.99r39
22:
23: * imach.c (Module): Version 0.99r39 with colored dummy covariates
24: (fixed or time varying), using new last columns of
25: ILK_parameter.txt file.
26:
1.343 brouard 27: Revision 1.342 2022/09/11 19:54:09 brouard
28: Summary: 0.99r38
29:
30: * imach.c (Module): Adding timevarying products of any kinds,
31: should work before shifting cotvar from ncovcol+nqv columns in
32: order to have a correspondance between the column of cotvar and
33: the id of column.
34: (Module): Some cleaning and adding covariates in ILK.txt
35:
1.342 brouard 36: Revision 1.341 2022/09/11 07:58:42 brouard
37: Summary: Version 0.99r38
38:
39: After adding change in cotvar.
40:
1.341 brouard 41: Revision 1.340 2022/09/11 07:53:11 brouard
42: Summary: Version imach 0.99r37
43:
44: * imach.c (Module): Adding timevarying products of any kinds,
45: should work before shifting cotvar from ncovcol+nqv columns in
46: order to have a correspondance between the column of cotvar and
47: the id of column.
48:
1.340 brouard 49: Revision 1.339 2022/09/09 17:55:22 brouard
50: Summary: version 0.99r37
51:
52: * imach.c (Module): Many improvements for fixing products of fixed
53: timevarying as well as fixed * fixed, and test with quantitative
54: covariate.
55:
1.339 brouard 56: Revision 1.338 2022/09/04 17:40:33 brouard
57: Summary: 0.99r36
58:
59: * imach.c (Module): Now the easy runs i.e. without result or
60: model=1+age only did not work. The defautl combination should be 1
61: and not 0 because everything hasn't been tranformed yet.
62:
1.338 brouard 63: Revision 1.337 2022/09/02 14:26:02 brouard
64: Summary: version 0.99r35
65:
66: * src/imach.c: Version 0.99r35 because it outputs same results with
67: 1+age+V1+V1*age for females and 1+age for females only
68: (education=1 noweight)
69:
1.337 brouard 70: Revision 1.336 2022/08/31 09:52:36 brouard
71: *** empty log message ***
72:
1.336 brouard 73: Revision 1.335 2022/08/31 08:23:16 brouard
74: Summary: improvements...
75:
1.335 brouard 76: Revision 1.334 2022/08/25 09:08:41 brouard
77: Summary: In progress for quantitative
78:
1.334 brouard 79: Revision 1.333 2022/08/21 09:10:30 brouard
80: * src/imach.c (Module): Version 0.99r33 A lot of changes in
81: reassigning covariates: my first idea was that people will always
82: use the first covariate V1 into the model but in fact they are
83: producing data with many covariates and can use an equation model
84: with some of the covariate; it means that in a model V2+V3 instead
85: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
86: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
87: the equation model is restricted to two variables only (V2, V3)
88: and the combination for V2 should be codtabm(k,1) instead of
89: (codtabm(k,2), and the code should be
90: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
91: made. All of these should be simplified once a day like we did in
92: hpxij() for example by using precov[nres] which is computed in
93: decoderesult for each nres of each resultline. Loop should be done
94: on the equation model globally by distinguishing only product with
95: age (which are changing with age) and no more on type of
96: covariates, single dummies, single covariates.
97:
1.333 brouard 98: Revision 1.332 2022/08/21 09:06:25 brouard
99: Summary: Version 0.99r33
100:
101: * src/imach.c (Module): Version 0.99r33 A lot of changes in
102: reassigning covariates: my first idea was that people will always
103: use the first covariate V1 into the model but in fact they are
104: producing data with many covariates and can use an equation model
105: with some of the covariate; it means that in a model V2+V3 instead
106: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
107: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
108: the equation model is restricted to two variables only (V2, V3)
109: and the combination for V2 should be codtabm(k,1) instead of
110: (codtabm(k,2), and the code should be
111: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
112: made. All of these should be simplified once a day like we did in
113: hpxij() for example by using precov[nres] which is computed in
114: decoderesult for each nres of each resultline. Loop should be done
115: on the equation model globally by distinguishing only product with
116: age (which are changing with age) and no more on type of
117: covariates, single dummies, single covariates.
118:
1.332 brouard 119: Revision 1.331 2022/08/07 05:40:09 brouard
120: *** empty log message ***
121:
1.331 brouard 122: Revision 1.330 2022/08/06 07:18:25 brouard
123: Summary: last 0.99r31
124:
125: * imach.c (Module): Version of imach using partly decoderesult to rebuild xpxij function
126:
1.330 brouard 127: Revision 1.329 2022/08/03 17:29:54 brouard
128: * imach.c (Module): Many errors in graphs fixed with Vn*age covariates.
129:
1.329 brouard 130: Revision 1.328 2022/07/27 17:40:48 brouard
131: Summary: valgrind bug fixed by initializing to zero DummyV as well as Tage
132:
1.328 brouard 133: Revision 1.327 2022/07/27 14:47:35 brouard
134: Summary: Still a problem for one-step probabilities in case of quantitative variables
135:
1.327 brouard 136: Revision 1.326 2022/07/26 17:33:55 brouard
137: Summary: some test with nres=1
138:
1.326 brouard 139: Revision 1.325 2022/07/25 14:27:23 brouard
140: Summary: r30
141:
142: * imach.c (Module): Error cptcovn instead of nsd in bmij (was
143: coredumped, revealed by Feiuno, thank you.
144:
1.325 brouard 145: Revision 1.324 2022/07/23 17:44:26 brouard
146: *** empty log message ***
147:
1.324 brouard 148: Revision 1.323 2022/07/22 12:30:08 brouard
149: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
150:
1.323 brouard 151: Revision 1.322 2022/07/22 12:27:48 brouard
152: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
153:
1.322 brouard 154: Revision 1.321 2022/07/22 12:04:24 brouard
155: Summary: r28
156:
157: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
158:
1.321 brouard 159: Revision 1.320 2022/06/02 05:10:11 brouard
160: *** empty log message ***
161:
1.320 brouard 162: Revision 1.319 2022/06/02 04:45:11 brouard
163: * imach.c (Module): Adding the Wald tests from the log to the main
164: htm for better display of the maximum likelihood estimators.
165:
1.319 brouard 166: Revision 1.318 2022/05/24 08:10:59 brouard
167: * imach.c (Module): Some attempts to find a bug of wrong estimates
168: of confidencce intervals with product in the equation modelC
169:
1.318 brouard 170: Revision 1.317 2022/05/15 15:06:23 brouard
171: * imach.c (Module): Some minor improvements
172:
1.317 brouard 173: Revision 1.316 2022/05/11 15:11:31 brouard
174: Summary: r27
175:
1.316 brouard 176: Revision 1.315 2022/05/11 15:06:32 brouard
177: *** empty log message ***
178:
1.315 brouard 179: Revision 1.314 2022/04/13 17:43:09 brouard
180: * imach.c (Module): Adding link to text data files
181:
1.314 brouard 182: Revision 1.313 2022/04/11 15:57:42 brouard
183: * imach.c (Module): Error in rewriting the 'r' file with yearsfproj or yearsbproj fixed
184:
1.313 brouard 185: Revision 1.312 2022/04/05 21:24:39 brouard
186: *** empty log message ***
187:
1.312 brouard 188: Revision 1.311 2022/04/05 21:03:51 brouard
189: Summary: Fixed quantitative covariates
190:
191: Fixed covariates (dummy or quantitative)
192: with missing values have never been allowed but are ERRORS and
193: program quits. Standard deviations of fixed covariates were
194: wrongly computed. Mean and standard deviations of time varying
195: covariates are still not computed.
196:
1.311 brouard 197: Revision 1.310 2022/03/17 08:45:53 brouard
198: Summary: 99r25
199:
200: Improving detection of errors: result lines should be compatible with
201: the model.
202:
1.310 brouard 203: Revision 1.309 2021/05/20 12:39:14 brouard
204: Summary: Version 0.99r24
205:
1.309 brouard 206: Revision 1.308 2021/03/31 13:11:57 brouard
207: Summary: Version 0.99r23
208:
209:
210: * imach.c (Module): Still bugs in the result loop. Thank to Holly Benett
211:
1.308 brouard 212: Revision 1.307 2021/03/08 18:11:32 brouard
213: Summary: 0.99r22 fixed bug on result:
214:
1.307 brouard 215: Revision 1.306 2021/02/20 15:44:02 brouard
216: Summary: Version 0.99r21
217:
218: * imach.c (Module): Fix bug on quitting after result lines!
219: (Module): Version 0.99r21
220:
1.306 brouard 221: Revision 1.305 2021/02/20 15:28:30 brouard
222: * imach.c (Module): Fix bug on quitting after result lines!
223:
1.305 brouard 224: Revision 1.304 2021/02/12 11:34:20 brouard
225: * imach.c (Module): The use of a Windows BOM (huge) file is now an error
226:
1.304 brouard 227: Revision 1.303 2021/02/11 19:50:15 brouard
228: * (Module): imach.c Someone entered 'results:' instead of 'result:'. Now it is an error which is printed.
229:
1.303 brouard 230: Revision 1.302 2020/02/22 21:00:05 brouard
231: * (Module): imach.c Update mle=-3 (for computing Life expectancy
232: and life table from the data without any state)
233:
1.302 brouard 234: Revision 1.301 2019/06/04 13:51:20 brouard
235: Summary: Error in 'r'parameter file backcast yearsbproj instead of yearsfproj
236:
1.301 brouard 237: Revision 1.300 2019/05/22 19:09:45 brouard
238: Summary: version 0.99r19 of May 2019
239:
1.300 brouard 240: Revision 1.299 2019/05/22 18:37:08 brouard
241: Summary: Cleaned 0.99r19
242:
1.299 brouard 243: Revision 1.298 2019/05/22 18:19:56 brouard
244: *** empty log message ***
245:
1.298 brouard 246: Revision 1.297 2019/05/22 17:56:10 brouard
247: Summary: Fix bug by moving date2dmy and nhstepm which gaefin=-1
248:
1.297 brouard 249: Revision 1.296 2019/05/20 13:03:18 brouard
250: Summary: Projection syntax simplified
251:
252:
253: We can now start projections, forward or backward, from the mean date
254: of inteviews up to or down to a number of years of projection:
255: prevforecast=1 yearsfproj=15.3 mobil_average=0
256: or
257: prevforecast=1 starting-proj-date=1/1/2007 final-proj-date=12/31/2017 mobil_average=0
258: or
259: prevbackcast=1 yearsbproj=12.3 mobil_average=1
260: or
261: prevbackcast=1 starting-back-date=1/10/1999 final-back-date=1/1/1985 mobil_average=1
262:
1.296 brouard 263: Revision 1.295 2019/05/18 09:52:50 brouard
264: Summary: doxygen tex bug
265:
1.295 brouard 266: Revision 1.294 2019/05/16 14:54:33 brouard
267: Summary: There was some wrong lines added
268:
1.294 brouard 269: Revision 1.293 2019/05/09 15:17:34 brouard
270: *** empty log message ***
271:
1.293 brouard 272: Revision 1.292 2019/05/09 14:17:20 brouard
273: Summary: Some updates
274:
1.292 brouard 275: Revision 1.291 2019/05/09 13:44:18 brouard
276: Summary: Before ncovmax
277:
1.291 brouard 278: Revision 1.290 2019/05/09 13:39:37 brouard
279: Summary: 0.99r18 unlimited number of individuals
280:
281: 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.
282:
1.290 brouard 283: Revision 1.289 2018/12/13 09:16:26 brouard
284: Summary: Bug for young ages (<-30) will be in r17
285:
1.289 brouard 286: Revision 1.288 2018/05/02 20:58:27 brouard
287: Summary: Some bugs fixed
288:
1.288 brouard 289: Revision 1.287 2018/05/01 17:57:25 brouard
290: Summary: Bug fixed by providing frequencies only for non missing covariates
291:
1.287 brouard 292: Revision 1.286 2018/04/27 14:27:04 brouard
293: Summary: some minor bugs
294:
1.286 brouard 295: Revision 1.285 2018/04/21 21:02:16 brouard
296: Summary: Some bugs fixed, valgrind tested
297:
1.285 brouard 298: Revision 1.284 2018/04/20 05:22:13 brouard
299: Summary: Computing mean and stdeviation of fixed quantitative variables
300:
1.284 brouard 301: Revision 1.283 2018/04/19 14:49:16 brouard
302: Summary: Some minor bugs fixed
303:
1.283 brouard 304: Revision 1.282 2018/02/27 22:50:02 brouard
305: *** empty log message ***
306:
1.282 brouard 307: Revision 1.281 2018/02/27 19:25:23 brouard
308: Summary: Adding second argument for quitting
309:
1.281 brouard 310: Revision 1.280 2018/02/21 07:58:13 brouard
311: Summary: 0.99r15
312:
313: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
314:
1.280 brouard 315: Revision 1.279 2017/07/20 13:35:01 brouard
316: Summary: temporary working
317:
1.279 brouard 318: Revision 1.278 2017/07/19 14:09:02 brouard
319: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
320:
1.278 brouard 321: Revision 1.277 2017/07/17 08:53:49 brouard
322: Summary: BOM files can be read now
323:
1.277 brouard 324: Revision 1.276 2017/06/30 15:48:31 brouard
325: Summary: Graphs improvements
326:
1.276 brouard 327: Revision 1.275 2017/06/30 13:39:33 brouard
328: Summary: Saito's color
329:
1.275 brouard 330: Revision 1.274 2017/06/29 09:47:08 brouard
331: Summary: Version 0.99r14
332:
1.274 brouard 333: Revision 1.273 2017/06/27 11:06:02 brouard
334: Summary: More documentation on projections
335:
1.273 brouard 336: Revision 1.272 2017/06/27 10:22:40 brouard
337: Summary: Color of backprojection changed from 6 to 5(yellow)
338:
1.272 brouard 339: Revision 1.271 2017/06/27 10:17:50 brouard
340: Summary: Some bug with rint
341:
1.271 brouard 342: Revision 1.270 2017/05/24 05:45:29 brouard
343: *** empty log message ***
344:
1.270 brouard 345: Revision 1.269 2017/05/23 08:39:25 brouard
346: Summary: Code into subroutine, cleanings
347:
1.269 brouard 348: Revision 1.268 2017/05/18 20:09:32 brouard
349: Summary: backprojection and confidence intervals of backprevalence
350:
1.268 brouard 351: Revision 1.267 2017/05/13 10:25:05 brouard
352: Summary: temporary save for backprojection
353:
1.267 brouard 354: Revision 1.266 2017/05/13 07:26:12 brouard
355: Summary: Version 0.99r13 (improvements and bugs fixed)
356:
1.266 brouard 357: Revision 1.265 2017/04/26 16:22:11 brouard
358: Summary: imach 0.99r13 Some bugs fixed
359:
1.265 brouard 360: Revision 1.264 2017/04/26 06:01:29 brouard
361: Summary: Labels in graphs
362:
1.264 brouard 363: Revision 1.263 2017/04/24 15:23:15 brouard
364: Summary: to save
365:
1.263 brouard 366: Revision 1.262 2017/04/18 16:48:12 brouard
367: *** empty log message ***
368:
1.262 brouard 369: Revision 1.261 2017/04/05 10:14:09 brouard
370: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
371:
1.261 brouard 372: Revision 1.260 2017/04/04 17:46:59 brouard
373: Summary: Gnuplot indexations fixed (humm)
374:
1.260 brouard 375: Revision 1.259 2017/04/04 13:01:16 brouard
376: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
377:
1.259 brouard 378: Revision 1.258 2017/04/03 10:17:47 brouard
379: Summary: Version 0.99r12
380:
381: Some cleanings, conformed with updated documentation.
382:
1.258 brouard 383: Revision 1.257 2017/03/29 16:53:30 brouard
384: Summary: Temp
385:
1.257 brouard 386: Revision 1.256 2017/03/27 05:50:23 brouard
387: Summary: Temporary
388:
1.256 brouard 389: Revision 1.255 2017/03/08 16:02:28 brouard
390: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
391:
1.255 brouard 392: Revision 1.254 2017/03/08 07:13:00 brouard
393: Summary: Fixing data parameter line
394:
1.254 brouard 395: Revision 1.253 2016/12/15 11:59:41 brouard
396: Summary: 0.99 in progress
397:
1.253 brouard 398: Revision 1.252 2016/09/15 21:15:37 brouard
399: *** empty log message ***
400:
1.252 brouard 401: Revision 1.251 2016/09/15 15:01:13 brouard
402: Summary: not working
403:
1.251 brouard 404: Revision 1.250 2016/09/08 16:07:27 brouard
405: Summary: continue
406:
1.250 brouard 407: Revision 1.249 2016/09/07 17:14:18 brouard
408: Summary: Starting values from frequencies
409:
1.249 brouard 410: Revision 1.248 2016/09/07 14:10:18 brouard
411: *** empty log message ***
412:
1.248 brouard 413: Revision 1.247 2016/09/02 11:11:21 brouard
414: *** empty log message ***
415:
1.247 brouard 416: Revision 1.246 2016/09/02 08:49:22 brouard
417: *** empty log message ***
418:
1.246 brouard 419: Revision 1.245 2016/09/02 07:25:01 brouard
420: *** empty log message ***
421:
1.245 brouard 422: Revision 1.244 2016/09/02 07:17:34 brouard
423: *** empty log message ***
424:
1.244 brouard 425: Revision 1.243 2016/09/02 06:45:35 brouard
426: *** empty log message ***
427:
1.243 brouard 428: Revision 1.242 2016/08/30 15:01:20 brouard
429: Summary: Fixing a lots
430:
1.242 brouard 431: Revision 1.241 2016/08/29 17:17:25 brouard
432: Summary: gnuplot problem in Back projection to fix
433:
1.241 brouard 434: Revision 1.240 2016/08/29 07:53:18 brouard
435: Summary: Better
436:
1.240 brouard 437: Revision 1.239 2016/08/26 15:51:03 brouard
438: Summary: Improvement in Powell output in order to copy and paste
439:
440: Author:
441:
1.239 brouard 442: Revision 1.238 2016/08/26 14:23:35 brouard
443: Summary: Starting tests of 0.99
444:
1.238 brouard 445: Revision 1.237 2016/08/26 09:20:19 brouard
446: Summary: to valgrind
447:
1.237 brouard 448: Revision 1.236 2016/08/25 10:50:18 brouard
449: *** empty log message ***
450:
1.236 brouard 451: Revision 1.235 2016/08/25 06:59:23 brouard
452: *** empty log message ***
453:
1.235 brouard 454: Revision 1.234 2016/08/23 16:51:20 brouard
455: *** empty log message ***
456:
1.234 brouard 457: Revision 1.233 2016/08/23 07:40:50 brouard
458: Summary: not working
459:
1.233 brouard 460: Revision 1.232 2016/08/22 14:20:21 brouard
461: Summary: not working
462:
1.232 brouard 463: Revision 1.231 2016/08/22 07:17:15 brouard
464: Summary: not working
465:
1.231 brouard 466: Revision 1.230 2016/08/22 06:55:53 brouard
467: Summary: Not working
468:
1.230 brouard 469: Revision 1.229 2016/07/23 09:45:53 brouard
470: Summary: Completing for func too
471:
1.229 brouard 472: Revision 1.228 2016/07/22 17:45:30 brouard
473: Summary: Fixing some arrays, still debugging
474:
1.227 brouard 475: Revision 1.226 2016/07/12 18:42:34 brouard
476: Summary: temp
477:
1.226 brouard 478: Revision 1.225 2016/07/12 08:40:03 brouard
479: Summary: saving but not running
480:
1.225 brouard 481: Revision 1.224 2016/07/01 13:16:01 brouard
482: Summary: Fixes
483:
1.224 brouard 484: Revision 1.223 2016/02/19 09:23:35 brouard
485: Summary: temporary
486:
1.223 brouard 487: Revision 1.222 2016/02/17 08:14:50 brouard
488: Summary: Probably last 0.98 stable version 0.98r6
489:
1.222 brouard 490: Revision 1.221 2016/02/15 23:35:36 brouard
491: Summary: minor bug
492:
1.220 brouard 493: Revision 1.219 2016/02/15 00:48:12 brouard
494: *** empty log message ***
495:
1.219 brouard 496: Revision 1.218 2016/02/12 11:29:23 brouard
497: Summary: 0.99 Back projections
498:
1.218 brouard 499: Revision 1.217 2015/12/23 17:18:31 brouard
500: Summary: Experimental backcast
501:
1.217 brouard 502: Revision 1.216 2015/12/18 17:32:11 brouard
503: Summary: 0.98r4 Warning and status=-2
504:
505: Version 0.98r4 is now:
506: - displaying an error when status is -1, date of interview unknown and date of death known;
507: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
508: Older changes concerning s=-2, dating from 2005 have been supersed.
509:
1.216 brouard 510: Revision 1.215 2015/12/16 08:52:24 brouard
511: Summary: 0.98r4 working
512:
1.215 brouard 513: Revision 1.214 2015/12/16 06:57:54 brouard
514: Summary: temporary not working
515:
1.214 brouard 516: Revision 1.213 2015/12/11 18:22:17 brouard
517: Summary: 0.98r4
518:
1.213 brouard 519: Revision 1.212 2015/11/21 12:47:24 brouard
520: Summary: minor typo
521:
1.212 brouard 522: Revision 1.211 2015/11/21 12:41:11 brouard
523: Summary: 0.98r3 with some graph of projected cross-sectional
524:
525: Author: Nicolas Brouard
526:
1.211 brouard 527: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 528: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 529: Summary: Adding ftolpl parameter
530: Author: N Brouard
531:
532: We had difficulties to get smoothed confidence intervals. It was due
533: to the period prevalence which wasn't computed accurately. The inner
534: parameter ftolpl is now an outer parameter of the .imach parameter
535: file after estepm. If ftolpl is small 1.e-4 and estepm too,
536: computation are long.
537:
1.209 brouard 538: Revision 1.208 2015/11/17 14:31:57 brouard
539: Summary: temporary
540:
1.208 brouard 541: Revision 1.207 2015/10/27 17:36:57 brouard
542: *** empty log message ***
543:
1.207 brouard 544: Revision 1.206 2015/10/24 07:14:11 brouard
545: *** empty log message ***
546:
1.206 brouard 547: Revision 1.205 2015/10/23 15:50:53 brouard
548: Summary: 0.98r3 some clarification for graphs on likelihood contributions
549:
1.205 brouard 550: Revision 1.204 2015/10/01 16:20:26 brouard
551: Summary: Some new graphs of contribution to likelihood
552:
1.204 brouard 553: Revision 1.203 2015/09/30 17:45:14 brouard
554: Summary: looking at better estimation of the hessian
555:
556: Also a better criteria for convergence to the period prevalence And
557: therefore adding the number of years needed to converge. (The
558: prevalence in any alive state shold sum to one
559:
1.203 brouard 560: Revision 1.202 2015/09/22 19:45:16 brouard
561: Summary: Adding some overall graph on contribution to likelihood. Might change
562:
1.202 brouard 563: Revision 1.201 2015/09/15 17:34:58 brouard
564: Summary: 0.98r0
565:
566: - Some new graphs like suvival functions
567: - Some bugs fixed like model=1+age+V2.
568:
1.201 brouard 569: Revision 1.200 2015/09/09 16:53:55 brouard
570: Summary: Big bug thanks to Flavia
571:
572: Even model=1+age+V2. did not work anymore
573:
1.200 brouard 574: Revision 1.199 2015/09/07 14:09:23 brouard
575: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
576:
1.199 brouard 577: Revision 1.198 2015/09/03 07:14:39 brouard
578: Summary: 0.98q5 Flavia
579:
1.198 brouard 580: Revision 1.197 2015/09/01 18:24:39 brouard
581: *** empty log message ***
582:
1.197 brouard 583: Revision 1.196 2015/08/18 23:17:52 brouard
584: Summary: 0.98q5
585:
1.196 brouard 586: Revision 1.195 2015/08/18 16:28:39 brouard
587: Summary: Adding a hack for testing purpose
588:
589: After reading the title, ftol and model lines, if the comment line has
590: a q, starting with #q, the answer at the end of the run is quit. It
591: permits to run test files in batch with ctest. The former workaround was
592: $ echo q | imach foo.imach
593:
1.195 brouard 594: Revision 1.194 2015/08/18 13:32:00 brouard
595: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
596:
1.194 brouard 597: Revision 1.193 2015/08/04 07:17:42 brouard
598: Summary: 0.98q4
599:
1.193 brouard 600: Revision 1.192 2015/07/16 16:49:02 brouard
601: Summary: Fixing some outputs
602:
1.192 brouard 603: Revision 1.191 2015/07/14 10:00:33 brouard
604: Summary: Some fixes
605:
1.191 brouard 606: Revision 1.190 2015/05/05 08:51:13 brouard
607: Summary: Adding digits in output parameters (7 digits instead of 6)
608:
609: Fix 1+age+.
610:
1.190 brouard 611: Revision 1.189 2015/04/30 14:45:16 brouard
612: Summary: 0.98q2
613:
1.189 brouard 614: Revision 1.188 2015/04/30 08:27:53 brouard
615: *** empty log message ***
616:
1.188 brouard 617: Revision 1.187 2015/04/29 09:11:15 brouard
618: *** empty log message ***
619:
1.187 brouard 620: Revision 1.186 2015/04/23 12:01:52 brouard
621: Summary: V1*age is working now, version 0.98q1
622:
623: Some codes had been disabled in order to simplify and Vn*age was
624: working in the optimization phase, ie, giving correct MLE parameters,
625: but, as usual, outputs were not correct and program core dumped.
626:
1.186 brouard 627: Revision 1.185 2015/03/11 13:26:42 brouard
628: Summary: Inclusion of compile and links command line for Intel Compiler
629:
1.185 brouard 630: Revision 1.184 2015/03/11 11:52:39 brouard
631: Summary: Back from Windows 8. Intel Compiler
632:
1.184 brouard 633: Revision 1.183 2015/03/10 20:34:32 brouard
634: Summary: 0.98q0, trying with directest, mnbrak fixed
635:
636: We use directest instead of original Powell test; probably no
637: incidence on the results, but better justifications;
638: We fixed Numerical Recipes mnbrak routine which was wrong and gave
639: wrong results.
640:
1.183 brouard 641: Revision 1.182 2015/02/12 08:19:57 brouard
642: Summary: Trying to keep directest which seems simpler and more general
643: Author: Nicolas Brouard
644:
1.182 brouard 645: Revision 1.181 2015/02/11 23:22:24 brouard
646: Summary: Comments on Powell added
647:
648: Author:
649:
1.181 brouard 650: Revision 1.180 2015/02/11 17:33:45 brouard
651: Summary: Finishing move from main to function (hpijx and prevalence_limit)
652:
1.180 brouard 653: Revision 1.179 2015/01/04 09:57:06 brouard
654: Summary: back to OS/X
655:
1.179 brouard 656: Revision 1.178 2015/01/04 09:35:48 brouard
657: *** empty log message ***
658:
1.178 brouard 659: Revision 1.177 2015/01/03 18:40:56 brouard
660: Summary: Still testing ilc32 on OSX
661:
1.177 brouard 662: Revision 1.176 2015/01/03 16:45:04 brouard
663: *** empty log message ***
664:
1.176 brouard 665: Revision 1.175 2015/01/03 16:33:42 brouard
666: *** empty log message ***
667:
1.175 brouard 668: Revision 1.174 2015/01/03 16:15:49 brouard
669: Summary: Still in cross-compilation
670:
1.174 brouard 671: Revision 1.173 2015/01/03 12:06:26 brouard
672: Summary: trying to detect cross-compilation
673:
1.173 brouard 674: Revision 1.172 2014/12/27 12:07:47 brouard
675: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
676:
1.172 brouard 677: Revision 1.171 2014/12/23 13:26:59 brouard
678: Summary: Back from Visual C
679:
680: Still problem with utsname.h on Windows
681:
1.171 brouard 682: Revision 1.170 2014/12/23 11:17:12 brouard
683: Summary: Cleaning some \%% back to %%
684:
685: The escape was mandatory for a specific compiler (which one?), but too many warnings.
686:
1.170 brouard 687: Revision 1.169 2014/12/22 23:08:31 brouard
688: Summary: 0.98p
689:
690: Outputs some informations on compiler used, OS etc. Testing on different platforms.
691:
1.169 brouard 692: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 693: Summary: update
1.169 brouard 694:
1.168 brouard 695: Revision 1.167 2014/12/22 13:50:56 brouard
696: Summary: Testing uname and compiler version and if compiled 32 or 64
697:
698: Testing on Linux 64
699:
1.167 brouard 700: Revision 1.166 2014/12/22 11:40:47 brouard
701: *** empty log message ***
702:
1.166 brouard 703: Revision 1.165 2014/12/16 11:20:36 brouard
704: Summary: After compiling on Visual C
705:
706: * imach.c (Module): Merging 1.61 to 1.162
707:
1.165 brouard 708: Revision 1.164 2014/12/16 10:52:11 brouard
709: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
710:
711: * imach.c (Module): Merging 1.61 to 1.162
712:
1.164 brouard 713: Revision 1.163 2014/12/16 10:30:11 brouard
714: * imach.c (Module): Merging 1.61 to 1.162
715:
1.163 brouard 716: Revision 1.162 2014/09/25 11:43:39 brouard
717: Summary: temporary backup 0.99!
718:
1.162 brouard 719: Revision 1.1 2014/09/16 11:06:58 brouard
720: Summary: With some code (wrong) for nlopt
721:
722: Author:
723:
724: Revision 1.161 2014/09/15 20:41:41 brouard
725: Summary: Problem with macro SQR on Intel compiler
726:
1.161 brouard 727: Revision 1.160 2014/09/02 09:24:05 brouard
728: *** empty log message ***
729:
1.160 brouard 730: Revision 1.159 2014/09/01 10:34:10 brouard
731: Summary: WIN32
732: Author: Brouard
733:
1.159 brouard 734: Revision 1.158 2014/08/27 17:11:51 brouard
735: *** empty log message ***
736:
1.158 brouard 737: Revision 1.157 2014/08/27 16:26:55 brouard
738: Summary: Preparing windows Visual studio version
739: Author: Brouard
740:
741: In order to compile on Visual studio, time.h is now correct and time_t
742: and tm struct should be used. difftime should be used but sometimes I
743: just make the differences in raw time format (time(&now).
744: Trying to suppress #ifdef LINUX
745: Add xdg-open for __linux in order to open default browser.
746:
1.157 brouard 747: Revision 1.156 2014/08/25 20:10:10 brouard
748: *** empty log message ***
749:
1.156 brouard 750: Revision 1.155 2014/08/25 18:32:34 brouard
751: Summary: New compile, minor changes
752: Author: Brouard
753:
1.155 brouard 754: Revision 1.154 2014/06/20 17:32:08 brouard
755: Summary: Outputs now all graphs of convergence to period prevalence
756:
1.154 brouard 757: Revision 1.153 2014/06/20 16:45:46 brouard
758: Summary: If 3 live state, convergence to period prevalence on same graph
759: Author: Brouard
760:
1.153 brouard 761: Revision 1.152 2014/06/18 17:54:09 brouard
762: Summary: open browser, use gnuplot on same dir than imach if not found in the path
763:
1.152 brouard 764: Revision 1.151 2014/06/18 16:43:30 brouard
765: *** empty log message ***
766:
1.151 brouard 767: Revision 1.150 2014/06/18 16:42:35 brouard
768: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
769: Author: brouard
770:
1.150 brouard 771: Revision 1.149 2014/06/18 15:51:14 brouard
772: Summary: Some fixes in parameter files errors
773: Author: Nicolas Brouard
774:
1.149 brouard 775: Revision 1.148 2014/06/17 17:38:48 brouard
776: Summary: Nothing new
777: Author: Brouard
778:
779: Just a new packaging for OS/X version 0.98nS
780:
1.148 brouard 781: Revision 1.147 2014/06/16 10:33:11 brouard
782: *** empty log message ***
783:
1.147 brouard 784: Revision 1.146 2014/06/16 10:20:28 brouard
785: Summary: Merge
786: Author: Brouard
787:
788: Merge, before building revised version.
789:
1.146 brouard 790: Revision 1.145 2014/06/10 21:23:15 brouard
791: Summary: Debugging with valgrind
792: Author: Nicolas Brouard
793:
794: Lot of changes in order to output the results with some covariates
795: After the Edimburgh REVES conference 2014, it seems mandatory to
796: improve the code.
797: No more memory valgrind error but a lot has to be done in order to
798: continue the work of splitting the code into subroutines.
799: Also, decodemodel has been improved. Tricode is still not
800: optimal. nbcode should be improved. Documentation has been added in
801: the source code.
802:
1.144 brouard 803: Revision 1.143 2014/01/26 09:45:38 brouard
804: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
805:
806: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
807: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
808:
1.143 brouard 809: Revision 1.142 2014/01/26 03:57:36 brouard
810: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
811:
812: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
813:
1.142 brouard 814: Revision 1.141 2014/01/26 02:42:01 brouard
815: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
816:
1.141 brouard 817: Revision 1.140 2011/09/02 10:37:54 brouard
818: Summary: times.h is ok with mingw32 now.
819:
1.140 brouard 820: Revision 1.139 2010/06/14 07:50:17 brouard
821: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
822: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
823:
1.139 brouard 824: Revision 1.138 2010/04/30 18:19:40 brouard
825: *** empty log message ***
826:
1.138 brouard 827: Revision 1.137 2010/04/29 18:11:38 brouard
828: (Module): Checking covariates for more complex models
829: than V1+V2. A lot of change to be done. Unstable.
830:
1.137 brouard 831: Revision 1.136 2010/04/26 20:30:53 brouard
832: (Module): merging some libgsl code. Fixing computation
833: of likelione (using inter/intrapolation if mle = 0) in order to
834: get same likelihood as if mle=1.
835: Some cleaning of code and comments added.
836:
1.136 brouard 837: Revision 1.135 2009/10/29 15:33:14 brouard
838: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
839:
1.135 brouard 840: Revision 1.134 2009/10/29 13:18:53 brouard
841: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
842:
1.134 brouard 843: Revision 1.133 2009/07/06 10:21:25 brouard
844: just nforces
845:
1.133 brouard 846: Revision 1.132 2009/07/06 08:22:05 brouard
847: Many tings
848:
1.132 brouard 849: Revision 1.131 2009/06/20 16:22:47 brouard
850: Some dimensions resccaled
851:
1.131 brouard 852: Revision 1.130 2009/05/26 06:44:34 brouard
853: (Module): Max Covariate is now set to 20 instead of 8. A
854: lot of cleaning with variables initialized to 0. Trying to make
855: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
856:
1.130 brouard 857: Revision 1.129 2007/08/31 13:49:27 lievre
858: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
859:
1.129 lievre 860: Revision 1.128 2006/06/30 13:02:05 brouard
861: (Module): Clarifications on computing e.j
862:
1.128 brouard 863: Revision 1.127 2006/04/28 18:11:50 brouard
864: (Module): Yes the sum of survivors was wrong since
865: imach-114 because nhstepm was no more computed in the age
866: loop. Now we define nhstepma in the age loop.
867: (Module): In order to speed up (in case of numerous covariates) we
868: compute health expectancies (without variances) in a first step
869: and then all the health expectancies with variances or standard
870: deviation (needs data from the Hessian matrices) which slows the
871: computation.
872: In the future we should be able to stop the program is only health
873: expectancies and graph are needed without standard deviations.
874:
1.127 brouard 875: Revision 1.126 2006/04/28 17:23:28 brouard
876: (Module): Yes the sum of survivors was wrong since
877: imach-114 because nhstepm was no more computed in the age
878: loop. Now we define nhstepma in the age loop.
879: Version 0.98h
880:
1.126 brouard 881: Revision 1.125 2006/04/04 15:20:31 lievre
882: Errors in calculation of health expectancies. Age was not initialized.
883: Forecasting file added.
884:
885: Revision 1.124 2006/03/22 17:13:53 lievre
886: Parameters are printed with %lf instead of %f (more numbers after the comma).
887: The log-likelihood is printed in the log file
888:
889: Revision 1.123 2006/03/20 10:52:43 brouard
890: * imach.c (Module): <title> changed, corresponds to .htm file
891: name. <head> headers where missing.
892:
893: * imach.c (Module): Weights can have a decimal point as for
894: English (a comma might work with a correct LC_NUMERIC environment,
895: otherwise the weight is truncated).
896: Modification of warning when the covariates values are not 0 or
897: 1.
898: Version 0.98g
899:
900: Revision 1.122 2006/03/20 09:45:41 brouard
901: (Module): Weights can have a decimal point as for
902: English (a comma might work with a correct LC_NUMERIC environment,
903: otherwise the weight is truncated).
904: Modification of warning when the covariates values are not 0 or
905: 1.
906: Version 0.98g
907:
908: Revision 1.121 2006/03/16 17:45:01 lievre
909: * imach.c (Module): Comments concerning covariates added
910:
911: * imach.c (Module): refinements in the computation of lli if
912: status=-2 in order to have more reliable computation if stepm is
913: not 1 month. Version 0.98f
914:
915: Revision 1.120 2006/03/16 15:10:38 lievre
916: (Module): refinements in the computation of lli if
917: status=-2 in order to have more reliable computation if stepm is
918: not 1 month. Version 0.98f
919:
920: Revision 1.119 2006/03/15 17:42:26 brouard
921: (Module): Bug if status = -2, the loglikelihood was
922: computed as likelihood omitting the logarithm. Version O.98e
923:
924: Revision 1.118 2006/03/14 18:20:07 brouard
925: (Module): varevsij Comments added explaining the second
926: table of variances if popbased=1 .
927: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
928: (Module): Function pstamp added
929: (Module): Version 0.98d
930:
931: Revision 1.117 2006/03/14 17:16:22 brouard
932: (Module): varevsij Comments added explaining the second
933: table of variances if popbased=1 .
934: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
935: (Module): Function pstamp added
936: (Module): Version 0.98d
937:
938: Revision 1.116 2006/03/06 10:29:27 brouard
939: (Module): Variance-covariance wrong links and
940: varian-covariance of ej. is needed (Saito).
941:
942: Revision 1.115 2006/02/27 12:17:45 brouard
943: (Module): One freematrix added in mlikeli! 0.98c
944:
945: Revision 1.114 2006/02/26 12:57:58 brouard
946: (Module): Some improvements in processing parameter
947: filename with strsep.
948:
949: Revision 1.113 2006/02/24 14:20:24 brouard
950: (Module): Memory leaks checks with valgrind and:
951: datafile was not closed, some imatrix were not freed and on matrix
952: allocation too.
953:
954: Revision 1.112 2006/01/30 09:55:26 brouard
955: (Module): Back to gnuplot.exe instead of wgnuplot.exe
956:
957: Revision 1.111 2006/01/25 20:38:18 brouard
958: (Module): Lots of cleaning and bugs added (Gompertz)
959: (Module): Comments can be added in data file. Missing date values
960: can be a simple dot '.'.
961:
962: Revision 1.110 2006/01/25 00:51:50 brouard
963: (Module): Lots of cleaning and bugs added (Gompertz)
964:
965: Revision 1.109 2006/01/24 19:37:15 brouard
966: (Module): Comments (lines starting with a #) are allowed in data.
967:
968: Revision 1.108 2006/01/19 18:05:42 lievre
969: Gnuplot problem appeared...
970: To be fixed
971:
972: Revision 1.107 2006/01/19 16:20:37 brouard
973: Test existence of gnuplot in imach path
974:
975: Revision 1.106 2006/01/19 13:24:36 brouard
976: Some cleaning and links added in html output
977:
978: Revision 1.105 2006/01/05 20:23:19 lievre
979: *** empty log message ***
980:
981: Revision 1.104 2005/09/30 16:11:43 lievre
982: (Module): sump fixed, loop imx fixed, and simplifications.
983: (Module): If the status is missing at the last wave but we know
984: that the person is alive, then we can code his/her status as -2
985: (instead of missing=-1 in earlier versions) and his/her
986: contributions to the likelihood is 1 - Prob of dying from last
987: health status (= 1-p13= p11+p12 in the easiest case of somebody in
988: the healthy state at last known wave). Version is 0.98
989:
990: Revision 1.103 2005/09/30 15:54:49 lievre
991: (Module): sump fixed, loop imx fixed, and simplifications.
992:
993: Revision 1.102 2004/09/15 17:31:30 brouard
994: Add the possibility to read data file including tab characters.
995:
996: Revision 1.101 2004/09/15 10:38:38 brouard
997: Fix on curr_time
998:
999: Revision 1.100 2004/07/12 18:29:06 brouard
1000: Add version for Mac OS X. Just define UNIX in Makefile
1001:
1002: Revision 1.99 2004/06/05 08:57:40 brouard
1003: *** empty log message ***
1004:
1005: Revision 1.98 2004/05/16 15:05:56 brouard
1006: New version 0.97 . First attempt to estimate force of mortality
1007: directly from the data i.e. without the need of knowing the health
1008: state at each age, but using a Gompertz model: log u =a + b*age .
1009: This is the basic analysis of mortality and should be done before any
1010: other analysis, in order to test if the mortality estimated from the
1011: cross-longitudinal survey is different from the mortality estimated
1012: from other sources like vital statistic data.
1013:
1014: The same imach parameter file can be used but the option for mle should be -3.
1015:
1.324 brouard 1016: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 1017: former routines in order to include the new code within the former code.
1018:
1019: The output is very simple: only an estimate of the intercept and of
1020: the slope with 95% confident intervals.
1021:
1022: Current limitations:
1023: A) Even if you enter covariates, i.e. with the
1024: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
1025: B) There is no computation of Life Expectancy nor Life Table.
1026:
1027: Revision 1.97 2004/02/20 13:25:42 lievre
1028: Version 0.96d. Population forecasting command line is (temporarily)
1029: suppressed.
1030:
1031: Revision 1.96 2003/07/15 15:38:55 brouard
1032: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
1033: rewritten within the same printf. Workaround: many printfs.
1034:
1035: Revision 1.95 2003/07/08 07:54:34 brouard
1036: * imach.c (Repository):
1037: (Repository): Using imachwizard code to output a more meaningful covariance
1038: matrix (cov(a12,c31) instead of numbers.
1039:
1040: Revision 1.94 2003/06/27 13:00:02 brouard
1041: Just cleaning
1042:
1043: Revision 1.93 2003/06/25 16:33:55 brouard
1044: (Module): On windows (cygwin) function asctime_r doesn't
1045: exist so I changed back to asctime which exists.
1046: (Module): Version 0.96b
1047:
1048: Revision 1.92 2003/06/25 16:30:45 brouard
1049: (Module): On windows (cygwin) function asctime_r doesn't
1050: exist so I changed back to asctime which exists.
1051:
1052: Revision 1.91 2003/06/25 15:30:29 brouard
1053: * imach.c (Repository): Duplicated warning errors corrected.
1054: (Repository): Elapsed time after each iteration is now output. It
1055: helps to forecast when convergence will be reached. Elapsed time
1056: is stamped in powell. We created a new html file for the graphs
1057: concerning matrix of covariance. It has extension -cov.htm.
1058:
1059: Revision 1.90 2003/06/24 12:34:15 brouard
1060: (Module): Some bugs corrected for windows. Also, when
1061: mle=-1 a template is output in file "or"mypar.txt with the design
1062: of the covariance matrix to be input.
1063:
1064: Revision 1.89 2003/06/24 12:30:52 brouard
1065: (Module): Some bugs corrected for windows. Also, when
1066: mle=-1 a template is output in file "or"mypar.txt with the design
1067: of the covariance matrix to be input.
1068:
1069: Revision 1.88 2003/06/23 17:54:56 brouard
1070: * 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.
1071:
1072: Revision 1.87 2003/06/18 12:26:01 brouard
1073: Version 0.96
1074:
1075: Revision 1.86 2003/06/17 20:04:08 brouard
1076: (Module): Change position of html and gnuplot routines and added
1077: routine fileappend.
1078:
1079: Revision 1.85 2003/06/17 13:12:43 brouard
1080: * imach.c (Repository): Check when date of death was earlier that
1081: current date of interview. It may happen when the death was just
1082: prior to the death. In this case, dh was negative and likelihood
1083: was wrong (infinity). We still send an "Error" but patch by
1084: assuming that the date of death was just one stepm after the
1085: interview.
1086: (Repository): Because some people have very long ID (first column)
1087: we changed int to long in num[] and we added a new lvector for
1088: memory allocation. But we also truncated to 8 characters (left
1089: truncation)
1090: (Repository): No more line truncation errors.
1091:
1092: Revision 1.84 2003/06/13 21:44:43 brouard
1093: * imach.c (Repository): Replace "freqsummary" at a correct
1094: place. It differs from routine "prevalence" which may be called
1095: many times. Probs is memory consuming and must be used with
1096: parcimony.
1097: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
1098:
1099: Revision 1.83 2003/06/10 13:39:11 lievre
1100: *** empty log message ***
1101:
1102: Revision 1.82 2003/06/05 15:57:20 brouard
1103: Add log in imach.c and fullversion number is now printed.
1104:
1105: */
1106: /*
1107: Interpolated Markov Chain
1108:
1109: Short summary of the programme:
1110:
1.227 brouard 1111: This program computes Healthy Life Expectancies or State-specific
1112: (if states aren't health statuses) Expectancies from
1113: cross-longitudinal data. Cross-longitudinal data consist in:
1114:
1115: -1- a first survey ("cross") where individuals from different ages
1116: are interviewed on their health status or degree of disability (in
1117: the case of a health survey which is our main interest)
1118:
1119: -2- at least a second wave of interviews ("longitudinal") which
1120: measure each change (if any) in individual health status. Health
1121: expectancies are computed from the time spent in each health state
1122: according to a model. More health states you consider, more time is
1123: necessary to reach the Maximum Likelihood of the parameters involved
1124: in the model. The simplest model is the multinomial logistic model
1125: where pij is the probability to be observed in state j at the second
1126: wave conditional to be observed in state i at the first
1127: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
1128: etc , where 'age' is age and 'sex' is a covariate. If you want to
1129: have a more complex model than "constant and age", you should modify
1130: the program where the markup *Covariates have to be included here
1131: again* invites you to do it. More covariates you add, slower the
1.126 brouard 1132: convergence.
1133:
1134: The advantage of this computer programme, compared to a simple
1135: multinomial logistic model, is clear when the delay between waves is not
1136: identical for each individual. Also, if a individual missed an
1137: intermediate interview, the information is lost, but taken into
1138: account using an interpolation or extrapolation.
1139:
1140: hPijx is the probability to be observed in state i at age x+h
1141: conditional to the observed state i at age x. The delay 'h' can be
1142: split into an exact number (nh*stepm) of unobserved intermediate
1143: states. This elementary transition (by month, quarter,
1144: semester or year) is modelled as a multinomial logistic. The hPx
1145: matrix is simply the matrix product of nh*stepm elementary matrices
1146: and the contribution of each individual to the likelihood is simply
1147: hPijx.
1148:
1149: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 1150: of the life expectancies. It also computes the period (stable) prevalence.
1151:
1152: Back prevalence and projections:
1.227 brouard 1153:
1154: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
1155: double agemaxpar, double ftolpl, int *ncvyearp, double
1156: dateprev1,double dateprev2, int firstpass, int lastpass, int
1157: mobilavproj)
1158:
1159: Computes the back prevalence limit for any combination of
1160: covariate values k at any age between ageminpar and agemaxpar and
1161: returns it in **bprlim. In the loops,
1162:
1163: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
1164: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
1165:
1166: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 1167: Computes for any combination of covariates k and any age between bage and fage
1168: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
1169: oldm=oldms;savm=savms;
1.227 brouard 1170:
1.267 brouard 1171: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 1172: Computes the transition matrix starting at age 'age' over
1173: 'nhstepm*hstepm*stepm' months (i.e. until
1174: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 1175: nhstepm*hstepm matrices.
1176:
1177: Returns p3mat[i][j][h] after calling
1178: p3mat[i][j][h]=matprod2(newm,
1179: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
1180: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
1181: oldm);
1.226 brouard 1182:
1183: Important routines
1184:
1185: - func (or funcone), computes logit (pij) distinguishing
1186: o fixed variables (single or product dummies or quantitative);
1187: o varying variables by:
1188: (1) wave (single, product dummies, quantitative),
1189: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
1190: % fixed dummy (treated) or quantitative (not done because time-consuming);
1191: % varying dummy (not done) or quantitative (not done);
1192: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
1193: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
1194: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
1.325 brouard 1195: o There are 2**cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
1.226 brouard 1196: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 1197:
1.226 brouard 1198:
1199:
1.324 brouard 1200: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
1201: Institut national d'études démographiques, Paris.
1.126 brouard 1202: This software have been partly granted by Euro-REVES, a concerted action
1203: from the European Union.
1204: It is copyrighted identically to a GNU software product, ie programme and
1205: software can be distributed freely for non commercial use. Latest version
1206: can be accessed at http://euroreves.ined.fr/imach .
1207:
1208: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
1209: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
1210:
1211: **********************************************************************/
1212: /*
1213: main
1214: read parameterfile
1215: read datafile
1216: concatwav
1217: freqsummary
1218: if (mle >= 1)
1219: mlikeli
1220: print results files
1221: if mle==1
1222: computes hessian
1223: read end of parameter file: agemin, agemax, bage, fage, estepm
1224: begin-prev-date,...
1225: open gnuplot file
1226: open html file
1.145 brouard 1227: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
1228: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
1229: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
1230: freexexit2 possible for memory heap.
1231:
1232: h Pij x | pij_nom ficrestpij
1233: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
1234: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
1235: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
1236:
1237: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
1238: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
1239: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
1240: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
1241: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
1242:
1.126 brouard 1243: forecasting if prevfcast==1 prevforecast call prevalence()
1244: health expectancies
1245: Variance-covariance of DFLE
1246: prevalence()
1247: movingaverage()
1248: varevsij()
1249: if popbased==1 varevsij(,popbased)
1250: total life expectancies
1251: Variance of period (stable) prevalence
1252: end
1253: */
1254:
1.187 brouard 1255: /* #define DEBUG */
1256: /* #define DEBUGBRENT */
1.203 brouard 1257: /* #define DEBUGLINMIN */
1258: /* #define DEBUGHESS */
1259: #define DEBUGHESSIJ
1.224 brouard 1260: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 1261: #define POWELL /* Instead of NLOPT */
1.224 brouard 1262: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 1263: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
1264: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.319 brouard 1265: /* #define FLATSUP *//* Suppresses directions where likelihood is flat */
1.126 brouard 1266:
1267: #include <math.h>
1268: #include <stdio.h>
1269: #include <stdlib.h>
1270: #include <string.h>
1.226 brouard 1271: #include <ctype.h>
1.159 brouard 1272:
1273: #ifdef _WIN32
1274: #include <io.h>
1.172 brouard 1275: #include <windows.h>
1276: #include <tchar.h>
1.159 brouard 1277: #else
1.126 brouard 1278: #include <unistd.h>
1.159 brouard 1279: #endif
1.126 brouard 1280:
1281: #include <limits.h>
1282: #include <sys/types.h>
1.171 brouard 1283:
1284: #if defined(__GNUC__)
1285: #include <sys/utsname.h> /* Doesn't work on Windows */
1286: #endif
1287:
1.126 brouard 1288: #include <sys/stat.h>
1289: #include <errno.h>
1.159 brouard 1290: /* extern int errno; */
1.126 brouard 1291:
1.157 brouard 1292: /* #ifdef LINUX */
1293: /* #include <time.h> */
1294: /* #include "timeval.h" */
1295: /* #else */
1296: /* #include <sys/time.h> */
1297: /* #endif */
1298:
1.126 brouard 1299: #include <time.h>
1300:
1.136 brouard 1301: #ifdef GSL
1302: #include <gsl/gsl_errno.h>
1303: #include <gsl/gsl_multimin.h>
1304: #endif
1305:
1.167 brouard 1306:
1.162 brouard 1307: #ifdef NLOPT
1308: #include <nlopt.h>
1309: typedef struct {
1310: double (* function)(double [] );
1311: } myfunc_data ;
1312: #endif
1313:
1.126 brouard 1314: /* #include <libintl.h> */
1315: /* #define _(String) gettext (String) */
1316:
1.349 ! brouard 1317: #define MAXLINE 16384 /* Was 256 and 1024 and 2048. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1318:
1319: #define GNUPLOTPROGRAM "gnuplot"
1.343 brouard 1320: #define GNUPLOTVERSION 5.1
1321: double gnuplotversion=GNUPLOTVERSION;
1.126 brouard 1322: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1.329 brouard 1323: #define FILENAMELENGTH 256
1.126 brouard 1324:
1325: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1326: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1327:
1.349 ! brouard 1328: #define MAXPARM 216 /**< Maximum number of parameters for the optimization was 128 */
1.144 brouard 1329: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1330:
1331: #define NINTERVMAX 8
1.144 brouard 1332: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1333: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.325 brouard 1334: #define NCOVMAX 30 /**< Maximum number of covariates used in the model, including generated covariates V1*V2 or V1*age */
1.197 brouard 1335: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1336: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1337: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1338: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1339: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1340: /* #define AGESUP 130 */
1.288 brouard 1341: /* #define AGESUP 150 */
1342: #define AGESUP 200
1.268 brouard 1343: #define AGEINF 0
1.218 brouard 1344: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1345: #define AGEBASE 40
1.194 brouard 1346: #define AGEOVERFLOW 1.e20
1.164 brouard 1347: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1348: #ifdef _WIN32
1349: #define DIRSEPARATOR '\\'
1350: #define CHARSEPARATOR "\\"
1351: #define ODIRSEPARATOR '/'
1352: #else
1.126 brouard 1353: #define DIRSEPARATOR '/'
1354: #define CHARSEPARATOR "/"
1355: #define ODIRSEPARATOR '\\'
1356: #endif
1357:
1.348 brouard 1358: /* $Id: imach.c,v 1.347 2022/09/18 14:36:44 brouard Exp $ */
1.126 brouard 1359: /* $State: Exp $ */
1.196 brouard 1360: #include "version.h"
1361: char version[]=__IMACH_VERSION__;
1.349 ! brouard 1362: char copyright[]="January 2023,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";
1.348 brouard 1363: char fullversion[]="$Revision: 1.347 $ $Date: 2022/09/18 14:36:44 $";
1.126 brouard 1364: char strstart[80];
1365: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1366: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.342 brouard 1367: int debugILK=0; /* debugILK is set by a #d in a comment line */
1.187 brouard 1368: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.330 brouard 1369: /* Number of covariates model (1)=V2+V1+ V3*age+V2*V4 */
1370: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
1.335 brouard 1371: 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 1372: 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 1373: int cptcovs=0; /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
1374: int cptcovsnq=0; /**< cptcovsnq number of SIMPLE covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1375: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1.349 ! brouard 1376: int cptcovprodage=0; /**< Number of fixed covariates with age: V3*age or V2*V3*age 1 */
! 1377: int cptcovprodvage=0; /**< Number of varying covariates with age: V7*age or V7*V6*age */
! 1378: int cptcovdageprod=0; /**< Number of doubleproducts with age, since 0.99r44 only: age*Vn*Vm for gnuplot printing*/
1.145 brouard 1379: int cptcovprodnoage=0; /**< Number of covariate products without age */
1.335 brouard 1380: 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 1381: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1382: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.339 brouard 1383: int ncovvt=0; /* Total number of effective (wave) varying covariates (dummy or quantitative or products [without age]) in the model */
1.349 ! brouard 1384: int ncovvta=0; /* +age*V6 + age*V7+ age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 Total number of expandend products [with age]) in the model */
! 1385: int ncovta=0; /*age*V3*V2 +age*V2+agev3+ageV4 +age*V6 + age*V7+ age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 Total number of expandend products [with age]) in the model */
! 1386: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (single or product, dummy or quantitative) in the model */
! 1387: int ncovva=0; /* +age*V6 + age*V7+ge*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 Total number of effective (wave and stepm) varying with age covariates (single or product, dummy or quantitative) in the model */
1.234 brouard 1388: int nsd=0; /**< Total number of single dummy variables (output) */
1389: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1390: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1391: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1392: int ntveff=0; /**< ntveff number of effective time varying variables */
1393: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1394: int cptcov=0; /* Working variable */
1.334 brouard 1395: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs+1 declared globally ;*/
1.290 brouard 1396: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1397: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.302 brouard 1398: int npar=NPARMAX; /* Number of parameters (nlstate+ndeath-1)*nlstate*ncovmodel; */
1.126 brouard 1399: int nlstate=2; /* Number of live states */
1400: int ndeath=1; /* Number of dead states */
1.130 brouard 1401: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.339 brouard 1402: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable*/
1403: int ncovcolt=0; /* ncovcolt=ncovcol+nqv+ntv+nqtv; total of covariates in the data, not in the model equation*/
1.126 brouard 1404: int popbased=0;
1405:
1406: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1407: int maxwav=0; /* Maxim number of waves */
1408: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1409: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1410: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1411: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1412: int mle=1, weightopt=0;
1.126 brouard 1413: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1414: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1415: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1416: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1417: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1418: int selected(int kvar); /* Is covariate kvar selected for printing results */
1419:
1.130 brouard 1420: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1421: double **matprod2(); /* test */
1.126 brouard 1422: double **oldm, **newm, **savm; /* Working pointers to matrices */
1423: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1424: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1425:
1.136 brouard 1426: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1427: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1428: FILE *ficlog, *ficrespow;
1.130 brouard 1429: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1430: double fretone; /* Only one call to likelihood */
1.130 brouard 1431: long ipmx=0; /* Number of contributions */
1.126 brouard 1432: double sw; /* Sum of weights */
1433: char filerespow[FILENAMELENGTH];
1434: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1435: FILE *ficresilk;
1436: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1437: FILE *ficresprobmorprev;
1438: FILE *fichtm, *fichtmcov; /* Html File */
1439: FILE *ficreseij;
1440: char filerese[FILENAMELENGTH];
1441: FILE *ficresstdeij;
1442: char fileresstde[FILENAMELENGTH];
1443: FILE *ficrescveij;
1444: char filerescve[FILENAMELENGTH];
1445: FILE *ficresvij;
1446: char fileresv[FILENAMELENGTH];
1.269 brouard 1447:
1.126 brouard 1448: char title[MAXLINE];
1.234 brouard 1449: char model[MAXLINE]; /**< The model line */
1.217 brouard 1450: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1451: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1452: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1453: char command[FILENAMELENGTH];
1454: int outcmd=0;
1455:
1.217 brouard 1456: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1457: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1458: char filelog[FILENAMELENGTH]; /* Log file */
1459: char filerest[FILENAMELENGTH];
1460: char fileregp[FILENAMELENGTH];
1461: char popfile[FILENAMELENGTH];
1462:
1463: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1464:
1.157 brouard 1465: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1466: /* struct timezone tzp; */
1467: /* extern int gettimeofday(); */
1468: struct tm tml, *gmtime(), *localtime();
1469:
1470: extern time_t time();
1471:
1472: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1473: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1.349 ! brouard 1474: time_t rlast_btime; /* raw time */
1.157 brouard 1475: struct tm tm;
1476:
1.126 brouard 1477: char strcurr[80], strfor[80];
1478:
1479: char *endptr;
1480: long lval;
1481: double dval;
1482:
1483: #define NR_END 1
1484: #define FREE_ARG char*
1485: #define FTOL 1.0e-10
1486:
1487: #define NRANSI
1.240 brouard 1488: #define ITMAX 200
1489: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1490:
1491: #define TOL 2.0e-4
1492:
1493: #define CGOLD 0.3819660
1494: #define ZEPS 1.0e-10
1495: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1496:
1497: #define GOLD 1.618034
1498: #define GLIMIT 100.0
1499: #define TINY 1.0e-20
1500:
1501: static double maxarg1,maxarg2;
1502: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1503: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1504:
1505: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1506: #define rint(a) floor(a+0.5)
1.166 brouard 1507: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1508: #define mytinydouble 1.0e-16
1.166 brouard 1509: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1510: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1511: /* static double dsqrarg; */
1512: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1513: static double sqrarg;
1514: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1515: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1516: int agegomp= AGEGOMP;
1517:
1518: int imx;
1519: int stepm=1;
1520: /* Stepm, step in month: minimum step interpolation*/
1521:
1522: int estepm;
1523: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1524:
1525: int m,nb;
1526: long *num;
1.197 brouard 1527: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1528: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1529: covariate for which somebody answered excluding
1530: undefined. Usually 2: 0 and 1. */
1531: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1532: covariate for which somebody answered including
1533: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1534: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1535: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1536: double ***mobaverage, ***mobaverages; /* New global variable */
1.332 brouard 1537: 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 1538: double *ageexmed,*agecens;
1539: double dateintmean=0;
1.296 brouard 1540: double anprojd, mprojd, jprojd; /* For eventual projections */
1541: double anprojf, mprojf, jprojf;
1.126 brouard 1542:
1.296 brouard 1543: double anbackd, mbackd, jbackd; /* For eventual backprojections */
1544: double anbackf, mbackf, jbackf;
1545: double jintmean,mintmean,aintmean;
1.126 brouard 1546: double *weight;
1547: int **s; /* Status */
1.141 brouard 1548: double *agedc;
1.145 brouard 1549: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1550: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1551: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1552: double **coqvar; /* Fixed quantitative covariate nqv */
1.341 brouard 1553: double ***cotvar; /* Time varying covariate start at ncovcol + nqv + (1 to ntv) */
1.225 brouard 1554: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1555: double idx;
1556: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.319 brouard 1557: /* Some documentation */
1558: /* Design original data
1559: * V1 V2 V3 V4 V5 V6 V7 V8 Weight ddb ddth d1st s1 V9 V10 V11 V12 s2 V9 V10 V11 V12
1560: * < ncovcol=6 > nqv=2 (V7 V8) dv dv dv qtv dv dv dvv qtv
1561: * ntv=3 nqtv=1
1.330 brouard 1562: * cptcovn number of covariates (not including constant and age or age*age) = number of plus sign + 1 = 10+1=11
1.319 brouard 1563: * For time varying covariate, quanti or dummies
1564: * cotqvar[wav][iv(1 to nqtv)][i]= [1][12][i]=(V12) quanti
1.341 brouard 1565: * cotvar[wav][ncovcol+nqv+ iv(1 to nqtv)][i]= [(1 to nqtv)][i]=(V12) quanti
1.319 brouard 1566: * cotvar[wav][iv(1 to ntv)][i]= [1][1][i]=(V9) dummies at wav 1
1567: * cotvar[wav][iv(1 to ntv)][i]= [1][2][i]=(V10) dummies at wav 1
1.332 brouard 1568: * covar[Vk,i], value of the Vkth fixed covariate dummy or quanti for individual i:
1.319 brouard 1569: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
1570: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 + V9 + V9*age + V10
1571: * k= 1 2 3 4 5 6 7 8 9 10 11
1572: */
1573: /* According to the model, more columns can be added to covar by the product of covariates */
1.318 brouard 1574: /* 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
1575: # States 1=Coresidence, 2 Living alone, 3 Institution
1576: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1577: */
1.349 ! brouard 1578: /* V5+V4+ V3+V4*V3 +V5*age+V2 +V1*V2+V1*age+V1+V4*V3*age */
! 1579: /* kmodel 1 2 3 4 5 6 7 8 9 10 */
! 1580: /*Typevar[k]= 0 0 0 2 1 0 2 1 0 3 *//*0 for simple covariate (dummy, quantitative,*/
! 1581: /* fixed or varying), 1 for age product, 2 for*/
! 1582: /* product without age, 3 for age and double product */
! 1583: /*Dummy[k]= 1 0 0 1 3 1 1 2 0 3 *//*Dummy[k] 0=dummy (0 1), 1 quantitative */
! 1584: /*(single or product without age), 2 dummy*/
! 1585: /* with age product, 3 quant with age product*/
! 1586: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 6 */
! 1587: /* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */
! 1588: /*TnsdVar[Tvar] 1 2 3 */
! 1589: /*Tvaraff[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
! 1590: /*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
! 1591: /*TvarsDind[nsd] 2 3 9 */ /* position K of single dummy cova */
! 1592: /* nsq 1 2 */ /* Counting single quantit tv */
! 1593: /* TvarsQ[k] 5 2 */ /* Number of single quantitative cova */
! 1594: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
! 1595: /* Tprod[i]=k 1 2 */ /* Position in model of the ith prod without age */
! 1596: /* cptcovage 1 2 3 */ /* Counting cov*age in the model equation */
! 1597: /* Tage[cptcovage]=k 5 8 10 */ /* Position in the model of ith cov*age */
! 1598: /* Tvard[1][1]@4={4,3,1,2} V4*V3 V1*V2 */ /* Position in model of the ith prod without age */
1.330 brouard 1599: /* 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 1600: /* 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 1601: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.234 brouard 1602: /* Type */
1603: /* V 1 2 3 4 5 */
1604: /* F F V V V */
1605: /* D Q D D Q */
1606: /* */
1607: int *TvarsD;
1.330 brouard 1608: int *TnsdVar;
1.234 brouard 1609: int *TvarsDind;
1610: int *TvarsQ;
1611: int *TvarsQind;
1612:
1.318 brouard 1613: #define MAXRESULTLINESPONE 10+1
1.235 brouard 1614: int nresult=0;
1.258 brouard 1615: int parameterline=0; /* # of the parameter (type) line */
1.334 brouard 1616: int TKresult[MAXRESULTLINESPONE]; /* TKresult[nres]=k for each resultline nres give the corresponding combination of dummies */
1617: int resultmodel[MAXRESULTLINESPONE][NCOVMAX];/* resultmodel[k1]=k3: k1th position in the model corresponds to the k3 position in the resultline */
1618: int modelresult[MAXRESULTLINESPONE][NCOVMAX];/* modelresult[k3]=k1: k1th position in the model corresponds to the k3 position in the resultline */
1619: int Tresult[MAXRESULTLINESPONE][NCOVMAX];/* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1620: int Tinvresult[MAXRESULTLINESPONE][NCOVMAX];/* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1621: double TinvDoQresult[MAXRESULTLINESPONE][NCOVMAX];/* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.334 brouard 1622: int Tvresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1623: double Tqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.318 brouard 1624: double Tqinvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
1.332 brouard 1625: int Tvqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.318 brouard 1626:
1627: /* 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
1628: # States 1=Coresidence, 2 Living alone, 3 Institution
1629: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1630: */
1.234 brouard 1631: /* 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 1632: 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 */
1633: 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 */
1634: 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 */
1635: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1636: 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 */
1637: 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 1638: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1639: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1640: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1641: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1642: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1643: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1644: 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 */
1645: 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 1646: int *TvarVV; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1647: int *TvarVVind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1.349 ! brouard 1648: int *TvarVVA; /* We count ncovvt time varying covariates (single or products with age) and put their name into TvarVVA */
! 1649: int *TvarVVAind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
! 1650: int *TvarAVVA; /* We count ALL ncovta time varying covariates (single or products with age) and put their name into TvarVVA */
! 1651: int *TvarAVVAind; /* We count ALL ncovta time varying covariates (single or products without age) and put their name into TvarVV */
1.339 brouard 1652: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
1.349 ! brouard 1653: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age */
! 1654: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
! 1655: /* TvarVV={3,1,3,1,3}, for V3 and then the product V1*V3 is decomposed into V1 and V3 */
! 1656: /* TvarVVind={2,5,5,6,6}, for V3 and then the product V1*V3 is decomposed into V1 and V3 and V1*V3*age into 6,6 */
1.230 brouard 1657: int *Tvarsel; /**< Selected covariates for output */
1658: double *Tvalsel; /**< Selected modality value of covariate for output */
1.349 ! brouard 1659: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product, 3 age*Vn*Vm */
1.227 brouard 1660: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1661: 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 1662: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1663: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1664: int *Tage;
1.227 brouard 1665: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1666: 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 1667: 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*/
1668: 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 1669: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1670: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1671: int **Tvard;
1.330 brouard 1672: int **Tvardk;
1.227 brouard 1673: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1674: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1675: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1676: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1677: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1678: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1679: double *lsurv, *lpop, *tpop;
1680:
1.231 brouard 1681: #define FD 1; /* Fixed dummy covariate */
1682: #define FQ 2; /* Fixed quantitative covariate */
1683: #define FP 3; /* Fixed product covariate */
1684: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1685: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1686: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1687: #define VD 10; /* Varying dummy covariate */
1688: #define VQ 11; /* Varying quantitative covariate */
1689: #define VP 12; /* Varying product covariate */
1690: #define VPDD 13; /* Varying product dummy*dummy covariate */
1691: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1692: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1693: #define APFD 16; /* Age product * fixed dummy covariate */
1694: #define APFQ 17; /* Age product * fixed quantitative covariate */
1695: #define APVD 18; /* Age product * varying dummy covariate */
1696: #define APVQ 19; /* Age product * varying quantitative covariate */
1697:
1698: #define FTYPE 1; /* Fixed covariate */
1699: #define VTYPE 2; /* Varying covariate (loop in wave) */
1700: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1701:
1702: struct kmodel{
1703: int maintype; /* main type */
1704: int subtype; /* subtype */
1705: };
1706: struct kmodel modell[NCOVMAX];
1707:
1.143 brouard 1708: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1709: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1710:
1711: /**************** split *************************/
1712: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1713: {
1714: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1715: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1716: */
1717: char *ss; /* pointer */
1.186 brouard 1718: int l1=0, l2=0; /* length counters */
1.126 brouard 1719:
1720: l1 = strlen(path ); /* length of path */
1721: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1722: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1723: if ( ss == NULL ) { /* no directory, so determine current directory */
1724: strcpy( name, path ); /* we got the fullname name because no directory */
1725: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1726: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1727: /* get current working directory */
1728: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1729: #ifdef WIN32
1730: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1731: #else
1732: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1733: #endif
1.126 brouard 1734: return( GLOCK_ERROR_GETCWD );
1735: }
1736: /* got dirc from getcwd*/
1737: printf(" DIRC = %s \n",dirc);
1.205 brouard 1738: } else { /* strip directory from path */
1.126 brouard 1739: ss++; /* after this, the filename */
1740: l2 = strlen( ss ); /* length of filename */
1741: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1742: strcpy( name, ss ); /* save file name */
1743: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1744: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1745: printf(" DIRC2 = %s \n",dirc);
1746: }
1747: /* We add a separator at the end of dirc if not exists */
1748: l1 = strlen( dirc ); /* length of directory */
1749: if( dirc[l1-1] != DIRSEPARATOR ){
1750: dirc[l1] = DIRSEPARATOR;
1751: dirc[l1+1] = 0;
1752: printf(" DIRC3 = %s \n",dirc);
1753: }
1754: ss = strrchr( name, '.' ); /* find last / */
1755: if (ss >0){
1756: ss++;
1757: strcpy(ext,ss); /* save extension */
1758: l1= strlen( name);
1759: l2= strlen(ss)+1;
1760: strncpy( finame, name, l1-l2);
1761: finame[l1-l2]= 0;
1762: }
1763:
1764: return( 0 ); /* we're done */
1765: }
1766:
1767:
1768: /******************************************/
1769:
1770: void replace_back_to_slash(char *s, char*t)
1771: {
1772: int i;
1773: int lg=0;
1774: i=0;
1775: lg=strlen(t);
1776: for(i=0; i<= lg; i++) {
1777: (s[i] = t[i]);
1778: if (t[i]== '\\') s[i]='/';
1779: }
1780: }
1781:
1.132 brouard 1782: char *trimbb(char *out, char *in)
1.137 brouard 1783: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1784: char *s;
1785: s=out;
1786: while (*in != '\0'){
1.137 brouard 1787: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1788: in++;
1789: }
1790: *out++ = *in++;
1791: }
1792: *out='\0';
1793: return s;
1794: }
1795:
1.187 brouard 1796: /* char *substrchaine(char *out, char *in, char *chain) */
1797: /* { */
1798: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1799: /* char *s, *t; */
1800: /* t=in;s=out; */
1801: /* while ((*in != *chain) && (*in != '\0')){ */
1802: /* *out++ = *in++; */
1803: /* } */
1804:
1805: /* /\* *in matches *chain *\/ */
1806: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1807: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1808: /* } */
1809: /* in--; chain--; */
1810: /* while ( (*in != '\0')){ */
1811: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1812: /* *out++ = *in++; */
1813: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1814: /* } */
1815: /* *out='\0'; */
1816: /* out=s; */
1817: /* return out; */
1818: /* } */
1819: char *substrchaine(char *out, char *in, char *chain)
1820: {
1821: /* Substract chain 'chain' from 'in', return and output 'out' */
1.349 ! brouard 1822: /* in="V1+V1*age+age*age+V2", chain="+age*age" out="V1+V1*age+V2" */
1.187 brouard 1823:
1824: char *strloc;
1825:
1.349 ! brouard 1826: strcpy (out, in); /* out="V1+V1*age+age*age+V2" */
! 1827: strloc = strstr(out, chain); /* strloc points to out at "+age*age+V2" */
! 1828: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out); /* strloc=+age*age+V2 chain="+age*age", out="V1+V1*age+age*age+V2" */
1.187 brouard 1829: if(strloc != NULL){
1.349 ! brouard 1830: /* will affect out */ /* strloc+strlen(chain)=|+V2 = "V1+V1*age+age*age|+V2" */ /* Will also work in Unicodek */
! 1831: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1); /* move number of bytes corresponding to the length of "+V2" which is 3, plus one is 4 (including the null)*/
! 1832: /* equivalent to strcpy (strloc, strloc +strlen(chain)) if no overlap; Copies from "+V2" to V1+V1*age+ */
1.187 brouard 1833: }
1.349 ! brouard 1834: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out); /* strloc=+V2 chain="+age*age", in="V1+V1*age+age*age+V2", out="V1+V1*age+V2" */
1.187 brouard 1835: return out;
1836: }
1837:
1838:
1.145 brouard 1839: char *cutl(char *blocc, char *alocc, char *in, char occ)
1840: {
1.187 brouard 1841: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.349 ! brouard 1842: and alocc starts after first occurence of char 'occ' : ex cutl(blocc,alocc,"abcdef2ghi2j",'2')
1.310 brouard 1843: gives alocc="abcdef" and blocc="ghi2j".
1.145 brouard 1844: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1845: */
1.160 brouard 1846: char *s, *t;
1.145 brouard 1847: t=in;s=in;
1848: while ((*in != occ) && (*in != '\0')){
1849: *alocc++ = *in++;
1850: }
1851: if( *in == occ){
1852: *(alocc)='\0';
1853: s=++in;
1854: }
1855:
1856: if (s == t) {/* occ not found */
1857: *(alocc-(in-s))='\0';
1858: in=s;
1859: }
1860: while ( *in != '\0'){
1861: *blocc++ = *in++;
1862: }
1863:
1864: *blocc='\0';
1865: return t;
1866: }
1.137 brouard 1867: char *cutv(char *blocc, char *alocc, char *in, char occ)
1868: {
1.187 brouard 1869: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1870: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1871: gives blocc="abcdef2ghi" and alocc="j".
1872: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1873: */
1874: char *s, *t;
1875: t=in;s=in;
1876: while (*in != '\0'){
1877: while( *in == occ){
1878: *blocc++ = *in++;
1879: s=in;
1880: }
1881: *blocc++ = *in++;
1882: }
1883: if (s == t) /* occ not found */
1884: *(blocc-(in-s))='\0';
1885: else
1886: *(blocc-(in-s)-1)='\0';
1887: in=s;
1888: while ( *in != '\0'){
1889: *alocc++ = *in++;
1890: }
1891:
1892: *alocc='\0';
1893: return s;
1894: }
1895:
1.126 brouard 1896: int nbocc(char *s, char occ)
1897: {
1898: int i,j=0;
1899: int lg=20;
1900: i=0;
1901: lg=strlen(s);
1902: for(i=0; i<= lg; i++) {
1.234 brouard 1903: if (s[i] == occ ) j++;
1.126 brouard 1904: }
1905: return j;
1906: }
1907:
1.349 ! brouard 1908: int nboccstr(char *textin, char *chain)
! 1909: {
! 1910: /* Counts the number of occurence of "chain" in string textin */
! 1911: /* in="+V7*V4+age*V2+age*V3+age*V4" chain="age" */
! 1912: char *strloc;
! 1913:
! 1914: int i,j=0;
! 1915:
! 1916: i=0;
! 1917:
! 1918: strloc=textin; /* strloc points to "^+V7*V4+age+..." in textin */
! 1919: for(;;) {
! 1920: strloc= strstr(strloc,chain); /* strloc points to first character of chain in textin if found. Example strloc points^ to "+V7*V4+^age" in textin */
! 1921: if(strloc != NULL){
! 1922: strloc = strloc+strlen(chain); /* strloc points to "+V7*V4+age^" in textin */
! 1923: j++;
! 1924: }else
! 1925: break;
! 1926: }
! 1927: return j;
! 1928:
! 1929: }
1.137 brouard 1930: /* void cutv(char *u,char *v, char*t, char occ) */
1931: /* { */
1932: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1933: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1934: /* gives u="abcdef2ghi" and v="j" *\/ */
1935: /* int i,lg,j,p=0; */
1936: /* i=0; */
1937: /* lg=strlen(t); */
1938: /* for(j=0; j<=lg-1; j++) { */
1939: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1940: /* } */
1.126 brouard 1941:
1.137 brouard 1942: /* for(j=0; j<p; j++) { */
1943: /* (u[j] = t[j]); */
1944: /* } */
1945: /* u[p]='\0'; */
1.126 brouard 1946:
1.137 brouard 1947: /* for(j=0; j<= lg; j++) { */
1948: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1949: /* } */
1950: /* } */
1.126 brouard 1951:
1.160 brouard 1952: #ifdef _WIN32
1953: char * strsep(char **pp, const char *delim)
1954: {
1955: char *p, *q;
1956:
1957: if ((p = *pp) == NULL)
1958: return 0;
1959: if ((q = strpbrk (p, delim)) != NULL)
1960: {
1961: *pp = q + 1;
1962: *q = '\0';
1963: }
1964: else
1965: *pp = 0;
1966: return p;
1967: }
1968: #endif
1969:
1.126 brouard 1970: /********************** nrerror ********************/
1971:
1972: void nrerror(char error_text[])
1973: {
1974: fprintf(stderr,"ERREUR ...\n");
1975: fprintf(stderr,"%s\n",error_text);
1976: exit(EXIT_FAILURE);
1977: }
1978: /*********************** vector *******************/
1979: double *vector(int nl, int nh)
1980: {
1981: double *v;
1982: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1983: if (!v) nrerror("allocation failure in vector");
1984: return v-nl+NR_END;
1985: }
1986:
1987: /************************ free vector ******************/
1988: void free_vector(double*v, int nl, int nh)
1989: {
1990: free((FREE_ARG)(v+nl-NR_END));
1991: }
1992:
1993: /************************ivector *******************************/
1994: int *ivector(long nl,long nh)
1995: {
1996: int *v;
1997: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1998: if (!v) nrerror("allocation failure in ivector");
1999: return v-nl+NR_END;
2000: }
2001:
2002: /******************free ivector **************************/
2003: void free_ivector(int *v, long nl, long nh)
2004: {
2005: free((FREE_ARG)(v+nl-NR_END));
2006: }
2007:
2008: /************************lvector *******************************/
2009: long *lvector(long nl,long nh)
2010: {
2011: long *v;
2012: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
2013: if (!v) nrerror("allocation failure in ivector");
2014: return v-nl+NR_END;
2015: }
2016:
2017: /******************free lvector **************************/
2018: void free_lvector(long *v, long nl, long nh)
2019: {
2020: free((FREE_ARG)(v+nl-NR_END));
2021: }
2022:
2023: /******************* imatrix *******************************/
2024: int **imatrix(long nrl, long nrh, long ncl, long nch)
2025: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
2026: {
2027: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
2028: int **m;
2029:
2030: /* allocate pointers to rows */
2031: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
2032: if (!m) nrerror("allocation failure 1 in matrix()");
2033: m += NR_END;
2034: m -= nrl;
2035:
2036:
2037: /* allocate rows and set pointers to them */
2038: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
2039: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2040: m[nrl] += NR_END;
2041: m[nrl] -= ncl;
2042:
2043: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
2044:
2045: /* return pointer to array of pointers to rows */
2046: return m;
2047: }
2048:
2049: /****************** free_imatrix *************************/
2050: void free_imatrix(m,nrl,nrh,ncl,nch)
2051: int **m;
2052: long nch,ncl,nrh,nrl;
2053: /* free an int matrix allocated by imatrix() */
2054: {
2055: free((FREE_ARG) (m[nrl]+ncl-NR_END));
2056: free((FREE_ARG) (m+nrl-NR_END));
2057: }
2058:
2059: /******************* matrix *******************************/
2060: double **matrix(long nrl, long nrh, long ncl, long nch)
2061: {
2062: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
2063: double **m;
2064:
2065: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
2066: if (!m) nrerror("allocation failure 1 in matrix()");
2067: m += NR_END;
2068: m -= nrl;
2069:
2070: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
2071: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2072: m[nrl] += NR_END;
2073: m[nrl] -= ncl;
2074:
2075: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2076: return m;
1.145 brouard 2077: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
2078: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
2079: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 2080: */
2081: }
2082:
2083: /*************************free matrix ************************/
2084: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
2085: {
2086: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2087: free((FREE_ARG)(m+nrl-NR_END));
2088: }
2089:
2090: /******************* ma3x *******************************/
2091: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
2092: {
2093: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
2094: double ***m;
2095:
2096: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
2097: if (!m) nrerror("allocation failure 1 in matrix()");
2098: m += NR_END;
2099: m -= nrl;
2100:
2101: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
2102: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2103: m[nrl] += NR_END;
2104: m[nrl] -= ncl;
2105:
2106: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2107:
2108: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
2109: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
2110: m[nrl][ncl] += NR_END;
2111: m[nrl][ncl] -= nll;
2112: for (j=ncl+1; j<=nch; j++)
2113: m[nrl][j]=m[nrl][j-1]+nlay;
2114:
2115: for (i=nrl+1; i<=nrh; i++) {
2116: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
2117: for (j=ncl+1; j<=nch; j++)
2118: m[i][j]=m[i][j-1]+nlay;
2119: }
2120: return m;
2121: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
2122: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
2123: */
2124: }
2125:
2126: /*************************free ma3x ************************/
2127: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
2128: {
2129: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
2130: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2131: free((FREE_ARG)(m+nrl-NR_END));
2132: }
2133:
2134: /*************** function subdirf ***********/
2135: char *subdirf(char fileres[])
2136: {
2137: /* Caution optionfilefiname is hidden */
2138: strcpy(tmpout,optionfilefiname);
2139: strcat(tmpout,"/"); /* Add to the right */
2140: strcat(tmpout,fileres);
2141: return tmpout;
2142: }
2143:
2144: /*************** function subdirf2 ***********/
2145: char *subdirf2(char fileres[], char *preop)
2146: {
1.314 brouard 2147: /* Example subdirf2(optionfilefiname,"FB_") with optionfilefiname="texte", result="texte/FB_texte"
2148: Errors in subdirf, 2, 3 while printing tmpout is
1.315 brouard 2149: rewritten within the same printf. Workaround: many printfs */
1.126 brouard 2150: /* Caution optionfilefiname is hidden */
2151: strcpy(tmpout,optionfilefiname);
2152: strcat(tmpout,"/");
2153: strcat(tmpout,preop);
2154: strcat(tmpout,fileres);
2155: return tmpout;
2156: }
2157:
2158: /*************** function subdirf3 ***********/
2159: char *subdirf3(char fileres[], char *preop, char *preop2)
2160: {
2161:
2162: /* Caution optionfilefiname is hidden */
2163: strcpy(tmpout,optionfilefiname);
2164: strcat(tmpout,"/");
2165: strcat(tmpout,preop);
2166: strcat(tmpout,preop2);
2167: strcat(tmpout,fileres);
2168: return tmpout;
2169: }
1.213 brouard 2170:
2171: /*************** function subdirfext ***********/
2172: char *subdirfext(char fileres[], char *preop, char *postop)
2173: {
2174:
2175: strcpy(tmpout,preop);
2176: strcat(tmpout,fileres);
2177: strcat(tmpout,postop);
2178: return tmpout;
2179: }
1.126 brouard 2180:
1.213 brouard 2181: /*************** function subdirfext3 ***********/
2182: char *subdirfext3(char fileres[], char *preop, char *postop)
2183: {
2184:
2185: /* Caution optionfilefiname is hidden */
2186: strcpy(tmpout,optionfilefiname);
2187: strcat(tmpout,"/");
2188: strcat(tmpout,preop);
2189: strcat(tmpout,fileres);
2190: strcat(tmpout,postop);
2191: return tmpout;
2192: }
2193:
1.162 brouard 2194: char *asc_diff_time(long time_sec, char ascdiff[])
2195: {
2196: long sec_left, days, hours, minutes;
2197: days = (time_sec) / (60*60*24);
2198: sec_left = (time_sec) % (60*60*24);
2199: hours = (sec_left) / (60*60) ;
2200: sec_left = (sec_left) %(60*60);
2201: minutes = (sec_left) /60;
2202: sec_left = (sec_left) % (60);
2203: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
2204: return ascdiff;
2205: }
2206:
1.126 brouard 2207: /***************** f1dim *************************/
2208: extern int ncom;
2209: extern double *pcom,*xicom;
2210: extern double (*nrfunc)(double []);
2211:
2212: double f1dim(double x)
2213: {
2214: int j;
2215: double f;
2216: double *xt;
2217:
2218: xt=vector(1,ncom);
2219: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
2220: f=(*nrfunc)(xt);
2221: free_vector(xt,1,ncom);
2222: return f;
2223: }
2224:
2225: /*****************brent *************************/
2226: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 2227: {
2228: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
2229: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
2230: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
2231: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
2232: * returned function value.
2233: */
1.126 brouard 2234: int iter;
2235: double a,b,d,etemp;
1.159 brouard 2236: double fu=0,fv,fw,fx;
1.164 brouard 2237: double ftemp=0.;
1.126 brouard 2238: double p,q,r,tol1,tol2,u,v,w,x,xm;
2239: double e=0.0;
2240:
2241: a=(ax < cx ? ax : cx);
2242: b=(ax > cx ? ax : cx);
2243: x=w=v=bx;
2244: fw=fv=fx=(*f)(x);
2245: for (iter=1;iter<=ITMAX;iter++) {
2246: xm=0.5*(a+b);
2247: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
2248: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
2249: printf(".");fflush(stdout);
2250: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 2251: #ifdef DEBUGBRENT
1.126 brouard 2252: 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);
2253: 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);
2254: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
2255: #endif
2256: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
2257: *xmin=x;
2258: return fx;
2259: }
2260: ftemp=fu;
2261: if (fabs(e) > tol1) {
2262: r=(x-w)*(fx-fv);
2263: q=(x-v)*(fx-fw);
2264: p=(x-v)*q-(x-w)*r;
2265: q=2.0*(q-r);
2266: if (q > 0.0) p = -p;
2267: q=fabs(q);
2268: etemp=e;
2269: e=d;
2270: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 2271: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 2272: else {
1.224 brouard 2273: d=p/q;
2274: u=x+d;
2275: if (u-a < tol2 || b-u < tol2)
2276: d=SIGN(tol1,xm-x);
1.126 brouard 2277: }
2278: } else {
2279: d=CGOLD*(e=(x >= xm ? a-x : b-x));
2280: }
2281: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
2282: fu=(*f)(u);
2283: if (fu <= fx) {
2284: if (u >= x) a=x; else b=x;
2285: SHFT(v,w,x,u)
1.183 brouard 2286: SHFT(fv,fw,fx,fu)
2287: } else {
2288: if (u < x) a=u; else b=u;
2289: if (fu <= fw || w == x) {
1.224 brouard 2290: v=w;
2291: w=u;
2292: fv=fw;
2293: fw=fu;
1.183 brouard 2294: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 2295: v=u;
2296: fv=fu;
1.183 brouard 2297: }
2298: }
1.126 brouard 2299: }
2300: nrerror("Too many iterations in brent");
2301: *xmin=x;
2302: return fx;
2303: }
2304:
2305: /****************** mnbrak ***********************/
2306:
2307: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
2308: double (*func)(double))
1.183 brouard 2309: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
2310: the downhill direction (defined by the function as evaluated at the initial points) and returns
2311: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
2312: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
2313: */
1.126 brouard 2314: double ulim,u,r,q, dum;
2315: double fu;
1.187 brouard 2316:
2317: double scale=10.;
2318: int iterscale=0;
2319:
2320: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
2321: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
2322:
2323:
2324: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
2325: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
2326: /* *bx = *ax - (*ax - *bx)/scale; */
2327: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
2328: /* } */
2329:
1.126 brouard 2330: if (*fb > *fa) {
2331: SHFT(dum,*ax,*bx,dum)
1.183 brouard 2332: SHFT(dum,*fb,*fa,dum)
2333: }
1.126 brouard 2334: *cx=(*bx)+GOLD*(*bx-*ax);
2335: *fc=(*func)(*cx);
1.183 brouard 2336: #ifdef DEBUG
1.224 brouard 2337: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
2338: 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 2339: #endif
1.224 brouard 2340: 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 2341: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 2342: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 2343: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 2344: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
2345: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
2346: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 2347: fu=(*func)(u);
1.163 brouard 2348: #ifdef DEBUG
2349: /* f(x)=A(x-u)**2+f(u) */
2350: double A, fparabu;
2351: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2352: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 2353: 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);
2354: 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 2355: /* And thus,it can be that fu > *fc even if fparabu < *fc */
2356: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
2357: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
2358: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 2359: #endif
1.184 brouard 2360: #ifdef MNBRAKORIGINAL
1.183 brouard 2361: #else
1.191 brouard 2362: /* if (fu > *fc) { */
2363: /* #ifdef DEBUG */
2364: /* printf("mnbrak4 fu > fc \n"); */
2365: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
2366: /* #endif */
2367: /* /\* 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 *\\/ *\/ */
2368: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2369: /* dum=u; /\* Shifting c and u *\/ */
2370: /* u = *cx; */
2371: /* *cx = dum; */
2372: /* dum = fu; */
2373: /* fu = *fc; */
2374: /* *fc =dum; */
2375: /* } else { /\* end *\/ */
2376: /* #ifdef DEBUG */
2377: /* printf("mnbrak3 fu < fc \n"); */
2378: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2379: /* #endif */
2380: /* dum=u; /\* Shifting c and u *\/ */
2381: /* u = *cx; */
2382: /* *cx = dum; */
2383: /* dum = fu; */
2384: /* fu = *fc; */
2385: /* *fc =dum; */
2386: /* } */
1.224 brouard 2387: #ifdef DEBUGMNBRAK
2388: double A, fparabu;
2389: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2390: fparabu= *fa - A*(*ax-u)*(*ax-u);
2391: 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);
2392: 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 2393: #endif
1.191 brouard 2394: dum=u; /* Shifting c and u */
2395: u = *cx;
2396: *cx = dum;
2397: dum = fu;
2398: fu = *fc;
2399: *fc =dum;
1.183 brouard 2400: #endif
1.162 brouard 2401: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2402: #ifdef DEBUG
1.224 brouard 2403: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2404: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2405: #endif
1.126 brouard 2406: fu=(*func)(u);
2407: if (fu < *fc) {
1.183 brouard 2408: #ifdef DEBUG
1.224 brouard 2409: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2410: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2411: #endif
2412: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2413: SHFT(*fb,*fc,fu,(*func)(u))
2414: #ifdef DEBUG
2415: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2416: #endif
2417: }
1.162 brouard 2418: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2419: #ifdef DEBUG
1.224 brouard 2420: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2421: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2422: #endif
1.126 brouard 2423: u=ulim;
2424: fu=(*func)(u);
1.183 brouard 2425: } else { /* u could be left to b (if r > q parabola has a maximum) */
2426: #ifdef DEBUG
1.224 brouard 2427: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2428: 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 2429: #endif
1.126 brouard 2430: u=(*cx)+GOLD*(*cx-*bx);
2431: fu=(*func)(u);
1.224 brouard 2432: #ifdef DEBUG
2433: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2434: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2435: #endif
1.183 brouard 2436: } /* end tests */
1.126 brouard 2437: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2438: SHFT(*fa,*fb,*fc,fu)
2439: #ifdef DEBUG
1.224 brouard 2440: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2441: 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 2442: #endif
2443: } /* 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 2444: }
2445:
2446: /*************** linmin ************************/
1.162 brouard 2447: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2448: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2449: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2450: the value of func at the returned location p . This is actually all accomplished by calling the
2451: routines mnbrak and brent .*/
1.126 brouard 2452: int ncom;
2453: double *pcom,*xicom;
2454: double (*nrfunc)(double []);
2455:
1.224 brouard 2456: #ifdef LINMINORIGINAL
1.126 brouard 2457: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2458: #else
2459: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2460: #endif
1.126 brouard 2461: {
2462: double brent(double ax, double bx, double cx,
2463: double (*f)(double), double tol, double *xmin);
2464: double f1dim(double x);
2465: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2466: double *fc, double (*func)(double));
2467: int j;
2468: double xx,xmin,bx,ax;
2469: double fx,fb,fa;
1.187 brouard 2470:
1.203 brouard 2471: #ifdef LINMINORIGINAL
2472: #else
2473: double scale=10., axs, xxs; /* Scale added for infinity */
2474: #endif
2475:
1.126 brouard 2476: ncom=n;
2477: pcom=vector(1,n);
2478: xicom=vector(1,n);
2479: nrfunc=func;
2480: for (j=1;j<=n;j++) {
2481: pcom[j]=p[j];
1.202 brouard 2482: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2483: }
1.187 brouard 2484:
1.203 brouard 2485: #ifdef LINMINORIGINAL
2486: xx=1.;
2487: #else
2488: axs=0.0;
2489: xxs=1.;
2490: do{
2491: xx= xxs;
2492: #endif
1.187 brouard 2493: ax=0.;
2494: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2495: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2496: /* 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)) */
2497: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2498: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2499: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2500: /* 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 2501: #ifdef LINMINORIGINAL
2502: #else
2503: if (fx != fx){
1.224 brouard 2504: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2505: printf("|");
2506: fprintf(ficlog,"|");
1.203 brouard 2507: #ifdef DEBUGLINMIN
1.224 brouard 2508: 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 2509: #endif
2510: }
1.224 brouard 2511: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2512: #endif
2513:
1.191 brouard 2514: #ifdef DEBUGLINMIN
2515: 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 2516: 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 2517: #endif
1.224 brouard 2518: #ifdef LINMINORIGINAL
2519: #else
1.317 brouard 2520: if(fb == fx){ /* Flat function in the direction */
2521: xmin=xx;
1.224 brouard 2522: *flat=1;
1.317 brouard 2523: }else{
1.224 brouard 2524: *flat=0;
2525: #endif
2526: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2527: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2528: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2529: /* fmin = f(p[j] + xmin * xi[j]) */
2530: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2531: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2532: #ifdef DEBUG
1.224 brouard 2533: 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);
2534: 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);
2535: #endif
2536: #ifdef LINMINORIGINAL
2537: #else
2538: }
1.126 brouard 2539: #endif
1.191 brouard 2540: #ifdef DEBUGLINMIN
2541: printf("linmin end ");
1.202 brouard 2542: fprintf(ficlog,"linmin end ");
1.191 brouard 2543: #endif
1.126 brouard 2544: for (j=1;j<=n;j++) {
1.203 brouard 2545: #ifdef LINMINORIGINAL
2546: xi[j] *= xmin;
2547: #else
2548: #ifdef DEBUGLINMIN
2549: if(xxs <1.0)
2550: printf(" before xi[%d]=%12.8f", j,xi[j]);
2551: #endif
2552: 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) */
2553: #ifdef DEBUGLINMIN
2554: if(xxs <1.0)
2555: 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 );
2556: #endif
2557: #endif
1.187 brouard 2558: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2559: }
1.191 brouard 2560: #ifdef DEBUGLINMIN
1.203 brouard 2561: printf("\n");
1.191 brouard 2562: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2563: 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 2564: for (j=1;j<=n;j++) {
1.202 brouard 2565: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2566: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2567: if(j % ncovmodel == 0){
1.191 brouard 2568: printf("\n");
1.202 brouard 2569: fprintf(ficlog,"\n");
2570: }
1.191 brouard 2571: }
1.203 brouard 2572: #else
1.191 brouard 2573: #endif
1.126 brouard 2574: free_vector(xicom,1,n);
2575: free_vector(pcom,1,n);
2576: }
2577:
2578:
2579: /*************** powell ************************/
1.162 brouard 2580: /*
1.317 brouard 2581: Minimization of a function func of n variables. Input consists in an initial starting point
2582: p[1..n] ; an initial matrix xi[1..n][1..n] whose columns contain the initial set of di-
2583: rections (usually the n unit vectors); and ftol, the fractional tolerance in the function value
2584: such that failure to decrease by more than this amount in one iteration signals doneness. On
1.162 brouard 2585: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2586: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2587: */
1.224 brouard 2588: #ifdef LINMINORIGINAL
2589: #else
2590: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2591: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2592: #endif
1.126 brouard 2593: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2594: double (*func)(double []))
2595: {
1.224 brouard 2596: #ifdef LINMINORIGINAL
2597: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2598: double (*func)(double []));
1.224 brouard 2599: #else
1.241 brouard 2600: void linmin(double p[], double xi[], int n, double *fret,
2601: double (*func)(double []),int *flat);
1.224 brouard 2602: #endif
1.239 brouard 2603: int i,ibig,j,jk,k;
1.126 brouard 2604: double del,t,*pt,*ptt,*xit;
1.181 brouard 2605: double directest;
1.126 brouard 2606: double fp,fptt;
2607: double *xits;
2608: int niterf, itmp;
1.349 ! brouard 2609: int Bigter=0, nBigterf=1;
! 2610:
1.126 brouard 2611: pt=vector(1,n);
2612: ptt=vector(1,n);
2613: xit=vector(1,n);
2614: xits=vector(1,n);
2615: *fret=(*func)(p);
2616: for (j=1;j<=n;j++) pt[j]=p[j];
1.338 brouard 2617: rcurr_time = time(NULL);
2618: fp=(*fret); /* Initialisation */
1.126 brouard 2619: for (*iter=1;;++(*iter)) {
2620: ibig=0;
2621: del=0.0;
1.157 brouard 2622: rlast_time=rcurr_time;
1.349 ! brouard 2623: rlast_btime=rcurr_time;
1.157 brouard 2624: /* (void) gettimeofday(&curr_time,&tzp); */
2625: rcurr_time = time(NULL);
2626: curr_time = *localtime(&rcurr_time);
1.337 brouard 2627: /* 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); */
2628: /* fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f gain=%.12f=%.3g %ld sec. %ld sec.",*iter,*fret, fp-*fret,fp-*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog); */
1.349 ! brouard 2629: Bigter=(*iter - *iter % ncovmodel)/ncovmodel +1; /* Big iteration, i.e on ncovmodel cycle */
! 2630: printf("\nPowell iter=%d Big Iter=%d -2*LL=%.12f gain=%.3lg %ld sec. %ld sec.",*iter,Bigter,*fret,fp-*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
! 2631: fprintf(ficlog,"\nPowell iter=%d Big Iter=%d -2*LL=%.12f gain=%.3lg %ld sec. %ld sec.",*iter,Bigter,*fret,fp-*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
! 2632: fprintf(ficrespow,"%d %d %.12f %d",*iter,Bigter, *fret,curr_time.tm_sec-start_time.tm_sec);
1.324 brouard 2633: fp=(*fret); /* From former iteration or initial value */
1.192 brouard 2634: for (i=1;i<=n;i++) {
1.126 brouard 2635: fprintf(ficrespow," %.12lf", p[i]);
2636: }
1.239 brouard 2637: fprintf(ficrespow,"\n");fflush(ficrespow);
2638: printf("\n#model= 1 + age ");
2639: fprintf(ficlog,"\n#model= 1 + age ");
2640: if(nagesqr==1){
1.241 brouard 2641: printf(" + age*age ");
2642: fprintf(ficlog," + age*age ");
1.239 brouard 2643: }
2644: for(j=1;j <=ncovmodel-2;j++){
2645: if(Typevar[j]==0) {
2646: printf(" + V%d ",Tvar[j]);
2647: fprintf(ficlog," + V%d ",Tvar[j]);
2648: }else if(Typevar[j]==1) {
2649: printf(" + V%d*age ",Tvar[j]);
2650: fprintf(ficlog," + V%d*age ",Tvar[j]);
2651: }else if(Typevar[j]==2) {
2652: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2653: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 ! brouard 2654: }else if(Typevar[j]==3) {
! 2655: printf(" + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
! 2656: fprintf(ficlog," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.239 brouard 2657: }
2658: }
1.126 brouard 2659: printf("\n");
1.239 brouard 2660: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2661: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2662: fprintf(ficlog,"\n");
1.239 brouard 2663: for(i=1,jk=1; i <=nlstate; i++){
2664: for(k=1; k <=(nlstate+ndeath); k++){
2665: if (k != i) {
2666: printf("%d%d ",i,k);
2667: fprintf(ficlog,"%d%d ",i,k);
2668: for(j=1; j <=ncovmodel; j++){
2669: printf("%12.7f ",p[jk]);
2670: fprintf(ficlog,"%12.7f ",p[jk]);
2671: jk++;
2672: }
2673: printf("\n");
2674: fprintf(ficlog,"\n");
2675: }
2676: }
2677: }
1.241 brouard 2678: if(*iter <=3 && *iter >1){
1.157 brouard 2679: tml = *localtime(&rcurr_time);
2680: strcpy(strcurr,asctime(&tml));
2681: rforecast_time=rcurr_time;
1.126 brouard 2682: itmp = strlen(strcurr);
2683: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2684: strcurr[itmp-1]='\0';
1.162 brouard 2685: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2686: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.349 ! brouard 2687: for(nBigterf=1;nBigterf<=31;nBigterf+=10){
! 2688: niterf=nBigterf*ncovmodel;
! 2689: /* rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time); */
1.241 brouard 2690: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2691: forecast_time = *localtime(&rforecast_time);
2692: strcpy(strfor,asctime(&forecast_time));
2693: itmp = strlen(strfor);
2694: if(strfor[itmp-1]=='\n')
2695: strfor[itmp-1]='\0';
1.349 ! brouard 2696: printf(" - if your program needs %d BIG iterations (%d iterations) to converge, convergence will be \n reached in %s i.e.\n on %s (current time is %s);\n",nBigterf, niterf, asc_diff_time(rforecast_time-rcurr_time,tmpout),strfor,strcurr);
! 2697: fprintf(ficlog," - if your program needs %d BIG iterations (%d iterations) to converge, convergence will be \n reached in %s i.e.\n on %s (current time is %s);\n",nBigterf, niterf, asc_diff_time(rforecast_time-rcurr_time,tmpout),strfor,strcurr);
1.126 brouard 2698: }
2699: }
1.187 brouard 2700: for (i=1;i<=n;i++) { /* For each direction i */
2701: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2702: fptt=(*fret);
2703: #ifdef DEBUG
1.203 brouard 2704: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2705: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2706: #endif
1.203 brouard 2707: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2708: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2709: #ifdef LINMINORIGINAL
1.188 brouard 2710: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2711: #else
2712: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2713: flatdir[i]=flat; /* Function is vanishing in that direction i */
2714: #endif
2715: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2716: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2717: /* because that direction will be replaced unless the gain del is small */
2718: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2719: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2720: /* with the new direction. */
2721: del=fabs(fptt-(*fret));
2722: ibig=i;
1.126 brouard 2723: }
2724: #ifdef DEBUG
2725: printf("%d %.12e",i,(*fret));
2726: fprintf(ficlog,"%d %.12e",i,(*fret));
2727: for (j=1;j<=n;j++) {
1.224 brouard 2728: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2729: printf(" x(%d)=%.12e",j,xit[j]);
2730: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2731: }
2732: for(j=1;j<=n;j++) {
1.225 brouard 2733: printf(" p(%d)=%.12e",j,p[j]);
2734: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2735: }
2736: printf("\n");
2737: fprintf(ficlog,"\n");
2738: #endif
1.187 brouard 2739: } /* end loop on each direction i */
2740: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2741: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2742: /* New value of last point Pn is not computed, P(n-1) */
1.319 brouard 2743: for(j=1;j<=n;j++) {
2744: if(flatdir[j] >0){
2745: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2746: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
1.302 brouard 2747: }
1.319 brouard 2748: /* printf("\n"); */
2749: /* fprintf(ficlog,"\n"); */
2750: }
1.243 brouard 2751: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2752: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2753: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2754: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2755: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2756: /* decreased of more than 3.84 */
2757: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2758: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2759: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2760:
1.188 brouard 2761: /* Starting the program with initial values given by a former maximization will simply change */
2762: /* the scales of the directions and the directions, because the are reset to canonical directions */
2763: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2764: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2765: #ifdef DEBUG
2766: int k[2],l;
2767: k[0]=1;
2768: k[1]=-1;
2769: printf("Max: %.12e",(*func)(p));
2770: fprintf(ficlog,"Max: %.12e",(*func)(p));
2771: for (j=1;j<=n;j++) {
2772: printf(" %.12e",p[j]);
2773: fprintf(ficlog," %.12e",p[j]);
2774: }
2775: printf("\n");
2776: fprintf(ficlog,"\n");
2777: for(l=0;l<=1;l++) {
2778: for (j=1;j<=n;j++) {
2779: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2780: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2781: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2782: }
2783: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2784: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2785: }
2786: #endif
2787:
2788: free_vector(xit,1,n);
2789: free_vector(xits,1,n);
2790: free_vector(ptt,1,n);
2791: free_vector(pt,1,n);
2792: return;
1.192 brouard 2793: } /* enough precision */
1.240 brouard 2794: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2795: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2796: ptt[j]=2.0*p[j]-pt[j];
2797: xit[j]=p[j]-pt[j];
2798: pt[j]=p[j];
2799: }
1.181 brouard 2800: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2801: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2802: if (*iter <=4) {
1.225 brouard 2803: #else
2804: #endif
1.224 brouard 2805: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2806: #else
1.161 brouard 2807: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2808: #endif
1.162 brouard 2809: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2810: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2811: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2812: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2813: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2814: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2815: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2816: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2817: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2818: /* Even if f3 <f1, directest can be negative and t >0 */
2819: /* mu² and del² are equal when f3=f1 */
2820: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2821: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2822: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2823: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2824: #ifdef NRCORIGINAL
2825: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2826: #else
2827: 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 2828: t= t- del*SQR(fp-fptt);
1.183 brouard 2829: #endif
1.202 brouard 2830: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2831: #ifdef DEBUG
1.181 brouard 2832: 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);
2833: 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 2834: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2835: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2836: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2837: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2838: 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);
2839: 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);
2840: #endif
1.183 brouard 2841: #ifdef POWELLORIGINAL
2842: if (t < 0.0) { /* Then we use it for new direction */
2843: #else
1.182 brouard 2844: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2845: 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 2846: 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 2847: 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 2848: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2849: }
1.181 brouard 2850: if (directest < 0.0) { /* Then we use it for new direction */
2851: #endif
1.191 brouard 2852: #ifdef DEBUGLINMIN
1.234 brouard 2853: printf("Before linmin in direction P%d-P0\n",n);
2854: for (j=1;j<=n;j++) {
2855: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2856: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2857: if(j % ncovmodel == 0){
2858: printf("\n");
2859: fprintf(ficlog,"\n");
2860: }
2861: }
1.224 brouard 2862: #endif
2863: #ifdef LINMINORIGINAL
1.234 brouard 2864: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2865: #else
1.234 brouard 2866: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2867: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2868: #endif
1.234 brouard 2869:
1.191 brouard 2870: #ifdef DEBUGLINMIN
1.234 brouard 2871: for (j=1;j<=n;j++) {
2872: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2873: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2874: if(j % ncovmodel == 0){
2875: printf("\n");
2876: fprintf(ficlog,"\n");
2877: }
2878: }
1.224 brouard 2879: #endif
1.234 brouard 2880: for (j=1;j<=n;j++) {
2881: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2882: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2883: }
1.224 brouard 2884: #ifdef LINMINORIGINAL
2885: #else
1.234 brouard 2886: for (j=1, flatd=0;j<=n;j++) {
2887: if(flatdir[j]>0)
2888: flatd++;
2889: }
2890: if(flatd >0){
1.255 brouard 2891: printf("%d flat directions: ",flatd);
2892: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2893: for (j=1;j<=n;j++) {
2894: if(flatdir[j]>0){
2895: printf("%d ",j);
2896: fprintf(ficlog,"%d ",j);
2897: }
2898: }
2899: printf("\n");
2900: fprintf(ficlog,"\n");
1.319 brouard 2901: #ifdef FLATSUP
2902: free_vector(xit,1,n);
2903: free_vector(xits,1,n);
2904: free_vector(ptt,1,n);
2905: free_vector(pt,1,n);
2906: return;
2907: #endif
1.234 brouard 2908: }
1.191 brouard 2909: #endif
1.234 brouard 2910: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2911: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2912:
1.126 brouard 2913: #ifdef DEBUG
1.234 brouard 2914: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2915: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2916: for(j=1;j<=n;j++){
2917: printf(" %lf",xit[j]);
2918: fprintf(ficlog," %lf",xit[j]);
2919: }
2920: printf("\n");
2921: fprintf(ficlog,"\n");
1.126 brouard 2922: #endif
1.192 brouard 2923: } /* end of t or directest negative */
1.224 brouard 2924: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2925: #else
1.234 brouard 2926: } /* end if (fptt < fp) */
1.192 brouard 2927: #endif
1.225 brouard 2928: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2929: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2930: #else
1.224 brouard 2931: #endif
1.234 brouard 2932: } /* loop iteration */
1.126 brouard 2933: }
1.234 brouard 2934:
1.126 brouard 2935: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2936:
1.235 brouard 2937: 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 2938: {
1.338 brouard 2939: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij . Nicely done
1.279 brouard 2940: * (and selected quantitative values in nres)
2941: * by left multiplying the unit
2942: * matrix by transitions matrix until convergence is reached with precision ftolpl
2943: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2944: * Wx is row vector: population in state 1, population in state 2, population dead
2945: * or prevalence in state 1, prevalence in state 2, 0
2946: * newm is the matrix after multiplications, its rows are identical at a factor.
2947: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2948: * Output is prlim.
2949: * Initial matrix pimij
2950: */
1.206 brouard 2951: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2952: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2953: /* 0, 0 , 1} */
2954: /*
2955: * and after some iteration: */
2956: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2957: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2958: /* 0, 0 , 1} */
2959: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2960: /* {0.51571254859325999, 0.4842874514067399, */
2961: /* 0.51326036147820708, 0.48673963852179264} */
2962: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2963:
1.332 brouard 2964: int i, ii,j,k, k1;
1.209 brouard 2965: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2966: /* double **matprod2(); */ /* test */
1.218 brouard 2967: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2968: double **newm;
1.209 brouard 2969: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2970: int ncvloop=0;
1.288 brouard 2971: int first=0;
1.169 brouard 2972:
1.209 brouard 2973: min=vector(1,nlstate);
2974: max=vector(1,nlstate);
2975: meandiff=vector(1,nlstate);
2976:
1.218 brouard 2977: /* Starting with matrix unity */
1.126 brouard 2978: for (ii=1;ii<=nlstate+ndeath;ii++)
2979: for (j=1;j<=nlstate+ndeath;j++){
2980: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2981: }
1.169 brouard 2982:
2983: cov[1]=1.;
2984:
2985: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2986: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2987: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2988: ncvloop++;
1.126 brouard 2989: newm=savm;
2990: /* Covariates have to be included here again */
1.138 brouard 2991: cov[2]=agefin;
1.319 brouard 2992: if(nagesqr==1){
2993: cov[3]= agefin*agefin;
2994: }
1.332 brouard 2995: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
2996: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
2997: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 ! brouard 2998: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 2999: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
3000: }else{
3001: cov[2+nagesqr+k1]=precov[nres][k1];
3002: }
3003: }/* End of loop on model equation */
3004:
3005: /* Start of old code (replaced by a loop on position in the model equation */
3006: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only of the model *\/ */
3007: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
3008: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; *\/ */
3009: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TnsdVar[TvarsD[k]])]; */
3010: /* /\* model = 1 +age + V1*V3 + age*V1 + V2 + V1 + age*V2 + V3 + V3*age + V1*V2 */
3011: /* * k 1 2 3 4 5 6 7 8 */
3012: /* *cov[] 1 2 3 4 5 6 7 8 9 10 */
3013: /* *TypeVar[k] 2 1 0 0 1 0 1 2 */
3014: /* *Dummy[k] 0 2 0 0 2 0 2 0 */
3015: /* *Tvar[k] 4 1 2 1 2 3 3 5 */
3016: /* *nsd=3 (1) (2) (3) */
3017: /* *TvarsD[nsd] [1]=2 1 3 */
3018: /* *TnsdVar [2]=2 [1]=1 [3]=3 */
3019: /* *TvarsDind[nsd](=k) [1]=3 [2]=4 [3]=6 */
3020: /* *Tage[] [1]=1 [2]=2 [3]=3 */
3021: /* *Tvard[] [1][1]=1 [2][1]=1 */
3022: /* * [1][2]=3 [2][2]=2 */
3023: /* *Tprod[](=k) [1]=1 [2]=8 */
3024: /* *TvarsDp(=Tvar) [1]=1 [2]=2 [3]=3 [4]=5 */
3025: /* *TvarD (=k) [1]=1 [2]=3 [3]=4 [3]=6 [4]=6 */
3026: /* *TvarsDpType */
3027: /* *si model= 1 + age + V3 + V2*age + V2 + V3*age */
3028: /* * nsd=1 (1) (2) */
3029: /* *TvarsD[nsd] 3 2 */
3030: /* *TnsdVar (3)=1 (2)=2 */
3031: /* *TvarsDind[nsd](=k) [1]=1 [2]=3 */
3032: /* *Tage[] [1]=2 [2]= 3 */
3033: /* *\/ */
3034: /* /\* cov[++k1]=nbcode[TvarsD[k]][codtabm(ij,k)]; *\/ */
3035: /* /\* 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)); *\/ */
3036: /* } */
3037: /* for (k=1; k<=nsq;k++) { /\* For single quantitative varying covariates only of the model *\/ */
3038: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3039: /* /\* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline *\/ */
3040: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
3041: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][resultmodel[nres][k1]] */
3042: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
3043: /* /\* 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]); *\/ */
3044: /* } */
3045: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
3046: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
3047: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3048: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
3049: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
3050: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3051: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
3052: /* } */
3053: /* /\* 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]); *\/ */
3054: /* } */
3055: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
3056: /* /\* 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]); *\/ */
3057: /* if(Dummy[Tvard[k][1]]==0){ */
3058: /* if(Dummy[Tvard[k][2]]==0){ */
3059: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3060: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3061: /* }else{ */
3062: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3063: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
3064: /* } */
3065: /* }else{ */
3066: /* if(Dummy[Tvard[k][2]]==0){ */
3067: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3068: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
3069: /* }else{ */
3070: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3071: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
3072: /* } */
3073: /* } */
3074: /* } /\* End product without age *\/ */
3075: /* ENd of old code */
1.138 brouard 3076: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
3077: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
3078: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 3079: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3080: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.319 brouard 3081: /* age and covariate values of ij are in 'cov' */
1.142 brouard 3082: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 3083:
1.126 brouard 3084: savm=oldm;
3085: oldm=newm;
1.209 brouard 3086:
3087: for(j=1; j<=nlstate; j++){
3088: max[j]=0.;
3089: min[j]=1.;
3090: }
3091: for(i=1;i<=nlstate;i++){
3092: sumnew=0;
3093: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
3094: for(j=1; j<=nlstate; j++){
3095: prlim[i][j]= newm[i][j]/(1-sumnew);
3096: max[j]=FMAX(max[j],prlim[i][j]);
3097: min[j]=FMIN(min[j],prlim[i][j]);
3098: }
3099: }
3100:
1.126 brouard 3101: maxmax=0.;
1.209 brouard 3102: for(j=1; j<=nlstate; j++){
3103: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
3104: maxmax=FMAX(maxmax,meandiff[j]);
3105: /* 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 3106: } /* j loop */
1.203 brouard 3107: *ncvyear= (int)age- (int)agefin;
1.208 brouard 3108: /* 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 3109: if(maxmax < ftolpl){
1.209 brouard 3110: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
3111: free_vector(min,1,nlstate);
3112: free_vector(max,1,nlstate);
3113: free_vector(meandiff,1,nlstate);
1.126 brouard 3114: return prlim;
3115: }
1.288 brouard 3116: } /* agefin loop */
1.208 brouard 3117: /* After some age loop it doesn't converge */
1.288 brouard 3118: if(!first){
3119: first=1;
3120: 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 3121: 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);
3122: }else if (first >=1 && first <10){
3123: 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);
3124: first++;
3125: }else if (first ==10){
3126: 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);
3127: 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");
3128: fprintf(ficlog,"Warning: the stable prevalence no convergence; too many cases, giving up noticing, even in log file\n");
3129: first++;
1.288 brouard 3130: }
3131:
1.209 brouard 3132: /* 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); */
3133: free_vector(min,1,nlstate);
3134: free_vector(max,1,nlstate);
3135: free_vector(meandiff,1,nlstate);
1.208 brouard 3136:
1.169 brouard 3137: return prlim; /* should not reach here */
1.126 brouard 3138: }
3139:
1.217 brouard 3140:
3141: /**** Back Prevalence limit (stable or period prevalence) ****************/
3142:
1.218 brouard 3143: /* 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) */
3144: /* 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 3145: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 3146: {
1.264 brouard 3147: /* 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 3148: matrix by transitions matrix until convergence is reached with precision ftolpl */
3149: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
3150: /* Wx is row vector: population in state 1, population in state 2, population dead */
3151: /* or prevalence in state 1, prevalence in state 2, 0 */
3152: /* newm is the matrix after multiplications, its rows are identical at a factor */
3153: /* Initial matrix pimij */
3154: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
3155: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
3156: /* 0, 0 , 1} */
3157: /*
3158: * and after some iteration: */
3159: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
3160: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
3161: /* 0, 0 , 1} */
3162: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
3163: /* {0.51571254859325999, 0.4842874514067399, */
3164: /* 0.51326036147820708, 0.48673963852179264} */
3165: /* If we start from prlim again, prlim tends to a constant matrix */
3166:
1.332 brouard 3167: int i, ii,j,k, k1;
1.247 brouard 3168: int first=0;
1.217 brouard 3169: double *min, *max, *meandiff, maxmax,sumnew=0.;
3170: /* double **matprod2(); */ /* test */
3171: double **out, cov[NCOVMAX+1], **bmij();
3172: double **newm;
1.218 brouard 3173: double **dnewm, **doldm, **dsavm; /* for use */
3174: double **oldm, **savm; /* for use */
3175:
1.217 brouard 3176: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
3177: int ncvloop=0;
3178:
3179: min=vector(1,nlstate);
3180: max=vector(1,nlstate);
3181: meandiff=vector(1,nlstate);
3182:
1.266 brouard 3183: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
3184: oldm=oldms; savm=savms;
3185:
3186: /* Starting with matrix unity */
3187: for (ii=1;ii<=nlstate+ndeath;ii++)
3188: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 3189: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3190: }
3191:
3192: cov[1]=1.;
3193:
3194: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3195: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 3196: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 3197: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
3198: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 3199: ncvloop++;
1.218 brouard 3200: newm=savm; /* oldm should be kept from previous iteration or unity at start */
3201: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 3202: /* Covariates have to be included here again */
3203: cov[2]=agefin;
1.319 brouard 3204: if(nagesqr==1){
1.217 brouard 3205: cov[3]= agefin*agefin;;
1.319 brouard 3206: }
1.332 brouard 3207: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 ! brouard 3208: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3209: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.242 brouard 3210: }else{
1.332 brouard 3211: cov[2+nagesqr+k1]=precov[nres][k1];
1.242 brouard 3212: }
1.332 brouard 3213: }/* End of loop on model equation */
3214:
3215: /* Old code */
3216:
3217: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
3218: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
3219: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; */
3220: /* /\* 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)); *\/ */
3221: /* } */
3222: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
3223: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
3224: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
3225: /* /\* /\\* 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])]); *\\/ *\/ */
3226: /* /\* } *\/ */
3227: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
3228: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3229: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
3230: /* /\* 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]); *\/ */
3231: /* } */
3232: /* /\* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; *\/ */
3233: /* /\* for (k=1; k<=cptcovprod;k++) /\\* Useless *\\/ *\/ */
3234: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\\/ *\/ */
3235: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3236: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
3237: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age *\\/ ERROR ???*\/ */
3238: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
3239: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3240: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
3241: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3242: /* } */
3243: /* /\* 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]); *\/ */
3244: /* } */
3245: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
3246: /* /\* 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]); *\/ */
3247: /* if(Dummy[Tvard[k][1]]==0){ */
3248: /* if(Dummy[Tvard[k][2]]==0){ */
3249: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3250: /* }else{ */
3251: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3252: /* } */
3253: /* }else{ */
3254: /* if(Dummy[Tvard[k][2]]==0){ */
3255: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3256: /* }else{ */
3257: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3258: /* } */
3259: /* } */
3260: /* } */
1.217 brouard 3261:
3262: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
3263: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
3264: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
3265: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3266: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 3267: /* ij should be linked to the correct index of cov */
3268: /* age and covariate values ij are in 'cov', but we need to pass
3269: * ij for the observed prevalence at age and status and covariate
3270: * number: prevacurrent[(int)agefin][ii][ij]
3271: */
3272: /* 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 *\/ */
3273: /* 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 *\/ */
3274: 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 3275: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 3276: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
3277: /* for(i=1; i<=nlstate+ndeath; i++) { */
3278: /* printf("%d newm= ",i); */
3279: /* for(j=1;j<=nlstate+ndeath;j++) { */
3280: /* printf("%f ",newm[i][j]); */
3281: /* } */
3282: /* printf("oldm * "); */
3283: /* for(j=1;j<=nlstate+ndeath;j++) { */
3284: /* printf("%f ",oldm[i][j]); */
3285: /* } */
1.268 brouard 3286: /* printf(" bmmij "); */
1.266 brouard 3287: /* for(j=1;j<=nlstate+ndeath;j++) { */
3288: /* printf("%f ",pmmij[i][j]); */
3289: /* } */
3290: /* printf("\n"); */
3291: /* } */
3292: /* } */
1.217 brouard 3293: savm=oldm;
3294: oldm=newm;
1.266 brouard 3295:
1.217 brouard 3296: for(j=1; j<=nlstate; j++){
3297: max[j]=0.;
3298: min[j]=1.;
3299: }
3300: for(j=1; j<=nlstate; j++){
3301: for(i=1;i<=nlstate;i++){
1.234 brouard 3302: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
3303: bprlim[i][j]= newm[i][j];
3304: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
3305: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 3306: }
3307: }
1.218 brouard 3308:
1.217 brouard 3309: maxmax=0.;
3310: for(i=1; i<=nlstate; i++){
1.318 brouard 3311: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column, could be nan! */
1.217 brouard 3312: maxmax=FMAX(maxmax,meandiff[i]);
3313: /* 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 3314: } /* i loop */
1.217 brouard 3315: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 3316: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3317: if(maxmax < ftolpl){
1.220 brouard 3318: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3319: free_vector(min,1,nlstate);
3320: free_vector(max,1,nlstate);
3321: free_vector(meandiff,1,nlstate);
3322: return bprlim;
3323: }
1.288 brouard 3324: } /* agefin loop */
1.217 brouard 3325: /* After some age loop it doesn't converge */
1.288 brouard 3326: if(!first){
1.247 brouard 3327: first=1;
3328: 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\
3329: 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);
3330: }
3331: 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 3332: 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);
3333: /* 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); */
3334: free_vector(min,1,nlstate);
3335: free_vector(max,1,nlstate);
3336: free_vector(meandiff,1,nlstate);
3337:
3338: return bprlim; /* should not reach here */
3339: }
3340:
1.126 brouard 3341: /*************** transition probabilities ***************/
3342:
3343: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
3344: {
1.138 brouard 3345: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 3346: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 3347: model to the ncovmodel covariates (including constant and age).
3348: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3349: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3350: ncth covariate in the global vector x is given by the formula:
3351: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3352: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3353: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3354: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 3355: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 3356: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 3357: Sum on j ps[i][j] should equal to 1.
1.138 brouard 3358: */
3359: double s1, lnpijopii;
1.126 brouard 3360: /*double t34;*/
1.164 brouard 3361: int i,j, nc, ii, jj;
1.126 brouard 3362:
1.223 brouard 3363: for(i=1; i<= nlstate; i++){
3364: for(j=1; j<i;j++){
3365: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3366: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3367: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3368: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3369: }
3370: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3371: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3372: }
3373: for(j=i+1; j<=nlstate+ndeath;j++){
3374: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3375: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3376: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3377: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3378: }
3379: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3380: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3381: }
3382: }
1.218 brouard 3383:
1.223 brouard 3384: for(i=1; i<= nlstate; i++){
3385: s1=0;
3386: for(j=1; j<i; j++){
1.339 brouard 3387: /* printf("debug1 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 3388: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3389: }
3390: for(j=i+1; j<=nlstate+ndeath; j++){
1.339 brouard 3391: /* printf("debug2 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 3392: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3393: }
3394: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3395: ps[i][i]=1./(s1+1.);
3396: /* Computing other pijs */
3397: for(j=1; j<i; j++)
1.325 brouard 3398: ps[i][j]= exp(ps[i][j])*ps[i][i];/* Bug valgrind */
1.223 brouard 3399: for(j=i+1; j<=nlstate+ndeath; j++)
3400: ps[i][j]= exp(ps[i][j])*ps[i][i];
3401: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3402: } /* end i */
1.218 brouard 3403:
1.223 brouard 3404: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3405: for(jj=1; jj<= nlstate+ndeath; jj++){
3406: ps[ii][jj]=0;
3407: ps[ii][ii]=1;
3408: }
3409: }
1.294 brouard 3410:
3411:
1.223 brouard 3412: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3413: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3414: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3415: /* } */
3416: /* printf("\n "); */
3417: /* } */
3418: /* printf("\n ");printf("%lf ",cov[2]);*/
3419: /*
3420: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 3421: goto end;*/
1.266 brouard 3422: return ps; /* Pointer is unchanged since its call */
1.126 brouard 3423: }
3424:
1.218 brouard 3425: /*************** backward transition probabilities ***************/
3426:
3427: /* 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 ) */
3428: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
3429: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
3430: {
1.302 brouard 3431: /* 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 3432: * 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 3433: */
1.218 brouard 3434: int i, ii, j,k;
1.222 brouard 3435:
3436: double **out, **pmij();
3437: double sumnew=0.;
1.218 brouard 3438: double agefin;
1.292 brouard 3439: 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 3440: double **dnewm, **dsavm, **doldm;
3441: double **bbmij;
3442:
1.218 brouard 3443: doldm=ddoldms; /* global pointers */
1.222 brouard 3444: dnewm=ddnewms;
3445: dsavm=ddsavms;
1.318 brouard 3446:
3447: /* Debug */
3448: /* printf("Bmij ij=%d, cov[2}=%f\n", ij, cov[2]); */
1.222 brouard 3449: agefin=cov[2];
1.268 brouard 3450: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 3451: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 3452: the observed prevalence (with this covariate ij) at beginning of transition */
3453: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 3454:
3455: /* P_x */
1.325 brouard 3456: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm *//* Bug valgrind */
1.268 brouard 3457: /* outputs pmmij which is a stochastic matrix in row */
3458:
3459: /* Diag(w_x) */
1.292 brouard 3460: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 3461: sumnew=0.;
1.269 brouard 3462: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 3463: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.297 brouard 3464: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 3465: sumnew+=prevacurrent[(int)agefin][ii][ij];
3466: }
3467: if(sumnew >0.01){ /* At least some value in the prevalence */
3468: for (ii=1;ii<=nlstate+ndeath;ii++){
3469: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 3470: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 3471: }
3472: }else{
3473: for (ii=1;ii<=nlstate+ndeath;ii++){
3474: for (j=1;j<=nlstate+ndeath;j++)
3475: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
3476: }
3477: /* if(sumnew <0.9){ */
3478: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3479: /* } */
3480: }
3481: k3=0.0; /* We put the last diagonal to 0 */
3482: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3483: doldm[ii][ii]= k3;
3484: }
3485: /* End doldm, At the end doldm is diag[(w_i)] */
3486:
1.292 brouard 3487: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
3488: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 3489:
1.292 brouard 3490: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 3491: /* 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 3492: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3493: sumnew=0.;
1.222 brouard 3494: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3495: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3496: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3497: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3498: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3499: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3500: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3501: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3502: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3503: /* }else */
1.268 brouard 3504: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3505: } /*End ii */
3506: } /* 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 */
3507:
1.292 brouard 3508: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 3509: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3510: /* end bmij */
1.266 brouard 3511: return ps; /*pointer is unchanged */
1.218 brouard 3512: }
1.217 brouard 3513: /*************** transition probabilities ***************/
3514:
1.218 brouard 3515: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3516: {
3517: /* According to parameters values stored in x and the covariate's values stored in cov,
3518: computes the probability to be observed in state j being in state i by appying the
3519: model to the ncovmodel covariates (including constant and age).
3520: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3521: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3522: ncth covariate in the global vector x is given by the formula:
3523: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3524: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3525: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3526: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3527: Outputs ps[i][j] the probability to be observed in j being in j according to
3528: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3529: */
3530: double s1, lnpijopii;
3531: /*double t34;*/
3532: int i,j, nc, ii, jj;
3533:
1.234 brouard 3534: for(i=1; i<= nlstate; i++){
3535: for(j=1; j<i;j++){
3536: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3537: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3538: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3539: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3540: }
3541: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3542: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3543: }
3544: for(j=i+1; j<=nlstate+ndeath;j++){
3545: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3546: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3547: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3548: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3549: }
3550: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3551: }
3552: }
3553:
3554: for(i=1; i<= nlstate; i++){
3555: s1=0;
3556: for(j=1; j<i; j++){
3557: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3558: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3559: }
3560: for(j=i+1; j<=nlstate+ndeath; j++){
3561: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3562: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3563: }
3564: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3565: ps[i][i]=1./(s1+1.);
3566: /* Computing other pijs */
3567: for(j=1; j<i; j++)
3568: ps[i][j]= exp(ps[i][j])*ps[i][i];
3569: for(j=i+1; j<=nlstate+ndeath; j++)
3570: ps[i][j]= exp(ps[i][j])*ps[i][i];
3571: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3572: } /* end i */
3573:
3574: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3575: for(jj=1; jj<= nlstate+ndeath; jj++){
3576: ps[ii][jj]=0;
3577: ps[ii][ii]=1;
3578: }
3579: }
1.296 brouard 3580: /* Added for prevbcast */ /* Transposed matrix too */
1.234 brouard 3581: for(jj=1; jj<= nlstate+ndeath; jj++){
3582: s1=0.;
3583: for(ii=1; ii<= nlstate+ndeath; ii++){
3584: s1+=ps[ii][jj];
3585: }
3586: for(ii=1; ii<= nlstate; ii++){
3587: ps[ii][jj]=ps[ii][jj]/s1;
3588: }
3589: }
3590: /* Transposition */
3591: for(jj=1; jj<= nlstate+ndeath; jj++){
3592: for(ii=jj; ii<= nlstate+ndeath; ii++){
3593: s1=ps[ii][jj];
3594: ps[ii][jj]=ps[jj][ii];
3595: ps[jj][ii]=s1;
3596: }
3597: }
3598: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3599: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3600: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3601: /* } */
3602: /* printf("\n "); */
3603: /* } */
3604: /* printf("\n ");printf("%lf ",cov[2]);*/
3605: /*
3606: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3607: goto end;*/
3608: return ps;
1.217 brouard 3609: }
3610:
3611:
1.126 brouard 3612: /**************** Product of 2 matrices ******************/
3613:
1.145 brouard 3614: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3615: {
3616: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3617: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3618: /* in, b, out are matrice of pointers which should have been initialized
3619: before: only the contents of out is modified. The function returns
3620: a pointer to pointers identical to out */
1.145 brouard 3621: int i, j, k;
1.126 brouard 3622: for(i=nrl; i<= nrh; i++)
1.145 brouard 3623: for(k=ncolol; k<=ncoloh; k++){
3624: out[i][k]=0.;
3625: for(j=ncl; j<=nch; j++)
3626: out[i][k] +=in[i][j]*b[j][k];
3627: }
1.126 brouard 3628: return out;
3629: }
3630:
3631:
3632: /************* Higher Matrix Product ***************/
3633:
1.235 brouard 3634: 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 3635: {
1.336 brouard 3636: /* Already optimized with precov.
3637: 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 3638: 'nhstepm*hstepm*stepm' months (i.e. until
3639: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3640: nhstepm*hstepm matrices.
3641: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3642: (typically every 2 years instead of every month which is too big
3643: for the memory).
3644: Model is determined by parameters x and covariates have to be
3645: included manually here.
3646:
3647: */
3648:
1.330 brouard 3649: int i, j, d, h, k, k1;
1.131 brouard 3650: double **out, cov[NCOVMAX+1];
1.126 brouard 3651: double **newm;
1.187 brouard 3652: double agexact;
1.214 brouard 3653: double agebegin, ageend;
1.126 brouard 3654:
3655: /* Hstepm could be zero and should return the unit matrix */
3656: for (i=1;i<=nlstate+ndeath;i++)
3657: for (j=1;j<=nlstate+ndeath;j++){
3658: oldm[i][j]=(i==j ? 1.0 : 0.0);
3659: po[i][j][0]=(i==j ? 1.0 : 0.0);
3660: }
3661: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3662: for(h=1; h <=nhstepm; h++){
3663: for(d=1; d <=hstepm; d++){
3664: newm=savm;
3665: /* Covariates have to be included here again */
3666: cov[1]=1.;
1.214 brouard 3667: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3668: cov[2]=agexact;
1.319 brouard 3669: if(nagesqr==1){
1.227 brouard 3670: cov[3]= agexact*agexact;
1.319 brouard 3671: }
1.330 brouard 3672: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
3673: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
3674: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 ! brouard 3675: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3676: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
3677: }else{
3678: cov[2+nagesqr+k1]=precov[nres][k1];
3679: }
3680: }/* End of loop on model equation */
3681: /* Old code */
3682: /* if( Dummy[k1]==0 && Typevar[k1]==0 ){ /\* Single dummy *\/ */
3683: /* /\* V(Tvarsel)=Tvalsel=Tresult[nres][pos](value); V(Tvresult[nres][pos] (variable): V(variable)=value) *\/ */
3684: /* /\* for (k=1; k<=nsd;k++) { /\\* For single dummy covariates only *\\/ *\/ */
3685: /* /\* /\\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\\/ *\/ */
3686: /* /\* codtabm(ij,k) (1 & (ij-1) >> (k-1))+1 *\/ */
3687: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3688: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3689: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
3690: /* /\* nsd 1 2 3 *\/ /\* Counting single dummies covar fixed or tv *\/ */
3691: /* /\*TvarsD[nsd] 4 3 1 *\/ /\* ID of single dummy cova fixed or timevary*\/ */
3692: /* /\*TvarsDind[k] 2 3 9 *\/ /\* position K of single dummy cova *\/ */
3693: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];or [codtabm(ij,TnsdVar[TvarsD[k]] *\/ */
3694: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
3695: /* /\* 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]])); *\/ */
3696: /* 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); */
3697: /* printf("hpxij new Dummy precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3698: /* }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /\* Single quantitative variables *\/ */
3699: /* /\* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline *\/ */
3700: /* cov[2+nagesqr+k1]=Tqresult[nres][resultmodel[nres][k1]]; */
3701: /* /\* for (k=1; k<=nsq;k++) { /\\* For single varying covariates only *\\/ *\/ */
3702: /* /\* /\\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\\/ *\/ */
3703: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
3704: /* 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]]); */
3705: /* printf("hpxij new Quanti precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3706: /* }else if( Dummy[k1]==2 ){ /\* For dummy with age product *\/ */
3707: /* /\* Tvar[k1] Variable in the age product age*V1 is 1 *\/ */
3708: /* /\* [Tinvresult[nres][V1] is its value in the resultline nres *\/ */
3709: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvar[k1]]*cov[2]; */
3710: /* 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]); */
3711: /* printf("hpxij new Dummy with age product precov[nres=%d][k1=%d]=%.4f * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
3712:
3713: /* /\* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; *\/ */
3714: /* /\* for (k=1; k<=cptcovage;k++){ /\\* For product with age V1+V1*age +V4 +age*V3 *\\/ *\/ */
3715: /* /\* 1+2 Tage[1]=2 TVar[2]=1 Dummy[2]=2, Tage[2]=4 TVar[4]=3 Dummy[4]=3 quant*\/ */
3716: /* /\* *\/ */
1.330 brouard 3717: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3718: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3719: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
1.332 brouard 3720: /* /\*cptcovage=2 1 2 *\/ */
3721: /* /\*Tage[k]= 5 8 *\/ */
3722: /* }else if( Dummy[k1]==3 ){ /\* For quant with age product *\/ */
3723: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
3724: /* 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]]); */
3725: /* printf("hpxij new Quanti with age product precov[nres=%d][k1=%d] * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
3726: /* /\* if(Dummy[Tage[k]]== 2){ /\\* dummy with age *\\/ *\/ */
3727: /* /\* /\\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\\* dummy with age *\\\/ *\\/ *\/ */
3728: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\\/ *\/ */
3729: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\\/ *\/ */
3730: /* /\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\/ */
3731: /* /\* 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); *\/ */
3732: /* /\* } else if(Dummy[Tage[k]]== 3){ /\\* quantitative with age *\\/ *\/ */
3733: /* /\* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; *\/ */
3734: /* /\* } *\/ */
3735: /* /\* 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]); *\/ */
3736: /* }else if(Typevar[k1]==2 ){ /\* For product (not with age) *\/ */
3737: /* /\* for (k=1; k<=cptcovprod;k++){ /\\* For product without age *\\/ *\/ */
3738: /* /\* /\\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\\/ *\/ */
3739: /* /\* /\\* k 1 2 3 4 5 6 7 8 9 *\\/ *\/ */
3740: /* /\* /\\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\\/ *\/ */
3741: /* /\* /\\*cptcovprod=1 1 2 *\\/ *\/ */
3742: /* /\* /\\*Tprod[]= 4 7 *\\/ *\/ */
3743: /* /\* /\\*Tvard[][1] 4 1 *\\/ *\/ */
3744: /* /\* /\\*Tvard[][2] 3 2 *\\/ *\/ */
1.330 brouard 3745:
1.332 brouard 3746: /* /\* 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])]); *\/ */
3747: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3748: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]]; */
3749: /* 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]]); */
3750: /* printf("hpxij new Product no age product precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3751:
3752: /* /\* if(Dummy[Tvardk[k1][1]]==0){ *\/ */
3753: /* /\* if(Dummy[Tvardk[k1][2]]==0){ /\\* Product of dummies *\\/ *\/ */
3754: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3755: /* /\* cov[2+nagesqr+k1]=Tinvresult[nres][Tvardk[k1][1]] * Tinvresult[nres][Tvardk[k1][2]]; *\/ */
3756: /* /\* 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]])]; *\/ */
3757: /* /\* }else{ /\\* Product of dummy by quantitative *\\/ *\/ */
3758: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,TnsdVar[Tvard[k][1]])] * Tqresult[nres][k]; *\/ */
3759: /* /\* cov[2+nagesqr+k1]=Tresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]]; *\/ */
3760: /* /\* } *\/ */
3761: /* /\* }else{ /\\* Product of quantitative by...*\\/ *\/ */
3762: /* /\* if(Dummy[Tvard[k][2]]==0){ /\\* quant by dummy *\\/ *\/ */
3763: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][Tvard[k][1]]; *\\/ *\/ */
3764: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
3765: /* /\* }else{ /\\* Product of two quant *\\/ *\/ */
3766: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\\/ *\/ */
3767: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
3768: /* /\* } *\/ */
3769: /* /\* }/\\*end of products quantitative *\\/ *\/ */
3770: /* }/\*end of products *\/ */
3771: /* } /\* End of loop on model equation *\/ */
1.235 brouard 3772: /* for (k=1; k<=cptcovn;k++) */
3773: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3774: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3775: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3776: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3777: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3778:
3779:
1.126 brouard 3780: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3781: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.319 brouard 3782: /* right multiplication of oldm by the current matrix */
1.126 brouard 3783: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3784: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3785: /* if((int)age == 70){ */
3786: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3787: /* for(i=1; i<=nlstate+ndeath; i++) { */
3788: /* printf("%d pmmij ",i); */
3789: /* for(j=1;j<=nlstate+ndeath;j++) { */
3790: /* printf("%f ",pmmij[i][j]); */
3791: /* } */
3792: /* printf(" oldm "); */
3793: /* for(j=1;j<=nlstate+ndeath;j++) { */
3794: /* printf("%f ",oldm[i][j]); */
3795: /* } */
3796: /* printf("\n"); */
3797: /* } */
3798: /* } */
1.126 brouard 3799: savm=oldm;
3800: oldm=newm;
3801: }
3802: for(i=1; i<=nlstate+ndeath; i++)
3803: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3804: po[i][j][h]=newm[i][j];
3805: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3806: }
1.128 brouard 3807: /*printf("h=%d ",h);*/
1.126 brouard 3808: } /* end h */
1.267 brouard 3809: /* printf("\n H=%d \n",h); */
1.126 brouard 3810: return po;
3811: }
3812:
1.217 brouard 3813: /************* Higher Back Matrix Product ***************/
1.218 brouard 3814: /* 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 3815: 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 3816: {
1.332 brouard 3817: /* For dummy covariates given in each resultline (for historical, computes the corresponding combination ij),
3818: computes the transition matrix starting at age 'age' over
1.217 brouard 3819: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3820: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3821: nhstepm*hstepm matrices.
3822: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3823: (typically every 2 years instead of every month which is too big
1.217 brouard 3824: for the memory).
1.218 brouard 3825: Model is determined by parameters x and covariates have to be
1.266 brouard 3826: included manually here. Then we use a call to bmij(x and cov)
3827: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3828: */
1.217 brouard 3829:
1.332 brouard 3830: int i, j, d, h, k, k1;
1.266 brouard 3831: double **out, cov[NCOVMAX+1], **bmij();
3832: double **newm, ***newmm;
1.217 brouard 3833: double agexact;
3834: double agebegin, ageend;
1.222 brouard 3835: double **oldm, **savm;
1.217 brouard 3836:
1.266 brouard 3837: newmm=po; /* To be saved */
3838: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3839: /* Hstepm could be zero and should return the unit matrix */
3840: for (i=1;i<=nlstate+ndeath;i++)
3841: for (j=1;j<=nlstate+ndeath;j++){
3842: oldm[i][j]=(i==j ? 1.0 : 0.0);
3843: po[i][j][0]=(i==j ? 1.0 : 0.0);
3844: }
3845: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3846: for(h=1; h <=nhstepm; h++){
3847: for(d=1; d <=hstepm; d++){
3848: newm=savm;
3849: /* Covariates have to be included here again */
3850: cov[1]=1.;
1.271 brouard 3851: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3852: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
1.318 brouard 3853: /* Debug */
3854: /* printf("hBxij age=%lf, agexact=%lf\n", age, agexact); */
1.217 brouard 3855: cov[2]=agexact;
1.332 brouard 3856: if(nagesqr==1){
1.222 brouard 3857: cov[3]= agexact*agexact;
1.332 brouard 3858: }
3859: /** New code */
3860: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 ! brouard 3861: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3862: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.325 brouard 3863: }else{
1.332 brouard 3864: cov[2+nagesqr+k1]=precov[nres][k1];
1.325 brouard 3865: }
1.332 brouard 3866: }/* End of loop on model equation */
3867: /** End of new code */
3868: /** This was old code */
3869: /* for (k=1; k<=nsd;k++){ /\* For single dummy covariates only *\//\* cptcovn error *\/ */
3870: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
3871: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
3872: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])];/\* Bug valgrind *\/ */
3873: /* /\* 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)); *\/ */
3874: /* } */
3875: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
3876: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3877: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
3878: /* /\* 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]); *\/ */
3879: /* } */
3880: /* for (k=1; k<=cptcovage;k++){ /\* Should start at cptcovn+1 *\//\* For product with age *\/ */
3881: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age error!!!*\\/ *\/ */
3882: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
3883: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3884: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
3885: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3886: /* } */
3887: /* /\* 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]); *\/ */
3888: /* } */
3889: /* for (k=1; k<=cptcovprod;k++){ /\* Useless because included in cptcovn *\/ */
3890: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])]*nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3891: /* if(Dummy[Tvard[k][1]]==0){ */
3892: /* if(Dummy[Tvard[k][2]]==0){ */
3893: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][1])]; */
3894: /* }else{ */
3895: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3896: /* } */
3897: /* }else{ */
3898: /* if(Dummy[Tvard[k][2]]==0){ */
3899: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3900: /* }else{ */
3901: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3902: /* } */
3903: /* } */
3904: /* } */
3905: /* /\*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*\/ */
3906: /* /\*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*\/ */
3907: /** End of old code */
3908:
1.218 brouard 3909: /* Careful transposed matrix */
1.266 brouard 3910: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3911: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3912: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3913: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.325 brouard 3914: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);/* Bug valgrind */
1.217 brouard 3915: /* if((int)age == 70){ */
3916: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3917: /* for(i=1; i<=nlstate+ndeath; i++) { */
3918: /* printf("%d pmmij ",i); */
3919: /* for(j=1;j<=nlstate+ndeath;j++) { */
3920: /* printf("%f ",pmmij[i][j]); */
3921: /* } */
3922: /* printf(" oldm "); */
3923: /* for(j=1;j<=nlstate+ndeath;j++) { */
3924: /* printf("%f ",oldm[i][j]); */
3925: /* } */
3926: /* printf("\n"); */
3927: /* } */
3928: /* } */
3929: savm=oldm;
3930: oldm=newm;
3931: }
3932: for(i=1; i<=nlstate+ndeath; i++)
3933: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3934: po[i][j][h]=newm[i][j];
1.268 brouard 3935: /* if(h==nhstepm) */
3936: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3937: }
1.268 brouard 3938: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3939: } /* end h */
1.268 brouard 3940: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3941: return po;
3942: }
3943:
3944:
1.162 brouard 3945: #ifdef NLOPT
3946: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3947: double fret;
3948: double *xt;
3949: int j;
3950: myfunc_data *d2 = (myfunc_data *) pd;
3951: /* xt = (p1-1); */
3952: xt=vector(1,n);
3953: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3954:
3955: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3956: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3957: printf("Function = %.12lf ",fret);
3958: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3959: printf("\n");
3960: free_vector(xt,1,n);
3961: return fret;
3962: }
3963: #endif
1.126 brouard 3964:
3965: /*************** log-likelihood *************/
3966: double func( double *x)
3967: {
1.336 brouard 3968: int i, ii, j, k, mi, d, kk, kf=0;
1.226 brouard 3969: int ioffset=0;
1.339 brouard 3970: int ipos=0,iposold=0,ncovv=0;
3971:
1.340 brouard 3972: double cotvarv, cotvarvold;
1.226 brouard 3973: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3974: double **out;
3975: double lli; /* Individual log likelihood */
3976: int s1, s2;
1.228 brouard 3977: 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 3978:
1.226 brouard 3979: double bbh, survp;
3980: double agexact;
1.336 brouard 3981: double agebegin, ageend;
1.226 brouard 3982: /*extern weight */
3983: /* We are differentiating ll according to initial status */
3984: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3985: /*for(i=1;i<imx;i++)
3986: printf(" %d\n",s[4][i]);
3987: */
1.162 brouard 3988:
1.226 brouard 3989: ++countcallfunc;
1.162 brouard 3990:
1.226 brouard 3991: cov[1]=1.;
1.126 brouard 3992:
1.226 brouard 3993: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3994: ioffset=0;
1.226 brouard 3995: if(mle==1){
3996: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3997: /* Computes the values of the ncovmodel covariates of the model
3998: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3999: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
4000: to be observed in j being in i according to the model.
4001: */
1.243 brouard 4002: ioffset=2+nagesqr ;
1.233 brouard 4003: /* Fixed */
1.345 brouard 4004: for (kf=1; kf<=ncovf;kf++){ /* For each fixed covariate dummy or quant or prod */
1.319 brouard 4005: /* # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi */
4006: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
4007: /* 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 4008: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.336 brouard 4009: 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 4010: /* V1*V2 (7) TvarFind[2]=7, TvarFind[3]=9 */
1.234 brouard 4011: }
1.226 brouard 4012: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
1.319 brouard 4013: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
1.226 brouard 4014: has been calculated etc */
4015: /* For an individual i, wav[i] gives the number of effective waves */
4016: /* We compute the contribution to Likelihood of each effective transition
4017: mw[mi][i] is real wave of the mi th effectve wave */
4018: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
4019: s2=s[mw[mi+1][i]][i];
1.341 brouard 4020: 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 4021: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
4022: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
4023: */
1.336 brouard 4024: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
4025: /* Wave varying (but not age varying) */
1.339 brouard 4026: /* 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*\/ */
4027: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; but where is the crossproduct? *\/ */
4028: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
4029: /* } */
1.340 brouard 4030: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age )*/
4031: itv=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
4032: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
1.345 brouard 4033: if(FixedV[itv]!=0){ /* Not a fixed covariate */
1.341 brouard 4034: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]][i]; /* cotvar[wav][ncovcol+nqv+iv][i] */
1.340 brouard 4035: }else{ /* fixed covariate */
1.345 brouard 4036: 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 4037: }
1.339 brouard 4038: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 brouard 4039: cotvarvold=cotvarv;
4040: }else{ /* A second product */
4041: cotvarv=cotvarv*cotvarvold;
1.339 brouard 4042: }
4043: iposold=ipos;
1.340 brouard 4044: cov[ioffset+ipos]=cotvarv;
1.234 brouard 4045: }
1.339 brouard 4046: /* for products of time varying to be done */
1.234 brouard 4047: for (ii=1;ii<=nlstate+ndeath;ii++)
4048: for (j=1;j<=nlstate+ndeath;j++){
4049: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4050: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4051: }
1.336 brouard 4052:
4053: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4054: 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 4055: for(d=0; d<dh[mi][i]; d++){
4056: newm=savm;
4057: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4058: cov[2]=agexact;
4059: if(nagesqr==1)
4060: cov[3]= agexact*agexact; /* Should be changed here */
1.349 ! brouard 4061: /* for (kk=1; kk<=cptcovage;kk++) { */
! 4062: /* if(!FixedV[Tvar[Tage[kk]]]) */
! 4063: /* cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /\* Tage[kk] gives the data-covariate associated with age *\/ */
! 4064: /* else */
! 4065: /* 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) *\/ */
! 4066: /* } */
! 4067: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
! 4068: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
! 4069: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
! 4070: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
! 4071: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
! 4072: }else{ /* fixed covariate */
! 4073: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
! 4074: }
! 4075: if(ipos!=iposold){ /* Not a product or first of a product */
! 4076: cotvarvold=cotvarv;
! 4077: }else{ /* A second product */
! 4078: cotvarv=cotvarv*cotvarvold;
! 4079: }
! 4080: iposold=ipos;
! 4081: cov[ioffset+ipos]=cotvarv*agexact;
! 4082: /* For products */
1.234 brouard 4083: }
1.349 ! brouard 4084:
1.234 brouard 4085: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4086: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4087: savm=oldm;
4088: oldm=newm;
4089: } /* end mult */
4090:
4091: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
4092: /* But now since version 0.9 we anticipate for bias at large stepm.
4093: * If stepm is larger than one month (smallest stepm) and if the exact delay
4094: * (in months) between two waves is not a multiple of stepm, we rounded to
4095: * the nearest (and in case of equal distance, to the lowest) interval but now
4096: * we keep into memory the bias bh[mi][i] and also the previous matrix product
4097: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
4098: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 4099: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
4100: * -stepm/2 to stepm/2 .
4101: * For stepm=1 the results are the same as for previous versions of Imach.
4102: * For stepm > 1 the results are less biased than in previous versions.
4103: */
1.234 brouard 4104: s1=s[mw[mi][i]][i];
4105: s2=s[mw[mi+1][i]][i];
4106: bbh=(double)bh[mi][i]/(double)stepm;
4107: /* bias bh is positive if real duration
4108: * is higher than the multiple of stepm and negative otherwise.
4109: */
4110: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
4111: if( s2 > nlstate){
4112: /* i.e. if s2 is a death state and if the date of death is known
4113: then the contribution to the likelihood is the probability to
4114: die between last step unit time and current step unit time,
4115: which is also equal to probability to die before dh
4116: minus probability to die before dh-stepm .
4117: In version up to 0.92 likelihood was computed
4118: as if date of death was unknown. Death was treated as any other
4119: health state: the date of the interview describes the actual state
4120: and not the date of a change in health state. The former idea was
4121: to consider that at each interview the state was recorded
4122: (healthy, disable or death) and IMaCh was corrected; but when we
4123: introduced the exact date of death then we should have modified
4124: the contribution of an exact death to the likelihood. This new
4125: contribution is smaller and very dependent of the step unit
4126: stepm. It is no more the probability to die between last interview
4127: and month of death but the probability to survive from last
4128: interview up to one month before death multiplied by the
4129: probability to die within a month. Thanks to Chris
4130: Jackson for correcting this bug. Former versions increased
4131: mortality artificially. The bad side is that we add another loop
4132: which slows down the processing. The difference can be up to 10%
4133: lower mortality.
4134: */
4135: /* If, at the beginning of the maximization mostly, the
4136: cumulative probability or probability to be dead is
4137: constant (ie = 1) over time d, the difference is equal to
4138: 0. out[s1][3] = savm[s1][3]: probability, being at state
4139: s1 at precedent wave, to be dead a month before current
4140: wave is equal to probability, being at state s1 at
4141: precedent wave, to be dead at mont of the current
4142: wave. Then the observed probability (that this person died)
4143: is null according to current estimated parameter. In fact,
4144: it should be very low but not zero otherwise the log go to
4145: infinity.
4146: */
1.183 brouard 4147: /* #ifdef INFINITYORIGINAL */
4148: /* lli=log(out[s1][s2] - savm[s1][s2]); */
4149: /* #else */
4150: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
4151: /* lli=log(mytinydouble); */
4152: /* else */
4153: /* lli=log(out[s1][s2] - savm[s1][s2]); */
4154: /* #endif */
1.226 brouard 4155: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4156:
1.226 brouard 4157: } else if ( s2==-1 ) { /* alive */
4158: for (j=1,survp=0. ; j<=nlstate; j++)
4159: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4160: /*survp += out[s1][j]; */
4161: lli= log(survp);
4162: }
1.336 brouard 4163: /* else if (s2==-4) { */
4164: /* for (j=3,survp=0. ; j<=nlstate; j++) */
4165: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
4166: /* lli= log(survp); */
4167: /* } */
4168: /* else if (s2==-5) { */
4169: /* for (j=1,survp=0. ; j<=2; j++) */
4170: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
4171: /* lli= log(survp); */
4172: /* } */
1.226 brouard 4173: else{
4174: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4175: /* 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 */
4176: }
4177: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
4178: /*if(lli ==000.0)*/
1.340 brouard 4179: /* 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 4180: ipmx +=1;
4181: sw += weight[i];
4182: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4183: /* if (lli < log(mytinydouble)){ */
4184: /* 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); */
4185: /* 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]); */
4186: /* } */
4187: } /* end of wave */
4188: } /* end of individual */
4189: } else if(mle==2){
4190: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.319 brouard 4191: ioffset=2+nagesqr ;
4192: for (k=1; k<=ncovf;k++)
4193: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];
1.226 brouard 4194: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 4195: for(k=1; k <= ncovv ; k++){
1.341 brouard 4196: 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 4197: }
1.226 brouard 4198: for (ii=1;ii<=nlstate+ndeath;ii++)
4199: for (j=1;j<=nlstate+ndeath;j++){
4200: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4201: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4202: }
4203: for(d=0; d<=dh[mi][i]; d++){
4204: newm=savm;
4205: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4206: cov[2]=agexact;
4207: if(nagesqr==1)
4208: cov[3]= agexact*agexact;
4209: for (kk=1; kk<=cptcovage;kk++) {
4210: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4211: }
4212: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4213: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4214: savm=oldm;
4215: oldm=newm;
4216: } /* end mult */
4217:
4218: s1=s[mw[mi][i]][i];
4219: s2=s[mw[mi+1][i]][i];
4220: bbh=(double)bh[mi][i]/(double)stepm;
4221: 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 */
4222: ipmx +=1;
4223: sw += weight[i];
4224: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4225: } /* end of wave */
4226: } /* end of individual */
4227: } else if(mle==3){ /* exponential inter-extrapolation */
4228: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4229: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4230: for(mi=1; mi<= wav[i]-1; mi++){
4231: for (ii=1;ii<=nlstate+ndeath;ii++)
4232: for (j=1;j<=nlstate+ndeath;j++){
4233: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4234: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4235: }
4236: for(d=0; d<dh[mi][i]; d++){
4237: newm=savm;
4238: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4239: cov[2]=agexact;
4240: if(nagesqr==1)
4241: cov[3]= agexact*agexact;
4242: for (kk=1; kk<=cptcovage;kk++) {
1.340 brouard 4243: if(!FixedV[Tvar[Tage[kk]]])
4244: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
4245: else
1.341 brouard 4246: 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 4247: }
4248: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4249: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4250: savm=oldm;
4251: oldm=newm;
4252: } /* end mult */
4253:
4254: s1=s[mw[mi][i]][i];
4255: s2=s[mw[mi+1][i]][i];
4256: bbh=(double)bh[mi][i]/(double)stepm;
4257: 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 */
4258: ipmx +=1;
4259: sw += weight[i];
4260: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4261: } /* end of wave */
4262: } /* end of individual */
4263: }else if (mle==4){ /* ml=4 no inter-extrapolation */
4264: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4265: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4266: for(mi=1; mi<= wav[i]-1; mi++){
4267: for (ii=1;ii<=nlstate+ndeath;ii++)
4268: for (j=1;j<=nlstate+ndeath;j++){
4269: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4270: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4271: }
4272: for(d=0; d<dh[mi][i]; d++){
4273: newm=savm;
4274: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4275: cov[2]=agexact;
4276: if(nagesqr==1)
4277: cov[3]= agexact*agexact;
4278: for (kk=1; kk<=cptcovage;kk++) {
4279: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4280: }
1.126 brouard 4281:
1.226 brouard 4282: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4283: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4284: savm=oldm;
4285: oldm=newm;
4286: } /* end mult */
4287:
4288: s1=s[mw[mi][i]][i];
4289: s2=s[mw[mi+1][i]][i];
4290: if( s2 > nlstate){
4291: lli=log(out[s1][s2] - savm[s1][s2]);
4292: } else if ( s2==-1 ) { /* alive */
4293: for (j=1,survp=0. ; j<=nlstate; j++)
4294: survp += out[s1][j];
4295: lli= log(survp);
4296: }else{
4297: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4298: }
4299: ipmx +=1;
4300: sw += weight[i];
4301: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.343 brouard 4302: /* 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 4303: } /* end of wave */
4304: } /* end of individual */
4305: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
4306: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4307: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4308: for(mi=1; mi<= wav[i]-1; mi++){
4309: for (ii=1;ii<=nlstate+ndeath;ii++)
4310: for (j=1;j<=nlstate+ndeath;j++){
4311: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4312: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4313: }
4314: for(d=0; d<dh[mi][i]; d++){
4315: newm=savm;
4316: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4317: cov[2]=agexact;
4318: if(nagesqr==1)
4319: cov[3]= agexact*agexact;
4320: for (kk=1; kk<=cptcovage;kk++) {
1.340 brouard 4321: if(!FixedV[Tvar[Tage[kk]]])
4322: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
4323: else
1.341 brouard 4324: 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 4325: }
1.126 brouard 4326:
1.226 brouard 4327: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4328: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4329: savm=oldm;
4330: oldm=newm;
4331: } /* end mult */
4332:
4333: s1=s[mw[mi][i]][i];
4334: s2=s[mw[mi+1][i]][i];
4335: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4336: ipmx +=1;
4337: sw += weight[i];
4338: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4339: /*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]);*/
4340: } /* end of wave */
4341: } /* end of individual */
4342: } /* End of if */
4343: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
4344: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
4345: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4346: return -l;
1.126 brouard 4347: }
4348:
4349: /*************** log-likelihood *************/
4350: double funcone( double *x)
4351: {
1.228 brouard 4352: /* Same as func but slower because of a lot of printf and if */
1.349 ! brouard 4353: int i, ii, j, k, mi, d, kk, kv=0, kf=0;
1.228 brouard 4354: int ioffset=0;
1.339 brouard 4355: int ipos=0,iposold=0,ncovv=0;
4356:
1.340 brouard 4357: double cotvarv, cotvarvold;
1.131 brouard 4358: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 4359: double **out;
4360: double lli; /* Individual log likelihood */
4361: double llt;
4362: int s1, s2;
1.228 brouard 4363: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
4364:
1.126 brouard 4365: double bbh, survp;
1.187 brouard 4366: double agexact;
1.214 brouard 4367: double agebegin, ageend;
1.126 brouard 4368: /*extern weight */
4369: /* We are differentiating ll according to initial status */
4370: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
4371: /*for(i=1;i<imx;i++)
4372: printf(" %d\n",s[4][i]);
4373: */
4374: cov[1]=1.;
4375:
4376: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 4377: ioffset=0;
4378: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.336 brouard 4379: /* Computes the values of the ncovmodel covariates of the model
4380: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
4381: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
4382: to be observed in j being in i according to the model.
4383: */
1.243 brouard 4384: /* ioffset=2+nagesqr+cptcovage; */
4385: ioffset=2+nagesqr;
1.232 brouard 4386: /* Fixed */
1.224 brouard 4387: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 4388: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
1.349 ! brouard 4389: for (kf=1; kf<=ncovf;kf++){ /* V2 + V3 + V4 Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */
1.339 brouard 4390: /* printf("Debug3 TvarFind[%d]=%d",kf, TvarFind[kf]); */
4391: /* printf(" Tvar[TvarFind[kf]]=%d", Tvar[TvarFind[kf]]); */
4392: /* printf(" i=%d covar[Tvar[TvarFind[kf]]][i]=%f\n",i,covar[Tvar[TvarFind[kf]]][i]); */
1.335 brouard 4393: 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 4394: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
4395: /* cov[2+6]=covar[Tvar[6]][i]; */
4396: /* cov[2+6]=covar[2][i]; V2 */
4397: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
4398: /* cov[2+7]=covar[Tvar[7]][i]; */
4399: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
4400: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
4401: /* cov[2+9]=covar[Tvar[9]][i]; */
4402: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 4403: }
1.336 brouard 4404: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
4405: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
4406: has been calculated etc */
4407: /* For an individual i, wav[i] gives the number of effective waves */
4408: /* We compute the contribution to Likelihood of each effective transition
4409: mw[mi][i] is real wave of the mi th effectve wave */
4410: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
4411: s2=s[mw[mi+1][i]][i];
1.341 brouard 4412: And the iv th varying covariate in the DATA is the cotvar[mw[mi+1][i]][ncovcol+nqv+iv][i]
1.336 brouard 4413: */
4414: /* This part may be useless now because everythin should be in covar */
1.232 brouard 4415: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
4416: /* 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?)*\/ */
4417: /* } */
1.231 brouard 4418: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
4419: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
4420: /* } */
1.225 brouard 4421:
1.233 brouard 4422:
4423: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.339 brouard 4424: /* 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 */
4425: /* for(k=1; k <= ncovv ; k++){ /\* Varying covariates (single and product but no age )*\/ */
4426: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; *\/ */
4427: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
4428: /* } */
4429:
4430: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
4431: /* model V1+V3+age*V1+age*V3+V1*V3 */
4432: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
4433: /* TvarVV[1]=V3 (first time varying in the model equation, TvarVV[2]=V1 (in V1*V3) TvarVV[3]=3(V3) */
4434: /* We need the position of the time varying or product in the model */
4435: /* 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 */
4436: /* TvarVV gives the variable name */
1.340 brouard 4437: /* Other example V1 + V3 + V5 + age*V1 + age*V3 + age*V5 + V1*V3 + V3*V5 + V1*V5
4438: * k= 1 2 3 4 5 6 7 8 9
4439: * varying 1 2 3 4 5
4440: * ncovv 1 2 3 4 5 6 7 8
1.343 brouard 4441: * TvarVV[ncovv] V3 5 1 3 3 5 1 5
1.340 brouard 4442: * TvarVVind 2 3 7 7 8 8 9 9
4443: * TvarFind[k] 1 0 0 0 0 0 0 0 0
4444: */
1.345 brouard 4445: /* Other model ncovcol=5 nqv=0 ntv=3 nqtv=0 nlstate=3
1.349 ! brouard 4446: * V2 V3 V4 are fixed V6 V7 are timevarying so V8 and V5 are not in the model and product column will start at 9 Tvar[(v6*V2)6]=9
1.345 brouard 4447: * FixedV[ncovcol+qv+ntv+nqtv] V5
1.349 ! brouard 4448: * 3 V1 V2 V3 V4 V5 V6 V7 V8 V3*V2 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
! 4449: * 0 0 0 0 0 1 1 1 0, 0, 1,1, 1, 0, 1, 0, 1, 0, 1, 0}
! 4450: * 3 0 0 0 0 0 1 1 1 0, 1 1 1 1 1}
! 4451: * model= V2 + V3 + V4 + V6 + V7 + V6*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
! 4452: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
! 4453: * +age*V6*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
! 4454: * model2= V2 + V3 + V4 + V6 + V7 + V3*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
! 4455: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
! 4456: * +age*V3*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
! 4457: * model3= V2 + V3 + V4 + V6 + V7 + age*V3*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
! 4458: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
! 4459: * +V3*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
! 4460: * kmodel 1 2 3 4 5 6 7 8 9 10 11
! 4461: * 12 13 14 15 16
! 4462: * 17 18 19 20 21
! 4463: * Tvar[kmodel] 2 3 4 6 7 9 10 11 12 13 14
! 4464: * 2 3 4 6 7
! 4465: * 9 11 12 13 14
! 4466: * cptcovage=5+5 total of covariates with age
! 4467: * Tage[cptcovage] age*V2=12 13 14 15 16
! 4468: *1 17 18 19 20 21 gives the position in model of covariates associated with age
! 4469: *3 Tage[cptcovage] age*V3*V2=6
! 4470: *3 age*V2=12 13 14 15 16
! 4471: *3 age*V6*V3=18 19 20 21
! 4472: * Tvar[Tage[cptcovage]] Tvar[12]=2 3 4 6 Tvar[16]=7(age*V7)
! 4473: * Tvar[17]age*V6*V2=9 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14
! 4474: * 2 Tvar[17]age*V3*V2=9 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14
! 4475: * 3 Tvar[Tage[cptcovage]] Tvar[6]=9 Tvar[12]=2 3 4 6 Tvar[16]=7(age*V7)
! 4476: * 3 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14
! 4477: * 3 Tage[cptcovage] age*V3*V2=6 age*V2=12 age*V3 13 14 15 16
! 4478: * age*V6*V3=18 19 20 21 gives the position in model of covariates associated with age
! 4479: * 3 Tvar[17]age*V3*V2=9 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14
! 4480: * Tvar= {2, 3, 4, 6, 7,
! 4481: * 9, 10, 11, 12, 13, 14,
! 4482: * Tvar[12]=2, 3, 4, 6, 7,
! 4483: * Tvar[17]=9, 11, 12, 13, 14}
! 4484: * Typevar[1]@21 = {0, 0, 0, 0, 0,
! 4485: * 2, 2, 2, 2, 2, 2,
! 4486: * 3 3, 2, 2, 2, 2, 2,
! 4487: * 1, 1, 1, 1, 1,
! 4488: * 3, 3, 3, 3, 3}
! 4489: * 3 2, 3, 3, 3, 3}
! 4490: * p Tposprod[1]@21 {0, 0, 0, 0, 0, 1, 2, 3, 4, 5, 6, 0, 0, 0, 0, 0, 1, 3, 4, 5, 6} Id of the prod at position k in the model
! 4491: * p Tprod[1]@21 {6, 7, 8, 9, 10, 11, 0 <repeats 15 times>}
! 4492: * 3 Tposprod[1]@21 {0, 0, 0, 0, 0, 1, 2, 3, 4, 5, 6, 0, 0, 0, 0, 0, 1, 3, 4, 5, 6}
! 4493: * 3 Tprod[1]@21 {17, 7, 8, 9, 10, 11, 0 <repeats 15 times>}
! 4494: * cptcovprod=11 (6+5)
! 4495: * FixedV[Tvar[Tage[cptcovage]]]] FixedV[2]=0 FixedV[3]=0 0 1 (age*V7)Tvar[16]=1 FixedV[absolute] not [kmodel]
! 4496: * FixedV[Tvar[17]=FixedV[age*V6*V2]=FixedV[9]=1 1 1 1 1
! 4497: * 3 FixedV[Tvar[17]=FixedV[age*V3*V2]=FixedV[9]=0 [11]=1 1 1 1
! 4498: * FixedV[] V1=0 V2=0 V3=0 v4=0 V5=0 V6=1 V7=1 v8=1 OK then model dependent
! 4499: * 9=1 [V7*V2]=[10]=1 11=1 12=1 13=1 14=1
! 4500: * 3 9=0 [V7*V2]=[10]=1 11=1 12=1 13=1 14=1
! 4501: * cptcovdageprod=5 for gnuplot printing
! 4502: * cptcovprodvage=6
! 4503: * ncova=15 1 2 3 4 5
! 4504: * 6 7 8 9 10 11 12 13 14 15
! 4505: * TvarA 2 3 4 6 7
! 4506: * 6 2 6 7 7 3 6 4 7 4
! 4507: * TvaAind 12 12 13 13 14 14 15 15 16 16
1.345 brouard 4508: * ncovf 1 2 3
1.349 ! brouard 4509: * V6 V7 V6*V2 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
! 4510: * ncovvt=14 1 2 3 4 5 6 7 8 9 10 11 12 13 14
! 4511: * TvarVV[1]@14 = itv {V6=6, 7, V6*V2=6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
! 4512: * TvarVVind[1]@14= {4, 5, 6, 6, 7, 7, 8, 8, 9, 9, 10, 10, 11, 11}
! 4513: * 3 ncovvt=12 V6 V7 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
! 4514: * 3 TvarVV[1]@12 = itv {6, 7, V7*V2=7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
! 4515: * 3 1 2 3 4 5 6 7 8 9 10 11 12
! 4516: * TvarVVind[1]@12= {V6 is in k=4, 5, 7,(4isV2)=7, 8, 8, 9, 9, 10,10, 11,11}TvarVVind[12]=k=11
! 4517: * TvarV 6, 7, 9, 10, 11, 12, 13, 14
! 4518: * 3 cptcovprodvage=6
! 4519: * 3 ncovta=15 +age*V3*V2+age*V2+agev3+ageV4 +age*V6 + age*V7 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
! 4520: * 3 TvarAVVA[1]@15= itva 3 2 2 3 4 6 7 6 3 7 3 6 4 7 4
! 4521: * 3 ncovta 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
! 4522: * TvarAVVAind[1]@15= V3 is in k=2 1 1 2 3 4 5 4,2 5,2, 4,3 5 3}TvarVVAind[]
! 4523: * TvarAVVAind[1]@15= V3 is in k=6 6 12 13 14 15 16 18 18 19,19, 20,20 21,21}TvarVVAind[]
! 4524: * 3 ncovvta=10 +age*V6 + age*V7 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
! 4525: * 3 we want to compute =cotvar[mw[mi][i]][TvarVVA[ncovva]][i] at position TvarVVAind[ncovva]
! 4526: * 3 TvarVVA[1]@10= itva 6 7 6 3 7 3 6 4 7 4
! 4527: * 3 ncovva 1 2 3 4 5 6 7 8 9 10
! 4528: * TvarVVAind[1]@10= V6 is in k=4 5 8,8 9, 9, 10,10 11 11}TvarVVAind[]
! 4529: * TvarVVAind[1]@10= 15 16 18,18 19,19, 20,20 21 21}TvarVVAind[]
! 4530: * TvarVA V3*V2=6 6 , 1, 2, 11, 12, 13, 14
1.345 brouard 4531: * TvarFind[1]@14= {1, 2, 3, 0 <repeats 12 times>}
1.349 ! brouard 4532: * Tvar[1]@21= {2, 3, 4, 6, 7, 9, 10, 11, 12, 13, 14,
! 4533: * 2, 3, 4, 6, 7,
! 4534: * 6, 8, 9, 10, 11}
1.345 brouard 4535: * TvarFind[itv] 0 0 0
4536: * FixedV[itv] 1 1 1 0 1 0 1 0 1 0 0
4537: * Tvar[TvarFind[ncovf]]=[1]=2 [2]=3 [4]=4
4538: * Tvar[TvarFind[itv]] [0]=? ?ncovv 1 à ncovvt]
4539: * Not a fixed cotvar[mw][itv][i] 6 7 6 2 7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
1.349 ! brouard 4540: * fixed covar[itv] [6] [7] [6][2]
1.345 brouard 4541: */
4542:
1.349 ! brouard 4543: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* V6 V7 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4 Time varying covariates (single and extended product but no age) including individual from products, product is computed dynamically */
! 4544: itv=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, or fixed covariate of a varying product after exploding product Vn*Vm into Vn and then Vm */
1.340 brouard 4545: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
1.345 brouard 4546: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
4547: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
4548: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
1.340 brouard 4549: }else{ /* fixed covariate */
1.345 brouard 4550: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
1.349 ! brouard 4551: cotvarv=covar[itv][i]; /* Good: In V6*V3, 3 is fixed at position of the data */
1.340 brouard 4552: }
1.339 brouard 4553: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 brouard 4554: cotvarvold=cotvarv;
4555: }else{ /* A second product */
4556: cotvarv=cotvarv*cotvarvold;
1.339 brouard 4557: }
4558: iposold=ipos;
1.340 brouard 4559: cov[ioffset+ipos]=cotvarv;
1.339 brouard 4560: /* For products */
4561: }
4562: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates single *\/ */
4563: /* iv=TvarVDind[itv]; /\* iv, position in the model equation of time varying covariate itv *\/ */
4564: /* /\* "V1+V3+age*V1+age*V3+V1*V3" with V3 time varying *\/ */
4565: /* /\* 1 2 3 4 5 *\/ */
4566: /* /\*itv 1 *\/ */
4567: /* /\* TvarVInd[1]= 2 *\/ */
4568: /* /\* iv= Tvar[Tmodelind[itv]]-ncovcol-nqv; /\\* Counting the # varying covariate from 1 to ntveff *\\/ *\/ */
4569: /* /\* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; *\/ */
4570: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; *\/ */
4571: /* /\* k=ioffset-2-nagesqr-cptcovage+itv; /\\* position in simple model *\\/ *\/ */
4572: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; *\/ */
4573: /* cov[ioffset+iv]=cotvar[mw[mi][i]][itv][i]; */
4574: /* /\* 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]); *\/ */
4575: /* } */
1.232 brouard 4576: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 4577: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4578: /* /\* 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]); *\/ */
4579: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 4580: /* } */
1.126 brouard 4581: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 4582: for (j=1;j<=nlstate+ndeath;j++){
4583: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4584: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4585: }
1.214 brouard 4586:
4587: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4588: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
4589: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 4590: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 4591: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
4592: and mw[mi+1][i]. dh depends on stepm.*/
4593: newm=savm;
1.247 brouard 4594: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 4595: cov[2]=agexact;
4596: if(nagesqr==1)
4597: cov[3]= agexact*agexact;
1.349 ! brouard 4598: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
! 4599: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
! 4600: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
! 4601: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
! 4602: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
! 4603: /* printf("DEBUG ncovva=%d, Varying TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
! 4604: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
! 4605: }else{ /* fixed covariate */
! 4606: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
! 4607: /* printf("DEBUG ncovva=%d, Fixed TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
! 4608: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
! 4609: }
! 4610: if(ipos!=iposold){ /* Not a product or first of a product */
! 4611: cotvarvold=cotvarv;
! 4612: }else{ /* A second product */
! 4613: /* printf("DEBUG * \n"); */
! 4614: cotvarv=cotvarv*cotvarvold;
! 4615: }
! 4616: iposold=ipos;
! 4617: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
! 4618: cov[ioffset+ipos]=cotvarv*agexact;
! 4619: /* For products */
1.242 brouard 4620: }
1.349 ! brouard 4621:
1.242 brouard 4622: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
4623: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
4624: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4625: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4626: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
4627: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
4628: savm=oldm;
4629: oldm=newm;
1.126 brouard 4630: } /* end mult */
1.336 brouard 4631: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
4632: /* But now since version 0.9 we anticipate for bias at large stepm.
4633: * If stepm is larger than one month (smallest stepm) and if the exact delay
4634: * (in months) between two waves is not a multiple of stepm, we rounded to
4635: * the nearest (and in case of equal distance, to the lowest) interval but now
4636: * we keep into memory the bias bh[mi][i] and also the previous matrix product
4637: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
4638: * probability in order to take into account the bias as a fraction of the way
4639: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
4640: * -stepm/2 to stepm/2 .
4641: * For stepm=1 the results are the same as for previous versions of Imach.
4642: * For stepm > 1 the results are less biased than in previous versions.
4643: */
1.126 brouard 4644: s1=s[mw[mi][i]][i];
4645: s2=s[mw[mi+1][i]][i];
1.217 brouard 4646: /* if(s2==-1){ */
1.268 brouard 4647: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 4648: /* /\* exit(1); *\/ */
4649: /* } */
1.126 brouard 4650: bbh=(double)bh[mi][i]/(double)stepm;
4651: /* bias is positive if real duration
4652: * is higher than the multiple of stepm and negative otherwise.
4653: */
4654: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 4655: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4656: } else if ( s2==-1 ) { /* alive */
1.242 brouard 4657: for (j=1,survp=0. ; j<=nlstate; j++)
4658: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4659: lli= log(survp);
1.126 brouard 4660: }else if (mle==1){
1.242 brouard 4661: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 4662: } else if(mle==2){
1.242 brouard 4663: 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 4664: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 4665: 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 4666: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 4667: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 4668: } else{ /* mle=0 back to 1 */
1.242 brouard 4669: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4670: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 4671: } /* End of if */
4672: ipmx +=1;
4673: sw += weight[i];
4674: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.342 brouard 4675: /* Printing covariates values for each contribution for checking */
1.343 brouard 4676: /* 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 4677: if(globpr){
1.246 brouard 4678: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 4679: %11.6f %11.6f %11.6f ", \
1.242 brouard 4680: 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 4681: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.343 brouard 4682: /* printf("%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\ */
4683: /* %11.6f %11.6f %11.6f ", \ */
4684: /* num[i], agebegin, ageend, i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],weight[i]*gipmx/gsw, */
4685: /* 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2])); */
1.242 brouard 4686: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
4687: llt +=ll[k]*gipmx/gsw;
4688: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
1.335 brouard 4689: /* printf(" %10.6f",-ll[k]*gipmx/gsw); */
1.242 brouard 4690: }
1.343 brouard 4691: fprintf(ficresilk," %10.6f ", -llt);
1.335 brouard 4692: /* printf(" %10.6f\n", -llt); */
1.342 brouard 4693: /* if(debugILK){ /\* debugILK is set by a #d in a comment line *\/ */
1.343 brouard 4694: /* fprintf(ficresilk,"%09ld ", num[i]); */ /* not necessary */
4695: for (kf=1; kf<=ncovf;kf++){ /* Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */
4696: fprintf(ficresilk," %g",covar[Tvar[TvarFind[kf]]][i]);
4697: }
4698: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age) including individual from products */
4699: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4700: if(ipos!=iposold){ /* Not a product or first of a product */
4701: fprintf(ficresilk," %g",cov[ioffset+ipos]);
4702: /* printf(" %g",cov[ioffset+ipos]); */
4703: }else{
4704: fprintf(ficresilk,"*");
4705: /* printf("*"); */
1.342 brouard 4706: }
1.343 brouard 4707: iposold=ipos;
4708: }
1.349 ! brouard 4709: /* for (kk=1; kk<=cptcovage;kk++) { */
! 4710: /* if(!FixedV[Tvar[Tage[kk]]]){ */
! 4711: /* fprintf(ficresilk," %g*age",covar[Tvar[Tage[kk]]][i]); */
! 4712: /* /\* printf(" %g*age",covar[Tvar[Tage[kk]]][i]); *\/ */
! 4713: /* }else{ */
! 4714: /* fprintf(ficresilk," %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */
! 4715: /* /\* printf(" %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/\\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\\/ *\/ */
! 4716: /* } */
! 4717: /* } */
! 4718: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
! 4719: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
! 4720: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
! 4721: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
! 4722: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
! 4723: /* printf("DEBUG ncovva=%d, Varying TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
! 4724: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
! 4725: }else{ /* fixed covariate */
! 4726: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
! 4727: /* printf("DEBUG ncovva=%d, Fixed TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
! 4728: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
! 4729: }
! 4730: if(ipos!=iposold){ /* Not a product or first of a product */
! 4731: cotvarvold=cotvarv;
! 4732: }else{ /* A second product */
! 4733: /* printf("DEBUG * \n"); */
! 4734: cotvarv=cotvarv*cotvarvold;
1.342 brouard 4735: }
1.349 ! brouard 4736: cotvarv=cotvarv*agexact;
! 4737: fprintf(ficresilk," %g*age",cotvarv);
! 4738: iposold=ipos;
! 4739: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
! 4740: cov[ioffset+ipos]=cotvarv;
! 4741: /* For products */
1.343 brouard 4742: }
4743: /* printf("\n"); */
1.342 brouard 4744: /* } /\* End debugILK *\/ */
4745: fprintf(ficresilk,"\n");
4746: } /* End if globpr */
1.335 brouard 4747: } /* end of wave */
4748: } /* end of individual */
4749: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
1.232 brouard 4750: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
1.335 brouard 4751: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4752: if(globpr==0){ /* First time we count the contributions and weights */
4753: gipmx=ipmx;
4754: gsw=sw;
4755: }
1.343 brouard 4756: return -l;
1.126 brouard 4757: }
4758:
4759:
4760: /*************** function likelione ***********/
1.292 brouard 4761: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 4762: {
4763: /* This routine should help understanding what is done with
4764: the selection of individuals/waves and
4765: to check the exact contribution to the likelihood.
4766: Plotting could be done.
1.342 brouard 4767: */
4768: void pstamp(FILE *ficres);
1.343 brouard 4769: int k, kf, kk, kvar, ncovv, iposold, ipos;
1.126 brouard 4770:
4771: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 4772: strcpy(fileresilk,"ILK_");
1.202 brouard 4773: strcat(fileresilk,fileresu);
1.126 brouard 4774: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
4775: printf("Problem with resultfile: %s\n", fileresilk);
4776: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
4777: }
1.342 brouard 4778: pstamp(ficresilk);fprintf(ficresilk,"# model=1+age+%s\n",model);
1.214 brouard 4779: 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");
4780: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 4781: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
4782: for(k=1; k<=nlstate; k++)
4783: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
1.342 brouard 4784: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total) ");
4785:
4786: /* if(debugILK){ /\* debugILK is set by a #d in a comment line *\/ */
4787: for(kf=1;kf <= ncovf; kf++){
4788: fprintf(ficresilk,"V%d",Tvar[TvarFind[kf]]);
4789: /* printf("V%d",Tvar[TvarFind[kf]]); */
4790: }
4791: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){
1.343 brouard 4792: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
1.342 brouard 4793: if(ipos!=iposold){ /* Not a product or first of a product */
4794: /* printf(" %d",ipos); */
4795: fprintf(ficresilk," V%d",TvarVV[ncovv]);
4796: }else{
4797: /* printf("*"); */
4798: fprintf(ficresilk,"*");
1.343 brouard 4799: }
1.342 brouard 4800: iposold=ipos;
4801: }
4802: for (kk=1; kk<=cptcovage;kk++) {
4803: if(!FixedV[Tvar[Tage[kk]]]){
4804: /* printf(" %d*age(Fixed)",Tvar[Tage[kk]]); */
4805: fprintf(ficresilk," %d*age(Fixed)",Tvar[Tage[kk]]);
4806: }else{
4807: fprintf(ficresilk," %d*age(Varying)",Tvar[Tage[kk]]);/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
4808: /* printf(" %d*age(Varying)",Tvar[Tage[kk]]);/\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */
4809: }
4810: }
4811: /* } /\* End if debugILK *\/ */
4812: /* printf("\n"); */
4813: fprintf(ficresilk,"\n");
4814: } /* End glogpri */
1.126 brouard 4815:
1.292 brouard 4816: *fretone=(*func)(p);
1.126 brouard 4817: if(*globpri !=0){
4818: fclose(ficresilk);
1.205 brouard 4819: if (mle ==0)
4820: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
4821: else if(mle >=1)
4822: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
4823: 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 4824: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 4825:
1.207 brouard 4826: 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 4827: <img src=\"%s-ori.png\">\n",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4828: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.343 brouard 4829: <img src=\"%s-dest.png\">\n",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
4830:
4831: for (k=1; k<= nlstate ; k++) {
4832: 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 \
4833: <img src=\"%s-p%dj.png\">\n",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
4834: for(kf=1; kf <= ncovf; kf++){ /* For each simple dummy covariate of the model */
4835: /* kvar=Tvar[TvarFind[kf]]; */ /* variable */
4836: 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> \
4837: <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]]);
4838: }
4839: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Loop on the time varying extended covariates (with extension of Vn*Vm */
4840: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
4841: kvar=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
4842: /* 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]); */
4843: if(ipos!=iposold){ /* Not a product or first of a product */
4844: /* fprintf(ficresilk," V%d",TvarVV[ncovv]); */
4845: /* printf(" DebugILK fichtm ipos=%d != iposold=%d\n", ipos, iposold); */
4846: 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) */
4847: 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> \
4848: <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);
4849: } /* End only for dummies time varying (single?) */
4850: }else{ /* Useless product */
4851: /* printf("*"); */
4852: /* fprintf(ficresilk,"*"); */
4853: }
4854: iposold=ipos;
4855: } /* For each time varying covariate */
4856: } /* End loop on states */
4857:
4858: /* if(debugILK){ */
4859: /* for(kf=1; kf <= ncovf; kf++){ /\* For each simple dummy covariate of the model *\/ */
4860: /* /\* kvar=Tvar[TvarFind[kf]]; *\/ /\* variable *\/ */
4861: /* for (k=1; k<= nlstate ; k++) { */
4862: /* 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> \ */
4863: /* <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]]); */
4864: /* } */
4865: /* } */
4866: /* for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /\* Loop on the time varying extended covariates (with extension of Vn*Vm *\/ */
4867: /* ipos=TvarVVind[ncovv]; /\* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate *\/ */
4868: /* kvar=TvarVV[ncovv]; /\* TvarVV={3, 1, 3} gives the name of each varying covariate *\/ */
4869: /* /\* 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]); *\/ */
4870: /* if(ipos!=iposold){ /\* Not a product or first of a product *\/ */
4871: /* /\* fprintf(ficresilk," V%d",TvarVV[ncovv]); *\/ */
4872: /* /\* printf(" DebugILK fichtm ipos=%d != iposold=%d\n", ipos, iposold); *\/ */
4873: /* 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) *\/ */
4874: /* for (k=1; k<= nlstate ; k++) { */
4875: /* 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> \ */
4876: /* <img src=\"%s-p%dj-%d.png\">",k,k,kvar,kvar,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,kvar); */
4877: /* } /\* End state *\/ */
4878: /* } /\* End only for dummies time varying (single?) *\/ */
4879: /* }else{ /\* Useless product *\/ */
4880: /* /\* printf("*"); *\/ */
4881: /* /\* fprintf(ficresilk,"*"); *\/ */
4882: /* } */
4883: /* iposold=ipos; */
4884: /* } /\* For each time varying covariate *\/ */
4885: /* }/\* End debugILK *\/ */
1.207 brouard 4886: fflush(fichtm);
1.343 brouard 4887: }/* End globpri */
1.126 brouard 4888: return;
4889: }
4890:
4891:
4892: /*********** Maximum Likelihood Estimation ***************/
4893:
4894: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
4895: {
1.319 brouard 4896: int i,j,k, jk, jkk=0, iter=0;
1.126 brouard 4897: double **xi;
4898: double fret;
4899: double fretone; /* Only one call to likelihood */
4900: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 4901:
4902: #ifdef NLOPT
4903: int creturn;
4904: nlopt_opt opt;
4905: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
4906: double *lb;
4907: double minf; /* the minimum objective value, upon return */
4908: double * p1; /* Shifted parameters from 0 instead of 1 */
4909: myfunc_data dinst, *d = &dinst;
4910: #endif
4911:
4912:
1.126 brouard 4913: xi=matrix(1,npar,1,npar);
4914: for (i=1;i<=npar;i++)
4915: for (j=1;j<=npar;j++)
4916: xi[i][j]=(i==j ? 1.0 : 0.0);
4917: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 4918: strcpy(filerespow,"POW_");
1.126 brouard 4919: strcat(filerespow,fileres);
4920: if((ficrespow=fopen(filerespow,"w"))==NULL) {
4921: printf("Problem with resultfile: %s\n", filerespow);
4922: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
4923: }
4924: fprintf(ficrespow,"# Powell\n# iter -2*LL");
4925: for (i=1;i<=nlstate;i++)
4926: for(j=1;j<=nlstate+ndeath;j++)
4927: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
4928: fprintf(ficrespow,"\n");
1.162 brouard 4929: #ifdef POWELL
1.319 brouard 4930: #ifdef LINMINORIGINAL
4931: #else /* LINMINORIGINAL */
4932:
4933: flatdir=ivector(1,npar);
4934: for (j=1;j<=npar;j++) flatdir[j]=0;
4935: #endif /*LINMINORIGINAL */
4936:
4937: #ifdef FLATSUP
4938: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4939: /* reorganizing p by suppressing flat directions */
4940: for(i=1, jk=1; i <=nlstate; i++){
4941: for(k=1; k <=(nlstate+ndeath); k++){
4942: if (k != i) {
4943: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4944: if(flatdir[jk]==1){
4945: printf(" To be skipped %d%d flatdir[%d]=%d ",i,k,jk, flatdir[jk]);
4946: }
4947: for(j=1; j <=ncovmodel; j++){
4948: printf("%12.7f ",p[jk]);
4949: jk++;
4950: }
4951: printf("\n");
4952: }
4953: }
4954: }
4955: /* skipping */
4956: /* for(i=1, jk=1, jkk=1;(flatdir[jk]==0)&& (i <=nlstate); i++){ */
4957: for(i=1, jk=1, jkk=1;i <=nlstate; i++){
4958: for(k=1; k <=(nlstate+ndeath); k++){
4959: if (k != i) {
4960: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4961: if(flatdir[jk]==1){
4962: printf(" To be skipped %d%d flatdir[%d]=%d jk=%d p[%d] ",i,k,jk, flatdir[jk],jk, jk);
4963: for(j=1; j <=ncovmodel; jk++,j++){
4964: printf(" p[%d]=%12.7f",jk, p[jk]);
4965: /*q[jjk]=p[jk];*/
4966: }
4967: }else{
4968: printf(" To be kept %d%d flatdir[%d]=%d jk=%d q[%d]=p[%d] ",i,k,jk, flatdir[jk],jk, jkk, jk);
4969: for(j=1; j <=ncovmodel; jk++,jkk++,j++){
4970: printf(" p[%d]=%12.7f=q[%d]",jk, p[jk],jkk);
4971: /*q[jjk]=p[jk];*/
4972: }
4973: }
4974: printf("\n");
4975: }
4976: fflush(stdout);
4977: }
4978: }
4979: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4980: #else /* FLATSUP */
1.126 brouard 4981: powell(p,xi,npar,ftol,&iter,&fret,func);
1.319 brouard 4982: #endif /* FLATSUP */
4983:
4984: #ifdef LINMINORIGINAL
4985: #else
4986: free_ivector(flatdir,1,npar);
4987: #endif /* LINMINORIGINAL*/
4988: #endif /* POWELL */
1.126 brouard 4989:
1.162 brouard 4990: #ifdef NLOPT
4991: #ifdef NEWUOA
4992: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
4993: #else
4994: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
4995: #endif
4996: lb=vector(0,npar-1);
4997: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
4998: nlopt_set_lower_bounds(opt, lb);
4999: nlopt_set_initial_step1(opt, 0.1);
5000:
5001: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
5002: d->function = func;
5003: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
5004: nlopt_set_min_objective(opt, myfunc, d);
5005: nlopt_set_xtol_rel(opt, ftol);
5006: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
5007: printf("nlopt failed! %d\n",creturn);
5008: }
5009: else {
5010: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
5011: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
5012: iter=1; /* not equal */
5013: }
5014: nlopt_destroy(opt);
5015: #endif
1.319 brouard 5016: #ifdef FLATSUP
5017: /* npared = npar -flatd/ncovmodel; */
5018: /* xired= matrix(1,npared,1,npared); */
5019: /* paramred= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); */
5020: /* powell(pred,xired,npared,ftol,&iter,&fret,flatdir,func); */
5021: /* free_matrix(xire,1,npared,1,npared); */
5022: #else /* FLATSUP */
5023: #endif /* FLATSUP */
1.126 brouard 5024: free_matrix(xi,1,npar,1,npar);
5025: fclose(ficrespow);
1.203 brouard 5026: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
5027: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 5028: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 5029:
5030: }
5031:
5032: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 5033: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 5034: {
5035: double **a,**y,*x,pd;
1.203 brouard 5036: /* double **hess; */
1.164 brouard 5037: int i, j;
1.126 brouard 5038: int *indx;
5039:
5040: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 5041: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 5042: void lubksb(double **a, int npar, int *indx, double b[]) ;
5043: void ludcmp(double **a, int npar, int *indx, double *d) ;
5044: double gompertz(double p[]);
1.203 brouard 5045: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 5046:
5047: printf("\nCalculation of the hessian matrix. Wait...\n");
5048: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
5049: for (i=1;i<=npar;i++){
1.203 brouard 5050: printf("%d-",i);fflush(stdout);
5051: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 5052:
5053: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
5054:
5055: /* printf(" %f ",p[i]);
5056: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
5057: }
5058:
5059: for (i=1;i<=npar;i++) {
5060: for (j=1;j<=npar;j++) {
5061: if (j>i) {
1.203 brouard 5062: printf(".%d-%d",i,j);fflush(stdout);
5063: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
5064: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 5065:
5066: hess[j][i]=hess[i][j];
5067: /*printf(" %lf ",hess[i][j]);*/
5068: }
5069: }
5070: }
5071: printf("\n");
5072: fprintf(ficlog,"\n");
5073:
5074: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
5075: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
5076:
5077: a=matrix(1,npar,1,npar);
5078: y=matrix(1,npar,1,npar);
5079: x=vector(1,npar);
5080: indx=ivector(1,npar);
5081: for (i=1;i<=npar;i++)
5082: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
5083: ludcmp(a,npar,indx,&pd);
5084:
5085: for (j=1;j<=npar;j++) {
5086: for (i=1;i<=npar;i++) x[i]=0;
5087: x[j]=1;
5088: lubksb(a,npar,indx,x);
5089: for (i=1;i<=npar;i++){
5090: matcov[i][j]=x[i];
5091: }
5092: }
5093:
5094: printf("\n#Hessian matrix#\n");
5095: fprintf(ficlog,"\n#Hessian matrix#\n");
5096: for (i=1;i<=npar;i++) {
5097: for (j=1;j<=npar;j++) {
1.203 brouard 5098: printf("%.6e ",hess[i][j]);
5099: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 5100: }
5101: printf("\n");
5102: fprintf(ficlog,"\n");
5103: }
5104:
1.203 brouard 5105: /* printf("\n#Covariance matrix#\n"); */
5106: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
5107: /* for (i=1;i<=npar;i++) { */
5108: /* for (j=1;j<=npar;j++) { */
5109: /* printf("%.6e ",matcov[i][j]); */
5110: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
5111: /* } */
5112: /* printf("\n"); */
5113: /* fprintf(ficlog,"\n"); */
5114: /* } */
5115:
1.126 brouard 5116: /* Recompute Inverse */
1.203 brouard 5117: /* for (i=1;i<=npar;i++) */
5118: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
5119: /* ludcmp(a,npar,indx,&pd); */
5120:
5121: /* printf("\n#Hessian matrix recomputed#\n"); */
5122:
5123: /* for (j=1;j<=npar;j++) { */
5124: /* for (i=1;i<=npar;i++) x[i]=0; */
5125: /* x[j]=1; */
5126: /* lubksb(a,npar,indx,x); */
5127: /* for (i=1;i<=npar;i++){ */
5128: /* y[i][j]=x[i]; */
5129: /* printf("%.3e ",y[i][j]); */
5130: /* fprintf(ficlog,"%.3e ",y[i][j]); */
5131: /* } */
5132: /* printf("\n"); */
5133: /* fprintf(ficlog,"\n"); */
5134: /* } */
5135:
5136: /* Verifying the inverse matrix */
5137: #ifdef DEBUGHESS
5138: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 5139:
1.203 brouard 5140: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
5141: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 5142:
5143: for (j=1;j<=npar;j++) {
5144: for (i=1;i<=npar;i++){
1.203 brouard 5145: printf("%.2f ",y[i][j]);
5146: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 5147: }
5148: printf("\n");
5149: fprintf(ficlog,"\n");
5150: }
1.203 brouard 5151: #endif
1.126 brouard 5152:
5153: free_matrix(a,1,npar,1,npar);
5154: free_matrix(y,1,npar,1,npar);
5155: free_vector(x,1,npar);
5156: free_ivector(indx,1,npar);
1.203 brouard 5157: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 5158:
5159:
5160: }
5161:
5162: /*************** hessian matrix ****************/
5163: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 5164: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 5165: int i;
5166: int l=1, lmax=20;
1.203 brouard 5167: double k1,k2, res, fx;
1.132 brouard 5168: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 5169: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
5170: int k=0,kmax=10;
5171: double l1;
5172:
5173: fx=func(x);
5174: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 5175: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 5176: l1=pow(10,l);
5177: delts=delt;
5178: for(k=1 ; k <kmax; k=k+1){
5179: delt = delta*(l1*k);
5180: p2[theta]=x[theta] +delt;
1.145 brouard 5181: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 5182: p2[theta]=x[theta]-delt;
5183: k2=func(p2)-fx;
5184: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 5185: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 5186:
1.203 brouard 5187: #ifdef DEBUGHESSII
1.126 brouard 5188: 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);
5189: 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);
5190: #endif
5191: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
5192: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
5193: k=kmax;
5194: }
5195: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 5196: k=kmax; l=lmax*10;
1.126 brouard 5197: }
5198: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
5199: delts=delt;
5200: }
1.203 brouard 5201: } /* End loop k */
1.126 brouard 5202: }
5203: delti[theta]=delts;
5204: return res;
5205:
5206: }
5207:
1.203 brouard 5208: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 5209: {
5210: int i;
1.164 brouard 5211: int l=1, lmax=20;
1.126 brouard 5212: double k1,k2,k3,k4,res,fx;
1.132 brouard 5213: double p2[MAXPARM+1];
1.203 brouard 5214: int k, kmax=1;
5215: double v1, v2, cv12, lc1, lc2;
1.208 brouard 5216:
5217: int firstime=0;
1.203 brouard 5218:
1.126 brouard 5219: fx=func(x);
1.203 brouard 5220: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 5221: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 5222: p2[thetai]=x[thetai]+delti[thetai]*k;
5223: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 5224: k1=func(p2)-fx;
5225:
1.203 brouard 5226: p2[thetai]=x[thetai]+delti[thetai]*k;
5227: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 5228: k2=func(p2)-fx;
5229:
1.203 brouard 5230: p2[thetai]=x[thetai]-delti[thetai]*k;
5231: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 5232: k3=func(p2)-fx;
5233:
1.203 brouard 5234: p2[thetai]=x[thetai]-delti[thetai]*k;
5235: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 5236: k4=func(p2)-fx;
1.203 brouard 5237: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
5238: if(k1*k2*k3*k4 <0.){
1.208 brouard 5239: firstime=1;
1.203 brouard 5240: kmax=kmax+10;
1.208 brouard 5241: }
5242: if(kmax >=10 || firstime ==1){
1.246 brouard 5243: 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);
5244: 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 5245: 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);
5246: 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);
5247: }
5248: #ifdef DEBUGHESSIJ
5249: v1=hess[thetai][thetai];
5250: v2=hess[thetaj][thetaj];
5251: cv12=res;
5252: /* Computing eigen value of Hessian matrix */
5253: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
5254: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
5255: if ((lc2 <0) || (lc1 <0) ){
5256: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
5257: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
5258: 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);
5259: 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);
5260: }
1.126 brouard 5261: #endif
5262: }
5263: return res;
5264: }
5265:
1.203 brouard 5266: /* Not done yet: Was supposed to fix if not exactly at the maximum */
5267: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
5268: /* { */
5269: /* int i; */
5270: /* int l=1, lmax=20; */
5271: /* double k1,k2,k3,k4,res,fx; */
5272: /* double p2[MAXPARM+1]; */
5273: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
5274: /* int k=0,kmax=10; */
5275: /* double l1; */
5276:
5277: /* fx=func(x); */
5278: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
5279: /* l1=pow(10,l); */
5280: /* delts=delt; */
5281: /* for(k=1 ; k <kmax; k=k+1){ */
5282: /* delt = delti*(l1*k); */
5283: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
5284: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
5285: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
5286: /* k1=func(p2)-fx; */
5287:
5288: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
5289: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
5290: /* k2=func(p2)-fx; */
5291:
5292: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
5293: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
5294: /* k3=func(p2)-fx; */
5295:
5296: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
5297: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
5298: /* k4=func(p2)-fx; */
5299: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
5300: /* #ifdef DEBUGHESSIJ */
5301: /* 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); */
5302: /* 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); */
5303: /* #endif */
5304: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
5305: /* k=kmax; */
5306: /* } */
5307: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
5308: /* k=kmax; l=lmax*10; */
5309: /* } */
5310: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
5311: /* delts=delt; */
5312: /* } */
5313: /* } /\* End loop k *\/ */
5314: /* } */
5315: /* delti[theta]=delts; */
5316: /* return res; */
5317: /* } */
5318:
5319:
1.126 brouard 5320: /************** Inverse of matrix **************/
5321: void ludcmp(double **a, int n, int *indx, double *d)
5322: {
5323: int i,imax,j,k;
5324: double big,dum,sum,temp;
5325: double *vv;
5326:
5327: vv=vector(1,n);
5328: *d=1.0;
5329: for (i=1;i<=n;i++) {
5330: big=0.0;
5331: for (j=1;j<=n;j++)
5332: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 5333: if (big == 0.0){
5334: printf(" Singular Hessian matrix at row %d:\n",i);
5335: for (j=1;j<=n;j++) {
5336: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
5337: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
5338: }
5339: fflush(ficlog);
5340: fclose(ficlog);
5341: nrerror("Singular matrix in routine ludcmp");
5342: }
1.126 brouard 5343: vv[i]=1.0/big;
5344: }
5345: for (j=1;j<=n;j++) {
5346: for (i=1;i<j;i++) {
5347: sum=a[i][j];
5348: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
5349: a[i][j]=sum;
5350: }
5351: big=0.0;
5352: for (i=j;i<=n;i++) {
5353: sum=a[i][j];
5354: for (k=1;k<j;k++)
5355: sum -= a[i][k]*a[k][j];
5356: a[i][j]=sum;
5357: if ( (dum=vv[i]*fabs(sum)) >= big) {
5358: big=dum;
5359: imax=i;
5360: }
5361: }
5362: if (j != imax) {
5363: for (k=1;k<=n;k++) {
5364: dum=a[imax][k];
5365: a[imax][k]=a[j][k];
5366: a[j][k]=dum;
5367: }
5368: *d = -(*d);
5369: vv[imax]=vv[j];
5370: }
5371: indx[j]=imax;
5372: if (a[j][j] == 0.0) a[j][j]=TINY;
5373: if (j != n) {
5374: dum=1.0/(a[j][j]);
5375: for (i=j+1;i<=n;i++) a[i][j] *= dum;
5376: }
5377: }
5378: free_vector(vv,1,n); /* Doesn't work */
5379: ;
5380: }
5381:
5382: void lubksb(double **a, int n, int *indx, double b[])
5383: {
5384: int i,ii=0,ip,j;
5385: double sum;
5386:
5387: for (i=1;i<=n;i++) {
5388: ip=indx[i];
5389: sum=b[ip];
5390: b[ip]=b[i];
5391: if (ii)
5392: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
5393: else if (sum) ii=i;
5394: b[i]=sum;
5395: }
5396: for (i=n;i>=1;i--) {
5397: sum=b[i];
5398: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
5399: b[i]=sum/a[i][i];
5400: }
5401: }
5402:
5403: void pstamp(FILE *fichier)
5404: {
1.196 brouard 5405: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 5406: }
5407:
1.297 brouard 5408: void date2dmy(double date,double *day, double *month, double *year){
5409: double yp=0., yp1=0., yp2=0.;
5410:
5411: yp1=modf(date,&yp);/* extracts integral of date in yp and
5412: fractional in yp1 */
5413: *year=yp;
5414: yp2=modf((yp1*12),&yp);
5415: *month=yp;
5416: yp1=modf((yp2*30.5),&yp);
5417: *day=yp;
5418: if(*day==0) *day=1;
5419: if(*month==0) *month=1;
5420: }
5421:
1.253 brouard 5422:
5423:
1.126 brouard 5424: /************ Frequencies ********************/
1.251 brouard 5425: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 5426: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
5427: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 5428: { /* Some frequencies as well as proposing some starting values */
1.332 brouard 5429: /* Frequencies of any combination of dummy covariate used in the model equation */
1.265 brouard 5430: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 5431: int iind=0, iage=0;
5432: int mi; /* Effective wave */
5433: int first;
5434: double ***freq; /* Frequencies */
1.268 brouard 5435: 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 */
5436: 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 5437: double *meanq, *stdq, *idq;
1.226 brouard 5438: double **meanqt;
5439: double *pp, **prop, *posprop, *pospropt;
5440: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
5441: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
5442: double agebegin, ageend;
5443:
5444: pp=vector(1,nlstate);
1.251 brouard 5445: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 5446: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
5447: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
5448: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
5449: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 5450: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 5451: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 5452: meanqt=matrix(1,lastpass,1,nqtveff);
5453: strcpy(fileresp,"P_");
5454: strcat(fileresp,fileresu);
5455: /*strcat(fileresphtm,fileresu);*/
5456: if((ficresp=fopen(fileresp,"w"))==NULL) {
5457: printf("Problem with prevalence resultfile: %s\n", fileresp);
5458: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
5459: exit(0);
5460: }
1.240 brouard 5461:
1.226 brouard 5462: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
5463: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
5464: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
5465: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
5466: fflush(ficlog);
5467: exit(70);
5468: }
5469: else{
5470: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 5471: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 5472: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 5473: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
5474: }
1.319 brouard 5475: 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 5476:
1.226 brouard 5477: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
5478: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
5479: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
5480: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
5481: fflush(ficlog);
5482: exit(70);
1.240 brouard 5483: } else{
1.226 brouard 5484: 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 5485: ,<hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 5486: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 5487: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
5488: }
1.319 brouard 5489: 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 5490:
1.253 brouard 5491: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
5492: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 5493: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 5494: j1=0;
1.126 brouard 5495:
1.227 brouard 5496: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
1.335 brouard 5497: j=cptcoveff; /* Only simple dummy covariates used in the model */
1.330 brouard 5498: /* j=cptcovn; /\* Only dummy covariates of the model *\/ */
1.226 brouard 5499: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 5500:
5501:
1.226 brouard 5502: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
5503: reference=low_education V1=0,V2=0
5504: med_educ V1=1 V2=0,
5505: high_educ V1=0 V2=1
1.330 brouard 5506: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcovn
1.226 brouard 5507: */
1.249 brouard 5508: dateintsum=0;
5509: k2cpt=0;
5510:
1.253 brouard 5511: if(cptcoveff == 0 )
1.265 brouard 5512: nl=1; /* Constant and age model only */
1.253 brouard 5513: else
5514: nl=2;
1.265 brouard 5515:
5516: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
5517: /* Loop on nj=1 or 2 if dummy covariates j!=0
1.335 brouard 5518: * Loop on j1(1 to 2**cptcoveff) covariate combination
1.265 brouard 5519: * freq[s1][s2][iage] =0.
5520: * Loop on iind
5521: * ++freq[s1][s2][iage] weighted
5522: * end iind
5523: * if covariate and j!0
5524: * headers Variable on one line
5525: * endif cov j!=0
5526: * header of frequency table by age
5527: * Loop on age
5528: * pp[s1]+=freq[s1][s2][iage] weighted
5529: * pos+=freq[s1][s2][iage] weighted
5530: * Loop on s1 initial state
5531: * fprintf(ficresp
5532: * end s1
5533: * end age
5534: * if j!=0 computes starting values
5535: * end compute starting values
5536: * end j1
5537: * end nl
5538: */
1.253 brouard 5539: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
5540: if(nj==1)
5541: j=0; /* First pass for the constant */
1.265 brouard 5542: else{
1.335 brouard 5543: 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 5544: }
1.251 brouard 5545: first=1;
1.332 brouard 5546: 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 5547: posproptt=0.;
1.330 brouard 5548: /*printf("cptcovn=%d Tvaraff=%d", cptcovn,Tvaraff[1]);
1.251 brouard 5549: scanf("%d", i);*/
5550: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 5551: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 5552: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 5553: freq[i][s2][m]=0;
1.251 brouard 5554:
5555: for (i=1; i<=nlstate; i++) {
1.240 brouard 5556: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 5557: prop[i][m]=0;
5558: posprop[i]=0;
5559: pospropt[i]=0;
5560: }
1.283 brouard 5561: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 5562: idq[z1]=0.;
5563: meanq[z1]=0.;
5564: stdq[z1]=0.;
1.283 brouard 5565: }
5566: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 5567: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 5568: /* meanqt[m][z1]=0.; */
5569: /* } */
5570: /* } */
1.251 brouard 5571: /* dateintsum=0; */
5572: /* k2cpt=0; */
5573:
1.265 brouard 5574: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 5575: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
5576: bool=1;
5577: if(j !=0){
5578: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
1.335 brouard 5579: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
5580: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
1.251 brouard 5581: /* if(Tvaraff[z1] ==-20){ */
5582: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
5583: /* }else if(Tvaraff[z1] ==-10){ */
5584: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
1.330 brouard 5585: /* }else */ /* TODO TODO codtabm(j1,z1) or codtabm(j1,Tvaraff[z1]]z1)*/
1.335 brouard 5586: /* 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); */
5587: if(Tvaraff[z1]<1 || Tvaraff[z1]>=NCOVMAX)
1.338 brouard 5588: printf("Error Tvaraff[z1]=%d<1 or >=%d, cptcoveff=%d model=1+age+%s\n",Tvaraff[z1],NCOVMAX, cptcoveff, model);
1.332 brouard 5589: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]){ /* for combination j1 of covariates */
1.265 brouard 5590: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 5591: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
1.332 brouard 5592: /* 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", */
5593: /* bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),*/
5594: /* j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
1.251 brouard 5595: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
5596: } /* Onlyf fixed */
5597: } /* end z1 */
1.335 brouard 5598: } /* cptcoveff > 0 */
1.251 brouard 5599: } /* end any */
5600: }/* end j==0 */
1.265 brouard 5601: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 5602: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 5603: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 5604: m=mw[mi][iind];
5605: if(j!=0){
5606: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
1.335 brouard 5607: for (z1=1; z1<=cptcoveff; z1++) {
1.251 brouard 5608: if( Fixed[Tmodelind[z1]]==1){
1.341 brouard 5609: /* iv= Tvar[Tmodelind[z1]]-ncovcol-nqv; /\* Good *\/ */
5610: iv= Tvar[Tmodelind[z1]]; /* Good *//* because cotvar starts now at first at ncovcol+nqv+ntv */
1.332 brouard 5611: 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 5612: value is -1, we don't select. It differs from the
5613: constant and age model which counts them. */
5614: bool=0; /* not selected */
5615: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
1.334 brouard 5616: /* i1=Tvaraff[z1]; */
5617: /* i2=TnsdVar[i1]; */
5618: /* i3=nbcode[i1][i2]; */
5619: /* i4=covar[i1][iind]; */
5620: /* if(i4 != i3){ */
5621: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) { /* Bug valgrind */
1.251 brouard 5622: bool=0;
5623: }
5624: }
5625: }
5626: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
5627: } /* end j==0 */
5628: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 5629: if(bool==1){ /*Selected */
1.251 brouard 5630: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
5631: and mw[mi+1][iind]. dh depends on stepm. */
5632: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
5633: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
5634: if(m >=firstpass && m <=lastpass){
5635: k2=anint[m][iind]+(mint[m][iind]/12.);
5636: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
5637: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
5638: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
5639: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
5640: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
5641: if (m<lastpass) {
5642: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
5643: /* 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]); */
5644: if(s[m][iind]==-1)
5645: 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.));
5646: 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 5647: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean on known values only */
5648: if(!isnan(covar[ncovcol+z1][iind])){
1.332 brouard 5649: idq[z1]=idq[z1]+weight[iind];
5650: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
5651: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; *//*error*/
5652: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
1.311 brouard 5653: }
1.284 brouard 5654: }
1.251 brouard 5655: /* if((int)agev[m][iind] == 55) */
5656: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
5657: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
5658: 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 5659: }
1.251 brouard 5660: } /* end if between passes */
5661: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
5662: dateintsum=dateintsum+k2; /* on all covariates ?*/
5663: k2cpt++;
5664: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 5665: }
1.251 brouard 5666: }else{
5667: bool=1;
5668: }/* end bool 2 */
5669: } /* end m */
1.284 brouard 5670: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
5671: /* idq[z1]=idq[z1]+weight[iind]; */
5672: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
5673: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
5674: /* } */
1.251 brouard 5675: } /* end bool */
5676: } /* end iind = 1 to imx */
1.319 brouard 5677: /* prop[s][age] is fed for any initial and valid live state as well as
1.251 brouard 5678: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
5679:
5680:
5681: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.335 brouard 5682: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
1.265 brouard 5683: pstamp(ficresp);
1.335 brouard 5684: if (cptcoveff>0 && j!=0){
1.265 brouard 5685: pstamp(ficresp);
1.251 brouard 5686: printf( "\n#********** Variable ");
5687: fprintf(ficresp, "\n#********** Variable ");
5688: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
5689: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
5690: fprintf(ficlog, "\n#********** Variable ");
1.340 brouard 5691: for (z1=1; z1<=cptcoveff; z1++){
1.251 brouard 5692: if(!FixedV[Tvaraff[z1]]){
1.330 brouard 5693: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5694: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5695: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5696: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5697: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.250 brouard 5698: }else{
1.330 brouard 5699: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5700: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5701: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5702: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5703: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.251 brouard 5704: }
5705: }
5706: printf( "**********\n#");
5707: fprintf(ficresp, "**********\n#");
5708: fprintf(ficresphtm, "**********</h3>\n");
5709: fprintf(ficresphtmfr, "**********</h3>\n");
5710: fprintf(ficlog, "**********\n");
5711: }
1.284 brouard 5712: /*
5713: Printing means of quantitative variables if any
5714: */
5715: for (z1=1; z1<= nqfveff; z1++) {
1.311 brouard 5716: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.3g (weighted) individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.312 brouard 5717: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
1.284 brouard 5718: if(weightopt==1){
5719: printf(" Weighted mean and standard deviation of");
5720: fprintf(ficlog," Weighted mean and standard deviation of");
5721: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
5722: }
1.311 brouard 5723: /* mu = \frac{w x}{\sum w}
5724: var = \frac{\sum w (x-mu)^2}{\sum w} = \frac{w x^2}{\sum w} - mu^2
5725: */
5726: 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]));
5727: 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]));
5728: 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 5729: }
5730: /* for (z1=1; z1<= nqtveff; z1++) { */
5731: /* for(m=1;m<=lastpass;m++){ */
5732: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
5733: /* } */
5734: /* } */
1.283 brouard 5735:
1.251 brouard 5736: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.335 brouard 5737: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
1.265 brouard 5738: fprintf(ficresp, " Age");
1.335 brouard 5739: if(nj==2) for (z1=1; z1<=cptcoveff; z1++) {
5740: 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]]);
5741: fprintf(ficresp, " V%d=%d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5742: }
1.251 brouard 5743: for(i=1; i<=nlstate;i++) {
1.335 brouard 5744: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 5745: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
5746: }
1.335 brouard 5747: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 5748: fprintf(ficresphtm, "\n");
5749:
5750: /* Header of frequency table by age */
5751: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
5752: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 5753: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 5754: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5755: if(s2!=0 && m!=0)
5756: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 5757: }
1.226 brouard 5758: }
1.251 brouard 5759: fprintf(ficresphtmfr, "\n");
5760:
5761: /* For each age */
5762: for(iage=iagemin; iage <= iagemax+3; iage++){
5763: fprintf(ficresphtm,"<tr>");
5764: if(iage==iagemax+1){
5765: fprintf(ficlog,"1");
5766: fprintf(ficresphtmfr,"<tr><th>0</th> ");
5767: }else if(iage==iagemax+2){
5768: fprintf(ficlog,"0");
5769: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
5770: }else if(iage==iagemax+3){
5771: fprintf(ficlog,"Total");
5772: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
5773: }else{
1.240 brouard 5774: if(first==1){
1.251 brouard 5775: first=0;
5776: printf("See log file for details...\n");
5777: }
5778: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
5779: fprintf(ficlog,"Age %d", iage);
5780: }
1.265 brouard 5781: for(s1=1; s1 <=nlstate ; s1++){
5782: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
5783: pp[s1] += freq[s1][m][iage];
1.251 brouard 5784: }
1.265 brouard 5785: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5786: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 5787: pos += freq[s1][m][iage];
5788: if(pp[s1]>=1.e-10){
1.251 brouard 5789: if(first==1){
1.265 brouard 5790: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5791: }
1.265 brouard 5792: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5793: }else{
5794: if(first==1)
1.265 brouard 5795: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
5796: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 5797: }
5798: }
5799:
1.265 brouard 5800: for(s1=1; s1 <=nlstate ; s1++){
5801: /* posprop[s1]=0; */
5802: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
5803: pp[s1] += freq[s1][m][iage];
5804: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
5805:
5806: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
5807: pos += pp[s1]; /* pos is the total number of transitions until this age */
5808: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
5809: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5810: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
5811: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5812: }
5813:
5814: /* Writing ficresp */
1.335 brouard 5815: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5816: if( iage <= iagemax){
5817: fprintf(ficresp," %d",iage);
5818: }
5819: }else if( nj==2){
5820: if( iage <= iagemax){
5821: fprintf(ficresp," %d",iage);
1.335 brouard 5822: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.265 brouard 5823: }
1.240 brouard 5824: }
1.265 brouard 5825: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 5826: if(pos>=1.e-5){
1.251 brouard 5827: if(first==1)
1.265 brouard 5828: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
5829: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 5830: }else{
5831: if(first==1)
1.265 brouard 5832: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
5833: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 5834: }
5835: if( iage <= iagemax){
5836: if(pos>=1.e-5){
1.335 brouard 5837: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5838: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5839: }else if( nj==2){
5840: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5841: }
5842: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5843: /*probs[iage][s1][j1]= pp[s1]/pos;*/
5844: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
5845: } else{
1.335 brouard 5846: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
1.265 brouard 5847: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 5848: }
1.240 brouard 5849: }
1.265 brouard 5850: pospropt[s1] +=posprop[s1];
5851: } /* end loop s1 */
1.251 brouard 5852: /* pospropt=0.; */
1.265 brouard 5853: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 5854: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5855: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 5856: if(first==1){
1.265 brouard 5857: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5858: }
1.265 brouard 5859: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
5860: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5861: }
1.265 brouard 5862: if(s1!=0 && m!=0)
5863: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 5864: }
1.265 brouard 5865: } /* end loop s1 */
1.251 brouard 5866: posproptt=0.;
1.265 brouard 5867: for(s1=1; s1 <=nlstate; s1++){
5868: posproptt += pospropt[s1];
1.251 brouard 5869: }
5870: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 5871: fprintf(ficresphtm,"</tr>\n");
1.335 brouard 5872: if((cptcoveff==0 && nj==1)|| nj==2 ) {
1.265 brouard 5873: if(iage <= iagemax)
5874: fprintf(ficresp,"\n");
1.240 brouard 5875: }
1.251 brouard 5876: if(first==1)
5877: printf("Others in log...\n");
5878: fprintf(ficlog,"\n");
5879: } /* end loop age iage */
1.265 brouard 5880:
1.251 brouard 5881: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 5882: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5883: if(posproptt < 1.e-5){
1.265 brouard 5884: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 5885: }else{
1.265 brouard 5886: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 5887: }
1.226 brouard 5888: }
1.251 brouard 5889: fprintf(ficresphtm,"</tr>\n");
5890: fprintf(ficresphtm,"</table>\n");
5891: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 5892: if(posproptt < 1.e-5){
1.251 brouard 5893: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
5894: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 5895: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
5896: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 5897: invalidvarcomb[j1]=1;
1.226 brouard 5898: }else{
1.338 brouard 5899: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced (or no resultline).</p>",j1);
1.251 brouard 5900: invalidvarcomb[j1]=0;
1.226 brouard 5901: }
1.251 brouard 5902: fprintf(ficresphtmfr,"</table>\n");
5903: fprintf(ficlog,"\n");
5904: if(j!=0){
5905: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 5906: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5907: for(k=1; k <=(nlstate+ndeath); k++){
5908: if (k != i) {
1.265 brouard 5909: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 5910: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 5911: if(j1==1){ /* All dummy covariates to zero */
5912: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
5913: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 5914: printf("%d%d ",i,k);
5915: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5916: 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]));
5917: 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]));
5918: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 5919: }
1.253 brouard 5920: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
5921: for(iage=iagemin; iage <= iagemax+3; iage++){
5922: x[iage]= (double)iage;
5923: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 5924: /* 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 5925: }
1.268 brouard 5926: /* Some are not finite, but linreg will ignore these ages */
5927: no=0;
1.253 brouard 5928: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 5929: pstart[s1]=b;
5930: pstart[s1-1]=a;
1.252 brouard 5931: }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 */
5932: 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]);
5933: 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 5934: 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 5935: printf("%d%d ",i,k);
5936: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5937: 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 5938: }else{ /* Other cases, like quantitative fixed or varying covariates */
5939: ;
5940: }
5941: /* printf("%12.7f )", param[i][jj][k]); */
5942: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5943: s1++;
1.251 brouard 5944: } /* end jj */
5945: } /* end k!= i */
5946: } /* end k */
1.265 brouard 5947: } /* end i, s1 */
1.251 brouard 5948: } /* end j !=0 */
5949: } /* end selected combination of covariate j1 */
5950: if(j==0){ /* We can estimate starting values from the occurences in each case */
5951: printf("#Freqsummary: Starting values for the constants:\n");
5952: fprintf(ficlog,"\n");
1.265 brouard 5953: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5954: for(k=1; k <=(nlstate+ndeath); k++){
5955: if (k != i) {
5956: printf("%d%d ",i,k);
5957: fprintf(ficlog,"%d%d ",i,k);
5958: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 5959: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 5960: if(jj==1){ /* Age has to be done */
1.265 brouard 5961: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
5962: 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]));
5963: 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 5964: }
5965: /* printf("%12.7f )", param[i][jj][k]); */
5966: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5967: s1++;
1.250 brouard 5968: }
1.251 brouard 5969: printf("\n");
5970: fprintf(ficlog,"\n");
1.250 brouard 5971: }
5972: }
1.284 brouard 5973: } /* end of state i */
1.251 brouard 5974: printf("#Freqsummary\n");
5975: fprintf(ficlog,"\n");
1.265 brouard 5976: for(s1=-1; s1 <=nlstate+ndeath; s1++){
5977: for(s2=-1; s2 <=nlstate+ndeath; s2++){
5978: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
5979: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5980: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5981: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
5982: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
5983: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 5984: /* } */
5985: }
1.265 brouard 5986: } /* end loop s1 */
1.251 brouard 5987:
5988: printf("\n");
5989: fprintf(ficlog,"\n");
5990: } /* end j=0 */
1.249 brouard 5991: } /* end j */
1.252 brouard 5992:
1.253 brouard 5993: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 5994: for(i=1, jk=1; i <=nlstate; i++){
5995: for(j=1; j <=nlstate+ndeath; j++){
5996: if(j!=i){
5997: /*ca[0]= k+'a'-1;ca[1]='\0';*/
5998: printf("%1d%1d",i,j);
5999: fprintf(ficparo,"%1d%1d",i,j);
6000: for(k=1; k<=ncovmodel;k++){
6001: /* printf(" %lf",param[i][j][k]); */
6002: /* fprintf(ficparo," %lf",param[i][j][k]); */
6003: p[jk]=pstart[jk];
6004: printf(" %f ",pstart[jk]);
6005: fprintf(ficparo," %f ",pstart[jk]);
6006: jk++;
6007: }
6008: printf("\n");
6009: fprintf(ficparo,"\n");
6010: }
6011: }
6012: }
6013: } /* end mle=-2 */
1.226 brouard 6014: dateintmean=dateintsum/k2cpt;
1.296 brouard 6015: date2dmy(dateintmean,&jintmean,&mintmean,&aintmean);
1.240 brouard 6016:
1.226 brouard 6017: fclose(ficresp);
6018: fclose(ficresphtm);
6019: fclose(ficresphtmfr);
1.283 brouard 6020: free_vector(idq,1,nqfveff);
1.226 brouard 6021: free_vector(meanq,1,nqfveff);
1.284 brouard 6022: free_vector(stdq,1,nqfveff);
1.226 brouard 6023: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 6024: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
6025: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 6026: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 6027: free_vector(pospropt,1,nlstate);
6028: free_vector(posprop,1,nlstate);
1.251 brouard 6029: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 6030: free_vector(pp,1,nlstate);
6031: /* End of freqsummary */
6032: }
1.126 brouard 6033:
1.268 brouard 6034: /* Simple linear regression */
6035: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
6036:
6037: /* y=a+bx regression */
6038: double sumx = 0.0; /* sum of x */
6039: double sumx2 = 0.0; /* sum of x**2 */
6040: double sumxy = 0.0; /* sum of x * y */
6041: double sumy = 0.0; /* sum of y */
6042: double sumy2 = 0.0; /* sum of y**2 */
6043: double sume2 = 0.0; /* sum of square or residuals */
6044: double yhat;
6045:
6046: double denom=0;
6047: int i;
6048: int ne=*no;
6049:
6050: for ( i=ifi, ne=0;i<=ila;i++) {
6051: if(!isfinite(x[i]) || !isfinite(y[i])){
6052: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
6053: continue;
6054: }
6055: ne=ne+1;
6056: sumx += x[i];
6057: sumx2 += x[i]*x[i];
6058: sumxy += x[i] * y[i];
6059: sumy += y[i];
6060: sumy2 += y[i]*y[i];
6061: denom = (ne * sumx2 - sumx*sumx);
6062: /* 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); */
6063: }
6064:
6065: denom = (ne * sumx2 - sumx*sumx);
6066: if (denom == 0) {
6067: // vertical, slope m is infinity
6068: *b = INFINITY;
6069: *a = 0;
6070: if (r) *r = 0;
6071: return 1;
6072: }
6073:
6074: *b = (ne * sumxy - sumx * sumy) / denom;
6075: *a = (sumy * sumx2 - sumx * sumxy) / denom;
6076: if (r!=NULL) {
6077: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
6078: sqrt((sumx2 - sumx*sumx/ne) *
6079: (sumy2 - sumy*sumy/ne));
6080: }
6081: *no=ne;
6082: for ( i=ifi, ne=0;i<=ila;i++) {
6083: if(!isfinite(x[i]) || !isfinite(y[i])){
6084: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
6085: continue;
6086: }
6087: ne=ne+1;
6088: yhat = y[i] - *a -*b* x[i];
6089: sume2 += yhat * yhat ;
6090:
6091: denom = (ne * sumx2 - sumx*sumx);
6092: /* 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); */
6093: }
6094: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
6095: *sa= *sb * sqrt(sumx2/ne);
6096:
6097: return 0;
6098: }
6099:
1.126 brouard 6100: /************ Prevalence ********************/
1.227 brouard 6101: 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)
6102: {
6103: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
6104: in each health status at the date of interview (if between dateprev1 and dateprev2).
6105: We still use firstpass and lastpass as another selection.
6106: */
1.126 brouard 6107:
1.227 brouard 6108: int i, m, jk, j1, bool, z1,j, iv;
6109: int mi; /* Effective wave */
6110: int iage;
6111: double agebegin, ageend;
6112:
6113: double **prop;
6114: double posprop;
6115: double y2; /* in fractional years */
6116: int iagemin, iagemax;
6117: int first; /** to stop verbosity which is redirected to log file */
6118:
6119: iagemin= (int) agemin;
6120: iagemax= (int) agemax;
6121: /*pp=vector(1,nlstate);*/
1.251 brouard 6122: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 6123: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
6124: j1=0;
1.222 brouard 6125:
1.227 brouard 6126: /*j=cptcoveff;*/
6127: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 6128:
1.288 brouard 6129: first=0;
1.335 brouard 6130: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of simple dummy covariates */
1.227 brouard 6131: for (i=1; i<=nlstate; i++)
1.251 brouard 6132: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 6133: prop[i][iage]=0.0;
6134: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
6135: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
6136: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
6137:
6138: for (i=1; i<=imx; i++) { /* Each individual */
6139: bool=1;
6140: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
6141: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
6142: m=mw[mi][i];
6143: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
6144: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
6145: for (z1=1; z1<=cptcoveff; z1++){
6146: if( Fixed[Tmodelind[z1]]==1){
1.341 brouard 6147: iv= Tvar[Tmodelind[z1]];/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
1.332 brouard 6148: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) /* iv=1 to ntv, right modality */
1.227 brouard 6149: bool=0;
6150: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
1.332 brouard 6151: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) {
1.227 brouard 6152: bool=0;
6153: }
6154: }
6155: if(bool==1){ /* Otherwise we skip that wave/person */
6156: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
6157: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
6158: if(m >=firstpass && m <=lastpass){
6159: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
6160: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
6161: if(agev[m][i]==0) agev[m][i]=iagemax+1;
6162: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 6163: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 6164: 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);
6165: exit(1);
6166: }
6167: if (s[m][i]>0 && s[m][i]<=nlstate) {
6168: /*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]]);*/
6169: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
6170: prop[s[m][i]][iagemax+3] += weight[i];
6171: } /* end valid statuses */
6172: } /* end selection of dates */
6173: } /* end selection of waves */
6174: } /* end bool */
6175: } /* end wave */
6176: } /* end individual */
6177: for(i=iagemin; i <= iagemax+3; i++){
6178: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
6179: posprop += prop[jk][i];
6180: }
6181:
6182: for(jk=1; jk <=nlstate ; jk++){
6183: if( i <= iagemax){
6184: if(posprop>=1.e-5){
6185: probs[i][jk][j1]= prop[jk][i]/posprop;
6186: } else{
1.288 brouard 6187: if(!first){
6188: first=1;
1.266 brouard 6189: 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]);
6190: }else{
1.288 brouard 6191: 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 6192: }
6193: }
6194: }
6195: }/* end jk */
6196: }/* end i */
1.222 brouard 6197: /*} *//* end i1 */
1.227 brouard 6198: } /* end j1 */
1.222 brouard 6199:
1.227 brouard 6200: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
6201: /*free_vector(pp,1,nlstate);*/
1.251 brouard 6202: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 6203: } /* End of prevalence */
1.126 brouard 6204:
6205: /************* Waves Concatenation ***************/
6206:
6207: 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)
6208: {
1.298 brouard 6209: /* 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 6210: Death is a valid wave (if date is known).
6211: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
6212: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
1.298 brouard 6213: and mw[mi+1][i]. dh depends on stepm. s[m][i] exists for any wave from firstpass to lastpass
1.227 brouard 6214: */
1.126 brouard 6215:
1.224 brouard 6216: int i=0, mi=0, m=0, mli=0;
1.126 brouard 6217: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
6218: double sum=0., jmean=0.;*/
1.224 brouard 6219: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 6220: int j, k=0,jk, ju, jl;
6221: double sum=0.;
6222: first=0;
1.214 brouard 6223: firstwo=0;
1.217 brouard 6224: firsthree=0;
1.218 brouard 6225: firstfour=0;
1.164 brouard 6226: jmin=100000;
1.126 brouard 6227: jmax=-1;
6228: jmean=0.;
1.224 brouard 6229:
6230: /* Treating live states */
1.214 brouard 6231: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 6232: mi=0; /* First valid wave */
1.227 brouard 6233: mli=0; /* Last valid wave */
1.309 brouard 6234: m=firstpass; /* Loop on waves */
6235: while(s[m][i] <= nlstate){ /* a live state or unknown state */
1.227 brouard 6236: 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 */
6237: mli=m-1;/* mw[++mi][i]=m-1; */
6238: }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 6239: 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 6240: mli=m;
1.224 brouard 6241: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
6242: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 6243: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 6244: }
1.309 brouard 6245: else{ /* m = lastpass, eventual special issue with warning */
1.224 brouard 6246: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 6247: break;
1.224 brouard 6248: #else
1.317 brouard 6249: 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 6250: if(firsthree == 0){
1.302 brouard 6251: 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 6252: firsthree=1;
1.317 brouard 6253: }else if(firsthree >=1 && firsthree < 10){
6254: 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);
6255: firsthree++;
6256: }else if(firsthree == 10){
6257: printf("Information, too many Information flags: no more reported to log either\n");
6258: fprintf(ficlog,"Information, too many Information flags: no more reported to log either\n");
6259: firsthree++;
6260: }else{
6261: firsthree++;
1.227 brouard 6262: }
1.309 brouard 6263: mw[++mi][i]=m; /* Valid transition with unknown status */
1.227 brouard 6264: mli=m;
6265: }
6266: if(s[m][i]==-2){ /* Vital status is really unknown */
6267: nbwarn++;
1.309 brouard 6268: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified?not a transition */
1.227 brouard 6269: 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);
6270: 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);
6271: }
6272: break;
6273: }
6274: break;
1.224 brouard 6275: #endif
1.227 brouard 6276: }/* End m >= lastpass */
1.126 brouard 6277: }/* end while */
1.224 brouard 6278:
1.227 brouard 6279: /* 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 6280: /* After last pass */
1.224 brouard 6281: /* Treating death states */
1.214 brouard 6282: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 6283: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
6284: /* } */
1.126 brouard 6285: mi++; /* Death is another wave */
6286: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 6287: /* Only death is a correct wave */
1.126 brouard 6288: mw[mi][i]=m;
1.257 brouard 6289: } /* else not in a death state */
1.224 brouard 6290: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 6291: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 6292: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.309 brouard 6293: 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 6294: nbwarn++;
6295: if(firstfiv==0){
1.309 brouard 6296: 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 6297: firstfiv=1;
6298: }else{
1.309 brouard 6299: 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 6300: }
1.309 brouard 6301: s[m][i]=nlstate+1; /* Fixing the status as death. Be careful if multiple death states */
6302: }else{ /* Month of Death occured afer last wave month, potential bias */
1.227 brouard 6303: nberr++;
6304: if(firstwo==0){
1.309 brouard 6305: 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 6306: firstwo=1;
6307: }
1.309 brouard 6308: 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 6309: }
1.257 brouard 6310: }else{ /* if date of interview is unknown */
1.227 brouard 6311: /* death is known but not confirmed by death status at any wave */
6312: if(firstfour==0){
1.309 brouard 6313: 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 6314: firstfour=1;
6315: }
1.309 brouard 6316: 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 6317: }
1.224 brouard 6318: } /* end if date of death is known */
6319: #endif
1.309 brouard 6320: wav[i]=mi; /* mi should be the last effective wave (or mli), */
6321: /* wav[i]=mw[mi][i]; */
1.126 brouard 6322: if(mi==0){
6323: nbwarn++;
6324: if(first==0){
1.227 brouard 6325: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
6326: first=1;
1.126 brouard 6327: }
6328: if(first==1){
1.227 brouard 6329: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 6330: }
6331: } /* end mi==0 */
6332: } /* End individuals */
1.214 brouard 6333: /* wav and mw are no more changed */
1.223 brouard 6334:
1.317 brouard 6335: printf("Information, you have to check %d informations which haven't been logged!\n",firsthree);
6336: fprintf(ficlog,"Information, you have to check %d informations which haven't been logged!\n",firsthree);
6337:
6338:
1.126 brouard 6339: for(i=1; i<=imx; i++){
6340: for(mi=1; mi<wav[i];mi++){
6341: if (stepm <=0)
1.227 brouard 6342: dh[mi][i]=1;
1.126 brouard 6343: else{
1.260 brouard 6344: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 6345: if (agedc[i] < 2*AGESUP) {
6346: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
6347: if(j==0) j=1; /* Survives at least one month after exam */
6348: else if(j<0){
6349: nberr++;
6350: 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]);
6351: j=1; /* Temporary Dangerous patch */
6352: 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);
6353: 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]);
6354: 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);
6355: }
6356: k=k+1;
6357: if (j >= jmax){
6358: jmax=j;
6359: ijmax=i;
6360: }
6361: if (j <= jmin){
6362: jmin=j;
6363: ijmin=i;
6364: }
6365: sum=sum+j;
6366: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
6367: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
6368: }
6369: }
6370: else{
6371: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 6372: /* 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 6373:
1.227 brouard 6374: k=k+1;
6375: if (j >= jmax) {
6376: jmax=j;
6377: ijmax=i;
6378: }
6379: else if (j <= jmin){
6380: jmin=j;
6381: ijmin=i;
6382: }
6383: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
6384: /*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]);*/
6385: if(j<0){
6386: nberr++;
6387: 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]);
6388: 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]);
6389: }
6390: sum=sum+j;
6391: }
6392: jk= j/stepm;
6393: jl= j -jk*stepm;
6394: ju= j -(jk+1)*stepm;
6395: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
6396: if(jl==0){
6397: dh[mi][i]=jk;
6398: bh[mi][i]=0;
6399: }else{ /* We want a negative bias in order to only have interpolation ie
6400: * to avoid the price of an extra matrix product in likelihood */
6401: dh[mi][i]=jk+1;
6402: bh[mi][i]=ju;
6403: }
6404: }else{
6405: if(jl <= -ju){
6406: dh[mi][i]=jk;
6407: bh[mi][i]=jl; /* bias is positive if real duration
6408: * is higher than the multiple of stepm and negative otherwise.
6409: */
6410: }
6411: else{
6412: dh[mi][i]=jk+1;
6413: bh[mi][i]=ju;
6414: }
6415: if(dh[mi][i]==0){
6416: dh[mi][i]=1; /* At least one step */
6417: bh[mi][i]=ju; /* At least one step */
6418: /* 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);*/
6419: }
6420: } /* end if mle */
1.126 brouard 6421: }
6422: } /* end wave */
6423: }
6424: jmean=sum/k;
6425: 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 6426: 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 6427: }
1.126 brouard 6428:
6429: /*********** Tricode ****************************/
1.220 brouard 6430: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 6431: {
6432: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
6433: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
6434: * Boring subroutine which should only output nbcode[Tvar[j]][k]
6435: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
6436: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
6437: */
1.130 brouard 6438:
1.242 brouard 6439: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
6440: int modmaxcovj=0; /* Modality max of covariates j */
6441: int cptcode=0; /* Modality max of covariates j */
6442: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 6443:
6444:
1.242 brouard 6445: /* cptcoveff=0; */
6446: /* *cptcov=0; */
1.126 brouard 6447:
1.242 brouard 6448: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 6449: for (k=1; k <= maxncov; k++)
6450: for(j=1; j<=2; j++)
6451: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 6452:
1.242 brouard 6453: /* Loop on covariates without age and products and no quantitative variable */
1.335 brouard 6454: 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 6455: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
1.343 brouard 6456: /* printf("Testing k=%d, cptcovt=%d\n",k, cptcovt); */
1.349 ! brouard 6457: if(Dummy[k]==0 && Typevar[k] !=1 && Typevar[k] != 3 && Typevar[k] != 2){ /* Dummy covariate and not age product nor fixed product */
1.242 brouard 6458: switch(Fixed[k]) {
6459: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
1.311 brouard 6460: modmaxcovj=0;
6461: modmincovj=0;
1.242 brouard 6462: 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 6463: /* 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 6464: ij=(int)(covar[Tvar[k]][i]);
6465: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
6466: * If product of Vn*Vm, still boolean *:
6467: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
6468: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
6469: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
6470: modality of the nth covariate of individual i. */
6471: if (ij > modmaxcovj)
6472: modmaxcovj=ij;
6473: else if (ij < modmincovj)
6474: modmincovj=ij;
1.287 brouard 6475: if (ij <0 || ij >1 ){
1.311 brouard 6476: printf("ERROR, IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
6477: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
6478: fflush(ficlog);
6479: exit(1);
1.287 brouard 6480: }
6481: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 6482: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
6483: exit(1);
6484: }else
6485: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
6486: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
6487: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
6488: /* getting the maximum value of the modality of the covariate
6489: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
6490: female ies 1, then modmaxcovj=1.
6491: */
6492: } /* end for loop on individuals i */
6493: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
6494: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
6495: cptcode=modmaxcovj;
6496: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
6497: /*for (i=0; i<=cptcode; i++) {*/
6498: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
6499: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
6500: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
6501: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
6502: if( j != -1){
6503: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
6504: covariate for which somebody answered excluding
6505: undefined. Usually 2: 0 and 1. */
6506: }
6507: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
6508: covariate for which somebody answered including
6509: undefined. Usually 3: -1, 0 and 1. */
6510: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
6511: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
6512: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 6513:
1.242 brouard 6514: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
6515: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
6516: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
6517: /* modmincovj=3; modmaxcovj = 7; */
6518: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
6519: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
6520: /* defining two dummy variables: variables V1_1 and V1_2.*/
6521: /* nbcode[Tvar[j]][ij]=k; */
6522: /* nbcode[Tvar[j]][1]=0; */
6523: /* nbcode[Tvar[j]][2]=1; */
6524: /* nbcode[Tvar[j]][3]=2; */
6525: /* To be continued (not working yet). */
6526: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 6527:
6528: /* 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*/
6529: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
6530: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
6531: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
6532: /*, could be restored in the future */
6533: 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 6534: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
6535: break;
6536: }
6537: ij++;
1.287 brouard 6538: 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 6539: cptcode = ij; /* New max modality for covar j */
6540: } /* end of loop on modality i=-1 to 1 or more */
6541: break;
6542: case 1: /* Testing on varying covariate, could be simple and
6543: * should look at waves or product of fixed *
6544: * varying. No time to test -1, assuming 0 and 1 only */
6545: ij=0;
6546: for(i=0; i<=1;i++){
6547: nbcode[Tvar[k]][++ij]=i;
6548: }
6549: break;
6550: default:
6551: break;
6552: } /* end switch */
6553: } /* end dummy test */
1.349 ! brouard 6554: if(Dummy[k]==1 && Typevar[k] !=1 && Typevar[k] !=3 && Fixed ==0){ /* Fixed Quantitative covariate and not age product */
1.311 brouard 6555: 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 6556: if(Tvar[k]<=0 || Tvar[k]>=NCOVMAX){
6557: printf("Error k=%d \n",k);
6558: exit(1);
6559: }
1.311 brouard 6560: if(isnan(covar[Tvar[k]][i])){
6561: printf("ERROR, IMaCh doesn't treat fixed quantitative covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
6562: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
6563: fflush(ficlog);
6564: exit(1);
6565: }
6566: }
1.335 brouard 6567: } /* end Quanti */
1.287 brouard 6568: } /* 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 6569:
6570: for (k=-1; k< maxncov; k++) Ndum[k]=0;
6571: /* Look at fixed dummy (single or product) covariates to check empty modalities */
6572: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
6573: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
6574: 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 */
6575: 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 */
6576: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
6577: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
6578:
6579: ij=0;
6580: /* 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 6581: 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 */
6582: /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
1.242 brouard 6583: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
6584: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
1.335 brouard 6585: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy simple and non empty in the model */
6586: /* Typevar[k] =0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
6587: /* 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 6588: /* If product not in single variable we don't print results */
6589: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
1.335 brouard 6590: ++ij;/* V5 + V4 + V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V1, *//* V5 quanti, V2 quanti, V4, V3, V1 dummies */
6591: /* k= 1 2 3 4 5 6 7 8 9 */
6592: /* Tvar[k]= 5 4 3 6 5 2 7 1 1 */
6593: /* ij 1 2 3 */
6594: /* Tvaraff[ij]= 4 3 1 */
6595: /* Tmodelind[ij]=2 3 9 */
6596: /* TmodelInvind[ij]=2 1 1 */
1.242 brouard 6597: 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*/
6598: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
6599: 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 */
6600: if(Fixed[k]!=0)
6601: anyvaryingduminmodel=1;
6602: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
6603: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
6604: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
6605: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
6606: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
6607: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
6608: }
6609: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
6610: /* ij--; */
6611: /* cptcoveff=ij; /\*Number of total covariates*\/ */
1.335 brouard 6612: *cptcov=ij; /* cptcov= Number of total real effective simple dummies (fixed or time arying) effective (used as cptcoveff in other functions)
1.242 brouard 6613: * because they can be excluded from the model and real
6614: * if in the model but excluded because missing values, but how to get k from ij?*/
6615: for(j=ij+1; j<= cptcovt; j++){
6616: Tvaraff[j]=0;
6617: Tmodelind[j]=0;
6618: }
6619: for(j=ntveff+1; j<= cptcovt; j++){
6620: TmodelInvind[j]=0;
6621: }
6622: /* To be sorted */
6623: ;
6624: }
1.126 brouard 6625:
1.145 brouard 6626:
1.126 brouard 6627: /*********** Health Expectancies ****************/
6628:
1.235 brouard 6629: 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 6630:
6631: {
6632: /* Health expectancies, no variances */
1.329 brouard 6633: /* cij is the combination in the list of combination of dummy covariates */
6634: /* strstart is a string of time at start of computing */
1.164 brouard 6635: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 6636: int nhstepma, nstepma; /* Decreasing with age */
6637: double age, agelim, hf;
6638: double ***p3mat;
6639: double eip;
6640:
1.238 brouard 6641: /* pstamp(ficreseij); */
1.126 brouard 6642: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
6643: fprintf(ficreseij,"# Age");
6644: for(i=1; i<=nlstate;i++){
6645: for(j=1; j<=nlstate;j++){
6646: fprintf(ficreseij," e%1d%1d ",i,j);
6647: }
6648: fprintf(ficreseij," e%1d. ",i);
6649: }
6650: fprintf(ficreseij,"\n");
6651:
6652:
6653: if(estepm < stepm){
6654: printf ("Problem %d lower than %d\n",estepm, stepm);
6655: }
6656: else hstepm=estepm;
6657: /* We compute the life expectancy from trapezoids spaced every estepm months
6658: * This is mainly to measure the difference between two models: for example
6659: * if stepm=24 months pijx are given only every 2 years and by summing them
6660: * we are calculating an estimate of the Life Expectancy assuming a linear
6661: * progression in between and thus overestimating or underestimating according
6662: * to the curvature of the survival function. If, for the same date, we
6663: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6664: * to compare the new estimate of Life expectancy with the same linear
6665: * hypothesis. A more precise result, taking into account a more precise
6666: * curvature will be obtained if estepm is as small as stepm. */
6667:
6668: /* For example we decided to compute the life expectancy with the smallest unit */
6669: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6670: nhstepm is the number of hstepm from age to agelim
6671: nstepm is the number of stepm from age to agelin.
1.270 brouard 6672: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 6673: and note for a fixed period like estepm months */
6674: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6675: survival function given by stepm (the optimization length). Unfortunately it
6676: means that if the survival funtion is printed only each two years of age and if
6677: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6678: results. So we changed our mind and took the option of the best precision.
6679: */
6680: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6681:
6682: agelim=AGESUP;
6683: /* If stepm=6 months */
6684: /* Computed by stepm unit matrices, product of hstepm matrices, stored
6685: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
6686:
6687: /* nhstepm age range expressed in number of stepm */
6688: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6689: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6690: /* if (stepm >= YEARM) hstepm=1;*/
6691: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6692: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6693:
6694: for (age=bage; age<=fage; age ++){
6695: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6696: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6697: /* if (stepm >= YEARM) hstepm=1;*/
6698: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
6699:
6700: /* If stepm=6 months */
6701: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6702: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
1.330 brouard 6703: /* 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 6704: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 6705:
6706: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6707:
6708: printf("%d|",(int)age);fflush(stdout);
6709: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6710:
6711: /* Computing expectancies */
6712: for(i=1; i<=nlstate;i++)
6713: for(j=1; j<=nlstate;j++)
6714: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6715: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
6716:
6717: /* 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]);*/
6718:
6719: }
6720:
6721: fprintf(ficreseij,"%3.0f",age );
6722: for(i=1; i<=nlstate;i++){
6723: eip=0;
6724: for(j=1; j<=nlstate;j++){
6725: eip +=eij[i][j][(int)age];
6726: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
6727: }
6728: fprintf(ficreseij,"%9.4f", eip );
6729: }
6730: fprintf(ficreseij,"\n");
6731:
6732: }
6733: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6734: printf("\n");
6735: fprintf(ficlog,"\n");
6736:
6737: }
6738:
1.235 brouard 6739: 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 6740:
6741: {
6742: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 6743: to initial status i, ei. .
1.126 brouard 6744: */
1.336 brouard 6745: /* Very time consuming function, but already optimized with precov */
1.126 brouard 6746: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
6747: int nhstepma, nstepma; /* Decreasing with age */
6748: double age, agelim, hf;
6749: double ***p3matp, ***p3matm, ***varhe;
6750: double **dnewm,**doldm;
6751: double *xp, *xm;
6752: double **gp, **gm;
6753: double ***gradg, ***trgradg;
6754: int theta;
6755:
6756: double eip, vip;
6757:
6758: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
6759: xp=vector(1,npar);
6760: xm=vector(1,npar);
6761: dnewm=matrix(1,nlstate*nlstate,1,npar);
6762: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
6763:
6764: pstamp(ficresstdeij);
6765: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
6766: fprintf(ficresstdeij,"# Age");
6767: for(i=1; i<=nlstate;i++){
6768: for(j=1; j<=nlstate;j++)
6769: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
6770: fprintf(ficresstdeij," e%1d. ",i);
6771: }
6772: fprintf(ficresstdeij,"\n");
6773:
6774: pstamp(ficrescveij);
6775: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
6776: fprintf(ficrescveij,"# Age");
6777: for(i=1; i<=nlstate;i++)
6778: for(j=1; j<=nlstate;j++){
6779: cptj= (j-1)*nlstate+i;
6780: for(i2=1; i2<=nlstate;i2++)
6781: for(j2=1; j2<=nlstate;j2++){
6782: cptj2= (j2-1)*nlstate+i2;
6783: if(cptj2 <= cptj)
6784: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
6785: }
6786: }
6787: fprintf(ficrescveij,"\n");
6788:
6789: if(estepm < stepm){
6790: printf ("Problem %d lower than %d\n",estepm, stepm);
6791: }
6792: else hstepm=estepm;
6793: /* We compute the life expectancy from trapezoids spaced every estepm months
6794: * This is mainly to measure the difference between two models: for example
6795: * if stepm=24 months pijx are given only every 2 years and by summing them
6796: * we are calculating an estimate of the Life Expectancy assuming a linear
6797: * progression in between and thus overestimating or underestimating according
6798: * to the curvature of the survival function. If, for the same date, we
6799: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6800: * to compare the new estimate of Life expectancy with the same linear
6801: * hypothesis. A more precise result, taking into account a more precise
6802: * curvature will be obtained if estepm is as small as stepm. */
6803:
6804: /* For example we decided to compute the life expectancy with the smallest unit */
6805: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6806: nhstepm is the number of hstepm from age to agelim
6807: nstepm is the number of stepm from age to agelin.
6808: Look at hpijx to understand the reason of that which relies in memory size
6809: and note for a fixed period like estepm months */
6810: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6811: survival function given by stepm (the optimization length). Unfortunately it
6812: means that if the survival funtion is printed only each two years of age and if
6813: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6814: results. So we changed our mind and took the option of the best precision.
6815: */
6816: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6817:
6818: /* If stepm=6 months */
6819: /* nhstepm age range expressed in number of stepm */
6820: agelim=AGESUP;
6821: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
6822: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6823: /* if (stepm >= YEARM) hstepm=1;*/
6824: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6825:
6826: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6827: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6828: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
6829: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
6830: gp=matrix(0,nhstepm,1,nlstate*nlstate);
6831: gm=matrix(0,nhstepm,1,nlstate*nlstate);
6832:
6833: for (age=bage; age<=fage; age ++){
6834: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6835: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6836: /* if (stepm >= YEARM) hstepm=1;*/
6837: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 6838:
1.126 brouard 6839: /* If stepm=6 months */
6840: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6841: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
6842:
6843: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 6844:
1.126 brouard 6845: /* Computing Variances of health expectancies */
6846: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
6847: decrease memory allocation */
6848: for(theta=1; theta <=npar; theta++){
6849: for(i=1; i<=npar; i++){
1.222 brouard 6850: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6851: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 6852: }
1.235 brouard 6853: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
6854: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 6855:
1.126 brouard 6856: for(j=1; j<= nlstate; j++){
1.222 brouard 6857: for(i=1; i<=nlstate; i++){
6858: for(h=0; h<=nhstepm-1; h++){
6859: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
6860: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
6861: }
6862: }
1.126 brouard 6863: }
1.218 brouard 6864:
1.126 brouard 6865: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 6866: for(h=0; h<=nhstepm-1; h++){
6867: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
6868: }
1.126 brouard 6869: }/* End theta */
6870:
6871:
6872: for(h=0; h<=nhstepm-1; h++)
6873: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 6874: for(theta=1; theta <=npar; theta++)
6875: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 6876:
1.218 brouard 6877:
1.222 brouard 6878: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 6879: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 6880: varhe[ij][ji][(int)age] =0.;
1.218 brouard 6881:
1.222 brouard 6882: printf("%d|",(int)age);fflush(stdout);
6883: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6884: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 6885: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 6886: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
6887: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
6888: for(ij=1;ij<=nlstate*nlstate;ij++)
6889: for(ji=1;ji<=nlstate*nlstate;ji++)
6890: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 6891: }
6892: }
1.320 brouard 6893: /* if((int)age ==50){ */
6894: /* printf(" age=%d cij=%d nres=%d varhe[%d][%d]=%f ",(int)age, cij, nres, 1,2,varhe[1][2]); */
6895: /* } */
1.126 brouard 6896: /* Computing expectancies */
1.235 brouard 6897: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 6898: for(i=1; i<=nlstate;i++)
6899: for(j=1; j<=nlstate;j++)
1.222 brouard 6900: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6901: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 6902:
1.222 brouard 6903: /* 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 6904:
1.222 brouard 6905: }
1.269 brouard 6906:
6907: /* Standard deviation of expectancies ij */
1.126 brouard 6908: fprintf(ficresstdeij,"%3.0f",age );
6909: for(i=1; i<=nlstate;i++){
6910: eip=0.;
6911: vip=0.;
6912: for(j=1; j<=nlstate;j++){
1.222 brouard 6913: eip += eij[i][j][(int)age];
6914: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
6915: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
6916: 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 6917: }
6918: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
6919: }
6920: fprintf(ficresstdeij,"\n");
1.218 brouard 6921:
1.269 brouard 6922: /* Variance of expectancies ij */
1.126 brouard 6923: fprintf(ficrescveij,"%3.0f",age );
6924: for(i=1; i<=nlstate;i++)
6925: for(j=1; j<=nlstate;j++){
1.222 brouard 6926: cptj= (j-1)*nlstate+i;
6927: for(i2=1; i2<=nlstate;i2++)
6928: for(j2=1; j2<=nlstate;j2++){
6929: cptj2= (j2-1)*nlstate+i2;
6930: if(cptj2 <= cptj)
6931: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
6932: }
1.126 brouard 6933: }
6934: fprintf(ficrescveij,"\n");
1.218 brouard 6935:
1.126 brouard 6936: }
6937: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
6938: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
6939: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
6940: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
6941: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6942: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6943: printf("\n");
6944: fprintf(ficlog,"\n");
1.218 brouard 6945:
1.126 brouard 6946: free_vector(xm,1,npar);
6947: free_vector(xp,1,npar);
6948: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
6949: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
6950: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
6951: }
1.218 brouard 6952:
1.126 brouard 6953: /************ Variance ******************/
1.235 brouard 6954: 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 6955: {
1.279 brouard 6956: /** Variance of health expectancies
6957: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
6958: * double **newm;
6959: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
6960: */
1.218 brouard 6961:
6962: /* int movingaverage(); */
6963: double **dnewm,**doldm;
6964: double **dnewmp,**doldmp;
6965: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 6966: int first=0;
1.218 brouard 6967: int k;
6968: double *xp;
1.279 brouard 6969: double **gp, **gm; /**< for var eij */
6970: double ***gradg, ***trgradg; /**< for var eij */
6971: double **gradgp, **trgradgp; /**< for var p point j */
6972: double *gpp, *gmp; /**< for var p point j */
6973: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 6974: double ***p3mat;
6975: double age,agelim, hf;
6976: /* double ***mobaverage; */
6977: int theta;
6978: char digit[4];
6979: char digitp[25];
6980:
6981: char fileresprobmorprev[FILENAMELENGTH];
6982:
6983: if(popbased==1){
6984: if(mobilav!=0)
6985: strcpy(digitp,"-POPULBASED-MOBILAV_");
6986: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
6987: }
6988: else
6989: strcpy(digitp,"-STABLBASED_");
1.126 brouard 6990:
1.218 brouard 6991: /* if (mobilav!=0) { */
6992: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6993: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
6994: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
6995: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
6996: /* } */
6997: /* } */
6998:
6999: strcpy(fileresprobmorprev,"PRMORPREV-");
7000: sprintf(digit,"%-d",ij);
7001: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
7002: strcat(fileresprobmorprev,digit); /* Tvar to be done */
7003: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
7004: strcat(fileresprobmorprev,fileresu);
7005: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
7006: printf("Problem with resultfile: %s\n", fileresprobmorprev);
7007: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
7008: }
7009: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
7010: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
7011: pstamp(ficresprobmorprev);
7012: 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 7013: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
1.337 brouard 7014:
7015: /* We use TinvDoQresult[nres][resultmodel[nres][j] we sort according to the equation model and the resultline: it is a choice */
7016: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ /\* To be done*\/ */
7017: /* fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
7018: /* } */
7019: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */ /* To be done*/
1.344 brouard 7020: /* fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); */
1.337 brouard 7021: fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 7022: }
1.337 brouard 7023: /* for(j=1;j<=cptcoveff;j++) */
7024: /* fprintf(ficresprobmorprev," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,TnsdVar[Tvaraff[j]])]); */
1.238 brouard 7025: fprintf(ficresprobmorprev,"\n");
7026:
1.218 brouard 7027: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
7028: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
7029: fprintf(ficresprobmorprev," p.%-d SE",j);
7030: for(i=1; i<=nlstate;i++)
7031: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
7032: }
7033: fprintf(ficresprobmorprev,"\n");
7034:
7035: fprintf(ficgp,"\n# Routine varevsij");
7036: fprintf(ficgp,"\nunset title \n");
7037: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
7038: 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");
7039: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 7040:
1.218 brouard 7041: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7042: pstamp(ficresvij);
7043: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
7044: if(popbased==1)
7045: 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);
7046: else
7047: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
7048: fprintf(ficresvij,"# Age");
7049: for(i=1; i<=nlstate;i++)
7050: for(j=1; j<=nlstate;j++)
7051: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
7052: fprintf(ficresvij,"\n");
7053:
7054: xp=vector(1,npar);
7055: dnewm=matrix(1,nlstate,1,npar);
7056: doldm=matrix(1,nlstate,1,nlstate);
7057: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
7058: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7059:
7060: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
7061: gpp=vector(nlstate+1,nlstate+ndeath);
7062: gmp=vector(nlstate+1,nlstate+ndeath);
7063: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 7064:
1.218 brouard 7065: if(estepm < stepm){
7066: printf ("Problem %d lower than %d\n",estepm, stepm);
7067: }
7068: else hstepm=estepm;
7069: /* For example we decided to compute the life expectancy with the smallest unit */
7070: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
7071: nhstepm is the number of hstepm from age to agelim
7072: nstepm is the number of stepm from age to agelim.
7073: Look at function hpijx to understand why because of memory size limitations,
7074: we decided (b) to get a life expectancy respecting the most precise curvature of the
7075: survival function given by stepm (the optimization length). Unfortunately it
7076: means that if the survival funtion is printed every two years of age and if
7077: you sum them up and add 1 year (area under the trapezoids) you won't get the same
7078: results. So we changed our mind and took the option of the best precision.
7079: */
7080: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
7081: agelim = AGESUP;
7082: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
7083: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7084: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
7085: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
7086: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
7087: gp=matrix(0,nhstepm,1,nlstate);
7088: gm=matrix(0,nhstepm,1,nlstate);
7089:
7090:
7091: for(theta=1; theta <=npar; theta++){
7092: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
7093: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7094: }
1.279 brouard 7095: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
7096: * returns into prlim .
1.288 brouard 7097: */
1.242 brouard 7098: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 7099:
7100: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 7101: if (popbased==1) {
7102: if(mobilav ==0){
7103: for(i=1; i<=nlstate;i++)
7104: prlim[i][i]=probs[(int)age][i][ij];
7105: }else{ /* mobilav */
7106: for(i=1; i<=nlstate;i++)
7107: prlim[i][i]=mobaverage[(int)age][i][ij];
7108: }
7109: }
1.295 brouard 7110: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h.
1.279 brouard 7111: */
7112: 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 7113: /**< 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 7114: * at horizon h in state j including mortality.
7115: */
1.218 brouard 7116: for(j=1; j<= nlstate; j++){
7117: for(h=0; h<=nhstepm; h++){
7118: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
7119: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
7120: }
7121: }
1.279 brouard 7122: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 7123: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 7124: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 7125: */
7126: for(j=nlstate+1;j<=nlstate+ndeath;j++){
7127: for(i=1,gpp[j]=0.; i<= nlstate; i++)
7128: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 7129: }
7130:
7131: /* Again with minus shift */
1.218 brouard 7132:
7133: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
7134: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 7135:
1.242 brouard 7136: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 7137:
7138: if (popbased==1) {
7139: if(mobilav ==0){
7140: for(i=1; i<=nlstate;i++)
7141: prlim[i][i]=probs[(int)age][i][ij];
7142: }else{ /* mobilav */
7143: for(i=1; i<=nlstate;i++)
7144: prlim[i][i]=mobaverage[(int)age][i][ij];
7145: }
7146: }
7147:
1.235 brouard 7148: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 7149:
7150: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
7151: for(h=0; h<=nhstepm; h++){
7152: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
7153: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
7154: }
7155: }
7156: /* This for computing probability of death (h=1 means
7157: computed over hstepm matrices product = hstepm*stepm months)
7158: as a weighted average of prlim.
7159: */
7160: for(j=nlstate+1;j<=nlstate+ndeath;j++){
7161: for(i=1,gmp[j]=0.; i<= nlstate; i++)
7162: gmp[j] += prlim[i][i]*p3mat[i][j][1];
7163: }
1.279 brouard 7164: /* end shifting computations */
7165:
7166: /**< Computing gradient matrix at horizon h
7167: */
1.218 brouard 7168: for(j=1; j<= nlstate; j++) /* vareij */
7169: for(h=0; h<=nhstepm; h++){
7170: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
7171: }
1.279 brouard 7172: /**< Gradient of overall mortality p.3 (or p.j)
7173: */
7174: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 7175: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
7176: }
7177:
7178: } /* End theta */
1.279 brouard 7179:
7180: /* We got the gradient matrix for each theta and state j */
1.218 brouard 7181: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
7182:
7183: for(h=0; h<=nhstepm; h++) /* veij */
7184: for(j=1; j<=nlstate;j++)
7185: for(theta=1; theta <=npar; theta++)
7186: trgradg[h][j][theta]=gradg[h][theta][j];
7187:
7188: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
7189: for(theta=1; theta <=npar; theta++)
7190: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 7191: /**< as well as its transposed matrix
7192: */
1.218 brouard 7193:
7194: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
7195: for(i=1;i<=nlstate;i++)
7196: for(j=1;j<=nlstate;j++)
7197: vareij[i][j][(int)age] =0.;
1.279 brouard 7198:
7199: /* Computing trgradg by matcov by gradg at age and summing over h
7200: * and k (nhstepm) formula 15 of article
7201: * Lievre-Brouard-Heathcote
7202: */
7203:
1.218 brouard 7204: for(h=0;h<=nhstepm;h++){
7205: for(k=0;k<=nhstepm;k++){
7206: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
7207: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
7208: for(i=1;i<=nlstate;i++)
7209: for(j=1;j<=nlstate;j++)
7210: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
7211: }
7212: }
7213:
1.279 brouard 7214: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
7215: * p.j overall mortality formula 49 but computed directly because
7216: * we compute the grad (wix pijx) instead of grad (pijx),even if
7217: * wix is independent of theta.
7218: */
1.218 brouard 7219: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
7220: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
7221: for(j=nlstate+1;j<=nlstate+ndeath;j++)
7222: for(i=nlstate+1;i<=nlstate+ndeath;i++)
7223: varppt[j][i]=doldmp[j][i];
7224: /* end ppptj */
7225: /* x centered again */
7226:
1.242 brouard 7227: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 7228:
7229: if (popbased==1) {
7230: if(mobilav ==0){
7231: for(i=1; i<=nlstate;i++)
7232: prlim[i][i]=probs[(int)age][i][ij];
7233: }else{ /* mobilav */
7234: for(i=1; i<=nlstate;i++)
7235: prlim[i][i]=mobaverage[(int)age][i][ij];
7236: }
7237: }
7238:
7239: /* This for computing probability of death (h=1 means
7240: computed over hstepm (estepm) matrices product = hstepm*stepm months)
7241: as a weighted average of prlim.
7242: */
1.235 brouard 7243: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 7244: for(j=nlstate+1;j<=nlstate+ndeath;j++){
7245: for(i=1,gmp[j]=0.;i<= nlstate; i++)
7246: gmp[j] += prlim[i][i]*p3mat[i][j][1];
7247: }
7248: /* end probability of death */
7249:
7250: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
7251: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
7252: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
7253: for(i=1; i<=nlstate;i++){
7254: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
7255: }
7256: }
7257: fprintf(ficresprobmorprev,"\n");
7258:
7259: fprintf(ficresvij,"%.0f ",age );
7260: for(i=1; i<=nlstate;i++)
7261: for(j=1; j<=nlstate;j++){
7262: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
7263: }
7264: fprintf(ficresvij,"\n");
7265: free_matrix(gp,0,nhstepm,1,nlstate);
7266: free_matrix(gm,0,nhstepm,1,nlstate);
7267: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
7268: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
7269: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
7270: } /* End age */
7271: free_vector(gpp,nlstate+1,nlstate+ndeath);
7272: free_vector(gmp,nlstate+1,nlstate+ndeath);
7273: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
7274: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
7275: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
7276: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
7277: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
7278: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
7279: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
7280: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
7281: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
7282: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
7283: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
7284: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
7285: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
7286: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
7287: 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);
7288: /* 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 7289: */
1.218 brouard 7290: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
7291: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 7292:
1.218 brouard 7293: free_vector(xp,1,npar);
7294: free_matrix(doldm,1,nlstate,1,nlstate);
7295: free_matrix(dnewm,1,nlstate,1,npar);
7296: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7297: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
7298: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7299: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
7300: fclose(ficresprobmorprev);
7301: fflush(ficgp);
7302: fflush(fichtm);
7303: } /* end varevsij */
1.126 brouard 7304:
7305: /************ Variance of prevlim ******************/
1.269 brouard 7306: 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 7307: {
1.205 brouard 7308: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 7309: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 7310:
1.268 brouard 7311: double **dnewmpar,**doldm;
1.126 brouard 7312: int i, j, nhstepm, hstepm;
7313: double *xp;
7314: double *gp, *gm;
7315: double **gradg, **trgradg;
1.208 brouard 7316: double **mgm, **mgp;
1.126 brouard 7317: double age,agelim;
7318: int theta;
7319:
7320: pstamp(ficresvpl);
1.288 brouard 7321: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 7322: fprintf(ficresvpl,"# Age ");
7323: if(nresult >=1)
7324: fprintf(ficresvpl," Result# ");
1.126 brouard 7325: for(i=1; i<=nlstate;i++)
7326: fprintf(ficresvpl," %1d-%1d",i,i);
7327: fprintf(ficresvpl,"\n");
7328:
7329: xp=vector(1,npar);
1.268 brouard 7330: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 7331: doldm=matrix(1,nlstate,1,nlstate);
7332:
7333: hstepm=1*YEARM; /* Every year of age */
7334: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
7335: agelim = AGESUP;
7336: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
7337: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7338: if (stepm >= YEARM) hstepm=1;
7339: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
7340: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 7341: mgp=matrix(1,npar,1,nlstate);
7342: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 7343: gp=vector(1,nlstate);
7344: gm=vector(1,nlstate);
7345:
7346: for(theta=1; theta <=npar; theta++){
7347: for(i=1; i<=npar; i++){ /* Computes gradient */
7348: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7349: }
1.288 brouard 7350: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
7351: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
7352: /* else */
7353: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 7354: for(i=1;i<=nlstate;i++){
1.126 brouard 7355: gp[i] = prlim[i][i];
1.208 brouard 7356: mgp[theta][i] = prlim[i][i];
7357: }
1.126 brouard 7358: for(i=1; i<=npar; i++) /* Computes gradient */
7359: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 7360: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
7361: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
7362: /* else */
7363: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 7364: for(i=1;i<=nlstate;i++){
1.126 brouard 7365: gm[i] = prlim[i][i];
1.208 brouard 7366: mgm[theta][i] = prlim[i][i];
7367: }
1.126 brouard 7368: for(i=1;i<=nlstate;i++)
7369: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 7370: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 7371: } /* End theta */
7372:
7373: trgradg =matrix(1,nlstate,1,npar);
7374:
7375: for(j=1; j<=nlstate;j++)
7376: for(theta=1; theta <=npar; theta++)
7377: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 7378: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7379: /* printf("\nmgm mgp %d ",(int)age); */
7380: /* for(j=1; j<=nlstate;j++){ */
7381: /* printf(" %d ",j); */
7382: /* for(theta=1; theta <=npar; theta++) */
7383: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
7384: /* printf("\n "); */
7385: /* } */
7386: /* } */
7387: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7388: /* printf("\n gradg %d ",(int)age); */
7389: /* for(j=1; j<=nlstate;j++){ */
7390: /* printf("%d ",j); */
7391: /* for(theta=1; theta <=npar; theta++) */
7392: /* printf("%d %lf ",theta,gradg[theta][j]); */
7393: /* printf("\n "); */
7394: /* } */
7395: /* } */
1.126 brouard 7396:
7397: for(i=1;i<=nlstate;i++)
7398: varpl[i][(int)age] =0.;
1.209 brouard 7399: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 7400: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7401: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 7402: }else{
1.268 brouard 7403: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7404: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 7405: }
1.126 brouard 7406: for(i=1;i<=nlstate;i++)
7407: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
7408:
7409: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 7410: if(nresult >=1)
7411: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 7412: for(i=1; i<=nlstate;i++){
1.126 brouard 7413: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 7414: /* for(j=1;j<=nlstate;j++) */
7415: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
7416: }
1.126 brouard 7417: fprintf(ficresvpl,"\n");
7418: free_vector(gp,1,nlstate);
7419: free_vector(gm,1,nlstate);
1.208 brouard 7420: free_matrix(mgm,1,npar,1,nlstate);
7421: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 7422: free_matrix(gradg,1,npar,1,nlstate);
7423: free_matrix(trgradg,1,nlstate,1,npar);
7424: } /* End age */
7425:
7426: free_vector(xp,1,npar);
7427: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 7428: free_matrix(dnewmpar,1,nlstate,1,nlstate);
7429:
7430: }
7431:
7432:
7433: /************ Variance of backprevalence limit ******************/
1.269 brouard 7434: 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 7435: {
7436: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
7437: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
7438:
7439: double **dnewmpar,**doldm;
7440: int i, j, nhstepm, hstepm;
7441: double *xp;
7442: double *gp, *gm;
7443: double **gradg, **trgradg;
7444: double **mgm, **mgp;
7445: double age,agelim;
7446: int theta;
7447:
7448: pstamp(ficresvbl);
7449: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
7450: fprintf(ficresvbl,"# Age ");
7451: if(nresult >=1)
7452: fprintf(ficresvbl," Result# ");
7453: for(i=1; i<=nlstate;i++)
7454: fprintf(ficresvbl," %1d-%1d",i,i);
7455: fprintf(ficresvbl,"\n");
7456:
7457: xp=vector(1,npar);
7458: dnewmpar=matrix(1,nlstate,1,npar);
7459: doldm=matrix(1,nlstate,1,nlstate);
7460:
7461: hstepm=1*YEARM; /* Every year of age */
7462: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
7463: agelim = AGEINF;
7464: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
7465: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7466: if (stepm >= YEARM) hstepm=1;
7467: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
7468: gradg=matrix(1,npar,1,nlstate);
7469: mgp=matrix(1,npar,1,nlstate);
7470: mgm=matrix(1,npar,1,nlstate);
7471: gp=vector(1,nlstate);
7472: gm=vector(1,nlstate);
7473:
7474: for(theta=1; theta <=npar; theta++){
7475: for(i=1; i<=npar; i++){ /* Computes gradient */
7476: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7477: }
7478: if(mobilavproj > 0 )
7479: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7480: else
7481: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7482: for(i=1;i<=nlstate;i++){
7483: gp[i] = bprlim[i][i];
7484: mgp[theta][i] = bprlim[i][i];
7485: }
7486: for(i=1; i<=npar; i++) /* Computes gradient */
7487: xp[i] = x[i] - (i==theta ?delti[theta]:0);
7488: if(mobilavproj > 0 )
7489: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7490: else
7491: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7492: for(i=1;i<=nlstate;i++){
7493: gm[i] = bprlim[i][i];
7494: mgm[theta][i] = bprlim[i][i];
7495: }
7496: for(i=1;i<=nlstate;i++)
7497: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
7498: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
7499: } /* End theta */
7500:
7501: trgradg =matrix(1,nlstate,1,npar);
7502:
7503: for(j=1; j<=nlstate;j++)
7504: for(theta=1; theta <=npar; theta++)
7505: trgradg[j][theta]=gradg[theta][j];
7506: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7507: /* printf("\nmgm mgp %d ",(int)age); */
7508: /* for(j=1; j<=nlstate;j++){ */
7509: /* printf(" %d ",j); */
7510: /* for(theta=1; theta <=npar; theta++) */
7511: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
7512: /* printf("\n "); */
7513: /* } */
7514: /* } */
7515: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7516: /* printf("\n gradg %d ",(int)age); */
7517: /* for(j=1; j<=nlstate;j++){ */
7518: /* printf("%d ",j); */
7519: /* for(theta=1; theta <=npar; theta++) */
7520: /* printf("%d %lf ",theta,gradg[theta][j]); */
7521: /* printf("\n "); */
7522: /* } */
7523: /* } */
7524:
7525: for(i=1;i<=nlstate;i++)
7526: varbpl[i][(int)age] =0.;
7527: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
7528: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7529: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
7530: }else{
7531: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7532: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
7533: }
7534: for(i=1;i<=nlstate;i++)
7535: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
7536:
7537: fprintf(ficresvbl,"%.0f ",age );
7538: if(nresult >=1)
7539: fprintf(ficresvbl,"%d ",nres );
7540: for(i=1; i<=nlstate;i++)
7541: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
7542: fprintf(ficresvbl,"\n");
7543: free_vector(gp,1,nlstate);
7544: free_vector(gm,1,nlstate);
7545: free_matrix(mgm,1,npar,1,nlstate);
7546: free_matrix(mgp,1,npar,1,nlstate);
7547: free_matrix(gradg,1,npar,1,nlstate);
7548: free_matrix(trgradg,1,nlstate,1,npar);
7549: } /* End age */
7550:
7551: free_vector(xp,1,npar);
7552: free_matrix(doldm,1,nlstate,1,npar);
7553: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 7554:
7555: }
7556:
7557: /************ Variance of one-step probabilities ******************/
7558: 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 7559: {
7560: int i, j=0, k1, l1, tj;
7561: int k2, l2, j1, z1;
7562: int k=0, l;
7563: int first=1, first1, first2;
1.326 brouard 7564: int nres=0; /* New */
1.222 brouard 7565: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
7566: double **dnewm,**doldm;
7567: double *xp;
7568: double *gp, *gm;
7569: double **gradg, **trgradg;
7570: double **mu;
7571: double age, cov[NCOVMAX+1];
7572: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
7573: int theta;
7574: char fileresprob[FILENAMELENGTH];
7575: char fileresprobcov[FILENAMELENGTH];
7576: char fileresprobcor[FILENAMELENGTH];
7577: double ***varpij;
7578:
7579: strcpy(fileresprob,"PROB_");
7580: strcat(fileresprob,fileres);
7581: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
7582: printf("Problem with resultfile: %s\n", fileresprob);
7583: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
7584: }
7585: strcpy(fileresprobcov,"PROBCOV_");
7586: strcat(fileresprobcov,fileresu);
7587: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
7588: printf("Problem with resultfile: %s\n", fileresprobcov);
7589: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
7590: }
7591: strcpy(fileresprobcor,"PROBCOR_");
7592: strcat(fileresprobcor,fileresu);
7593: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
7594: printf("Problem with resultfile: %s\n", fileresprobcor);
7595: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
7596: }
7597: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7598: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7599: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7600: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7601: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7602: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7603: pstamp(ficresprob);
7604: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
7605: fprintf(ficresprob,"# Age");
7606: pstamp(ficresprobcov);
7607: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
7608: fprintf(ficresprobcov,"# Age");
7609: pstamp(ficresprobcor);
7610: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
7611: fprintf(ficresprobcor,"# Age");
1.126 brouard 7612:
7613:
1.222 brouard 7614: for(i=1; i<=nlstate;i++)
7615: for(j=1; j<=(nlstate+ndeath);j++){
7616: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
7617: fprintf(ficresprobcov," p%1d-%1d ",i,j);
7618: fprintf(ficresprobcor," p%1d-%1d ",i,j);
7619: }
7620: /* fprintf(ficresprob,"\n");
7621: fprintf(ficresprobcov,"\n");
7622: fprintf(ficresprobcor,"\n");
7623: */
7624: xp=vector(1,npar);
7625: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7626: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
7627: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
7628: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
7629: first=1;
7630: fprintf(ficgp,"\n# Routine varprob");
7631: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
7632: fprintf(fichtm,"\n");
7633:
1.288 brouard 7634: 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 7635: 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);
7636: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 7637: and drawn. It helps understanding how is the covariance between two incidences.\
7638: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 7639: 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 7640: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
7641: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
7642: standard deviations wide on each axis. <br>\
7643: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
7644: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
7645: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
7646:
1.222 brouard 7647: cov[1]=1;
7648: /* tj=cptcoveff; */
1.225 brouard 7649: tj = (int) pow(2,cptcoveff);
1.222 brouard 7650: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
7651: j1=0;
1.332 brouard 7652:
7653: for(nres=1;nres <=nresult; nres++){ /* For each resultline */
7654: for(j1=1; j1<=tj;j1++){ /* For any combination of dummy covariates, fixed and varying */
1.342 brouard 7655: /* 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 7656: if(tj != 1 && TKresult[nres]!= j1)
7657: continue;
7658:
7659: /* for(j1=1; j1<=tj;j1++){ /\* For each valid combination of covariates or only once*\/ */
7660: /* for(nres=1;nres <=1; nres++){ /\* For each resultline *\/ */
7661: /* /\* for(nres=1;nres <=nresult; nres++){ /\\* For each resultline *\\/ *\/ */
1.222 brouard 7662: if (cptcovn>0) {
1.334 brouard 7663: fprintf(ficresprob, "\n#********** Variable ");
7664: fprintf(ficresprobcov, "\n#********** Variable ");
7665: fprintf(ficgp, "\n#********** Variable ");
7666: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
7667: fprintf(ficresprobcor, "\n#********** Variable ");
7668:
7669: /* Including quantitative variables of the resultline to be done */
7670: for (z1=1; z1<=cptcovs; z1++){ /* Loop on each variable of this resultline */
1.343 brouard 7671: /* printf("Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model); */
1.338 brouard 7672: fprintf(ficlog,"Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model);
7673: /* 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 7674: if(Dummy[modelresult[nres][z1]]==0){/* Dummy variable of the variable in position modelresult in the model corresponding to z1 in resultline */
7675: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed referenced to model equation */
7676: 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 */
7677: 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 */
7678: 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 */
7679: 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 */
7680: 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 */
7681: fprintf(ficresprob,"fixed ");
7682: fprintf(ficresprobcov,"fixed ");
7683: fprintf(ficgp,"fixed ");
7684: fprintf(fichtmcov,"fixed ");
7685: fprintf(ficresprobcor,"fixed ");
7686: }else{
7687: fprintf(ficresprob,"varyi ");
7688: fprintf(ficresprobcov,"varyi ");
7689: fprintf(ficgp,"varyi ");
7690: fprintf(fichtmcov,"varyi ");
7691: fprintf(ficresprobcor,"varyi ");
7692: }
7693: }else if(Dummy[modelresult[nres][z1]]==1){ /* Quanti variable */
7694: /* For each selected (single) quantitative value */
1.337 brouard 7695: fprintf(ficresprob," V%d=%lg ",Tvqresult[nres][z1],Tqresult[nres][z1]);
1.334 brouard 7696: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed */
7697: fprintf(ficresprob,"fixed ");
7698: fprintf(ficresprobcov,"fixed ");
7699: fprintf(ficgp,"fixed ");
7700: fprintf(fichtmcov,"fixed ");
7701: fprintf(ficresprobcor,"fixed ");
7702: }else{
7703: fprintf(ficresprob,"varyi ");
7704: fprintf(ficresprobcov,"varyi ");
7705: fprintf(ficgp,"varyi ");
7706: fprintf(fichtmcov,"varyi ");
7707: fprintf(ficresprobcor,"varyi ");
7708: }
7709: }else{
7710: 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 */
7711: 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 */
7712: exit(1);
7713: }
7714: } /* End loop on variable of this resultline */
7715: /* for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]); */
1.222 brouard 7716: fprintf(ficresprob, "**********\n#\n");
7717: fprintf(ficresprobcov, "**********\n#\n");
7718: fprintf(ficgp, "**********\n#\n");
7719: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
7720: fprintf(ficresprobcor, "**********\n#");
7721: if(invalidvarcomb[j1]){
7722: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
7723: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
7724: continue;
7725: }
7726: }
7727: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
7728: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7729: gp=vector(1,(nlstate)*(nlstate+ndeath));
7730: gm=vector(1,(nlstate)*(nlstate+ndeath));
1.334 brouard 7731: for (age=bage; age<=fage; age ++){ /* Fo each age we feed the model equation with covariates, using precov as in hpxij() ? */
1.222 brouard 7732: cov[2]=age;
7733: if(nagesqr==1)
7734: cov[3]= age*age;
1.334 brouard 7735: /* New code end of combination but for each resultline */
7736: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 ! brouard 7737: if(Typevar[k1]==1 || Typevar[k1] ==3){ /* A product with age */
1.334 brouard 7738: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.326 brouard 7739: }else{
1.334 brouard 7740: cov[2+nagesqr+k1]=precov[nres][k1];
1.326 brouard 7741: }
1.334 brouard 7742: }/* End of loop on model equation */
7743: /* Old code */
7744: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
7745: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)]; *\/ */
7746: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
7747: /* /\* Here comes the value of the covariate 'j1' after renumbering k with single dummy covariates *\/ */
7748: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(j1,TnsdVar[TvarsD[k]])]; */
7749: /* /\*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*\//\* j1 1 2 3 4 */
7750: /* * 1 1 1 1 1 */
7751: /* * 2 2 1 1 1 */
7752: /* * 3 1 2 1 1 */
7753: /* *\/ */
7754: /* /\* nbcode[1][1]=0 nbcode[1][2]=1;*\/ */
7755: /* } */
7756: /* /\* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
7757: /* /\* ) p nbcode[Tvar[Tage[k]]][(1 & (ij-1) >> (k-1))+1] *\/ */
7758: /* /\*for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; *\/ */
7759: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
7760: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
7761: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(j1,TnsdVar[Tvar[Tage[k]]])]*cov[2]; */
7762: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
7763: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
7764: /* 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]); */
7765: /* /\* cov[2+nagesqr+Tage[k]]=meanq[k]/idq[k]*cov[2];/\\* Using the mean of quantitative variable Tvar[Tage[k]] /\\* Tqresult[nres][k]; *\\/ *\/ */
7766: /* /\* exit(1); *\/ */
7767: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
7768: /* } */
7769: /* /\* cov[2+Tage[k]+nagesqr]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
7770: /* } */
7771: /* for (k=1; k<=cptcovprod;k++){/\* For product without age *\/ */
7772: /* if(Dummy[Tvard[k][1]]==0){ */
7773: /* if(Dummy[Tvard[k][2]]==0){ */
7774: /* 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]])]; */
7775: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
7776: /* }else{ /\* Should we use the mean of the quantitative variables? *\/ */
7777: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(j1,TnsdVar[Tvard[k][1]])] * Tqresult[nres][resultmodel[nres][k]]; */
7778: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
7779: /* } */
7780: /* }else{ */
7781: /* if(Dummy[Tvard[k][2]]==0){ */
7782: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(j1,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][TnsdVar[Tvard[k][1]]]; */
7783: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
7784: /* }else{ */
7785: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][TnsdVar[Tvard[k][1]]]* Tqinvresult[nres][TnsdVar[Tvard[k][2]]]; */
7786: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
7787: /* } */
7788: /* } */
7789: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
7790: /* } */
1.326 brouard 7791: /* For each age and combination of dummy covariates we slightly move the parameters of delti in order to get the gradient*/
1.222 brouard 7792: for(theta=1; theta <=npar; theta++){
7793: for(i=1; i<=npar; i++)
7794: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 7795:
1.222 brouard 7796: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 7797:
1.222 brouard 7798: k=0;
7799: for(i=1; i<= (nlstate); i++){
7800: for(j=1; j<=(nlstate+ndeath);j++){
7801: k=k+1;
7802: gp[k]=pmmij[i][j];
7803: }
7804: }
1.220 brouard 7805:
1.222 brouard 7806: for(i=1; i<=npar; i++)
7807: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 7808:
1.222 brouard 7809: pmij(pmmij,cov,ncovmodel,xp,nlstate);
7810: k=0;
7811: for(i=1; i<=(nlstate); i++){
7812: for(j=1; j<=(nlstate+ndeath);j++){
7813: k=k+1;
7814: gm[k]=pmmij[i][j];
7815: }
7816: }
1.220 brouard 7817:
1.222 brouard 7818: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
7819: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
7820: }
1.126 brouard 7821:
1.222 brouard 7822: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
7823: for(theta=1; theta <=npar; theta++)
7824: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 7825:
1.222 brouard 7826: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
7827: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 7828:
1.222 brouard 7829: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 7830:
1.222 brouard 7831: k=0;
7832: for(i=1; i<=(nlstate); i++){
7833: for(j=1; j<=(nlstate+ndeath);j++){
7834: k=k+1;
7835: mu[k][(int) age]=pmmij[i][j];
7836: }
7837: }
7838: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
7839: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
7840: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 7841:
1.222 brouard 7842: /*printf("\n%d ",(int)age);
7843: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7844: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7845: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7846: }*/
1.220 brouard 7847:
1.222 brouard 7848: fprintf(ficresprob,"\n%d ",(int)age);
7849: fprintf(ficresprobcov,"\n%d ",(int)age);
7850: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 7851:
1.222 brouard 7852: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
7853: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
7854: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7855: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
7856: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
7857: }
7858: i=0;
7859: for (k=1; k<=(nlstate);k++){
7860: for (l=1; l<=(nlstate+ndeath);l++){
7861: i++;
7862: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
7863: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
7864: for (j=1; j<=i;j++){
7865: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
7866: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
7867: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
7868: }
7869: }
7870: }/* end of loop for state */
7871: } /* end of loop for age */
7872: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
7873: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
7874: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7875: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7876:
7877: /* Confidence intervalle of pij */
7878: /*
7879: fprintf(ficgp,"\nunset parametric;unset label");
7880: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
7881: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
7882: 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);
7883: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
7884: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
7885: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
7886: */
7887:
7888: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
7889: first1=1;first2=2;
7890: for (k2=1; k2<=(nlstate);k2++){
7891: for (l2=1; l2<=(nlstate+ndeath);l2++){
7892: if(l2==k2) continue;
7893: j=(k2-1)*(nlstate+ndeath)+l2;
7894: for (k1=1; k1<=(nlstate);k1++){
7895: for (l1=1; l1<=(nlstate+ndeath);l1++){
7896: if(l1==k1) continue;
7897: i=(k1-1)*(nlstate+ndeath)+l1;
7898: if(i<=j) continue;
7899: for (age=bage; age<=fage; age ++){
7900: if ((int)age %5==0){
7901: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
7902: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
7903: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
7904: mu1=mu[i][(int) age]/stepm*YEARM ;
7905: mu2=mu[j][(int) age]/stepm*YEARM;
7906: c12=cv12/sqrt(v1*v2);
7907: /* Computing eigen value of matrix of covariance */
7908: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7909: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7910: if ((lc2 <0) || (lc1 <0) ){
7911: if(first2==1){
7912: first1=0;
7913: 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);
7914: }
7915: 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);
7916: /* lc1=fabs(lc1); */ /* If we want to have them positive */
7917: /* lc2=fabs(lc2); */
7918: }
1.220 brouard 7919:
1.222 brouard 7920: /* Eigen vectors */
1.280 brouard 7921: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
7922: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7923: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7924: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
7925: }else
7926: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 7927: /*v21=sqrt(1.-v11*v11); *//* error */
7928: v21=(lc1-v1)/cv12*v11;
7929: v12=-v21;
7930: v22=v11;
7931: tnalp=v21/v11;
7932: if(first1==1){
7933: first1=0;
7934: 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);
7935: }
7936: 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);
7937: /*printf(fignu*/
7938: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
7939: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
7940: if(first==1){
7941: first=0;
7942: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
7943: fprintf(ficgp,"\nset parametric;unset label");
7944: 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);
7945: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 7946: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 7947: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 7948: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 7949: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
7950: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7951: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7952: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
7953: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7954: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7955: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7956: 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 7957: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
7958: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 7959: }else{
7960: first=0;
7961: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
7962: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7963: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7964: 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 7965: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
7966: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 7967: }/* if first */
7968: } /* age mod 5 */
7969: } /* end loop age */
7970: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7971: first=1;
7972: } /*l12 */
7973: } /* k12 */
7974: } /*l1 */
7975: }/* k1 */
1.332 brouard 7976: } /* loop on combination of covariates j1 */
1.326 brouard 7977: } /* loop on nres */
1.222 brouard 7978: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
7979: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
7980: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
7981: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
7982: free_vector(xp,1,npar);
7983: fclose(ficresprob);
7984: fclose(ficresprobcov);
7985: fclose(ficresprobcor);
7986: fflush(ficgp);
7987: fflush(fichtmcov);
7988: }
1.126 brouard 7989:
7990:
7991: /******************* Printing html file ***********/
1.201 brouard 7992: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 7993: int lastpass, int stepm, int weightopt, char model[],\
7994: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.296 brouard 7995: int popforecast, int mobilav, int prevfcast, int mobilavproj, int prevbcast, int estepm , \
7996: double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \
7997: double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){
1.237 brouard 7998: int jj1, k1, i1, cpt, k4, nres;
1.319 brouard 7999: /* In fact some results are already printed in fichtm which is open */
1.126 brouard 8000: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
8001: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
8002: </ul>");
1.319 brouard 8003: /* fprintf(fichtm,"<ul><li> model=1+age+%s\n \ */
8004: /* </ul>", model); */
1.214 brouard 8005: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
8006: 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",
8007: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
1.332 brouard 8008: 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 8009: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
8010: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 8011: fprintf(fichtm,"\
8012: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 8013: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 8014: fprintf(fichtm,"\
1.217 brouard 8015: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
8016: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
8017: fprintf(fichtm,"\
1.288 brouard 8018: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 8019: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 8020: fprintf(fichtm,"\
1.288 brouard 8021: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 8022: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
8023: fprintf(fichtm,"\
1.211 brouard 8024: - (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 8025: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 8026: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 8027: if(prevfcast==1){
8028: fprintf(fichtm,"\
8029: - Prevalence projections by age and states: \
1.201 brouard 8030: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 8031: }
1.126 brouard 8032:
8033:
1.225 brouard 8034: m=pow(2,cptcoveff);
1.222 brouard 8035: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 8036:
1.317 brouard 8037: fprintf(fichtm," \n<ul><li><b>Graphs (first order)</b></li><p>");
1.264 brouard 8038:
8039: jj1=0;
8040:
8041: fprintf(fichtm," \n<ul>");
1.337 brouard 8042: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8043: /* k1=nres; */
1.338 brouard 8044: k1=TKresult[nres];
8045: if(TKresult[nres]==0)k1=1; /* To be checked for no result */
1.337 brouard 8046: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
8047: /* if(m != 1 && TKresult[nres]!= k1) */
8048: /* continue; */
1.264 brouard 8049: jj1++;
8050: if (cptcovn > 0) {
8051: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
1.337 brouard 8052: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
8053: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 8054: }
1.337 brouard 8055: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
8056: /* fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
8057: /* } */
8058: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8059: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8060: /* } */
1.264 brouard 8061: fprintf(fichtm,"\">");
8062:
8063: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
8064: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 8065: for (cpt=1; cpt<=cptcovs;cpt++){
8066: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 8067: }
1.337 brouard 8068: /* fprintf(fichtm,"************ Results for covariates"); */
8069: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
8070: /* fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
8071: /* } */
8072: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8073: /* fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8074: /* } */
1.264 brouard 8075: if(invalidvarcomb[k1]){
8076: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
8077: continue;
8078: }
8079: fprintf(fichtm,"</a></li>");
8080: } /* cptcovn >0 */
8081: }
1.317 brouard 8082: fprintf(fichtm," \n</ul>");
1.264 brouard 8083:
1.222 brouard 8084: jj1=0;
1.237 brouard 8085:
1.337 brouard 8086: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8087: /* k1=nres; */
1.338 brouard 8088: k1=TKresult[nres];
8089: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8090: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
8091: /* if(m != 1 && TKresult[nres]!= k1) */
8092: /* continue; */
1.220 brouard 8093:
1.222 brouard 8094: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
8095: jj1++;
8096: if (cptcovn > 0) {
1.264 brouard 8097: fprintf(fichtm,"\n<p><a name=\"rescov");
1.337 brouard 8098: for (cpt=1; cpt<=cptcovs;cpt++){
8099: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 8100: }
1.337 brouard 8101: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8102: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8103: /* } */
1.264 brouard 8104: fprintf(fichtm,"\"</a>");
8105:
1.222 brouard 8106: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 8107: for (cpt=1; cpt<=cptcovs;cpt++){
8108: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
8109: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 8110: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
8111: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 8112: }
1.230 brouard 8113: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.338 brouard 8114: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.222 brouard 8115: if(invalidvarcomb[k1]){
8116: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
8117: printf("\nCombination (%d) ignored because no cases \n",k1);
8118: continue;
8119: }
8120: }
8121: /* aij, bij */
1.259 brouard 8122: 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 8123: <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 8124: /* Pij */
1.241 brouard 8125: 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> \
8126: <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 8127: /* Quasi-incidences */
8128: 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 8129: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 8130: 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 8131: 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> \
8132: <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 8133: /* Survival functions (period) in state j */
8134: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 8135: 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);
8136: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
8137: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.222 brouard 8138: }
8139: /* State specific survival functions (period) */
8140: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 8141: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
8142: And probability to be observed in various states (up to %d) being in state %d at different ages. \
1.329 brouard 8143: <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);
8144: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
8145: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.222 brouard 8146: }
1.288 brouard 8147: /* Period (forward stable) prevalence in each health state */
1.222 brouard 8148: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 8149: 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 8150: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
1.329 brouard 8151: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.222 brouard 8152: }
1.296 brouard 8153: if(prevbcast==1){
1.288 brouard 8154: /* Backward prevalence in each health state */
1.222 brouard 8155: for(cpt=1; cpt<=nlstate;cpt++){
1.338 brouard 8156: 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);
8157: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJB_"),subdirf2(optionfilefiname,"PIJB_"));
8158: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.222 brouard 8159: }
1.217 brouard 8160: }
1.222 brouard 8161: if(prevfcast==1){
1.288 brouard 8162: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 8163: for(cpt=1; cpt<=nlstate;cpt++){
1.314 brouard 8164: 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);
8165: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"F_"),subdirf2(optionfilefiname,"F_"));
8166: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",
8167: subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 8168: }
8169: }
1.296 brouard 8170: if(prevbcast==1){
1.268 brouard 8171: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
8172: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 8173: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
8174: 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 \
8175: 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 8176: 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);
8177: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"FB_"),subdirf2(optionfilefiname,"FB_"));
8178: fprintf(fichtm," <img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
1.268 brouard 8179: }
8180: }
1.220 brouard 8181:
1.222 brouard 8182: for(cpt=1; cpt<=nlstate;cpt++) {
1.314 brouard 8183: 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);
8184: fprintf(fichtm," (data from text file <a href=\"%s.txt\"> %s.txt</a>)\n<br>",subdirf2(optionfilefiname,"E_"),subdirf2(optionfilefiname,"E_"));
8185: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres );
1.222 brouard 8186: }
8187: /* } /\* end i1 *\/ */
1.337 brouard 8188: }/* End k1=nres */
1.222 brouard 8189: fprintf(fichtm,"</ul>");
1.126 brouard 8190:
1.222 brouard 8191: fprintf(fichtm,"\
1.126 brouard 8192: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 8193: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 8194: - 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 8195: But because parameters are usually highly correlated (a higher incidence of disability \
8196: and a higher incidence of recovery can give very close observed transition) it might \
8197: be very useful to look not only at linear confidence intervals estimated from the \
8198: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
8199: (parameters) of the logistic regression, it might be more meaningful to visualize the \
8200: covariance matrix of the one-step probabilities. \
8201: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 8202:
1.222 brouard 8203: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
8204: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
8205: fprintf(fichtm,"\
1.126 brouard 8206: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 8207: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 8208:
1.222 brouard 8209: fprintf(fichtm,"\
1.126 brouard 8210: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 8211: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
8212: fprintf(fichtm,"\
1.126 brouard 8213: - 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): \
8214: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 8215: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 8216: fprintf(fichtm,"\
1.126 brouard 8217: - (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): \
8218: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 8219: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 8220: fprintf(fichtm,"\
1.288 brouard 8221: - 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 8222: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
8223: fprintf(fichtm,"\
1.128 brouard 8224: - 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 8225: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
8226: fprintf(fichtm,"\
1.288 brouard 8227: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 8228: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 8229:
8230: /* if(popforecast==1) fprintf(fichtm,"\n */
8231: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
8232: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
8233: /* <br>",fileres,fileres,fileres,fileres); */
8234: /* else */
1.338 brouard 8235: /* 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 8236: fflush(fichtm);
1.126 brouard 8237:
1.225 brouard 8238: m=pow(2,cptcoveff);
1.222 brouard 8239: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 8240:
1.317 brouard 8241: fprintf(fichtm," <ul><li><b>Graphs (second order)</b></li><p>");
8242:
8243: jj1=0;
8244:
8245: fprintf(fichtm," \n<ul>");
1.337 brouard 8246: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8247: /* k1=nres; */
1.338 brouard 8248: k1=TKresult[nres];
1.337 brouard 8249: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
8250: /* if(m != 1 && TKresult[nres]!= k1) */
8251: /* continue; */
1.317 brouard 8252: jj1++;
8253: if (cptcovn > 0) {
8254: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescovsecond");
1.337 brouard 8255: for (cpt=1; cpt<=cptcovs;cpt++){
8256: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8257: }
8258: fprintf(fichtm,"\">");
8259:
8260: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
8261: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 8262: for (cpt=1; cpt<=cptcovs;cpt++){
8263: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8264: }
8265: if(invalidvarcomb[k1]){
8266: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
8267: continue;
8268: }
8269: fprintf(fichtm,"</a></li>");
8270: } /* cptcovn >0 */
1.337 brouard 8271: } /* End nres */
1.317 brouard 8272: fprintf(fichtm," \n</ul>");
8273:
1.222 brouard 8274: jj1=0;
1.237 brouard 8275:
1.241 brouard 8276: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8277: /* k1=nres; */
1.338 brouard 8278: k1=TKresult[nres];
8279: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8280: /* for(k1=1; k1<=m;k1++){ */
8281: /* if(m != 1 && TKresult[nres]!= k1) */
8282: /* continue; */
1.222 brouard 8283: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
8284: jj1++;
1.126 brouard 8285: if (cptcovn > 0) {
1.317 brouard 8286: fprintf(fichtm,"\n<p><a name=\"rescovsecond");
1.337 brouard 8287: for (cpt=1; cpt<=cptcovs;cpt++){
8288: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8289: }
8290: fprintf(fichtm,"\"</a>");
8291:
1.126 brouard 8292: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 8293: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcoveff number of variables */
8294: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
8295: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 8296: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
1.317 brouard 8297: }
1.237 brouard 8298:
1.338 brouard 8299: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.220 brouard 8300:
1.222 brouard 8301: if(invalidvarcomb[k1]){
8302: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
8303: continue;
8304: }
1.337 brouard 8305: } /* If cptcovn >0 */
1.126 brouard 8306: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 8307: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.314 brouard 8308: 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);
8309: fprintf(fichtm," (data from text file <a href=\"%s\">%s</a>)\n <br>",subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
8310: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"V_"), cpt,k1,nres);
1.126 brouard 8311: }
8312: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.314 brouard 8313: health expectancies in each live states (1 to %d). If popbased=1 the smooth (due to the model) \
1.128 brouard 8314: true period expectancies (those weighted with period prevalences are also\
8315: drawn in addition to the population based expectancies computed using\
1.314 brouard 8316: 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);
8317: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>) \n<br>",subdirf2(optionfilefiname,"T_"),subdirf2(optionfilefiname,"T_"));
8318: fprintf(fichtm,"<img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 8319: /* } /\* end i1 *\/ */
1.241 brouard 8320: }/* End nres */
1.222 brouard 8321: fprintf(fichtm,"</ul>");
8322: fflush(fichtm);
1.126 brouard 8323: }
8324:
8325: /******************* Gnuplot file **************/
1.296 brouard 8326: 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 8327:
8328: char dirfileres[132],optfileres[132];
1.264 brouard 8329: char gplotcondition[132], gplotlabel[132];
1.343 brouard 8330: 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 8331: int lv=0, vlv=0, kl=0;
1.130 brouard 8332: int ng=0;
1.201 brouard 8333: int vpopbased;
1.223 brouard 8334: int ioffset; /* variable offset for columns */
1.270 brouard 8335: int iyearc=1; /* variable column for year of projection */
8336: int iagec=1; /* variable column for age of projection */
1.235 brouard 8337: int nres=0; /* Index of resultline */
1.266 brouard 8338: int istart=1; /* For starting graphs in projections */
1.219 brouard 8339:
1.126 brouard 8340: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
8341: /* printf("Problem with file %s",optionfilegnuplot); */
8342: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
8343: /* } */
8344:
8345: /*#ifdef windows */
8346: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 8347: /*#endif */
1.225 brouard 8348: m=pow(2,cptcoveff);
1.126 brouard 8349:
1.274 brouard 8350: /* diagram of the model */
8351: fprintf(ficgp,"\n#Diagram of the model \n");
8352: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
8353: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
8354: 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);
8355:
1.343 brouard 8356: 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 8357: fprintf(ficgp,"\n#show arrow\nunset label\n");
8358: 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);
8359: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
8360: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
8361: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
8362: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
8363:
1.202 brouard 8364: /* Contribution to likelihood */
8365: /* Plot the probability implied in the likelihood */
1.223 brouard 8366: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
8367: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
8368: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
8369: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 8370: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 8371: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
8372: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 8373: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
8374: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
8375: 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));
8376: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
8377: 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));
8378: for (i=1; i<= nlstate ; i ++) {
8379: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
8380: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
8381: 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);
8382: for (j=2; j<= nlstate+ndeath ; j ++) {
8383: 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);
8384: }
8385: fprintf(ficgp,";\nset out; unset ylabel;\n");
8386: }
8387: /* 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 */
8388: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
8389: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
8390: fprintf(ficgp,"\nset out;unset log\n");
8391: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 8392:
1.343 brouard 8393: /* Plot the probability implied in the likelihood by covariate value */
8394: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
8395: /* if(debugILK==1){ */
8396: for(kf=1; kf <= ncovf; kf++){ /* For each simple dummy covariate of the model */
1.347 brouard 8397: kvar=Tvar[TvarFind[kf]]; /* variable name */
8398: /* k=18+Tvar[TvarFind[kf]];/\*offset because there are 18 columns in the ILK_ file but could be placed else where *\/ */
8399: k=18+kf;/*offset because there are 18 columns in the ILK_ file */
1.343 brouard 8400: for (i=1; i<= nlstate ; i ++) {
8401: fprintf(ficgp,"\nset out \"%s-p%dj-%d.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i,kvar);
8402: fprintf(ficgp,"unset log;\n# For each simple dummy covariate of the model \n plot \"%s\"",subdirf(fileresilk));
1.348 brouard 8403: if(gnuplotversion >=5.2){ /* Former gnuplot versions do not have variable pointsize!! */
8404: 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);
8405: for (j=2; j<= nlstate+ndeath ; j ++) {
8406: 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);
8407: }
8408: }else{
8409: 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);
8410: for (j=2; j<= nlstate+ndeath ; j ++) {
8411: 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);
8412: }
1.343 brouard 8413: }
8414: fprintf(ficgp,";\nset out; unset ylabel;\n");
8415: }
8416: } /* End of each covariate dummy */
8417: for(ncovv=1, iposold=0, kk=0; ncovv <= ncovvt ; ncovv++){
8418: /* Other example V1 + V3 + V5 + age*V1 + age*V3 + age*V5 + V1*V3 + V3*V5 + V1*V5
8419: * kmodel = 1 2 3 4 5 6 7 8 9
8420: * varying 1 2 3 4 5
8421: * ncovv 1 2 3 4 5 6 7 8
8422: * TvarVV[ncovv] V3 5 1 3 3 5 1 5
8423: * TvarVVind[ncovv]=kmodel 2 3 7 7 8 8 9 9
8424: * TvarFind[kmodel] 1 0 0 0 0 0 0 0 0
8425: * kdata ncovcol=[V1 V2] nqv=0 ntv=[V3 V4] nqtv=V5
8426: * Dummy[kmodel] 0 0 1 2 2 3 1 1 1
8427: */
8428: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
8429: kvar=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
8430: /* 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]); */
8431: if(ipos!=iposold){ /* Not a product or first of a product */
8432: /* printf(" %d",ipos); */
8433: /* fprintf(ficresilk," V%d",TvarVV[ncovv]); */
8434: /* printf(" DebugILK ficgp suite ipos=%d != iposold=%d\n", ipos, iposold); */
8435: kk++; /* Position of the ncovv column in ILK_ */
8436: k=18+ncovf+kk; /*offset because there are 18 columns in the ILK_ file plus ncovf fixed covariate */
8437: 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) */
8438: for (i=1; i<= nlstate ; i ++) {
8439: fprintf(ficgp,"\nset out \"%s-p%dj-%d.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i,kvar);
8440: fprintf(ficgp,"unset log;\n# For each simple dummy covariate of the model \n plot \"%s\"",subdirf(fileresilk));
8441:
1.348 brouard 8442: /* printf("Before DebugILK gnuplotversion=%g >=5.2\n",gnuplotversion); */
1.343 brouard 8443: if(gnuplotversion >=5.2){ /* Former gnuplot versions do not have variable pointsize!! */
8444: /* printf("DebugILK gnuplotversion=%g >=5.2\n",gnuplotversion); */
8445: 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);
8446: for (j=2; j<= nlstate+ndeath ; j ++) {
8447: 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);
8448: }
8449: }else{
8450: /* printf("DebugILK gnuplotversion=%g <5.2\n",gnuplotversion); */
8451: 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);
8452: for (j=2; j<= nlstate+ndeath ; j ++) {
8453: 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);
8454: }
8455: }
8456: fprintf(ficgp,";\nset out; unset ylabel;\n");
8457: }
8458: }/* End if dummy varying */
8459: }else{ /*Product */
8460: /* printf("*"); */
8461: /* fprintf(ficresilk,"*"); */
8462: }
8463: iposold=ipos;
8464: } /* For each time varying covariate */
8465: /* } /\* debugILK==1 *\/ */
8466: /* 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 */
8467: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
8468: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
8469: fprintf(ficgp,"\nset out;unset log\n");
8470: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
8471:
8472:
8473:
1.126 brouard 8474: strcpy(dirfileres,optionfilefiname);
8475: strcpy(optfileres,"vpl");
1.223 brouard 8476: /* 1eme*/
1.238 brouard 8477: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
1.337 brouard 8478: /* for (k1=1; k1<= m ; k1 ++){ /\* For each valid combination of covariate *\/ */
1.236 brouard 8479: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8480: k1=TKresult[nres];
1.338 brouard 8481: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.238 brouard 8482: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.337 brouard 8483: /* if(m != 1 && TKresult[nres]!= k1) */
8484: /* continue; */
1.238 brouard 8485: /* We are interested in selected combination by the resultline */
1.246 brouard 8486: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 8487: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 8488: strcpy(gplotlabel,"(");
1.337 brouard 8489: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8490: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8491: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8492:
8493: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate k get corresponding value lv for combination k1 *\/ */
8494: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the value of the covariate corresponding to k1 combination *\\/ *\/ */
8495: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8496: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8497: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8498: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8499: /* vlv= nbcode[Tvaraff[k]][lv]; /\* vlv is the value of the covariate lv, 0 or 1 *\/ */
8500: /* /\* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv *\/ */
8501: /* /\* printf(" V%d=%d ",Tvaraff[k],vlv); *\/ */
8502: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8503: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8504: /* } */
8505: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8506: /* /\* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); *\/ */
8507: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8508: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.264 brouard 8509: }
8510: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 8511: /* printf("\n#\n"); */
1.238 brouard 8512: fprintf(ficgp,"\n#\n");
8513: if(invalidvarcomb[k1]){
1.260 brouard 8514: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 8515: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8516: continue;
8517: }
1.235 brouard 8518:
1.241 brouard 8519: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
8520: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 8521: /* 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 8522: fprintf(ficgp,"set title \"Alive state %d %s model=1+age+%s\" font \"Helvetica,12\"\n",cpt,gplotlabel,model);
1.260 brouard 8523: 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);
8524: /* 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); */
8525: /* k1-1 error should be nres-1*/
1.238 brouard 8526: for (i=1; i<= nlstate ; i ++) {
8527: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8528: else fprintf(ficgp," %%*lf (%%*lf)");
8529: }
1.288 brouard 8530: 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 8531: for (i=1; i<= nlstate ; i ++) {
8532: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8533: else fprintf(ficgp," %%*lf (%%*lf)");
8534: }
1.260 brouard 8535: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 8536: for (i=1; i<= nlstate ; i ++) {
8537: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8538: else fprintf(ficgp," %%*lf (%%*lf)");
8539: }
1.265 brouard 8540: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
8541:
8542: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
8543: if(cptcoveff ==0){
1.271 brouard 8544: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 8545: }else{
8546: kl=0;
8547: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 8548: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
8549: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.265 brouard 8550: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8551: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8552: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8553: vlv= nbcode[Tvaraff[k]][lv];
8554: kl++;
8555: /* 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 *\/ */
8556: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8557: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8558: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
8559: if(k==cptcoveff){
8560: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
8561: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
8562: }else{
8563: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
8564: kl++;
8565: }
8566: } /* end covariate */
8567: } /* end if no covariate */
8568:
1.296 brouard 8569: if(prevbcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
1.238 brouard 8570: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 8571: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 8572: if(cptcoveff ==0){
1.245 brouard 8573: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 8574: }else{
8575: kl=0;
8576: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 8577: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
8578: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.238 brouard 8579: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8580: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8581: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 8582: /* vlv= nbcode[Tvaraff[k]][lv]; */
8583: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.223 brouard 8584: kl++;
1.238 brouard 8585: /* 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 *\/ */
8586: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8587: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8588: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
8589: if(k==cptcoveff){
1.245 brouard 8590: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 8591: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 8592: }else{
1.332 brouard 8593: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]);
1.238 brouard 8594: kl++;
8595: }
8596: } /* end covariate */
8597: } /* end if no covariate */
1.296 brouard 8598: if(prevbcast == 1){
1.268 brouard 8599: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
8600: /* k1-1 error should be nres-1*/
8601: for (i=1; i<= nlstate ; i ++) {
8602: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8603: else fprintf(ficgp," %%*lf (%%*lf)");
8604: }
1.271 brouard 8605: 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 8606: for (i=1; i<= nlstate ; i ++) {
8607: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8608: else fprintf(ficgp," %%*lf (%%*lf)");
8609: }
1.276 brouard 8610: 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 8611: for (i=1; i<= nlstate ; i ++) {
8612: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8613: else fprintf(ficgp," %%*lf (%%*lf)");
8614: }
1.274 brouard 8615: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 8616: } /* end if backprojcast */
1.296 brouard 8617: } /* end if prevbcast */
1.276 brouard 8618: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
8619: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 8620: } /* nres */
1.337 brouard 8621: /* } /\* k1 *\/ */
1.201 brouard 8622: } /* cpt */
1.235 brouard 8623:
8624:
1.126 brouard 8625: /*2 eme*/
1.337 brouard 8626: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 8627: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8628: k1=TKresult[nres];
1.338 brouard 8629: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8630: /* if(m != 1 && TKresult[nres]!= k1) */
8631: /* continue; */
1.238 brouard 8632: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 8633: strcpy(gplotlabel,"(");
1.337 brouard 8634: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8635: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8636: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8637: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8638: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8639: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8640: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8641: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8642: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8643: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8644: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8645: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8646: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8647: /* } */
8648: /* /\* for(k=1; k <= ncovds; k++){ *\/ */
8649: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8650: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8651: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8652: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 8653: }
1.264 brouard 8654: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8655: fprintf(ficgp,"\n#\n");
1.223 brouard 8656: if(invalidvarcomb[k1]){
8657: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8658: continue;
8659: }
1.219 brouard 8660:
1.241 brouard 8661: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 8662: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 8663: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
8664: if(vpopbased==0){
1.238 brouard 8665: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 8666: }else
1.238 brouard 8667: fprintf(ficgp,"\nreplot ");
8668: for (i=1; i<= nlstate+1 ; i ++) {
8669: k=2*i;
1.261 brouard 8670: 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 8671: for (j=1; j<= nlstate+1 ; j ++) {
8672: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8673: else fprintf(ficgp," %%*lf (%%*lf)");
8674: }
8675: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
8676: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 8677: 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 8678: for (j=1; j<= nlstate+1 ; j ++) {
8679: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8680: else fprintf(ficgp," %%*lf (%%*lf)");
8681: }
8682: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 8683: 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 8684: for (j=1; j<= nlstate+1 ; j ++) {
8685: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8686: else fprintf(ficgp," %%*lf (%%*lf)");
8687: }
8688: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
8689: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
8690: } /* state */
8691: } /* vpopbased */
1.264 brouard 8692: 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 8693: } /* end nres */
1.337 brouard 8694: /* } /\* k1 end 2 eme*\/ */
1.238 brouard 8695:
8696:
8697: /*3eme*/
1.337 brouard 8698: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 8699: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8700: k1=TKresult[nres];
1.338 brouard 8701: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8702: /* if(m != 1 && TKresult[nres]!= k1) */
8703: /* continue; */
1.238 brouard 8704:
1.332 brouard 8705: for (cpt=1; cpt<= nlstate ; cpt ++) { /* Fragile no verification of covariate values */
1.261 brouard 8706: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 8707: strcpy(gplotlabel,"(");
1.337 brouard 8708: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8709: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8710: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8711: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8712: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8713: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8714: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8715: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8716: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8717: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8718: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8719: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8720: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8721: /* } */
8722: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8723: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
8724: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
8725: }
1.264 brouard 8726: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8727: fprintf(ficgp,"\n#\n");
8728: if(invalidvarcomb[k1]){
8729: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8730: continue;
8731: }
8732:
8733: /* k=2+nlstate*(2*cpt-2); */
8734: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 8735: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 8736: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 8737: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 8738: 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 8739: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8740: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8741: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
8742: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8743: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8744: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 8745:
1.238 brouard 8746: */
8747: for (i=1; i< nlstate ; i ++) {
1.261 brouard 8748: 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 8749: /* 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 8750:
1.238 brouard 8751: }
1.261 brouard 8752: 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 8753: }
1.264 brouard 8754: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 8755: } /* end nres */
1.337 brouard 8756: /* } /\* end kl 3eme *\/ */
1.126 brouard 8757:
1.223 brouard 8758: /* 4eme */
1.201 brouard 8759: /* Survival functions (period) from state i in state j by initial state i */
1.337 brouard 8760: /* for (k1=1; k1<=m; k1++){ /\* For each covariate and each value *\/ */
1.238 brouard 8761: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8762: k1=TKresult[nres];
1.338 brouard 8763: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8764: /* if(m != 1 && TKresult[nres]!= k1) */
8765: /* continue; */
1.238 brouard 8766: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 8767: strcpy(gplotlabel,"(");
1.337 brouard 8768: fprintf(ficgp,"\n#\n#\n# Survival functions in state %d : 'LIJ_' files, cov=%d state=%d", cpt, k1, cpt);
8769: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8770: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8771: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8772: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8773: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8774: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8775: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8776: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8777: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8778: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8779: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8780: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8781: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8782: /* } */
8783: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8784: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8785: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 8786: }
1.264 brouard 8787: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8788: fprintf(ficgp,"\n#\n");
8789: if(invalidvarcomb[k1]){
8790: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8791: continue;
1.223 brouard 8792: }
1.238 brouard 8793:
1.241 brouard 8794: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 8795: 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 8796: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8797: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8798: k=3;
8799: for (i=1; i<= nlstate ; i ++){
8800: if(i==1){
8801: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8802: }else{
8803: fprintf(ficgp,", '' ");
8804: }
8805: l=(nlstate+ndeath)*(i-1)+1;
8806: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8807: for (j=2; j<= nlstate+ndeath ; j ++)
8808: fprintf(ficgp,"+$%d",k+l+j-1);
8809: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
8810: } /* nlstate */
1.264 brouard 8811: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8812: } /* end cpt state*/
8813: } /* end nres */
1.337 brouard 8814: /* } /\* end covariate k1 *\/ */
1.238 brouard 8815:
1.220 brouard 8816: /* 5eme */
1.201 brouard 8817: /* Survival functions (period) from state i in state j by final state j */
1.337 brouard 8818: /* for (k1=1; k1<= m ; k1++){ /\* For each covariate combination if any *\/ */
1.238 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; */
1.238 brouard 8824: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 8825: strcpy(gplotlabel,"(");
1.238 brouard 8826: 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 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 covariate and each value *\/ */
8831: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8832: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
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]]); */
1.238 brouard 8844: }
1.264 brouard 8845: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8846: fprintf(ficgp,"\n#\n");
8847: if(invalidvarcomb[k1]){
8848: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8849: continue;
8850: }
1.227 brouard 8851:
1.241 brouard 8852: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 8853: 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 8854: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8855: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8856: k=3;
8857: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8858: if(j==1)
8859: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8860: else
8861: fprintf(ficgp,", '' ");
8862: l=(nlstate+ndeath)*(cpt-1) +j;
8863: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
8864: /* for (i=2; i<= nlstate+ndeath ; i ++) */
8865: /* fprintf(ficgp,"+$%d",k+l+i-1); */
8866: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
8867: } /* nlstate */
8868: fprintf(ficgp,", '' ");
8869: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
8870: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8871: l=(nlstate+ndeath)*(cpt-1) +j;
8872: if(j < nlstate)
8873: fprintf(ficgp,"$%d +",k+l);
8874: else
8875: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
8876: }
1.264 brouard 8877: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8878: } /* end cpt state*/
1.337 brouard 8879: /* } /\* end covariate *\/ */
1.238 brouard 8880: } /* end nres */
1.227 brouard 8881:
1.220 brouard 8882: /* 6eme */
1.202 brouard 8883: /* CV preval stable (period) for each covariate */
1.337 brouard 8884: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8885: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8886: k1=TKresult[nres];
1.338 brouard 8887: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8888: /* if(m != 1 && TKresult[nres]!= k1) */
8889: /* continue; */
1.255 brouard 8890: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 8891: strcpy(gplotlabel,"(");
1.288 brouard 8892: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 8893: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8894: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8895: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8896: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8897: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8898: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8899: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8900: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8901: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8902: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8903: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8904: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8905: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8906: /* } */
8907: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8908: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8909: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 8910: }
1.264 brouard 8911: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8912: fprintf(ficgp,"\n#\n");
1.223 brouard 8913: if(invalidvarcomb[k1]){
1.227 brouard 8914: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8915: continue;
1.223 brouard 8916: }
1.227 brouard 8917:
1.241 brouard 8918: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 8919: 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 8920: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 8921: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 8922: k=3; /* Offset */
1.255 brouard 8923: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 8924: if(i==1)
8925: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8926: else
8927: fprintf(ficgp,", '' ");
1.255 brouard 8928: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 8929: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8930: for (j=2; j<= nlstate ; j ++)
8931: fprintf(ficgp,"+$%d",k+l+j-1);
8932: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 8933: } /* nlstate */
1.264 brouard 8934: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 8935: } /* end cpt state*/
8936: } /* end covariate */
1.227 brouard 8937:
8938:
1.220 brouard 8939: /* 7eme */
1.296 brouard 8940: if(prevbcast == 1){
1.288 brouard 8941: /* CV backward prevalence for each covariate */
1.337 brouard 8942: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8943: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8944: k1=TKresult[nres];
1.338 brouard 8945: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8946: /* if(m != 1 && TKresult[nres]!= k1) */
8947: /* continue; */
1.268 brouard 8948: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 8949: strcpy(gplotlabel,"(");
1.288 brouard 8950: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 8951: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8952: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8953: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8954: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8955: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8956: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8957: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8958: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8959: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8960: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8961: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8962: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8963: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8964: /* } */
8965: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8966: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8967: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 8968: }
1.264 brouard 8969: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 8970: fprintf(ficgp,"\n#\n");
8971: if(invalidvarcomb[k1]){
8972: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8973: continue;
8974: }
8975:
1.241 brouard 8976: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 8977: 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 8978: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 8979: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 8980: k=3; /* Offset */
1.268 brouard 8981: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 8982: if(i==1)
8983: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
8984: else
8985: fprintf(ficgp,", '' ");
8986: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 8987: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.324 brouard 8988: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
8989: /* 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 8990: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 8991: /* for (j=2; j<= nlstate ; j ++) */
8992: /* fprintf(ficgp,"+$%d",k+l+j-1); */
8993: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 8994: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 8995: } /* nlstate */
1.264 brouard 8996: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 8997: } /* end cpt state*/
8998: } /* end covariate */
1.296 brouard 8999: } /* End if prevbcast */
1.218 brouard 9000:
1.223 brouard 9001: /* 8eme */
1.218 brouard 9002: if(prevfcast==1){
1.288 brouard 9003: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 9004:
1.337 brouard 9005: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 9006: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9007: k1=TKresult[nres];
1.338 brouard 9008: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9009: /* if(m != 1 && TKresult[nres]!= k1) */
9010: /* continue; */
1.211 brouard 9011: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 9012: strcpy(gplotlabel,"(");
1.288 brouard 9013: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 9014: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
9015: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9016: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9017: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
9018: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
9019: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
9020: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9021: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9022: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9023: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9024: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9025: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9026: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9027: /* } */
9028: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9029: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9030: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 9031: }
1.264 brouard 9032: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 9033: fprintf(ficgp,"\n#\n");
9034: if(invalidvarcomb[k1]){
9035: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
9036: continue;
9037: }
9038:
9039: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 9040: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 9041: 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 9042: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 9043: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 9044:
9045: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
9046: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
9047: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
9048: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 9049: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9050: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9051: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9052: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 9053: if(i==istart){
1.227 brouard 9054: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
9055: }else{
9056: fprintf(ficgp,",\\\n '' ");
9057: }
9058: if(cptcoveff ==0){ /* No covariate */
9059: ioffset=2; /* Age is in 2 */
9060: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9061: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9062: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9063: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9064: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 9065: if(i==nlstate+1){
1.270 brouard 9066: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 9067: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
9068: fprintf(ficgp,",\\\n '' ");
9069: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 9070: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 9071: offyear, \
1.268 brouard 9072: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 9073: }else
1.227 brouard 9074: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
9075: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
9076: }else{ /* more than 2 covariates */
1.270 brouard 9077: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
9078: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9079: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9080: iyearc=ioffset-1;
9081: iagec=ioffset;
1.227 brouard 9082: fprintf(ficgp," u %d:(",ioffset);
9083: kl=0;
9084: strcpy(gplotcondition,"(");
9085: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
1.332 brouard 9086: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9087: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.227 brouard 9088: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
9089: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
9090: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 9091: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
9092: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.227 brouard 9093: kl++;
9094: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
9095: kl++;
9096: if(k <cptcoveff && cptcoveff>1)
9097: sprintf(gplotcondition+strlen(gplotcondition)," && ");
9098: }
9099: strcpy(gplotcondition+strlen(gplotcondition),")");
9100: /* 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 *\/ */
9101: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
9102: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
9103: /* '' 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*/
9104: if(i==nlstate+1){
1.270 brouard 9105: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
9106: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 9107: fprintf(ficgp,",\\\n '' ");
1.270 brouard 9108: fprintf(ficgp," u %d:(",iagec);
9109: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
9110: iyearc, iagec, offyear, \
9111: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 9112: /* '' 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 9113: }else{
9114: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
9115: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
9116: }
9117: } /* end if covariate */
9118: } /* nlstate */
1.264 brouard 9119: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 9120: } /* end cpt state*/
9121: } /* end covariate */
9122: } /* End if prevfcast */
1.227 brouard 9123:
1.296 brouard 9124: if(prevbcast==1){
1.268 brouard 9125: /* Back projection from cross-sectional to stable (mixed) for each covariate */
9126:
1.337 brouard 9127: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.268 brouard 9128: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9129: k1=TKresult[nres];
1.338 brouard 9130: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9131: /* if(m != 1 && TKresult[nres]!= k1) */
9132: /* continue; */
1.268 brouard 9133: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
9134: strcpy(gplotlabel,"(");
9135: 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 9136: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
9137: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9138: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9139: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
9140: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
9141: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9142: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9143: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9144: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9145: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9146: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9147: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9148: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9149: /* } */
9150: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9151: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9152: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.268 brouard 9153: }
9154: strcpy(gplotlabel+strlen(gplotlabel),")");
9155: fprintf(ficgp,"\n#\n");
9156: if(invalidvarcomb[k1]){
9157: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
9158: continue;
9159: }
9160:
9161: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
9162: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
9163: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
9164: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
9165: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
9166:
9167: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
9168: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
9169: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
9170: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
9171: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9172: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9173: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9174: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9175: if(i==istart){
9176: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
9177: }else{
9178: fprintf(ficgp,",\\\n '' ");
9179: }
9180: if(cptcoveff ==0){ /* No covariate */
9181: ioffset=2; /* Age is in 2 */
9182: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9183: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9184: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9185: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9186: fprintf(ficgp," u %d:(", ioffset);
9187: if(i==nlstate+1){
1.270 brouard 9188: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 9189: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
9190: fprintf(ficgp,",\\\n '' ");
9191: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 9192: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 9193: offbyear, \
9194: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
9195: }else
9196: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
9197: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
9198: }else{ /* more than 2 covariates */
1.270 brouard 9199: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
9200: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9201: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9202: iyearc=ioffset-1;
9203: iagec=ioffset;
1.268 brouard 9204: fprintf(ficgp," u %d:(",ioffset);
9205: kl=0;
9206: strcpy(gplotcondition,"(");
1.337 brouard 9207: for (k=1; k<=cptcovs; k++){ /* For each covariate k of the resultline, get corresponding value lv for combination k1 */
1.338 brouard 9208: if(Dummy[modelresult[nres][k]]==0){ /* To be verified */
1.337 brouard 9209: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate writing the chain of conditions *\/ */
9210: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9211: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9212: lv=Tvresult[nres][k];
9213: vlv=TinvDoQresult[nres][Tvresult[nres][k]];
9214: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
9215: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
9216: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
9217: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
9218: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9219: kl++;
9220: /* sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); */
9221: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%lg " ,kl,Tvresult[nres][k], kl+1,TinvDoQresult[nres][Tvresult[nres][k]]);
9222: kl++;
1.338 brouard 9223: if(k <cptcovs && cptcovs>1)
1.337 brouard 9224: sprintf(gplotcondition+strlen(gplotcondition)," && ");
9225: }
1.268 brouard 9226: }
9227: strcpy(gplotcondition+strlen(gplotcondition),")");
9228: /* 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 *\/ */
9229: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
9230: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
9231: /* '' 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*/
9232: if(i==nlstate+1){
1.270 brouard 9233: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
9234: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 9235: fprintf(ficgp,",\\\n '' ");
1.270 brouard 9236: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 9237: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 9238: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
9239: iyearc,iagec,offbyear, \
9240: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 9241: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
9242: }else{
9243: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
9244: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
9245: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
9246: }
9247: } /* end if covariate */
9248: } /* nlstate */
9249: fprintf(ficgp,"\nset out; unset label;\n");
9250: } /* end cpt state*/
9251: } /* end covariate */
1.296 brouard 9252: } /* End if prevbcast */
1.268 brouard 9253:
1.227 brouard 9254:
1.238 brouard 9255: /* 9eme writing MLE parameters */
9256: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 9257: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 9258: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 9259: for(k=1; k <=(nlstate+ndeath); k++){
9260: if (k != i) {
1.227 brouard 9261: fprintf(ficgp,"# current state %d\n",k);
9262: for(j=1; j <=ncovmodel; j++){
9263: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
9264: jk++;
9265: }
9266: fprintf(ficgp,"\n");
1.126 brouard 9267: }
9268: }
1.223 brouard 9269: }
1.187 brouard 9270: fprintf(ficgp,"##############\n#\n");
1.227 brouard 9271:
1.145 brouard 9272: /*goto avoid;*/
1.238 brouard 9273: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
9274: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 9275: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
9276: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
9277: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
9278: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
9279: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
9280: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
9281: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
9282: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
9283: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
9284: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
9285: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
9286: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
9287: fprintf(ficgp,"#\n");
1.223 brouard 9288: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 9289: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.338 brouard 9290: fprintf(ficgp,"#model=1+age+%s \n",model);
1.238 brouard 9291: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 brouard 9292: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
1.337 brouard 9293: /* for(k1=1; k1 <=m; k1++) /\* For each combination of covariate *\/ */
1.237 brouard 9294: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9295: /* k1=nres; */
1.338 brouard 9296: k1=TKresult[nres];
9297: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9298: fprintf(ficgp,"\n\n# Resultline k1=%d ",k1);
1.264 brouard 9299: strcpy(gplotlabel,"(");
1.276 brouard 9300: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.337 brouard 9301: for (k=1; k<=cptcovs; k++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
9302: /* for each resultline nres, and position k, Tvresult[nres][k] gives the name of the variable and
9303: TinvDoQresult[nres][Tvresult[nres][k]] gives its value double or integer) */
9304: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9305: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9306: }
9307: /* if(m != 1 && TKresult[nres]!= k1) */
9308: /* continue; */
9309: /* fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1); */
9310: /* strcpy(gplotlabel,"("); */
9311: /* /\*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*\/ */
9312: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
9313: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
9314: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9315: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9316: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9317: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9318: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9319: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9320: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9321: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9322: /* } */
9323: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9324: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9325: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9326: /* } */
1.264 brouard 9327: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 9328: fprintf(ficgp,"\n#\n");
1.264 brouard 9329: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 9330: fprintf(ficgp,"\nset key outside ");
9331: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
9332: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 9333: fprintf(ficgp,"\nset ter svg size 640, 480 ");
9334: if (ng==1){
9335: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
9336: fprintf(ficgp,"\nunset log y");
9337: }else if (ng==2){
9338: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
9339: fprintf(ficgp,"\nset log y");
9340: }else if (ng==3){
9341: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
9342: fprintf(ficgp,"\nset log y");
9343: }else
9344: fprintf(ficgp,"\nunset title ");
9345: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
9346: i=1;
9347: for(k2=1; k2<=nlstate; k2++) {
9348: k3=i;
9349: for(k=1; k<=(nlstate+ndeath); k++) {
9350: if (k != k2){
9351: switch( ng) {
9352: case 1:
9353: if(nagesqr==0)
9354: fprintf(ficgp," p%d+p%d*x",i,i+1);
9355: else /* nagesqr =1 */
9356: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
9357: break;
9358: case 2: /* ng=2 */
9359: if(nagesqr==0)
9360: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
9361: else /* nagesqr =1 */
9362: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
9363: break;
9364: case 3:
9365: if(nagesqr==0)
9366: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
9367: else /* nagesqr =1 */
9368: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
9369: break;
9370: }
9371: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 9372: ijp=1; /* product no age */
9373: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
9374: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 9375: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.329 brouard 9376: switch(Typevar[j]){
9377: case 1:
9378: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
9379: if(j==Tage[ij]) { /* Product by age To be looked at!!*//* Bug valgrind */
9380: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
9381: if(DummyV[j]==0){/* Bug valgrind */
9382: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
9383: }else{ /* quantitative */
9384: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
9385: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9386: }
9387: ij++;
1.268 brouard 9388: }
1.237 brouard 9389: }
1.329 brouard 9390: }
9391: break;
9392: case 2:
9393: if(cptcovprod >0){
9394: if(j==Tprod[ijp]) { /* */
9395: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9396: if(ijp <=cptcovprod) { /* Product */
9397: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
9398: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
9399: /* 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)]); */
9400: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9401: }else{ /* Vn is dummy and Vm is quanti */
9402: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
9403: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9404: }
9405: }else{ /* Vn*Vm Vn is quanti */
9406: if(DummyV[Tvard[ijp][2]]==0){
9407: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
9408: }else{ /* Both quanti */
9409: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9410: }
1.268 brouard 9411: }
1.329 brouard 9412: ijp++;
1.237 brouard 9413: }
1.329 brouard 9414: } /* end Tprod */
9415: }
9416: break;
1.349 ! brouard 9417: case 3:
! 9418: if(cptcovdageprod >0){
! 9419: /* if(j==Tprod[ijp]) { */ /* not necessary */
! 9420: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
! 9421: if(ijp <=cptcovprod) { /* Product */
! 9422: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
! 9423: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
! 9424: /* 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)]); */
! 9425: fprintf(ficgp,"+p%d*%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
! 9426: }else{ /* Vn is dummy and Vm is quanti */
! 9427: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
! 9428: fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
! 9429: }
! 9430: }else{ /* Vn*Vm Vn is quanti */
! 9431: if(DummyV[Tvard[ijp][2]]==0){
! 9432: fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
! 9433: }else{ /* Both quanti */
! 9434: fprintf(ficgp,"+p%d*%f*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
! 9435: }
! 9436: }
! 9437: ijp++;
! 9438: }
! 9439: /* } */ /* end Tprod */
! 9440: }
! 9441: break;
1.329 brouard 9442: case 0:
9443: /* simple covariate */
1.264 brouard 9444: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 9445: if(Dummy[j]==0){
9446: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
9447: }else{ /* quantitative */
9448: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 9449: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 9450: }
1.329 brouard 9451: /* end simple */
9452: break;
9453: default:
9454: break;
9455: } /* end switch */
1.237 brouard 9456: } /* end j */
1.329 brouard 9457: }else{ /* k=k2 */
9458: if(ng !=1 ){ /* For logit formula of log p11 is more difficult to get */
9459: fprintf(ficgp," (1.");i=i-ncovmodel;
9460: }else
9461: i=i-ncovmodel;
1.223 brouard 9462: }
1.227 brouard 9463:
1.223 brouard 9464: if(ng != 1){
9465: fprintf(ficgp,")/(1");
1.227 brouard 9466:
1.264 brouard 9467: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 9468: if(nagesqr==0)
1.264 brouard 9469: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 9470: else /* nagesqr =1 */
1.264 brouard 9471: 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 9472:
1.223 brouard 9473: ij=1;
1.329 brouard 9474: ijp=1;
9475: /* for(j=3; j <=ncovmodel-nagesqr; j++){ */
9476: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
9477: switch(Typevar[j]){
9478: case 1:
9479: if(cptcovage >0){
9480: if(j==Tage[ij]) { /* Bug valgrind */
9481: if(ij <=cptcovage) { /* Bug valgrind */
9482: if(DummyV[j]==0){/* Bug valgrind */
9483: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]); */
9484: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,nbcode[Tvar[j]][codtabm(k1,j)]); */
9485: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]);
9486: /* fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);; */
9487: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9488: }else{ /* quantitative */
9489: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
9490: fprintf(ficgp,"+p%d*%f*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
9491: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
9492: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9493: }
9494: ij++;
9495: }
9496: }
9497: }
9498: break;
9499: case 2:
9500: if(cptcovprod >0){
9501: if(j==Tprod[ijp]) { /* */
9502: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9503: if(ijp <=cptcovprod) { /* Product */
9504: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
9505: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
9506: /* 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)]); */
9507: fprintf(ficgp,"+p%d*%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9508: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
9509: }else{ /* Vn is dummy and Vm is quanti */
9510: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
9511: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9512: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9513: }
9514: }else{ /* Vn*Vm Vn is quanti */
9515: if(DummyV[Tvard[ijp][2]]==0){
9516: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
9517: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
9518: }else{ /* Both quanti */
9519: fprintf(ficgp,"+p%d*%f*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9520: /* fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9521: }
9522: }
9523: ijp++;
9524: }
9525: } /* end Tprod */
9526: } /* end if */
9527: break;
1.349 ! brouard 9528: case 3:
! 9529: if(cptcovdageprod >0){
! 9530: /* if(j==Tprod[ijp]) { /\* *\/ */
! 9531: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
! 9532: if(ijp <=cptcovprod) { /* Product */
! 9533: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
! 9534: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
! 9535: /* 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)]); */
! 9536: fprintf(ficgp,"+p%d*%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
! 9537: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
! 9538: }else{ /* Vn is dummy and Vm is quanti */
! 9539: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
! 9540: fprintf(ficgp,"+p%d*%d*%f*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
! 9541: /* fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
! 9542: }
! 9543: }else{ /* Vn*Vm Vn is quanti */
! 9544: if(DummyV[Tvard[ijp][2]]==0){
! 9545: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
! 9546: /* fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
! 9547: }else{ /* Both quanti */
! 9548: fprintf(ficgp,"+p%d*%f*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
! 9549: /* fprintf(ficgp,"+p%d*%f*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
! 9550: }
! 9551: }
! 9552: ijp++;
! 9553: }
! 9554: /* } /\* end Tprod *\/ */
! 9555: } /* end if */
! 9556: break;
1.329 brouard 9557: case 0:
9558: /* simple covariate */
9559: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
9560: if(Dummy[j]==0){
9561: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
9562: fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]); /* */
9563: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
9564: }else{ /* quantitative */
9565: fprintf(ficgp,"+p%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* */
9566: /* fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* *\/ */
9567: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9568: }
9569: /* end simple */
9570: /* fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);/\* Valgrind bug nbcode *\/ */
9571: break;
9572: default:
9573: break;
9574: } /* end switch */
1.223 brouard 9575: }
9576: fprintf(ficgp,")");
9577: }
9578: fprintf(ficgp,")");
9579: if(ng ==2)
1.276 brouard 9580: 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 9581: else /* ng= 3 */
1.276 brouard 9582: 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 9583: }else{ /* end ng <> 1 */
1.223 brouard 9584: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 9585: 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 9586: }
9587: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
9588: fprintf(ficgp,",");
9589: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
9590: fprintf(ficgp,",");
9591: i=i+ncovmodel;
9592: } /* end k */
9593: } /* end k2 */
1.276 brouard 9594: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
9595: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.337 brouard 9596: } /* end resultline */
1.223 brouard 9597: } /* end ng */
9598: /* avoid: */
9599: fflush(ficgp);
1.126 brouard 9600: } /* end gnuplot */
9601:
9602:
9603: /*************** Moving average **************/
1.219 brouard 9604: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 9605: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 9606:
1.222 brouard 9607: int i, cpt, cptcod;
9608: int modcovmax =1;
9609: int mobilavrange, mob;
9610: int iage=0;
1.288 brouard 9611: int firstA1=0, firstA2=0;
1.222 brouard 9612:
1.266 brouard 9613: double sum=0., sumr=0.;
1.222 brouard 9614: double age;
1.266 brouard 9615: double *sumnewp, *sumnewm, *sumnewmr;
9616: double *agemingood, *agemaxgood;
9617: double *agemingoodr, *agemaxgoodr;
1.222 brouard 9618:
9619:
1.278 brouard 9620: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
9621: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 9622:
9623: sumnewp = vector(1,ncovcombmax);
9624: sumnewm = vector(1,ncovcombmax);
1.266 brouard 9625: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 9626: agemingood = vector(1,ncovcombmax);
1.266 brouard 9627: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 9628: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 9629: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 9630:
9631: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 9632: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 9633: sumnewp[cptcod]=0.;
1.266 brouard 9634: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
9635: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 9636: }
9637: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
9638:
1.266 brouard 9639: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
9640: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 9641: else mobilavrange=mobilav;
9642: for (age=bage; age<=fage; age++)
9643: for (i=1; i<=nlstate;i++)
9644: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
9645: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9646: /* We keep the original values on the extreme ages bage, fage and for
9647: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
9648: we use a 5 terms etc. until the borders are no more concerned.
9649: */
9650: for (mob=3;mob <=mobilavrange;mob=mob+2){
9651: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 9652: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
9653: sumnewm[cptcod]=0.;
9654: for (i=1; i<=nlstate;i++){
1.222 brouard 9655: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
9656: for (cpt=1;cpt<=(mob-1)/2;cpt++){
9657: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
9658: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
9659: }
9660: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 9661: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9662: } /* end i */
9663: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
9664: } /* end cptcod */
1.222 brouard 9665: }/* end age */
9666: }/* end mob */
1.266 brouard 9667: }else{
9668: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 9669: return -1;
1.266 brouard 9670: }
9671:
9672: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 9673: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
9674: if(invalidvarcomb[cptcod]){
9675: printf("\nCombination (%d) ignored because no cases \n",cptcod);
9676: continue;
9677: }
1.219 brouard 9678:
1.266 brouard 9679: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
9680: sumnewm[cptcod]=0.;
9681: sumnewmr[cptcod]=0.;
9682: for (i=1; i<=nlstate;i++){
9683: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9684: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9685: }
9686: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9687: agemingoodr[cptcod]=age;
9688: }
9689: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9690: agemingood[cptcod]=age;
9691: }
9692: } /* age */
9693: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 9694: sumnewm[cptcod]=0.;
1.266 brouard 9695: sumnewmr[cptcod]=0.;
1.222 brouard 9696: for (i=1; i<=nlstate;i++){
9697: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 9698: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9699: }
9700: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9701: agemaxgoodr[cptcod]=age;
1.222 brouard 9702: }
9703: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 9704: agemaxgood[cptcod]=age;
9705: }
9706: } /* age */
9707: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
9708: /* but they will change */
1.288 brouard 9709: firstA1=0;firstA2=0;
1.266 brouard 9710: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
9711: sumnewm[cptcod]=0.;
9712: sumnewmr[cptcod]=0.;
9713: for (i=1; i<=nlstate;i++){
9714: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9715: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9716: }
9717: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
9718: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9719: agemaxgoodr[cptcod]=age; /* age min */
9720: for (i=1; i<=nlstate;i++)
9721: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9722: }else{ /* bad we change the value with the values of good ages */
9723: for (i=1; i<=nlstate;i++){
9724: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
9725: } /* i */
9726: } /* end bad */
9727: }else{
9728: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9729: agemaxgood[cptcod]=age;
9730: }else{ /* bad we change the value with the values of good ages */
9731: for (i=1; i<=nlstate;i++){
9732: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
9733: } /* i */
9734: } /* end bad */
9735: }/* end else */
9736: sum=0.;sumr=0.;
9737: for (i=1; i<=nlstate;i++){
9738: sum+=mobaverage[(int)age][i][cptcod];
9739: sumr+=probs[(int)age][i][cptcod];
9740: }
9741: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 9742: if(!firstA1){
9743: firstA1=1;
9744: 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);
9745: }
9746: 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 9747: } /* end bad */
9748: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
9749: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 9750: if(!firstA2){
9751: firstA2=1;
9752: 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);
9753: }
9754: 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 9755: } /* end bad */
9756: }/* age */
1.266 brouard 9757:
9758: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 9759: sumnewm[cptcod]=0.;
1.266 brouard 9760: sumnewmr[cptcod]=0.;
1.222 brouard 9761: for (i=1; i<=nlstate;i++){
9762: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 9763: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9764: }
9765: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
9766: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
9767: agemingoodr[cptcod]=age;
9768: for (i=1; i<=nlstate;i++)
9769: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9770: }else{ /* bad we change the value with the values of good ages */
9771: for (i=1; i<=nlstate;i++){
9772: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
9773: } /* i */
9774: } /* end bad */
9775: }else{
9776: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9777: agemingood[cptcod]=age;
9778: }else{ /* bad */
9779: for (i=1; i<=nlstate;i++){
9780: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
9781: } /* i */
9782: } /* end bad */
9783: }/* end else */
9784: sum=0.;sumr=0.;
9785: for (i=1; i<=nlstate;i++){
9786: sum+=mobaverage[(int)age][i][cptcod];
9787: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 9788: }
1.266 brouard 9789: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 9790: 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 9791: } /* end bad */
9792: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
9793: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 9794: 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 9795: } /* end bad */
9796: }/* age */
1.266 brouard 9797:
1.222 brouard 9798:
9799: for (age=bage; age<=fage; age++){
1.235 brouard 9800: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 9801: sumnewp[cptcod]=0.;
9802: sumnewm[cptcod]=0.;
9803: for (i=1; i<=nlstate;i++){
9804: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
9805: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9806: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
9807: }
9808: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
9809: }
9810: /* printf("\n"); */
9811: /* } */
1.266 brouard 9812:
1.222 brouard 9813: /* brutal averaging */
1.266 brouard 9814: /* for (i=1; i<=nlstate;i++){ */
9815: /* for (age=1; age<=bage; age++){ */
9816: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
9817: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
9818: /* } */
9819: /* for (age=fage; age<=AGESUP; age++){ */
9820: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
9821: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
9822: /* } */
9823: /* } /\* end i status *\/ */
9824: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
9825: /* for (age=1; age<=AGESUP; age++){ */
9826: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
9827: /* mobaverage[(int)age][i][cptcod]=0.; */
9828: /* } */
9829: /* } */
1.222 brouard 9830: }/* end cptcod */
1.266 brouard 9831: free_vector(agemaxgoodr,1, ncovcombmax);
9832: free_vector(agemaxgood,1, ncovcombmax);
9833: free_vector(agemingood,1, ncovcombmax);
9834: free_vector(agemingoodr,1, ncovcombmax);
9835: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 9836: free_vector(sumnewm,1, ncovcombmax);
9837: free_vector(sumnewp,1, ncovcombmax);
9838: return 0;
9839: }/* End movingaverage */
1.218 brouard 9840:
1.126 brouard 9841:
1.296 brouard 9842:
1.126 brouard 9843: /************** Forecasting ******************/
1.296 brouard 9844: /* 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)*/
9845: 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){
9846: /* dateintemean, mean date of interviews
9847: dateprojd, year, month, day of starting projection
9848: dateprojf date of end of projection;year of end of projection (same day and month as proj1).
1.126 brouard 9849: agemin, agemax range of age
9850: dateprev1 dateprev2 range of dates during which prevalence is computed
9851: */
1.296 brouard 9852: /* double anprojd, mprojd, jprojd; */
9853: /* double anprojf, mprojf, jprojf; */
1.267 brouard 9854: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 9855: double agec; /* generic age */
1.296 brouard 9856: double agelim, ppij, yp,yp1,yp2;
1.126 brouard 9857: double *popeffectif,*popcount;
9858: double ***p3mat;
1.218 brouard 9859: /* double ***mobaverage; */
1.126 brouard 9860: char fileresf[FILENAMELENGTH];
9861:
9862: agelim=AGESUP;
1.211 brouard 9863: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
9864: in each health status at the date of interview (if between dateprev1 and dateprev2).
9865: We still use firstpass and lastpass as another selection.
9866: */
1.214 brouard 9867: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
9868: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 9869:
1.201 brouard 9870: strcpy(fileresf,"F_");
9871: strcat(fileresf,fileresu);
1.126 brouard 9872: if((ficresf=fopen(fileresf,"w"))==NULL) {
9873: printf("Problem with forecast resultfile: %s\n", fileresf);
9874: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
9875: }
1.235 brouard 9876: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
9877: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 9878:
1.225 brouard 9879: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 9880:
9881:
9882: stepsize=(int) (stepm+YEARM-1)/YEARM;
9883: if (stepm<=12) stepsize=1;
9884: if(estepm < stepm){
9885: printf ("Problem %d lower than %d\n",estepm, stepm);
9886: }
1.270 brouard 9887: else{
9888: hstepm=estepm;
9889: }
9890: if(estepm > stepm){ /* Yes every two year */
9891: stepsize=2;
9892: }
1.296 brouard 9893: hstepm=hstepm/stepm;
1.126 brouard 9894:
1.296 brouard 9895:
9896: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
9897: /* fractional in yp1 *\/ */
9898: /* aintmean=yp; */
9899: /* yp2=modf((yp1*12),&yp); */
9900: /* mintmean=yp; */
9901: /* yp1=modf((yp2*30.5),&yp); */
9902: /* jintmean=yp; */
9903: /* if(jintmean==0) jintmean=1; */
9904: /* if(mintmean==0) mintmean=1; */
1.126 brouard 9905:
1.296 brouard 9906:
9907: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */
9908: /* date2dmy(dateprojd,&jprojd, &mprojd, &anprojd); */
9909: /* date2dmy(dateprojf,&jprojf, &mprojf, &anprojf); */
1.227 brouard 9910: i1=pow(2,cptcoveff);
1.126 brouard 9911: if (cptcovn < 1){i1=1;}
9912:
1.296 brouard 9913: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.126 brouard 9914:
9915: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 9916:
1.126 brouard 9917: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 9918: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.332 brouard 9919: 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 9920: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 9921: continue;
1.227 brouard 9922: if(invalidvarcomb[k]){
9923: printf("\nCombination (%d) projection ignored because no cases \n",k);
9924: continue;
9925: }
9926: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
9927: for(j=1;j<=cptcoveff;j++) {
1.332 brouard 9928: /* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); */
9929: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.227 brouard 9930: }
1.235 brouard 9931: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 9932: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 9933: }
1.227 brouard 9934: fprintf(ficresf," yearproj age");
9935: for(j=1; j<=nlstate+ndeath;j++){
9936: for(i=1; i<=nlstate;i++)
9937: fprintf(ficresf," p%d%d",i,j);
9938: fprintf(ficresf," wp.%d",j);
9939: }
1.296 brouard 9940: for (yearp=0; yearp<=(anprojf-anprojd);yearp +=stepsize) {
1.227 brouard 9941: fprintf(ficresf,"\n");
1.296 brouard 9942: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jprojd,mprojd,anprojd+yearp);
1.270 brouard 9943: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
9944: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 9945: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
9946: nhstepm = nhstepm/hstepm;
9947: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9948: oldm=oldms;savm=savms;
1.268 brouard 9949: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 9950: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 9951: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 9952: for (h=0; h<=nhstepm; h++){
9953: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 9954: break;
9955: }
9956: }
9957: fprintf(ficresf,"\n");
9958: for(j=1;j<=cptcoveff;j++)
1.332 brouard 9959: /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Tvaraff not correct *\/ */
9960: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /* TnsdVar[Tvaraff] correct */
1.296 brouard 9961: fprintf(ficresf,"%.f %.f ",anprojd+yearp,agec+h*hstepm/YEARM*stepm);
1.268 brouard 9962:
9963: for(j=1; j<=nlstate+ndeath;j++) {
9964: ppij=0.;
9965: for(i=1; i<=nlstate;i++) {
1.278 brouard 9966: if (mobilav>=1)
9967: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
9968: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
9969: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
9970: }
1.268 brouard 9971: fprintf(ficresf," %.3f", p3mat[i][j][h]);
9972: } /* end i */
9973: fprintf(ficresf," %.3f", ppij);
9974: }/* end j */
1.227 brouard 9975: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9976: } /* end agec */
1.266 brouard 9977: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
9978: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 9979: } /* end yearp */
9980: } /* end k */
1.219 brouard 9981:
1.126 brouard 9982: fclose(ficresf);
1.215 brouard 9983: printf("End of Computing forecasting \n");
9984: fprintf(ficlog,"End of Computing forecasting\n");
9985:
1.126 brouard 9986: }
9987:
1.269 brouard 9988: /************** Back Forecasting ******************/
1.296 brouard 9989: /* 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){ */
9990: 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){
9991: /* back1, year, month, day of starting backprojection
1.267 brouard 9992: agemin, agemax range of age
9993: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 9994: anback2 year of end of backprojection (same day and month as back1).
9995: prevacurrent and prev are prevalences.
1.267 brouard 9996: */
9997: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
9998: double agec; /* generic age */
1.302 brouard 9999: double agelim, ppij, ppi, yp,yp1,yp2; /* ,jintmean,mintmean,aintmean;*/
1.267 brouard 10000: double *popeffectif,*popcount;
10001: double ***p3mat;
10002: /* double ***mobaverage; */
10003: char fileresfb[FILENAMELENGTH];
10004:
1.268 brouard 10005: agelim=AGEINF;
1.267 brouard 10006: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
10007: in each health status at the date of interview (if between dateprev1 and dateprev2).
10008: We still use firstpass and lastpass as another selection.
10009: */
10010: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
10011: /* firstpass, lastpass, stepm, weightopt, model); */
10012:
10013: /*Do we need to compute prevalence again?*/
10014:
10015: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
10016:
10017: strcpy(fileresfb,"FB_");
10018: strcat(fileresfb,fileresu);
10019: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
10020: printf("Problem with back forecast resultfile: %s\n", fileresfb);
10021: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
10022: }
10023: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
10024: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
10025:
10026: if (cptcoveff==0) ncodemax[cptcoveff]=1;
10027:
10028:
10029: stepsize=(int) (stepm+YEARM-1)/YEARM;
10030: if (stepm<=12) stepsize=1;
10031: if(estepm < stepm){
10032: printf ("Problem %d lower than %d\n",estepm, stepm);
10033: }
1.270 brouard 10034: else{
10035: hstepm=estepm;
10036: }
10037: if(estepm >= stepm){ /* Yes every two year */
10038: stepsize=2;
10039: }
1.267 brouard 10040:
10041: hstepm=hstepm/stepm;
1.296 brouard 10042: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
10043: /* fractional in yp1 *\/ */
10044: /* aintmean=yp; */
10045: /* yp2=modf((yp1*12),&yp); */
10046: /* mintmean=yp; */
10047: /* yp1=modf((yp2*30.5),&yp); */
10048: /* jintmean=yp; */
10049: /* if(jintmean==0) jintmean=1; */
10050: /* if(mintmean==0) jintmean=1; */
1.267 brouard 10051:
10052: i1=pow(2,cptcoveff);
10053: if (cptcovn < 1){i1=1;}
10054:
1.296 brouard 10055: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
10056: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 10057:
10058: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
10059:
10060: for(nres=1; nres <= nresult; nres++) /* For each resultline */
10061: for(k=1; k<=i1;k++){
10062: if(i1 != 1 && TKresult[nres]!= k)
10063: continue;
10064: if(invalidvarcomb[k]){
10065: printf("\nCombination (%d) projection ignored because no cases \n",k);
10066: continue;
10067: }
1.268 brouard 10068: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.267 brouard 10069: for(j=1;j<=cptcoveff;j++) {
1.332 brouard 10070: fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.267 brouard 10071: }
10072: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10073: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10074: }
10075: fprintf(ficresfb," yearbproj age");
10076: for(j=1; j<=nlstate+ndeath;j++){
10077: for(i=1; i<=nlstate;i++)
1.268 brouard 10078: fprintf(ficresfb," b%d%d",i,j);
10079: fprintf(ficresfb," b.%d",j);
1.267 brouard 10080: }
1.296 brouard 10081: for (yearp=0; yearp>=(anbackf-anbackd);yearp -=stepsize) {
1.267 brouard 10082: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
10083: fprintf(ficresfb,"\n");
1.296 brouard 10084: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jbackd,mbackd,anbackd+yearp);
1.273 brouard 10085: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 10086: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
10087: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 10088: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 10089: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 10090: nhstepm = nhstepm/hstepm;
10091: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10092: oldm=oldms;savm=savms;
1.268 brouard 10093: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 10094: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 10095: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 10096: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
10097: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
10098: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 10099: for (h=0; h<=nhstepm; h++){
1.268 brouard 10100: if (h*hstepm/YEARM*stepm ==-yearp) {
10101: break;
10102: }
10103: }
10104: fprintf(ficresfb,"\n");
10105: for(j=1;j<=cptcoveff;j++)
1.332 brouard 10106: fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.296 brouard 10107: fprintf(ficresfb,"%.f %.f ",anbackd+yearp,agec-h*hstepm/YEARM*stepm);
1.268 brouard 10108: for(i=1; i<=nlstate+ndeath;i++) {
10109: ppij=0.;ppi=0.;
10110: for(j=1; j<=nlstate;j++) {
10111: /* if (mobilav==1) */
1.269 brouard 10112: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
10113: ppi=ppi+prevacurrent[(int)agec][j][k];
10114: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
10115: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 10116: /* else { */
10117: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
10118: /* } */
1.268 brouard 10119: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
10120: } /* end j */
10121: if(ppi <0.99){
10122: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
10123: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
10124: }
10125: fprintf(ficresfb," %.3f", ppij);
10126: }/* end j */
1.267 brouard 10127: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10128: } /* end agec */
10129: } /* end yearp */
10130: } /* end k */
1.217 brouard 10131:
1.267 brouard 10132: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 10133:
1.267 brouard 10134: fclose(ficresfb);
10135: printf("End of Computing Back forecasting \n");
10136: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 10137:
1.267 brouard 10138: }
1.217 brouard 10139:
1.269 brouard 10140: /* Variance of prevalence limit: varprlim */
10141: 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 10142: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 10143:
10144: char fileresvpl[FILENAMELENGTH];
10145: FILE *ficresvpl;
10146: double **oldm, **savm;
10147: double **varpl; /* Variances of prevalence limits by age */
10148: int i1, k, nres, j ;
10149:
10150: strcpy(fileresvpl,"VPL_");
10151: strcat(fileresvpl,fileresu);
10152: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 10153: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 10154: exit(0);
10155: }
1.288 brouard 10156: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
10157: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 10158:
10159: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
10160: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
10161:
10162: i1=pow(2,cptcoveff);
10163: if (cptcovn < 1){i1=1;}
10164:
1.337 brouard 10165: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10166: k=TKresult[nres];
1.338 brouard 10167: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 10168: /* for(k=1; k<=i1;k++){ /\* We find the combination equivalent to result line values of dummies *\/ */
1.269 brouard 10169: if(i1 != 1 && TKresult[nres]!= k)
10170: continue;
10171: fprintf(ficresvpl,"\n#****** ");
10172: printf("\n#****** ");
10173: fprintf(ficlog,"\n#****** ");
1.337 brouard 10174: for(j=1;j<=cptcovs;j++) {
10175: fprintf(ficresvpl,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10176: fprintf(ficlog,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10177: printf("V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10178: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10179: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.269 brouard 10180: }
1.337 brouard 10181: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
10182: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10183: /* fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10184: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10185: /* } */
1.269 brouard 10186: fprintf(ficresvpl,"******\n");
10187: printf("******\n");
10188: fprintf(ficlog,"******\n");
10189:
10190: varpl=matrix(1,nlstate,(int) bage, (int) fage);
10191: oldm=oldms;savm=savms;
10192: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
10193: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
10194: /*}*/
10195: }
10196:
10197: fclose(ficresvpl);
1.288 brouard 10198: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
10199: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 10200:
10201: }
10202: /* Variance of back prevalence: varbprlim */
10203: 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){
10204: /*------- Variance of back (stable) prevalence------*/
10205:
10206: char fileresvbl[FILENAMELENGTH];
10207: FILE *ficresvbl;
10208:
10209: double **oldm, **savm;
10210: double **varbpl; /* Variances of back prevalence limits by age */
10211: int i1, k, nres, j ;
10212:
10213: strcpy(fileresvbl,"VBL_");
10214: strcat(fileresvbl,fileresu);
10215: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
10216: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
10217: exit(0);
10218: }
10219: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
10220: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
10221:
10222:
10223: i1=pow(2,cptcoveff);
10224: if (cptcovn < 1){i1=1;}
10225:
1.337 brouard 10226: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10227: k=TKresult[nres];
1.338 brouard 10228: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 10229: /* for(k=1; k<=i1;k++){ */
10230: /* if(i1 != 1 && TKresult[nres]!= k) */
10231: /* continue; */
1.269 brouard 10232: fprintf(ficresvbl,"\n#****** ");
10233: printf("\n#****** ");
10234: fprintf(ficlog,"\n#****** ");
1.337 brouard 10235: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */
1.338 brouard 10236: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
10237: fprintf(ficresvbl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
10238: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
1.337 brouard 10239: /* for(j=1;j<=cptcoveff;j++) { */
10240: /* fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10241: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10242: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10243: /* } */
10244: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
10245: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10246: /* fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10247: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
1.269 brouard 10248: }
10249: fprintf(ficresvbl,"******\n");
10250: printf("******\n");
10251: fprintf(ficlog,"******\n");
10252:
10253: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
10254: oldm=oldms;savm=savms;
10255:
10256: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
10257: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
10258: /*}*/
10259: }
10260:
10261: fclose(ficresvbl);
10262: printf("done variance-covariance of back prevalence\n");fflush(stdout);
10263: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
10264:
10265: } /* End of varbprlim */
10266:
1.126 brouard 10267: /************** Forecasting *****not tested NB*************/
1.227 brouard 10268: /* 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 10269:
1.227 brouard 10270: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
10271: /* int *popage; */
10272: /* double calagedatem, agelim, kk1, kk2; */
10273: /* double *popeffectif,*popcount; */
10274: /* double ***p3mat,***tabpop,***tabpopprev; */
10275: /* /\* double ***mobaverage; *\/ */
10276: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 10277:
1.227 brouard 10278: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10279: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10280: /* agelim=AGESUP; */
10281: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 10282:
1.227 brouard 10283: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 10284:
10285:
1.227 brouard 10286: /* strcpy(filerespop,"POP_"); */
10287: /* strcat(filerespop,fileresu); */
10288: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
10289: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
10290: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
10291: /* } */
10292: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
10293: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 10294:
1.227 brouard 10295: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 10296:
1.227 brouard 10297: /* /\* if (mobilav!=0) { *\/ */
10298: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
10299: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
10300: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
10301: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
10302: /* /\* } *\/ */
10303: /* /\* } *\/ */
1.126 brouard 10304:
1.227 brouard 10305: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
10306: /* if (stepm<=12) stepsize=1; */
1.126 brouard 10307:
1.227 brouard 10308: /* agelim=AGESUP; */
1.126 brouard 10309:
1.227 brouard 10310: /* hstepm=1; */
10311: /* hstepm=hstepm/stepm; */
1.218 brouard 10312:
1.227 brouard 10313: /* if (popforecast==1) { */
10314: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
10315: /* printf("Problem with population file : %s\n",popfile);exit(0); */
10316: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
10317: /* } */
10318: /* popage=ivector(0,AGESUP); */
10319: /* popeffectif=vector(0,AGESUP); */
10320: /* popcount=vector(0,AGESUP); */
1.126 brouard 10321:
1.227 brouard 10322: /* i=1; */
10323: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 10324:
1.227 brouard 10325: /* imx=i; */
10326: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
10327: /* } */
1.218 brouard 10328:
1.227 brouard 10329: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
10330: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
10331: /* k=k+1; */
10332: /* fprintf(ficrespop,"\n#******"); */
10333: /* for(j=1;j<=cptcoveff;j++) { */
10334: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
10335: /* } */
10336: /* fprintf(ficrespop,"******\n"); */
10337: /* fprintf(ficrespop,"# Age"); */
10338: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
10339: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 10340:
1.227 brouard 10341: /* for (cpt=0; cpt<=0;cpt++) { */
10342: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 10343:
1.227 brouard 10344: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
10345: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
10346: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 10347:
1.227 brouard 10348: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10349: /* oldm=oldms;savm=savms; */
10350: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 10351:
1.227 brouard 10352: /* for (h=0; h<=nhstepm; h++){ */
10353: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
10354: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
10355: /* } */
10356: /* for(j=1; j<=nlstate+ndeath;j++) { */
10357: /* kk1=0.;kk2=0; */
10358: /* for(i=1; i<=nlstate;i++) { */
10359: /* if (mobilav==1) */
10360: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
10361: /* else { */
10362: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
10363: /* } */
10364: /* } */
10365: /* if (h==(int)(calagedatem+12*cpt)){ */
10366: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
10367: /* /\*fprintf(ficrespop," %.3f", kk1); */
10368: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
10369: /* } */
10370: /* } */
10371: /* for(i=1; i<=nlstate;i++){ */
10372: /* kk1=0.; */
10373: /* for(j=1; j<=nlstate;j++){ */
10374: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
10375: /* } */
10376: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
10377: /* } */
1.218 brouard 10378:
1.227 brouard 10379: /* if (h==(int)(calagedatem+12*cpt)) */
10380: /* for(j=1; j<=nlstate;j++) */
10381: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
10382: /* } */
10383: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10384: /* } */
10385: /* } */
1.218 brouard 10386:
1.227 brouard 10387: /* /\******\/ */
1.218 brouard 10388:
1.227 brouard 10389: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
10390: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
10391: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
10392: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
10393: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 10394:
1.227 brouard 10395: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10396: /* oldm=oldms;savm=savms; */
10397: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
10398: /* for (h=0; h<=nhstepm; h++){ */
10399: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
10400: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
10401: /* } */
10402: /* for(j=1; j<=nlstate+ndeath;j++) { */
10403: /* kk1=0.;kk2=0; */
10404: /* for(i=1; i<=nlstate;i++) { */
10405: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
10406: /* } */
10407: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
10408: /* } */
10409: /* } */
10410: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10411: /* } */
10412: /* } */
10413: /* } */
10414: /* } */
1.218 brouard 10415:
1.227 brouard 10416: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 10417:
1.227 brouard 10418: /* if (popforecast==1) { */
10419: /* free_ivector(popage,0,AGESUP); */
10420: /* free_vector(popeffectif,0,AGESUP); */
10421: /* free_vector(popcount,0,AGESUP); */
10422: /* } */
10423: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10424: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10425: /* fclose(ficrespop); */
10426: /* } /\* End of popforecast *\/ */
1.218 brouard 10427:
1.126 brouard 10428: int fileappend(FILE *fichier, char *optionfich)
10429: {
10430: if((fichier=fopen(optionfich,"a"))==NULL) {
10431: printf("Problem with file: %s\n", optionfich);
10432: fprintf(ficlog,"Problem with file: %s\n", optionfich);
10433: return (0);
10434: }
10435: fflush(fichier);
10436: return (1);
10437: }
10438:
10439:
10440: /**************** function prwizard **********************/
10441: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
10442: {
10443:
10444: /* Wizard to print covariance matrix template */
10445:
1.164 brouard 10446: char ca[32], cb[32];
10447: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 10448: int numlinepar;
10449:
10450: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
10451: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
10452: for(i=1; i <=nlstate; i++){
10453: jj=0;
10454: for(j=1; j <=nlstate+ndeath; j++){
10455: if(j==i) continue;
10456: jj++;
10457: /*ca[0]= k+'a'-1;ca[1]='\0';*/
10458: printf("%1d%1d",i,j);
10459: fprintf(ficparo,"%1d%1d",i,j);
10460: for(k=1; k<=ncovmodel;k++){
10461: /* printf(" %lf",param[i][j][k]); */
10462: /* fprintf(ficparo," %lf",param[i][j][k]); */
10463: printf(" 0.");
10464: fprintf(ficparo," 0.");
10465: }
10466: printf("\n");
10467: fprintf(ficparo,"\n");
10468: }
10469: }
10470: printf("# Scales (for hessian or gradient estimation)\n");
10471: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
10472: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
10473: for(i=1; i <=nlstate; i++){
10474: jj=0;
10475: for(j=1; j <=nlstate+ndeath; j++){
10476: if(j==i) continue;
10477: jj++;
10478: fprintf(ficparo,"%1d%1d",i,j);
10479: printf("%1d%1d",i,j);
10480: fflush(stdout);
10481: for(k=1; k<=ncovmodel;k++){
10482: /* printf(" %le",delti3[i][j][k]); */
10483: /* fprintf(ficparo," %le",delti3[i][j][k]); */
10484: printf(" 0.");
10485: fprintf(ficparo," 0.");
10486: }
10487: numlinepar++;
10488: printf("\n");
10489: fprintf(ficparo,"\n");
10490: }
10491: }
10492: printf("# Covariance matrix\n");
10493: /* # 121 Var(a12)\n\ */
10494: /* # 122 Cov(b12,a12) Var(b12)\n\ */
10495: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
10496: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
10497: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
10498: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
10499: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
10500: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
10501: fflush(stdout);
10502: fprintf(ficparo,"# Covariance matrix\n");
10503: /* # 121 Var(a12)\n\ */
10504: /* # 122 Cov(b12,a12) Var(b12)\n\ */
10505: /* # ...\n\ */
10506: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
10507:
10508: for(itimes=1;itimes<=2;itimes++){
10509: jj=0;
10510: for(i=1; i <=nlstate; i++){
10511: for(j=1; j <=nlstate+ndeath; j++){
10512: if(j==i) continue;
10513: for(k=1; k<=ncovmodel;k++){
10514: jj++;
10515: ca[0]= k+'a'-1;ca[1]='\0';
10516: if(itimes==1){
10517: printf("#%1d%1d%d",i,j,k);
10518: fprintf(ficparo,"#%1d%1d%d",i,j,k);
10519: }else{
10520: printf("%1d%1d%d",i,j,k);
10521: fprintf(ficparo,"%1d%1d%d",i,j,k);
10522: /* printf(" %.5le",matcov[i][j]); */
10523: }
10524: ll=0;
10525: for(li=1;li <=nlstate; li++){
10526: for(lj=1;lj <=nlstate+ndeath; lj++){
10527: if(lj==li) continue;
10528: for(lk=1;lk<=ncovmodel;lk++){
10529: ll++;
10530: if(ll<=jj){
10531: cb[0]= lk +'a'-1;cb[1]='\0';
10532: if(ll<jj){
10533: if(itimes==1){
10534: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10535: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10536: }else{
10537: printf(" 0.");
10538: fprintf(ficparo," 0.");
10539: }
10540: }else{
10541: if(itimes==1){
10542: printf(" Var(%s%1d%1d)",ca,i,j);
10543: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
10544: }else{
10545: printf(" 0.");
10546: fprintf(ficparo," 0.");
10547: }
10548: }
10549: }
10550: } /* end lk */
10551: } /* end lj */
10552: } /* end li */
10553: printf("\n");
10554: fprintf(ficparo,"\n");
10555: numlinepar++;
10556: } /* end k*/
10557: } /*end j */
10558: } /* end i */
10559: } /* end itimes */
10560:
10561: } /* end of prwizard */
10562: /******************* Gompertz Likelihood ******************************/
10563: double gompertz(double x[])
10564: {
1.302 brouard 10565: double A=0.0,B=0.,L=0.0,sump=0.,num=0.;
1.126 brouard 10566: int i,n=0; /* n is the size of the sample */
10567:
1.220 brouard 10568: for (i=1;i<=imx ; i++) {
1.126 brouard 10569: sump=sump+weight[i];
10570: /* sump=sump+1;*/
10571: num=num+1;
10572: }
1.302 brouard 10573: L=0.0;
10574: /* agegomp=AGEGOMP; */
1.126 brouard 10575: /* for (i=0; i<=imx; i++)
10576: 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]);*/
10577:
1.302 brouard 10578: for (i=1;i<=imx ; i++) {
10579: /* mu(a)=mu(agecomp)*exp(teta*(age-agegomp))
10580: mu(a)=x[1]*exp(x[2]*(age-agegomp)); x[1] and x[2] are per year.
10581: * L= Product mu(agedeces)exp(-\int_ageexam^agedc mu(u) du ) for a death between agedc (in month)
10582: * and agedc +1 month, cens[i]=0: log(x[1]/YEARM)
10583: * +
10584: * exp(-\int_ageexam^agecens mu(u) du ) when censored, cens[i]=1
10585: */
10586: if (wav[i] > 1 || agedc[i] < AGESUP) {
10587: if (cens[i] == 1){
10588: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
10589: } else if (cens[i] == 0){
1.126 brouard 10590: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
1.302 brouard 10591: +log(x[1]/YEARM) +x[2]*(agedc[i]-agegomp)+log(YEARM);
10592: } else
10593: printf("Gompertz cens[%d] neither 1 nor 0\n",i);
1.126 brouard 10594: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
1.302 brouard 10595: L=L+A*weight[i];
1.126 brouard 10596: /* 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 10597: }
10598: }
1.126 brouard 10599:
1.302 brouard 10600: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
1.126 brouard 10601:
10602: return -2*L*num/sump;
10603: }
10604:
1.136 brouard 10605: #ifdef GSL
10606: /******************* Gompertz_f Likelihood ******************************/
10607: double gompertz_f(const gsl_vector *v, void *params)
10608: {
1.302 brouard 10609: double A=0.,B=0.,LL=0.0,sump=0.,num=0.;
1.136 brouard 10610: double *x= (double *) v->data;
10611: int i,n=0; /* n is the size of the sample */
10612:
10613: for (i=0;i<=imx-1 ; i++) {
10614: sump=sump+weight[i];
10615: /* sump=sump+1;*/
10616: num=num+1;
10617: }
10618:
10619:
10620: /* for (i=0; i<=imx; i++)
10621: 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]);*/
10622: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
10623: for (i=1;i<=imx ; i++)
10624: {
10625: if (cens[i] == 1 && wav[i]>1)
10626: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
10627:
10628: if (cens[i] == 0 && wav[i]>1)
10629: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
10630: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
10631:
10632: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
10633: if (wav[i] > 1 ) { /* ??? */
10634: LL=LL+A*weight[i];
10635: /* 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]);*/
10636: }
10637: }
10638:
10639: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
10640: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
10641:
10642: return -2*LL*num/sump;
10643: }
10644: #endif
10645:
1.126 brouard 10646: /******************* Printing html file ***********/
1.201 brouard 10647: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 10648: int lastpass, int stepm, int weightopt, char model[],\
10649: int imx, double p[],double **matcov,double agemortsup){
10650: int i,k;
10651:
10652: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
10653: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
10654: for (i=1;i<=2;i++)
10655: 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 10656: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 10657: fprintf(fichtm,"</ul>");
10658:
10659: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
10660:
10661: 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>");
10662:
10663: for (k=agegomp;k<(agemortsup-2);k++)
10664: 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]);
10665:
10666:
10667: fflush(fichtm);
10668: }
10669:
10670: /******************* Gnuplot file **************/
1.201 brouard 10671: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 10672:
10673: char dirfileres[132],optfileres[132];
1.164 brouard 10674:
1.126 brouard 10675: int ng;
10676:
10677:
10678: /*#ifdef windows */
10679: fprintf(ficgp,"cd \"%s\" \n",pathc);
10680: /*#endif */
10681:
10682:
10683: strcpy(dirfileres,optionfilefiname);
10684: strcpy(optfileres,"vpl");
1.199 brouard 10685: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 10686: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 10687: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 10688: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 10689: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
10690:
10691: }
10692:
1.136 brouard 10693: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
10694: {
1.126 brouard 10695:
1.136 brouard 10696: /*-------- data file ----------*/
10697: FILE *fic;
10698: char dummy[]=" ";
1.240 brouard 10699: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 10700: int lstra;
1.136 brouard 10701: int linei, month, year,iout;
1.302 brouard 10702: int noffset=0; /* This is the offset if BOM data file */
1.136 brouard 10703: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 10704: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 10705: char *stratrunc;
1.223 brouard 10706:
1.349 ! brouard 10707: /* DummyV=ivector(-1,NCOVMAX); /\* 1 to 3 *\/ */
! 10708: /* FixedV=ivector(-1,NCOVMAX); /\* 1 to 3 *\/ */
1.339 brouard 10709:
10710: ncovcolt=ncovcol+nqv+ntv+nqtv; /* total of covariates in the data, not in the model equation */
10711:
1.136 brouard 10712: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 10713: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
10714: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 10715: }
1.126 brouard 10716:
1.302 brouard 10717: /* Is it a BOM UTF-8 Windows file? */
10718: /* First data line */
10719: linei=0;
10720: while(fgets(line, MAXLINE, fic)) {
10721: noffset=0;
10722: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
10723: {
10724: noffset=noffset+3;
10725: printf("# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);fflush(stdout);
10726: fprintf(ficlog,"# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);
10727: fflush(ficlog); return 1;
10728: }
10729: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
10730: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
10731: {
10732: noffset=noffset+2;
1.304 brouard 10733: 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);
10734: 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 10735: fflush(ficlog); return 1;
10736: }
10737: else if( line[0] == 0 && line[1] == 0)
10738: {
10739: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
10740: noffset=noffset+4;
1.304 brouard 10741: 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);
10742: 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 10743: fflush(ficlog); return 1;
10744: }
10745: } else{
10746: ;/*printf(" Not a BOM file\n");*/
10747: }
10748: /* If line starts with a # it is a comment */
10749: if (line[noffset] == '#') {
10750: linei=linei+1;
10751: break;
10752: }else{
10753: break;
10754: }
10755: }
10756: fclose(fic);
10757: if((fic=fopen(datafile,"r"))==NULL) {
10758: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
10759: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
10760: }
10761: /* Not a Bom file */
10762:
1.136 brouard 10763: i=1;
10764: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
10765: linei=linei+1;
10766: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
10767: if(line[j] == '\t')
10768: line[j] = ' ';
10769: }
10770: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
10771: ;
10772: };
10773: line[j+1]=0; /* Trims blanks at end of line */
10774: if(line[0]=='#'){
10775: fprintf(ficlog,"Comment line\n%s\n",line);
10776: printf("Comment line\n%s\n",line);
10777: continue;
10778: }
10779: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 10780: strcpy(line, linetmp);
1.223 brouard 10781:
10782: /* Loops on waves */
10783: for (j=maxwav;j>=1;j--){
10784: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 10785: cutv(stra, strb, line, ' ');
10786: if(strb[0]=='.') { /* Missing value */
10787: lval=-1;
10788: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
1.341 brouard 10789: cotvar[j][ncovcol+nqv+ntv+iv][i]=-1; /* For performance reasons */
1.238 brouard 10790: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
10791: 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);
10792: 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);
10793: return 1;
10794: }
10795: }else{
10796: errno=0;
10797: /* what_kind_of_number(strb); */
10798: dval=strtod(strb,&endptr);
10799: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
10800: /* if(strb != endptr && *endptr == '\0') */
10801: /* dval=dlval; */
10802: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
10803: if( strb[0]=='\0' || (*endptr != '\0')){
10804: 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);
10805: 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);
10806: return 1;
10807: }
10808: cotqvar[j][iv][i]=dval;
1.341 brouard 10809: cotvar[j][ncovcol+nqv+ntv+iv][i]=dval; /* because cotvar starts now at first ntv */
1.238 brouard 10810: }
10811: strcpy(line,stra);
1.223 brouard 10812: }/* end loop ntqv */
1.225 brouard 10813:
1.223 brouard 10814: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 10815: cutv(stra, strb, line, ' ');
10816: if(strb[0]=='.') { /* Missing value */
10817: lval=-1;
10818: }else{
10819: errno=0;
10820: lval=strtol(strb,&endptr,10);
10821: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
10822: if( strb[0]=='\0' || (*endptr != '\0')){
10823: 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);
10824: 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);
10825: return 1;
10826: }
10827: }
10828: if(lval <-1 || lval >1){
10829: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10830: 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 10831: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10832: For example, for multinomial values like 1, 2 and 3,\n \
10833: build V1=0 V2=0 for the reference value (1),\n \
10834: V1=1 V2=0 for (2) \n \
1.223 brouard 10835: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10836: output of IMaCh is often meaningless.\n \
1.319 brouard 10837: Exiting.\n",lval,linei, i,line,iv,j);
1.238 brouard 10838: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10839: 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 10840: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10841: For example, for multinomial values like 1, 2 and 3,\n \
10842: build V1=0 V2=0 for the reference value (1),\n \
10843: V1=1 V2=0 for (2) \n \
1.223 brouard 10844: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10845: output of IMaCh is often meaningless.\n \
1.319 brouard 10846: Exiting.\n",lval,linei, i,line,iv,j);fflush(ficlog);
1.238 brouard 10847: return 1;
10848: }
1.341 brouard 10849: cotvar[j][ncovcol+nqv+iv][i]=(double)(lval);
1.238 brouard 10850: strcpy(line,stra);
1.223 brouard 10851: }/* end loop ntv */
1.225 brouard 10852:
1.223 brouard 10853: /* Statuses at wave */
1.137 brouard 10854: cutv(stra, strb, line, ' ');
1.223 brouard 10855: if(strb[0]=='.') { /* Missing value */
1.238 brouard 10856: lval=-1;
1.136 brouard 10857: }else{
1.238 brouard 10858: errno=0;
10859: lval=strtol(strb,&endptr,10);
10860: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
1.347 brouard 10861: if( strb[0]=='\0' || (*endptr != '\0' )){
10862: 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);
10863: 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);
10864: return 1;
10865: }else if( lval==0 || lval > nlstate+ndeath){
1.348 brouard 10866: printf("Error in data around '%s' at line number %d for individual %d, '%s'\n Should be a state at wave %d. A state should be 1 to %d and not %ld.\n Fix your data file '%s'! Exiting.\n", strb, linei,i,line,j,nlstate+ndeath, lval, datafile);fflush(stdout);
10867: fprintf(ficlog,"Error in data around '%s' at line number %d for individual %d, '%s'\n Should be a state at wave %d. A state should be 1 to %d and not %ld.\n Fix your data file '%s'! Exiting.\n", strb, linei,i,line,j,nlstate+ndeath, lval, datafile); fflush(ficlog);
1.238 brouard 10868: return 1;
10869: }
1.136 brouard 10870: }
1.225 brouard 10871:
1.136 brouard 10872: s[j][i]=lval;
1.225 brouard 10873:
1.223 brouard 10874: /* Date of Interview */
1.136 brouard 10875: strcpy(line,stra);
10876: cutv(stra, strb,line,' ');
1.169 brouard 10877: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10878: }
1.169 brouard 10879: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 10880: month=99;
10881: year=9999;
1.136 brouard 10882: }else{
1.225 brouard 10883: 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);
10884: 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);
10885: return 1;
1.136 brouard 10886: }
10887: anint[j][i]= (double) year;
1.302 brouard 10888: mint[j][i]= (double)month;
10889: /* if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){ */
10890: /* 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]); */
10891: /* 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]); */
10892: /* } */
1.136 brouard 10893: strcpy(line,stra);
1.223 brouard 10894: } /* End loop on waves */
1.225 brouard 10895:
1.223 brouard 10896: /* Date of death */
1.136 brouard 10897: cutv(stra, strb,line,' ');
1.169 brouard 10898: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10899: }
1.169 brouard 10900: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 10901: month=99;
10902: year=9999;
10903: }else{
1.141 brouard 10904: 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 10905: 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);
10906: return 1;
1.136 brouard 10907: }
10908: andc[i]=(double) year;
10909: moisdc[i]=(double) month;
10910: strcpy(line,stra);
10911:
1.223 brouard 10912: /* Date of birth */
1.136 brouard 10913: cutv(stra, strb,line,' ');
1.169 brouard 10914: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10915: }
1.169 brouard 10916: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 10917: month=99;
10918: year=9999;
10919: }else{
1.141 brouard 10920: 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);
10921: 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 10922: return 1;
1.136 brouard 10923: }
10924: if (year==9999) {
1.141 brouard 10925: 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);
10926: 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 10927: return 1;
10928:
1.136 brouard 10929: }
10930: annais[i]=(double)(year);
1.302 brouard 10931: moisnais[i]=(double)(month);
10932: for (j=1;j<=maxwav;j++){
10933: if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){
10934: 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]);
10935: 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]);
10936: }
10937: }
10938:
1.136 brouard 10939: strcpy(line,stra);
1.225 brouard 10940:
1.223 brouard 10941: /* Sample weight */
1.136 brouard 10942: cutv(stra, strb,line,' ');
10943: errno=0;
10944: dval=strtod(strb,&endptr);
10945: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 10946: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
10947: 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 10948: fflush(ficlog);
10949: return 1;
10950: }
10951: weight[i]=dval;
10952: strcpy(line,stra);
1.225 brouard 10953:
1.223 brouard 10954: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
10955: cutv(stra, strb, line, ' ');
10956: if(strb[0]=='.') { /* Missing value */
1.225 brouard 10957: lval=-1;
1.311 brouard 10958: coqvar[iv][i]=NAN;
10959: covar[ncovcol+iv][i]=NAN; /* including qvar in standard covar for performance reasons */
1.223 brouard 10960: }else{
1.225 brouard 10961: errno=0;
10962: /* what_kind_of_number(strb); */
10963: dval=strtod(strb,&endptr);
10964: /* if(strb != endptr && *endptr == '\0') */
10965: /* dval=dlval; */
10966: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
10967: if( strb[0]=='\0' || (*endptr != '\0')){
10968: 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);
10969: 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);
10970: return 1;
10971: }
10972: coqvar[iv][i]=dval;
1.226 brouard 10973: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 10974: }
10975: strcpy(line,stra);
10976: }/* end loop nqv */
1.136 brouard 10977:
1.223 brouard 10978: /* Covariate values */
1.136 brouard 10979: for (j=ncovcol;j>=1;j--){
10980: cutv(stra, strb,line,' ');
1.223 brouard 10981: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 10982: lval=-1;
1.136 brouard 10983: }else{
1.225 brouard 10984: errno=0;
10985: lval=strtol(strb,&endptr,10);
10986: if( strb[0]=='\0' || (*endptr != '\0')){
10987: 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);
10988: 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);
10989: return 1;
10990: }
1.136 brouard 10991: }
10992: if(lval <-1 || lval >1){
1.225 brouard 10993: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 10994: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
10995: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 10996: For example, for multinomial values like 1, 2 and 3,\n \
10997: build V1=0 V2=0 for the reference value (1),\n \
10998: V1=1 V2=0 for (2) \n \
1.136 brouard 10999: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 11000: output of IMaCh is often meaningless.\n \
1.136 brouard 11001: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 11002: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 11003: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
11004: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 11005: For example, for multinomial values like 1, 2 and 3,\n \
11006: build V1=0 V2=0 for the reference value (1),\n \
11007: V1=1 V2=0 for (2) \n \
1.136 brouard 11008: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 11009: output of IMaCh is often meaningless.\n \
1.136 brouard 11010: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 11011: return 1;
1.136 brouard 11012: }
11013: covar[j][i]=(double)(lval);
11014: strcpy(line,stra);
11015: }
11016: lstra=strlen(stra);
1.225 brouard 11017:
1.136 brouard 11018: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
11019: stratrunc = &(stra[lstra-9]);
11020: num[i]=atol(stratrunc);
11021: }
11022: else
11023: num[i]=atol(stra);
11024: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
11025: 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;}*/
11026:
11027: i=i+1;
11028: } /* End loop reading data */
1.225 brouard 11029:
1.136 brouard 11030: *imax=i-1; /* Number of individuals */
11031: fclose(fic);
1.225 brouard 11032:
1.136 brouard 11033: return (0);
1.164 brouard 11034: /* endread: */
1.225 brouard 11035: printf("Exiting readdata: ");
11036: fclose(fic);
11037: return (1);
1.223 brouard 11038: }
1.126 brouard 11039:
1.234 brouard 11040: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 11041: char *p1 = *stri, *p2 = *stri;
1.235 brouard 11042: while (*p2 == ' ')
1.234 brouard 11043: p2++;
11044: /* while ((*p1++ = *p2++) !=0) */
11045: /* ; */
11046: /* do */
11047: /* while (*p2 == ' ') */
11048: /* p2++; */
11049: /* while (*p1++ == *p2++); */
11050: *stri=p2;
1.145 brouard 11051: }
11052:
1.330 brouard 11053: int decoderesult( char resultline[], int nres)
1.230 brouard 11054: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
11055: {
1.235 brouard 11056: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 11057: char resultsav[MAXLINE];
1.330 brouard 11058: /* int resultmodel[MAXLINE]; */
1.334 brouard 11059: /* int modelresult[MAXLINE]; */
1.230 brouard 11060: char stra[80], strb[80], strc[80], strd[80],stre[80];
11061:
1.234 brouard 11062: removefirstspace(&resultline);
1.332 brouard 11063: printf("decoderesult:%s\n",resultline);
1.230 brouard 11064:
1.332 brouard 11065: strcpy(resultsav,resultline);
1.342 brouard 11066: /* printf("Decoderesult resultsav=\"%s\" resultline=\"%s\"\n", resultsav, resultline); */
1.230 brouard 11067: if (strlen(resultsav) >1){
1.334 brouard 11068: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' in this resultline */
1.230 brouard 11069: }
1.253 brouard 11070: if(j == 0){ /* Resultline but no = */
11071: TKresult[nres]=0; /* Combination for the nresult and the model */
11072: return (0);
11073: }
1.234 brouard 11074: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
1.334 brouard 11075: 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);
11076: 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 11077: /* return 1;*/
1.234 brouard 11078: }
1.334 brouard 11079: for(k=1; k<=j;k++){ /* Loop on any covariate of the RESULT LINE */
1.234 brouard 11080: if(nbocc(resultsav,'=') >1){
1.318 brouard 11081: 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 11082: /* 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 11083: cutl(strc,strd,strb,'='); /* strb:"V4=1" strc="1" strd="V4" */
1.332 brouard 11084: /* If a blank, then strc="V4=" and strd='\0' */
11085: if(strc[0]=='\0'){
11086: printf("Error in resultline, probably a blank after the \"%s\", \"result:%s\", stra=\"%s\" resultsav=\"%s\"\n",strb,resultline, stra, resultsav);
11087: fprintf(ficlog,"Error in resultline, probably a blank after the \"V%s=\", resultline=%s\n",strb,resultline);
11088: return 1;
11089: }
1.234 brouard 11090: }else
11091: cutl(strc,strd,resultsav,'=');
1.318 brouard 11092: Tvalsel[k]=atof(strc); /* 1 */ /* Tvalsel of k is the float value of the kth covariate appearing in this result line */
1.234 brouard 11093:
1.230 brouard 11094: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
1.318 brouard 11095: 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 11096: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
11097: /* cptcovsel++; */
11098: if (nbocc(stra,'=') >0)
11099: strcpy(resultsav,stra); /* and analyzes it */
11100: }
1.235 brouard 11101: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 11102: /* 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 11103: 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 11104: if(Typevar[k1]==0){ /* Single covariate in model */
11105: /* 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.234 brouard 11106: match=0;
1.318 brouard 11107: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
11108: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 11109: modelresult[nres][k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.318 brouard 11110: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
1.234 brouard 11111: break;
11112: }
11113: }
11114: if(match == 0){
1.338 brouard 11115: 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]);
11116: 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 11117: return 1;
1.234 brouard 11118: }
1.332 brouard 11119: }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*/
11120: /* We feed resultmodel[k1]=k2; */
11121: match=0;
11122: 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 */
11123: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 11124: 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 11125: resultmodel[nres][k1]=k2; /* Added here */
1.342 brouard 11126: /* printf("Decoderesult first modelresult[k2=%d]=%d (k1) V%d*AGE\n",k2,k1,Tvar[k1]); */
1.332 brouard 11127: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
11128: break;
11129: }
11130: }
11131: if(match == 0){
1.338 brouard 11132: 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]);
11133: 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 11134: return 1;
11135: }
1.349 ! brouard 11136: }else if(Typevar[k1]==2 || Typevar[k1]==3){ /* Product with or without age. We want to get the position in the resultline of the product in the model line*/
1.332 brouard 11137: /* resultmodel[nres][of such a Vn * Vm product k1] is not unique, so can't exist, we feed Tvard[k1][1] and [2] */
11138: match=0;
1.342 brouard 11139: /* 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 11140: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
11141: if(Tvardk[k1][1]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
11142: /* modelresult[k2]=k1; */
1.342 brouard 11143: /* printf("Decoderesult first Product modelresult[k2=%d]=%d (k1) V%d * \n",k2,k1,Tvarsel[k2]); */
1.332 brouard 11144: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
11145: }
11146: }
11147: if(match == 0){
1.349 ! brouard 11148: printf("Error in result line (Product without age first variable or double product with age): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][1], resultline, model);
! 11149: fprintf(ficlog,"Error in result line (Product without age first variable or double product with age): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][1], resultline, model);
1.332 brouard 11150: return 1;
11151: }
11152: match=0;
11153: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
11154: if(Tvardk[k1][2]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
11155: /* modelresult[k2]=k1;*/
1.342 brouard 11156: /* printf("Decoderesult second Product modelresult[k2=%d]=%d (k1) * V%d \n ",k2,k1,Tvarsel[k2]); */
1.332 brouard 11157: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
11158: break;
11159: }
11160: }
11161: if(match == 0){
1.349 ! brouard 11162: printf("Error in result line (Product without age second variable or double product with age): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][2], resultline, model);
! 11163: fprintf(ficlog,"Error in result line (Product without age second variable or double product with age): V%d is missing in result : %s according to model=1+age+%s\n",Tvardk[k1][2], resultline, model);
1.332 brouard 11164: return 1;
11165: }
11166: }/* End of testing */
1.333 brouard 11167: }/* End loop cptcovt */
1.235 brouard 11168: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 11169: /* Feeds resultmodel[nres][k1]=k2 for single covariate (k1) in the model equation */
1.334 brouard 11170: 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)
11171: * Loop on resultline variables: result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 11172: match=0;
1.318 brouard 11173: 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 11174: if(Typevar[k1]==0){ /* Single only */
1.349 ! brouard 11175: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 What if a product? */
1.330 brouard 11176: 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 11177: 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 11178: ++match;
11179: }
11180: }
11181: }
11182: if(match == 0){
1.338 brouard 11183: printf("Error in result line: variable V%d is missing in model; result: %s, model=1+age+%s\n",Tvarsel[k2], resultline, model);
11184: 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 11185: return 1;
1.234 brouard 11186: }else if(match > 1){
1.338 brouard 11187: printf("Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
11188: fprintf(ficlog,"Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
1.310 brouard 11189: return 1;
1.234 brouard 11190: }
11191: }
1.334 brouard 11192: /* cptcovres=j /\* Number of variables in the resultline is equal to cptcovs and thus useless *\/ */
1.234 brouard 11193: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 11194: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.330 brouard 11195: /* nres=1st result line: V4=1 V5=25.1 V3=0 V2=8 V1=1 */
11196: /* 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*/
11197: /* nres=2nd result line: V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.235 brouard 11198: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
11199: /* 1 0 0 0 */
11200: /* 2 1 0 0 */
11201: /* 3 0 1 0 */
1.330 brouard 11202: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 (nres=2)*/
1.235 brouard 11203: /* 5 0 0 1 */
1.330 brouard 11204: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 (nres=1)*/
1.235 brouard 11205: /* 7 0 1 1 */
11206: /* 8 1 1 1 */
1.237 brouard 11207: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
11208: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
11209: /* V5*age V5 known which value for nres? */
11210: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.334 brouard 11211: 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.
11212: * loop on position k1 in the MODEL LINE */
1.331 brouard 11213: /* k counting number of combination of single dummies in the equation model */
11214: /* k4 counting single dummies in the equation model */
11215: /* k4q counting single quantitatives in the equation model */
1.344 brouard 11216: 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 11217: /* 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 11218: /* 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 11219: /* Value in the (current nres) resultline of the variable at the k1th position in the model equation resultmodel[nres][k1]= k3 */
1.332 brouard 11220: /* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline */
11221: /* k3 is the position in the nres result line of the k1th variable of the model equation */
11222: /* Tvarsel[k3]: Name of the variable at the k3th position in the result line. */
11223: /* Tvalsel[k3]: Value of the variable at the k3th position in the result line. */
11224: /* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.334 brouard 11225: /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 11226: /* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1.330 brouard 11227: /* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.332 brouard 11228: k3= resultmodel[nres][k1]; /* From position k1 in model get position k3 in result line */
11229: /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
11230: 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 11231: 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 11232: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][Name]=Value; stores the value into the name of the variable. */
1.332 brouard 11233: /* Tinvresult[nres][4]=1 */
1.334 brouard 11234: /* Tresult[nres][k4+1]=Tvalsel[k3];/\* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) *\/ */
11235: Tresult[nres][k3]=Tvalsel[k3];/* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) */
11236: /* Tvresult[nres][k4+1]=(int)Tvarsel[k3];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
11237: Tvresult[nres][k3]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
1.237 brouard 11238: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.334 brouard 11239: precov[nres][k1]=Tvalsel[k3]; /* Value from resultline of the variable at the k1 position in the model */
1.342 brouard 11240: /* 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 11241: k4++;;
1.331 brouard 11242: }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Quantitative and single */
1.330 brouard 11243: /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.332 brouard 11244: /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.330 brouard 11245: /* Tqinvresult[nres][Name of a quantitative variable]= value of the variable in the result line */
1.332 brouard 11246: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 5 =k3q */
11247: k2q=(int)Tvarsel[k3q]; /* Name of variable at k3q th position in the resultline */
11248: /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.334 brouard 11249: /* Tqresult[nres][k4q+1]=Tvalsel[k3q]; /\* Tqresult[nres][1]=25.1 *\/ */
11250: /* Tvresult[nres][k4q+1]=(int)Tvarsel[k3q];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
11251: /* Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /\* Tvqresult[nres][1]=5 *\/ */
11252: Tqresult[nres][k3q]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
11253: Tvresult[nres][k3q]=(int)Tvarsel[k3q];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
11254: Tvqresult[nres][k3q]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
1.237 brouard 11255: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.330 brouard 11256: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.332 brouard 11257: precov[nres][k1]=Tvalsel[k3q];
1.342 brouard 11258: /* 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 11259: k4q++;;
1.331 brouard 11260: }else if( Dummy[k1]==2 ){ /* For dummy with age product */
11261: /* Tvar[k1]; */ /* Age variable */
1.332 brouard 11262: /* Wrong we want the value of variable name Tvar[k1] */
11263:
11264: k3= resultmodel[nres][k1]; /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
1.331 brouard 11265: 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 11266: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][4]=1 */
1.332 brouard 11267: precov[nres][k1]=Tvalsel[k3];
1.342 brouard 11268: /* 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 11269: }else if( Dummy[k1]==3 ){ /* For quant with age product */
1.332 brouard 11270: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 25.1=k3q */
1.331 brouard 11271: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.334 brouard 11272: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* TinvDoQresult[nres][5]=25.1 */
1.332 brouard 11273: precov[nres][k1]=Tvalsel[k3q];
1.342 brouard 11274: /* printf("Decoderesult Quantitative with age nres=%d, k1=%d, precov[nres=%d][k1=%d]=%f Tvar[%d]=V%d V(k2q=%d)= Tvarsel[%d]=%d, Tvalsel[%d]=%f\n",nres, k1, nres, k1,precov[nres][k1], k1, Tvar[k1], k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]); */
1.349 ! brouard 11275: }else if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
1.332 brouard 11276: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
1.342 brouard 11277: /* 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 11278: }else{
1.332 brouard 11279: printf("Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
11280: fprintf(ficlog,"Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
1.235 brouard 11281: }
11282: }
1.234 brouard 11283:
1.334 brouard 11284: TKresult[nres]=++k; /* Number of combinations of dummies for the nresult and the model =Tvalsel[k3]*pow(2,k4) + 1*/
1.230 brouard 11285: return (0);
11286: }
1.235 brouard 11287:
1.230 brouard 11288: int decodemodel( char model[], int lastobs)
11289: /**< This routine decodes the model and returns:
1.224 brouard 11290: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
11291: * - nagesqr = 1 if age*age in the model, otherwise 0.
11292: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
11293: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
11294: * - cptcovage number of covariates with age*products =2
11295: * - cptcovs number of simple covariates
1.339 brouard 11296: * ncovcolt=ncovcol+nqv+ntv+nqtv total of covariates in the data, not in the model equation
1.224 brouard 11297: * - 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 11298: * which is a new column after the 9 (ncovcol+nqv+ntv+nqtv) variables.
1.319 brouard 11299: * - if k is a product Vn*Vm, covar[k][i] is filled with correct values for each individual
1.224 brouard 11300: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
11301: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
11302: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
11303: */
1.319 brouard 11304: /* 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 11305: {
1.238 brouard 11306: int i, j, k, ks, v;
1.349 ! brouard 11307: int n,m;
! 11308: int j1, k1, k11, k12, k2, k3, k4;
! 11309: char modelsav[300];
! 11310: char stra[300], strb[300], strc[300], strd[300],stre[300],strf[300];
1.187 brouard 11311: char *strpt;
1.349 ! brouard 11312: int **existcomb;
! 11313:
! 11314: existcomb=imatrix(1,NCOVMAX,1,NCOVMAX);
! 11315: for(i=1;i<=NCOVMAX;i++)
! 11316: for(j=1;j<=NCOVMAX;j++)
! 11317: existcomb[i][j]=0;
! 11318:
1.145 brouard 11319: /*removespace(model);*/
1.136 brouard 11320: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.349 ! brouard 11321: j=0, j1=0, k1=0, k12=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 11322: if (strstr(model,"AGE") !=0){
1.192 brouard 11323: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
11324: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 11325: return 1;
11326: }
1.141 brouard 11327: if (strstr(model,"v") !=0){
1.338 brouard 11328: printf("Error. 'v' must be in upper case 'V' model=1+age+%s ",model);
11329: fprintf(ficlog,"Error. 'v' must be in upper case model=1+age+%s ",model);fflush(ficlog);
1.141 brouard 11330: return 1;
11331: }
1.187 brouard 11332: strcpy(modelsav,model);
11333: if ((strpt=strstr(model,"age*age")) !=0){
1.338 brouard 11334: printf(" strpt=%s, model=1+age+%s\n",strpt, model);
1.187 brouard 11335: if(strpt != model){
1.338 brouard 11336: printf("Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 11337: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 11338: corresponding column of parameters.\n",model);
1.338 brouard 11339: fprintf(ficlog,"Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 11340: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 11341: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 11342: return 1;
1.225 brouard 11343: }
1.187 brouard 11344: nagesqr=1;
11345: if (strstr(model,"+age*age") !=0)
1.234 brouard 11346: substrchaine(modelsav, model, "+age*age");
1.187 brouard 11347: else if (strstr(model,"age*age+") !=0)
1.234 brouard 11348: substrchaine(modelsav, model, "age*age+");
1.187 brouard 11349: else
1.234 brouard 11350: substrchaine(modelsav, model, "age*age");
1.187 brouard 11351: }else
11352: nagesqr=0;
1.349 ! brouard 11353: if (strlen(modelsav) >1){ /* V2 +V3 +V4 +V6 +V7 +V6*V2 +V7*V2 +V6*V3 +V7*V3 +V6*V4 +V7*V4 +age*V2 +age*V3 +age*V4 +age*V6 +age*V7 +age*V6*V2 +V7*V2 +age*V6*V3 +age*V7*V3 +age*V6*V4 +age*V7*V4 */
1.187 brouard 11354: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
11355: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.349 ! brouard 11356: cptcovs=j+1-j1; /**< Number of simple covariates V1 +V1*age +V3 +V3*V4 +age*age => V1 + V3 =4+1-3=2 */
1.187 brouard 11357: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 11358: * cst, age and age*age
11359: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
11360: /* including age products which are counted in cptcovage.
11361: * but the covariates which are products must be treated
11362: * separately: ncovn=4- 2=2 (V1+V3). */
1.349 ! brouard 11363: cptcovprod=0; /**< Number of products V1*V2 +v3*age = 2 */
! 11364: cptcovdageprod=0; /* Number of doouble products with age age*Vn*VM or Vn*age*Vm or Vn*Vm*age */
1.187 brouard 11365: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.349 ! brouard 11366: cptcovprodage=0;
! 11367: /* cptcovprodage=nboccstr(modelsav,"age");*/
1.225 brouard 11368:
1.187 brouard 11369: /* Design
11370: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
11371: * < ncovcol=8 >
11372: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
11373: * k= 1 2 3 4 5 6 7 8
11374: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
1.345 brouard 11375: * covar[k,i], are for fixed covariates, value of kth covariate if not including age for individual i:
1.224 brouard 11376: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
11377: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 11378: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
11379: * Tage[++cptcovage]=k
1.345 brouard 11380: * if products, new covar are created after ncovcol + nqv (quanti fixed) with k1
1.187 brouard 11381: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
11382: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
11383: * 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
11384: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
11385: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
11386: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
1.345 brouard 11387: * < ncovcol=8 8 fixed covariate. Additional starts at 9 (V5*V6) and 10(V7*V8) >
1.187 brouard 11388: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
11389: * k= 1 2 3 4 5 6 7 8 9 10 11 12
1.345 brouard 11390: * Tvard[k]= 2 1 3 3 10 11 8 8 5 6 7 8
11391: * p Tvar[1]@12={2, 1, 3, 3, 9, 10, 8, 8}
1.187 brouard 11392: * p Tprod[1]@2={ 6, 5}
11393: *p Tvard[1][1]@4= {7, 8, 5, 6}
11394: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
11395: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
1.319 brouard 11396: *How to reorganize? Tvars(orted)
1.187 brouard 11397: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
11398: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
11399: * {2, 1, 4, 8, 5, 6, 3, 7}
11400: * Struct []
11401: */
1.225 brouard 11402:
1.187 brouard 11403: /* This loop fills the array Tvar from the string 'model'.*/
11404: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
11405: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
11406: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
11407: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
11408: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
11409: /* k=1 Tvar[1]=2 (from V2) */
11410: /* k=5 Tvar[5] */
11411: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 11412: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 11413: /* } */
1.198 brouard 11414: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 11415: /*
11416: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 11417: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
11418: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
11419: }
1.187 brouard 11420: cptcovage=0;
1.319 brouard 11421: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model line */
11422: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+' cutl from left to right
11423: 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" */
11424: if (nbocc(modelsav,'+')==0)
11425: strcpy(strb,modelsav); /* and analyzes it */
1.234 brouard 11426: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
11427: /*scanf("%d",i);*/
1.349 ! brouard 11428: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V5*age+ V4+V3*age strb=V3*age OR double product with age strb=age*V6*V2 or V6*V2*age or V6*age*V2 */
! 11429: cutl(strc,strd,strb,'*'); /**< k=1 strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 OR strb=age*V6*V2 strc=V6*V2 strd=age OR c=V2*age OR c=age*V2 */
! 11430: if(strchr(strc,'*')) { /**< Model with age and DOUBLE product: allowed since 0.99r44, strc=V6*V2 or V2*age or age*V2, strd=age or V6 or V6 */
! 11431: Typevar[k]=3; /* 3 for age and double product age*Vn*Vm varying of fixed */
! 11432: if(strstr(strc,"age")!=0) { /* It means that strc=V2*age or age*V2 and thus that strd=Vn */
! 11433: cutl(stre,strf,strc,'*') ; /* strf=age or Vm, stre=Vm or age. If strc=V6*V2 then strf=V6 and stre=V2 */
! 11434: strcpy(strc,strb); /* save strb(=age*Vn*Vm) into strc */
! 11435: /* We want strb=Vn*Vm */
! 11436: if(strcmp(strf,"age")==0){ /* strf is "age" so that stre=Vm =V2 . */
! 11437: strcpy(strb,strd);
! 11438: strcat(strb,"*");
! 11439: strcat(strb,stre);
! 11440: }else{ /* strf=Vm If strf=V6 then stre=V2 */
! 11441: strcpy(strb,strf);
! 11442: strcat(strb,"*");
! 11443: strcat(strb,stre);
! 11444: strcpy(strd,strb); /* in order for strd to not be "age" for next test (will be Vn*Vm */
! 11445: }
! 11446: printf("DEBUG FIXED k=%d, Tage[k]=%d, Tvar[Tage[k]=%d,FixedV[Tvar[Tage[k]]]=%d\n",k,Tage[k],Tvar[Tage[k]],FixedV[Tvar[Tage[k]]]);
! 11447: FixedV[Tvar[Tage[k]]]=0; /* HERY not sure */
! 11448: }else{ /* strc=Vn*Vm (and strd=age) and should be strb=Vn*Vm but want to keep original strb double product */
! 11449: strcpy(stre,strb); /* save full b in stre */
! 11450: strcpy(strb,strc); /* save short c in new short b for next block strb=Vn*Vm*/
! 11451: strcpy(strf,strc); /* save short c in new short f */
! 11452: cutl(strc,strd,strf,'*'); /* We get strd=Vn and strc=Vm for next block (strb=Vn*Vm)*/
! 11453: /* strcpy(strc,stre);*/ /* save full e in c for future */
! 11454: }
! 11455: cptcovdageprod++; /* double product with age Which product is it? */
! 11456: /* strcpy(strb,strc); /\* strb was age*V6*V2 or V6*V2*age or V6*age*V2 IS now V6*V2 or V2*age or age*V2 *\/ */
! 11457: /* cutl(strc,strd,strb,'*'); /\* strd= V6 or V2 or age and strc= V2 or age or V2 *\/ */
1.234 brouard 11458: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
1.349 ! brouard 11459: n=atoi(stre);
1.234 brouard 11460: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
1.349 ! brouard 11461: m=atoi(strc);
! 11462: cptcovage++; /* Counts the number of covariates which include age as a product */
! 11463: Tage[cptcovage]=k; /* For age*V3*V2 gives the position in model of covariates associated with age Tage[1]=6 HERY too*/
! 11464: if(existcomb[n][m] == 0){
! 11465: /* r /home/brouard/Documents/Recherches/REVES/Zachary/Zach-2022/Feinuo_Sun/Feinuo-threeway/femV12V15_3wayintNBe.imach */
! 11466: printf("Warning in model combination V%d*V%d should exist in the model before adding V%d*V%d*age !\n",n,m,n,m);
! 11467: fprintf(ficlog,"Warning in model combination V%d*V%d should exist in the model before adding V%d*V%d*age !\n",n,m,n,m);
! 11468: fflush(ficlog);
! 11469: k1++; /* The combination Vn*Vm will be in the model so we create it at k1 */
! 11470: k12++;
! 11471: existcomb[n][m]=k1;
! 11472: existcomb[m][n]=k1;
! 11473: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1;
! 11474: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2+ age*V6*V3 Gives the k position of the k1 double product Vn*Vm or age*Vn*Vm*/
! 11475: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 Gives the k1 double product Vn*Vm or age*Vn*Vm at the k position */
! 11476: Tvard[k1][1] =m; /* m 1 for V1*/
! 11477: Tvardk[k][1] =m; /* m 1 for V1*/
! 11478: Tvard[k1][2] =n; /* n 4 for V4*/
! 11479: Tvardk[k][2] =n; /* n 4 for V4*/
! 11480: /* Tvar[Tage[cptcovage]]=k1;*/ /* Tvar[6=age*V3*V2]=9 (new fixed covariate) */
! 11481: 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 */
! 11482: for (i=1; i<=lastobs;i++){/* For fixed product */
! 11483: /* Computes the new covariate which is a product of
! 11484: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
! 11485: covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
! 11486: }
! 11487: cptcovprodage++; /* Counting the number of fixed covariate with age */
! 11488: FixedV[ncovcolt+k12]=0; /* We expand Vn*Vm */
! 11489: k12++;
! 11490: FixedV[ncovcolt+k12]=0;
! 11491: }else{ /*End of FixedV */
! 11492: cptcovprodvage++; /* Counting the number of varying covariate with age */
! 11493: FixedV[ncovcolt+k12]=1; /* We expand Vn*Vm */
! 11494: k12++;
! 11495: FixedV[ncovcolt+k12]=1;
! 11496: }
! 11497: }else{ /* k1 Vn*Vm already exists */
! 11498: k11=existcomb[n][m];
! 11499: Tposprod[k]=k11; /* OK */
! 11500: Tvar[k]=Tvar[Tprod[k11]]; /* HERY */
! 11501: Tvardk[k][1]=m;
! 11502: Tvardk[k][2]=n;
! 11503: 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 */
! 11504: /*cptcovage++;*/ /* Counts the number of covariates which include age as a product */
! 11505: cptcovprodage++; /* Counting the number of fixed covariate with age */
! 11506: /*Tage[cptcovage]=k;*/ /* For age*V3*V2 Tage[1]=V3*V3=9 HERY too*/
! 11507: Tvar[Tage[cptcovage]]=k1;
! 11508: FixedV[ncovcolt+k12]=0; /* We expand Vn*Vm */
! 11509: k12++;
! 11510: FixedV[ncovcolt+k12]=0;
! 11511: }else{ /* Already exists but time varying (and age) */
! 11512: /*cptcovage++;*/ /* Counts the number of covariates which include age as a product */
! 11513: /*Tage[cptcovage]=k;*/ /* For age*V3*V2 Tage[1]=V3*V3=9 HERY too*/
! 11514: /* Tvar[Tage[cptcovage]]=k1; */
! 11515: cptcovprodvage++;
! 11516: FixedV[ncovcolt+k12]=1; /* We expand Vn*Vm */
! 11517: k12++;
! 11518: FixedV[ncovcolt+k12]=1;
! 11519: }
! 11520: }
! 11521: /* Tage[cptcovage]=k; /\* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
! 11522: /* Tvar[k]=k11; /\* HERY *\/ */
! 11523: } else {/* simple product strb=age*Vn so that c=Vn and d=age, or strb=Vn*age so that c=age and d=Vn, or b=Vn*Vm so that c=Vm and d=Vn */
! 11524: cptcovprod++;
! 11525: if (strcmp(strc,"age")==0) { /**< Model includes age: strb= Vn*age c=age d=Vn*/
! 11526: /* covar is not filled and then is empty */
! 11527: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
! 11528: 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 */
! 11529: Typevar[k]=1; /* 1 for age product */
! 11530: cptcovage++; /* Counts the number of covariates which include age as a product */
! 11531: Tage[cptcovage]=k; /* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
! 11532: if( FixedV[Tvar[k]] == 0){
! 11533: cptcovprodage++; /* Counting the number of fixed covariate with age */
! 11534: }else{
! 11535: cptcovprodvage++; /* Counting the number of fixedvarying covariate with age */
! 11536: }
! 11537: /*printf("stre=%s ", stre);*/
! 11538: } else if (strcmp(strd,"age")==0) { /* strb= age*Vn c=Vn */
! 11539: cutl(stre,strb,strc,'V');
! 11540: Tvar[k]=atoi(stre);
! 11541: Typevar[k]=1; /* 1 for age product */
! 11542: cptcovage++;
! 11543: Tage[cptcovage]=k;
! 11544: if( FixedV[Tvar[k]] == 0){
! 11545: cptcovprodage++; /* Counting the number of fixed covariate with age */
! 11546: }else{
! 11547: cptcovprodvage++; /* Counting the number of fixedvarying covariate with age */
1.339 brouard 11548: }
1.349 ! brouard 11549: }else{ /* for product Vn*Vm */
! 11550: Typevar[k]=2; /* 2 for product Vn*Vm */
! 11551: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
! 11552: n=atoi(stre);
! 11553: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
! 11554: m=atoi(strc);
! 11555: k1++;
! 11556: cptcovprodnoage++;
! 11557: if(existcomb[n][m] != 0 || existcomb[m][n] != 0){
! 11558: printf("Warning in model combination V%d*V%d already exists in the model in position k1=%d!\n",n,m,existcomb[n][m]);
! 11559: fprintf(ficlog,"Warning in model combination V%d*V%d already exists in the model in position k1=%d!\n",n,m,existcomb[n][m]);
! 11560: fflush(ficlog);
! 11561: k11=existcomb[n][m];
! 11562: Tvar[k]=ncovcol+nqv+ntv+nqtv+k11;
! 11563: Tposprod[k]=k11;
! 11564: Tprod[k11]=k;
! 11565: Tvardk[k][1] =m; /* m 1 for V1*/
! 11566: /* Tvard[k11][1] =m; /\* n 4 for V4*\/ */
! 11567: Tvardk[k][2] =n; /* n 4 for V4*/
! 11568: /* Tvard[k11][2] =n; /\* n 4 for V4*\/ */
! 11569: }else{ /* combination Vn*Vm doesn't exist we create it (no age)*/
! 11570: existcomb[n][m]=k1;
! 11571: existcomb[m][n]=k1;
! 11572: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* ncovcolt+k1; For model-covariate k tells which data-covariate to use but
! 11573: because this model-covariate is a construction we invent a new column
! 11574: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
! 11575: If already ncovcol=4 and model= V2 + V1 + V1*V4 + age*V3 + V3*V2
! 11576: thus after V4 we invent V5 and V6 because age*V3 will be computed in 4
! 11577: Tvar[3=V1*V4]=4+1=5 Tvar[5=V3*V2]=4 + 2= 6, Tvar[4=age*V3]=3 etc */
! 11578: /* Please remark that the new variables are model dependent */
! 11579: /* If we have 4 variable but the model uses only 3, like in
! 11580: * model= V1 + age*V1 + V2 + V3 + age*V2 + age*V3 + V1*V2 + V1*V3
! 11581: * k= 1 2 3 4 5 6 7 8
! 11582: * Tvar[k]=1 1 2 3 2 3 (5 6) (and not 4 5 because of V4 missing)
! 11583: * Tage[kk] [1]= 2 [2]=5 [3]=6 kk=1 to cptcovage=3
! 11584: * Tvar[Tage[kk]][1]=2 [2]=2 [3]=3
! 11585: */
! 11586: /* We need to feed some variables like TvarVV, but later on next loop because of ncovv (k2) is not correct */
! 11587: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 +V6*V2*age */
! 11588: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 */
! 11589: Tvard[k1][1] =m; /* m 1 for V1*/
! 11590: Tvardk[k][1] =m; /* m 1 for V1*/
! 11591: Tvard[k1][2] =n; /* n 4 for V4*/
! 11592: Tvardk[k][2] =n; /* n 4 for V4*/
! 11593: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
! 11594: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
! 11595: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
! 11596: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
! 11597: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
! 11598: 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 */
! 11599: for (i=1; i<=lastobs;i++){/* For fixed product */
! 11600: /* Computes the new covariate which is a product of
! 11601: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
! 11602: covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
! 11603: }
! 11604: /* TvarVV[k2]=n; */
! 11605: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
! 11606: /* TvarVV[k2+1]=m; */
! 11607: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
! 11608: }else{ /* not FixedV */
! 11609: /* TvarVV[k2]=n; */
! 11610: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
! 11611: /* TvarVV[k2+1]=m; */
! 11612: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
! 11613: }
! 11614: } /* End of creation of Vn*Vm if not created by age*Vn*Vm earlier */
! 11615: } /* End of product Vn*Vm */
! 11616: } /* End of age*double product or simple product */
! 11617: }else { /* not a product */
1.234 brouard 11618: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
11619: /* scanf("%d",i);*/
11620: cutl(strd,strc,strb,'V');
11621: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
11622: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
11623: Tvar[k]=atoi(strd);
11624: Typevar[k]=0; /* 0 for simple covariates */
11625: }
11626: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 11627: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 11628: scanf("%d",i);*/
1.187 brouard 11629: } /* end of loop + on total covariates */
11630: } /* end if strlen(modelsave == 0) age*age might exist */
11631: } /* end if strlen(model == 0) */
1.349 ! brouard 11632: cptcovs=cptcovt - cptcovdageprod - cptcovprod;/**< Number of simple covariates V1 +V1*age +V3 +V3*V4 +age*age + age*v4*V3=> V1 + V3 =4+1-3=2 */
! 11633:
1.136 brouard 11634: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
11635: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 11636:
1.136 brouard 11637: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 11638: printf("cptcovprod=%d ", cptcovprod);
11639: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
11640: scanf("%d ",i);*/
11641:
11642:
1.230 brouard 11643: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
11644: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 11645: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
11646: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
11647: k = 1 2 3 4 5 6 7 8 9
11648: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
1.319 brouard 11649: Typevar[k]= 0 0 0 2 1 0 2 1 0
1.227 brouard 11650: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
11651: Dummy[k] 1 0 0 0 3 1 1 2 3
11652: Tmodelind[combination of covar]=k;
1.225 brouard 11653: */
11654: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 11655: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 11656: /* 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 11657: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.318 brouard 11658: printf("Model=1+age+%s\n\
1.349 ! brouard 11659: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product, 3 for double product with age \n\
1.227 brouard 11660: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
11661: 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 11662: fprintf(ficlog,"Model=1+age+%s\n\
1.349 ! brouard 11663: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product, 3 for double product with age \n\
1.227 brouard 11664: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
11665: 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 11666: for(k=-1;k<=NCOVMAX; k++){ Fixed[k]=0; Dummy[k]=0;}
11667: for(k=1;k<=NCOVMAX; k++){TvarFind[k]=0; TvarVind[k]=0;}
1.349 ! brouard 11668: for(k=1, ncovf=0, nsd=0, nsq=0, ncovv=0,ncovva=0,ncovvta=0, ncova=0, ncoveff=0, nqfveff=0, ntveff=0, nqtveff=0, ncovvt=0;k<=cptcovt; k++){ /* or cptocvt loop on k from model */
1.234 brouard 11669: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 11670: Fixed[k]= 0;
11671: Dummy[k]= 0;
1.225 brouard 11672: ncoveff++;
1.232 brouard 11673: ncovf++;
1.234 brouard 11674: nsd++;
11675: modell[k].maintype= FTYPE;
11676: TvarsD[nsd]=Tvar[k];
11677: TvarsDind[nsd]=k;
1.330 brouard 11678: TnsdVar[Tvar[k]]=nsd;
1.234 brouard 11679: TvarF[ncovf]=Tvar[k];
11680: TvarFind[ncovf]=k;
11681: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
11682: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.339 brouard 11683: /* }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /\* Product of fixed dummy (<=ncovcol) covariates For a fixed product k is higher than ncovcol *\/ */
1.240 brouard 11684: }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 11685: Fixed[k]= 0;
11686: Dummy[k]= 1;
1.230 brouard 11687: nqfveff++;
1.234 brouard 11688: modell[k].maintype= FTYPE;
11689: modell[k].subtype= FQ;
11690: nsq++;
1.334 brouard 11691: TvarsQ[nsq]=Tvar[k]; /* Gives the variable name (extended to products) of first nsq simple quantitative covariates (fixed or time vary see below */
11692: TvarsQind[nsq]=k; /* Gives the position in the model equation of the first nsq simple quantitative covariates (fixed or time vary) */
1.232 brouard 11693: ncovf++;
1.234 brouard 11694: TvarF[ncovf]=Tvar[k];
11695: TvarFind[ncovf]=k;
1.231 brouard 11696: 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 11697: 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 11698: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.339 brouard 11699: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11700: /* model V1+V3+age*V1+age*V3+V1*V3 */
11701: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11702: ncovvt++;
11703: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
11704: TvarVVind[ncovvt]=k; /* TvarVVind[1]=2 (second position in the model equation */
11705:
1.227 brouard 11706: Fixed[k]= 1;
11707: Dummy[k]= 0;
1.225 brouard 11708: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 11709: modell[k].maintype= VTYPE;
11710: modell[k].subtype= VD;
11711: nsd++;
11712: TvarsD[nsd]=Tvar[k];
11713: TvarsDind[nsd]=k;
1.330 brouard 11714: TnsdVar[Tvar[k]]=nsd; /* To be verified */
1.234 brouard 11715: ncovv++; /* Only simple time varying variables */
11716: TvarV[ncovv]=Tvar[k];
1.242 brouard 11717: 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 11718: 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 */
11719: 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 11720: 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);
11721: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 11722: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.339 brouard 11723: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11724: /* model V1+V3+age*V1+age*V3+V1*V3 */
11725: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11726: ncovvt++;
11727: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
11728: TvarVVind[ncovvt]=k; /* TvarVV[1]=V3 (first time varying in the model equation */
11729:
1.234 brouard 11730: Fixed[k]= 1;
11731: Dummy[k]= 1;
11732: nqtveff++;
11733: modell[k].maintype= VTYPE;
11734: modell[k].subtype= VQ;
11735: ncovv++; /* Only simple time varying variables */
11736: nsq++;
1.334 brouard 11737: 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) */
11738: 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 11739: TvarV[ncovv]=Tvar[k];
1.242 brouard 11740: 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 11741: 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 */
11742: 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 11743: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
11744: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
1.349 ! brouard 11745: /* printf("Quasi TmodelQind[%d]=%d,Tvar[TmodelQind[%d]]=V%d, ncovcol=%d, nqv=%d, ntv=%Ad,Tvar[k]- ncovcol-nqv-ntv=%d\n",nqtveff,k,nqtveff,Tvar[k], ncovcol, nqv, ntv, Tvar[k]- ncovcol-nqv-ntv); */
1.342 brouard 11746: /* printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv); */
1.227 brouard 11747: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 11748: ncova++;
11749: TvarA[ncova]=Tvar[k];
11750: TvarAind[ncova]=k;
1.349 ! brouard 11751: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
! 11752: /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
1.231 brouard 11753: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 11754: Fixed[k]= 2;
11755: Dummy[k]= 2;
11756: modell[k].maintype= ATYPE;
11757: modell[k].subtype= APFD;
1.349 ! brouard 11758: ncovta++;
! 11759: TvarAVVA[ncovta]=Tvar[k]; /* (2)age*V3 */
! 11760: TvarAVVAind[ncovta]=k;
1.240 brouard 11761: /* ncoveff++; */
1.227 brouard 11762: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 11763: Fixed[k]= 2;
11764: Dummy[k]= 3;
11765: modell[k].maintype= ATYPE;
11766: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
1.349 ! brouard 11767: ncovta++;
! 11768: TvarAVVA[ncovta]=Tvar[k]; /* */
! 11769: TvarAVVAind[ncovta]=k;
1.240 brouard 11770: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 11771: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 11772: Fixed[k]= 3;
11773: Dummy[k]= 2;
11774: modell[k].maintype= ATYPE;
11775: modell[k].subtype= APVD; /* Product age * varying dummy */
1.349 ! brouard 11776: ncovva++;
! 11777: TvarVVA[ncovva]=Tvar[k]; /* (1)+age*V6 + (2)age*V7 */
! 11778: TvarVVAind[ncovva]=k;
! 11779: ncovta++;
! 11780: TvarAVVA[ncovta]=Tvar[k]; /* */
! 11781: TvarAVVAind[ncovta]=k;
1.240 brouard 11782: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 11783: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 11784: Fixed[k]= 3;
11785: Dummy[k]= 3;
11786: modell[k].maintype= ATYPE;
11787: modell[k].subtype= APVQ; /* Product age * varying quantitative */
1.349 ! brouard 11788: ncovva++;
! 11789: TvarVVA[ncovva]=Tvar[k]; /* */
! 11790: TvarVVAind[ncovva]=k;
! 11791: ncovta++;
! 11792: TvarAVVA[ncovta]=Tvar[k]; /* (1)+age*V6 + (2)age*V7 */
! 11793: TvarAVVAind[ncovta]=k;
1.240 brouard 11794: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 11795: }
1.349 ! brouard 11796: }else if( Tposprod[k]>0 && Typevar[k]==2){ /* Detects if fixed product no age Vm*Vn */
! 11797: printf("MEMORY ERRORR k=%d Tposprod[k]=%d, Typevar[k]=%d\n ",k, Tposprod[k], Typevar[k]);
! 11798: if(FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){ /* Needs a fixed product Product of fixed dummy (<=ncovcol) covariates For a fixed product k is higher than ncovcol V3*V2 */
! 11799: printf("MEMORY ERRORR k=%d Tvardk[k][1]=%d, Tvardk[k][2]=%d, FixedV[Tvardk[k][1]]=%d,FixedV[Tvardk[k][2]]=%d\n ",k,Tvardk[k][1],Tvardk[k][2],FixedV[Tvardk[k][1]],FixedV[Tvardk[k][2]]);
! 11800: Fixed[k]= 0;
! 11801: Dummy[k]= 0;
! 11802: ncoveff++;
! 11803: ncovf++;
! 11804: /* ncovv++; */
! 11805: /* TvarVV[ncovv]=Tvardk[k][1]; */
! 11806: /* FixedV[ncovcolt+ncovv]=0; /\* or FixedV[TvarVV[ncovv]]=0 HERE *\/ */
! 11807: /* ncovv++; */
! 11808: /* TvarVV[ncovv]=Tvardk[k][2]; */
! 11809: /* FixedV[ncovcolt+ncovv]=0; /\* or FixedV[TvarVV[ncovv]]=0 HERE *\/ */
! 11810: modell[k].maintype= FTYPE;
! 11811: TvarF[ncovf]=Tvar[k];
! 11812: /* TnsdVar[Tvar[k]]=nsd; */ /* To be done */
! 11813: TvarFind[ncovf]=k;
! 11814: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
! 11815: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
! 11816: }else{/* product varying Vn * Vm without age, V1+V3+age*V1+age*V3+V1*V3 looking at V1*V3, Typevar={0, 0, 1, 1, 2}, k=5, V1 is fixed, V3 is timevary, V5 is a product */
! 11817: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
! 11818: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age*/
! 11819: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
! 11820: k1=Tposprod[k]; /* Position in the products of product k, Tposprod={0, 0, 0, 0, 1, 1} k1=1 first product but second time varying because of V3 */
! 11821: ncovvt++;
! 11822: TvarVV[ncovvt]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */
! 11823: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
! 11824: ncovvt++;
! 11825: TvarVV[ncovvt]=Tvard[k1][2]; /* TvarVV[3]=V3 */
! 11826: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
! 11827:
! 11828: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
! 11829: /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
! 11830:
! 11831: if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */
! 11832: if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */
! 11833: Fixed[k]= 1;
! 11834: Dummy[k]= 0;
! 11835: modell[k].maintype= FTYPE;
! 11836: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
! 11837: ncovf++; /* Fixed variables without age */
! 11838: TvarF[ncovf]=Tvar[k];
! 11839: TvarFind[ncovf]=k;
! 11840: }else if(Tvard[k1][2] <=ncovcol+nqv){ /* Vm is quanti fixed */
! 11841: Fixed[k]= 0; /* Fixed product */
! 11842: Dummy[k]= 1;
! 11843: modell[k].maintype= FTYPE;
! 11844: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
! 11845: ncovf++; /* Varying variables without age */
! 11846: TvarF[ncovf]=Tvar[k];
! 11847: TvarFind[ncovf]=k;
! 11848: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is a time varying dummy covariate */
! 11849: Fixed[k]= 1;
! 11850: Dummy[k]= 0;
! 11851: modell[k].maintype= VTYPE;
! 11852: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
! 11853: ncovv++; /* Varying variables without age */
! 11854: TvarV[ncovv]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */
! 11855: TvarVind[ncovv]=k;/* TvarVind[1]=5 */
! 11856: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */
! 11857: Fixed[k]= 1;
! 11858: Dummy[k]= 1;
! 11859: modell[k].maintype= VTYPE;
! 11860: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
! 11861: ncovv++; /* Varying variables without age */
! 11862: TvarV[ncovv]=Tvar[k];
! 11863: TvarVind[ncovv]=k;
! 11864: }
! 11865: }else if(Tvard[k1][1] <=ncovcol+nqv){ /* Vn is fixed quanti */
! 11866: if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */
! 11867: Fixed[k]= 0; /* Fixed product */
! 11868: Dummy[k]= 1;
! 11869: modell[k].maintype= FTYPE;
! 11870: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
! 11871: ncovf++; /* Fixed variables without age */
! 11872: TvarF[ncovf]=Tvar[k];
! 11873: TvarFind[ncovf]=k;
! 11874: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is time varying */
! 11875: Fixed[k]= 1;
! 11876: Dummy[k]= 1;
! 11877: modell[k].maintype= VTYPE;
! 11878: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
! 11879: ncovv++; /* Varying variables without age */
! 11880: TvarV[ncovv]=Tvar[k];
! 11881: TvarVind[ncovv]=k;
! 11882: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is time varying quanti */
! 11883: Fixed[k]= 1;
! 11884: Dummy[k]= 1;
! 11885: modell[k].maintype= VTYPE;
! 11886: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
! 11887: ncovv++; /* Varying variables without age */
! 11888: TvarV[ncovv]=Tvar[k];
! 11889: TvarVind[ncovv]=k;
! 11890: ncovv++; /* Varying variables without age */
! 11891: TvarV[ncovv]=Tvar[k];
! 11892: TvarVind[ncovv]=k;
! 11893: }
! 11894: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ /* Vn is time varying dummy */
! 11895: if(Tvard[k1][2] <=ncovcol){
! 11896: Fixed[k]= 1;
! 11897: Dummy[k]= 1;
! 11898: modell[k].maintype= VTYPE;
! 11899: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
! 11900: ncovv++; /* Varying variables without age */
! 11901: TvarV[ncovv]=Tvar[k];
! 11902: TvarVind[ncovv]=k;
! 11903: }else if(Tvard[k1][2] <=ncovcol+nqv){
! 11904: Fixed[k]= 1;
! 11905: Dummy[k]= 1;
! 11906: modell[k].maintype= VTYPE;
! 11907: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
! 11908: ncovv++; /* Varying variables without age */
! 11909: TvarV[ncovv]=Tvar[k];
! 11910: TvarVind[ncovv]=k;
! 11911: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
! 11912: Fixed[k]= 1;
! 11913: Dummy[k]= 0;
! 11914: modell[k].maintype= VTYPE;
! 11915: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
! 11916: ncovv++; /* Varying variables without age */
! 11917: TvarV[ncovv]=Tvar[k];
! 11918: TvarVind[ncovv]=k;
! 11919: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
! 11920: Fixed[k]= 1;
! 11921: Dummy[k]= 1;
! 11922: modell[k].maintype= VTYPE;
! 11923: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
! 11924: ncovv++; /* Varying variables without age */
! 11925: TvarV[ncovv]=Tvar[k];
! 11926: TvarVind[ncovv]=k;
! 11927: }
! 11928: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ /* Vn is time varying quanti */
! 11929: if(Tvard[k1][2] <=ncovcol){
! 11930: Fixed[k]= 1;
! 11931: Dummy[k]= 1;
! 11932: modell[k].maintype= VTYPE;
! 11933: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
! 11934: ncovv++; /* Varying variables without age */
! 11935: TvarV[ncovv]=Tvar[k];
! 11936: TvarVind[ncovv]=k;
! 11937: }else if(Tvard[k1][2] <=ncovcol+nqv){
! 11938: Fixed[k]= 1;
! 11939: Dummy[k]= 1;
! 11940: modell[k].maintype= VTYPE;
! 11941: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
! 11942: ncovv++; /* Varying variables without age */
! 11943: TvarV[ncovv]=Tvar[k];
! 11944: TvarVind[ncovv]=k;
! 11945: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
! 11946: Fixed[k]= 1;
! 11947: Dummy[k]= 1;
! 11948: modell[k].maintype= VTYPE;
! 11949: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
! 11950: ncovv++; /* Varying variables without age */
! 11951: TvarV[ncovv]=Tvar[k];
! 11952: TvarVind[ncovv]=k;
! 11953: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
! 11954: Fixed[k]= 1;
! 11955: Dummy[k]= 1;
! 11956: modell[k].maintype= VTYPE;
! 11957: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
! 11958: ncovv++; /* Varying variables without age */
! 11959: TvarV[ncovv]=Tvar[k];
! 11960: TvarVind[ncovv]=k;
! 11961: }
! 11962: }else{
! 11963: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
! 11964: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
! 11965: } /*end k1*/
! 11966: }
! 11967: }else if(Typevar[k] == 3){ /* product Vn * Vm with age, V1+V3+age*V1+age*V3+V1*V3 looking at V1*V3, Typevar={0, 0, 1, 1, 2}, k=5, V1 is fixed, V3 is timevary, V5 is a product */
1.339 brouard 11968: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
1.349 ! brouard 11969: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age*/
! 11970: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
! 11971: k1=Tposprod[k]; /* Position in the products of product k, Tposprod={0, 0, 0, 0, 1, 1} k1=1 first product but second time varying because of V3 */
! 11972: ncova++;
! 11973: TvarA[ncova]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */
! 11974: TvarAind[ncova]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
! 11975: ncova++;
! 11976: TvarA[ncova]=Tvard[k1][2]; /* TvarVV[3]=V3 */
! 11977: TvarAind[ncova]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
1.339 brouard 11978:
1.349 ! brouard 11979: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
! 11980: /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
! 11981: if( FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){
! 11982: ncovta++;
! 11983: TvarAVVA[ncovta]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
! 11984: TvarAVVAind[ncovta]=k;
! 11985: ncovta++;
! 11986: TvarAVVA[ncovta]=Tvard[k1][2]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
! 11987: TvarAVVAind[ncovta]=k;
! 11988: }else{
! 11989: ncovva++; /* HERY reached */
! 11990: TvarVVA[ncovva]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
! 11991: TvarVVAind[ncovva]=k;
! 11992: ncovva++;
! 11993: TvarVVA[ncovva]=Tvard[k1][2]; /* */
! 11994: TvarVVAind[ncovva]=k;
! 11995: ncovta++;
! 11996: TvarAVVA[ncovta]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
! 11997: TvarAVVAind[ncovta]=k;
! 11998: ncovta++;
! 11999: TvarAVVA[ncovta]=Tvard[k1][2]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
! 12000: TvarAVVAind[ncovta]=k;
! 12001: }
1.339 brouard 12002: if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */
12003: if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */
1.349 ! brouard 12004: Fixed[k]= 2;
! 12005: Dummy[k]= 2;
1.240 brouard 12006: modell[k].maintype= FTYPE;
12007: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
1.349 ! brouard 12008: /* TvarF[ncova]=Tvar[k]; /\* Problem to solve *\/ */
! 12009: /* TvarFind[ncova]=k; */
1.339 brouard 12010: }else if(Tvard[k1][2] <=ncovcol+nqv){ /* Vm is quanti fixed */
1.349 ! brouard 12011: Fixed[k]= 2; /* Fixed product */
! 12012: Dummy[k]= 3;
1.240 brouard 12013: modell[k].maintype= FTYPE;
12014: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
1.349 ! brouard 12015: /* TvarF[ncova]=Tvar[k]; */
! 12016: /* TvarFind[ncova]=k; */
1.339 brouard 12017: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is a time varying dummy covariate */
1.349 ! brouard 12018: Fixed[k]= 3;
! 12019: Dummy[k]= 2;
1.240 brouard 12020: modell[k].maintype= VTYPE;
12021: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
1.349 ! brouard 12022: TvarV[ncova]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */
! 12023: TvarVind[ncova]=k;/* TvarVind[1]=5 */
1.339 brouard 12024: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */
1.349 ! brouard 12025: Fixed[k]= 3;
! 12026: Dummy[k]= 3;
1.240 brouard 12027: modell[k].maintype= VTYPE;
12028: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
1.349 ! brouard 12029: /* ncovv++; /\* Varying variables without age *\/ */
! 12030: /* TvarV[ncovv]=Tvar[k]; */
! 12031: /* TvarVind[ncovv]=k; */
1.240 brouard 12032: }
1.339 brouard 12033: }else if(Tvard[k1][1] <=ncovcol+nqv){ /* Vn is fixed quanti */
12034: if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */
1.349 ! brouard 12035: Fixed[k]= 2; /* Fixed product */
! 12036: Dummy[k]= 2;
1.240 brouard 12037: modell[k].maintype= FTYPE;
12038: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
1.349 ! brouard 12039: /* ncova++; /\* Fixed variables with age *\/ */
! 12040: /* TvarF[ncovf]=Tvar[k]; */
! 12041: /* TvarFind[ncovf]=k; */
1.339 brouard 12042: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is time varying */
1.349 ! brouard 12043: Fixed[k]= 2;
! 12044: Dummy[k]= 3;
1.240 brouard 12045: modell[k].maintype= VTYPE;
12046: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
1.349 ! brouard 12047: /* ncova++; /\* Varying variables with age *\/ */
! 12048: /* TvarV[ncova]=Tvar[k]; */
! 12049: /* TvarVind[ncova]=k; */
1.339 brouard 12050: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is time varying quanti */
1.349 ! brouard 12051: Fixed[k]= 3;
! 12052: Dummy[k]= 2;
1.240 brouard 12053: modell[k].maintype= VTYPE;
12054: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
1.349 ! brouard 12055: ncova++; /* Varying variables without age */
! 12056: TvarV[ncova]=Tvar[k];
! 12057: TvarVind[ncova]=k;
! 12058: /* ncova++; /\* Varying variables without age *\/ */
! 12059: /* TvarV[ncova]=Tvar[k]; */
! 12060: /* TvarVind[ncova]=k; */
1.240 brouard 12061: }
1.339 brouard 12062: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ /* Vn is time varying dummy */
1.240 brouard 12063: if(Tvard[k1][2] <=ncovcol){
1.349 ! brouard 12064: Fixed[k]= 2;
! 12065: Dummy[k]= 2;
1.240 brouard 12066: modell[k].maintype= VTYPE;
12067: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
1.349 ! brouard 12068: /* ncova++; /\* Varying variables with age *\/ */
! 12069: /* TvarV[ncova]=Tvar[k]; */
! 12070: /* TvarVind[ncova]=k; */
1.240 brouard 12071: }else if(Tvard[k1][2] <=ncovcol+nqv){
1.349 ! brouard 12072: Fixed[k]= 2;
! 12073: Dummy[k]= 3;
1.240 brouard 12074: modell[k].maintype= VTYPE;
12075: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
1.349 ! brouard 12076: /* ncova++; /\* Varying variables with age *\/ */
! 12077: /* TvarV[ncova]=Tvar[k]; */
! 12078: /* TvarVind[ncova]=k; */
1.240 brouard 12079: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
1.349 ! brouard 12080: Fixed[k]= 3;
! 12081: Dummy[k]= 2;
1.240 brouard 12082: modell[k].maintype= VTYPE;
12083: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
1.349 ! brouard 12084: /* ncova++; /\* Varying variables with age *\/ */
! 12085: /* TvarV[ncova]=Tvar[k]; */
! 12086: /* TvarVind[ncova]=k; */
1.240 brouard 12087: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
1.349 ! brouard 12088: Fixed[k]= 3;
! 12089: Dummy[k]= 3;
1.240 brouard 12090: modell[k].maintype= VTYPE;
12091: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
1.349 ! brouard 12092: /* ncova++; /\* Varying variables with age *\/ */
! 12093: /* TvarV[ncova]=Tvar[k]; */
! 12094: /* TvarVind[ncova]=k; */
1.240 brouard 12095: }
1.339 brouard 12096: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ /* Vn is time varying quanti */
1.240 brouard 12097: if(Tvard[k1][2] <=ncovcol){
1.349 ! brouard 12098: Fixed[k]= 2;
! 12099: Dummy[k]= 2;
1.240 brouard 12100: modell[k].maintype= VTYPE;
12101: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
1.349 ! brouard 12102: /* ncova++; /\* Varying variables with age *\/ */
! 12103: /* TvarV[ncova]=Tvar[k]; */
! 12104: /* TvarVind[ncova]=k; */
1.240 brouard 12105: }else if(Tvard[k1][2] <=ncovcol+nqv){
1.349 ! brouard 12106: Fixed[k]= 2;
! 12107: Dummy[k]= 3;
1.240 brouard 12108: modell[k].maintype= VTYPE;
12109: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
1.349 ! brouard 12110: /* ncova++; /\* Varying variables with age *\/ */
! 12111: /* TvarV[ncova]=Tvar[k]; */
! 12112: /* TvarVind[ncova]=k; */
1.240 brouard 12113: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
1.349 ! brouard 12114: Fixed[k]= 3;
! 12115: Dummy[k]= 2;
1.240 brouard 12116: modell[k].maintype= VTYPE;
12117: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
1.349 ! brouard 12118: /* ncova++; /\* Varying variables with age *\/ */
! 12119: /* TvarV[ncova]=Tvar[k]; */
! 12120: /* TvarVind[ncova]=k; */
1.240 brouard 12121: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
1.349 ! brouard 12122: Fixed[k]= 3;
! 12123: Dummy[k]= 3;
1.240 brouard 12124: modell[k].maintype= VTYPE;
12125: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
1.349 ! brouard 12126: /* ncova++; /\* Varying variables with age *\/ */
! 12127: /* TvarV[ncova]=Tvar[k]; */
! 12128: /* TvarVind[ncova]=k; */
1.240 brouard 12129: }
1.227 brouard 12130: }else{
1.240 brouard 12131: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12132: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12133: } /*end k1*/
1.349 ! brouard 12134: } else{
1.226 brouard 12135: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
12136: 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 12137: }
1.342 brouard 12138: /* 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]); */
12139: /* printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype); */
1.227 brouard 12140: 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]);
12141: }
1.349 ! brouard 12142: ncovvta=ncovva;
1.227 brouard 12143: /* Searching for doublons in the model */
12144: for(k1=1; k1<= cptcovt;k1++){
12145: for(k2=1; k2 <k1;k2++){
1.285 brouard 12146: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
12147: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 12148: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
12149: if(Tvar[k1]==Tvar[k2]){
1.338 brouard 12150: 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]);
12151: 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 12152: return(1);
12153: }
12154: }else if (Typevar[k1] ==2){
12155: k3=Tposprod[k1];
12156: k4=Tposprod[k2];
12157: 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 12158: 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]]);
12159: 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 12160: return(1);
12161: }
12162: }
1.227 brouard 12163: }
12164: }
1.225 brouard 12165: }
12166: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
12167: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 12168: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
12169: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.349 ! brouard 12170:
! 12171: free_imatrix(existcomb,1,NCOVMAX,1,NCOVMAX);
1.137 brouard 12172: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 12173: /*endread:*/
1.225 brouard 12174: printf("Exiting decodemodel: ");
12175: return (1);
1.136 brouard 12176: }
12177:
1.169 brouard 12178: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 12179: {/* Check ages at death */
1.136 brouard 12180: int i, m;
1.218 brouard 12181: int firstone=0;
12182:
1.136 brouard 12183: for (i=1; i<=imx; i++) {
12184: for(m=2; (m<= maxwav); m++) {
12185: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
12186: anint[m][i]=9999;
1.216 brouard 12187: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
12188: s[m][i]=-1;
1.136 brouard 12189: }
12190: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 12191: *nberr = *nberr + 1;
1.218 brouard 12192: if(firstone == 0){
12193: firstone=1;
1.260 brouard 12194: 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 12195: }
1.262 brouard 12196: 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 12197: s[m][i]=-1; /* Droping the death status */
1.136 brouard 12198: }
12199: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 12200: (*nberr)++;
1.259 brouard 12201: 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 12202: 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 12203: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 12204: }
12205: }
12206: }
12207:
12208: for (i=1; i<=imx; i++) {
12209: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
12210: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 12211: 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 12212: if (s[m][i] >= nlstate+1) {
1.169 brouard 12213: if(agedc[i]>0){
12214: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 12215: agev[m][i]=agedc[i];
1.214 brouard 12216: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 12217: }else {
1.136 brouard 12218: if ((int)andc[i]!=9999){
12219: nbwarn++;
12220: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
12221: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
12222: agev[m][i]=-1;
12223: }
12224: }
1.169 brouard 12225: } /* agedc > 0 */
1.214 brouard 12226: } /* end if */
1.136 brouard 12227: else if(s[m][i] !=9){ /* Standard case, age in fractional
12228: years but with the precision of a month */
12229: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
12230: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
12231: agev[m][i]=1;
12232: else if(agev[m][i] < *agemin){
12233: *agemin=agev[m][i];
12234: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
12235: }
12236: else if(agev[m][i] >*agemax){
12237: *agemax=agev[m][i];
1.156 brouard 12238: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 12239: }
12240: /*agev[m][i]=anint[m][i]-annais[i];*/
12241: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 12242: } /* en if 9*/
1.136 brouard 12243: else { /* =9 */
1.214 brouard 12244: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 12245: agev[m][i]=1;
12246: s[m][i]=-1;
12247: }
12248: }
1.214 brouard 12249: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 12250: agev[m][i]=1;
1.214 brouard 12251: else{
12252: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
12253: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
12254: agev[m][i]=0;
12255: }
12256: } /* End for lastpass */
12257: }
1.136 brouard 12258:
12259: for (i=1; i<=imx; i++) {
12260: for(m=firstpass; (m<=lastpass); m++){
12261: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 12262: (*nberr)++;
1.136 brouard 12263: 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);
12264: 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);
12265: return 1;
12266: }
12267: }
12268: }
12269:
12270: /*for (i=1; i<=imx; i++){
12271: for (m=firstpass; (m<lastpass); m++){
12272: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
12273: }
12274:
12275: }*/
12276:
12277:
1.139 brouard 12278: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
12279: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 12280:
12281: return (0);
1.164 brouard 12282: /* endread:*/
1.136 brouard 12283: printf("Exiting calandcheckages: ");
12284: return (1);
12285: }
12286:
1.172 brouard 12287: #if defined(_MSC_VER)
12288: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
12289: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
12290: //#include "stdafx.h"
12291: //#include <stdio.h>
12292: //#include <tchar.h>
12293: //#include <windows.h>
12294: //#include <iostream>
12295: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
12296:
12297: LPFN_ISWOW64PROCESS fnIsWow64Process;
12298:
12299: BOOL IsWow64()
12300: {
12301: BOOL bIsWow64 = FALSE;
12302:
12303: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
12304: // (HANDLE, PBOOL);
12305:
12306: //LPFN_ISWOW64PROCESS fnIsWow64Process;
12307:
12308: HMODULE module = GetModuleHandle(_T("kernel32"));
12309: const char funcName[] = "IsWow64Process";
12310: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
12311: GetProcAddress(module, funcName);
12312:
12313: if (NULL != fnIsWow64Process)
12314: {
12315: if (!fnIsWow64Process(GetCurrentProcess(),
12316: &bIsWow64))
12317: //throw std::exception("Unknown error");
12318: printf("Unknown error\n");
12319: }
12320: return bIsWow64 != FALSE;
12321: }
12322: #endif
1.177 brouard 12323:
1.191 brouard 12324: void syscompilerinfo(int logged)
1.292 brouard 12325: {
12326: #include <stdint.h>
12327:
12328: /* #include "syscompilerinfo.h"*/
1.185 brouard 12329: /* command line Intel compiler 32bit windows, XP compatible:*/
12330: /* /GS /W3 /Gy
12331: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
12332: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
12333: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 12334: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
12335: */
12336: /* 64 bits */
1.185 brouard 12337: /*
12338: /GS /W3 /Gy
12339: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
12340: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
12341: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
12342: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
12343: /* Optimization are useless and O3 is slower than O2 */
12344: /*
12345: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
12346: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
12347: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
12348: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
12349: */
1.186 brouard 12350: /* Link is */ /* /OUT:"visual studio
1.185 brouard 12351: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
12352: /PDB:"visual studio
12353: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
12354: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
12355: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
12356: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
12357: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
12358: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
12359: uiAccess='false'"
12360: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
12361: /NOLOGO /TLBID:1
12362: */
1.292 brouard 12363:
12364:
1.177 brouard 12365: #if defined __INTEL_COMPILER
1.178 brouard 12366: #if defined(__GNUC__)
12367: struct utsname sysInfo; /* For Intel on Linux and OS/X */
12368: #endif
1.177 brouard 12369: #elif defined(__GNUC__)
1.179 brouard 12370: #ifndef __APPLE__
1.174 brouard 12371: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 12372: #endif
1.177 brouard 12373: struct utsname sysInfo;
1.178 brouard 12374: int cross = CROSS;
12375: if (cross){
12376: printf("Cross-");
1.191 brouard 12377: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 12378: }
1.174 brouard 12379: #endif
12380:
1.191 brouard 12381: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 12382: #if defined(__clang__)
1.191 brouard 12383: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 12384: #endif
12385: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 12386: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 12387: #endif
12388: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 12389: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 12390: #endif
12391: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 12392: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 12393: #endif
12394: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 12395: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 12396: #endif
12397: #if defined(_MSC_VER)
1.191 brouard 12398: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 12399: #endif
12400: #if defined(__PGI)
1.191 brouard 12401: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 12402: #endif
12403: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 12404: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 12405: #endif
1.191 brouard 12406: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 12407:
1.167 brouard 12408: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
12409: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
12410: // Windows (x64 and x86)
1.191 brouard 12411: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 12412: #elif __unix__ // all unices, not all compilers
12413: // Unix
1.191 brouard 12414: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 12415: #elif __linux__
12416: // linux
1.191 brouard 12417: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 12418: #elif __APPLE__
1.174 brouard 12419: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 12420: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 12421: #endif
12422:
12423: /* __MINGW32__ */
12424: /* __CYGWIN__ */
12425: /* __MINGW64__ */
12426: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
12427: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
12428: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
12429: /* _WIN64 // Defined for applications for Win64. */
12430: /* _M_X64 // Defined for compilations that target x64 processors. */
12431: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 12432:
1.167 brouard 12433: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 12434: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 12435: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 12436: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 12437: #else
1.191 brouard 12438: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 12439: #endif
12440:
1.169 brouard 12441: #if defined(__GNUC__)
12442: # if defined(__GNUC_PATCHLEVEL__)
12443: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
12444: + __GNUC_MINOR__ * 100 \
12445: + __GNUC_PATCHLEVEL__)
12446: # else
12447: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
12448: + __GNUC_MINOR__ * 100)
12449: # endif
1.174 brouard 12450: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 12451: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 12452:
12453: if (uname(&sysInfo) != -1) {
12454: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 12455: 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 12456: }
12457: else
12458: perror("uname() error");
1.179 brouard 12459: //#ifndef __INTEL_COMPILER
12460: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 12461: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 12462: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 12463: #endif
1.169 brouard 12464: #endif
1.172 brouard 12465:
1.286 brouard 12466: // void main ()
1.172 brouard 12467: // {
1.169 brouard 12468: #if defined(_MSC_VER)
1.174 brouard 12469: if (IsWow64()){
1.191 brouard 12470: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
12471: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 12472: }
12473: else{
1.191 brouard 12474: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
12475: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 12476: }
1.172 brouard 12477: // printf("\nPress Enter to continue...");
12478: // getchar();
12479: // }
12480:
1.169 brouard 12481: #endif
12482:
1.167 brouard 12483:
1.219 brouard 12484: }
1.136 brouard 12485:
1.219 brouard 12486: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 12487: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.332 brouard 12488: /* Computes the prevalence limit for each combination of the dummy covariates */
1.235 brouard 12489: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 12490: /* double ftolpl = 1.e-10; */
1.180 brouard 12491: double age, agebase, agelim;
1.203 brouard 12492: double tot;
1.180 brouard 12493:
1.202 brouard 12494: strcpy(filerespl,"PL_");
12495: strcat(filerespl,fileresu);
12496: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 12497: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
12498: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 12499: }
1.288 brouard 12500: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
12501: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 12502: pstamp(ficrespl);
1.288 brouard 12503: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 12504: fprintf(ficrespl,"#Age ");
12505: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
12506: fprintf(ficrespl,"\n");
1.180 brouard 12507:
1.219 brouard 12508: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 12509:
1.219 brouard 12510: agebase=ageminpar;
12511: agelim=agemaxpar;
1.180 brouard 12512:
1.227 brouard 12513: /* i1=pow(2,ncoveff); */
1.234 brouard 12514: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 12515: if (cptcovn < 1){i1=1;}
1.180 brouard 12516:
1.337 brouard 12517: /* for(k=1; k<=i1;k++){ /\* For each combination k of dummy covariates in the model *\/ */
1.238 brouard 12518: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 12519: k=TKresult[nres];
1.338 brouard 12520: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12521: /* if(i1 != 1 && TKresult[nres]!= k) /\* We found the combination k corresponding to the resultline value of dummies *\/ */
12522: /* continue; */
1.235 brouard 12523:
1.238 brouard 12524: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12525: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
12526: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
12527: /* k=k+1; */
12528: /* to clean */
1.332 brouard 12529: /*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*/
1.238 brouard 12530: fprintf(ficrespl,"#******");
12531: printf("#******");
12532: fprintf(ficlog,"#******");
1.337 brouard 12533: 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 12534: /* fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Here problem for varying dummy*\/ */
1.337 brouard 12535: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12536: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12537: fprintf(ficrespl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12538: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12539: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12540: }
12541: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
12542: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12543: /* fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12544: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12545: /* } */
1.238 brouard 12546: fprintf(ficrespl,"******\n");
12547: printf("******\n");
12548: fprintf(ficlog,"******\n");
12549: if(invalidvarcomb[k]){
12550: printf("\nCombination (%d) ignored because no case \n",k);
12551: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
12552: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
12553: continue;
12554: }
1.219 brouard 12555:
1.238 brouard 12556: fprintf(ficrespl,"#Age ");
1.337 brouard 12557: /* for(j=1;j<=cptcoveff;j++) { */
12558: /* fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12559: /* } */
12560: for(j=1;j<=cptcovs;j++) { /* New the quanti variable is added */
12561: fprintf(ficrespl,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12562: }
12563: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
12564: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 12565:
1.238 brouard 12566: for (age=agebase; age<=agelim; age++){
12567: /* for (age=agebase; age<=agebase; age++){ */
1.337 brouard 12568: /**< Computes the prevalence limit in each live state at age x and for covariate combination (k and) nres */
12569: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres); /* Nicely done */
1.238 brouard 12570: fprintf(ficrespl,"%.0f ",age );
1.337 brouard 12571: /* for(j=1;j<=cptcoveff;j++) */
12572: /* fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12573: for(j=1;j<=cptcovs;j++)
12574: fprintf(ficrespl,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12575: tot=0.;
12576: for(i=1; i<=nlstate;i++){
12577: tot += prlim[i][i];
12578: fprintf(ficrespl," %.5f", prlim[i][i]);
12579: }
12580: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
12581: } /* Age */
12582: /* was end of cptcod */
1.337 brouard 12583: } /* nres */
12584: /* } /\* for each combination *\/ */
1.219 brouard 12585: return 0;
1.180 brouard 12586: }
12587:
1.218 brouard 12588: 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 12589: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 12590:
12591: /* Computes the back prevalence limit for any combination of covariate values
12592: * at any age between ageminpar and agemaxpar
12593: */
1.235 brouard 12594: int i, j, k, i1, nres=0 ;
1.217 brouard 12595: /* double ftolpl = 1.e-10; */
12596: double age, agebase, agelim;
12597: double tot;
1.218 brouard 12598: /* double ***mobaverage; */
12599: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 12600:
12601: strcpy(fileresplb,"PLB_");
12602: strcat(fileresplb,fileresu);
12603: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 12604: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
12605: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 12606: }
1.288 brouard 12607: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
12608: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 12609: pstamp(ficresplb);
1.288 brouard 12610: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 12611: fprintf(ficresplb,"#Age ");
12612: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
12613: fprintf(ficresplb,"\n");
12614:
1.218 brouard 12615:
12616: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
12617:
12618: agebase=ageminpar;
12619: agelim=agemaxpar;
12620:
12621:
1.227 brouard 12622: i1=pow(2,cptcoveff);
1.218 brouard 12623: if (cptcovn < 1){i1=1;}
1.227 brouard 12624:
1.238 brouard 12625: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.338 brouard 12626: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
12627: k=TKresult[nres];
12628: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
12629: /* if(i1 != 1 && TKresult[nres]!= k) */
12630: /* continue; */
12631: /* /\*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*\/ */
1.238 brouard 12632: fprintf(ficresplb,"#******");
12633: printf("#******");
12634: fprintf(ficlog,"#******");
1.338 brouard 12635: 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) */
12636: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12637: fprintf(ficresplb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12638: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12639: }
1.338 brouard 12640: /* for(j=1;j<=cptcoveff ;j++) {/\* all covariates *\/ */
12641: /* fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12642: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12643: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12644: /* } */
12645: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
12646: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12647: /* fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12648: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12649: /* } */
1.238 brouard 12650: fprintf(ficresplb,"******\n");
12651: printf("******\n");
12652: fprintf(ficlog,"******\n");
12653: if(invalidvarcomb[k]){
12654: printf("\nCombination (%d) ignored because no cases \n",k);
12655: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
12656: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
12657: continue;
12658: }
1.218 brouard 12659:
1.238 brouard 12660: fprintf(ficresplb,"#Age ");
1.338 brouard 12661: for(j=1;j<=cptcovs;j++) {
12662: fprintf(ficresplb,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12663: }
12664: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
12665: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 12666:
12667:
1.238 brouard 12668: for (age=agebase; age<=agelim; age++){
12669: /* for (age=agebase; age<=agebase; age++){ */
12670: if(mobilavproj > 0){
12671: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
12672: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 12673: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 12674: }else if (mobilavproj == 0){
12675: 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);
12676: 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);
12677: exit(1);
12678: }else{
12679: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 12680: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 12681: /* printf("TOTOT\n"); */
12682: /* exit(1); */
1.238 brouard 12683: }
12684: fprintf(ficresplb,"%.0f ",age );
1.338 brouard 12685: for(j=1;j<=cptcovs;j++)
12686: fprintf(ficresplb,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12687: tot=0.;
12688: for(i=1; i<=nlstate;i++){
12689: tot += bprlim[i][i];
12690: fprintf(ficresplb," %.5f", bprlim[i][i]);
12691: }
12692: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
12693: } /* Age */
12694: /* was end of cptcod */
1.255 brouard 12695: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.338 brouard 12696: /* } /\* end of any combination *\/ */
1.238 brouard 12697: } /* end of nres */
1.218 brouard 12698: /* hBijx(p, bage, fage); */
12699: /* fclose(ficrespijb); */
12700:
12701: return 0;
1.217 brouard 12702: }
1.218 brouard 12703:
1.180 brouard 12704: int hPijx(double *p, int bage, int fage){
12705: /*------------- h Pij x at various ages ------------*/
1.336 brouard 12706: /* to be optimized with precov */
1.180 brouard 12707: int stepsize;
12708: int agelim;
12709: int hstepm;
12710: int nhstepm;
1.235 brouard 12711: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 12712:
12713: double agedeb;
12714: double ***p3mat;
12715:
1.337 brouard 12716: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
12717: if((ficrespij=fopen(filerespij,"w"))==NULL) {
12718: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
12719: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
12720: }
12721: printf("Computing pij: result on file '%s' \n", filerespij);
12722: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
12723:
12724: stepsize=(int) (stepm+YEARM-1)/YEARM;
12725: /*if (stepm<=24) stepsize=2;*/
12726:
12727: agelim=AGESUP;
12728: hstepm=stepsize*YEARM; /* Every year of age */
12729: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
12730:
12731: /* hstepm=1; aff par mois*/
12732: pstamp(ficrespij);
12733: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
12734: i1= pow(2,cptcoveff);
12735: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12736: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
12737: /* k=k+1; */
12738: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
12739: k=TKresult[nres];
1.338 brouard 12740: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12741: /* for(k=1; k<=i1;k++){ */
12742: /* if(i1 != 1 && TKresult[nres]!= k) */
12743: /* continue; */
12744: fprintf(ficrespij,"\n#****** ");
12745: for(j=1;j<=cptcovs;j++){
12746: fprintf(ficrespij," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12747: /* fprintf(ficrespij,"@wV%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12748: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
12749: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12750: /* fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12751: }
12752: fprintf(ficrespij,"******\n");
12753:
12754: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
12755: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
12756: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
12757:
12758: /* nhstepm=nhstepm*YEARM; aff par mois*/
12759:
12760: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12761: oldm=oldms;savm=savms;
12762: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
12763: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
12764: for(i=1; i<=nlstate;i++)
12765: for(j=1; j<=nlstate+ndeath;j++)
12766: fprintf(ficrespij," %1d-%1d",i,j);
12767: fprintf(ficrespij,"\n");
12768: for (h=0; h<=nhstepm; h++){
12769: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
12770: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.183 brouard 12771: for(i=1; i<=nlstate;i++)
12772: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 12773: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.183 brouard 12774: fprintf(ficrespij,"\n");
12775: }
1.337 brouard 12776: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12777: fprintf(ficrespij,"\n");
1.180 brouard 12778: }
1.337 brouard 12779: }
12780: /*}*/
12781: return 0;
1.180 brouard 12782: }
1.218 brouard 12783:
12784: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 12785: /*------------- h Bij x at various ages ------------*/
1.336 brouard 12786: /* To be optimized with precov */
1.217 brouard 12787: int stepsize;
1.218 brouard 12788: /* int agelim; */
12789: int ageminl;
1.217 brouard 12790: int hstepm;
12791: int nhstepm;
1.238 brouard 12792: int h, i, i1, j, k, nres;
1.218 brouard 12793:
1.217 brouard 12794: double agedeb;
12795: double ***p3mat;
1.218 brouard 12796:
12797: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
12798: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
12799: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
12800: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
12801: }
12802: printf("Computing pij back: result on file '%s' \n", filerespijb);
12803: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
12804:
12805: stepsize=(int) (stepm+YEARM-1)/YEARM;
12806: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 12807:
1.218 brouard 12808: /* agelim=AGESUP; */
1.289 brouard 12809: ageminl=AGEINF; /* was 30 */
1.218 brouard 12810: hstepm=stepsize*YEARM; /* Every year of age */
12811: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
12812:
12813: /* hstepm=1; aff par mois*/
12814: pstamp(ficrespijb);
1.255 brouard 12815: 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 12816: i1= pow(2,cptcoveff);
1.218 brouard 12817: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12818: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
12819: /* k=k+1; */
1.238 brouard 12820: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 12821: k=TKresult[nres];
1.338 brouard 12822: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12823: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
12824: /* if(i1 != 1 && TKresult[nres]!= k) */
12825: /* continue; */
12826: fprintf(ficrespijb,"\n#****** ");
12827: for(j=1;j<=cptcovs;j++){
1.338 brouard 12828: fprintf(ficrespijb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.337 brouard 12829: /* for(j=1;j<=cptcoveff;j++) */
12830: /* fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12831: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
12832: /* fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12833: }
12834: fprintf(ficrespijb,"******\n");
12835: if(invalidvarcomb[k]){ /* Is it necessary here? */
12836: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
12837: continue;
12838: }
12839:
12840: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
12841: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
12842: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
12843: 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 */
12844: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 or 28*/
12845:
12846: /* nhstepm=nhstepm*YEARM; aff par mois*/
12847:
12848: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
12849: /* and memory limitations if stepm is small */
12850:
12851: /* oldm=oldms;savm=savms; */
12852: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
12853: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);/* Bug valgrind */
12854: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
12855: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
12856: for(i=1; i<=nlstate;i++)
12857: for(j=1; j<=nlstate+ndeath;j++)
12858: fprintf(ficrespijb," %1d-%1d",i,j);
12859: fprintf(ficrespijb,"\n");
12860: for (h=0; h<=nhstepm; h++){
12861: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
12862: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
12863: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
1.217 brouard 12864: for(i=1; i<=nlstate;i++)
12865: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 12866: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);/* Bug valgrind */
1.217 brouard 12867: fprintf(ficrespijb,"\n");
1.337 brouard 12868: }
12869: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12870: fprintf(ficrespijb,"\n");
12871: } /* end age deb */
12872: /* } /\* end combination *\/ */
1.238 brouard 12873: } /* end nres */
1.218 brouard 12874: return 0;
12875: } /* hBijx */
1.217 brouard 12876:
1.180 brouard 12877:
1.136 brouard 12878: /***********************************************/
12879: /**************** Main Program *****************/
12880: /***********************************************/
12881:
12882: int main(int argc, char *argv[])
12883: {
12884: #ifdef GSL
12885: const gsl_multimin_fminimizer_type *T;
12886: size_t iteri = 0, it;
12887: int rval = GSL_CONTINUE;
12888: int status = GSL_SUCCESS;
12889: double ssval;
12890: #endif
12891: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 12892: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
12893: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 12894: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 12895: int jj, ll, li, lj, lk;
1.136 brouard 12896: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 12897: int num_filled;
1.136 brouard 12898: int itimes;
12899: int NDIM=2;
12900: int vpopbased=0;
1.235 brouard 12901: int nres=0;
1.258 brouard 12902: int endishere=0;
1.277 brouard 12903: int noffset=0;
1.274 brouard 12904: int ncurrv=0; /* Temporary variable */
12905:
1.164 brouard 12906: char ca[32], cb[32];
1.136 brouard 12907: /* FILE *fichtm; *//* Html File */
12908: /* FILE *ficgp;*/ /*Gnuplot File */
12909: struct stat info;
1.191 brouard 12910: double agedeb=0.;
1.194 brouard 12911:
12912: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 12913: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 12914:
1.165 brouard 12915: double fret;
1.191 brouard 12916: double dum=0.; /* Dummy variable */
1.136 brouard 12917: double ***p3mat;
1.218 brouard 12918: /* double ***mobaverage; */
1.319 brouard 12919: double wald;
1.164 brouard 12920:
12921: char line[MAXLINE];
1.197 brouard 12922: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
12923:
1.234 brouard 12924: char modeltemp[MAXLINE];
1.332 brouard 12925: char resultline[MAXLINE], resultlineori[MAXLINE];
1.230 brouard 12926:
1.136 brouard 12927: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 12928: char *tok, *val; /* pathtot */
1.334 brouard 12929: /* int firstobs=1, lastobs=10; /\* nobs = lastobs-firstobs declared globally ;*\/ */
1.195 brouard 12930: int c, h , cpt, c2;
1.191 brouard 12931: int jl=0;
12932: int i1, j1, jk, stepsize=0;
1.194 brouard 12933: int count=0;
12934:
1.164 brouard 12935: int *tab;
1.136 brouard 12936: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.296 brouard 12937: /* double anprojd, mprojd, jprojd; /\* For eventual projections *\/ */
12938: /* double anprojf, mprojf, jprojf; */
12939: /* double jintmean,mintmean,aintmean; */
12940: int prvforecast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
12941: int prvbackcast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
12942: double yrfproj= 10.0; /* Number of years of forward projections */
12943: double yrbproj= 10.0; /* Number of years of backward projections */
12944: int prevbcast=0; /* defined as global for mlikeli and mle, replacing backcast */
1.136 brouard 12945: int mobilav=0,popforecast=0;
1.191 brouard 12946: int hstepm=0, nhstepm=0;
1.136 brouard 12947: int agemortsup;
12948: float sumlpop=0.;
12949: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
12950: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
12951:
1.191 brouard 12952: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 12953: double ftolpl=FTOL;
12954: double **prlim;
1.217 brouard 12955: double **bprlim;
1.317 brouard 12956: double ***param; /* Matrix of parameters, param[i][j][k] param=ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel)
12957: state of origin, state of destination including death, for each covariate: constante, age, and V1 V2 etc. */
1.251 brouard 12958: double ***paramstart; /* Matrix of starting parameter values */
12959: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 12960: double **matcov; /* Matrix of covariance */
1.203 brouard 12961: double **hess; /* Hessian matrix */
1.136 brouard 12962: double ***delti3; /* Scale */
12963: double *delti; /* Scale */
12964: double ***eij, ***vareij;
12965: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 12966:
1.136 brouard 12967: double *epj, vepp;
1.164 brouard 12968:
1.273 brouard 12969: double dateprev1, dateprev2;
1.296 brouard 12970: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0, dateprojd=0, dateprojf=0;
12971: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0, datebackd=0, datebackf=0;
12972:
1.217 brouard 12973:
1.136 brouard 12974: double **ximort;
1.145 brouard 12975: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 12976: int *dcwave;
12977:
1.164 brouard 12978: char z[1]="c";
1.136 brouard 12979:
12980: /*char *strt;*/
12981: char strtend[80];
1.126 brouard 12982:
1.164 brouard 12983:
1.126 brouard 12984: /* setlocale (LC_ALL, ""); */
12985: /* bindtextdomain (PACKAGE, LOCALEDIR); */
12986: /* textdomain (PACKAGE); */
12987: /* setlocale (LC_CTYPE, ""); */
12988: /* setlocale (LC_MESSAGES, ""); */
12989:
12990: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 12991: rstart_time = time(NULL);
12992: /* (void) gettimeofday(&start_time,&tzp);*/
12993: start_time = *localtime(&rstart_time);
1.126 brouard 12994: curr_time=start_time;
1.157 brouard 12995: /*tml = *localtime(&start_time.tm_sec);*/
12996: /* strcpy(strstart,asctime(&tml)); */
12997: strcpy(strstart,asctime(&start_time));
1.126 brouard 12998:
12999: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 13000: /* tp.tm_sec = tp.tm_sec +86400; */
13001: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 13002: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
13003: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
13004: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 13005: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 13006: /* strt=asctime(&tmg); */
13007: /* printf("Time(after) =%s",strstart); */
13008: /* (void) time (&time_value);
13009: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
13010: * tm = *localtime(&time_value);
13011: * strstart=asctime(&tm);
13012: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
13013: */
13014:
13015: nberr=0; /* Number of errors and warnings */
13016: nbwarn=0;
1.184 brouard 13017: #ifdef WIN32
13018: _getcwd(pathcd, size);
13019: #else
1.126 brouard 13020: getcwd(pathcd, size);
1.184 brouard 13021: #endif
1.191 brouard 13022: syscompilerinfo(0);
1.196 brouard 13023: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 13024: if(argc <=1){
13025: printf("\nEnter the parameter file name: ");
1.205 brouard 13026: if(!fgets(pathr,FILENAMELENGTH,stdin)){
13027: printf("ERROR Empty parameter file name\n");
13028: goto end;
13029: }
1.126 brouard 13030: i=strlen(pathr);
13031: if(pathr[i-1]=='\n')
13032: pathr[i-1]='\0';
1.156 brouard 13033: i=strlen(pathr);
1.205 brouard 13034: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 13035: pathr[i-1]='\0';
1.205 brouard 13036: }
13037: i=strlen(pathr);
13038: if( i==0 ){
13039: printf("ERROR Empty parameter file name\n");
13040: goto end;
13041: }
13042: for (tok = pathr; tok != NULL; ){
1.126 brouard 13043: printf("Pathr |%s|\n",pathr);
13044: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
13045: printf("val= |%s| pathr=%s\n",val,pathr);
13046: strcpy (pathtot, val);
13047: if(pathr[0] == '\0') break; /* Dirty */
13048: }
13049: }
1.281 brouard 13050: else if (argc<=2){
13051: strcpy(pathtot,argv[1]);
13052: }
1.126 brouard 13053: else{
13054: strcpy(pathtot,argv[1]);
1.281 brouard 13055: strcpy(z,argv[2]);
13056: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 13057: }
13058: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
13059: /*cygwin_split_path(pathtot,path,optionfile);
13060: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
13061: /* cutv(path,optionfile,pathtot,'\\');*/
13062:
13063: /* Split argv[0], imach program to get pathimach */
13064: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
13065: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
13066: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
13067: /* strcpy(pathimach,argv[0]); */
13068: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
13069: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
13070: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 13071: #ifdef WIN32
13072: _chdir(path); /* Can be a relative path */
13073: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
13074: #else
1.126 brouard 13075: chdir(path); /* Can be a relative path */
1.184 brouard 13076: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
13077: #endif
13078: printf("Current directory %s!\n",pathcd);
1.126 brouard 13079: strcpy(command,"mkdir ");
13080: strcat(command,optionfilefiname);
13081: if((outcmd=system(command)) != 0){
1.169 brouard 13082: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 13083: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
13084: /* fclose(ficlog); */
13085: /* exit(1); */
13086: }
13087: /* if((imk=mkdir(optionfilefiname))<0){ */
13088: /* perror("mkdir"); */
13089: /* } */
13090:
13091: /*-------- arguments in the command line --------*/
13092:
1.186 brouard 13093: /* Main Log file */
1.126 brouard 13094: strcat(filelog, optionfilefiname);
13095: strcat(filelog,".log"); /* */
13096: if((ficlog=fopen(filelog,"w"))==NULL) {
13097: printf("Problem with logfile %s\n",filelog);
13098: goto end;
13099: }
13100: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 13101: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 13102: fprintf(ficlog,"\nEnter the parameter file name: \n");
13103: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
13104: path=%s \n\
13105: optionfile=%s\n\
13106: optionfilext=%s\n\
1.156 brouard 13107: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 13108:
1.197 brouard 13109: syscompilerinfo(1);
1.167 brouard 13110:
1.126 brouard 13111: printf("Local time (at start):%s",strstart);
13112: fprintf(ficlog,"Local time (at start): %s",strstart);
13113: fflush(ficlog);
13114: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 13115: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 13116:
13117: /* */
13118: strcpy(fileres,"r");
13119: strcat(fileres, optionfilefiname);
1.201 brouard 13120: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 13121: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 13122: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 13123:
1.186 brouard 13124: /* Main ---------arguments file --------*/
1.126 brouard 13125:
13126: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 13127: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
13128: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 13129: fflush(ficlog);
1.149 brouard 13130: /* goto end; */
13131: exit(70);
1.126 brouard 13132: }
13133:
13134: strcpy(filereso,"o");
1.201 brouard 13135: strcat(filereso,fileresu);
1.126 brouard 13136: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
13137: printf("Problem with Output resultfile: %s\n", filereso);
13138: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
13139: fflush(ficlog);
13140: goto end;
13141: }
1.278 brouard 13142: /*-------- Rewriting parameter file ----------*/
13143: strcpy(rfileres,"r"); /* "Rparameterfile */
13144: strcat(rfileres,optionfilefiname); /* Parameter file first name */
13145: strcat(rfileres,"."); /* */
13146: strcat(rfileres,optionfilext); /* Other files have txt extension */
13147: if((ficres =fopen(rfileres,"w"))==NULL) {
13148: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
13149: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
13150: fflush(ficlog);
13151: goto end;
13152: }
13153: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 13154:
1.278 brouard 13155:
1.126 brouard 13156: /* Reads comments: lines beginning with '#' */
13157: numlinepar=0;
1.277 brouard 13158: /* Is it a BOM UTF-8 Windows file? */
13159: /* First parameter line */
1.197 brouard 13160: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 13161: noffset=0;
13162: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
13163: {
13164: noffset=noffset+3;
13165: printf("# File is an UTF8 Bom.\n"); // 0xBF
13166: }
1.302 brouard 13167: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
13168: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
1.277 brouard 13169: {
13170: noffset=noffset+2;
13171: printf("# File is an UTF16BE BOM file\n");
13172: }
13173: else if( line[0] == 0 && line[1] == 0)
13174: {
13175: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
13176: noffset=noffset+4;
13177: printf("# File is an UTF16BE BOM file\n");
13178: }
13179: } else{
13180: ;/*printf(" Not a BOM file\n");*/
13181: }
13182:
1.197 brouard 13183: /* If line starts with a # it is a comment */
1.277 brouard 13184: if (line[noffset] == '#') {
1.197 brouard 13185: numlinepar++;
13186: fputs(line,stdout);
13187: fputs(line,ficparo);
1.278 brouard 13188: fputs(line,ficres);
1.197 brouard 13189: fputs(line,ficlog);
13190: continue;
13191: }else
13192: break;
13193: }
13194: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
13195: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
13196: if (num_filled != 5) {
13197: printf("Should be 5 parameters\n");
1.283 brouard 13198: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 13199: }
1.126 brouard 13200: numlinepar++;
1.197 brouard 13201: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 13202: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
13203: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
13204: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 13205: }
13206: /* Second parameter line */
13207: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 13208: /* while(fscanf(ficpar,"%[^\n]", line)) { */
13209: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 13210: if (line[0] == '#') {
13211: numlinepar++;
1.283 brouard 13212: printf("%s",line);
13213: fprintf(ficres,"%s",line);
13214: fprintf(ficparo,"%s",line);
13215: fprintf(ficlog,"%s",line);
1.197 brouard 13216: continue;
13217: }else
13218: break;
13219: }
1.223 brouard 13220: 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", \
13221: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
13222: if (num_filled != 11) {
13223: 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 13224: printf("but line=%s\n",line);
1.283 brouard 13225: 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");
13226: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 13227: }
1.286 brouard 13228: if( lastpass > maxwav){
13229: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
13230: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
13231: fflush(ficlog);
13232: goto end;
13233: }
13234: 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 13235: 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 13236: 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 13237: 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 13238: }
1.203 brouard 13239: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 13240: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 13241: /* Third parameter line */
13242: while(fgets(line, MAXLINE, ficpar)) {
13243: /* If line starts with a # it is a comment */
13244: if (line[0] == '#') {
13245: numlinepar++;
1.283 brouard 13246: printf("%s",line);
13247: fprintf(ficres,"%s",line);
13248: fprintf(ficparo,"%s",line);
13249: fprintf(ficlog,"%s",line);
1.197 brouard 13250: continue;
13251: }else
13252: break;
13253: }
1.201 brouard 13254: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.279 brouard 13255: if (num_filled != 1){
1.302 brouard 13256: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
13257: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
1.197 brouard 13258: model[0]='\0';
13259: goto end;
13260: }
13261: else{
13262: if (model[0]=='+'){
13263: for(i=1; i<=strlen(model);i++)
13264: modeltemp[i-1]=model[i];
1.201 brouard 13265: strcpy(model,modeltemp);
1.197 brouard 13266: }
13267: }
1.338 brouard 13268: /* printf(" model=1+age%s modeltemp= %s, model=1+age+%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 13269: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 13270: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
13271: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
13272: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 13273: }
13274: /* 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); */
13275: /* numlinepar=numlinepar+3; /\* In general *\/ */
13276: /* 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 13277: /* 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); */
13278: /* 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 13279: fflush(ficlog);
1.190 brouard 13280: /* if(model[0]=='#'|| model[0]== '\0'){ */
13281: if(model[0]=='#'){
1.279 brouard 13282: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
13283: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
13284: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 13285: if(mle != -1){
1.279 brouard 13286: 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 13287: exit(1);
13288: }
13289: }
1.126 brouard 13290: while((c=getc(ficpar))=='#' && c!= EOF){
13291: ungetc(c,ficpar);
13292: fgets(line, MAXLINE, ficpar);
13293: numlinepar++;
1.195 brouard 13294: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
13295: z[0]=line[1];
1.342 brouard 13296: }else if(line[1]=='d'){ /* For debugging individual values of covariates in ficresilk */
1.343 brouard 13297: debugILK=1;printf("DebugILK\n");
1.195 brouard 13298: }
13299: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 13300: fputs(line, stdout);
13301: //puts(line);
1.126 brouard 13302: fputs(line,ficparo);
13303: fputs(line,ficlog);
13304: }
13305: ungetc(c,ficpar);
13306:
13307:
1.290 brouard 13308: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
13309: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
13310: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
1.341 brouard 13311: /* if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /\**< Time varying covariate (dummy and quantitative)*\/ */
13312: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs); /**< Might be better */
1.136 brouard 13313: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
13314: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
13315: v1+v2*age+v2*v3 makes cptcovn = 3
13316: */
13317: if (strlen(model)>1)
1.187 brouard 13318: 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 13319: else
1.187 brouard 13320: ncovmodel=2; /* Constant and age */
1.133 brouard 13321: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
13322: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 13323: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
13324: 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);
13325: 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);
13326: fflush(stdout);
13327: fclose (ficlog);
13328: goto end;
13329: }
1.126 brouard 13330: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
13331: delti=delti3[1][1];
13332: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
13333: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 13334: /* We could also provide initial parameters values giving by simple logistic regression
13335: * only one way, that is without matrix product. We will have nlstate maximizations */
13336: /* for(i=1;i<nlstate;i++){ */
13337: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
13338: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
13339: /* } */
1.126 brouard 13340: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 13341: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
13342: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 13343: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
13344: fclose (ficparo);
13345: fclose (ficlog);
13346: goto end;
13347: exit(0);
1.220 brouard 13348: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 13349: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 13350: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
13351: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 13352: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
13353: matcov=matrix(1,npar,1,npar);
1.203 brouard 13354: hess=matrix(1,npar,1,npar);
1.220 brouard 13355: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 13356: /* Read guessed parameters */
1.126 brouard 13357: /* Reads comments: lines beginning with '#' */
13358: while((c=getc(ficpar))=='#' && c!= EOF){
13359: ungetc(c,ficpar);
13360: fgets(line, MAXLINE, ficpar);
13361: numlinepar++;
1.141 brouard 13362: fputs(line,stdout);
1.126 brouard 13363: fputs(line,ficparo);
13364: fputs(line,ficlog);
13365: }
13366: ungetc(c,ficpar);
13367:
13368: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 13369: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 13370: for(i=1; i <=nlstate; i++){
1.234 brouard 13371: j=0;
1.126 brouard 13372: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 13373: if(jj==i) continue;
13374: j++;
1.292 brouard 13375: while((c=getc(ficpar))=='#' && c!= EOF){
13376: ungetc(c,ficpar);
13377: fgets(line, MAXLINE, ficpar);
13378: numlinepar++;
13379: fputs(line,stdout);
13380: fputs(line,ficparo);
13381: fputs(line,ficlog);
13382: }
13383: ungetc(c,ficpar);
1.234 brouard 13384: fscanf(ficpar,"%1d%1d",&i1,&j1);
13385: if ((i1 != i) || (j1 != jj)){
13386: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 13387: It might be a problem of design; if ncovcol and the model are correct\n \
13388: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 13389: exit(1);
13390: }
13391: fprintf(ficparo,"%1d%1d",i1,j1);
13392: if(mle==1)
13393: printf("%1d%1d",i,jj);
13394: fprintf(ficlog,"%1d%1d",i,jj);
13395: for(k=1; k<=ncovmodel;k++){
13396: fscanf(ficpar," %lf",¶m[i][j][k]);
13397: if(mle==1){
13398: printf(" %lf",param[i][j][k]);
13399: fprintf(ficlog," %lf",param[i][j][k]);
13400: }
13401: else
13402: fprintf(ficlog," %lf",param[i][j][k]);
13403: fprintf(ficparo," %lf",param[i][j][k]);
13404: }
13405: fscanf(ficpar,"\n");
13406: numlinepar++;
13407: if(mle==1)
13408: printf("\n");
13409: fprintf(ficlog,"\n");
13410: fprintf(ficparo,"\n");
1.126 brouard 13411: }
13412: }
13413: fflush(ficlog);
1.234 brouard 13414:
1.251 brouard 13415: /* Reads parameters values */
1.126 brouard 13416: p=param[1][1];
1.251 brouard 13417: pstart=paramstart[1][1];
1.126 brouard 13418:
13419: /* Reads comments: lines beginning with '#' */
13420: while((c=getc(ficpar))=='#' && c!= EOF){
13421: ungetc(c,ficpar);
13422: fgets(line, MAXLINE, ficpar);
13423: numlinepar++;
1.141 brouard 13424: fputs(line,stdout);
1.126 brouard 13425: fputs(line,ficparo);
13426: fputs(line,ficlog);
13427: }
13428: ungetc(c,ficpar);
13429:
13430: for(i=1; i <=nlstate; i++){
13431: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 13432: fscanf(ficpar,"%1d%1d",&i1,&j1);
13433: if ( (i1-i) * (j1-j) != 0){
13434: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
13435: exit(1);
13436: }
13437: printf("%1d%1d",i,j);
13438: fprintf(ficparo,"%1d%1d",i1,j1);
13439: fprintf(ficlog,"%1d%1d",i1,j1);
13440: for(k=1; k<=ncovmodel;k++){
13441: fscanf(ficpar,"%le",&delti3[i][j][k]);
13442: printf(" %le",delti3[i][j][k]);
13443: fprintf(ficparo," %le",delti3[i][j][k]);
13444: fprintf(ficlog," %le",delti3[i][j][k]);
13445: }
13446: fscanf(ficpar,"\n");
13447: numlinepar++;
13448: printf("\n");
13449: fprintf(ficparo,"\n");
13450: fprintf(ficlog,"\n");
1.126 brouard 13451: }
13452: }
13453: fflush(ficlog);
1.234 brouard 13454:
1.145 brouard 13455: /* Reads covariance matrix */
1.126 brouard 13456: delti=delti3[1][1];
1.220 brouard 13457:
13458:
1.126 brouard 13459: /* 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 13460:
1.126 brouard 13461: /* Reads comments: lines beginning with '#' */
13462: while((c=getc(ficpar))=='#' && c!= EOF){
13463: ungetc(c,ficpar);
13464: fgets(line, MAXLINE, ficpar);
13465: numlinepar++;
1.141 brouard 13466: fputs(line,stdout);
1.126 brouard 13467: fputs(line,ficparo);
13468: fputs(line,ficlog);
13469: }
13470: ungetc(c,ficpar);
1.220 brouard 13471:
1.126 brouard 13472: matcov=matrix(1,npar,1,npar);
1.203 brouard 13473: hess=matrix(1,npar,1,npar);
1.131 brouard 13474: for(i=1; i <=npar; i++)
13475: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 13476:
1.194 brouard 13477: /* Scans npar lines */
1.126 brouard 13478: for(i=1; i <=npar; i++){
1.226 brouard 13479: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 13480: if(count != 3){
1.226 brouard 13481: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 13482: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
13483: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 13484: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 13485: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
13486: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 13487: exit(1);
1.220 brouard 13488: }else{
1.226 brouard 13489: if(mle==1)
13490: printf("%1d%1d%d",i1,j1,jk);
13491: }
13492: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
13493: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 13494: for(j=1; j <=i; j++){
1.226 brouard 13495: fscanf(ficpar," %le",&matcov[i][j]);
13496: if(mle==1){
13497: printf(" %.5le",matcov[i][j]);
13498: }
13499: fprintf(ficlog," %.5le",matcov[i][j]);
13500: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 13501: }
13502: fscanf(ficpar,"\n");
13503: numlinepar++;
13504: if(mle==1)
1.220 brouard 13505: printf("\n");
1.126 brouard 13506: fprintf(ficlog,"\n");
13507: fprintf(ficparo,"\n");
13508: }
1.194 brouard 13509: /* End of read covariance matrix npar lines */
1.126 brouard 13510: for(i=1; i <=npar; i++)
13511: for(j=i+1;j<=npar;j++)
1.226 brouard 13512: matcov[i][j]=matcov[j][i];
1.126 brouard 13513:
13514: if(mle==1)
13515: printf("\n");
13516: fprintf(ficlog,"\n");
13517:
13518: fflush(ficlog);
13519:
13520: } /* End of mle != -3 */
1.218 brouard 13521:
1.186 brouard 13522: /* Main data
13523: */
1.290 brouard 13524: nobs=lastobs-firstobs+1; /* was = lastobs;*/
13525: /* num=lvector(1,n); */
13526: /* moisnais=vector(1,n); */
13527: /* annais=vector(1,n); */
13528: /* moisdc=vector(1,n); */
13529: /* andc=vector(1,n); */
13530: /* weight=vector(1,n); */
13531: /* agedc=vector(1,n); */
13532: /* cod=ivector(1,n); */
13533: /* for(i=1;i<=n;i++){ */
13534: num=lvector(firstobs,lastobs);
13535: moisnais=vector(firstobs,lastobs);
13536: annais=vector(firstobs,lastobs);
13537: moisdc=vector(firstobs,lastobs);
13538: andc=vector(firstobs,lastobs);
13539: weight=vector(firstobs,lastobs);
13540: agedc=vector(firstobs,lastobs);
13541: cod=ivector(firstobs,lastobs);
13542: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 13543: num[i]=0;
13544: moisnais[i]=0;
13545: annais[i]=0;
13546: moisdc[i]=0;
13547: andc[i]=0;
13548: agedc[i]=0;
13549: cod[i]=0;
13550: weight[i]=1.0; /* Equal weights, 1 by default */
13551: }
1.290 brouard 13552: mint=matrix(1,maxwav,firstobs,lastobs);
13553: anint=matrix(1,maxwav,firstobs,lastobs);
1.325 brouard 13554: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
1.336 brouard 13555: /* printf("BUG ncovmodel=%d NCOVMAX=%d 2**ncovmodel=%f BUG\n",ncovmodel,NCOVMAX,pow(2,ncovmodel)); */
1.126 brouard 13556: tab=ivector(1,NCOVMAX);
1.144 brouard 13557: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 13558: 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 13559:
1.136 brouard 13560: /* Reads data from file datafile */
13561: if (readdata(datafile, firstobs, lastobs, &imx)==1)
13562: goto end;
13563:
13564: /* Calculation of the number of parameters from char model */
1.234 brouard 13565: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 13566: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
13567: k=3 V4 Tvar[k=3]= 4 (from V4)
13568: k=2 V1 Tvar[k=2]= 1 (from V1)
13569: k=1 Tvar[1]=2 (from V2)
1.234 brouard 13570: */
13571:
13572: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
13573: TvarsDind=ivector(1,NCOVMAX); /* */
1.330 brouard 13574: TnsdVar=ivector(1,NCOVMAX); /* */
1.335 brouard 13575: /* for(i=1; i<=NCOVMAX;i++) TnsdVar[i]=3; */
1.234 brouard 13576: TvarsD=ivector(1,NCOVMAX); /* */
13577: TvarsQind=ivector(1,NCOVMAX); /* */
13578: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 13579: TvarF=ivector(1,NCOVMAX); /* */
13580: TvarFind=ivector(1,NCOVMAX); /* */
13581: TvarV=ivector(1,NCOVMAX); /* */
13582: TvarVind=ivector(1,NCOVMAX); /* */
13583: TvarA=ivector(1,NCOVMAX); /* */
13584: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 13585: TvarFD=ivector(1,NCOVMAX); /* */
13586: TvarFDind=ivector(1,NCOVMAX); /* */
13587: TvarFQ=ivector(1,NCOVMAX); /* */
13588: TvarFQind=ivector(1,NCOVMAX); /* */
13589: TvarVD=ivector(1,NCOVMAX); /* */
13590: TvarVDind=ivector(1,NCOVMAX); /* */
13591: TvarVQ=ivector(1,NCOVMAX); /* */
13592: TvarVQind=ivector(1,NCOVMAX); /* */
1.339 brouard 13593: TvarVV=ivector(1,NCOVMAX); /* */
13594: TvarVVind=ivector(1,NCOVMAX); /* */
1.349 ! brouard 13595: TvarVVA=ivector(1,NCOVMAX); /* */
! 13596: TvarVVAind=ivector(1,NCOVMAX); /* */
! 13597: TvarAVVA=ivector(1,NCOVMAX); /* */
! 13598: TvarAVVAind=ivector(1,NCOVMAX); /* */
1.231 brouard 13599:
1.230 brouard 13600: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 13601: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 13602: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
13603: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
13604: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.349 ! brouard 13605: DummyV=ivector(-1,NCOVMAX); /* 1 to 3 */
! 13606: FixedV=ivector(-1,NCOVMAX); /* 1 to 3 */
! 13607:
1.137 brouard 13608: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
13609: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
13610: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
13611: */
13612: /* For model-covariate k tells which data-covariate to use but
13613: because this model-covariate is a construction we invent a new column
13614: ncovcol + k1
13615: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
13616: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 13617: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
13618: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 13619: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
13620: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 13621: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 13622: */
1.145 brouard 13623: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
13624: 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 13625: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
13626: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.349 ! brouard 13627: Tvardk=imatrix(-1,NCOVMAX,1,2);
1.145 brouard 13628: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 13629: 4 covariates (3 plus signs)
13630: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
1.328 brouard 13631: */
13632: for(i=1;i<NCOVMAX;i++)
13633: Tage[i]=0;
1.230 brouard 13634: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 13635: * individual dummy, fixed or varying:
13636: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
13637: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 13638: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
13639: * V1 df, V2 qf, V3 & V4 dv, V5 qv
13640: * Tmodelind[1]@9={9,0,3,2,}*/
13641: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
13642: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 13643: * individual quantitative, fixed or varying:
13644: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
13645: * 3, 1, 0, 0, 0, 0, 0, 0},
13646: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.349 ! brouard 13647:
! 13648: /* Probably useless zeroes */
! 13649: for(i=1;i<NCOVMAX;i++){
! 13650: DummyV[i]=0;
! 13651: FixedV[i]=0;
! 13652: }
! 13653:
! 13654: for(i=1; i <=ncovcol;i++){
! 13655: DummyV[i]=0;
! 13656: FixedV[i]=0;
! 13657: }
! 13658: for(i=ncovcol+1; i <=ncovcol+nqv;i++){
! 13659: DummyV[i]=1;
! 13660: FixedV[i]=0;
! 13661: }
! 13662: for(i=ncovcol+nqv+1; i <=ncovcol+nqv+ntv;i++){
! 13663: DummyV[i]=0;
! 13664: FixedV[i]=1;
! 13665: }
! 13666: for(i=ncovcol+nqv+ntv+1; i <=ncovcol+nqv+ntv+nqtv;i++){
! 13667: DummyV[i]=1;
! 13668: FixedV[i]=1;
! 13669: }
! 13670: for(i=1; i <=ncovcol+nqv+ntv+nqtv;i++){
! 13671: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",i,i,DummyV[i],i,FixedV[i]);
! 13672: fprintf(ficlog,"Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",i,i,DummyV[i],i,FixedV[i]);
! 13673: }
! 13674:
! 13675:
! 13676:
1.186 brouard 13677: /* Main decodemodel */
13678:
1.187 brouard 13679:
1.223 brouard 13680: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 13681: goto end;
13682:
1.137 brouard 13683: if((double)(lastobs-imx)/(double)imx > 1.10){
13684: nbwarn++;
13685: 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);
13686: 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);
13687: }
1.136 brouard 13688: /* if(mle==1){*/
1.137 brouard 13689: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
13690: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 13691: }
13692:
13693: /*-calculation of age at interview from date of interview and age at death -*/
13694: agev=matrix(1,maxwav,1,imx);
13695:
13696: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
13697: goto end;
13698:
1.126 brouard 13699:
1.136 brouard 13700: agegomp=(int)agemin;
1.290 brouard 13701: free_vector(moisnais,firstobs,lastobs);
13702: free_vector(annais,firstobs,lastobs);
1.126 brouard 13703: /* free_matrix(mint,1,maxwav,1,n);
13704: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 13705: /* free_vector(moisdc,1,n); */
13706: /* free_vector(andc,1,n); */
1.145 brouard 13707: /* */
13708:
1.126 brouard 13709: wav=ivector(1,imx);
1.214 brouard 13710: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
13711: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
13712: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
13713: 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.*/
13714: bh=imatrix(1,lastpass-firstpass+2,1,imx);
13715: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 13716:
13717: /* Concatenates waves */
1.214 brouard 13718: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
13719: Death is a valid wave (if date is known).
13720: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
13721: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
13722: and mw[mi+1][i]. dh depends on stepm.
13723: */
13724:
1.126 brouard 13725: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 13726: /* Concatenates waves */
1.145 brouard 13727:
1.290 brouard 13728: free_vector(moisdc,firstobs,lastobs);
13729: free_vector(andc,firstobs,lastobs);
1.215 brouard 13730:
1.126 brouard 13731: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
13732: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
13733: ncodemax[1]=1;
1.145 brouard 13734: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 13735: cptcoveff=0;
1.220 brouard 13736: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
1.335 brouard 13737: 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 13738: }
13739:
13740: ncovcombmax=pow(2,cptcoveff);
1.338 brouard 13741: invalidvarcomb=ivector(0, ncovcombmax);
13742: for(i=0;i<ncovcombmax;i++)
1.227 brouard 13743: invalidvarcomb[i]=0;
13744:
1.211 brouard 13745: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 13746: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 13747: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 13748:
1.200 brouard 13749: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 13750: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 13751: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 13752: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
13753: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
13754: * (currently 0 or 1) in the data.
13755: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
13756: * corresponding modality (h,j).
13757: */
13758:
1.145 brouard 13759: h=0;
13760: /*if (cptcovn > 0) */
1.126 brouard 13761: m=pow(2,cptcoveff);
13762:
1.144 brouard 13763: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 13764: * For k=4 covariates, h goes from 1 to m=2**k
13765: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
13766: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.329 brouard 13767: * h\k 1 2 3 4 * h-1\k-1 4 3 2 1
13768: *______________________________ *______________________
13769: * 1 i=1 1 i=1 1 i=1 1 i=1 1 * 0 0 0 0 0
13770: * 2 2 1 1 1 * 1 0 0 0 1
13771: * 3 i=2 1 2 1 1 * 2 0 0 1 0
13772: * 4 2 2 1 1 * 3 0 0 1 1
13773: * 5 i=3 1 i=2 1 2 1 * 4 0 1 0 0
13774: * 6 2 1 2 1 * 5 0 1 0 1
13775: * 7 i=4 1 2 2 1 * 6 0 1 1 0
13776: * 8 2 2 2 1 * 7 0 1 1 1
13777: * 9 i=5 1 i=3 1 i=2 1 2 * 8 1 0 0 0
13778: * 10 2 1 1 2 * 9 1 0 0 1
13779: * 11 i=6 1 2 1 2 * 10 1 0 1 0
13780: * 12 2 2 1 2 * 11 1 0 1 1
13781: * 13 i=7 1 i=4 1 2 2 * 12 1 1 0 0
13782: * 14 2 1 2 2 * 13 1 1 0 1
13783: * 15 i=8 1 2 2 2 * 14 1 1 1 0
13784: * 16 2 2 2 2 * 15 1 1 1 1
13785: */
1.212 brouard 13786: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 13787: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
13788: * and the value of each covariate?
13789: * V1=1, V2=1, V3=2, V4=1 ?
13790: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
13791: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
13792: * In order to get the real value in the data, we use nbcode
13793: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
13794: * We are keeping this crazy system in order to be able (in the future?)
13795: * to have more than 2 values (0 or 1) for a covariate.
13796: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
13797: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
13798: * bbbbbbbb
13799: * 76543210
13800: * h-1 00000101 (6-1=5)
1.219 brouard 13801: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 13802: * &
13803: * 1 00000001 (1)
1.219 brouard 13804: * 00000000 = 1 & ((h-1) >> (k-1))
13805: * +1= 00000001 =1
1.211 brouard 13806: *
13807: * h=14, k=3 => h'=h-1=13, k'=k-1=2
13808: * h' 1101 =2^3+2^2+0x2^1+2^0
13809: * >>k' 11
13810: * & 00000001
13811: * = 00000001
13812: * +1 = 00000010=2 = codtabm(14,3)
13813: * Reverse h=6 and m=16?
13814: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
13815: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
13816: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
13817: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
13818: * V3=decodtabm(14,3,2**4)=2
13819: * h'=13 1101 =2^3+2^2+0x2^1+2^0
13820: *(h-1) >> (j-1) 0011 =13 >> 2
13821: * &1 000000001
13822: * = 000000001
13823: * +1= 000000010 =2
13824: * 2211
13825: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
13826: * V3=2
1.220 brouard 13827: * codtabm and decodtabm are identical
1.211 brouard 13828: */
13829:
1.145 brouard 13830:
13831: free_ivector(Ndum,-1,NCOVMAX);
13832:
13833:
1.126 brouard 13834:
1.186 brouard 13835: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 13836: strcpy(optionfilegnuplot,optionfilefiname);
13837: if(mle==-3)
1.201 brouard 13838: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 13839: strcat(optionfilegnuplot,".gp");
13840:
13841: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
13842: printf("Problem with file %s",optionfilegnuplot);
13843: }
13844: else{
1.204 brouard 13845: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 13846: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 13847: //fprintf(ficgp,"set missing 'NaNq'\n");
13848: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 13849: }
13850: /* fclose(ficgp);*/
1.186 brouard 13851:
13852:
13853: /* Initialisation of --------- index.htm --------*/
1.126 brouard 13854:
13855: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
13856: if(mle==-3)
1.201 brouard 13857: strcat(optionfilehtm,"-MORT_");
1.126 brouard 13858: strcat(optionfilehtm,".htm");
13859: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 13860: printf("Problem with %s \n",optionfilehtm);
13861: exit(0);
1.126 brouard 13862: }
13863:
13864: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
13865: strcat(optionfilehtmcov,"-cov.htm");
13866: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
13867: printf("Problem with %s \n",optionfilehtmcov), exit(0);
13868: }
13869: else{
13870: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
13871: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 13872: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 13873: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
13874: }
13875:
1.335 brouard 13876: fprintf(fichtm,"<html><head>\n<meta charset=\"utf-8\"/><meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n\
13877: <title>IMaCh %s</title></head>\n\
13878: <body><font size=\"7\"><a href=http:/euroreves.ined.fr/imach>IMaCh for Interpolated Markov Chain</a> </font><br>\n\
13879: <font size=\"3\">Sponsored by Copyright (C) 2002-2015 <a href=http://www.ined.fr>INED</a>\
13880: -EUROREVES-Institut de longévité-2013-2022-Japan Society for the Promotion of Sciences 日本学術振興会 \
13881: (<a href=https://www.jsps.go.jp/english/e-grants/>Grant-in-Aid for Scientific Research 25293121</a>) - \
13882: <a href=https://software.intel.com/en-us>Intel Software 2015-2018</a></font><br> \n", optionfilehtm);
13883:
13884: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 13885: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 13886: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.337 brouard 13887: 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 13888: \n\
13889: <hr size=\"2\" color=\"#EC5E5E\">\
13890: <ul><li><h4>Parameter files</h4>\n\
13891: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
13892: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
13893: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
13894: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
13895: - Date and time at start: %s</ul>\n",\
1.335 brouard 13896: version,fullversion,optionfilehtm,optionfilehtm,title,datafile,datafile,firstpass,lastpass,stepm, weightopt, model, \
1.126 brouard 13897: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
13898: fileres,fileres,\
13899: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
13900: fflush(fichtm);
13901:
13902: strcpy(pathr,path);
13903: strcat(pathr,optionfilefiname);
1.184 brouard 13904: #ifdef WIN32
13905: _chdir(optionfilefiname); /* Move to directory named optionfile */
13906: #else
1.126 brouard 13907: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 13908: #endif
13909:
1.126 brouard 13910:
1.220 brouard 13911: /* Calculates basic frequencies. Computes observed prevalence at single age
13912: and for any valid combination of covariates
1.126 brouard 13913: and prints on file fileres'p'. */
1.251 brouard 13914: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 13915: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 13916:
13917: fprintf(fichtm,"\n");
1.286 brouard 13918: 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 13919: ftol, stepm);
13920: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
13921: ncurrv=1;
13922: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
13923: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
13924: ncurrv=i;
13925: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 13926: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 13927: ncurrv=i;
13928: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 13929: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 13930: ncurrv=i;
13931: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
13932: 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", \
13933: nlstate, ndeath, maxwav, mle, weightopt);
13934:
13935: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
13936: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
13937:
13938:
1.317 brouard 13939: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Number of (used) observations=%d <br>\n\
1.126 brouard 13940: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
13941: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 13942: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 13943: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 13944: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
13945: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
13946: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
13947: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 13948:
1.126 brouard 13949: /* For Powell, parameters are in a vector p[] starting at p[1]
13950: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
13951: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
13952:
13953: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 13954: /* For mortality only */
1.126 brouard 13955: if (mle==-3){
1.136 brouard 13956: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 13957: for(i=1;i<=NDIM;i++)
13958: for(j=1;j<=NDIM;j++)
13959: ximort[i][j]=0.;
1.186 brouard 13960: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 13961: cens=ivector(firstobs,lastobs);
13962: ageexmed=vector(firstobs,lastobs);
13963: agecens=vector(firstobs,lastobs);
13964: dcwave=ivector(firstobs,lastobs);
1.223 brouard 13965:
1.126 brouard 13966: for (i=1; i<=imx; i++){
13967: dcwave[i]=-1;
13968: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 13969: if (s[m][i]>nlstate) {
13970: dcwave[i]=m;
13971: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
13972: break;
13973: }
1.126 brouard 13974: }
1.226 brouard 13975:
1.126 brouard 13976: for (i=1; i<=imx; i++) {
13977: if (wav[i]>0){
1.226 brouard 13978: ageexmed[i]=agev[mw[1][i]][i];
13979: j=wav[i];
13980: agecens[i]=1.;
13981:
13982: if (ageexmed[i]> 1 && wav[i] > 0){
13983: agecens[i]=agev[mw[j][i]][i];
13984: cens[i]= 1;
13985: }else if (ageexmed[i]< 1)
13986: cens[i]= -1;
13987: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
13988: cens[i]=0 ;
1.126 brouard 13989: }
13990: else cens[i]=-1;
13991: }
13992:
13993: for (i=1;i<=NDIM;i++) {
13994: for (j=1;j<=NDIM;j++)
1.226 brouard 13995: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 13996: }
13997:
1.302 brouard 13998: p[1]=0.0268; p[NDIM]=0.083;
13999: /* printf("%lf %lf", p[1], p[2]); */
1.126 brouard 14000:
14001:
1.136 brouard 14002: #ifdef GSL
14003: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 14004: #else
1.126 brouard 14005: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 14006: #endif
1.201 brouard 14007: strcpy(filerespow,"POW-MORT_");
14008: strcat(filerespow,fileresu);
1.126 brouard 14009: if((ficrespow=fopen(filerespow,"w"))==NULL) {
14010: printf("Problem with resultfile: %s\n", filerespow);
14011: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
14012: }
1.136 brouard 14013: #ifdef GSL
14014: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 14015: #else
1.126 brouard 14016: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 14017: #endif
1.126 brouard 14018: /* for (i=1;i<=nlstate;i++)
14019: for(j=1;j<=nlstate+ndeath;j++)
14020: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
14021: */
14022: fprintf(ficrespow,"\n");
1.136 brouard 14023: #ifdef GSL
14024: /* gsl starts here */
14025: T = gsl_multimin_fminimizer_nmsimplex;
14026: gsl_multimin_fminimizer *sfm = NULL;
14027: gsl_vector *ss, *x;
14028: gsl_multimin_function minex_func;
14029:
14030: /* Initial vertex size vector */
14031: ss = gsl_vector_alloc (NDIM);
14032:
14033: if (ss == NULL){
14034: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
14035: }
14036: /* Set all step sizes to 1 */
14037: gsl_vector_set_all (ss, 0.001);
14038:
14039: /* Starting point */
1.126 brouard 14040:
1.136 brouard 14041: x = gsl_vector_alloc (NDIM);
14042:
14043: if (x == NULL){
14044: gsl_vector_free(ss);
14045: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
14046: }
14047:
14048: /* Initialize method and iterate */
14049: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 14050: /* gsl_vector_set(x, 0, 0.0268); */
14051: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 14052: gsl_vector_set(x, 0, p[1]);
14053: gsl_vector_set(x, 1, p[2]);
14054:
14055: minex_func.f = &gompertz_f;
14056: minex_func.n = NDIM;
14057: minex_func.params = (void *)&p; /* ??? */
14058:
14059: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
14060: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
14061:
14062: printf("Iterations beginning .....\n\n");
14063: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
14064:
14065: iteri=0;
14066: while (rval == GSL_CONTINUE){
14067: iteri++;
14068: status = gsl_multimin_fminimizer_iterate(sfm);
14069:
14070: if (status) printf("error: %s\n", gsl_strerror (status));
14071: fflush(0);
14072:
14073: if (status)
14074: break;
14075:
14076: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
14077: ssval = gsl_multimin_fminimizer_size (sfm);
14078:
14079: if (rval == GSL_SUCCESS)
14080: printf ("converged to a local maximum at\n");
14081:
14082: printf("%5d ", iteri);
14083: for (it = 0; it < NDIM; it++){
14084: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
14085: }
14086: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
14087: }
14088:
14089: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
14090:
14091: gsl_vector_free(x); /* initial values */
14092: gsl_vector_free(ss); /* inital step size */
14093: for (it=0; it<NDIM; it++){
14094: p[it+1]=gsl_vector_get(sfm->x,it);
14095: fprintf(ficrespow," %.12lf", p[it]);
14096: }
14097: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
14098: #endif
14099: #ifdef POWELL
14100: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
14101: #endif
1.126 brouard 14102: fclose(ficrespow);
14103:
1.203 brouard 14104: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 14105:
14106: for(i=1; i <=NDIM; i++)
14107: for(j=i+1;j<=NDIM;j++)
1.220 brouard 14108: matcov[i][j]=matcov[j][i];
1.126 brouard 14109:
14110: printf("\nCovariance matrix\n ");
1.203 brouard 14111: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 14112: for(i=1; i <=NDIM; i++) {
14113: for(j=1;j<=NDIM;j++){
1.220 brouard 14114: printf("%f ",matcov[i][j]);
14115: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 14116: }
1.203 brouard 14117: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 14118: }
14119:
14120: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 14121: for (i=1;i<=NDIM;i++) {
1.126 brouard 14122: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 14123: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
14124: }
1.302 brouard 14125: lsurv=vector(agegomp,AGESUP);
14126: lpop=vector(agegomp,AGESUP);
14127: tpop=vector(agegomp,AGESUP);
1.126 brouard 14128: lsurv[agegomp]=100000;
14129:
14130: for (k=agegomp;k<=AGESUP;k++) {
14131: agemortsup=k;
14132: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
14133: }
14134:
14135: for (k=agegomp;k<agemortsup;k++)
14136: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
14137:
14138: for (k=agegomp;k<agemortsup;k++){
14139: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
14140: sumlpop=sumlpop+lpop[k];
14141: }
14142:
14143: tpop[agegomp]=sumlpop;
14144: for (k=agegomp;k<(agemortsup-3);k++){
14145: /* tpop[k+1]=2;*/
14146: tpop[k+1]=tpop[k]-lpop[k];
14147: }
14148:
14149:
14150: printf("\nAge lx qx dx Lx Tx e(x)\n");
14151: for (k=agegomp;k<(agemortsup-2);k++)
14152: 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]);
14153:
14154:
14155: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 14156: ageminpar=50;
14157: agemaxpar=100;
1.194 brouard 14158: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
14159: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
14160: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14161: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
14162: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
14163: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14164: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 14165: }else{
14166: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
14167: 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 14168: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 14169: }
1.201 brouard 14170: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 14171: stepm, weightopt,\
14172: model,imx,p,matcov,agemortsup);
14173:
1.302 brouard 14174: free_vector(lsurv,agegomp,AGESUP);
14175: free_vector(lpop,agegomp,AGESUP);
14176: free_vector(tpop,agegomp,AGESUP);
1.220 brouard 14177: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 14178: free_ivector(dcwave,firstobs,lastobs);
14179: free_vector(agecens,firstobs,lastobs);
14180: free_vector(ageexmed,firstobs,lastobs);
14181: free_ivector(cens,firstobs,lastobs);
1.220 brouard 14182: #ifdef GSL
1.136 brouard 14183: #endif
1.186 brouard 14184: } /* Endof if mle==-3 mortality only */
1.205 brouard 14185: /* Standard */
14186: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
14187: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
14188: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 14189: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 14190: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
14191: for (k=1; k<=npar;k++)
14192: printf(" %d %8.5f",k,p[k]);
14193: printf("\n");
1.205 brouard 14194: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
14195: /* mlikeli uses func not funcone */
1.247 brouard 14196: /* for(i=1;i<nlstate;i++){ */
14197: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
14198: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
14199: /* } */
1.205 brouard 14200: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
14201: }
14202: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
14203: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
14204: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
14205: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
14206: }
14207: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 14208: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
14209: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
1.335 brouard 14210: /* exit(0); */
1.126 brouard 14211: for (k=1; k<=npar;k++)
14212: printf(" %d %8.5f",k,p[k]);
14213: printf("\n");
14214:
14215: /*--------- results files --------------*/
1.283 brouard 14216: /* 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 14217:
14218:
14219: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 14220: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); /* Printing model equation */
1.126 brouard 14221: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 14222:
14223: printf("#model= 1 + age ");
14224: fprintf(ficres,"#model= 1 + age ");
14225: fprintf(ficlog,"#model= 1 + age ");
14226: fprintf(fichtm,"\n<ul><li> model=1+age+%s\n \
14227: </ul>", model);
14228:
14229: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">\n");
14230: fprintf(fichtm, "<tr><th>Model=</th><th>1</th><th>+ age</th>");
14231: if(nagesqr==1){
14232: printf(" + age*age ");
14233: fprintf(ficres," + age*age ");
14234: fprintf(ficlog," + age*age ");
14235: fprintf(fichtm, "<th>+ age*age</th>");
14236: }
14237: for(j=1;j <=ncovmodel-2;j++){
14238: if(Typevar[j]==0) {
14239: printf(" + V%d ",Tvar[j]);
14240: fprintf(ficres," + V%d ",Tvar[j]);
14241: fprintf(ficlog," + V%d ",Tvar[j]);
14242: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
14243: }else if(Typevar[j]==1) {
14244: printf(" + V%d*age ",Tvar[j]);
14245: fprintf(ficres," + V%d*age ",Tvar[j]);
14246: fprintf(ficlog," + V%d*age ",Tvar[j]);
14247: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
14248: }else if(Typevar[j]==2) {
14249: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14250: fprintf(ficres," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14251: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14252: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 ! brouard 14253: }else if(Typevar[j]==3) { /* TO VERIFY */
! 14254: printf(" + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
! 14255: fprintf(ficres," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
! 14256: fprintf(ficlog," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
! 14257: fprintf(fichtm, "<th>+ V%d*V%d*age</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.319 brouard 14258: }
14259: }
14260: printf("\n");
14261: fprintf(ficres,"\n");
14262: fprintf(ficlog,"\n");
14263: fprintf(fichtm, "</tr>");
14264: fprintf(fichtm, "\n");
14265:
14266:
1.126 brouard 14267: for(i=1,jk=1; i <=nlstate; i++){
14268: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 14269: if (k != i) {
1.319 brouard 14270: fprintf(fichtm, "<tr>");
1.225 brouard 14271: printf("%d%d ",i,k);
14272: fprintf(ficlog,"%d%d ",i,k);
14273: fprintf(ficres,"%1d%1d ",i,k);
1.319 brouard 14274: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 14275: for(j=1; j <=ncovmodel; j++){
14276: printf("%12.7f ",p[jk]);
14277: fprintf(ficlog,"%12.7f ",p[jk]);
14278: fprintf(ficres,"%12.7f ",p[jk]);
1.319 brouard 14279: fprintf(fichtm, "<td>%12.7f</td>",p[jk]);
1.225 brouard 14280: jk++;
14281: }
14282: printf("\n");
14283: fprintf(ficlog,"\n");
14284: fprintf(ficres,"\n");
1.319 brouard 14285: fprintf(fichtm, "</tr>\n");
1.225 brouard 14286: }
1.126 brouard 14287: }
14288: }
1.319 brouard 14289: /* fprintf(fichtm,"</tr>\n"); */
14290: fprintf(fichtm,"</table>\n");
14291: fprintf(fichtm, "\n");
14292:
1.203 brouard 14293: if(mle != 0){
14294: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 14295: ftolhess=ftol; /* Usually correct */
1.203 brouard 14296: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
14297: 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");
14298: 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 14299: 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 14300: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">");
14301: fprintf(fichtm, "\n<tr><th>Model=</th><th>1</th><th>+ age</th>");
14302: if(nagesqr==1){
14303: printf(" + age*age ");
14304: fprintf(ficres," + age*age ");
14305: fprintf(ficlog," + age*age ");
14306: fprintf(fichtm, "<th>+ age*age</th>");
14307: }
14308: for(j=1;j <=ncovmodel-2;j++){
14309: if(Typevar[j]==0) {
14310: printf(" + V%d ",Tvar[j]);
14311: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
14312: }else if(Typevar[j]==1) {
14313: printf(" + V%d*age ",Tvar[j]);
14314: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
14315: }else if(Typevar[j]==2) {
14316: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 ! brouard 14317: }else if(Typevar[j]==3) { /* TO VERIFY */
! 14318: fprintf(fichtm, "<th>+ V%d*V%d*age</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.319 brouard 14319: }
14320: }
14321: fprintf(fichtm, "</tr>\n");
14322:
1.203 brouard 14323: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 14324: for(k=1; k <=(nlstate+ndeath); k++){
14325: if (k != i) {
1.319 brouard 14326: fprintf(fichtm, "<tr valign=top>");
1.225 brouard 14327: printf("%d%d ",i,k);
14328: fprintf(ficlog,"%d%d ",i,k);
1.319 brouard 14329: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 14330: for(j=1; j <=ncovmodel; j++){
1.319 brouard 14331: wald=p[jk]/sqrt(matcov[jk][jk]);
1.324 brouard 14332: 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]));
14333: 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 14334: if(fabs(wald) > 1.96){
1.321 brouard 14335: fprintf(fichtm, "<td><b>%12.7f</b></br> (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
1.319 brouard 14336: }else{
14337: fprintf(fichtm, "<td>%12.7f (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
14338: }
1.324 brouard 14339: fprintf(fichtm,"W=%8.3f</br>",wald);
1.319 brouard 14340: 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 14341: jk++;
14342: }
14343: printf("\n");
14344: fprintf(ficlog,"\n");
1.319 brouard 14345: fprintf(fichtm, "</tr>\n");
1.225 brouard 14346: }
14347: }
1.193 brouard 14348: }
1.203 brouard 14349: } /* end of hesscov and Wald tests */
1.319 brouard 14350: fprintf(fichtm,"</table>\n");
1.225 brouard 14351:
1.203 brouard 14352: /* */
1.126 brouard 14353: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
14354: printf("# Scales (for hessian or gradient estimation)\n");
14355: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
14356: for(i=1,jk=1; i <=nlstate; i++){
14357: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 14358: if (j!=i) {
14359: fprintf(ficres,"%1d%1d",i,j);
14360: printf("%1d%1d",i,j);
14361: fprintf(ficlog,"%1d%1d",i,j);
14362: for(k=1; k<=ncovmodel;k++){
14363: printf(" %.5e",delti[jk]);
14364: fprintf(ficlog," %.5e",delti[jk]);
14365: fprintf(ficres," %.5e",delti[jk]);
14366: jk++;
14367: }
14368: printf("\n");
14369: fprintf(ficlog,"\n");
14370: fprintf(ficres,"\n");
14371: }
1.126 brouard 14372: }
14373: }
14374:
14375: fprintf(ficres,"# Covariance matrix \n# 121 Var(a12)\n# 122 Cov(b12,a12) Var(b12)\n# ...\n# 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n");
1.349 ! brouard 14376: if(mle >= 1) /* Too big for the screen */
1.126 brouard 14377: 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");
14378: 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");
14379: /* # 121 Var(a12)\n\ */
14380: /* # 122 Cov(b12,a12) Var(b12)\n\ */
14381: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
14382: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
14383: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
14384: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
14385: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
14386: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
14387:
14388:
14389: /* Just to have a covariance matrix which will be more understandable
14390: even is we still don't want to manage dictionary of variables
14391: */
14392: for(itimes=1;itimes<=2;itimes++){
14393: jj=0;
14394: for(i=1; i <=nlstate; i++){
1.225 brouard 14395: for(j=1; j <=nlstate+ndeath; j++){
14396: if(j==i) continue;
14397: for(k=1; k<=ncovmodel;k++){
14398: jj++;
14399: ca[0]= k+'a'-1;ca[1]='\0';
14400: if(itimes==1){
14401: if(mle>=1)
14402: printf("#%1d%1d%d",i,j,k);
14403: fprintf(ficlog,"#%1d%1d%d",i,j,k);
14404: fprintf(ficres,"#%1d%1d%d",i,j,k);
14405: }else{
14406: if(mle>=1)
14407: printf("%1d%1d%d",i,j,k);
14408: fprintf(ficlog,"%1d%1d%d",i,j,k);
14409: fprintf(ficres,"%1d%1d%d",i,j,k);
14410: }
14411: ll=0;
14412: for(li=1;li <=nlstate; li++){
14413: for(lj=1;lj <=nlstate+ndeath; lj++){
14414: if(lj==li) continue;
14415: for(lk=1;lk<=ncovmodel;lk++){
14416: ll++;
14417: if(ll<=jj){
14418: cb[0]= lk +'a'-1;cb[1]='\0';
14419: if(ll<jj){
14420: if(itimes==1){
14421: if(mle>=1)
14422: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
14423: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
14424: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
14425: }else{
14426: if(mle>=1)
14427: printf(" %.5e",matcov[jj][ll]);
14428: fprintf(ficlog," %.5e",matcov[jj][ll]);
14429: fprintf(ficres," %.5e",matcov[jj][ll]);
14430: }
14431: }else{
14432: if(itimes==1){
14433: if(mle>=1)
14434: printf(" Var(%s%1d%1d)",ca,i,j);
14435: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
14436: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
14437: }else{
14438: if(mle>=1)
14439: printf(" %.7e",matcov[jj][ll]);
14440: fprintf(ficlog," %.7e",matcov[jj][ll]);
14441: fprintf(ficres," %.7e",matcov[jj][ll]);
14442: }
14443: }
14444: }
14445: } /* end lk */
14446: } /* end lj */
14447: } /* end li */
14448: if(mle>=1)
14449: printf("\n");
14450: fprintf(ficlog,"\n");
14451: fprintf(ficres,"\n");
14452: numlinepar++;
14453: } /* end k*/
14454: } /*end j */
1.126 brouard 14455: } /* end i */
14456: } /* end itimes */
14457:
14458: fflush(ficlog);
14459: fflush(ficres);
1.225 brouard 14460: while(fgets(line, MAXLINE, ficpar)) {
14461: /* If line starts with a # it is a comment */
14462: if (line[0] == '#') {
14463: numlinepar++;
14464: fputs(line,stdout);
14465: fputs(line,ficparo);
14466: fputs(line,ficlog);
1.299 brouard 14467: fputs(line,ficres);
1.225 brouard 14468: continue;
14469: }else
14470: break;
14471: }
14472:
1.209 brouard 14473: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
14474: /* ungetc(c,ficpar); */
14475: /* fgets(line, MAXLINE, ficpar); */
14476: /* fputs(line,stdout); */
14477: /* fputs(line,ficparo); */
14478: /* } */
14479: /* ungetc(c,ficpar); */
1.126 brouard 14480:
14481: estepm=0;
1.209 brouard 14482: 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 14483:
14484: if (num_filled != 6) {
14485: 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);
14486: 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);
14487: goto end;
14488: }
14489: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
14490: }
14491: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
14492: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
14493:
1.209 brouard 14494: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 14495: if (estepm==0 || estepm < stepm) estepm=stepm;
14496: if (fage <= 2) {
14497: bage = ageminpar;
14498: fage = agemaxpar;
14499: }
14500:
14501: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 14502: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
14503: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 14504:
1.186 brouard 14505: /* Other stuffs, more or less useful */
1.254 brouard 14506: while(fgets(line, MAXLINE, ficpar)) {
14507: /* If line starts with a # it is a comment */
14508: if (line[0] == '#') {
14509: numlinepar++;
14510: fputs(line,stdout);
14511: fputs(line,ficparo);
14512: fputs(line,ficlog);
1.299 brouard 14513: fputs(line,ficres);
1.254 brouard 14514: continue;
14515: }else
14516: break;
14517: }
14518:
14519: 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){
14520:
14521: if (num_filled != 7) {
14522: 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);
14523: 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);
14524: goto end;
14525: }
14526: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
14527: 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);
14528: 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);
14529: 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 14530: }
1.254 brouard 14531:
14532: while(fgets(line, MAXLINE, ficpar)) {
14533: /* If line starts with a # it is a comment */
14534: if (line[0] == '#') {
14535: numlinepar++;
14536: fputs(line,stdout);
14537: fputs(line,ficparo);
14538: fputs(line,ficlog);
1.299 brouard 14539: fputs(line,ficres);
1.254 brouard 14540: continue;
14541: }else
14542: break;
1.126 brouard 14543: }
14544:
14545:
14546: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
14547: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
14548:
1.254 brouard 14549: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
14550: if (num_filled != 1) {
14551: 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);
14552: 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);
14553: goto end;
14554: }
14555: printf("pop_based=%d\n",popbased);
14556: fprintf(ficlog,"pop_based=%d\n",popbased);
14557: fprintf(ficparo,"pop_based=%d\n",popbased);
14558: fprintf(ficres,"pop_based=%d\n",popbased);
14559: }
14560:
1.258 brouard 14561: /* Results */
1.332 brouard 14562: /* Value of covariate in each resultine will be compututed (if product) and sorted according to model rank */
14563: /* It is precov[] because we need the varying age in order to compute the real cov[] of the model equation */
14564: precov=matrix(1,MAXRESULTLINESPONE,1,NCOVMAX+1);
1.307 brouard 14565: endishere=0;
1.258 brouard 14566: nresult=0;
1.308 brouard 14567: parameterline=0;
1.258 brouard 14568: do{
14569: if(!fgets(line, MAXLINE, ficpar)){
14570: endishere=1;
1.308 brouard 14571: parameterline=15;
1.258 brouard 14572: }else if (line[0] == '#') {
14573: /* If line starts with a # it is a comment */
1.254 brouard 14574: numlinepar++;
14575: fputs(line,stdout);
14576: fputs(line,ficparo);
14577: fputs(line,ficlog);
1.299 brouard 14578: fputs(line,ficres);
1.254 brouard 14579: continue;
1.258 brouard 14580: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
14581: parameterline=11;
1.296 brouard 14582: else if(sscanf(line,"prevbackcast=%[^\n]\n",modeltemp))
1.258 brouard 14583: parameterline=12;
1.307 brouard 14584: else if(sscanf(line,"result:%[^\n]\n",modeltemp)){
1.258 brouard 14585: parameterline=13;
1.307 brouard 14586: }
1.258 brouard 14587: else{
14588: parameterline=14;
1.254 brouard 14589: }
1.308 brouard 14590: switch (parameterline){ /* =0 only if only comments */
1.258 brouard 14591: case 11:
1.296 brouard 14592: 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)){
14593: 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 14594: 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);
14595: 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);
14596: 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);
14597: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 14598: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
14599: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
1.296 brouard 14600: prvforecast = 1;
14601: }
14602: else if((num_filled=sscanf(line,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",&prevfcast,&yrfproj,&mobilavproj)) !=EOF){/* && (num_filled == 3))*/
1.313 brouard 14603: printf("prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
14604: fprintf(ficlog,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
14605: fprintf(ficres,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
1.296 brouard 14606: prvforecast = 2;
14607: }
14608: else {
14609: 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);
14610: 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);
14611: goto end;
1.258 brouard 14612: }
1.254 brouard 14613: break;
1.258 brouard 14614: case 12:
1.296 brouard 14615: 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)){
14616: 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);
14617: 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);
14618: 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);
14619: 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);
14620: /* day and month of back2 are not used but only year anback2.*/
1.273 brouard 14621: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
14622: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.296 brouard 14623: prvbackcast = 1;
14624: }
14625: else if((num_filled=sscanf(line,"prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",&prevbcast,&yrbproj,&mobilavproj)) ==3){/* && (num_filled == 3))*/
1.313 brouard 14626: printf("prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
14627: fprintf(ficlog,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
14628: fprintf(ficres,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
1.296 brouard 14629: prvbackcast = 2;
14630: }
14631: else {
14632: 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);
14633: 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);
14634: goto end;
1.258 brouard 14635: }
1.230 brouard 14636: break;
1.258 brouard 14637: case 13:
1.332 brouard 14638: num_filled=sscanf(line,"result:%[^\n]\n",resultlineori);
1.307 brouard 14639: nresult++; /* Sum of resultlines */
1.342 brouard 14640: /* printf("Result %d: result:%s\n",nresult, resultlineori); */
1.332 brouard 14641: /* removefirstspace(&resultlineori); */
14642:
14643: if(strstr(resultlineori,"v") !=0){
14644: printf("Error. 'v' must be in upper case 'V' result: %s ",resultlineori);
14645: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultlineori);fflush(ficlog);
14646: return 1;
14647: }
14648: trimbb(resultline, resultlineori); /* Suppressing double blank in the resultline */
1.342 brouard 14649: /* printf("Decoderesult resultline=\"%s\" resultlineori=\"%s\"\n", resultline, resultlineori); */
1.318 brouard 14650: if(nresult > MAXRESULTLINESPONE-1){
14651: 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);
14652: 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 14653: goto end;
14654: }
1.332 brouard 14655:
1.310 brouard 14656: if(!decoderesult(resultline, nresult)){ /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
1.314 brouard 14657: fprintf(ficparo,"result: %s\n",resultline);
14658: fprintf(ficres,"result: %s\n",resultline);
14659: fprintf(ficlog,"result: %s\n",resultline);
1.310 brouard 14660: } else
14661: goto end;
1.307 brouard 14662: break;
14663: case 14:
14664: printf("Error: Unknown command '%s'\n",line);
14665: fprintf(ficlog,"Error: Unknown command '%s'\n",line);
1.314 brouard 14666: if(line[0] == ' ' || line[0] == '\n'){
14667: printf("It should not be an empty line '%s'\n",line);
14668: fprintf(ficlog,"It should not be an empty line '%s'\n",line);
14669: }
1.307 brouard 14670: if(ncovmodel >=2 && nresult==0 ){
14671: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
14672: fprintf(ficlog,"ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 14673: }
1.307 brouard 14674: /* goto end; */
14675: break;
1.308 brouard 14676: case 15:
14677: printf("End of resultlines.\n");
14678: fprintf(ficlog,"End of resultlines.\n");
14679: break;
14680: default: /* parameterline =0 */
1.307 brouard 14681: nresult=1;
14682: decoderesult(".",nresult ); /* No covariate */
1.258 brouard 14683: } /* End switch parameterline */
14684: }while(endishere==0); /* End do */
1.126 brouard 14685:
1.230 brouard 14686: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 14687: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 14688:
14689: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 14690: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 14691: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 14692: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14693: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 14694: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 14695: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14696: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 14697: }else{
1.270 brouard 14698: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
1.296 brouard 14699: /* It seems that anprojd which is computed from the mean year at interview which is known yet because of freqsummary */
14700: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */ /* Done in freqsummary */
14701: if(prvforecast==1){
14702: dateprojd=(jproj1+12*mproj1+365*anproj1)/365;
14703: jprojd=jproj1;
14704: mprojd=mproj1;
14705: anprojd=anproj1;
14706: dateprojf=(jproj2+12*mproj2+365*anproj2)/365;
14707: jprojf=jproj2;
14708: mprojf=mproj2;
14709: anprojf=anproj2;
14710: } else if(prvforecast == 2){
14711: dateprojd=dateintmean;
14712: date2dmy(dateprojd,&jprojd, &mprojd, &anprojd);
14713: dateprojf=dateintmean+yrfproj;
14714: date2dmy(dateprojf,&jprojf, &mprojf, &anprojf);
14715: }
14716: if(prvbackcast==1){
14717: datebackd=(jback1+12*mback1+365*anback1)/365;
14718: jbackd=jback1;
14719: mbackd=mback1;
14720: anbackd=anback1;
14721: datebackf=(jback2+12*mback2+365*anback2)/365;
14722: jbackf=jback2;
14723: mbackf=mback2;
14724: anbackf=anback2;
14725: } else if(prvbackcast == 2){
14726: datebackd=dateintmean;
14727: date2dmy(datebackd,&jbackd, &mbackd, &anbackd);
14728: datebackf=dateintmean-yrbproj;
14729: date2dmy(datebackf,&jbackf, &mbackf, &anbackf);
14730: }
14731:
14732: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage);
1.220 brouard 14733: }
14734: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.296 brouard 14735: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,prevbcast, estepm, \
14736: jprev1,mprev1,anprev1,dateprev1, dateprojd, datebackd,jprev2,mprev2,anprev2,dateprev2,dateprojf, datebackf);
1.220 brouard 14737:
1.225 brouard 14738: /*------------ free_vector -------------*/
14739: /* chdir(path); */
1.220 brouard 14740:
1.215 brouard 14741: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
14742: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
14743: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
14744: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 14745: free_lvector(num,firstobs,lastobs);
14746: free_vector(agedc,firstobs,lastobs);
1.126 brouard 14747: /*free_matrix(covar,0,NCOVMAX,1,n);*/
14748: /*free_matrix(covar,1,NCOVMAX,1,n);*/
14749: fclose(ficparo);
14750: fclose(ficres);
1.220 brouard 14751:
14752:
1.186 brouard 14753: /* Other results (useful)*/
1.220 brouard 14754:
14755:
1.126 brouard 14756: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 14757: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
14758: prlim=matrix(1,nlstate,1,nlstate);
1.332 brouard 14759: /* Computes the prevalence limit for each combination k of the dummy covariates by calling prevalim(k) */
1.209 brouard 14760: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 14761: fclose(ficrespl);
14762:
14763: /*------------- h Pij x at various ages ------------*/
1.180 brouard 14764: /*#include "hpijx.h"*/
1.332 brouard 14765: /** 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?*/
14766: /* calls hpxij with combination k */
1.180 brouard 14767: hPijx(p, bage, fage);
1.145 brouard 14768: fclose(ficrespij);
1.227 brouard 14769:
1.220 brouard 14770: /* ncovcombmax= pow(2,cptcoveff); */
1.332 brouard 14771: /*-------------- Variance of one-step probabilities for a combination ij or for nres ?---*/
1.145 brouard 14772: k=1;
1.126 brouard 14773: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 14774:
1.269 brouard 14775: /* Prevalence for each covariate combination in probs[age][status][cov] */
14776: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
14777: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 14778: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 14779: for(k=1;k<=ncovcombmax;k++)
14780: probs[i][j][k]=0.;
1.269 brouard 14781: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
14782: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 14783: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 14784: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
14785: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 14786: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 14787: for(k=1;k<=ncovcombmax;k++)
14788: mobaverages[i][j][k]=0.;
1.219 brouard 14789: mobaverage=mobaverages;
14790: if (mobilav!=0) {
1.235 brouard 14791: printf("Movingaveraging observed prevalence\n");
1.258 brouard 14792: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 14793: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
14794: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
14795: printf(" Error in movingaverage mobilav=%d\n",mobilav);
14796: }
1.269 brouard 14797: } else if (mobilavproj !=0) {
1.235 brouard 14798: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 14799: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 14800: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
14801: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
14802: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
14803: }
1.269 brouard 14804: }else{
14805: printf("Internal error moving average\n");
14806: fflush(stdout);
14807: exit(1);
1.219 brouard 14808: }
14809: }/* end if moving average */
1.227 brouard 14810:
1.126 brouard 14811: /*---------- Forecasting ------------------*/
1.296 brouard 14812: if(prevfcast==1){
14813: /* /\* if(stepm ==1){*\/ */
14814: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
14815: /*This done previously after freqsummary.*/
14816: /* dateprojd=(jproj1+12*mproj1+365*anproj1)/365; */
14817: /* dateprojf=(jproj2+12*mproj2+365*anproj2)/365; */
14818:
14819: /* } else if (prvforecast==2){ */
14820: /* /\* if(stepm ==1){*\/ */
14821: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
14822: /* } */
14823: /*prevforecast(fileresu, dateintmean, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);*/
14824: prevforecast(fileresu,dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, p, cptcoveff);
1.126 brouard 14825: }
1.269 brouard 14826:
1.296 brouard 14827: /* Prevbcasting */
14828: if(prevbcast==1){
1.219 brouard 14829: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14830: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14831: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14832:
14833: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
14834:
14835: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 14836:
1.219 brouard 14837: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
14838: fclose(ficresplb);
14839:
1.222 brouard 14840: hBijx(p, bage, fage, mobaverage);
14841: fclose(ficrespijb);
1.219 brouard 14842:
1.296 brouard 14843: /* /\* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, *\/ */
14844: /* /\* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); *\/ */
14845: /* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, */
14846: /* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
14847: prevbackforecast(fileresu, mobaverage, dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2,
14848: mobilavproj, bage, fage, firstpass, lastpass, p, cptcoveff);
14849:
14850:
1.269 brouard 14851: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 14852:
14853:
1.269 brouard 14854: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 14855: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
14856: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
14857: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.296 brouard 14858: } /* end Prevbcasting */
1.268 brouard 14859:
1.186 brouard 14860:
14861: /* ------ Other prevalence ratios------------ */
1.126 brouard 14862:
1.215 brouard 14863: free_ivector(wav,1,imx);
14864: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
14865: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
14866: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 14867:
14868:
1.127 brouard 14869: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 14870:
1.201 brouard 14871: strcpy(filerese,"E_");
14872: strcat(filerese,fileresu);
1.126 brouard 14873: if((ficreseij=fopen(filerese,"w"))==NULL) {
14874: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
14875: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
14876: }
1.208 brouard 14877: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
14878: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 14879:
14880: pstamp(ficreseij);
1.219 brouard 14881:
1.235 brouard 14882: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
14883: if (cptcovn < 1){i1=1;}
14884:
14885: for(nres=1; nres <= nresult; nres++) /* For each resultline */
14886: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 14887: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 14888: continue;
1.219 brouard 14889: fprintf(ficreseij,"\n#****** ");
1.235 brouard 14890: printf("\n#****** ");
1.225 brouard 14891: for(j=1;j<=cptcoveff;j++) {
1.332 brouard 14892: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
14893: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.235 brouard 14894: }
14895: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.337 brouard 14896: printf(" V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]); /* TvarsQ[j] gives the name of the jth quantitative (fixed or time v) */
14897: fprintf(ficreseij,"V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]);
1.219 brouard 14898: }
14899: fprintf(ficreseij,"******\n");
1.235 brouard 14900: printf("******\n");
1.219 brouard 14901:
14902: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
14903: oldm=oldms;savm=savms;
1.330 brouard 14904: /* 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 14905: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 14906:
1.219 brouard 14907: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 14908: }
14909: fclose(ficreseij);
1.208 brouard 14910: printf("done evsij\n");fflush(stdout);
14911: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 14912:
1.218 brouard 14913:
1.227 brouard 14914: /*---------- State-specific expectancies and variances ------------*/
1.336 brouard 14915: /* Should be moved in a function */
1.201 brouard 14916: strcpy(filerest,"T_");
14917: strcat(filerest,fileresu);
1.127 brouard 14918: if((ficrest=fopen(filerest,"w"))==NULL) {
14919: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
14920: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
14921: }
1.208 brouard 14922: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
14923: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 14924: strcpy(fileresstde,"STDE_");
14925: strcat(fileresstde,fileresu);
1.126 brouard 14926: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 14927: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
14928: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 14929: }
1.227 brouard 14930: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
14931: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 14932:
1.201 brouard 14933: strcpy(filerescve,"CVE_");
14934: strcat(filerescve,fileresu);
1.126 brouard 14935: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 14936: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
14937: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 14938: }
1.227 brouard 14939: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
14940: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 14941:
1.201 brouard 14942: strcpy(fileresv,"V_");
14943: strcat(fileresv,fileresu);
1.126 brouard 14944: if((ficresvij=fopen(fileresv,"w"))==NULL) {
14945: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
14946: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
14947: }
1.227 brouard 14948: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
14949: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 14950:
1.235 brouard 14951: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
14952: if (cptcovn < 1){i1=1;}
14953:
1.334 brouard 14954: for(nres=1; nres <= nresult; nres++) /* For each resultline, find the combination and output results according to the values of dummies and then quanti. */
14955: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying. For each nres and each value at position k
14956: * we know Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline
14957: * Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline
14958: * and Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
14959: /* */
14960: 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 14961: continue;
1.321 brouard 14962: printf("\n# model %s \n#****** Result for:", model);
14963: fprintf(ficrest,"\n# model %s \n#****** Result for:", model);
14964: fprintf(ficlog,"\n# model %s \n#****** Result for:", model);
1.334 brouard 14965: /* It might not be a good idea to mix dummies and quantitative */
14966: /* 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 *\/ */
14967: 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 */
14968: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /\* Output by variables in the resultline *\/ */
14969: /* Tvaraff[j] is the name of the dummy variable in position j in the equation model:
14970: * Tvaraff[1]@9={4, 3, 0, 0, 0, 0, 0, 0, 0}, in model=V5+V4+V3+V4*V3+V5*age
14971: * (V5 is quanti) V4 and V3 are dummies
14972: * TnsdVar[4] is the position 1 and TnsdVar[3]=2 in codtabm(k,l)(V4 V3)=V4 V3
14973: * l=1 l=2
14974: * k=1 1 1 0 0
14975: * k=2 2 1 1 0
14976: * k=3 [1] [2] 0 1
14977: * k=4 2 2 1 1
14978: * If nres=1 result: V3=1 V4=0 then k=3 and outputs
14979: * If nres=2 result: V4=1 V3=0 then k=2 and outputs
14980: * nres=1 =>k=3 j=1 V4= nbcode[4][codtabm(3,1)=1)=0; j=2 V3= nbcode[3][codtabm(3,2)=2]=1
14981: * nres=2 =>k=2 j=1 V4= nbcode[4][codtabm(2,1)=2)=1; j=2 V3= nbcode[3][codtabm(2,2)=1]=0
14982: */
14983: /* Tvresult[nres][j] Name of the variable at position j in this resultline */
14984: /* Tresult[nres][j] Value of this variable at position j could be a float if quantitative */
14985: /* We give up with the combinations!! */
1.342 brouard 14986: /* if(debugILK) */
14987: /* 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 14988:
14989: 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 14990: /* 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] */
14991: 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 */
14992: 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 */
14993: 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 14994: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
14995: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
14996: }else{
14997: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
14998: }
14999: /* fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15000: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15001: }else if(Dummy[modelresult[nres][j]]==1){ /* Quanti variable */
15002: /* For each selected (single) quantitative value */
1.337 brouard 15003: printf(" V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
15004: fprintf(ficlog," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
15005: fprintf(ficrest," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
1.334 brouard 15006: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
15007: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
15008: }else{
15009: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
15010: }
15011: }else{
15012: 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 */
15013: 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 */
15014: exit(1);
15015: }
1.335 brouard 15016: } /* End loop for each variable in the resultline */
1.334 brouard 15017: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
15018: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /\* Wrong j is not in the equation model *\/ */
15019: /* fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
15020: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
15021: /* } */
1.208 brouard 15022: fprintf(ficrest,"******\n");
1.227 brouard 15023: fprintf(ficlog,"******\n");
15024: printf("******\n");
1.208 brouard 15025:
15026: fprintf(ficresstdeij,"\n#****** ");
15027: fprintf(ficrescveij,"\n#****** ");
1.337 brouard 15028: /* It could have been: for(j=1;j<=cptcoveff;j++) {printf("V=%d=%lg",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);} */
15029: /* But it won't be sorted and depends on how the resultline is ordered */
1.225 brouard 15030: for(j=1;j<=cptcoveff;j++) {
1.334 brouard 15031: fprintf(ficresstdeij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
15032: /* fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15033: /* fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15034: }
15035: 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 15036: fprintf(ficresstdeij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
15037: fprintf(ficrescveij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
1.235 brouard 15038: }
1.208 brouard 15039: fprintf(ficresstdeij,"******\n");
15040: fprintf(ficrescveij,"******\n");
15041:
15042: fprintf(ficresvij,"\n#****** ");
1.238 brouard 15043: /* pstamp(ficresvij); */
1.225 brouard 15044: for(j=1;j<=cptcoveff;j++)
1.335 brouard 15045: fprintf(ficresvij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
15046: /* fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[TnsdVar[Tvaraff[j]]])]); */
1.235 brouard 15047: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.332 brouard 15048: /* fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); /\* To solve *\/ */
1.337 brouard 15049: fprintf(ficresvij," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /* Solved */
1.235 brouard 15050: }
1.208 brouard 15051: fprintf(ficresvij,"******\n");
15052:
15053: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
15054: oldm=oldms;savm=savms;
1.235 brouard 15055: printf(" cvevsij ");
15056: fprintf(ficlog, " cvevsij ");
15057: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 15058: printf(" end cvevsij \n ");
15059: fprintf(ficlog, " end cvevsij \n ");
15060:
15061: /*
15062: */
15063: /* goto endfree; */
15064:
15065: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
15066: pstamp(ficrest);
15067:
1.269 brouard 15068: epj=vector(1,nlstate+1);
1.208 brouard 15069: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 15070: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
15071: cptcod= 0; /* To be deleted */
15072: printf("varevsij vpopbased=%d \n",vpopbased);
15073: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 15074: 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 15075: 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 ");
15076: if(vpopbased==1)
15077: 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);
15078: else
1.288 brouard 15079: fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n");
1.335 brouard 15080: fprintf(ficrest,"# Age popbased mobilav e.. (std) "); /* Adding covariate values? */
1.227 brouard 15081: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
15082: fprintf(ficrest,"\n");
15083: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 15084: printf("Computing age specific forward period (stable) prevalences in each health state \n");
15085: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 15086: for(age=bage; age <=fage ;age++){
1.235 brouard 15087: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 15088: if (vpopbased==1) {
15089: if(mobilav ==0){
15090: for(i=1; i<=nlstate;i++)
15091: prlim[i][i]=probs[(int)age][i][k];
15092: }else{ /* mobilav */
15093: for(i=1; i<=nlstate;i++)
15094: prlim[i][i]=mobaverage[(int)age][i][k];
15095: }
15096: }
1.219 brouard 15097:
1.227 brouard 15098: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
15099: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
15100: /* printf(" age %4.0f ",age); */
15101: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
15102: for(i=1, epj[j]=0.;i <=nlstate;i++) {
15103: epj[j] += prlim[i][i]*eij[i][j][(int)age];
15104: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
15105: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
15106: }
15107: epj[nlstate+1] +=epj[j];
15108: }
15109: /* printf(" age %4.0f \n",age); */
1.219 brouard 15110:
1.227 brouard 15111: for(i=1, vepp=0.;i <=nlstate;i++)
15112: for(j=1;j <=nlstate;j++)
15113: vepp += vareij[i][j][(int)age];
15114: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
15115: for(j=1;j <=nlstate;j++){
15116: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
15117: }
15118: fprintf(ficrest,"\n");
15119: }
1.208 brouard 15120: } /* End vpopbased */
1.269 brouard 15121: free_vector(epj,1,nlstate+1);
1.208 brouard 15122: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
15123: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 15124: printf("done selection\n");fflush(stdout);
15125: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 15126:
1.335 brouard 15127: } /* End k selection or end covariate selection for nres */
1.227 brouard 15128:
15129: printf("done State-specific expectancies\n");fflush(stdout);
15130: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
15131:
1.335 brouard 15132: /* variance-covariance of forward period prevalence */
1.269 brouard 15133: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 15134:
1.227 brouard 15135:
1.290 brouard 15136: free_vector(weight,firstobs,lastobs);
1.349 ! brouard 15137: free_imatrix(Tvardk,-1,NCOVMAX,1,2);
1.227 brouard 15138: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 15139: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
15140: free_matrix(anint,1,maxwav,firstobs,lastobs);
15141: free_matrix(mint,1,maxwav,firstobs,lastobs);
15142: free_ivector(cod,firstobs,lastobs);
1.227 brouard 15143: free_ivector(tab,1,NCOVMAX);
15144: fclose(ficresstdeij);
15145: fclose(ficrescveij);
15146: fclose(ficresvij);
15147: fclose(ficrest);
15148: fclose(ficpar);
15149:
15150:
1.126 brouard 15151: /*---------- End : free ----------------*/
1.219 brouard 15152: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 15153: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
15154: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 15155: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
15156: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 15157: } /* mle==-3 arrives here for freeing */
1.227 brouard 15158: /* endfree:*/
15159: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
15160: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
15161: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.341 brouard 15162: /* if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs); */
15163: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs);
1.290 brouard 15164: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
15165: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
15166: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 15167: free_matrix(matcov,1,npar,1,npar);
15168: free_matrix(hess,1,npar,1,npar);
15169: /*free_vector(delti,1,npar);*/
15170: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
15171: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 15172: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 15173: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
15174:
15175: free_ivector(ncodemax,1,NCOVMAX);
15176: free_ivector(ncodemaxwundef,1,NCOVMAX);
15177: free_ivector(Dummy,-1,NCOVMAX);
15178: free_ivector(Fixed,-1,NCOVMAX);
1.349 ! brouard 15179: free_ivector(DummyV,-1,NCOVMAX);
! 15180: free_ivector(FixedV,-1,NCOVMAX);
1.227 brouard 15181: free_ivector(Typevar,-1,NCOVMAX);
15182: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 15183: free_ivector(TvarsQ,1,NCOVMAX);
15184: free_ivector(TvarsQind,1,NCOVMAX);
15185: free_ivector(TvarsD,1,NCOVMAX);
1.330 brouard 15186: free_ivector(TnsdVar,1,NCOVMAX);
1.234 brouard 15187: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 15188: free_ivector(TvarFD,1,NCOVMAX);
15189: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 15190: free_ivector(TvarF,1,NCOVMAX);
15191: free_ivector(TvarFind,1,NCOVMAX);
15192: free_ivector(TvarV,1,NCOVMAX);
15193: free_ivector(TvarVind,1,NCOVMAX);
15194: free_ivector(TvarA,1,NCOVMAX);
15195: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 15196: free_ivector(TvarFQ,1,NCOVMAX);
15197: free_ivector(TvarFQind,1,NCOVMAX);
15198: free_ivector(TvarVD,1,NCOVMAX);
15199: free_ivector(TvarVDind,1,NCOVMAX);
15200: free_ivector(TvarVQ,1,NCOVMAX);
15201: free_ivector(TvarVQind,1,NCOVMAX);
1.349 ! brouard 15202: free_ivector(TvarAVVA,1,NCOVMAX);
! 15203: free_ivector(TvarAVVAind,1,NCOVMAX);
! 15204: free_ivector(TvarVVA,1,NCOVMAX);
! 15205: free_ivector(TvarVVAind,1,NCOVMAX);
1.339 brouard 15206: free_ivector(TvarVV,1,NCOVMAX);
15207: free_ivector(TvarVVind,1,NCOVMAX);
15208:
1.230 brouard 15209: free_ivector(Tvarsel,1,NCOVMAX);
15210: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 15211: free_ivector(Tposprod,1,NCOVMAX);
15212: free_ivector(Tprod,1,NCOVMAX);
15213: free_ivector(Tvaraff,1,NCOVMAX);
1.338 brouard 15214: free_ivector(invalidvarcomb,0,ncovcombmax);
1.227 brouard 15215: free_ivector(Tage,1,NCOVMAX);
15216: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 15217: free_ivector(TmodelInvind,1,NCOVMAX);
15218: free_ivector(TmodelInvQind,1,NCOVMAX);
1.332 brouard 15219:
15220: free_matrix(precov, 1,MAXRESULTLINESPONE,1,NCOVMAX+1); /* Could be elsewhere ?*/
15221:
1.227 brouard 15222: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
15223: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 15224: fflush(fichtm);
15225: fflush(ficgp);
15226:
1.227 brouard 15227:
1.126 brouard 15228: if((nberr >0) || (nbwarn>0)){
1.216 brouard 15229: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
15230: 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 15231: }else{
15232: printf("End of Imach\n");
15233: fprintf(ficlog,"End of Imach\n");
15234: }
15235: printf("See log file on %s\n",filelog);
15236: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 15237: /*(void) gettimeofday(&end_time,&tzp);*/
15238: rend_time = time(NULL);
15239: end_time = *localtime(&rend_time);
15240: /* tml = *localtime(&end_time.tm_sec); */
15241: strcpy(strtend,asctime(&end_time));
1.126 brouard 15242: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
15243: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 15244: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 15245:
1.157 brouard 15246: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
15247: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
15248: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 15249: /* printf("Total time was %d uSec.\n", total_usecs);*/
15250: /* if(fileappend(fichtm,optionfilehtm)){ */
15251: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
15252: fclose(fichtm);
15253: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
15254: fclose(fichtmcov);
15255: fclose(ficgp);
15256: fclose(ficlog);
15257: /*------ End -----------*/
1.227 brouard 15258:
1.281 brouard 15259:
15260: /* Executes gnuplot */
1.227 brouard 15261:
15262: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 15263: #ifdef WIN32
1.227 brouard 15264: if (_chdir(pathcd) != 0)
15265: printf("Can't move to directory %s!\n",path);
15266: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 15267: #else
1.227 brouard 15268: if(chdir(pathcd) != 0)
15269: printf("Can't move to directory %s!\n", path);
15270: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 15271: #endif
1.126 brouard 15272: printf("Current directory %s!\n",pathcd);
15273: /*strcat(plotcmd,CHARSEPARATOR);*/
15274: sprintf(plotcmd,"gnuplot");
1.157 brouard 15275: #ifdef _WIN32
1.126 brouard 15276: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
15277: #endif
15278: if(!stat(plotcmd,&info)){
1.158 brouard 15279: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 15280: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 15281: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 15282: }else
15283: strcpy(pplotcmd,plotcmd);
1.157 brouard 15284: #ifdef __unix
1.126 brouard 15285: strcpy(plotcmd,GNUPLOTPROGRAM);
15286: if(!stat(plotcmd,&info)){
1.158 brouard 15287: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 15288: }else
15289: strcpy(pplotcmd,plotcmd);
15290: #endif
15291: }else
15292: strcpy(pplotcmd,plotcmd);
15293:
15294: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 15295: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 brouard 15296: strcpy(pplotcmd,plotcmd);
1.227 brouard 15297:
1.126 brouard 15298: if((outcmd=system(plotcmd)) != 0){
1.292 brouard 15299: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 15300: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 15301: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 brouard 15302: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 15303: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 brouard 15304: strcpy(plotcmd,pplotcmd);
15305: }
1.126 brouard 15306: }
1.158 brouard 15307: printf(" Successful, please wait...");
1.126 brouard 15308: while (z[0] != 'q') {
15309: /* chdir(path); */
1.154 brouard 15310: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 15311: scanf("%s",z);
15312: /* if (z[0] == 'c') system("./imach"); */
15313: if (z[0] == 'e') {
1.158 brouard 15314: #ifdef __APPLE__
1.152 brouard 15315: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 15316: #elif __linux
15317: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 15318: #else
1.152 brouard 15319: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 15320: #endif
15321: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
15322: system(pplotcmd);
1.126 brouard 15323: }
15324: else if (z[0] == 'g') system(plotcmd);
15325: else if (z[0] == 'q') exit(0);
15326: }
1.227 brouard 15327: end:
1.126 brouard 15328: while (z[0] != 'q') {
1.195 brouard 15329: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 15330: scanf("%s",z);
15331: }
1.283 brouard 15332: printf("End\n");
1.282 brouard 15333: exit(0);
1.126 brouard 15334: }
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