Annotation of imach/src/imach.c, revision 1.347
1.347 ! brouard 1: /* $Id: imach.c,v 1.346 2022/09/16 13:52:36 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.347 ! brouard 4: Revision 1.346 2022/09/16 13:52:36 brouard
! 5: * src/imach.c (Module): 0.99r41 Was an error when product of timevarying and fixed. Using FixedV[of name] now. Thank you Feinuo
! 6:
1.346 brouard 7: Revision 1.345 2022/09/16 13:40:11 brouard
8: Summary: Version 0.99r41
9:
10: * imach.c (Module): 0.99r41 Was an error when product of timevarying and fixed. Using FixedV[of name] now. Thank you Feinuo
11:
1.345 brouard 12: Revision 1.344 2022/09/14 19:33:30 brouard
13: Summary: version 0.99r40
14:
15: * imach.c (Module): Fixing names of variables in T_ (thanks to Feinuo)
16:
1.344 brouard 17: Revision 1.343 2022/09/14 14:22:16 brouard
18: Summary: version 0.99r39
19:
20: * imach.c (Module): Version 0.99r39 with colored dummy covariates
21: (fixed or time varying), using new last columns of
22: ILK_parameter.txt file.
23:
1.343 brouard 24: Revision 1.342 2022/09/11 19:54:09 brouard
25: Summary: 0.99r38
26:
27: * imach.c (Module): Adding timevarying products of any kinds,
28: should work before shifting cotvar from ncovcol+nqv columns in
29: order to have a correspondance between the column of cotvar and
30: the id of column.
31: (Module): Some cleaning and adding covariates in ILK.txt
32:
1.342 brouard 33: Revision 1.341 2022/09/11 07:58:42 brouard
34: Summary: Version 0.99r38
35:
36: After adding change in cotvar.
37:
1.341 brouard 38: Revision 1.340 2022/09/11 07:53:11 brouard
39: Summary: Version imach 0.99r37
40:
41: * imach.c (Module): Adding timevarying products of any kinds,
42: should work before shifting cotvar from ncovcol+nqv columns in
43: order to have a correspondance between the column of cotvar and
44: the id of column.
45:
1.340 brouard 46: Revision 1.339 2022/09/09 17:55:22 brouard
47: Summary: version 0.99r37
48:
49: * imach.c (Module): Many improvements for fixing products of fixed
50: timevarying as well as fixed * fixed, and test with quantitative
51: covariate.
52:
1.339 brouard 53: Revision 1.338 2022/09/04 17:40:33 brouard
54: Summary: 0.99r36
55:
56: * imach.c (Module): Now the easy runs i.e. without result or
57: model=1+age only did not work. The defautl combination should be 1
58: and not 0 because everything hasn't been tranformed yet.
59:
1.338 brouard 60: Revision 1.337 2022/09/02 14:26:02 brouard
61: Summary: version 0.99r35
62:
63: * src/imach.c: Version 0.99r35 because it outputs same results with
64: 1+age+V1+V1*age for females and 1+age for females only
65: (education=1 noweight)
66:
1.337 brouard 67: Revision 1.336 2022/08/31 09:52:36 brouard
68: *** empty log message ***
69:
1.336 brouard 70: Revision 1.335 2022/08/31 08:23:16 brouard
71: Summary: improvements...
72:
1.335 brouard 73: Revision 1.334 2022/08/25 09:08:41 brouard
74: Summary: In progress for quantitative
75:
1.334 brouard 76: Revision 1.333 2022/08/21 09:10:30 brouard
77: * src/imach.c (Module): Version 0.99r33 A lot of changes in
78: reassigning covariates: my first idea was that people will always
79: use the first covariate V1 into the model but in fact they are
80: producing data with many covariates and can use an equation model
81: with some of the covariate; it means that in a model V2+V3 instead
82: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
83: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
84: the equation model is restricted to two variables only (V2, V3)
85: and the combination for V2 should be codtabm(k,1) instead of
86: (codtabm(k,2), and the code should be
87: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
88: made. All of these should be simplified once a day like we did in
89: hpxij() for example by using precov[nres] which is computed in
90: decoderesult for each nres of each resultline. Loop should be done
91: on the equation model globally by distinguishing only product with
92: age (which are changing with age) and no more on type of
93: covariates, single dummies, single covariates.
94:
1.333 brouard 95: Revision 1.332 2022/08/21 09:06:25 brouard
96: Summary: Version 0.99r33
97:
98: * src/imach.c (Module): Version 0.99r33 A lot of changes in
99: reassigning covariates: my first idea was that people will always
100: use the first covariate V1 into the model but in fact they are
101: producing data with many covariates and can use an equation model
102: with some of the covariate; it means that in a model V2+V3 instead
103: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
104: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
105: the equation model is restricted to two variables only (V2, V3)
106: and the combination for V2 should be codtabm(k,1) instead of
107: (codtabm(k,2), and the code should be
108: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
109: made. All of these should be simplified once a day like we did in
110: hpxij() for example by using precov[nres] which is computed in
111: decoderesult for each nres of each resultline. Loop should be done
112: on the equation model globally by distinguishing only product with
113: age (which are changing with age) and no more on type of
114: covariates, single dummies, single covariates.
115:
1.332 brouard 116: Revision 1.331 2022/08/07 05:40:09 brouard
117: *** empty log message ***
118:
1.331 brouard 119: Revision 1.330 2022/08/06 07:18:25 brouard
120: Summary: last 0.99r31
121:
122: * imach.c (Module): Version of imach using partly decoderesult to rebuild xpxij function
123:
1.330 brouard 124: Revision 1.329 2022/08/03 17:29:54 brouard
125: * imach.c (Module): Many errors in graphs fixed with Vn*age covariates.
126:
1.329 brouard 127: Revision 1.328 2022/07/27 17:40:48 brouard
128: Summary: valgrind bug fixed by initializing to zero DummyV as well as Tage
129:
1.328 brouard 130: Revision 1.327 2022/07/27 14:47:35 brouard
131: Summary: Still a problem for one-step probabilities in case of quantitative variables
132:
1.327 brouard 133: Revision 1.326 2022/07/26 17:33:55 brouard
134: Summary: some test with nres=1
135:
1.326 brouard 136: Revision 1.325 2022/07/25 14:27:23 brouard
137: Summary: r30
138:
139: * imach.c (Module): Error cptcovn instead of nsd in bmij (was
140: coredumped, revealed by Feiuno, thank you.
141:
1.325 brouard 142: Revision 1.324 2022/07/23 17:44:26 brouard
143: *** empty log message ***
144:
1.324 brouard 145: Revision 1.323 2022/07/22 12:30:08 brouard
146: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
147:
1.323 brouard 148: Revision 1.322 2022/07/22 12:27:48 brouard
149: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
150:
1.322 brouard 151: Revision 1.321 2022/07/22 12:04:24 brouard
152: Summary: r28
153:
154: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
155:
1.321 brouard 156: Revision 1.320 2022/06/02 05:10:11 brouard
157: *** empty log message ***
158:
1.320 brouard 159: Revision 1.319 2022/06/02 04:45:11 brouard
160: * imach.c (Module): Adding the Wald tests from the log to the main
161: htm for better display of the maximum likelihood estimators.
162:
1.319 brouard 163: Revision 1.318 2022/05/24 08:10:59 brouard
164: * imach.c (Module): Some attempts to find a bug of wrong estimates
165: of confidencce intervals with product in the equation modelC
166:
1.318 brouard 167: Revision 1.317 2022/05/15 15:06:23 brouard
168: * imach.c (Module): Some minor improvements
169:
1.317 brouard 170: Revision 1.316 2022/05/11 15:11:31 brouard
171: Summary: r27
172:
1.316 brouard 173: Revision 1.315 2022/05/11 15:06:32 brouard
174: *** empty log message ***
175:
1.315 brouard 176: Revision 1.314 2022/04/13 17:43:09 brouard
177: * imach.c (Module): Adding link to text data files
178:
1.314 brouard 179: Revision 1.313 2022/04/11 15:57:42 brouard
180: * imach.c (Module): Error in rewriting the 'r' file with yearsfproj or yearsbproj fixed
181:
1.313 brouard 182: Revision 1.312 2022/04/05 21:24:39 brouard
183: *** empty log message ***
184:
1.312 brouard 185: Revision 1.311 2022/04/05 21:03:51 brouard
186: Summary: Fixed quantitative covariates
187:
188: Fixed covariates (dummy or quantitative)
189: with missing values have never been allowed but are ERRORS and
190: program quits. Standard deviations of fixed covariates were
191: wrongly computed. Mean and standard deviations of time varying
192: covariates are still not computed.
193:
1.311 brouard 194: Revision 1.310 2022/03/17 08:45:53 brouard
195: Summary: 99r25
196:
197: Improving detection of errors: result lines should be compatible with
198: the model.
199:
1.310 brouard 200: Revision 1.309 2021/05/20 12:39:14 brouard
201: Summary: Version 0.99r24
202:
1.309 brouard 203: Revision 1.308 2021/03/31 13:11:57 brouard
204: Summary: Version 0.99r23
205:
206:
207: * imach.c (Module): Still bugs in the result loop. Thank to Holly Benett
208:
1.308 brouard 209: Revision 1.307 2021/03/08 18:11:32 brouard
210: Summary: 0.99r22 fixed bug on result:
211:
1.307 brouard 212: Revision 1.306 2021/02/20 15:44:02 brouard
213: Summary: Version 0.99r21
214:
215: * imach.c (Module): Fix bug on quitting after result lines!
216: (Module): Version 0.99r21
217:
1.306 brouard 218: Revision 1.305 2021/02/20 15:28:30 brouard
219: * imach.c (Module): Fix bug on quitting after result lines!
220:
1.305 brouard 221: Revision 1.304 2021/02/12 11:34:20 brouard
222: * imach.c (Module): The use of a Windows BOM (huge) file is now an error
223:
1.304 brouard 224: Revision 1.303 2021/02/11 19:50:15 brouard
225: * (Module): imach.c Someone entered 'results:' instead of 'result:'. Now it is an error which is printed.
226:
1.303 brouard 227: Revision 1.302 2020/02/22 21:00:05 brouard
228: * (Module): imach.c Update mle=-3 (for computing Life expectancy
229: and life table from the data without any state)
230:
1.302 brouard 231: Revision 1.301 2019/06/04 13:51:20 brouard
232: Summary: Error in 'r'parameter file backcast yearsbproj instead of yearsfproj
233:
1.301 brouard 234: Revision 1.300 2019/05/22 19:09:45 brouard
235: Summary: version 0.99r19 of May 2019
236:
1.300 brouard 237: Revision 1.299 2019/05/22 18:37:08 brouard
238: Summary: Cleaned 0.99r19
239:
1.299 brouard 240: Revision 1.298 2019/05/22 18:19:56 brouard
241: *** empty log message ***
242:
1.298 brouard 243: Revision 1.297 2019/05/22 17:56:10 brouard
244: Summary: Fix bug by moving date2dmy and nhstepm which gaefin=-1
245:
1.297 brouard 246: Revision 1.296 2019/05/20 13:03:18 brouard
247: Summary: Projection syntax simplified
248:
249:
250: We can now start projections, forward or backward, from the mean date
251: of inteviews up to or down to a number of years of projection:
252: prevforecast=1 yearsfproj=15.3 mobil_average=0
253: or
254: prevforecast=1 starting-proj-date=1/1/2007 final-proj-date=12/31/2017 mobil_average=0
255: or
256: prevbackcast=1 yearsbproj=12.3 mobil_average=1
257: or
258: prevbackcast=1 starting-back-date=1/10/1999 final-back-date=1/1/1985 mobil_average=1
259:
1.296 brouard 260: Revision 1.295 2019/05/18 09:52:50 brouard
261: Summary: doxygen tex bug
262:
1.295 brouard 263: Revision 1.294 2019/05/16 14:54:33 brouard
264: Summary: There was some wrong lines added
265:
1.294 brouard 266: Revision 1.293 2019/05/09 15:17:34 brouard
267: *** empty log message ***
268:
1.293 brouard 269: Revision 1.292 2019/05/09 14:17:20 brouard
270: Summary: Some updates
271:
1.292 brouard 272: Revision 1.291 2019/05/09 13:44:18 brouard
273: Summary: Before ncovmax
274:
1.291 brouard 275: Revision 1.290 2019/05/09 13:39:37 brouard
276: Summary: 0.99r18 unlimited number of individuals
277:
278: 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.
279:
1.290 brouard 280: Revision 1.289 2018/12/13 09:16:26 brouard
281: Summary: Bug for young ages (<-30) will be in r17
282:
1.289 brouard 283: Revision 1.288 2018/05/02 20:58:27 brouard
284: Summary: Some bugs fixed
285:
1.288 brouard 286: Revision 1.287 2018/05/01 17:57:25 brouard
287: Summary: Bug fixed by providing frequencies only for non missing covariates
288:
1.287 brouard 289: Revision 1.286 2018/04/27 14:27:04 brouard
290: Summary: some minor bugs
291:
1.286 brouard 292: Revision 1.285 2018/04/21 21:02:16 brouard
293: Summary: Some bugs fixed, valgrind tested
294:
1.285 brouard 295: Revision 1.284 2018/04/20 05:22:13 brouard
296: Summary: Computing mean and stdeviation of fixed quantitative variables
297:
1.284 brouard 298: Revision 1.283 2018/04/19 14:49:16 brouard
299: Summary: Some minor bugs fixed
300:
1.283 brouard 301: Revision 1.282 2018/02/27 22:50:02 brouard
302: *** empty log message ***
303:
1.282 brouard 304: Revision 1.281 2018/02/27 19:25:23 brouard
305: Summary: Adding second argument for quitting
306:
1.281 brouard 307: Revision 1.280 2018/02/21 07:58:13 brouard
308: Summary: 0.99r15
309:
310: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
311:
1.280 brouard 312: Revision 1.279 2017/07/20 13:35:01 brouard
313: Summary: temporary working
314:
1.279 brouard 315: Revision 1.278 2017/07/19 14:09:02 brouard
316: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
317:
1.278 brouard 318: Revision 1.277 2017/07/17 08:53:49 brouard
319: Summary: BOM files can be read now
320:
1.277 brouard 321: Revision 1.276 2017/06/30 15:48:31 brouard
322: Summary: Graphs improvements
323:
1.276 brouard 324: Revision 1.275 2017/06/30 13:39:33 brouard
325: Summary: Saito's color
326:
1.275 brouard 327: Revision 1.274 2017/06/29 09:47:08 brouard
328: Summary: Version 0.99r14
329:
1.274 brouard 330: Revision 1.273 2017/06/27 11:06:02 brouard
331: Summary: More documentation on projections
332:
1.273 brouard 333: Revision 1.272 2017/06/27 10:22:40 brouard
334: Summary: Color of backprojection changed from 6 to 5(yellow)
335:
1.272 brouard 336: Revision 1.271 2017/06/27 10:17:50 brouard
337: Summary: Some bug with rint
338:
1.271 brouard 339: Revision 1.270 2017/05/24 05:45:29 brouard
340: *** empty log message ***
341:
1.270 brouard 342: Revision 1.269 2017/05/23 08:39:25 brouard
343: Summary: Code into subroutine, cleanings
344:
1.269 brouard 345: Revision 1.268 2017/05/18 20:09:32 brouard
346: Summary: backprojection and confidence intervals of backprevalence
347:
1.268 brouard 348: Revision 1.267 2017/05/13 10:25:05 brouard
349: Summary: temporary save for backprojection
350:
1.267 brouard 351: Revision 1.266 2017/05/13 07:26:12 brouard
352: Summary: Version 0.99r13 (improvements and bugs fixed)
353:
1.266 brouard 354: Revision 1.265 2017/04/26 16:22:11 brouard
355: Summary: imach 0.99r13 Some bugs fixed
356:
1.265 brouard 357: Revision 1.264 2017/04/26 06:01:29 brouard
358: Summary: Labels in graphs
359:
1.264 brouard 360: Revision 1.263 2017/04/24 15:23:15 brouard
361: Summary: to save
362:
1.263 brouard 363: Revision 1.262 2017/04/18 16:48:12 brouard
364: *** empty log message ***
365:
1.262 brouard 366: Revision 1.261 2017/04/05 10:14:09 brouard
367: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
368:
1.261 brouard 369: Revision 1.260 2017/04/04 17:46:59 brouard
370: Summary: Gnuplot indexations fixed (humm)
371:
1.260 brouard 372: Revision 1.259 2017/04/04 13:01:16 brouard
373: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
374:
1.259 brouard 375: Revision 1.258 2017/04/03 10:17:47 brouard
376: Summary: Version 0.99r12
377:
378: Some cleanings, conformed with updated documentation.
379:
1.258 brouard 380: Revision 1.257 2017/03/29 16:53:30 brouard
381: Summary: Temp
382:
1.257 brouard 383: Revision 1.256 2017/03/27 05:50:23 brouard
384: Summary: Temporary
385:
1.256 brouard 386: Revision 1.255 2017/03/08 16:02:28 brouard
387: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
388:
1.255 brouard 389: Revision 1.254 2017/03/08 07:13:00 brouard
390: Summary: Fixing data parameter line
391:
1.254 brouard 392: Revision 1.253 2016/12/15 11:59:41 brouard
393: Summary: 0.99 in progress
394:
1.253 brouard 395: Revision 1.252 2016/09/15 21:15:37 brouard
396: *** empty log message ***
397:
1.252 brouard 398: Revision 1.251 2016/09/15 15:01:13 brouard
399: Summary: not working
400:
1.251 brouard 401: Revision 1.250 2016/09/08 16:07:27 brouard
402: Summary: continue
403:
1.250 brouard 404: Revision 1.249 2016/09/07 17:14:18 brouard
405: Summary: Starting values from frequencies
406:
1.249 brouard 407: Revision 1.248 2016/09/07 14:10:18 brouard
408: *** empty log message ***
409:
1.248 brouard 410: Revision 1.247 2016/09/02 11:11:21 brouard
411: *** empty log message ***
412:
1.247 brouard 413: Revision 1.246 2016/09/02 08:49:22 brouard
414: *** empty log message ***
415:
1.246 brouard 416: Revision 1.245 2016/09/02 07:25:01 brouard
417: *** empty log message ***
418:
1.245 brouard 419: Revision 1.244 2016/09/02 07:17:34 brouard
420: *** empty log message ***
421:
1.244 brouard 422: Revision 1.243 2016/09/02 06:45:35 brouard
423: *** empty log message ***
424:
1.243 brouard 425: Revision 1.242 2016/08/30 15:01:20 brouard
426: Summary: Fixing a lots
427:
1.242 brouard 428: Revision 1.241 2016/08/29 17:17:25 brouard
429: Summary: gnuplot problem in Back projection to fix
430:
1.241 brouard 431: Revision 1.240 2016/08/29 07:53:18 brouard
432: Summary: Better
433:
1.240 brouard 434: Revision 1.239 2016/08/26 15:51:03 brouard
435: Summary: Improvement in Powell output in order to copy and paste
436:
437: Author:
438:
1.239 brouard 439: Revision 1.238 2016/08/26 14:23:35 brouard
440: Summary: Starting tests of 0.99
441:
1.238 brouard 442: Revision 1.237 2016/08/26 09:20:19 brouard
443: Summary: to valgrind
444:
1.237 brouard 445: Revision 1.236 2016/08/25 10:50:18 brouard
446: *** empty log message ***
447:
1.236 brouard 448: Revision 1.235 2016/08/25 06:59:23 brouard
449: *** empty log message ***
450:
1.235 brouard 451: Revision 1.234 2016/08/23 16:51:20 brouard
452: *** empty log message ***
453:
1.234 brouard 454: Revision 1.233 2016/08/23 07:40:50 brouard
455: Summary: not working
456:
1.233 brouard 457: Revision 1.232 2016/08/22 14:20:21 brouard
458: Summary: not working
459:
1.232 brouard 460: Revision 1.231 2016/08/22 07:17:15 brouard
461: Summary: not working
462:
1.231 brouard 463: Revision 1.230 2016/08/22 06:55:53 brouard
464: Summary: Not working
465:
1.230 brouard 466: Revision 1.229 2016/07/23 09:45:53 brouard
467: Summary: Completing for func too
468:
1.229 brouard 469: Revision 1.228 2016/07/22 17:45:30 brouard
470: Summary: Fixing some arrays, still debugging
471:
1.227 brouard 472: Revision 1.226 2016/07/12 18:42:34 brouard
473: Summary: temp
474:
1.226 brouard 475: Revision 1.225 2016/07/12 08:40:03 brouard
476: Summary: saving but not running
477:
1.225 brouard 478: Revision 1.224 2016/07/01 13:16:01 brouard
479: Summary: Fixes
480:
1.224 brouard 481: Revision 1.223 2016/02/19 09:23:35 brouard
482: Summary: temporary
483:
1.223 brouard 484: Revision 1.222 2016/02/17 08:14:50 brouard
485: Summary: Probably last 0.98 stable version 0.98r6
486:
1.222 brouard 487: Revision 1.221 2016/02/15 23:35:36 brouard
488: Summary: minor bug
489:
1.220 brouard 490: Revision 1.219 2016/02/15 00:48:12 brouard
491: *** empty log message ***
492:
1.219 brouard 493: Revision 1.218 2016/02/12 11:29:23 brouard
494: Summary: 0.99 Back projections
495:
1.218 brouard 496: Revision 1.217 2015/12/23 17:18:31 brouard
497: Summary: Experimental backcast
498:
1.217 brouard 499: Revision 1.216 2015/12/18 17:32:11 brouard
500: Summary: 0.98r4 Warning and status=-2
501:
502: Version 0.98r4 is now:
503: - displaying an error when status is -1, date of interview unknown and date of death known;
504: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
505: Older changes concerning s=-2, dating from 2005 have been supersed.
506:
1.216 brouard 507: Revision 1.215 2015/12/16 08:52:24 brouard
508: Summary: 0.98r4 working
509:
1.215 brouard 510: Revision 1.214 2015/12/16 06:57:54 brouard
511: Summary: temporary not working
512:
1.214 brouard 513: Revision 1.213 2015/12/11 18:22:17 brouard
514: Summary: 0.98r4
515:
1.213 brouard 516: Revision 1.212 2015/11/21 12:47:24 brouard
517: Summary: minor typo
518:
1.212 brouard 519: Revision 1.211 2015/11/21 12:41:11 brouard
520: Summary: 0.98r3 with some graph of projected cross-sectional
521:
522: Author: Nicolas Brouard
523:
1.211 brouard 524: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 525: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 526: Summary: Adding ftolpl parameter
527: Author: N Brouard
528:
529: We had difficulties to get smoothed confidence intervals. It was due
530: to the period prevalence which wasn't computed accurately. The inner
531: parameter ftolpl is now an outer parameter of the .imach parameter
532: file after estepm. If ftolpl is small 1.e-4 and estepm too,
533: computation are long.
534:
1.209 brouard 535: Revision 1.208 2015/11/17 14:31:57 brouard
536: Summary: temporary
537:
1.208 brouard 538: Revision 1.207 2015/10/27 17:36:57 brouard
539: *** empty log message ***
540:
1.207 brouard 541: Revision 1.206 2015/10/24 07:14:11 brouard
542: *** empty log message ***
543:
1.206 brouard 544: Revision 1.205 2015/10/23 15:50:53 brouard
545: Summary: 0.98r3 some clarification for graphs on likelihood contributions
546:
1.205 brouard 547: Revision 1.204 2015/10/01 16:20:26 brouard
548: Summary: Some new graphs of contribution to likelihood
549:
1.204 brouard 550: Revision 1.203 2015/09/30 17:45:14 brouard
551: Summary: looking at better estimation of the hessian
552:
553: Also a better criteria for convergence to the period prevalence And
554: therefore adding the number of years needed to converge. (The
555: prevalence in any alive state shold sum to one
556:
1.203 brouard 557: Revision 1.202 2015/09/22 19:45:16 brouard
558: Summary: Adding some overall graph on contribution to likelihood. Might change
559:
1.202 brouard 560: Revision 1.201 2015/09/15 17:34:58 brouard
561: Summary: 0.98r0
562:
563: - Some new graphs like suvival functions
564: - Some bugs fixed like model=1+age+V2.
565:
1.201 brouard 566: Revision 1.200 2015/09/09 16:53:55 brouard
567: Summary: Big bug thanks to Flavia
568:
569: Even model=1+age+V2. did not work anymore
570:
1.200 brouard 571: Revision 1.199 2015/09/07 14:09:23 brouard
572: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
573:
1.199 brouard 574: Revision 1.198 2015/09/03 07:14:39 brouard
575: Summary: 0.98q5 Flavia
576:
1.198 brouard 577: Revision 1.197 2015/09/01 18:24:39 brouard
578: *** empty log message ***
579:
1.197 brouard 580: Revision 1.196 2015/08/18 23:17:52 brouard
581: Summary: 0.98q5
582:
1.196 brouard 583: Revision 1.195 2015/08/18 16:28:39 brouard
584: Summary: Adding a hack for testing purpose
585:
586: After reading the title, ftol and model lines, if the comment line has
587: a q, starting with #q, the answer at the end of the run is quit. It
588: permits to run test files in batch with ctest. The former workaround was
589: $ echo q | imach foo.imach
590:
1.195 brouard 591: Revision 1.194 2015/08/18 13:32:00 brouard
592: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
593:
1.194 brouard 594: Revision 1.193 2015/08/04 07:17:42 brouard
595: Summary: 0.98q4
596:
1.193 brouard 597: Revision 1.192 2015/07/16 16:49:02 brouard
598: Summary: Fixing some outputs
599:
1.192 brouard 600: Revision 1.191 2015/07/14 10:00:33 brouard
601: Summary: Some fixes
602:
1.191 brouard 603: Revision 1.190 2015/05/05 08:51:13 brouard
604: Summary: Adding digits in output parameters (7 digits instead of 6)
605:
606: Fix 1+age+.
607:
1.190 brouard 608: Revision 1.189 2015/04/30 14:45:16 brouard
609: Summary: 0.98q2
610:
1.189 brouard 611: Revision 1.188 2015/04/30 08:27:53 brouard
612: *** empty log message ***
613:
1.188 brouard 614: Revision 1.187 2015/04/29 09:11:15 brouard
615: *** empty log message ***
616:
1.187 brouard 617: Revision 1.186 2015/04/23 12:01:52 brouard
618: Summary: V1*age is working now, version 0.98q1
619:
620: Some codes had been disabled in order to simplify and Vn*age was
621: working in the optimization phase, ie, giving correct MLE parameters,
622: but, as usual, outputs were not correct and program core dumped.
623:
1.186 brouard 624: Revision 1.185 2015/03/11 13:26:42 brouard
625: Summary: Inclusion of compile and links command line for Intel Compiler
626:
1.185 brouard 627: Revision 1.184 2015/03/11 11:52:39 brouard
628: Summary: Back from Windows 8. Intel Compiler
629:
1.184 brouard 630: Revision 1.183 2015/03/10 20:34:32 brouard
631: Summary: 0.98q0, trying with directest, mnbrak fixed
632:
633: We use directest instead of original Powell test; probably no
634: incidence on the results, but better justifications;
635: We fixed Numerical Recipes mnbrak routine which was wrong and gave
636: wrong results.
637:
1.183 brouard 638: Revision 1.182 2015/02/12 08:19:57 brouard
639: Summary: Trying to keep directest which seems simpler and more general
640: Author: Nicolas Brouard
641:
1.182 brouard 642: Revision 1.181 2015/02/11 23:22:24 brouard
643: Summary: Comments on Powell added
644:
645: Author:
646:
1.181 brouard 647: Revision 1.180 2015/02/11 17:33:45 brouard
648: Summary: Finishing move from main to function (hpijx and prevalence_limit)
649:
1.180 brouard 650: Revision 1.179 2015/01/04 09:57:06 brouard
651: Summary: back to OS/X
652:
1.179 brouard 653: Revision 1.178 2015/01/04 09:35:48 brouard
654: *** empty log message ***
655:
1.178 brouard 656: Revision 1.177 2015/01/03 18:40:56 brouard
657: Summary: Still testing ilc32 on OSX
658:
1.177 brouard 659: Revision 1.176 2015/01/03 16:45:04 brouard
660: *** empty log message ***
661:
1.176 brouard 662: Revision 1.175 2015/01/03 16:33:42 brouard
663: *** empty log message ***
664:
1.175 brouard 665: Revision 1.174 2015/01/03 16:15:49 brouard
666: Summary: Still in cross-compilation
667:
1.174 brouard 668: Revision 1.173 2015/01/03 12:06:26 brouard
669: Summary: trying to detect cross-compilation
670:
1.173 brouard 671: Revision 1.172 2014/12/27 12:07:47 brouard
672: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
673:
1.172 brouard 674: Revision 1.171 2014/12/23 13:26:59 brouard
675: Summary: Back from Visual C
676:
677: Still problem with utsname.h on Windows
678:
1.171 brouard 679: Revision 1.170 2014/12/23 11:17:12 brouard
680: Summary: Cleaning some \%% back to %%
681:
682: The escape was mandatory for a specific compiler (which one?), but too many warnings.
683:
1.170 brouard 684: Revision 1.169 2014/12/22 23:08:31 brouard
685: Summary: 0.98p
686:
687: Outputs some informations on compiler used, OS etc. Testing on different platforms.
688:
1.169 brouard 689: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 690: Summary: update
1.169 brouard 691:
1.168 brouard 692: Revision 1.167 2014/12/22 13:50:56 brouard
693: Summary: Testing uname and compiler version and if compiled 32 or 64
694:
695: Testing on Linux 64
696:
1.167 brouard 697: Revision 1.166 2014/12/22 11:40:47 brouard
698: *** empty log message ***
699:
1.166 brouard 700: Revision 1.165 2014/12/16 11:20:36 brouard
701: Summary: After compiling on Visual C
702:
703: * imach.c (Module): Merging 1.61 to 1.162
704:
1.165 brouard 705: Revision 1.164 2014/12/16 10:52:11 brouard
706: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
707:
708: * imach.c (Module): Merging 1.61 to 1.162
709:
1.164 brouard 710: Revision 1.163 2014/12/16 10:30:11 brouard
711: * imach.c (Module): Merging 1.61 to 1.162
712:
1.163 brouard 713: Revision 1.162 2014/09/25 11:43:39 brouard
714: Summary: temporary backup 0.99!
715:
1.162 brouard 716: Revision 1.1 2014/09/16 11:06:58 brouard
717: Summary: With some code (wrong) for nlopt
718:
719: Author:
720:
721: Revision 1.161 2014/09/15 20:41:41 brouard
722: Summary: Problem with macro SQR on Intel compiler
723:
1.161 brouard 724: Revision 1.160 2014/09/02 09:24:05 brouard
725: *** empty log message ***
726:
1.160 brouard 727: Revision 1.159 2014/09/01 10:34:10 brouard
728: Summary: WIN32
729: Author: Brouard
730:
1.159 brouard 731: Revision 1.158 2014/08/27 17:11:51 brouard
732: *** empty log message ***
733:
1.158 brouard 734: Revision 1.157 2014/08/27 16:26:55 brouard
735: Summary: Preparing windows Visual studio version
736: Author: Brouard
737:
738: In order to compile on Visual studio, time.h is now correct and time_t
739: and tm struct should be used. difftime should be used but sometimes I
740: just make the differences in raw time format (time(&now).
741: Trying to suppress #ifdef LINUX
742: Add xdg-open for __linux in order to open default browser.
743:
1.157 brouard 744: Revision 1.156 2014/08/25 20:10:10 brouard
745: *** empty log message ***
746:
1.156 brouard 747: Revision 1.155 2014/08/25 18:32:34 brouard
748: Summary: New compile, minor changes
749: Author: Brouard
750:
1.155 brouard 751: Revision 1.154 2014/06/20 17:32:08 brouard
752: Summary: Outputs now all graphs of convergence to period prevalence
753:
1.154 brouard 754: Revision 1.153 2014/06/20 16:45:46 brouard
755: Summary: If 3 live state, convergence to period prevalence on same graph
756: Author: Brouard
757:
1.153 brouard 758: Revision 1.152 2014/06/18 17:54:09 brouard
759: Summary: open browser, use gnuplot on same dir than imach if not found in the path
760:
1.152 brouard 761: Revision 1.151 2014/06/18 16:43:30 brouard
762: *** empty log message ***
763:
1.151 brouard 764: Revision 1.150 2014/06/18 16:42:35 brouard
765: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
766: Author: brouard
767:
1.150 brouard 768: Revision 1.149 2014/06/18 15:51:14 brouard
769: Summary: Some fixes in parameter files errors
770: Author: Nicolas Brouard
771:
1.149 brouard 772: Revision 1.148 2014/06/17 17:38:48 brouard
773: Summary: Nothing new
774: Author: Brouard
775:
776: Just a new packaging for OS/X version 0.98nS
777:
1.148 brouard 778: Revision 1.147 2014/06/16 10:33:11 brouard
779: *** empty log message ***
780:
1.147 brouard 781: Revision 1.146 2014/06/16 10:20:28 brouard
782: Summary: Merge
783: Author: Brouard
784:
785: Merge, before building revised version.
786:
1.146 brouard 787: Revision 1.145 2014/06/10 21:23:15 brouard
788: Summary: Debugging with valgrind
789: Author: Nicolas Brouard
790:
791: Lot of changes in order to output the results with some covariates
792: After the Edimburgh REVES conference 2014, it seems mandatory to
793: improve the code.
794: No more memory valgrind error but a lot has to be done in order to
795: continue the work of splitting the code into subroutines.
796: Also, decodemodel has been improved. Tricode is still not
797: optimal. nbcode should be improved. Documentation has been added in
798: the source code.
799:
1.144 brouard 800: Revision 1.143 2014/01/26 09:45:38 brouard
801: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
802:
803: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
804: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
805:
1.143 brouard 806: Revision 1.142 2014/01/26 03:57:36 brouard
807: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
808:
809: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
810:
1.142 brouard 811: Revision 1.141 2014/01/26 02:42:01 brouard
812: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
813:
1.141 brouard 814: Revision 1.140 2011/09/02 10:37:54 brouard
815: Summary: times.h is ok with mingw32 now.
816:
1.140 brouard 817: Revision 1.139 2010/06/14 07:50:17 brouard
818: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
819: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
820:
1.139 brouard 821: Revision 1.138 2010/04/30 18:19:40 brouard
822: *** empty log message ***
823:
1.138 brouard 824: Revision 1.137 2010/04/29 18:11:38 brouard
825: (Module): Checking covariates for more complex models
826: than V1+V2. A lot of change to be done. Unstable.
827:
1.137 brouard 828: Revision 1.136 2010/04/26 20:30:53 brouard
829: (Module): merging some libgsl code. Fixing computation
830: of likelione (using inter/intrapolation if mle = 0) in order to
831: get same likelihood as if mle=1.
832: Some cleaning of code and comments added.
833:
1.136 brouard 834: Revision 1.135 2009/10/29 15:33:14 brouard
835: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
836:
1.135 brouard 837: Revision 1.134 2009/10/29 13:18:53 brouard
838: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
839:
1.134 brouard 840: Revision 1.133 2009/07/06 10:21:25 brouard
841: just nforces
842:
1.133 brouard 843: Revision 1.132 2009/07/06 08:22:05 brouard
844: Many tings
845:
1.132 brouard 846: Revision 1.131 2009/06/20 16:22:47 brouard
847: Some dimensions resccaled
848:
1.131 brouard 849: Revision 1.130 2009/05/26 06:44:34 brouard
850: (Module): Max Covariate is now set to 20 instead of 8. A
851: lot of cleaning with variables initialized to 0. Trying to make
852: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
853:
1.130 brouard 854: Revision 1.129 2007/08/31 13:49:27 lievre
855: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
856:
1.129 lievre 857: Revision 1.128 2006/06/30 13:02:05 brouard
858: (Module): Clarifications on computing e.j
859:
1.128 brouard 860: Revision 1.127 2006/04/28 18:11:50 brouard
861: (Module): Yes the sum of survivors was wrong since
862: imach-114 because nhstepm was no more computed in the age
863: loop. Now we define nhstepma in the age loop.
864: (Module): In order to speed up (in case of numerous covariates) we
865: compute health expectancies (without variances) in a first step
866: and then all the health expectancies with variances or standard
867: deviation (needs data from the Hessian matrices) which slows the
868: computation.
869: In the future we should be able to stop the program is only health
870: expectancies and graph are needed without standard deviations.
871:
1.127 brouard 872: Revision 1.126 2006/04/28 17:23:28 brouard
873: (Module): Yes the sum of survivors was wrong since
874: imach-114 because nhstepm was no more computed in the age
875: loop. Now we define nhstepma in the age loop.
876: Version 0.98h
877:
1.126 brouard 878: Revision 1.125 2006/04/04 15:20:31 lievre
879: Errors in calculation of health expectancies. Age was not initialized.
880: Forecasting file added.
881:
882: Revision 1.124 2006/03/22 17:13:53 lievre
883: Parameters are printed with %lf instead of %f (more numbers after the comma).
884: The log-likelihood is printed in the log file
885:
886: Revision 1.123 2006/03/20 10:52:43 brouard
887: * imach.c (Module): <title> changed, corresponds to .htm file
888: name. <head> headers where missing.
889:
890: * imach.c (Module): Weights can have a decimal point as for
891: English (a comma might work with a correct LC_NUMERIC environment,
892: otherwise the weight is truncated).
893: Modification of warning when the covariates values are not 0 or
894: 1.
895: Version 0.98g
896:
897: Revision 1.122 2006/03/20 09:45:41 brouard
898: (Module): Weights can have a decimal point as for
899: English (a comma might work with a correct LC_NUMERIC environment,
900: otherwise the weight is truncated).
901: Modification of warning when the covariates values are not 0 or
902: 1.
903: Version 0.98g
904:
905: Revision 1.121 2006/03/16 17:45:01 lievre
906: * imach.c (Module): Comments concerning covariates added
907:
908: * imach.c (Module): refinements in the computation of lli if
909: status=-2 in order to have more reliable computation if stepm is
910: not 1 month. Version 0.98f
911:
912: Revision 1.120 2006/03/16 15:10:38 lievre
913: (Module): refinements in the computation of lli if
914: status=-2 in order to have more reliable computation if stepm is
915: not 1 month. Version 0.98f
916:
917: Revision 1.119 2006/03/15 17:42:26 brouard
918: (Module): Bug if status = -2, the loglikelihood was
919: computed as likelihood omitting the logarithm. Version O.98e
920:
921: Revision 1.118 2006/03/14 18:20:07 brouard
922: (Module): varevsij Comments added explaining the second
923: table of variances if popbased=1 .
924: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
925: (Module): Function pstamp added
926: (Module): Version 0.98d
927:
928: Revision 1.117 2006/03/14 17:16:22 brouard
929: (Module): varevsij Comments added explaining the second
930: table of variances if popbased=1 .
931: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
932: (Module): Function pstamp added
933: (Module): Version 0.98d
934:
935: Revision 1.116 2006/03/06 10:29:27 brouard
936: (Module): Variance-covariance wrong links and
937: varian-covariance of ej. is needed (Saito).
938:
939: Revision 1.115 2006/02/27 12:17:45 brouard
940: (Module): One freematrix added in mlikeli! 0.98c
941:
942: Revision 1.114 2006/02/26 12:57:58 brouard
943: (Module): Some improvements in processing parameter
944: filename with strsep.
945:
946: Revision 1.113 2006/02/24 14:20:24 brouard
947: (Module): Memory leaks checks with valgrind and:
948: datafile was not closed, some imatrix were not freed and on matrix
949: allocation too.
950:
951: Revision 1.112 2006/01/30 09:55:26 brouard
952: (Module): Back to gnuplot.exe instead of wgnuplot.exe
953:
954: Revision 1.111 2006/01/25 20:38:18 brouard
955: (Module): Lots of cleaning and bugs added (Gompertz)
956: (Module): Comments can be added in data file. Missing date values
957: can be a simple dot '.'.
958:
959: Revision 1.110 2006/01/25 00:51:50 brouard
960: (Module): Lots of cleaning and bugs added (Gompertz)
961:
962: Revision 1.109 2006/01/24 19:37:15 brouard
963: (Module): Comments (lines starting with a #) are allowed in data.
964:
965: Revision 1.108 2006/01/19 18:05:42 lievre
966: Gnuplot problem appeared...
967: To be fixed
968:
969: Revision 1.107 2006/01/19 16:20:37 brouard
970: Test existence of gnuplot in imach path
971:
972: Revision 1.106 2006/01/19 13:24:36 brouard
973: Some cleaning and links added in html output
974:
975: Revision 1.105 2006/01/05 20:23:19 lievre
976: *** empty log message ***
977:
978: Revision 1.104 2005/09/30 16:11:43 lievre
979: (Module): sump fixed, loop imx fixed, and simplifications.
980: (Module): If the status is missing at the last wave but we know
981: that the person is alive, then we can code his/her status as -2
982: (instead of missing=-1 in earlier versions) and his/her
983: contributions to the likelihood is 1 - Prob of dying from last
984: health status (= 1-p13= p11+p12 in the easiest case of somebody in
985: the healthy state at last known wave). Version is 0.98
986:
987: Revision 1.103 2005/09/30 15:54:49 lievre
988: (Module): sump fixed, loop imx fixed, and simplifications.
989:
990: Revision 1.102 2004/09/15 17:31:30 brouard
991: Add the possibility to read data file including tab characters.
992:
993: Revision 1.101 2004/09/15 10:38:38 brouard
994: Fix on curr_time
995:
996: Revision 1.100 2004/07/12 18:29:06 brouard
997: Add version for Mac OS X. Just define UNIX in Makefile
998:
999: Revision 1.99 2004/06/05 08:57:40 brouard
1000: *** empty log message ***
1001:
1002: Revision 1.98 2004/05/16 15:05:56 brouard
1003: New version 0.97 . First attempt to estimate force of mortality
1004: directly from the data i.e. without the need of knowing the health
1005: state at each age, but using a Gompertz model: log u =a + b*age .
1006: This is the basic analysis of mortality and should be done before any
1007: other analysis, in order to test if the mortality estimated from the
1008: cross-longitudinal survey is different from the mortality estimated
1009: from other sources like vital statistic data.
1010:
1011: The same imach parameter file can be used but the option for mle should be -3.
1012:
1.324 brouard 1013: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 1014: former routines in order to include the new code within the former code.
1015:
1016: The output is very simple: only an estimate of the intercept and of
1017: the slope with 95% confident intervals.
1018:
1019: Current limitations:
1020: A) Even if you enter covariates, i.e. with the
1021: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
1022: B) There is no computation of Life Expectancy nor Life Table.
1023:
1024: Revision 1.97 2004/02/20 13:25:42 lievre
1025: Version 0.96d. Population forecasting command line is (temporarily)
1026: suppressed.
1027:
1028: Revision 1.96 2003/07/15 15:38:55 brouard
1029: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
1030: rewritten within the same printf. Workaround: many printfs.
1031:
1032: Revision 1.95 2003/07/08 07:54:34 brouard
1033: * imach.c (Repository):
1034: (Repository): Using imachwizard code to output a more meaningful covariance
1035: matrix (cov(a12,c31) instead of numbers.
1036:
1037: Revision 1.94 2003/06/27 13:00:02 brouard
1038: Just cleaning
1039:
1040: Revision 1.93 2003/06/25 16:33:55 brouard
1041: (Module): On windows (cygwin) function asctime_r doesn't
1042: exist so I changed back to asctime which exists.
1043: (Module): Version 0.96b
1044:
1045: Revision 1.92 2003/06/25 16:30:45 brouard
1046: (Module): On windows (cygwin) function asctime_r doesn't
1047: exist so I changed back to asctime which exists.
1048:
1049: Revision 1.91 2003/06/25 15:30:29 brouard
1050: * imach.c (Repository): Duplicated warning errors corrected.
1051: (Repository): Elapsed time after each iteration is now output. It
1052: helps to forecast when convergence will be reached. Elapsed time
1053: is stamped in powell. We created a new html file for the graphs
1054: concerning matrix of covariance. It has extension -cov.htm.
1055:
1056: Revision 1.90 2003/06/24 12:34:15 brouard
1057: (Module): Some bugs corrected for windows. Also, when
1058: mle=-1 a template is output in file "or"mypar.txt with the design
1059: of the covariance matrix to be input.
1060:
1061: Revision 1.89 2003/06/24 12:30:52 brouard
1062: (Module): Some bugs corrected for windows. Also, when
1063: mle=-1 a template is output in file "or"mypar.txt with the design
1064: of the covariance matrix to be input.
1065:
1066: Revision 1.88 2003/06/23 17:54:56 brouard
1067: * 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.
1068:
1069: Revision 1.87 2003/06/18 12:26:01 brouard
1070: Version 0.96
1071:
1072: Revision 1.86 2003/06/17 20:04:08 brouard
1073: (Module): Change position of html and gnuplot routines and added
1074: routine fileappend.
1075:
1076: Revision 1.85 2003/06/17 13:12:43 brouard
1077: * imach.c (Repository): Check when date of death was earlier that
1078: current date of interview. It may happen when the death was just
1079: prior to the death. In this case, dh was negative and likelihood
1080: was wrong (infinity). We still send an "Error" but patch by
1081: assuming that the date of death was just one stepm after the
1082: interview.
1083: (Repository): Because some people have very long ID (first column)
1084: we changed int to long in num[] and we added a new lvector for
1085: memory allocation. But we also truncated to 8 characters (left
1086: truncation)
1087: (Repository): No more line truncation errors.
1088:
1089: Revision 1.84 2003/06/13 21:44:43 brouard
1090: * imach.c (Repository): Replace "freqsummary" at a correct
1091: place. It differs from routine "prevalence" which may be called
1092: many times. Probs is memory consuming and must be used with
1093: parcimony.
1094: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
1095:
1096: Revision 1.83 2003/06/10 13:39:11 lievre
1097: *** empty log message ***
1098:
1099: Revision 1.82 2003/06/05 15:57:20 brouard
1100: Add log in imach.c and fullversion number is now printed.
1101:
1102: */
1103: /*
1104: Interpolated Markov Chain
1105:
1106: Short summary of the programme:
1107:
1.227 brouard 1108: This program computes Healthy Life Expectancies or State-specific
1109: (if states aren't health statuses) Expectancies from
1110: cross-longitudinal data. Cross-longitudinal data consist in:
1111:
1112: -1- a first survey ("cross") where individuals from different ages
1113: are interviewed on their health status or degree of disability (in
1114: the case of a health survey which is our main interest)
1115:
1116: -2- at least a second wave of interviews ("longitudinal") which
1117: measure each change (if any) in individual health status. Health
1118: expectancies are computed from the time spent in each health state
1119: according to a model. More health states you consider, more time is
1120: necessary to reach the Maximum Likelihood of the parameters involved
1121: in the model. The simplest model is the multinomial logistic model
1122: where pij is the probability to be observed in state j at the second
1123: wave conditional to be observed in state i at the first
1124: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
1125: etc , where 'age' is age and 'sex' is a covariate. If you want to
1126: have a more complex model than "constant and age", you should modify
1127: the program where the markup *Covariates have to be included here
1128: again* invites you to do it. More covariates you add, slower the
1.126 brouard 1129: convergence.
1130:
1131: The advantage of this computer programme, compared to a simple
1132: multinomial logistic model, is clear when the delay between waves is not
1133: identical for each individual. Also, if a individual missed an
1134: intermediate interview, the information is lost, but taken into
1135: account using an interpolation or extrapolation.
1136:
1137: hPijx is the probability to be observed in state i at age x+h
1138: conditional to the observed state i at age x. The delay 'h' can be
1139: split into an exact number (nh*stepm) of unobserved intermediate
1140: states. This elementary transition (by month, quarter,
1141: semester or year) is modelled as a multinomial logistic. The hPx
1142: matrix is simply the matrix product of nh*stepm elementary matrices
1143: and the contribution of each individual to the likelihood is simply
1144: hPijx.
1145:
1146: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 1147: of the life expectancies. It also computes the period (stable) prevalence.
1148:
1149: Back prevalence and projections:
1.227 brouard 1150:
1151: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
1152: double agemaxpar, double ftolpl, int *ncvyearp, double
1153: dateprev1,double dateprev2, int firstpass, int lastpass, int
1154: mobilavproj)
1155:
1156: Computes the back prevalence limit for any combination of
1157: covariate values k at any age between ageminpar and agemaxpar and
1158: returns it in **bprlim. In the loops,
1159:
1160: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
1161: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
1162:
1163: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 1164: Computes for any combination of covariates k and any age between bage and fage
1165: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
1166: oldm=oldms;savm=savms;
1.227 brouard 1167:
1.267 brouard 1168: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 1169: Computes the transition matrix starting at age 'age' over
1170: 'nhstepm*hstepm*stepm' months (i.e. until
1171: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 1172: nhstepm*hstepm matrices.
1173:
1174: Returns p3mat[i][j][h] after calling
1175: p3mat[i][j][h]=matprod2(newm,
1176: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
1177: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
1178: oldm);
1.226 brouard 1179:
1180: Important routines
1181:
1182: - func (or funcone), computes logit (pij) distinguishing
1183: o fixed variables (single or product dummies or quantitative);
1184: o varying variables by:
1185: (1) wave (single, product dummies, quantitative),
1186: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
1187: % fixed dummy (treated) or quantitative (not done because time-consuming);
1188: % varying dummy (not done) or quantitative (not done);
1189: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
1190: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
1191: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
1.325 brouard 1192: o There are 2**cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
1.226 brouard 1193: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 1194:
1.226 brouard 1195:
1196:
1.324 brouard 1197: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
1198: Institut national d'études démographiques, Paris.
1.126 brouard 1199: This software have been partly granted by Euro-REVES, a concerted action
1200: from the European Union.
1201: It is copyrighted identically to a GNU software product, ie programme and
1202: software can be distributed freely for non commercial use. Latest version
1203: can be accessed at http://euroreves.ined.fr/imach .
1204:
1205: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
1206: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
1207:
1208: **********************************************************************/
1209: /*
1210: main
1211: read parameterfile
1212: read datafile
1213: concatwav
1214: freqsummary
1215: if (mle >= 1)
1216: mlikeli
1217: print results files
1218: if mle==1
1219: computes hessian
1220: read end of parameter file: agemin, agemax, bage, fage, estepm
1221: begin-prev-date,...
1222: open gnuplot file
1223: open html file
1.145 brouard 1224: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
1225: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
1226: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
1227: freexexit2 possible for memory heap.
1228:
1229: h Pij x | pij_nom ficrestpij
1230: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
1231: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
1232: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
1233:
1234: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
1235: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
1236: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
1237: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
1238: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
1239:
1.126 brouard 1240: forecasting if prevfcast==1 prevforecast call prevalence()
1241: health expectancies
1242: Variance-covariance of DFLE
1243: prevalence()
1244: movingaverage()
1245: varevsij()
1246: if popbased==1 varevsij(,popbased)
1247: total life expectancies
1248: Variance of period (stable) prevalence
1249: end
1250: */
1251:
1.187 brouard 1252: /* #define DEBUG */
1253: /* #define DEBUGBRENT */
1.203 brouard 1254: /* #define DEBUGLINMIN */
1255: /* #define DEBUGHESS */
1256: #define DEBUGHESSIJ
1.224 brouard 1257: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 1258: #define POWELL /* Instead of NLOPT */
1.224 brouard 1259: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 1260: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
1261: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.319 brouard 1262: /* #define FLATSUP *//* Suppresses directions where likelihood is flat */
1.126 brouard 1263:
1264: #include <math.h>
1265: #include <stdio.h>
1266: #include <stdlib.h>
1267: #include <string.h>
1.226 brouard 1268: #include <ctype.h>
1.159 brouard 1269:
1270: #ifdef _WIN32
1271: #include <io.h>
1.172 brouard 1272: #include <windows.h>
1273: #include <tchar.h>
1.159 brouard 1274: #else
1.126 brouard 1275: #include <unistd.h>
1.159 brouard 1276: #endif
1.126 brouard 1277:
1278: #include <limits.h>
1279: #include <sys/types.h>
1.171 brouard 1280:
1281: #if defined(__GNUC__)
1282: #include <sys/utsname.h> /* Doesn't work on Windows */
1283: #endif
1284:
1.126 brouard 1285: #include <sys/stat.h>
1286: #include <errno.h>
1.159 brouard 1287: /* extern int errno; */
1.126 brouard 1288:
1.157 brouard 1289: /* #ifdef LINUX */
1290: /* #include <time.h> */
1291: /* #include "timeval.h" */
1292: /* #else */
1293: /* #include <sys/time.h> */
1294: /* #endif */
1295:
1.126 brouard 1296: #include <time.h>
1297:
1.136 brouard 1298: #ifdef GSL
1299: #include <gsl/gsl_errno.h>
1300: #include <gsl/gsl_multimin.h>
1301: #endif
1302:
1.167 brouard 1303:
1.162 brouard 1304: #ifdef NLOPT
1305: #include <nlopt.h>
1306: typedef struct {
1307: double (* function)(double [] );
1308: } myfunc_data ;
1309: #endif
1310:
1.126 brouard 1311: /* #include <libintl.h> */
1312: /* #define _(String) gettext (String) */
1313:
1.251 brouard 1314: #define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1315:
1316: #define GNUPLOTPROGRAM "gnuplot"
1.343 brouard 1317: #define GNUPLOTVERSION 5.1
1318: double gnuplotversion=GNUPLOTVERSION;
1.126 brouard 1319: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1.329 brouard 1320: #define FILENAMELENGTH 256
1.126 brouard 1321:
1322: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1323: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1324:
1.144 brouard 1325: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
1326: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1327:
1328: #define NINTERVMAX 8
1.144 brouard 1329: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1330: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.325 brouard 1331: #define NCOVMAX 30 /**< Maximum number of covariates used in the model, including generated covariates V1*V2 or V1*age */
1.197 brouard 1332: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1333: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1334: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1335: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1336: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1337: /* #define AGESUP 130 */
1.288 brouard 1338: /* #define AGESUP 150 */
1339: #define AGESUP 200
1.268 brouard 1340: #define AGEINF 0
1.218 brouard 1341: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1342: #define AGEBASE 40
1.194 brouard 1343: #define AGEOVERFLOW 1.e20
1.164 brouard 1344: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1345: #ifdef _WIN32
1346: #define DIRSEPARATOR '\\'
1347: #define CHARSEPARATOR "\\"
1348: #define ODIRSEPARATOR '/'
1349: #else
1.126 brouard 1350: #define DIRSEPARATOR '/'
1351: #define CHARSEPARATOR "/"
1352: #define ODIRSEPARATOR '\\'
1353: #endif
1354:
1.347 ! brouard 1355: /* $Id: imach.c,v 1.346 2022/09/16 13:52:36 brouard Exp $ */
1.126 brouard 1356: /* $State: Exp $ */
1.196 brouard 1357: #include "version.h"
1358: char version[]=__IMACH_VERSION__;
1.337 brouard 1359: char copyright[]="September 2022,INED-EUROREVES-Institut de longevite-Japan Society for the Promotion of Science (Grant-in-Aid for Scientific Research 25293121), Intel Software 2015-2020, Nihon University 2021-202, INED 2000-2022";
1.347 ! brouard 1360: char fullversion[]="$Revision: 1.346 $ $Date: 2022/09/16 13:52:36 $";
1.126 brouard 1361: char strstart[80];
1362: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1363: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.342 brouard 1364: int debugILK=0; /* debugILK is set by a #d in a comment line */
1.187 brouard 1365: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.330 brouard 1366: /* Number of covariates model (1)=V2+V1+ V3*age+V2*V4 */
1367: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
1.335 brouard 1368: 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 1369: 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 1370: int cptcovs=0; /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
1371: int cptcovsnq=0; /**< cptcovsnq number of SIMPLE covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1372: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1373: int cptcovprodnoage=0; /**< Number of covariate products without age */
1.335 brouard 1374: 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 1375: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1376: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.339 brouard 1377: int ncovvt=0; /* Total number of effective (wave) varying covariates (dummy or quantitative or products [without age]) in the model */
1.232 brouard 1378: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 1379: int nsd=0; /**< Total number of single dummy variables (output) */
1380: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1381: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1382: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1383: int ntveff=0; /**< ntveff number of effective time varying variables */
1384: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1385: int cptcov=0; /* Working variable */
1.334 brouard 1386: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs+1 declared globally ;*/
1.290 brouard 1387: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1388: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.302 brouard 1389: int npar=NPARMAX; /* Number of parameters (nlstate+ndeath-1)*nlstate*ncovmodel; */
1.126 brouard 1390: int nlstate=2; /* Number of live states */
1391: int ndeath=1; /* Number of dead states */
1.130 brouard 1392: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.339 brouard 1393: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable*/
1394: int ncovcolt=0; /* ncovcolt=ncovcol+nqv+ntv+nqtv; total of covariates in the data, not in the model equation*/
1.126 brouard 1395: int popbased=0;
1396:
1397: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1398: int maxwav=0; /* Maxim number of waves */
1399: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1400: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1401: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1402: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1403: int mle=1, weightopt=0;
1.126 brouard 1404: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1405: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1406: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1407: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1408: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1409: int selected(int kvar); /* Is covariate kvar selected for printing results */
1410:
1.130 brouard 1411: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1412: double **matprod2(); /* test */
1.126 brouard 1413: double **oldm, **newm, **savm; /* Working pointers to matrices */
1414: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1415: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1416:
1.136 brouard 1417: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1418: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1419: FILE *ficlog, *ficrespow;
1.130 brouard 1420: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1421: double fretone; /* Only one call to likelihood */
1.130 brouard 1422: long ipmx=0; /* Number of contributions */
1.126 brouard 1423: double sw; /* Sum of weights */
1424: char filerespow[FILENAMELENGTH];
1425: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1426: FILE *ficresilk;
1427: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1428: FILE *ficresprobmorprev;
1429: FILE *fichtm, *fichtmcov; /* Html File */
1430: FILE *ficreseij;
1431: char filerese[FILENAMELENGTH];
1432: FILE *ficresstdeij;
1433: char fileresstde[FILENAMELENGTH];
1434: FILE *ficrescveij;
1435: char filerescve[FILENAMELENGTH];
1436: FILE *ficresvij;
1437: char fileresv[FILENAMELENGTH];
1.269 brouard 1438:
1.126 brouard 1439: char title[MAXLINE];
1.234 brouard 1440: char model[MAXLINE]; /**< The model line */
1.217 brouard 1441: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1442: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1443: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1444: char command[FILENAMELENGTH];
1445: int outcmd=0;
1446:
1.217 brouard 1447: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1448: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1449: char filelog[FILENAMELENGTH]; /* Log file */
1450: char filerest[FILENAMELENGTH];
1451: char fileregp[FILENAMELENGTH];
1452: char popfile[FILENAMELENGTH];
1453:
1454: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1455:
1.157 brouard 1456: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1457: /* struct timezone tzp; */
1458: /* extern int gettimeofday(); */
1459: struct tm tml, *gmtime(), *localtime();
1460:
1461: extern time_t time();
1462:
1463: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1464: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1465: struct tm tm;
1466:
1.126 brouard 1467: char strcurr[80], strfor[80];
1468:
1469: char *endptr;
1470: long lval;
1471: double dval;
1472:
1473: #define NR_END 1
1474: #define FREE_ARG char*
1475: #define FTOL 1.0e-10
1476:
1477: #define NRANSI
1.240 brouard 1478: #define ITMAX 200
1479: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1480:
1481: #define TOL 2.0e-4
1482:
1483: #define CGOLD 0.3819660
1484: #define ZEPS 1.0e-10
1485: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1486:
1487: #define GOLD 1.618034
1488: #define GLIMIT 100.0
1489: #define TINY 1.0e-20
1490:
1491: static double maxarg1,maxarg2;
1492: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1493: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1494:
1495: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1496: #define rint(a) floor(a+0.5)
1.166 brouard 1497: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1498: #define mytinydouble 1.0e-16
1.166 brouard 1499: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1500: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1501: /* static double dsqrarg; */
1502: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1503: static double sqrarg;
1504: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1505: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1506: int agegomp= AGEGOMP;
1507:
1508: int imx;
1509: int stepm=1;
1510: /* Stepm, step in month: minimum step interpolation*/
1511:
1512: int estepm;
1513: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1514:
1515: int m,nb;
1516: long *num;
1.197 brouard 1517: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1518: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1519: covariate for which somebody answered excluding
1520: undefined. Usually 2: 0 and 1. */
1521: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1522: covariate for which somebody answered including
1523: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1524: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1525: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1526: double ***mobaverage, ***mobaverages; /* New global variable */
1.332 brouard 1527: 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 1528: double *ageexmed,*agecens;
1529: double dateintmean=0;
1.296 brouard 1530: double anprojd, mprojd, jprojd; /* For eventual projections */
1531: double anprojf, mprojf, jprojf;
1.126 brouard 1532:
1.296 brouard 1533: double anbackd, mbackd, jbackd; /* For eventual backprojections */
1534: double anbackf, mbackf, jbackf;
1535: double jintmean,mintmean,aintmean;
1.126 brouard 1536: double *weight;
1537: int **s; /* Status */
1.141 brouard 1538: double *agedc;
1.145 brouard 1539: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1540: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1541: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1542: double **coqvar; /* Fixed quantitative covariate nqv */
1.341 brouard 1543: double ***cotvar; /* Time varying covariate start at ncovcol + nqv + (1 to ntv) */
1.225 brouard 1544: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1545: double idx;
1546: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.319 brouard 1547: /* Some documentation */
1548: /* Design original data
1549: * V1 V2 V3 V4 V5 V6 V7 V8 Weight ddb ddth d1st s1 V9 V10 V11 V12 s2 V9 V10 V11 V12
1550: * < ncovcol=6 > nqv=2 (V7 V8) dv dv dv qtv dv dv dvv qtv
1551: * ntv=3 nqtv=1
1.330 brouard 1552: * cptcovn number of covariates (not including constant and age or age*age) = number of plus sign + 1 = 10+1=11
1.319 brouard 1553: * For time varying covariate, quanti or dummies
1554: * cotqvar[wav][iv(1 to nqtv)][i]= [1][12][i]=(V12) quanti
1.341 brouard 1555: * cotvar[wav][ncovcol+nqv+ iv(1 to nqtv)][i]= [(1 to nqtv)][i]=(V12) quanti
1.319 brouard 1556: * cotvar[wav][iv(1 to ntv)][i]= [1][1][i]=(V9) dummies at wav 1
1557: * cotvar[wav][iv(1 to ntv)][i]= [1][2][i]=(V10) dummies at wav 1
1.332 brouard 1558: * covar[Vk,i], value of the Vkth fixed covariate dummy or quanti for individual i:
1.319 brouard 1559: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
1560: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 + V9 + V9*age + V10
1561: * k= 1 2 3 4 5 6 7 8 9 10 11
1562: */
1563: /* According to the model, more columns can be added to covar by the product of covariates */
1.318 brouard 1564: /* 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
1565: # States 1=Coresidence, 2 Living alone, 3 Institution
1566: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1567: */
1.343 brouard 1568: /* V5+V4+ V3+V4*V3 +V5*age+V2 +V1*V2+V1*age+V1 */
1569: /* kmodel 1 2 3 4 5 6 7 8 9 */
1.319 brouard 1570: /*Typevar[k]= 0 0 0 2 1 0 2 1 0 *//*0 for simple covariate (dummy, quantitative,*/
1571: /* fixed or varying), 1 for age product, 2 for*/
1572: /* product */
1573: /*Dummy[k]= 1 0 0 1 3 1 1 2 0 *//*Dummy[k] 0=dummy (0 1), 1 quantitative */
1574: /*(single or product without age), 2 dummy*/
1575: /* with age product, 3 quant with age product*/
1576: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1577: /* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */
1.330 brouard 1578: /*TnsdVar[Tvar] 1 2 3 */
1.337 brouard 1579: /*Tvaraff[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1.319 brouard 1580: /*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1.338 brouard 1581: /*TvarsDind[nsd] 2 3 9 */ /* position K of single dummy cova */
1.319 brouard 1582: /* nsq 1 2 */ /* Counting single quantit tv */
1583: /* TvarsQ[k] 5 2 */ /* Number of single quantitative cova */
1584: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1585: /* Tprod[i]=k 1 2 */ /* Position in model of the ith prod without age */
1586: /* cptcovage 1 2 */ /* Counting cov*age in the model equation */
1587: /* Tage[cptcovage]=k 5 8 */ /* Position in the model of ith cov*age */
1588: /* Tvard[1][1]@4={4,3,1,2} V4*V3 V1*V2 */ /* Position in model of the ith prod without age */
1.330 brouard 1589: /* 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 1590: /* 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 1591: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.234 brouard 1592: /* Type */
1593: /* V 1 2 3 4 5 */
1594: /* F F V V V */
1595: /* D Q D D Q */
1596: /* */
1597: int *TvarsD;
1.330 brouard 1598: int *TnsdVar;
1.234 brouard 1599: int *TvarsDind;
1600: int *TvarsQ;
1601: int *TvarsQind;
1602:
1.318 brouard 1603: #define MAXRESULTLINESPONE 10+1
1.235 brouard 1604: int nresult=0;
1.258 brouard 1605: int parameterline=0; /* # of the parameter (type) line */
1.334 brouard 1606: int TKresult[MAXRESULTLINESPONE]; /* TKresult[nres]=k for each resultline nres give the corresponding combination of dummies */
1607: int resultmodel[MAXRESULTLINESPONE][NCOVMAX];/* resultmodel[k1]=k3: k1th position in the model corresponds to the k3 position in the resultline */
1608: int modelresult[MAXRESULTLINESPONE][NCOVMAX];/* modelresult[k3]=k1: k1th position in the model corresponds to the k3 position in the resultline */
1609: int Tresult[MAXRESULTLINESPONE][NCOVMAX];/* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1610: int Tinvresult[MAXRESULTLINESPONE][NCOVMAX];/* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1611: double TinvDoQresult[MAXRESULTLINESPONE][NCOVMAX];/* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.334 brouard 1612: int Tvresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1613: double Tqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.318 brouard 1614: double Tqinvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
1.332 brouard 1615: int Tvqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.318 brouard 1616:
1617: /* 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
1618: # States 1=Coresidence, 2 Living alone, 3 Institution
1619: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1620: */
1.234 brouard 1621: /* 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 1622: 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 */
1623: 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 */
1624: 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 */
1625: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1626: 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 */
1627: 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 1628: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1629: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1630: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1631: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1632: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1633: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1634: 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 */
1635: 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 1636: int *TvarVV; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1637: int *TvarVVind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1638: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
1639: /* model V1+V3+age*V1+age*V3+V1*V3 */
1640: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
1641: /* TvarVV={3,1,3}, for V3 and then the product V1*V3 is decomposed into V1 and V3 */
1642: /* TvarVVind={2,5,5}, for V3 and then the product V1*V3 is decomposed into V1 and V3 */
1.230 brouard 1643: int *Tvarsel; /**< Selected covariates for output */
1644: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1645: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1646: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1647: 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 1648: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1649: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1650: int *Tage;
1.227 brouard 1651: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1652: 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 1653: 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*/
1654: 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 1655: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1656: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1657: int **Tvard;
1.330 brouard 1658: int **Tvardk;
1.227 brouard 1659: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1660: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1661: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1662: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1663: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1664: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1665: double *lsurv, *lpop, *tpop;
1666:
1.231 brouard 1667: #define FD 1; /* Fixed dummy covariate */
1668: #define FQ 2; /* Fixed quantitative covariate */
1669: #define FP 3; /* Fixed product covariate */
1670: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1671: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1672: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1673: #define VD 10; /* Varying dummy covariate */
1674: #define VQ 11; /* Varying quantitative covariate */
1675: #define VP 12; /* Varying product covariate */
1676: #define VPDD 13; /* Varying product dummy*dummy covariate */
1677: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1678: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1679: #define APFD 16; /* Age product * fixed dummy covariate */
1680: #define APFQ 17; /* Age product * fixed quantitative covariate */
1681: #define APVD 18; /* Age product * varying dummy covariate */
1682: #define APVQ 19; /* Age product * varying quantitative covariate */
1683:
1684: #define FTYPE 1; /* Fixed covariate */
1685: #define VTYPE 2; /* Varying covariate (loop in wave) */
1686: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1687:
1688: struct kmodel{
1689: int maintype; /* main type */
1690: int subtype; /* subtype */
1691: };
1692: struct kmodel modell[NCOVMAX];
1693:
1.143 brouard 1694: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1695: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1696:
1697: /**************** split *************************/
1698: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1699: {
1700: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1701: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1702: */
1703: char *ss; /* pointer */
1.186 brouard 1704: int l1=0, l2=0; /* length counters */
1.126 brouard 1705:
1706: l1 = strlen(path ); /* length of path */
1707: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1708: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1709: if ( ss == NULL ) { /* no directory, so determine current directory */
1710: strcpy( name, path ); /* we got the fullname name because no directory */
1711: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1712: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1713: /* get current working directory */
1714: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1715: #ifdef WIN32
1716: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1717: #else
1718: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1719: #endif
1.126 brouard 1720: return( GLOCK_ERROR_GETCWD );
1721: }
1722: /* got dirc from getcwd*/
1723: printf(" DIRC = %s \n",dirc);
1.205 brouard 1724: } else { /* strip directory from path */
1.126 brouard 1725: ss++; /* after this, the filename */
1726: l2 = strlen( ss ); /* length of filename */
1727: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1728: strcpy( name, ss ); /* save file name */
1729: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1730: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1731: printf(" DIRC2 = %s \n",dirc);
1732: }
1733: /* We add a separator at the end of dirc if not exists */
1734: l1 = strlen( dirc ); /* length of directory */
1735: if( dirc[l1-1] != DIRSEPARATOR ){
1736: dirc[l1] = DIRSEPARATOR;
1737: dirc[l1+1] = 0;
1738: printf(" DIRC3 = %s \n",dirc);
1739: }
1740: ss = strrchr( name, '.' ); /* find last / */
1741: if (ss >0){
1742: ss++;
1743: strcpy(ext,ss); /* save extension */
1744: l1= strlen( name);
1745: l2= strlen(ss)+1;
1746: strncpy( finame, name, l1-l2);
1747: finame[l1-l2]= 0;
1748: }
1749:
1750: return( 0 ); /* we're done */
1751: }
1752:
1753:
1754: /******************************************/
1755:
1756: void replace_back_to_slash(char *s, char*t)
1757: {
1758: int i;
1759: int lg=0;
1760: i=0;
1761: lg=strlen(t);
1762: for(i=0; i<= lg; i++) {
1763: (s[i] = t[i]);
1764: if (t[i]== '\\') s[i]='/';
1765: }
1766: }
1767:
1.132 brouard 1768: char *trimbb(char *out, char *in)
1.137 brouard 1769: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1770: char *s;
1771: s=out;
1772: while (*in != '\0'){
1.137 brouard 1773: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1774: in++;
1775: }
1776: *out++ = *in++;
1777: }
1778: *out='\0';
1779: return s;
1780: }
1781:
1.187 brouard 1782: /* char *substrchaine(char *out, char *in, char *chain) */
1783: /* { */
1784: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1785: /* char *s, *t; */
1786: /* t=in;s=out; */
1787: /* while ((*in != *chain) && (*in != '\0')){ */
1788: /* *out++ = *in++; */
1789: /* } */
1790:
1791: /* /\* *in matches *chain *\/ */
1792: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1793: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1794: /* } */
1795: /* in--; chain--; */
1796: /* while ( (*in != '\0')){ */
1797: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1798: /* *out++ = *in++; */
1799: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1800: /* } */
1801: /* *out='\0'; */
1802: /* out=s; */
1803: /* return out; */
1804: /* } */
1805: char *substrchaine(char *out, char *in, char *chain)
1806: {
1807: /* Substract chain 'chain' from 'in', return and output 'out' */
1808: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1809:
1810: char *strloc;
1811:
1812: strcpy (out, in);
1813: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1814: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1815: if(strloc != NULL){
1816: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1817: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1818: /* strcpy (strloc, strloc +strlen(chain));*/
1819: }
1820: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1821: return out;
1822: }
1823:
1824:
1.145 brouard 1825: char *cutl(char *blocc, char *alocc, char *in, char occ)
1826: {
1.187 brouard 1827: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1828: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.310 brouard 1829: gives alocc="abcdef" and blocc="ghi2j".
1.145 brouard 1830: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1831: */
1.160 brouard 1832: char *s, *t;
1.145 brouard 1833: t=in;s=in;
1834: while ((*in != occ) && (*in != '\0')){
1835: *alocc++ = *in++;
1836: }
1837: if( *in == occ){
1838: *(alocc)='\0';
1839: s=++in;
1840: }
1841:
1842: if (s == t) {/* occ not found */
1843: *(alocc-(in-s))='\0';
1844: in=s;
1845: }
1846: while ( *in != '\0'){
1847: *blocc++ = *in++;
1848: }
1849:
1850: *blocc='\0';
1851: return t;
1852: }
1.137 brouard 1853: char *cutv(char *blocc, char *alocc, char *in, char occ)
1854: {
1.187 brouard 1855: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1856: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1857: gives blocc="abcdef2ghi" and alocc="j".
1858: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1859: */
1860: char *s, *t;
1861: t=in;s=in;
1862: while (*in != '\0'){
1863: while( *in == occ){
1864: *blocc++ = *in++;
1865: s=in;
1866: }
1867: *blocc++ = *in++;
1868: }
1869: if (s == t) /* occ not found */
1870: *(blocc-(in-s))='\0';
1871: else
1872: *(blocc-(in-s)-1)='\0';
1873: in=s;
1874: while ( *in != '\0'){
1875: *alocc++ = *in++;
1876: }
1877:
1878: *alocc='\0';
1879: return s;
1880: }
1881:
1.126 brouard 1882: int nbocc(char *s, char occ)
1883: {
1884: int i,j=0;
1885: int lg=20;
1886: i=0;
1887: lg=strlen(s);
1888: for(i=0; i<= lg; i++) {
1.234 brouard 1889: if (s[i] == occ ) j++;
1.126 brouard 1890: }
1891: return j;
1892: }
1893:
1.137 brouard 1894: /* void cutv(char *u,char *v, char*t, char occ) */
1895: /* { */
1896: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1897: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1898: /* gives u="abcdef2ghi" and v="j" *\/ */
1899: /* int i,lg,j,p=0; */
1900: /* i=0; */
1901: /* lg=strlen(t); */
1902: /* for(j=0; j<=lg-1; j++) { */
1903: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1904: /* } */
1.126 brouard 1905:
1.137 brouard 1906: /* for(j=0; j<p; j++) { */
1907: /* (u[j] = t[j]); */
1908: /* } */
1909: /* u[p]='\0'; */
1.126 brouard 1910:
1.137 brouard 1911: /* for(j=0; j<= lg; j++) { */
1912: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1913: /* } */
1914: /* } */
1.126 brouard 1915:
1.160 brouard 1916: #ifdef _WIN32
1917: char * strsep(char **pp, const char *delim)
1918: {
1919: char *p, *q;
1920:
1921: if ((p = *pp) == NULL)
1922: return 0;
1923: if ((q = strpbrk (p, delim)) != NULL)
1924: {
1925: *pp = q + 1;
1926: *q = '\0';
1927: }
1928: else
1929: *pp = 0;
1930: return p;
1931: }
1932: #endif
1933:
1.126 brouard 1934: /********************** nrerror ********************/
1935:
1936: void nrerror(char error_text[])
1937: {
1938: fprintf(stderr,"ERREUR ...\n");
1939: fprintf(stderr,"%s\n",error_text);
1940: exit(EXIT_FAILURE);
1941: }
1942: /*********************** vector *******************/
1943: double *vector(int nl, int nh)
1944: {
1945: double *v;
1946: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1947: if (!v) nrerror("allocation failure in vector");
1948: return v-nl+NR_END;
1949: }
1950:
1951: /************************ free vector ******************/
1952: void free_vector(double*v, int nl, int nh)
1953: {
1954: free((FREE_ARG)(v+nl-NR_END));
1955: }
1956:
1957: /************************ivector *******************************/
1958: int *ivector(long nl,long nh)
1959: {
1960: int *v;
1961: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1962: if (!v) nrerror("allocation failure in ivector");
1963: return v-nl+NR_END;
1964: }
1965:
1966: /******************free ivector **************************/
1967: void free_ivector(int *v, long nl, long nh)
1968: {
1969: free((FREE_ARG)(v+nl-NR_END));
1970: }
1971:
1972: /************************lvector *******************************/
1973: long *lvector(long nl,long nh)
1974: {
1975: long *v;
1976: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1977: if (!v) nrerror("allocation failure in ivector");
1978: return v-nl+NR_END;
1979: }
1980:
1981: /******************free lvector **************************/
1982: void free_lvector(long *v, long nl, long nh)
1983: {
1984: free((FREE_ARG)(v+nl-NR_END));
1985: }
1986:
1987: /******************* imatrix *******************************/
1988: int **imatrix(long nrl, long nrh, long ncl, long nch)
1989: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1990: {
1991: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1992: int **m;
1993:
1994: /* allocate pointers to rows */
1995: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1996: if (!m) nrerror("allocation failure 1 in matrix()");
1997: m += NR_END;
1998: m -= nrl;
1999:
2000:
2001: /* allocate rows and set pointers to them */
2002: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
2003: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2004: m[nrl] += NR_END;
2005: m[nrl] -= ncl;
2006:
2007: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
2008:
2009: /* return pointer to array of pointers to rows */
2010: return m;
2011: }
2012:
2013: /****************** free_imatrix *************************/
2014: void free_imatrix(m,nrl,nrh,ncl,nch)
2015: int **m;
2016: long nch,ncl,nrh,nrl;
2017: /* free an int matrix allocated by imatrix() */
2018: {
2019: free((FREE_ARG) (m[nrl]+ncl-NR_END));
2020: free((FREE_ARG) (m+nrl-NR_END));
2021: }
2022:
2023: /******************* matrix *******************************/
2024: double **matrix(long nrl, long nrh, long ncl, long nch)
2025: {
2026: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
2027: double **m;
2028:
2029: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
2030: if (!m) nrerror("allocation failure 1 in matrix()");
2031: m += NR_END;
2032: m -= nrl;
2033:
2034: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
2035: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2036: m[nrl] += NR_END;
2037: m[nrl] -= ncl;
2038:
2039: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2040: return m;
1.145 brouard 2041: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
2042: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
2043: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 2044: */
2045: }
2046:
2047: /*************************free matrix ************************/
2048: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
2049: {
2050: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2051: free((FREE_ARG)(m+nrl-NR_END));
2052: }
2053:
2054: /******************* ma3x *******************************/
2055: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
2056: {
2057: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
2058: double ***m;
2059:
2060: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
2061: if (!m) nrerror("allocation failure 1 in matrix()");
2062: m += NR_END;
2063: m -= nrl;
2064:
2065: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
2066: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2067: m[nrl] += NR_END;
2068: m[nrl] -= ncl;
2069:
2070: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2071:
2072: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
2073: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
2074: m[nrl][ncl] += NR_END;
2075: m[nrl][ncl] -= nll;
2076: for (j=ncl+1; j<=nch; j++)
2077: m[nrl][j]=m[nrl][j-1]+nlay;
2078:
2079: for (i=nrl+1; i<=nrh; i++) {
2080: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
2081: for (j=ncl+1; j<=nch; j++)
2082: m[i][j]=m[i][j-1]+nlay;
2083: }
2084: return m;
2085: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
2086: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
2087: */
2088: }
2089:
2090: /*************************free ma3x ************************/
2091: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
2092: {
2093: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
2094: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2095: free((FREE_ARG)(m+nrl-NR_END));
2096: }
2097:
2098: /*************** function subdirf ***********/
2099: char *subdirf(char fileres[])
2100: {
2101: /* Caution optionfilefiname is hidden */
2102: strcpy(tmpout,optionfilefiname);
2103: strcat(tmpout,"/"); /* Add to the right */
2104: strcat(tmpout,fileres);
2105: return tmpout;
2106: }
2107:
2108: /*************** function subdirf2 ***********/
2109: char *subdirf2(char fileres[], char *preop)
2110: {
1.314 brouard 2111: /* Example subdirf2(optionfilefiname,"FB_") with optionfilefiname="texte", result="texte/FB_texte"
2112: Errors in subdirf, 2, 3 while printing tmpout is
1.315 brouard 2113: rewritten within the same printf. Workaround: many printfs */
1.126 brouard 2114: /* Caution optionfilefiname is hidden */
2115: strcpy(tmpout,optionfilefiname);
2116: strcat(tmpout,"/");
2117: strcat(tmpout,preop);
2118: strcat(tmpout,fileres);
2119: return tmpout;
2120: }
2121:
2122: /*************** function subdirf3 ***********/
2123: char *subdirf3(char fileres[], char *preop, char *preop2)
2124: {
2125:
2126: /* Caution optionfilefiname is hidden */
2127: strcpy(tmpout,optionfilefiname);
2128: strcat(tmpout,"/");
2129: strcat(tmpout,preop);
2130: strcat(tmpout,preop2);
2131: strcat(tmpout,fileres);
2132: return tmpout;
2133: }
1.213 brouard 2134:
2135: /*************** function subdirfext ***********/
2136: char *subdirfext(char fileres[], char *preop, char *postop)
2137: {
2138:
2139: strcpy(tmpout,preop);
2140: strcat(tmpout,fileres);
2141: strcat(tmpout,postop);
2142: return tmpout;
2143: }
1.126 brouard 2144:
1.213 brouard 2145: /*************** function subdirfext3 ***********/
2146: char *subdirfext3(char fileres[], char *preop, char *postop)
2147: {
2148:
2149: /* Caution optionfilefiname is hidden */
2150: strcpy(tmpout,optionfilefiname);
2151: strcat(tmpout,"/");
2152: strcat(tmpout,preop);
2153: strcat(tmpout,fileres);
2154: strcat(tmpout,postop);
2155: return tmpout;
2156: }
2157:
1.162 brouard 2158: char *asc_diff_time(long time_sec, char ascdiff[])
2159: {
2160: long sec_left, days, hours, minutes;
2161: days = (time_sec) / (60*60*24);
2162: sec_left = (time_sec) % (60*60*24);
2163: hours = (sec_left) / (60*60) ;
2164: sec_left = (sec_left) %(60*60);
2165: minutes = (sec_left) /60;
2166: sec_left = (sec_left) % (60);
2167: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
2168: return ascdiff;
2169: }
2170:
1.126 brouard 2171: /***************** f1dim *************************/
2172: extern int ncom;
2173: extern double *pcom,*xicom;
2174: extern double (*nrfunc)(double []);
2175:
2176: double f1dim(double x)
2177: {
2178: int j;
2179: double f;
2180: double *xt;
2181:
2182: xt=vector(1,ncom);
2183: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
2184: f=(*nrfunc)(xt);
2185: free_vector(xt,1,ncom);
2186: return f;
2187: }
2188:
2189: /*****************brent *************************/
2190: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 2191: {
2192: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
2193: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
2194: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
2195: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
2196: * returned function value.
2197: */
1.126 brouard 2198: int iter;
2199: double a,b,d,etemp;
1.159 brouard 2200: double fu=0,fv,fw,fx;
1.164 brouard 2201: double ftemp=0.;
1.126 brouard 2202: double p,q,r,tol1,tol2,u,v,w,x,xm;
2203: double e=0.0;
2204:
2205: a=(ax < cx ? ax : cx);
2206: b=(ax > cx ? ax : cx);
2207: x=w=v=bx;
2208: fw=fv=fx=(*f)(x);
2209: for (iter=1;iter<=ITMAX;iter++) {
2210: xm=0.5*(a+b);
2211: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
2212: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
2213: printf(".");fflush(stdout);
2214: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 2215: #ifdef DEBUGBRENT
1.126 brouard 2216: 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);
2217: 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);
2218: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
2219: #endif
2220: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
2221: *xmin=x;
2222: return fx;
2223: }
2224: ftemp=fu;
2225: if (fabs(e) > tol1) {
2226: r=(x-w)*(fx-fv);
2227: q=(x-v)*(fx-fw);
2228: p=(x-v)*q-(x-w)*r;
2229: q=2.0*(q-r);
2230: if (q > 0.0) p = -p;
2231: q=fabs(q);
2232: etemp=e;
2233: e=d;
2234: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 2235: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 2236: else {
1.224 brouard 2237: d=p/q;
2238: u=x+d;
2239: if (u-a < tol2 || b-u < tol2)
2240: d=SIGN(tol1,xm-x);
1.126 brouard 2241: }
2242: } else {
2243: d=CGOLD*(e=(x >= xm ? a-x : b-x));
2244: }
2245: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
2246: fu=(*f)(u);
2247: if (fu <= fx) {
2248: if (u >= x) a=x; else b=x;
2249: SHFT(v,w,x,u)
1.183 brouard 2250: SHFT(fv,fw,fx,fu)
2251: } else {
2252: if (u < x) a=u; else b=u;
2253: if (fu <= fw || w == x) {
1.224 brouard 2254: v=w;
2255: w=u;
2256: fv=fw;
2257: fw=fu;
1.183 brouard 2258: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 2259: v=u;
2260: fv=fu;
1.183 brouard 2261: }
2262: }
1.126 brouard 2263: }
2264: nrerror("Too many iterations in brent");
2265: *xmin=x;
2266: return fx;
2267: }
2268:
2269: /****************** mnbrak ***********************/
2270:
2271: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
2272: double (*func)(double))
1.183 brouard 2273: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
2274: the downhill direction (defined by the function as evaluated at the initial points) and returns
2275: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
2276: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
2277: */
1.126 brouard 2278: double ulim,u,r,q, dum;
2279: double fu;
1.187 brouard 2280:
2281: double scale=10.;
2282: int iterscale=0;
2283:
2284: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
2285: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
2286:
2287:
2288: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
2289: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
2290: /* *bx = *ax - (*ax - *bx)/scale; */
2291: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
2292: /* } */
2293:
1.126 brouard 2294: if (*fb > *fa) {
2295: SHFT(dum,*ax,*bx,dum)
1.183 brouard 2296: SHFT(dum,*fb,*fa,dum)
2297: }
1.126 brouard 2298: *cx=(*bx)+GOLD*(*bx-*ax);
2299: *fc=(*func)(*cx);
1.183 brouard 2300: #ifdef DEBUG
1.224 brouard 2301: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
2302: 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 2303: #endif
1.224 brouard 2304: 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 2305: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 2306: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 2307: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 2308: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
2309: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
2310: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 2311: fu=(*func)(u);
1.163 brouard 2312: #ifdef DEBUG
2313: /* f(x)=A(x-u)**2+f(u) */
2314: double A, fparabu;
2315: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2316: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 2317: 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);
2318: 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 2319: /* And thus,it can be that fu > *fc even if fparabu < *fc */
2320: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
2321: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
2322: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 2323: #endif
1.184 brouard 2324: #ifdef MNBRAKORIGINAL
1.183 brouard 2325: #else
1.191 brouard 2326: /* if (fu > *fc) { */
2327: /* #ifdef DEBUG */
2328: /* printf("mnbrak4 fu > fc \n"); */
2329: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
2330: /* #endif */
2331: /* /\* 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 *\\/ *\/ */
2332: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2333: /* dum=u; /\* Shifting c and u *\/ */
2334: /* u = *cx; */
2335: /* *cx = dum; */
2336: /* dum = fu; */
2337: /* fu = *fc; */
2338: /* *fc =dum; */
2339: /* } else { /\* end *\/ */
2340: /* #ifdef DEBUG */
2341: /* printf("mnbrak3 fu < fc \n"); */
2342: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2343: /* #endif */
2344: /* dum=u; /\* Shifting c and u *\/ */
2345: /* u = *cx; */
2346: /* *cx = dum; */
2347: /* dum = fu; */
2348: /* fu = *fc; */
2349: /* *fc =dum; */
2350: /* } */
1.224 brouard 2351: #ifdef DEBUGMNBRAK
2352: double A, fparabu;
2353: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2354: fparabu= *fa - A*(*ax-u)*(*ax-u);
2355: 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);
2356: 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 2357: #endif
1.191 brouard 2358: dum=u; /* Shifting c and u */
2359: u = *cx;
2360: *cx = dum;
2361: dum = fu;
2362: fu = *fc;
2363: *fc =dum;
1.183 brouard 2364: #endif
1.162 brouard 2365: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2366: #ifdef DEBUG
1.224 brouard 2367: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2368: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2369: #endif
1.126 brouard 2370: fu=(*func)(u);
2371: if (fu < *fc) {
1.183 brouard 2372: #ifdef DEBUG
1.224 brouard 2373: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2374: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2375: #endif
2376: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2377: SHFT(*fb,*fc,fu,(*func)(u))
2378: #ifdef DEBUG
2379: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2380: #endif
2381: }
1.162 brouard 2382: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2383: #ifdef DEBUG
1.224 brouard 2384: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2385: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2386: #endif
1.126 brouard 2387: u=ulim;
2388: fu=(*func)(u);
1.183 brouard 2389: } else { /* u could be left to b (if r > q parabola has a maximum) */
2390: #ifdef DEBUG
1.224 brouard 2391: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2392: 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 2393: #endif
1.126 brouard 2394: u=(*cx)+GOLD*(*cx-*bx);
2395: fu=(*func)(u);
1.224 brouard 2396: #ifdef DEBUG
2397: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2398: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2399: #endif
1.183 brouard 2400: } /* end tests */
1.126 brouard 2401: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2402: SHFT(*fa,*fb,*fc,fu)
2403: #ifdef DEBUG
1.224 brouard 2404: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2405: 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 2406: #endif
2407: } /* 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 2408: }
2409:
2410: /*************** linmin ************************/
1.162 brouard 2411: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2412: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2413: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2414: the value of func at the returned location p . This is actually all accomplished by calling the
2415: routines mnbrak and brent .*/
1.126 brouard 2416: int ncom;
2417: double *pcom,*xicom;
2418: double (*nrfunc)(double []);
2419:
1.224 brouard 2420: #ifdef LINMINORIGINAL
1.126 brouard 2421: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2422: #else
2423: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2424: #endif
1.126 brouard 2425: {
2426: double brent(double ax, double bx, double cx,
2427: double (*f)(double), double tol, double *xmin);
2428: double f1dim(double x);
2429: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2430: double *fc, double (*func)(double));
2431: int j;
2432: double xx,xmin,bx,ax;
2433: double fx,fb,fa;
1.187 brouard 2434:
1.203 brouard 2435: #ifdef LINMINORIGINAL
2436: #else
2437: double scale=10., axs, xxs; /* Scale added for infinity */
2438: #endif
2439:
1.126 brouard 2440: ncom=n;
2441: pcom=vector(1,n);
2442: xicom=vector(1,n);
2443: nrfunc=func;
2444: for (j=1;j<=n;j++) {
2445: pcom[j]=p[j];
1.202 brouard 2446: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2447: }
1.187 brouard 2448:
1.203 brouard 2449: #ifdef LINMINORIGINAL
2450: xx=1.;
2451: #else
2452: axs=0.0;
2453: xxs=1.;
2454: do{
2455: xx= xxs;
2456: #endif
1.187 brouard 2457: ax=0.;
2458: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2459: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2460: /* 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)) */
2461: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2462: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2463: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2464: /* 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 2465: #ifdef LINMINORIGINAL
2466: #else
2467: if (fx != fx){
1.224 brouard 2468: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2469: printf("|");
2470: fprintf(ficlog,"|");
1.203 brouard 2471: #ifdef DEBUGLINMIN
1.224 brouard 2472: 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 2473: #endif
2474: }
1.224 brouard 2475: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2476: #endif
2477:
1.191 brouard 2478: #ifdef DEBUGLINMIN
2479: 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 2480: 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 2481: #endif
1.224 brouard 2482: #ifdef LINMINORIGINAL
2483: #else
1.317 brouard 2484: if(fb == fx){ /* Flat function in the direction */
2485: xmin=xx;
1.224 brouard 2486: *flat=1;
1.317 brouard 2487: }else{
1.224 brouard 2488: *flat=0;
2489: #endif
2490: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2491: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2492: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2493: /* fmin = f(p[j] + xmin * xi[j]) */
2494: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2495: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2496: #ifdef DEBUG
1.224 brouard 2497: 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);
2498: 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);
2499: #endif
2500: #ifdef LINMINORIGINAL
2501: #else
2502: }
1.126 brouard 2503: #endif
1.191 brouard 2504: #ifdef DEBUGLINMIN
2505: printf("linmin end ");
1.202 brouard 2506: fprintf(ficlog,"linmin end ");
1.191 brouard 2507: #endif
1.126 brouard 2508: for (j=1;j<=n;j++) {
1.203 brouard 2509: #ifdef LINMINORIGINAL
2510: xi[j] *= xmin;
2511: #else
2512: #ifdef DEBUGLINMIN
2513: if(xxs <1.0)
2514: printf(" before xi[%d]=%12.8f", j,xi[j]);
2515: #endif
2516: 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) */
2517: #ifdef DEBUGLINMIN
2518: if(xxs <1.0)
2519: 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 );
2520: #endif
2521: #endif
1.187 brouard 2522: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2523: }
1.191 brouard 2524: #ifdef DEBUGLINMIN
1.203 brouard 2525: printf("\n");
1.191 brouard 2526: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2527: 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 2528: for (j=1;j<=n;j++) {
1.202 brouard 2529: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2530: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2531: if(j % ncovmodel == 0){
1.191 brouard 2532: printf("\n");
1.202 brouard 2533: fprintf(ficlog,"\n");
2534: }
1.191 brouard 2535: }
1.203 brouard 2536: #else
1.191 brouard 2537: #endif
1.126 brouard 2538: free_vector(xicom,1,n);
2539: free_vector(pcom,1,n);
2540: }
2541:
2542:
2543: /*************** powell ************************/
1.162 brouard 2544: /*
1.317 brouard 2545: Minimization of a function func of n variables. Input consists in an initial starting point
2546: p[1..n] ; an initial matrix xi[1..n][1..n] whose columns contain the initial set of di-
2547: rections (usually the n unit vectors); and ftol, the fractional tolerance in the function value
2548: such that failure to decrease by more than this amount in one iteration signals doneness. On
1.162 brouard 2549: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2550: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2551: */
1.224 brouard 2552: #ifdef LINMINORIGINAL
2553: #else
2554: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2555: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2556: #endif
1.126 brouard 2557: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2558: double (*func)(double []))
2559: {
1.224 brouard 2560: #ifdef LINMINORIGINAL
2561: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2562: double (*func)(double []));
1.224 brouard 2563: #else
1.241 brouard 2564: void linmin(double p[], double xi[], int n, double *fret,
2565: double (*func)(double []),int *flat);
1.224 brouard 2566: #endif
1.239 brouard 2567: int i,ibig,j,jk,k;
1.126 brouard 2568: double del,t,*pt,*ptt,*xit;
1.181 brouard 2569: double directest;
1.126 brouard 2570: double fp,fptt;
2571: double *xits;
2572: int niterf, itmp;
2573:
2574: pt=vector(1,n);
2575: ptt=vector(1,n);
2576: xit=vector(1,n);
2577: xits=vector(1,n);
2578: *fret=(*func)(p);
2579: for (j=1;j<=n;j++) pt[j]=p[j];
1.338 brouard 2580: rcurr_time = time(NULL);
2581: fp=(*fret); /* Initialisation */
1.126 brouard 2582: for (*iter=1;;++(*iter)) {
2583: ibig=0;
2584: del=0.0;
1.157 brouard 2585: rlast_time=rcurr_time;
2586: /* (void) gettimeofday(&curr_time,&tzp); */
2587: rcurr_time = time(NULL);
2588: curr_time = *localtime(&rcurr_time);
1.337 brouard 2589: /* 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); */
2590: /* 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); */
2591: printf("\nPowell iter=%d -2*LL=%.12f gain=%.3lg %ld sec. %ld sec.",*iter,*fret,fp-*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
2592: fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f gain=%.3lg %ld sec. %ld sec.",*iter,*fret,fp-*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
1.157 brouard 2593: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.324 brouard 2594: fp=(*fret); /* From former iteration or initial value */
1.192 brouard 2595: for (i=1;i<=n;i++) {
1.126 brouard 2596: fprintf(ficrespow," %.12lf", p[i]);
2597: }
1.239 brouard 2598: fprintf(ficrespow,"\n");fflush(ficrespow);
2599: printf("\n#model= 1 + age ");
2600: fprintf(ficlog,"\n#model= 1 + age ");
2601: if(nagesqr==1){
1.241 brouard 2602: printf(" + age*age ");
2603: fprintf(ficlog," + age*age ");
1.239 brouard 2604: }
2605: for(j=1;j <=ncovmodel-2;j++){
2606: if(Typevar[j]==0) {
2607: printf(" + V%d ",Tvar[j]);
2608: fprintf(ficlog," + V%d ",Tvar[j]);
2609: }else if(Typevar[j]==1) {
2610: printf(" + V%d*age ",Tvar[j]);
2611: fprintf(ficlog," + V%d*age ",Tvar[j]);
2612: }else if(Typevar[j]==2) {
2613: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2614: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2615: }
2616: }
1.126 brouard 2617: printf("\n");
1.239 brouard 2618: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2619: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2620: fprintf(ficlog,"\n");
1.239 brouard 2621: for(i=1,jk=1; i <=nlstate; i++){
2622: for(k=1; k <=(nlstate+ndeath); k++){
2623: if (k != i) {
2624: printf("%d%d ",i,k);
2625: fprintf(ficlog,"%d%d ",i,k);
2626: for(j=1; j <=ncovmodel; j++){
2627: printf("%12.7f ",p[jk]);
2628: fprintf(ficlog,"%12.7f ",p[jk]);
2629: jk++;
2630: }
2631: printf("\n");
2632: fprintf(ficlog,"\n");
2633: }
2634: }
2635: }
1.241 brouard 2636: if(*iter <=3 && *iter >1){
1.157 brouard 2637: tml = *localtime(&rcurr_time);
2638: strcpy(strcurr,asctime(&tml));
2639: rforecast_time=rcurr_time;
1.126 brouard 2640: itmp = strlen(strcurr);
2641: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2642: strcurr[itmp-1]='\0';
1.162 brouard 2643: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2644: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2645: for(niterf=10;niterf<=30;niterf+=10){
1.241 brouard 2646: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2647: forecast_time = *localtime(&rforecast_time);
2648: strcpy(strfor,asctime(&forecast_time));
2649: itmp = strlen(strfor);
2650: if(strfor[itmp-1]=='\n')
2651: strfor[itmp-1]='\0';
2652: printf(" - if your program needs %d iterations to converge, convergence will be \n reached in %s i.e.\n on %s (current time is %s);\n",niterf, asc_diff_time(rforecast_time-rcurr_time,tmpout),strfor,strcurr);
2653: fprintf(ficlog," - if your program needs %d iterations to converge, convergence will be \n reached in %s i.e.\n on %s (current time is %s);\n",niterf, asc_diff_time(rforecast_time-rcurr_time,tmpout),strfor,strcurr);
1.126 brouard 2654: }
2655: }
1.187 brouard 2656: for (i=1;i<=n;i++) { /* For each direction i */
2657: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2658: fptt=(*fret);
2659: #ifdef DEBUG
1.203 brouard 2660: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2661: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2662: #endif
1.203 brouard 2663: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2664: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2665: #ifdef LINMINORIGINAL
1.188 brouard 2666: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2667: #else
2668: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2669: flatdir[i]=flat; /* Function is vanishing in that direction i */
2670: #endif
2671: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2672: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2673: /* because that direction will be replaced unless the gain del is small */
2674: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2675: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2676: /* with the new direction. */
2677: del=fabs(fptt-(*fret));
2678: ibig=i;
1.126 brouard 2679: }
2680: #ifdef DEBUG
2681: printf("%d %.12e",i,(*fret));
2682: fprintf(ficlog,"%d %.12e",i,(*fret));
2683: for (j=1;j<=n;j++) {
1.224 brouard 2684: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2685: printf(" x(%d)=%.12e",j,xit[j]);
2686: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2687: }
2688: for(j=1;j<=n;j++) {
1.225 brouard 2689: printf(" p(%d)=%.12e",j,p[j]);
2690: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2691: }
2692: printf("\n");
2693: fprintf(ficlog,"\n");
2694: #endif
1.187 brouard 2695: } /* end loop on each direction i */
2696: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2697: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2698: /* New value of last point Pn is not computed, P(n-1) */
1.319 brouard 2699: for(j=1;j<=n;j++) {
2700: if(flatdir[j] >0){
2701: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2702: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
1.302 brouard 2703: }
1.319 brouard 2704: /* printf("\n"); */
2705: /* fprintf(ficlog,"\n"); */
2706: }
1.243 brouard 2707: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2708: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2709: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2710: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2711: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2712: /* decreased of more than 3.84 */
2713: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2714: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2715: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2716:
1.188 brouard 2717: /* Starting the program with initial values given by a former maximization will simply change */
2718: /* the scales of the directions and the directions, because the are reset to canonical directions */
2719: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2720: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2721: #ifdef DEBUG
2722: int k[2],l;
2723: k[0]=1;
2724: k[1]=-1;
2725: printf("Max: %.12e",(*func)(p));
2726: fprintf(ficlog,"Max: %.12e",(*func)(p));
2727: for (j=1;j<=n;j++) {
2728: printf(" %.12e",p[j]);
2729: fprintf(ficlog," %.12e",p[j]);
2730: }
2731: printf("\n");
2732: fprintf(ficlog,"\n");
2733: for(l=0;l<=1;l++) {
2734: for (j=1;j<=n;j++) {
2735: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2736: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2737: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2738: }
2739: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2740: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2741: }
2742: #endif
2743:
2744: free_vector(xit,1,n);
2745: free_vector(xits,1,n);
2746: free_vector(ptt,1,n);
2747: free_vector(pt,1,n);
2748: return;
1.192 brouard 2749: } /* enough precision */
1.240 brouard 2750: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2751: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2752: ptt[j]=2.0*p[j]-pt[j];
2753: xit[j]=p[j]-pt[j];
2754: pt[j]=p[j];
2755: }
1.181 brouard 2756: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2757: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2758: if (*iter <=4) {
1.225 brouard 2759: #else
2760: #endif
1.224 brouard 2761: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2762: #else
1.161 brouard 2763: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2764: #endif
1.162 brouard 2765: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2766: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2767: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2768: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2769: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2770: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2771: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2772: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2773: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2774: /* Even if f3 <f1, directest can be negative and t >0 */
2775: /* mu² and del² are equal when f3=f1 */
2776: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2777: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2778: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2779: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2780: #ifdef NRCORIGINAL
2781: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2782: #else
2783: 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 2784: t= t- del*SQR(fp-fptt);
1.183 brouard 2785: #endif
1.202 brouard 2786: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2787: #ifdef DEBUG
1.181 brouard 2788: 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);
2789: 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 2790: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2791: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2792: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2793: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2794: 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);
2795: 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);
2796: #endif
1.183 brouard 2797: #ifdef POWELLORIGINAL
2798: if (t < 0.0) { /* Then we use it for new direction */
2799: #else
1.182 brouard 2800: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2801: 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 2802: 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 2803: 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 2804: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2805: }
1.181 brouard 2806: if (directest < 0.0) { /* Then we use it for new direction */
2807: #endif
1.191 brouard 2808: #ifdef DEBUGLINMIN
1.234 brouard 2809: printf("Before linmin in direction P%d-P0\n",n);
2810: for (j=1;j<=n;j++) {
2811: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2812: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2813: if(j % ncovmodel == 0){
2814: printf("\n");
2815: fprintf(ficlog,"\n");
2816: }
2817: }
1.224 brouard 2818: #endif
2819: #ifdef LINMINORIGINAL
1.234 brouard 2820: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2821: #else
1.234 brouard 2822: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2823: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2824: #endif
1.234 brouard 2825:
1.191 brouard 2826: #ifdef DEBUGLINMIN
1.234 brouard 2827: for (j=1;j<=n;j++) {
2828: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2829: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2830: if(j % ncovmodel == 0){
2831: printf("\n");
2832: fprintf(ficlog,"\n");
2833: }
2834: }
1.224 brouard 2835: #endif
1.234 brouard 2836: for (j=1;j<=n;j++) {
2837: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2838: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2839: }
1.224 brouard 2840: #ifdef LINMINORIGINAL
2841: #else
1.234 brouard 2842: for (j=1, flatd=0;j<=n;j++) {
2843: if(flatdir[j]>0)
2844: flatd++;
2845: }
2846: if(flatd >0){
1.255 brouard 2847: printf("%d flat directions: ",flatd);
2848: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2849: for (j=1;j<=n;j++) {
2850: if(flatdir[j]>0){
2851: printf("%d ",j);
2852: fprintf(ficlog,"%d ",j);
2853: }
2854: }
2855: printf("\n");
2856: fprintf(ficlog,"\n");
1.319 brouard 2857: #ifdef FLATSUP
2858: free_vector(xit,1,n);
2859: free_vector(xits,1,n);
2860: free_vector(ptt,1,n);
2861: free_vector(pt,1,n);
2862: return;
2863: #endif
1.234 brouard 2864: }
1.191 brouard 2865: #endif
1.234 brouard 2866: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2867: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2868:
1.126 brouard 2869: #ifdef DEBUG
1.234 brouard 2870: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2871: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2872: for(j=1;j<=n;j++){
2873: printf(" %lf",xit[j]);
2874: fprintf(ficlog," %lf",xit[j]);
2875: }
2876: printf("\n");
2877: fprintf(ficlog,"\n");
1.126 brouard 2878: #endif
1.192 brouard 2879: } /* end of t or directest negative */
1.224 brouard 2880: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2881: #else
1.234 brouard 2882: } /* end if (fptt < fp) */
1.192 brouard 2883: #endif
1.225 brouard 2884: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2885: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2886: #else
1.224 brouard 2887: #endif
1.234 brouard 2888: } /* loop iteration */
1.126 brouard 2889: }
1.234 brouard 2890:
1.126 brouard 2891: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2892:
1.235 brouard 2893: 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 2894: {
1.338 brouard 2895: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij . Nicely done
1.279 brouard 2896: * (and selected quantitative values in nres)
2897: * by left multiplying the unit
2898: * matrix by transitions matrix until convergence is reached with precision ftolpl
2899: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2900: * Wx is row vector: population in state 1, population in state 2, population dead
2901: * or prevalence in state 1, prevalence in state 2, 0
2902: * newm is the matrix after multiplications, its rows are identical at a factor.
2903: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2904: * Output is prlim.
2905: * Initial matrix pimij
2906: */
1.206 brouard 2907: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2908: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2909: /* 0, 0 , 1} */
2910: /*
2911: * and after some iteration: */
2912: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2913: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2914: /* 0, 0 , 1} */
2915: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2916: /* {0.51571254859325999, 0.4842874514067399, */
2917: /* 0.51326036147820708, 0.48673963852179264} */
2918: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2919:
1.332 brouard 2920: int i, ii,j,k, k1;
1.209 brouard 2921: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2922: /* double **matprod2(); */ /* test */
1.218 brouard 2923: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2924: double **newm;
1.209 brouard 2925: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2926: int ncvloop=0;
1.288 brouard 2927: int first=0;
1.169 brouard 2928:
1.209 brouard 2929: min=vector(1,nlstate);
2930: max=vector(1,nlstate);
2931: meandiff=vector(1,nlstate);
2932:
1.218 brouard 2933: /* Starting with matrix unity */
1.126 brouard 2934: for (ii=1;ii<=nlstate+ndeath;ii++)
2935: for (j=1;j<=nlstate+ndeath;j++){
2936: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2937: }
1.169 brouard 2938:
2939: cov[1]=1.;
2940:
2941: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2942: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2943: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2944: ncvloop++;
1.126 brouard 2945: newm=savm;
2946: /* Covariates have to be included here again */
1.138 brouard 2947: cov[2]=agefin;
1.319 brouard 2948: if(nagesqr==1){
2949: cov[3]= agefin*agefin;
2950: }
1.332 brouard 2951: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
2952: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
2953: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
2954: if(Typevar[k1]==1){ /* A product with age */
2955: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
2956: }else{
2957: cov[2+nagesqr+k1]=precov[nres][k1];
2958: }
2959: }/* End of loop on model equation */
2960:
2961: /* Start of old code (replaced by a loop on position in the model equation */
2962: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only of the model *\/ */
2963: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
2964: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; *\/ */
2965: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TnsdVar[TvarsD[k]])]; */
2966: /* /\* model = 1 +age + V1*V3 + age*V1 + V2 + V1 + age*V2 + V3 + V3*age + V1*V2 */
2967: /* * k 1 2 3 4 5 6 7 8 */
2968: /* *cov[] 1 2 3 4 5 6 7 8 9 10 */
2969: /* *TypeVar[k] 2 1 0 0 1 0 1 2 */
2970: /* *Dummy[k] 0 2 0 0 2 0 2 0 */
2971: /* *Tvar[k] 4 1 2 1 2 3 3 5 */
2972: /* *nsd=3 (1) (2) (3) */
2973: /* *TvarsD[nsd] [1]=2 1 3 */
2974: /* *TnsdVar [2]=2 [1]=1 [3]=3 */
2975: /* *TvarsDind[nsd](=k) [1]=3 [2]=4 [3]=6 */
2976: /* *Tage[] [1]=1 [2]=2 [3]=3 */
2977: /* *Tvard[] [1][1]=1 [2][1]=1 */
2978: /* * [1][2]=3 [2][2]=2 */
2979: /* *Tprod[](=k) [1]=1 [2]=8 */
2980: /* *TvarsDp(=Tvar) [1]=1 [2]=2 [3]=3 [4]=5 */
2981: /* *TvarD (=k) [1]=1 [2]=3 [3]=4 [3]=6 [4]=6 */
2982: /* *TvarsDpType */
2983: /* *si model= 1 + age + V3 + V2*age + V2 + V3*age */
2984: /* * nsd=1 (1) (2) */
2985: /* *TvarsD[nsd] 3 2 */
2986: /* *TnsdVar (3)=1 (2)=2 */
2987: /* *TvarsDind[nsd](=k) [1]=1 [2]=3 */
2988: /* *Tage[] [1]=2 [2]= 3 */
2989: /* *\/ */
2990: /* /\* cov[++k1]=nbcode[TvarsD[k]][codtabm(ij,k)]; *\/ */
2991: /* /\* 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)); *\/ */
2992: /* } */
2993: /* for (k=1; k<=nsq;k++) { /\* For single quantitative varying covariates only of the model *\/ */
2994: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
2995: /* /\* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline *\/ */
2996: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
2997: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][resultmodel[nres][k1]] */
2998: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
2999: /* /\* 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]); *\/ */
3000: /* } */
3001: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
3002: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
3003: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3004: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
3005: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
3006: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3007: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
3008: /* } */
3009: /* /\* 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]); *\/ */
3010: /* } */
3011: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
3012: /* /\* 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]); *\/ */
3013: /* if(Dummy[Tvard[k][1]]==0){ */
3014: /* if(Dummy[Tvard[k][2]]==0){ */
3015: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3016: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3017: /* }else{ */
3018: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3019: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
3020: /* } */
3021: /* }else{ */
3022: /* if(Dummy[Tvard[k][2]]==0){ */
3023: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3024: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
3025: /* }else{ */
3026: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3027: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
3028: /* } */
3029: /* } */
3030: /* } /\* End product without age *\/ */
3031: /* ENd of old code */
1.138 brouard 3032: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
3033: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
3034: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 3035: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3036: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.319 brouard 3037: /* age and covariate values of ij are in 'cov' */
1.142 brouard 3038: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 3039:
1.126 brouard 3040: savm=oldm;
3041: oldm=newm;
1.209 brouard 3042:
3043: for(j=1; j<=nlstate; j++){
3044: max[j]=0.;
3045: min[j]=1.;
3046: }
3047: for(i=1;i<=nlstate;i++){
3048: sumnew=0;
3049: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
3050: for(j=1; j<=nlstate; j++){
3051: prlim[i][j]= newm[i][j]/(1-sumnew);
3052: max[j]=FMAX(max[j],prlim[i][j]);
3053: min[j]=FMIN(min[j],prlim[i][j]);
3054: }
3055: }
3056:
1.126 brouard 3057: maxmax=0.;
1.209 brouard 3058: for(j=1; j<=nlstate; j++){
3059: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
3060: maxmax=FMAX(maxmax,meandiff[j]);
3061: /* 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 3062: } /* j loop */
1.203 brouard 3063: *ncvyear= (int)age- (int)agefin;
1.208 brouard 3064: /* 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 3065: if(maxmax < ftolpl){
1.209 brouard 3066: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
3067: free_vector(min,1,nlstate);
3068: free_vector(max,1,nlstate);
3069: free_vector(meandiff,1,nlstate);
1.126 brouard 3070: return prlim;
3071: }
1.288 brouard 3072: } /* agefin loop */
1.208 brouard 3073: /* After some age loop it doesn't converge */
1.288 brouard 3074: if(!first){
3075: first=1;
3076: 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 3077: 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);
3078: }else if (first >=1 && first <10){
3079: 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);
3080: first++;
3081: }else if (first ==10){
3082: 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);
3083: 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");
3084: fprintf(ficlog,"Warning: the stable prevalence no convergence; too many cases, giving up noticing, even in log file\n");
3085: first++;
1.288 brouard 3086: }
3087:
1.209 brouard 3088: /* 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); */
3089: free_vector(min,1,nlstate);
3090: free_vector(max,1,nlstate);
3091: free_vector(meandiff,1,nlstate);
1.208 brouard 3092:
1.169 brouard 3093: return prlim; /* should not reach here */
1.126 brouard 3094: }
3095:
1.217 brouard 3096:
3097: /**** Back Prevalence limit (stable or period prevalence) ****************/
3098:
1.218 brouard 3099: /* 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) */
3100: /* 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 3101: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 3102: {
1.264 brouard 3103: /* 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 3104: matrix by transitions matrix until convergence is reached with precision ftolpl */
3105: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
3106: /* Wx is row vector: population in state 1, population in state 2, population dead */
3107: /* or prevalence in state 1, prevalence in state 2, 0 */
3108: /* newm is the matrix after multiplications, its rows are identical at a factor */
3109: /* Initial matrix pimij */
3110: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
3111: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
3112: /* 0, 0 , 1} */
3113: /*
3114: * and after some iteration: */
3115: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
3116: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
3117: /* 0, 0 , 1} */
3118: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
3119: /* {0.51571254859325999, 0.4842874514067399, */
3120: /* 0.51326036147820708, 0.48673963852179264} */
3121: /* If we start from prlim again, prlim tends to a constant matrix */
3122:
1.332 brouard 3123: int i, ii,j,k, k1;
1.247 brouard 3124: int first=0;
1.217 brouard 3125: double *min, *max, *meandiff, maxmax,sumnew=0.;
3126: /* double **matprod2(); */ /* test */
3127: double **out, cov[NCOVMAX+1], **bmij();
3128: double **newm;
1.218 brouard 3129: double **dnewm, **doldm, **dsavm; /* for use */
3130: double **oldm, **savm; /* for use */
3131:
1.217 brouard 3132: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
3133: int ncvloop=0;
3134:
3135: min=vector(1,nlstate);
3136: max=vector(1,nlstate);
3137: meandiff=vector(1,nlstate);
3138:
1.266 brouard 3139: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
3140: oldm=oldms; savm=savms;
3141:
3142: /* Starting with matrix unity */
3143: for (ii=1;ii<=nlstate+ndeath;ii++)
3144: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 3145: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3146: }
3147:
3148: cov[1]=1.;
3149:
3150: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3151: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 3152: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 3153: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
3154: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 3155: ncvloop++;
1.218 brouard 3156: newm=savm; /* oldm should be kept from previous iteration or unity at start */
3157: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 3158: /* Covariates have to be included here again */
3159: cov[2]=agefin;
1.319 brouard 3160: if(nagesqr==1){
1.217 brouard 3161: cov[3]= agefin*agefin;;
1.319 brouard 3162: }
1.332 brouard 3163: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
3164: if(Typevar[k1]==1){ /* A product with age */
3165: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.242 brouard 3166: }else{
1.332 brouard 3167: cov[2+nagesqr+k1]=precov[nres][k1];
1.242 brouard 3168: }
1.332 brouard 3169: }/* End of loop on model equation */
3170:
3171: /* Old code */
3172:
3173: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
3174: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
3175: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; */
3176: /* /\* 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)); *\/ */
3177: /* } */
3178: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
3179: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
3180: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
3181: /* /\* /\\* 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])]); *\\/ *\/ */
3182: /* /\* } *\/ */
3183: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
3184: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3185: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
3186: /* /\* 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]); *\/ */
3187: /* } */
3188: /* /\* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; *\/ */
3189: /* /\* for (k=1; k<=cptcovprod;k++) /\\* Useless *\\/ *\/ */
3190: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\\/ *\/ */
3191: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3192: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
3193: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age *\\/ ERROR ???*\/ */
3194: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
3195: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3196: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
3197: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3198: /* } */
3199: /* /\* 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]); *\/ */
3200: /* } */
3201: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
3202: /* /\* 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]); *\/ */
3203: /* if(Dummy[Tvard[k][1]]==0){ */
3204: /* if(Dummy[Tvard[k][2]]==0){ */
3205: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3206: /* }else{ */
3207: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3208: /* } */
3209: /* }else{ */
3210: /* if(Dummy[Tvard[k][2]]==0){ */
3211: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3212: /* }else{ */
3213: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3214: /* } */
3215: /* } */
3216: /* } */
1.217 brouard 3217:
3218: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
3219: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
3220: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
3221: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3222: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 3223: /* ij should be linked to the correct index of cov */
3224: /* age and covariate values ij are in 'cov', but we need to pass
3225: * ij for the observed prevalence at age and status and covariate
3226: * number: prevacurrent[(int)agefin][ii][ij]
3227: */
3228: /* 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 *\/ */
3229: /* 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 *\/ */
3230: 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 3231: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 3232: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
3233: /* for(i=1; i<=nlstate+ndeath; i++) { */
3234: /* printf("%d newm= ",i); */
3235: /* for(j=1;j<=nlstate+ndeath;j++) { */
3236: /* printf("%f ",newm[i][j]); */
3237: /* } */
3238: /* printf("oldm * "); */
3239: /* for(j=1;j<=nlstate+ndeath;j++) { */
3240: /* printf("%f ",oldm[i][j]); */
3241: /* } */
1.268 brouard 3242: /* printf(" bmmij "); */
1.266 brouard 3243: /* for(j=1;j<=nlstate+ndeath;j++) { */
3244: /* printf("%f ",pmmij[i][j]); */
3245: /* } */
3246: /* printf("\n"); */
3247: /* } */
3248: /* } */
1.217 brouard 3249: savm=oldm;
3250: oldm=newm;
1.266 brouard 3251:
1.217 brouard 3252: for(j=1; j<=nlstate; j++){
3253: max[j]=0.;
3254: min[j]=1.;
3255: }
3256: for(j=1; j<=nlstate; j++){
3257: for(i=1;i<=nlstate;i++){
1.234 brouard 3258: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
3259: bprlim[i][j]= newm[i][j];
3260: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
3261: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 3262: }
3263: }
1.218 brouard 3264:
1.217 brouard 3265: maxmax=0.;
3266: for(i=1; i<=nlstate; i++){
1.318 brouard 3267: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column, could be nan! */
1.217 brouard 3268: maxmax=FMAX(maxmax,meandiff[i]);
3269: /* 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 3270: } /* i loop */
1.217 brouard 3271: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 3272: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3273: if(maxmax < ftolpl){
1.220 brouard 3274: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3275: free_vector(min,1,nlstate);
3276: free_vector(max,1,nlstate);
3277: free_vector(meandiff,1,nlstate);
3278: return bprlim;
3279: }
1.288 brouard 3280: } /* agefin loop */
1.217 brouard 3281: /* After some age loop it doesn't converge */
1.288 brouard 3282: if(!first){
1.247 brouard 3283: first=1;
3284: 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\
3285: 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);
3286: }
3287: 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 3288: 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);
3289: /* 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); */
3290: free_vector(min,1,nlstate);
3291: free_vector(max,1,nlstate);
3292: free_vector(meandiff,1,nlstate);
3293:
3294: return bprlim; /* should not reach here */
3295: }
3296:
1.126 brouard 3297: /*************** transition probabilities ***************/
3298:
3299: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
3300: {
1.138 brouard 3301: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 3302: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 3303: model to the ncovmodel covariates (including constant and age).
3304: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3305: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3306: ncth covariate in the global vector x is given by the formula:
3307: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3308: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3309: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3310: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 3311: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 3312: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 3313: Sum on j ps[i][j] should equal to 1.
1.138 brouard 3314: */
3315: double s1, lnpijopii;
1.126 brouard 3316: /*double t34;*/
1.164 brouard 3317: int i,j, nc, ii, jj;
1.126 brouard 3318:
1.223 brouard 3319: for(i=1; i<= nlstate; i++){
3320: for(j=1; j<i;j++){
3321: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3322: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3323: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3324: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3325: }
3326: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3327: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3328: }
3329: for(j=i+1; j<=nlstate+ndeath;j++){
3330: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3331: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3332: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3333: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3334: }
3335: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3336: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3337: }
3338: }
1.218 brouard 3339:
1.223 brouard 3340: for(i=1; i<= nlstate; i++){
3341: s1=0;
3342: for(j=1; j<i; j++){
1.339 brouard 3343: /* printf("debug1 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 3344: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3345: }
3346: for(j=i+1; j<=nlstate+ndeath; j++){
1.339 brouard 3347: /* printf("debug2 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 3348: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3349: }
3350: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3351: ps[i][i]=1./(s1+1.);
3352: /* Computing other pijs */
3353: for(j=1; j<i; j++)
1.325 brouard 3354: ps[i][j]= exp(ps[i][j])*ps[i][i];/* Bug valgrind */
1.223 brouard 3355: for(j=i+1; j<=nlstate+ndeath; j++)
3356: ps[i][j]= exp(ps[i][j])*ps[i][i];
3357: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3358: } /* end i */
1.218 brouard 3359:
1.223 brouard 3360: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3361: for(jj=1; jj<= nlstate+ndeath; jj++){
3362: ps[ii][jj]=0;
3363: ps[ii][ii]=1;
3364: }
3365: }
1.294 brouard 3366:
3367:
1.223 brouard 3368: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3369: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3370: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3371: /* } */
3372: /* printf("\n "); */
3373: /* } */
3374: /* printf("\n ");printf("%lf ",cov[2]);*/
3375: /*
3376: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 3377: goto end;*/
1.266 brouard 3378: return ps; /* Pointer is unchanged since its call */
1.126 brouard 3379: }
3380:
1.218 brouard 3381: /*************** backward transition probabilities ***************/
3382:
3383: /* 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 ) */
3384: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
3385: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
3386: {
1.302 brouard 3387: /* 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 3388: * 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 3389: */
1.218 brouard 3390: int i, ii, j,k;
1.222 brouard 3391:
3392: double **out, **pmij();
3393: double sumnew=0.;
1.218 brouard 3394: double agefin;
1.292 brouard 3395: 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 3396: double **dnewm, **dsavm, **doldm;
3397: double **bbmij;
3398:
1.218 brouard 3399: doldm=ddoldms; /* global pointers */
1.222 brouard 3400: dnewm=ddnewms;
3401: dsavm=ddsavms;
1.318 brouard 3402:
3403: /* Debug */
3404: /* printf("Bmij ij=%d, cov[2}=%f\n", ij, cov[2]); */
1.222 brouard 3405: agefin=cov[2];
1.268 brouard 3406: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 3407: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 3408: the observed prevalence (with this covariate ij) at beginning of transition */
3409: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 3410:
3411: /* P_x */
1.325 brouard 3412: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm *//* Bug valgrind */
1.268 brouard 3413: /* outputs pmmij which is a stochastic matrix in row */
3414:
3415: /* Diag(w_x) */
1.292 brouard 3416: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 3417: sumnew=0.;
1.269 brouard 3418: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 3419: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.297 brouard 3420: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 3421: sumnew+=prevacurrent[(int)agefin][ii][ij];
3422: }
3423: if(sumnew >0.01){ /* At least some value in the prevalence */
3424: for (ii=1;ii<=nlstate+ndeath;ii++){
3425: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 3426: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 3427: }
3428: }else{
3429: for (ii=1;ii<=nlstate+ndeath;ii++){
3430: for (j=1;j<=nlstate+ndeath;j++)
3431: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
3432: }
3433: /* if(sumnew <0.9){ */
3434: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3435: /* } */
3436: }
3437: k3=0.0; /* We put the last diagonal to 0 */
3438: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3439: doldm[ii][ii]= k3;
3440: }
3441: /* End doldm, At the end doldm is diag[(w_i)] */
3442:
1.292 brouard 3443: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
3444: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 3445:
1.292 brouard 3446: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 3447: /* 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 3448: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3449: sumnew=0.;
1.222 brouard 3450: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3451: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3452: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3453: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3454: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3455: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3456: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3457: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3458: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3459: /* }else */
1.268 brouard 3460: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3461: } /*End ii */
3462: } /* 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 */
3463:
1.292 brouard 3464: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 3465: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3466: /* end bmij */
1.266 brouard 3467: return ps; /*pointer is unchanged */
1.218 brouard 3468: }
1.217 brouard 3469: /*************** transition probabilities ***************/
3470:
1.218 brouard 3471: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3472: {
3473: /* According to parameters values stored in x and the covariate's values stored in cov,
3474: computes the probability to be observed in state j being in state i by appying the
3475: model to the ncovmodel covariates (including constant and age).
3476: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3477: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3478: ncth covariate in the global vector x is given by the formula:
3479: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3480: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3481: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3482: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3483: Outputs ps[i][j] the probability to be observed in j being in j according to
3484: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3485: */
3486: double s1, lnpijopii;
3487: /*double t34;*/
3488: int i,j, nc, ii, jj;
3489:
1.234 brouard 3490: for(i=1; i<= nlstate; i++){
3491: for(j=1; j<i;j++){
3492: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3493: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3494: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3495: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3496: }
3497: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3498: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3499: }
3500: for(j=i+1; j<=nlstate+ndeath;j++){
3501: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3502: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3503: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3504: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3505: }
3506: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3507: }
3508: }
3509:
3510: for(i=1; i<= nlstate; i++){
3511: s1=0;
3512: for(j=1; j<i; j++){
3513: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3514: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3515: }
3516: for(j=i+1; j<=nlstate+ndeath; j++){
3517: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3518: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3519: }
3520: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3521: ps[i][i]=1./(s1+1.);
3522: /* Computing other pijs */
3523: for(j=1; j<i; j++)
3524: ps[i][j]= exp(ps[i][j])*ps[i][i];
3525: for(j=i+1; j<=nlstate+ndeath; j++)
3526: ps[i][j]= exp(ps[i][j])*ps[i][i];
3527: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3528: } /* end i */
3529:
3530: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3531: for(jj=1; jj<= nlstate+ndeath; jj++){
3532: ps[ii][jj]=0;
3533: ps[ii][ii]=1;
3534: }
3535: }
1.296 brouard 3536: /* Added for prevbcast */ /* Transposed matrix too */
1.234 brouard 3537: for(jj=1; jj<= nlstate+ndeath; jj++){
3538: s1=0.;
3539: for(ii=1; ii<= nlstate+ndeath; ii++){
3540: s1+=ps[ii][jj];
3541: }
3542: for(ii=1; ii<= nlstate; ii++){
3543: ps[ii][jj]=ps[ii][jj]/s1;
3544: }
3545: }
3546: /* Transposition */
3547: for(jj=1; jj<= nlstate+ndeath; jj++){
3548: for(ii=jj; ii<= nlstate+ndeath; ii++){
3549: s1=ps[ii][jj];
3550: ps[ii][jj]=ps[jj][ii];
3551: ps[jj][ii]=s1;
3552: }
3553: }
3554: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3555: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3556: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3557: /* } */
3558: /* printf("\n "); */
3559: /* } */
3560: /* printf("\n ");printf("%lf ",cov[2]);*/
3561: /*
3562: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3563: goto end;*/
3564: return ps;
1.217 brouard 3565: }
3566:
3567:
1.126 brouard 3568: /**************** Product of 2 matrices ******************/
3569:
1.145 brouard 3570: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3571: {
3572: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3573: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3574: /* in, b, out are matrice of pointers which should have been initialized
3575: before: only the contents of out is modified. The function returns
3576: a pointer to pointers identical to out */
1.145 brouard 3577: int i, j, k;
1.126 brouard 3578: for(i=nrl; i<= nrh; i++)
1.145 brouard 3579: for(k=ncolol; k<=ncoloh; k++){
3580: out[i][k]=0.;
3581: for(j=ncl; j<=nch; j++)
3582: out[i][k] +=in[i][j]*b[j][k];
3583: }
1.126 brouard 3584: return out;
3585: }
3586:
3587:
3588: /************* Higher Matrix Product ***************/
3589:
1.235 brouard 3590: 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 3591: {
1.336 brouard 3592: /* Already optimized with precov.
3593: 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 3594: 'nhstepm*hstepm*stepm' months (i.e. until
3595: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3596: nhstepm*hstepm matrices.
3597: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3598: (typically every 2 years instead of every month which is too big
3599: for the memory).
3600: Model is determined by parameters x and covariates have to be
3601: included manually here.
3602:
3603: */
3604:
1.330 brouard 3605: int i, j, d, h, k, k1;
1.131 brouard 3606: double **out, cov[NCOVMAX+1];
1.126 brouard 3607: double **newm;
1.187 brouard 3608: double agexact;
1.214 brouard 3609: double agebegin, ageend;
1.126 brouard 3610:
3611: /* Hstepm could be zero and should return the unit matrix */
3612: for (i=1;i<=nlstate+ndeath;i++)
3613: for (j=1;j<=nlstate+ndeath;j++){
3614: oldm[i][j]=(i==j ? 1.0 : 0.0);
3615: po[i][j][0]=(i==j ? 1.0 : 0.0);
3616: }
3617: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3618: for(h=1; h <=nhstepm; h++){
3619: for(d=1; d <=hstepm; d++){
3620: newm=savm;
3621: /* Covariates have to be included here again */
3622: cov[1]=1.;
1.214 brouard 3623: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3624: cov[2]=agexact;
1.319 brouard 3625: if(nagesqr==1){
1.227 brouard 3626: cov[3]= agexact*agexact;
1.319 brouard 3627: }
1.330 brouard 3628: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
3629: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
3630: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.332 brouard 3631: if(Typevar[k1]==1){ /* A product with age */
3632: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
3633: }else{
3634: cov[2+nagesqr+k1]=precov[nres][k1];
3635: }
3636: }/* End of loop on model equation */
3637: /* Old code */
3638: /* if( Dummy[k1]==0 && Typevar[k1]==0 ){ /\* Single dummy *\/ */
3639: /* /\* V(Tvarsel)=Tvalsel=Tresult[nres][pos](value); V(Tvresult[nres][pos] (variable): V(variable)=value) *\/ */
3640: /* /\* for (k=1; k<=nsd;k++) { /\\* For single dummy covariates only *\\/ *\/ */
3641: /* /\* /\\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\\/ *\/ */
3642: /* /\* codtabm(ij,k) (1 & (ij-1) >> (k-1))+1 *\/ */
3643: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3644: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3645: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
3646: /* /\* nsd 1 2 3 *\/ /\* Counting single dummies covar fixed or tv *\/ */
3647: /* /\*TvarsD[nsd] 4 3 1 *\/ /\* ID of single dummy cova fixed or timevary*\/ */
3648: /* /\*TvarsDind[k] 2 3 9 *\/ /\* position K of single dummy cova *\/ */
3649: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];or [codtabm(ij,TnsdVar[TvarsD[k]] *\/ */
3650: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
3651: /* /\* 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]])); *\/ */
3652: /* 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); */
3653: /* printf("hpxij new Dummy precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3654: /* }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /\* Single quantitative variables *\/ */
3655: /* /\* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline *\/ */
3656: /* cov[2+nagesqr+k1]=Tqresult[nres][resultmodel[nres][k1]]; */
3657: /* /\* for (k=1; k<=nsq;k++) { /\\* For single varying covariates only *\\/ *\/ */
3658: /* /\* /\\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\\/ *\/ */
3659: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
3660: /* 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]]); */
3661: /* printf("hpxij new Quanti precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3662: /* }else if( Dummy[k1]==2 ){ /\* For dummy with age product *\/ */
3663: /* /\* Tvar[k1] Variable in the age product age*V1 is 1 *\/ */
3664: /* /\* [Tinvresult[nres][V1] is its value in the resultline nres *\/ */
3665: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvar[k1]]*cov[2]; */
3666: /* 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]); */
3667: /* printf("hpxij new Dummy with age product precov[nres=%d][k1=%d]=%.4f * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
3668:
3669: /* /\* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; *\/ */
3670: /* /\* for (k=1; k<=cptcovage;k++){ /\\* For product with age V1+V1*age +V4 +age*V3 *\\/ *\/ */
3671: /* /\* 1+2 Tage[1]=2 TVar[2]=1 Dummy[2]=2, Tage[2]=4 TVar[4]=3 Dummy[4]=3 quant*\/ */
3672: /* /\* *\/ */
1.330 brouard 3673: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3674: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3675: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
1.332 brouard 3676: /* /\*cptcovage=2 1 2 *\/ */
3677: /* /\*Tage[k]= 5 8 *\/ */
3678: /* }else if( Dummy[k1]==3 ){ /\* For quant with age product *\/ */
3679: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
3680: /* 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]]); */
3681: /* printf("hpxij new Quanti with age product precov[nres=%d][k1=%d] * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
3682: /* /\* if(Dummy[Tage[k]]== 2){ /\\* dummy with age *\\/ *\/ */
3683: /* /\* /\\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\\* dummy with age *\\\/ *\\/ *\/ */
3684: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\\/ *\/ */
3685: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\\/ *\/ */
3686: /* /\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\/ */
3687: /* /\* 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); *\/ */
3688: /* /\* } else if(Dummy[Tage[k]]== 3){ /\\* quantitative with age *\\/ *\/ */
3689: /* /\* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; *\/ */
3690: /* /\* } *\/ */
3691: /* /\* 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]); *\/ */
3692: /* }else if(Typevar[k1]==2 ){ /\* For product (not with age) *\/ */
3693: /* /\* for (k=1; k<=cptcovprod;k++){ /\\* For product without age *\\/ *\/ */
3694: /* /\* /\\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\\/ *\/ */
3695: /* /\* /\\* k 1 2 3 4 5 6 7 8 9 *\\/ *\/ */
3696: /* /\* /\\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\\/ *\/ */
3697: /* /\* /\\*cptcovprod=1 1 2 *\\/ *\/ */
3698: /* /\* /\\*Tprod[]= 4 7 *\\/ *\/ */
3699: /* /\* /\\*Tvard[][1] 4 1 *\\/ *\/ */
3700: /* /\* /\\*Tvard[][2] 3 2 *\\/ *\/ */
1.330 brouard 3701:
1.332 brouard 3702: /* /\* 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])]); *\/ */
3703: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3704: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]]; */
3705: /* 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]]); */
3706: /* printf("hpxij new Product no age product precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3707:
3708: /* /\* if(Dummy[Tvardk[k1][1]]==0){ *\/ */
3709: /* /\* if(Dummy[Tvardk[k1][2]]==0){ /\\* Product of dummies *\\/ *\/ */
3710: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3711: /* /\* cov[2+nagesqr+k1]=Tinvresult[nres][Tvardk[k1][1]] * Tinvresult[nres][Tvardk[k1][2]]; *\/ */
3712: /* /\* 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]])]; *\/ */
3713: /* /\* }else{ /\\* Product of dummy by quantitative *\\/ *\/ */
3714: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,TnsdVar[Tvard[k][1]])] * Tqresult[nres][k]; *\/ */
3715: /* /\* cov[2+nagesqr+k1]=Tresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]]; *\/ */
3716: /* /\* } *\/ */
3717: /* /\* }else{ /\\* Product of quantitative by...*\\/ *\/ */
3718: /* /\* if(Dummy[Tvard[k][2]]==0){ /\\* quant by dummy *\\/ *\/ */
3719: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][Tvard[k][1]]; *\\/ *\/ */
3720: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
3721: /* /\* }else{ /\\* Product of two quant *\\/ *\/ */
3722: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\\/ *\/ */
3723: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
3724: /* /\* } *\/ */
3725: /* /\* }/\\*end of products quantitative *\\/ *\/ */
3726: /* }/\*end of products *\/ */
3727: /* } /\* End of loop on model equation *\/ */
1.235 brouard 3728: /* for (k=1; k<=cptcovn;k++) */
3729: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3730: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3731: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3732: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3733: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3734:
3735:
1.126 brouard 3736: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3737: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.319 brouard 3738: /* right multiplication of oldm by the current matrix */
1.126 brouard 3739: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3740: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3741: /* if((int)age == 70){ */
3742: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3743: /* for(i=1; i<=nlstate+ndeath; i++) { */
3744: /* printf("%d pmmij ",i); */
3745: /* for(j=1;j<=nlstate+ndeath;j++) { */
3746: /* printf("%f ",pmmij[i][j]); */
3747: /* } */
3748: /* printf(" oldm "); */
3749: /* for(j=1;j<=nlstate+ndeath;j++) { */
3750: /* printf("%f ",oldm[i][j]); */
3751: /* } */
3752: /* printf("\n"); */
3753: /* } */
3754: /* } */
1.126 brouard 3755: savm=oldm;
3756: oldm=newm;
3757: }
3758: for(i=1; i<=nlstate+ndeath; i++)
3759: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3760: po[i][j][h]=newm[i][j];
3761: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3762: }
1.128 brouard 3763: /*printf("h=%d ",h);*/
1.126 brouard 3764: } /* end h */
1.267 brouard 3765: /* printf("\n H=%d \n",h); */
1.126 brouard 3766: return po;
3767: }
3768:
1.217 brouard 3769: /************* Higher Back Matrix Product ***************/
1.218 brouard 3770: /* 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 3771: 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 3772: {
1.332 brouard 3773: /* For dummy covariates given in each resultline (for historical, computes the corresponding combination ij),
3774: computes the transition matrix starting at age 'age' over
1.217 brouard 3775: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3776: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3777: nhstepm*hstepm matrices.
3778: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3779: (typically every 2 years instead of every month which is too big
1.217 brouard 3780: for the memory).
1.218 brouard 3781: Model is determined by parameters x and covariates have to be
1.266 brouard 3782: included manually here. Then we use a call to bmij(x and cov)
3783: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3784: */
1.217 brouard 3785:
1.332 brouard 3786: int i, j, d, h, k, k1;
1.266 brouard 3787: double **out, cov[NCOVMAX+1], **bmij();
3788: double **newm, ***newmm;
1.217 brouard 3789: double agexact;
3790: double agebegin, ageend;
1.222 brouard 3791: double **oldm, **savm;
1.217 brouard 3792:
1.266 brouard 3793: newmm=po; /* To be saved */
3794: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3795: /* Hstepm could be zero and should return the unit matrix */
3796: for (i=1;i<=nlstate+ndeath;i++)
3797: for (j=1;j<=nlstate+ndeath;j++){
3798: oldm[i][j]=(i==j ? 1.0 : 0.0);
3799: po[i][j][0]=(i==j ? 1.0 : 0.0);
3800: }
3801: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3802: for(h=1; h <=nhstepm; h++){
3803: for(d=1; d <=hstepm; d++){
3804: newm=savm;
3805: /* Covariates have to be included here again */
3806: cov[1]=1.;
1.271 brouard 3807: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3808: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
1.318 brouard 3809: /* Debug */
3810: /* printf("hBxij age=%lf, agexact=%lf\n", age, agexact); */
1.217 brouard 3811: cov[2]=agexact;
1.332 brouard 3812: if(nagesqr==1){
1.222 brouard 3813: cov[3]= agexact*agexact;
1.332 brouard 3814: }
3815: /** New code */
3816: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
3817: if(Typevar[k1]==1){ /* A product with age */
3818: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.325 brouard 3819: }else{
1.332 brouard 3820: cov[2+nagesqr+k1]=precov[nres][k1];
1.325 brouard 3821: }
1.332 brouard 3822: }/* End of loop on model equation */
3823: /** End of new code */
3824: /** This was old code */
3825: /* for (k=1; k<=nsd;k++){ /\* For single dummy covariates only *\//\* cptcovn error *\/ */
3826: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
3827: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
3828: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])];/\* Bug valgrind *\/ */
3829: /* /\* 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)); *\/ */
3830: /* } */
3831: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
3832: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3833: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
3834: /* /\* 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]); *\/ */
3835: /* } */
3836: /* for (k=1; k<=cptcovage;k++){ /\* Should start at cptcovn+1 *\//\* For product with age *\/ */
3837: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age error!!!*\\/ *\/ */
3838: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
3839: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3840: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
3841: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3842: /* } */
3843: /* /\* 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]); *\/ */
3844: /* } */
3845: /* for (k=1; k<=cptcovprod;k++){ /\* Useless because included in cptcovn *\/ */
3846: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])]*nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3847: /* if(Dummy[Tvard[k][1]]==0){ */
3848: /* if(Dummy[Tvard[k][2]]==0){ */
3849: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][1])]; */
3850: /* }else{ */
3851: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3852: /* } */
3853: /* }else{ */
3854: /* if(Dummy[Tvard[k][2]]==0){ */
3855: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3856: /* }else{ */
3857: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3858: /* } */
3859: /* } */
3860: /* } */
3861: /* /\*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*\/ */
3862: /* /\*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*\/ */
3863: /** End of old code */
3864:
1.218 brouard 3865: /* Careful transposed matrix */
1.266 brouard 3866: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3867: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3868: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3869: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.325 brouard 3870: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);/* Bug valgrind */
1.217 brouard 3871: /* if((int)age == 70){ */
3872: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3873: /* for(i=1; i<=nlstate+ndeath; i++) { */
3874: /* printf("%d pmmij ",i); */
3875: /* for(j=1;j<=nlstate+ndeath;j++) { */
3876: /* printf("%f ",pmmij[i][j]); */
3877: /* } */
3878: /* printf(" oldm "); */
3879: /* for(j=1;j<=nlstate+ndeath;j++) { */
3880: /* printf("%f ",oldm[i][j]); */
3881: /* } */
3882: /* printf("\n"); */
3883: /* } */
3884: /* } */
3885: savm=oldm;
3886: oldm=newm;
3887: }
3888: for(i=1; i<=nlstate+ndeath; i++)
3889: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3890: po[i][j][h]=newm[i][j];
1.268 brouard 3891: /* if(h==nhstepm) */
3892: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3893: }
1.268 brouard 3894: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3895: } /* end h */
1.268 brouard 3896: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3897: return po;
3898: }
3899:
3900:
1.162 brouard 3901: #ifdef NLOPT
3902: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3903: double fret;
3904: double *xt;
3905: int j;
3906: myfunc_data *d2 = (myfunc_data *) pd;
3907: /* xt = (p1-1); */
3908: xt=vector(1,n);
3909: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3910:
3911: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3912: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3913: printf("Function = %.12lf ",fret);
3914: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3915: printf("\n");
3916: free_vector(xt,1,n);
3917: return fret;
3918: }
3919: #endif
1.126 brouard 3920:
3921: /*************** log-likelihood *************/
3922: double func( double *x)
3923: {
1.336 brouard 3924: int i, ii, j, k, mi, d, kk, kf=0;
1.226 brouard 3925: int ioffset=0;
1.339 brouard 3926: int ipos=0,iposold=0,ncovv=0;
3927:
1.340 brouard 3928: double cotvarv, cotvarvold;
1.226 brouard 3929: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3930: double **out;
3931: double lli; /* Individual log likelihood */
3932: int s1, s2;
1.228 brouard 3933: 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 3934:
1.226 brouard 3935: double bbh, survp;
3936: double agexact;
1.336 brouard 3937: double agebegin, ageend;
1.226 brouard 3938: /*extern weight */
3939: /* We are differentiating ll according to initial status */
3940: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3941: /*for(i=1;i<imx;i++)
3942: printf(" %d\n",s[4][i]);
3943: */
1.162 brouard 3944:
1.226 brouard 3945: ++countcallfunc;
1.162 brouard 3946:
1.226 brouard 3947: cov[1]=1.;
1.126 brouard 3948:
1.226 brouard 3949: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3950: ioffset=0;
1.226 brouard 3951: if(mle==1){
3952: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3953: /* Computes the values of the ncovmodel covariates of the model
3954: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3955: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3956: to be observed in j being in i according to the model.
3957: */
1.243 brouard 3958: ioffset=2+nagesqr ;
1.233 brouard 3959: /* Fixed */
1.345 brouard 3960: for (kf=1; kf<=ncovf;kf++){ /* For each fixed covariate dummy or quant or prod */
1.319 brouard 3961: /* # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi */
3962: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
3963: /* 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 3964: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.336 brouard 3965: 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 3966: /* V1*V2 (7) TvarFind[2]=7, TvarFind[3]=9 */
1.234 brouard 3967: }
1.226 brouard 3968: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
1.319 brouard 3969: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
1.226 brouard 3970: has been calculated etc */
3971: /* For an individual i, wav[i] gives the number of effective waves */
3972: /* We compute the contribution to Likelihood of each effective transition
3973: mw[mi][i] is real wave of the mi th effectve wave */
3974: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3975: s2=s[mw[mi+1][i]][i];
1.341 brouard 3976: 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 3977: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3978: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3979: */
1.336 brouard 3980: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
3981: /* Wave varying (but not age varying) */
1.339 brouard 3982: /* 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*\/ */
3983: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; but where is the crossproduct? *\/ */
3984: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
3985: /* } */
1.340 brouard 3986: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age )*/
3987: itv=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
3988: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
1.345 brouard 3989: if(FixedV[itv]!=0){ /* Not a fixed covariate */
1.341 brouard 3990: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]][i]; /* cotvar[wav][ncovcol+nqv+iv][i] */
1.340 brouard 3991: }else{ /* fixed covariate */
1.345 brouard 3992: 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 3993: }
1.339 brouard 3994: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 brouard 3995: cotvarvold=cotvarv;
3996: }else{ /* A second product */
3997: cotvarv=cotvarv*cotvarvold;
1.339 brouard 3998: }
3999: iposold=ipos;
1.340 brouard 4000: cov[ioffset+ipos]=cotvarv;
1.234 brouard 4001: }
1.339 brouard 4002: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
4003: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4004: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
4005: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
4006: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
4007: /* printf(" i=%d,mi=%d,itv=%d,TmodelInvind[itv]=%d,cotvar[mw[mi][i]][TmodelInvind[itv]][i]=%f\n", i, mi, itv, TmodelInvind[itv],cotvar[mw[mi][i]][TmodelInvind[itv]][i]); */
4008: /* } */
4009: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
4010: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4011: /* /\* 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]); *\/ */
4012: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
4013: /* } */
4014: /* for products of time varying to be done */
1.234 brouard 4015: for (ii=1;ii<=nlstate+ndeath;ii++)
4016: for (j=1;j<=nlstate+ndeath;j++){
4017: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4018: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4019: }
1.336 brouard 4020:
4021: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4022: 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 4023: for(d=0; d<dh[mi][i]; d++){
4024: newm=savm;
4025: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4026: cov[2]=agexact;
4027: if(nagesqr==1)
4028: cov[3]= agexact*agexact; /* Should be changed here */
4029: for (kk=1; kk<=cptcovage;kk++) {
1.318 brouard 4030: if(!FixedV[Tvar[Tage[kk]]])
4031: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
4032: else
1.341 brouard 4033: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]*agexact; /* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
1.234 brouard 4034: }
4035: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4036: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4037: savm=oldm;
4038: oldm=newm;
4039: } /* end mult */
4040:
4041: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
4042: /* But now since version 0.9 we anticipate for bias at large stepm.
4043: * If stepm is larger than one month (smallest stepm) and if the exact delay
4044: * (in months) between two waves is not a multiple of stepm, we rounded to
4045: * the nearest (and in case of equal distance, to the lowest) interval but now
4046: * we keep into memory the bias bh[mi][i] and also the previous matrix product
4047: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
4048: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 4049: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
4050: * -stepm/2 to stepm/2 .
4051: * For stepm=1 the results are the same as for previous versions of Imach.
4052: * For stepm > 1 the results are less biased than in previous versions.
4053: */
1.234 brouard 4054: s1=s[mw[mi][i]][i];
4055: s2=s[mw[mi+1][i]][i];
4056: bbh=(double)bh[mi][i]/(double)stepm;
4057: /* bias bh is positive if real duration
4058: * is higher than the multiple of stepm and negative otherwise.
4059: */
4060: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
4061: if( s2 > nlstate){
4062: /* i.e. if s2 is a death state and if the date of death is known
4063: then the contribution to the likelihood is the probability to
4064: die between last step unit time and current step unit time,
4065: which is also equal to probability to die before dh
4066: minus probability to die before dh-stepm .
4067: In version up to 0.92 likelihood was computed
4068: as if date of death was unknown. Death was treated as any other
4069: health state: the date of the interview describes the actual state
4070: and not the date of a change in health state. The former idea was
4071: to consider that at each interview the state was recorded
4072: (healthy, disable or death) and IMaCh was corrected; but when we
4073: introduced the exact date of death then we should have modified
4074: the contribution of an exact death to the likelihood. This new
4075: contribution is smaller and very dependent of the step unit
4076: stepm. It is no more the probability to die between last interview
4077: and month of death but the probability to survive from last
4078: interview up to one month before death multiplied by the
4079: probability to die within a month. Thanks to Chris
4080: Jackson for correcting this bug. Former versions increased
4081: mortality artificially. The bad side is that we add another loop
4082: which slows down the processing. The difference can be up to 10%
4083: lower mortality.
4084: */
4085: /* If, at the beginning of the maximization mostly, the
4086: cumulative probability or probability to be dead is
4087: constant (ie = 1) over time d, the difference is equal to
4088: 0. out[s1][3] = savm[s1][3]: probability, being at state
4089: s1 at precedent wave, to be dead a month before current
4090: wave is equal to probability, being at state s1 at
4091: precedent wave, to be dead at mont of the current
4092: wave. Then the observed probability (that this person died)
4093: is null according to current estimated parameter. In fact,
4094: it should be very low but not zero otherwise the log go to
4095: infinity.
4096: */
1.183 brouard 4097: /* #ifdef INFINITYORIGINAL */
4098: /* lli=log(out[s1][s2] - savm[s1][s2]); */
4099: /* #else */
4100: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
4101: /* lli=log(mytinydouble); */
4102: /* else */
4103: /* lli=log(out[s1][s2] - savm[s1][s2]); */
4104: /* #endif */
1.226 brouard 4105: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4106:
1.226 brouard 4107: } else if ( s2==-1 ) { /* alive */
4108: for (j=1,survp=0. ; j<=nlstate; j++)
4109: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4110: /*survp += out[s1][j]; */
4111: lli= log(survp);
4112: }
1.336 brouard 4113: /* else if (s2==-4) { */
4114: /* for (j=3,survp=0. ; j<=nlstate; j++) */
4115: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
4116: /* lli= log(survp); */
4117: /* } */
4118: /* else if (s2==-5) { */
4119: /* for (j=1,survp=0. ; j<=2; j++) */
4120: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
4121: /* lli= log(survp); */
4122: /* } */
1.226 brouard 4123: else{
4124: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4125: /* 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 */
4126: }
4127: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
4128: /*if(lli ==000.0)*/
1.340 brouard 4129: /* 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 4130: ipmx +=1;
4131: sw += weight[i];
4132: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4133: /* if (lli < log(mytinydouble)){ */
4134: /* 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); */
4135: /* 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]); */
4136: /* } */
4137: } /* end of wave */
4138: } /* end of individual */
4139: } else if(mle==2){
4140: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.319 brouard 4141: ioffset=2+nagesqr ;
4142: for (k=1; k<=ncovf;k++)
4143: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];
1.226 brouard 4144: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 4145: for(k=1; k <= ncovv ; k++){
1.341 brouard 4146: 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 4147: }
1.226 brouard 4148: for (ii=1;ii<=nlstate+ndeath;ii++)
4149: for (j=1;j<=nlstate+ndeath;j++){
4150: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4151: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4152: }
4153: for(d=0; d<=dh[mi][i]; d++){
4154: newm=savm;
4155: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4156: cov[2]=agexact;
4157: if(nagesqr==1)
4158: cov[3]= agexact*agexact;
4159: for (kk=1; kk<=cptcovage;kk++) {
4160: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4161: }
4162: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4163: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4164: savm=oldm;
4165: oldm=newm;
4166: } /* end mult */
4167:
4168: s1=s[mw[mi][i]][i];
4169: s2=s[mw[mi+1][i]][i];
4170: bbh=(double)bh[mi][i]/(double)stepm;
4171: 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 */
4172: ipmx +=1;
4173: sw += weight[i];
4174: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4175: } /* end of wave */
4176: } /* end of individual */
4177: } else if(mle==3){ /* exponential inter-extrapolation */
4178: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4179: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4180: for(mi=1; mi<= wav[i]-1; mi++){
4181: for (ii=1;ii<=nlstate+ndeath;ii++)
4182: for (j=1;j<=nlstate+ndeath;j++){
4183: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4184: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4185: }
4186: for(d=0; d<dh[mi][i]; d++){
4187: newm=savm;
4188: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4189: cov[2]=agexact;
4190: if(nagesqr==1)
4191: cov[3]= agexact*agexact;
4192: for (kk=1; kk<=cptcovage;kk++) {
1.340 brouard 4193: if(!FixedV[Tvar[Tage[kk]]])
4194: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
4195: else
1.341 brouard 4196: 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 4197: }
4198: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4199: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4200: savm=oldm;
4201: oldm=newm;
4202: } /* end mult */
4203:
4204: s1=s[mw[mi][i]][i];
4205: s2=s[mw[mi+1][i]][i];
4206: bbh=(double)bh[mi][i]/(double)stepm;
4207: 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 */
4208: ipmx +=1;
4209: sw += weight[i];
4210: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4211: } /* end of wave */
4212: } /* end of individual */
4213: }else if (mle==4){ /* ml=4 no inter-extrapolation */
4214: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4215: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4216: for(mi=1; mi<= wav[i]-1; mi++){
4217: for (ii=1;ii<=nlstate+ndeath;ii++)
4218: for (j=1;j<=nlstate+ndeath;j++){
4219: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4220: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4221: }
4222: for(d=0; d<dh[mi][i]; d++){
4223: newm=savm;
4224: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4225: cov[2]=agexact;
4226: if(nagesqr==1)
4227: cov[3]= agexact*agexact;
4228: for (kk=1; kk<=cptcovage;kk++) {
4229: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4230: }
1.126 brouard 4231:
1.226 brouard 4232: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4233: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4234: savm=oldm;
4235: oldm=newm;
4236: } /* end mult */
4237:
4238: s1=s[mw[mi][i]][i];
4239: s2=s[mw[mi+1][i]][i];
4240: if( s2 > nlstate){
4241: lli=log(out[s1][s2] - savm[s1][s2]);
4242: } else if ( s2==-1 ) { /* alive */
4243: for (j=1,survp=0. ; j<=nlstate; j++)
4244: survp += out[s1][j];
4245: lli= log(survp);
4246: }else{
4247: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4248: }
4249: ipmx +=1;
4250: sw += weight[i];
4251: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.343 brouard 4252: /* 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 4253: } /* end of wave */
4254: } /* end of individual */
4255: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
4256: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4257: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4258: for(mi=1; mi<= wav[i]-1; mi++){
4259: for (ii=1;ii<=nlstate+ndeath;ii++)
4260: for (j=1;j<=nlstate+ndeath;j++){
4261: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4262: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4263: }
4264: for(d=0; d<dh[mi][i]; d++){
4265: newm=savm;
4266: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4267: cov[2]=agexact;
4268: if(nagesqr==1)
4269: cov[3]= agexact*agexact;
4270: for (kk=1; kk<=cptcovage;kk++) {
1.340 brouard 4271: if(!FixedV[Tvar[Tage[kk]]])
4272: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
4273: else
1.341 brouard 4274: 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 4275: }
1.126 brouard 4276:
1.226 brouard 4277: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4278: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4279: savm=oldm;
4280: oldm=newm;
4281: } /* end mult */
4282:
4283: s1=s[mw[mi][i]][i];
4284: s2=s[mw[mi+1][i]][i];
4285: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4286: ipmx +=1;
4287: sw += weight[i];
4288: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4289: /*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]);*/
4290: } /* end of wave */
4291: } /* end of individual */
4292: } /* End of if */
4293: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
4294: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
4295: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4296: return -l;
1.126 brouard 4297: }
4298:
4299: /*************** log-likelihood *************/
4300: double funcone( double *x)
4301: {
1.228 brouard 4302: /* Same as func but slower because of a lot of printf and if */
1.335 brouard 4303: int i, ii, j, k, mi, d, kk, kf=0;
1.228 brouard 4304: int ioffset=0;
1.339 brouard 4305: int ipos=0,iposold=0,ncovv=0;
4306:
1.340 brouard 4307: double cotvarv, cotvarvold;
1.131 brouard 4308: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 4309: double **out;
4310: double lli; /* Individual log likelihood */
4311: double llt;
4312: int s1, s2;
1.228 brouard 4313: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
4314:
1.126 brouard 4315: double bbh, survp;
1.187 brouard 4316: double agexact;
1.214 brouard 4317: double agebegin, ageend;
1.126 brouard 4318: /*extern weight */
4319: /* We are differentiating ll according to initial status */
4320: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
4321: /*for(i=1;i<imx;i++)
4322: printf(" %d\n",s[4][i]);
4323: */
4324: cov[1]=1.;
4325:
4326: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 4327: ioffset=0;
4328: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.336 brouard 4329: /* Computes the values of the ncovmodel covariates of the model
4330: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
4331: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
4332: to be observed in j being in i according to the model.
4333: */
1.243 brouard 4334: /* ioffset=2+nagesqr+cptcovage; */
4335: ioffset=2+nagesqr;
1.232 brouard 4336: /* Fixed */
1.224 brouard 4337: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 4338: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
1.335 brouard 4339: for (kf=1; kf<=ncovf;kf++){ /* Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */
1.339 brouard 4340: /* printf("Debug3 TvarFind[%d]=%d",kf, TvarFind[kf]); */
4341: /* printf(" Tvar[TvarFind[kf]]=%d", Tvar[TvarFind[kf]]); */
4342: /* printf(" i=%d covar[Tvar[TvarFind[kf]]][i]=%f\n",i,covar[Tvar[TvarFind[kf]]][i]); */
1.335 brouard 4343: 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 4344: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
4345: /* cov[2+6]=covar[Tvar[6]][i]; */
4346: /* cov[2+6]=covar[2][i]; V2 */
4347: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
4348: /* cov[2+7]=covar[Tvar[7]][i]; */
4349: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
4350: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
4351: /* cov[2+9]=covar[Tvar[9]][i]; */
4352: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 4353: }
1.336 brouard 4354: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
4355: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
4356: has been calculated etc */
4357: /* For an individual i, wav[i] gives the number of effective waves */
4358: /* We compute the contribution to Likelihood of each effective transition
4359: mw[mi][i] is real wave of the mi th effectve wave */
4360: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
4361: s2=s[mw[mi+1][i]][i];
1.341 brouard 4362: And the iv th varying covariate in the DATA is the cotvar[mw[mi+1][i]][ncovcol+nqv+iv][i]
1.336 brouard 4363: */
4364: /* This part may be useless now because everythin should be in covar */
1.232 brouard 4365: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
4366: /* 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?)*\/ */
4367: /* } */
1.231 brouard 4368: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
4369: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
4370: /* } */
1.225 brouard 4371:
1.233 brouard 4372:
4373: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.339 brouard 4374: /* 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 */
4375: /* for(k=1; k <= ncovv ; k++){ /\* Varying covariates (single and product but no age )*\/ */
4376: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; *\/ */
4377: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
4378: /* } */
4379:
4380: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
4381: /* model V1+V3+age*V1+age*V3+V1*V3 */
4382: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
4383: /* TvarVV[1]=V3 (first time varying in the model equation, TvarVV[2]=V1 (in V1*V3) TvarVV[3]=3(V3) */
4384: /* We need the position of the time varying or product in the model */
4385: /* 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 */
4386: /* TvarVV gives the variable name */
1.340 brouard 4387: /* Other example V1 + V3 + V5 + age*V1 + age*V3 + age*V5 + V1*V3 + V3*V5 + V1*V5
4388: * k= 1 2 3 4 5 6 7 8 9
4389: * varying 1 2 3 4 5
4390: * ncovv 1 2 3 4 5 6 7 8
1.343 brouard 4391: * TvarVV[ncovv] V3 5 1 3 3 5 1 5
1.340 brouard 4392: * TvarVVind 2 3 7 7 8 8 9 9
4393: * TvarFind[k] 1 0 0 0 0 0 0 0 0
4394: */
1.345 brouard 4395: /* Other model ncovcol=5 nqv=0 ntv=3 nqtv=0 nlstate=3
1.346 brouard 4396: * V2 V3 V4 are fixed V6 V7 are timevarying so V8 and V5 are not in the model and product column will start at 9 Tvar[4]=6
1.345 brouard 4397: * FixedV[ncovcol+qv+ntv+nqtv] V5
4398: * V1 V2 V3 V4 V5 V6 V7 V8
4399: * 0 0 0 0 0 1 1 1
4400: * model= V2 + V3 + V4 + V6 + V7 + V6*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
4401: * kmodel 1 2 3 4 5 6 7 8 9 10 11
4402: * ncovf 1 2 3
4403: * ncovvt=14 1 2 3 4 5 6 7 8 9 10 11 12 13 14
4404: * TvarVV[1]@14 = itv {6, 7, 6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
4405: * TvarVVind[1]@14= {4, 5, 6, 6, 7, 7, 8, 8, 9, 9, 10, 10, 11, 11}
4406: * TvarFind[1]@14= {1, 2, 3, 0 <repeats 12 times>}
4407: * Tvar[1]@20= {2, 3, 4, 6, 7, 9, 10, 11, 12, 13, 14}
4408: * TvarFind[itv] 0 0 0
4409: * FixedV[itv] 1 1 1 0 1 0 1 0 1 0 0
4410: * Tvar[TvarFind[ncovf]]=[1]=2 [2]=3 [4]=4
4411: * Tvar[TvarFind[itv]] [0]=? ?ncovv 1 à ncovvt]
4412: * Not a fixed cotvar[mw][itv][i] 6 7 6 2 7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
4413: * fixed covar[itv] [6] [7] [6][2]
4414: */
4415:
1.340 brouard 4416: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age) including individual from products */
1.345 brouard 4417: itv=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product */
1.340 brouard 4418: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
1.345 brouard 4419: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
4420: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
4421: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
1.340 brouard 4422: }else{ /* fixed covariate */
1.345 brouard 4423: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
4424: 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 4425: }
1.339 brouard 4426: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 brouard 4427: cotvarvold=cotvarv;
4428: }else{ /* A second product */
4429: cotvarv=cotvarv*cotvarvold;
1.339 brouard 4430: }
4431: iposold=ipos;
1.340 brouard 4432: cov[ioffset+ipos]=cotvarv;
1.339 brouard 4433: /* For products */
4434: }
4435: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates single *\/ */
4436: /* iv=TvarVDind[itv]; /\* iv, position in the model equation of time varying covariate itv *\/ */
4437: /* /\* "V1+V3+age*V1+age*V3+V1*V3" with V3 time varying *\/ */
4438: /* /\* 1 2 3 4 5 *\/ */
4439: /* /\*itv 1 *\/ */
4440: /* /\* TvarVInd[1]= 2 *\/ */
4441: /* /\* iv= Tvar[Tmodelind[itv]]-ncovcol-nqv; /\\* Counting the # varying covariate from 1 to ntveff *\\/ *\/ */
4442: /* /\* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; *\/ */
4443: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; *\/ */
4444: /* /\* k=ioffset-2-nagesqr-cptcovage+itv; /\\* position in simple model *\\/ *\/ */
4445: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; *\/ */
4446: /* cov[ioffset+iv]=cotvar[mw[mi][i]][itv][i]; */
4447: /* /\* 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]); *\/ */
4448: /* } */
1.232 brouard 4449: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 4450: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4451: /* /\* 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]); *\/ */
4452: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 4453: /* } */
1.126 brouard 4454: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 4455: for (j=1;j<=nlstate+ndeath;j++){
4456: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4457: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4458: }
1.214 brouard 4459:
4460: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4461: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
4462: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 4463: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 4464: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
4465: and mw[mi+1][i]. dh depends on stepm.*/
4466: newm=savm;
1.247 brouard 4467: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 4468: cov[2]=agexact;
4469: if(nagesqr==1)
4470: cov[3]= agexact*agexact;
4471: for (kk=1; kk<=cptcovage;kk++) {
4472: if(!FixedV[Tvar[Tage[kk]]])
4473: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4474: else
1.341 brouard 4475: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]*agexact; /* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
1.242 brouard 4476: }
4477: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
4478: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
4479: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4480: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4481: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
4482: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
4483: savm=oldm;
4484: oldm=newm;
1.126 brouard 4485: } /* end mult */
1.336 brouard 4486: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
4487: /* But now since version 0.9 we anticipate for bias at large stepm.
4488: * If stepm is larger than one month (smallest stepm) and if the exact delay
4489: * (in months) between two waves is not a multiple of stepm, we rounded to
4490: * the nearest (and in case of equal distance, to the lowest) interval but now
4491: * we keep into memory the bias bh[mi][i] and also the previous matrix product
4492: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
4493: * probability in order to take into account the bias as a fraction of the way
4494: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
4495: * -stepm/2 to stepm/2 .
4496: * For stepm=1 the results are the same as for previous versions of Imach.
4497: * For stepm > 1 the results are less biased than in previous versions.
4498: */
1.126 brouard 4499: s1=s[mw[mi][i]][i];
4500: s2=s[mw[mi+1][i]][i];
1.217 brouard 4501: /* if(s2==-1){ */
1.268 brouard 4502: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 4503: /* /\* exit(1); *\/ */
4504: /* } */
1.126 brouard 4505: bbh=(double)bh[mi][i]/(double)stepm;
4506: /* bias is positive if real duration
4507: * is higher than the multiple of stepm and negative otherwise.
4508: */
4509: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 4510: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4511: } else if ( s2==-1 ) { /* alive */
1.242 brouard 4512: for (j=1,survp=0. ; j<=nlstate; j++)
4513: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4514: lli= log(survp);
1.126 brouard 4515: }else if (mle==1){
1.242 brouard 4516: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 4517: } else if(mle==2){
1.242 brouard 4518: 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 4519: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 4520: 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 4521: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 4522: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 4523: } else{ /* mle=0 back to 1 */
1.242 brouard 4524: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4525: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 4526: } /* End of if */
4527: ipmx +=1;
4528: sw += weight[i];
4529: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.342 brouard 4530: /* Printing covariates values for each contribution for checking */
1.343 brouard 4531: /* 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 4532: if(globpr){
1.246 brouard 4533: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 4534: %11.6f %11.6f %11.6f ", \
1.242 brouard 4535: 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 4536: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.343 brouard 4537: /* printf("%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\ */
4538: /* %11.6f %11.6f %11.6f ", \ */
4539: /* num[i], agebegin, ageend, i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],weight[i]*gipmx/gsw, */
4540: /* 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2])); */
1.242 brouard 4541: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
4542: llt +=ll[k]*gipmx/gsw;
4543: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
1.335 brouard 4544: /* printf(" %10.6f",-ll[k]*gipmx/gsw); */
1.242 brouard 4545: }
1.343 brouard 4546: fprintf(ficresilk," %10.6f ", -llt);
1.335 brouard 4547: /* printf(" %10.6f\n", -llt); */
1.342 brouard 4548: /* if(debugILK){ /\* debugILK is set by a #d in a comment line *\/ */
1.343 brouard 4549: /* fprintf(ficresilk,"%09ld ", num[i]); */ /* not necessary */
4550: for (kf=1; kf<=ncovf;kf++){ /* Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */
4551: fprintf(ficresilk," %g",covar[Tvar[TvarFind[kf]]][i]);
4552: }
4553: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age) including individual from products */
4554: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4555: if(ipos!=iposold){ /* Not a product or first of a product */
4556: fprintf(ficresilk," %g",cov[ioffset+ipos]);
4557: /* printf(" %g",cov[ioffset+ipos]); */
4558: }else{
4559: fprintf(ficresilk,"*");
4560: /* printf("*"); */
1.342 brouard 4561: }
1.343 brouard 4562: iposold=ipos;
4563: }
4564: for (kk=1; kk<=cptcovage;kk++) {
4565: if(!FixedV[Tvar[Tage[kk]]]){
4566: fprintf(ficresilk," %g*age",covar[Tvar[Tage[kk]]][i]);
4567: /* printf(" %g*age",covar[Tvar[Tage[kk]]][i]); */
4568: }else{
4569: fprintf(ficresilk," %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
4570: /* printf(" %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */
1.342 brouard 4571: }
1.343 brouard 4572: }
4573: /* printf("\n"); */
1.342 brouard 4574: /* } /\* End debugILK *\/ */
4575: fprintf(ficresilk,"\n");
4576: } /* End if globpr */
1.335 brouard 4577: } /* end of wave */
4578: } /* end of individual */
4579: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
1.232 brouard 4580: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
1.335 brouard 4581: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4582: if(globpr==0){ /* First time we count the contributions and weights */
4583: gipmx=ipmx;
4584: gsw=sw;
4585: }
1.343 brouard 4586: return -l;
1.126 brouard 4587: }
4588:
4589:
4590: /*************** function likelione ***********/
1.292 brouard 4591: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 4592: {
4593: /* This routine should help understanding what is done with
4594: the selection of individuals/waves and
4595: to check the exact contribution to the likelihood.
4596: Plotting could be done.
1.342 brouard 4597: */
4598: void pstamp(FILE *ficres);
1.343 brouard 4599: int k, kf, kk, kvar, ncovv, iposold, ipos;
1.126 brouard 4600:
4601: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 4602: strcpy(fileresilk,"ILK_");
1.202 brouard 4603: strcat(fileresilk,fileresu);
1.126 brouard 4604: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
4605: printf("Problem with resultfile: %s\n", fileresilk);
4606: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
4607: }
1.342 brouard 4608: pstamp(ficresilk);fprintf(ficresilk,"# model=1+age+%s\n",model);
1.214 brouard 4609: 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");
4610: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 4611: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
4612: for(k=1; k<=nlstate; k++)
4613: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
1.342 brouard 4614: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total) ");
4615:
4616: /* if(debugILK){ /\* debugILK is set by a #d in a comment line *\/ */
4617: for(kf=1;kf <= ncovf; kf++){
4618: fprintf(ficresilk,"V%d",Tvar[TvarFind[kf]]);
4619: /* printf("V%d",Tvar[TvarFind[kf]]); */
4620: }
4621: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){
1.343 brouard 4622: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
1.342 brouard 4623: if(ipos!=iposold){ /* Not a product or first of a product */
4624: /* printf(" %d",ipos); */
4625: fprintf(ficresilk," V%d",TvarVV[ncovv]);
4626: }else{
4627: /* printf("*"); */
4628: fprintf(ficresilk,"*");
1.343 brouard 4629: }
1.342 brouard 4630: iposold=ipos;
4631: }
4632: for (kk=1; kk<=cptcovage;kk++) {
4633: if(!FixedV[Tvar[Tage[kk]]]){
4634: /* printf(" %d*age(Fixed)",Tvar[Tage[kk]]); */
4635: fprintf(ficresilk," %d*age(Fixed)",Tvar[Tage[kk]]);
4636: }else{
4637: fprintf(ficresilk," %d*age(Varying)",Tvar[Tage[kk]]);/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
4638: /* printf(" %d*age(Varying)",Tvar[Tage[kk]]);/\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */
4639: }
4640: }
4641: /* } /\* End if debugILK *\/ */
4642: /* printf("\n"); */
4643: fprintf(ficresilk,"\n");
4644: } /* End glogpri */
1.126 brouard 4645:
1.292 brouard 4646: *fretone=(*func)(p);
1.126 brouard 4647: if(*globpri !=0){
4648: fclose(ficresilk);
1.205 brouard 4649: if (mle ==0)
4650: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
4651: else if(mle >=1)
4652: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
4653: 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 4654: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 4655:
1.207 brouard 4656: 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 4657: <img src=\"%s-ori.png\">\n",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4658: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.343 brouard 4659: <img src=\"%s-dest.png\">\n",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
4660:
4661: for (k=1; k<= nlstate ; k++) {
4662: 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 \
4663: <img src=\"%s-p%dj.png\">\n",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
4664: for(kf=1; kf <= ncovf; kf++){ /* For each simple dummy covariate of the model */
4665: /* kvar=Tvar[TvarFind[kf]]; */ /* variable */
4666: 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> \
4667: <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]]);
4668: }
4669: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Loop on the time varying extended covariates (with extension of Vn*Vm */
4670: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
4671: kvar=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
4672: /* 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]); */
4673: if(ipos!=iposold){ /* Not a product or first of a product */
4674: /* fprintf(ficresilk," V%d",TvarVV[ncovv]); */
4675: /* printf(" DebugILK fichtm ipos=%d != iposold=%d\n", ipos, iposold); */
4676: 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) */
4677: 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> \
4678: <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);
4679: } /* End only for dummies time varying (single?) */
4680: }else{ /* Useless product */
4681: /* printf("*"); */
4682: /* fprintf(ficresilk,"*"); */
4683: }
4684: iposold=ipos;
4685: } /* For each time varying covariate */
4686: } /* End loop on states */
4687:
4688: /* if(debugILK){ */
4689: /* for(kf=1; kf <= ncovf; kf++){ /\* For each simple dummy covariate of the model *\/ */
4690: /* /\* kvar=Tvar[TvarFind[kf]]; *\/ /\* variable *\/ */
4691: /* for (k=1; k<= nlstate ; k++) { */
4692: /* 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> \ */
4693: /* <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]]); */
4694: /* } */
4695: /* } */
4696: /* for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /\* Loop on the time varying extended covariates (with extension of Vn*Vm *\/ */
4697: /* ipos=TvarVVind[ncovv]; /\* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate *\/ */
4698: /* kvar=TvarVV[ncovv]; /\* TvarVV={3, 1, 3} gives the name of each varying covariate *\/ */
4699: /* /\* 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]); *\/ */
4700: /* if(ipos!=iposold){ /\* Not a product or first of a product *\/ */
4701: /* /\* fprintf(ficresilk," V%d",TvarVV[ncovv]); *\/ */
4702: /* /\* printf(" DebugILK fichtm ipos=%d != iposold=%d\n", ipos, iposold); *\/ */
4703: /* 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) *\/ */
4704: /* for (k=1; k<= nlstate ; k++) { */
4705: /* 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> \ */
4706: /* <img src=\"%s-p%dj-%d.png\">",k,k,kvar,kvar,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,kvar); */
4707: /* } /\* End state *\/ */
4708: /* } /\* End only for dummies time varying (single?) *\/ */
4709: /* }else{ /\* Useless product *\/ */
4710: /* /\* printf("*"); *\/ */
4711: /* /\* fprintf(ficresilk,"*"); *\/ */
4712: /* } */
4713: /* iposold=ipos; */
4714: /* } /\* For each time varying covariate *\/ */
4715: /* }/\* End debugILK *\/ */
1.207 brouard 4716: fflush(fichtm);
1.343 brouard 4717: }/* End globpri */
1.126 brouard 4718: return;
4719: }
4720:
4721:
4722: /*********** Maximum Likelihood Estimation ***************/
4723:
4724: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
4725: {
1.319 brouard 4726: int i,j,k, jk, jkk=0, iter=0;
1.126 brouard 4727: double **xi;
4728: double fret;
4729: double fretone; /* Only one call to likelihood */
4730: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 4731:
4732: #ifdef NLOPT
4733: int creturn;
4734: nlopt_opt opt;
4735: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
4736: double *lb;
4737: double minf; /* the minimum objective value, upon return */
4738: double * p1; /* Shifted parameters from 0 instead of 1 */
4739: myfunc_data dinst, *d = &dinst;
4740: #endif
4741:
4742:
1.126 brouard 4743: xi=matrix(1,npar,1,npar);
4744: for (i=1;i<=npar;i++)
4745: for (j=1;j<=npar;j++)
4746: xi[i][j]=(i==j ? 1.0 : 0.0);
4747: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 4748: strcpy(filerespow,"POW_");
1.126 brouard 4749: strcat(filerespow,fileres);
4750: if((ficrespow=fopen(filerespow,"w"))==NULL) {
4751: printf("Problem with resultfile: %s\n", filerespow);
4752: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
4753: }
4754: fprintf(ficrespow,"# Powell\n# iter -2*LL");
4755: for (i=1;i<=nlstate;i++)
4756: for(j=1;j<=nlstate+ndeath;j++)
4757: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
4758: fprintf(ficrespow,"\n");
1.162 brouard 4759: #ifdef POWELL
1.319 brouard 4760: #ifdef LINMINORIGINAL
4761: #else /* LINMINORIGINAL */
4762:
4763: flatdir=ivector(1,npar);
4764: for (j=1;j<=npar;j++) flatdir[j]=0;
4765: #endif /*LINMINORIGINAL */
4766:
4767: #ifdef FLATSUP
4768: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4769: /* reorganizing p by suppressing flat directions */
4770: for(i=1, jk=1; i <=nlstate; i++){
4771: for(k=1; k <=(nlstate+ndeath); k++){
4772: if (k != i) {
4773: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4774: if(flatdir[jk]==1){
4775: printf(" To be skipped %d%d flatdir[%d]=%d ",i,k,jk, flatdir[jk]);
4776: }
4777: for(j=1; j <=ncovmodel; j++){
4778: printf("%12.7f ",p[jk]);
4779: jk++;
4780: }
4781: printf("\n");
4782: }
4783: }
4784: }
4785: /* skipping */
4786: /* for(i=1, jk=1, jkk=1;(flatdir[jk]==0)&& (i <=nlstate); i++){ */
4787: for(i=1, jk=1, jkk=1;i <=nlstate; i++){
4788: for(k=1; k <=(nlstate+ndeath); k++){
4789: if (k != i) {
4790: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4791: if(flatdir[jk]==1){
4792: printf(" To be skipped %d%d flatdir[%d]=%d jk=%d p[%d] ",i,k,jk, flatdir[jk],jk, jk);
4793: for(j=1; j <=ncovmodel; jk++,j++){
4794: printf(" p[%d]=%12.7f",jk, p[jk]);
4795: /*q[jjk]=p[jk];*/
4796: }
4797: }else{
4798: printf(" To be kept %d%d flatdir[%d]=%d jk=%d q[%d]=p[%d] ",i,k,jk, flatdir[jk],jk, jkk, jk);
4799: for(j=1; j <=ncovmodel; jk++,jkk++,j++){
4800: printf(" p[%d]=%12.7f=q[%d]",jk, p[jk],jkk);
4801: /*q[jjk]=p[jk];*/
4802: }
4803: }
4804: printf("\n");
4805: }
4806: fflush(stdout);
4807: }
4808: }
4809: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4810: #else /* FLATSUP */
1.126 brouard 4811: powell(p,xi,npar,ftol,&iter,&fret,func);
1.319 brouard 4812: #endif /* FLATSUP */
4813:
4814: #ifdef LINMINORIGINAL
4815: #else
4816: free_ivector(flatdir,1,npar);
4817: #endif /* LINMINORIGINAL*/
4818: #endif /* POWELL */
1.126 brouard 4819:
1.162 brouard 4820: #ifdef NLOPT
4821: #ifdef NEWUOA
4822: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
4823: #else
4824: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
4825: #endif
4826: lb=vector(0,npar-1);
4827: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
4828: nlopt_set_lower_bounds(opt, lb);
4829: nlopt_set_initial_step1(opt, 0.1);
4830:
4831: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
4832: d->function = func;
4833: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
4834: nlopt_set_min_objective(opt, myfunc, d);
4835: nlopt_set_xtol_rel(opt, ftol);
4836: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
4837: printf("nlopt failed! %d\n",creturn);
4838: }
4839: else {
4840: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
4841: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
4842: iter=1; /* not equal */
4843: }
4844: nlopt_destroy(opt);
4845: #endif
1.319 brouard 4846: #ifdef FLATSUP
4847: /* npared = npar -flatd/ncovmodel; */
4848: /* xired= matrix(1,npared,1,npared); */
4849: /* paramred= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); */
4850: /* powell(pred,xired,npared,ftol,&iter,&fret,flatdir,func); */
4851: /* free_matrix(xire,1,npared,1,npared); */
4852: #else /* FLATSUP */
4853: #endif /* FLATSUP */
1.126 brouard 4854: free_matrix(xi,1,npar,1,npar);
4855: fclose(ficrespow);
1.203 brouard 4856: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
4857: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 4858: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 4859:
4860: }
4861:
4862: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 4863: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 4864: {
4865: double **a,**y,*x,pd;
1.203 brouard 4866: /* double **hess; */
1.164 brouard 4867: int i, j;
1.126 brouard 4868: int *indx;
4869:
4870: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 4871: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 4872: void lubksb(double **a, int npar, int *indx, double b[]) ;
4873: void ludcmp(double **a, int npar, int *indx, double *d) ;
4874: double gompertz(double p[]);
1.203 brouard 4875: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 4876:
4877: printf("\nCalculation of the hessian matrix. Wait...\n");
4878: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
4879: for (i=1;i<=npar;i++){
1.203 brouard 4880: printf("%d-",i);fflush(stdout);
4881: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 4882:
4883: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
4884:
4885: /* printf(" %f ",p[i]);
4886: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
4887: }
4888:
4889: for (i=1;i<=npar;i++) {
4890: for (j=1;j<=npar;j++) {
4891: if (j>i) {
1.203 brouard 4892: printf(".%d-%d",i,j);fflush(stdout);
4893: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
4894: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 4895:
4896: hess[j][i]=hess[i][j];
4897: /*printf(" %lf ",hess[i][j]);*/
4898: }
4899: }
4900: }
4901: printf("\n");
4902: fprintf(ficlog,"\n");
4903:
4904: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
4905: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
4906:
4907: a=matrix(1,npar,1,npar);
4908: y=matrix(1,npar,1,npar);
4909: x=vector(1,npar);
4910: indx=ivector(1,npar);
4911: for (i=1;i<=npar;i++)
4912: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
4913: ludcmp(a,npar,indx,&pd);
4914:
4915: for (j=1;j<=npar;j++) {
4916: for (i=1;i<=npar;i++) x[i]=0;
4917: x[j]=1;
4918: lubksb(a,npar,indx,x);
4919: for (i=1;i<=npar;i++){
4920: matcov[i][j]=x[i];
4921: }
4922: }
4923:
4924: printf("\n#Hessian matrix#\n");
4925: fprintf(ficlog,"\n#Hessian matrix#\n");
4926: for (i=1;i<=npar;i++) {
4927: for (j=1;j<=npar;j++) {
1.203 brouard 4928: printf("%.6e ",hess[i][j]);
4929: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 4930: }
4931: printf("\n");
4932: fprintf(ficlog,"\n");
4933: }
4934:
1.203 brouard 4935: /* printf("\n#Covariance matrix#\n"); */
4936: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
4937: /* for (i=1;i<=npar;i++) { */
4938: /* for (j=1;j<=npar;j++) { */
4939: /* printf("%.6e ",matcov[i][j]); */
4940: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
4941: /* } */
4942: /* printf("\n"); */
4943: /* fprintf(ficlog,"\n"); */
4944: /* } */
4945:
1.126 brouard 4946: /* Recompute Inverse */
1.203 brouard 4947: /* for (i=1;i<=npar;i++) */
4948: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
4949: /* ludcmp(a,npar,indx,&pd); */
4950:
4951: /* printf("\n#Hessian matrix recomputed#\n"); */
4952:
4953: /* for (j=1;j<=npar;j++) { */
4954: /* for (i=1;i<=npar;i++) x[i]=0; */
4955: /* x[j]=1; */
4956: /* lubksb(a,npar,indx,x); */
4957: /* for (i=1;i<=npar;i++){ */
4958: /* y[i][j]=x[i]; */
4959: /* printf("%.3e ",y[i][j]); */
4960: /* fprintf(ficlog,"%.3e ",y[i][j]); */
4961: /* } */
4962: /* printf("\n"); */
4963: /* fprintf(ficlog,"\n"); */
4964: /* } */
4965:
4966: /* Verifying the inverse matrix */
4967: #ifdef DEBUGHESS
4968: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 4969:
1.203 brouard 4970: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
4971: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 4972:
4973: for (j=1;j<=npar;j++) {
4974: for (i=1;i<=npar;i++){
1.203 brouard 4975: printf("%.2f ",y[i][j]);
4976: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 4977: }
4978: printf("\n");
4979: fprintf(ficlog,"\n");
4980: }
1.203 brouard 4981: #endif
1.126 brouard 4982:
4983: free_matrix(a,1,npar,1,npar);
4984: free_matrix(y,1,npar,1,npar);
4985: free_vector(x,1,npar);
4986: free_ivector(indx,1,npar);
1.203 brouard 4987: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 4988:
4989:
4990: }
4991:
4992: /*************** hessian matrix ****************/
4993: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 4994: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 4995: int i;
4996: int l=1, lmax=20;
1.203 brouard 4997: double k1,k2, res, fx;
1.132 brouard 4998: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 4999: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
5000: int k=0,kmax=10;
5001: double l1;
5002:
5003: fx=func(x);
5004: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 5005: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 5006: l1=pow(10,l);
5007: delts=delt;
5008: for(k=1 ; k <kmax; k=k+1){
5009: delt = delta*(l1*k);
5010: p2[theta]=x[theta] +delt;
1.145 brouard 5011: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 5012: p2[theta]=x[theta]-delt;
5013: k2=func(p2)-fx;
5014: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 5015: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 5016:
1.203 brouard 5017: #ifdef DEBUGHESSII
1.126 brouard 5018: 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);
5019: 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);
5020: #endif
5021: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
5022: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
5023: k=kmax;
5024: }
5025: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 5026: k=kmax; l=lmax*10;
1.126 brouard 5027: }
5028: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
5029: delts=delt;
5030: }
1.203 brouard 5031: } /* End loop k */
1.126 brouard 5032: }
5033: delti[theta]=delts;
5034: return res;
5035:
5036: }
5037:
1.203 brouard 5038: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 5039: {
5040: int i;
1.164 brouard 5041: int l=1, lmax=20;
1.126 brouard 5042: double k1,k2,k3,k4,res,fx;
1.132 brouard 5043: double p2[MAXPARM+1];
1.203 brouard 5044: int k, kmax=1;
5045: double v1, v2, cv12, lc1, lc2;
1.208 brouard 5046:
5047: int firstime=0;
1.203 brouard 5048:
1.126 brouard 5049: fx=func(x);
1.203 brouard 5050: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 5051: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 5052: p2[thetai]=x[thetai]+delti[thetai]*k;
5053: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 5054: k1=func(p2)-fx;
5055:
1.203 brouard 5056: p2[thetai]=x[thetai]+delti[thetai]*k;
5057: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 5058: k2=func(p2)-fx;
5059:
1.203 brouard 5060: p2[thetai]=x[thetai]-delti[thetai]*k;
5061: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 5062: k3=func(p2)-fx;
5063:
1.203 brouard 5064: p2[thetai]=x[thetai]-delti[thetai]*k;
5065: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 5066: k4=func(p2)-fx;
1.203 brouard 5067: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
5068: if(k1*k2*k3*k4 <0.){
1.208 brouard 5069: firstime=1;
1.203 brouard 5070: kmax=kmax+10;
1.208 brouard 5071: }
5072: if(kmax >=10 || firstime ==1){
1.246 brouard 5073: 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);
5074: 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 5075: 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);
5076: 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);
5077: }
5078: #ifdef DEBUGHESSIJ
5079: v1=hess[thetai][thetai];
5080: v2=hess[thetaj][thetaj];
5081: cv12=res;
5082: /* Computing eigen value of Hessian matrix */
5083: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
5084: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
5085: if ((lc2 <0) || (lc1 <0) ){
5086: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
5087: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
5088: 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);
5089: 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);
5090: }
1.126 brouard 5091: #endif
5092: }
5093: return res;
5094: }
5095:
1.203 brouard 5096: /* Not done yet: Was supposed to fix if not exactly at the maximum */
5097: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
5098: /* { */
5099: /* int i; */
5100: /* int l=1, lmax=20; */
5101: /* double k1,k2,k3,k4,res,fx; */
5102: /* double p2[MAXPARM+1]; */
5103: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
5104: /* int k=0,kmax=10; */
5105: /* double l1; */
5106:
5107: /* fx=func(x); */
5108: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
5109: /* l1=pow(10,l); */
5110: /* delts=delt; */
5111: /* for(k=1 ; k <kmax; k=k+1){ */
5112: /* delt = delti*(l1*k); */
5113: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
5114: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
5115: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
5116: /* k1=func(p2)-fx; */
5117:
5118: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
5119: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
5120: /* k2=func(p2)-fx; */
5121:
5122: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
5123: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
5124: /* k3=func(p2)-fx; */
5125:
5126: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
5127: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
5128: /* k4=func(p2)-fx; */
5129: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
5130: /* #ifdef DEBUGHESSIJ */
5131: /* 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); */
5132: /* 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); */
5133: /* #endif */
5134: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
5135: /* k=kmax; */
5136: /* } */
5137: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
5138: /* k=kmax; l=lmax*10; */
5139: /* } */
5140: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
5141: /* delts=delt; */
5142: /* } */
5143: /* } /\* End loop k *\/ */
5144: /* } */
5145: /* delti[theta]=delts; */
5146: /* return res; */
5147: /* } */
5148:
5149:
1.126 brouard 5150: /************** Inverse of matrix **************/
5151: void ludcmp(double **a, int n, int *indx, double *d)
5152: {
5153: int i,imax,j,k;
5154: double big,dum,sum,temp;
5155: double *vv;
5156:
5157: vv=vector(1,n);
5158: *d=1.0;
5159: for (i=1;i<=n;i++) {
5160: big=0.0;
5161: for (j=1;j<=n;j++)
5162: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 5163: if (big == 0.0){
5164: printf(" Singular Hessian matrix at row %d:\n",i);
5165: for (j=1;j<=n;j++) {
5166: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
5167: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
5168: }
5169: fflush(ficlog);
5170: fclose(ficlog);
5171: nrerror("Singular matrix in routine ludcmp");
5172: }
1.126 brouard 5173: vv[i]=1.0/big;
5174: }
5175: for (j=1;j<=n;j++) {
5176: for (i=1;i<j;i++) {
5177: sum=a[i][j];
5178: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
5179: a[i][j]=sum;
5180: }
5181: big=0.0;
5182: for (i=j;i<=n;i++) {
5183: sum=a[i][j];
5184: for (k=1;k<j;k++)
5185: sum -= a[i][k]*a[k][j];
5186: a[i][j]=sum;
5187: if ( (dum=vv[i]*fabs(sum)) >= big) {
5188: big=dum;
5189: imax=i;
5190: }
5191: }
5192: if (j != imax) {
5193: for (k=1;k<=n;k++) {
5194: dum=a[imax][k];
5195: a[imax][k]=a[j][k];
5196: a[j][k]=dum;
5197: }
5198: *d = -(*d);
5199: vv[imax]=vv[j];
5200: }
5201: indx[j]=imax;
5202: if (a[j][j] == 0.0) a[j][j]=TINY;
5203: if (j != n) {
5204: dum=1.0/(a[j][j]);
5205: for (i=j+1;i<=n;i++) a[i][j] *= dum;
5206: }
5207: }
5208: free_vector(vv,1,n); /* Doesn't work */
5209: ;
5210: }
5211:
5212: void lubksb(double **a, int n, int *indx, double b[])
5213: {
5214: int i,ii=0,ip,j;
5215: double sum;
5216:
5217: for (i=1;i<=n;i++) {
5218: ip=indx[i];
5219: sum=b[ip];
5220: b[ip]=b[i];
5221: if (ii)
5222: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
5223: else if (sum) ii=i;
5224: b[i]=sum;
5225: }
5226: for (i=n;i>=1;i--) {
5227: sum=b[i];
5228: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
5229: b[i]=sum/a[i][i];
5230: }
5231: }
5232:
5233: void pstamp(FILE *fichier)
5234: {
1.196 brouard 5235: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 5236: }
5237:
1.297 brouard 5238: void date2dmy(double date,double *day, double *month, double *year){
5239: double yp=0., yp1=0., yp2=0.;
5240:
5241: yp1=modf(date,&yp);/* extracts integral of date in yp and
5242: fractional in yp1 */
5243: *year=yp;
5244: yp2=modf((yp1*12),&yp);
5245: *month=yp;
5246: yp1=modf((yp2*30.5),&yp);
5247: *day=yp;
5248: if(*day==0) *day=1;
5249: if(*month==0) *month=1;
5250: }
5251:
1.253 brouard 5252:
5253:
1.126 brouard 5254: /************ Frequencies ********************/
1.251 brouard 5255: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 5256: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
5257: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 5258: { /* Some frequencies as well as proposing some starting values */
1.332 brouard 5259: /* Frequencies of any combination of dummy covariate used in the model equation */
1.265 brouard 5260: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 5261: int iind=0, iage=0;
5262: int mi; /* Effective wave */
5263: int first;
5264: double ***freq; /* Frequencies */
1.268 brouard 5265: 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 */
5266: 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 5267: double *meanq, *stdq, *idq;
1.226 brouard 5268: double **meanqt;
5269: double *pp, **prop, *posprop, *pospropt;
5270: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
5271: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
5272: double agebegin, ageend;
5273:
5274: pp=vector(1,nlstate);
1.251 brouard 5275: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 5276: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
5277: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
5278: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
5279: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 5280: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 5281: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 5282: meanqt=matrix(1,lastpass,1,nqtveff);
5283: strcpy(fileresp,"P_");
5284: strcat(fileresp,fileresu);
5285: /*strcat(fileresphtm,fileresu);*/
5286: if((ficresp=fopen(fileresp,"w"))==NULL) {
5287: printf("Problem with prevalence resultfile: %s\n", fileresp);
5288: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
5289: exit(0);
5290: }
1.240 brouard 5291:
1.226 brouard 5292: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
5293: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
5294: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
5295: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
5296: fflush(ficlog);
5297: exit(70);
5298: }
5299: else{
5300: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 5301: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 5302: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 5303: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
5304: }
1.319 brouard 5305: 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 5306:
1.226 brouard 5307: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
5308: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
5309: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
5310: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
5311: fflush(ficlog);
5312: exit(70);
1.240 brouard 5313: } else{
1.226 brouard 5314: 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 5315: ,<hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 5316: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 5317: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
5318: }
1.319 brouard 5319: 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 5320:
1.253 brouard 5321: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
5322: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 5323: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 5324: j1=0;
1.126 brouard 5325:
1.227 brouard 5326: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
1.335 brouard 5327: j=cptcoveff; /* Only simple dummy covariates used in the model */
1.330 brouard 5328: /* j=cptcovn; /\* Only dummy covariates of the model *\/ */
1.226 brouard 5329: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 5330:
5331:
1.226 brouard 5332: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
5333: reference=low_education V1=0,V2=0
5334: med_educ V1=1 V2=0,
5335: high_educ V1=0 V2=1
1.330 brouard 5336: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcovn
1.226 brouard 5337: */
1.249 brouard 5338: dateintsum=0;
5339: k2cpt=0;
5340:
1.253 brouard 5341: if(cptcoveff == 0 )
1.265 brouard 5342: nl=1; /* Constant and age model only */
1.253 brouard 5343: else
5344: nl=2;
1.265 brouard 5345:
5346: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
5347: /* Loop on nj=1 or 2 if dummy covariates j!=0
1.335 brouard 5348: * Loop on j1(1 to 2**cptcoveff) covariate combination
1.265 brouard 5349: * freq[s1][s2][iage] =0.
5350: * Loop on iind
5351: * ++freq[s1][s2][iage] weighted
5352: * end iind
5353: * if covariate and j!0
5354: * headers Variable on one line
5355: * endif cov j!=0
5356: * header of frequency table by age
5357: * Loop on age
5358: * pp[s1]+=freq[s1][s2][iage] weighted
5359: * pos+=freq[s1][s2][iage] weighted
5360: * Loop on s1 initial state
5361: * fprintf(ficresp
5362: * end s1
5363: * end age
5364: * if j!=0 computes starting values
5365: * end compute starting values
5366: * end j1
5367: * end nl
5368: */
1.253 brouard 5369: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
5370: if(nj==1)
5371: j=0; /* First pass for the constant */
1.265 brouard 5372: else{
1.335 brouard 5373: 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 5374: }
1.251 brouard 5375: first=1;
1.332 brouard 5376: 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 5377: posproptt=0.;
1.330 brouard 5378: /*printf("cptcovn=%d Tvaraff=%d", cptcovn,Tvaraff[1]);
1.251 brouard 5379: scanf("%d", i);*/
5380: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 5381: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 5382: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 5383: freq[i][s2][m]=0;
1.251 brouard 5384:
5385: for (i=1; i<=nlstate; i++) {
1.240 brouard 5386: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 5387: prop[i][m]=0;
5388: posprop[i]=0;
5389: pospropt[i]=0;
5390: }
1.283 brouard 5391: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 5392: idq[z1]=0.;
5393: meanq[z1]=0.;
5394: stdq[z1]=0.;
1.283 brouard 5395: }
5396: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 5397: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 5398: /* meanqt[m][z1]=0.; */
5399: /* } */
5400: /* } */
1.251 brouard 5401: /* dateintsum=0; */
5402: /* k2cpt=0; */
5403:
1.265 brouard 5404: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 5405: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
5406: bool=1;
5407: if(j !=0){
5408: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
1.335 brouard 5409: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
5410: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
1.251 brouard 5411: /* if(Tvaraff[z1] ==-20){ */
5412: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
5413: /* }else if(Tvaraff[z1] ==-10){ */
5414: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
1.330 brouard 5415: /* }else */ /* TODO TODO codtabm(j1,z1) or codtabm(j1,Tvaraff[z1]]z1)*/
1.335 brouard 5416: /* 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); */
5417: if(Tvaraff[z1]<1 || Tvaraff[z1]>=NCOVMAX)
1.338 brouard 5418: printf("Error Tvaraff[z1]=%d<1 or >=%d, cptcoveff=%d model=1+age+%s\n",Tvaraff[z1],NCOVMAX, cptcoveff, model);
1.332 brouard 5419: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]){ /* for combination j1 of covariates */
1.265 brouard 5420: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 5421: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
1.332 brouard 5422: /* 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", */
5423: /* bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),*/
5424: /* j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
1.251 brouard 5425: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
5426: } /* Onlyf fixed */
5427: } /* end z1 */
1.335 brouard 5428: } /* cptcoveff > 0 */
1.251 brouard 5429: } /* end any */
5430: }/* end j==0 */
1.265 brouard 5431: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 5432: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 5433: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 5434: m=mw[mi][iind];
5435: if(j!=0){
5436: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
1.335 brouard 5437: for (z1=1; z1<=cptcoveff; z1++) {
1.251 brouard 5438: if( Fixed[Tmodelind[z1]]==1){
1.341 brouard 5439: /* iv= Tvar[Tmodelind[z1]]-ncovcol-nqv; /\* Good *\/ */
5440: iv= Tvar[Tmodelind[z1]]; /* Good *//* because cotvar starts now at first at ncovcol+nqv+ntv */
1.332 brouard 5441: 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 5442: value is -1, we don't select. It differs from the
5443: constant and age model which counts them. */
5444: bool=0; /* not selected */
5445: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
1.334 brouard 5446: /* i1=Tvaraff[z1]; */
5447: /* i2=TnsdVar[i1]; */
5448: /* i3=nbcode[i1][i2]; */
5449: /* i4=covar[i1][iind]; */
5450: /* if(i4 != i3){ */
5451: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) { /* Bug valgrind */
1.251 brouard 5452: bool=0;
5453: }
5454: }
5455: }
5456: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
5457: } /* end j==0 */
5458: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 5459: if(bool==1){ /*Selected */
1.251 brouard 5460: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
5461: and mw[mi+1][iind]. dh depends on stepm. */
5462: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
5463: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
5464: if(m >=firstpass && m <=lastpass){
5465: k2=anint[m][iind]+(mint[m][iind]/12.);
5466: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
5467: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
5468: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
5469: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
5470: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
5471: if (m<lastpass) {
5472: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
5473: /* 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]); */
5474: if(s[m][iind]==-1)
5475: 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.));
5476: 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 5477: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean on known values only */
5478: if(!isnan(covar[ncovcol+z1][iind])){
1.332 brouard 5479: idq[z1]=idq[z1]+weight[iind];
5480: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
5481: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; *//*error*/
5482: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
1.311 brouard 5483: }
1.284 brouard 5484: }
1.251 brouard 5485: /* if((int)agev[m][iind] == 55) */
5486: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
5487: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
5488: 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 5489: }
1.251 brouard 5490: } /* end if between passes */
5491: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
5492: dateintsum=dateintsum+k2; /* on all covariates ?*/
5493: k2cpt++;
5494: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 5495: }
1.251 brouard 5496: }else{
5497: bool=1;
5498: }/* end bool 2 */
5499: } /* end m */
1.284 brouard 5500: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
5501: /* idq[z1]=idq[z1]+weight[iind]; */
5502: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
5503: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
5504: /* } */
1.251 brouard 5505: } /* end bool */
5506: } /* end iind = 1 to imx */
1.319 brouard 5507: /* prop[s][age] is fed for any initial and valid live state as well as
1.251 brouard 5508: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
5509:
5510:
5511: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.335 brouard 5512: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
1.265 brouard 5513: pstamp(ficresp);
1.335 brouard 5514: if (cptcoveff>0 && j!=0){
1.265 brouard 5515: pstamp(ficresp);
1.251 brouard 5516: printf( "\n#********** Variable ");
5517: fprintf(ficresp, "\n#********** Variable ");
5518: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
5519: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
5520: fprintf(ficlog, "\n#********** Variable ");
1.340 brouard 5521: for (z1=1; z1<=cptcoveff; z1++){
1.251 brouard 5522: if(!FixedV[Tvaraff[z1]]){
1.330 brouard 5523: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5524: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5525: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5526: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5527: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.250 brouard 5528: }else{
1.330 brouard 5529: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5530: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5531: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5532: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5533: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.251 brouard 5534: }
5535: }
5536: printf( "**********\n#");
5537: fprintf(ficresp, "**********\n#");
5538: fprintf(ficresphtm, "**********</h3>\n");
5539: fprintf(ficresphtmfr, "**********</h3>\n");
5540: fprintf(ficlog, "**********\n");
5541: }
1.284 brouard 5542: /*
5543: Printing means of quantitative variables if any
5544: */
5545: for (z1=1; z1<= nqfveff; z1++) {
1.311 brouard 5546: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.3g (weighted) individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.312 brouard 5547: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
1.284 brouard 5548: if(weightopt==1){
5549: printf(" Weighted mean and standard deviation of");
5550: fprintf(ficlog," Weighted mean and standard deviation of");
5551: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
5552: }
1.311 brouard 5553: /* mu = \frac{w x}{\sum w}
5554: var = \frac{\sum w (x-mu)^2}{\sum w} = \frac{w x^2}{\sum w} - mu^2
5555: */
5556: 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]));
5557: 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]));
5558: 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 5559: }
5560: /* for (z1=1; z1<= nqtveff; z1++) { */
5561: /* for(m=1;m<=lastpass;m++){ */
5562: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
5563: /* } */
5564: /* } */
1.283 brouard 5565:
1.251 brouard 5566: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.335 brouard 5567: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
1.265 brouard 5568: fprintf(ficresp, " Age");
1.335 brouard 5569: if(nj==2) for (z1=1; z1<=cptcoveff; z1++) {
5570: 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]]);
5571: fprintf(ficresp, " V%d=%d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5572: }
1.251 brouard 5573: for(i=1; i<=nlstate;i++) {
1.335 brouard 5574: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 5575: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
5576: }
1.335 brouard 5577: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 5578: fprintf(ficresphtm, "\n");
5579:
5580: /* Header of frequency table by age */
5581: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
5582: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 5583: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 5584: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5585: if(s2!=0 && m!=0)
5586: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 5587: }
1.226 brouard 5588: }
1.251 brouard 5589: fprintf(ficresphtmfr, "\n");
5590:
5591: /* For each age */
5592: for(iage=iagemin; iage <= iagemax+3; iage++){
5593: fprintf(ficresphtm,"<tr>");
5594: if(iage==iagemax+1){
5595: fprintf(ficlog,"1");
5596: fprintf(ficresphtmfr,"<tr><th>0</th> ");
5597: }else if(iage==iagemax+2){
5598: fprintf(ficlog,"0");
5599: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
5600: }else if(iage==iagemax+3){
5601: fprintf(ficlog,"Total");
5602: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
5603: }else{
1.240 brouard 5604: if(first==1){
1.251 brouard 5605: first=0;
5606: printf("See log file for details...\n");
5607: }
5608: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
5609: fprintf(ficlog,"Age %d", iage);
5610: }
1.265 brouard 5611: for(s1=1; s1 <=nlstate ; s1++){
5612: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
5613: pp[s1] += freq[s1][m][iage];
1.251 brouard 5614: }
1.265 brouard 5615: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5616: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 5617: pos += freq[s1][m][iage];
5618: if(pp[s1]>=1.e-10){
1.251 brouard 5619: if(first==1){
1.265 brouard 5620: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5621: }
1.265 brouard 5622: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5623: }else{
5624: if(first==1)
1.265 brouard 5625: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
5626: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 5627: }
5628: }
5629:
1.265 brouard 5630: for(s1=1; s1 <=nlstate ; s1++){
5631: /* posprop[s1]=0; */
5632: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
5633: pp[s1] += freq[s1][m][iage];
5634: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
5635:
5636: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
5637: pos += pp[s1]; /* pos is the total number of transitions until this age */
5638: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
5639: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5640: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
5641: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5642: }
5643:
5644: /* Writing ficresp */
1.335 brouard 5645: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5646: if( iage <= iagemax){
5647: fprintf(ficresp," %d",iage);
5648: }
5649: }else if( nj==2){
5650: if( iage <= iagemax){
5651: fprintf(ficresp," %d",iage);
1.335 brouard 5652: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.265 brouard 5653: }
1.240 brouard 5654: }
1.265 brouard 5655: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 5656: if(pos>=1.e-5){
1.251 brouard 5657: if(first==1)
1.265 brouard 5658: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
5659: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 5660: }else{
5661: if(first==1)
1.265 brouard 5662: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
5663: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 5664: }
5665: if( iage <= iagemax){
5666: if(pos>=1.e-5){
1.335 brouard 5667: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5668: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5669: }else if( nj==2){
5670: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5671: }
5672: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5673: /*probs[iage][s1][j1]= pp[s1]/pos;*/
5674: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
5675: } else{
1.335 brouard 5676: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
1.265 brouard 5677: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 5678: }
1.240 brouard 5679: }
1.265 brouard 5680: pospropt[s1] +=posprop[s1];
5681: } /* end loop s1 */
1.251 brouard 5682: /* pospropt=0.; */
1.265 brouard 5683: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 5684: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5685: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 5686: if(first==1){
1.265 brouard 5687: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5688: }
1.265 brouard 5689: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
5690: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5691: }
1.265 brouard 5692: if(s1!=0 && m!=0)
5693: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 5694: }
1.265 brouard 5695: } /* end loop s1 */
1.251 brouard 5696: posproptt=0.;
1.265 brouard 5697: for(s1=1; s1 <=nlstate; s1++){
5698: posproptt += pospropt[s1];
1.251 brouard 5699: }
5700: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 5701: fprintf(ficresphtm,"</tr>\n");
1.335 brouard 5702: if((cptcoveff==0 && nj==1)|| nj==2 ) {
1.265 brouard 5703: if(iage <= iagemax)
5704: fprintf(ficresp,"\n");
1.240 brouard 5705: }
1.251 brouard 5706: if(first==1)
5707: printf("Others in log...\n");
5708: fprintf(ficlog,"\n");
5709: } /* end loop age iage */
1.265 brouard 5710:
1.251 brouard 5711: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 5712: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5713: if(posproptt < 1.e-5){
1.265 brouard 5714: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 5715: }else{
1.265 brouard 5716: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 5717: }
1.226 brouard 5718: }
1.251 brouard 5719: fprintf(ficresphtm,"</tr>\n");
5720: fprintf(ficresphtm,"</table>\n");
5721: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 5722: if(posproptt < 1.e-5){
1.251 brouard 5723: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
5724: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 5725: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
5726: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 5727: invalidvarcomb[j1]=1;
1.226 brouard 5728: }else{
1.338 brouard 5729: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced (or no resultline).</p>",j1);
1.251 brouard 5730: invalidvarcomb[j1]=0;
1.226 brouard 5731: }
1.251 brouard 5732: fprintf(ficresphtmfr,"</table>\n");
5733: fprintf(ficlog,"\n");
5734: if(j!=0){
5735: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 5736: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5737: for(k=1; k <=(nlstate+ndeath); k++){
5738: if (k != i) {
1.265 brouard 5739: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 5740: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 5741: if(j1==1){ /* All dummy covariates to zero */
5742: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
5743: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 5744: printf("%d%d ",i,k);
5745: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5746: 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]));
5747: 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]));
5748: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 5749: }
1.253 brouard 5750: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
5751: for(iage=iagemin; iage <= iagemax+3; iage++){
5752: x[iage]= (double)iage;
5753: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 5754: /* 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 5755: }
1.268 brouard 5756: /* Some are not finite, but linreg will ignore these ages */
5757: no=0;
1.253 brouard 5758: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 5759: pstart[s1]=b;
5760: pstart[s1-1]=a;
1.252 brouard 5761: }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 */
5762: 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]);
5763: 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 5764: 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 5765: printf("%d%d ",i,k);
5766: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5767: 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 5768: }else{ /* Other cases, like quantitative fixed or varying covariates */
5769: ;
5770: }
5771: /* printf("%12.7f )", param[i][jj][k]); */
5772: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5773: s1++;
1.251 brouard 5774: } /* end jj */
5775: } /* end k!= i */
5776: } /* end k */
1.265 brouard 5777: } /* end i, s1 */
1.251 brouard 5778: } /* end j !=0 */
5779: } /* end selected combination of covariate j1 */
5780: if(j==0){ /* We can estimate starting values from the occurences in each case */
5781: printf("#Freqsummary: Starting values for the constants:\n");
5782: fprintf(ficlog,"\n");
1.265 brouard 5783: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5784: for(k=1; k <=(nlstate+ndeath); k++){
5785: if (k != i) {
5786: printf("%d%d ",i,k);
5787: fprintf(ficlog,"%d%d ",i,k);
5788: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 5789: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 5790: if(jj==1){ /* Age has to be done */
1.265 brouard 5791: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
5792: 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]));
5793: 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 5794: }
5795: /* printf("%12.7f )", param[i][jj][k]); */
5796: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5797: s1++;
1.250 brouard 5798: }
1.251 brouard 5799: printf("\n");
5800: fprintf(ficlog,"\n");
1.250 brouard 5801: }
5802: }
1.284 brouard 5803: } /* end of state i */
1.251 brouard 5804: printf("#Freqsummary\n");
5805: fprintf(ficlog,"\n");
1.265 brouard 5806: for(s1=-1; s1 <=nlstate+ndeath; s1++){
5807: for(s2=-1; s2 <=nlstate+ndeath; s2++){
5808: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
5809: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5810: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5811: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
5812: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
5813: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 5814: /* } */
5815: }
1.265 brouard 5816: } /* end loop s1 */
1.251 brouard 5817:
5818: printf("\n");
5819: fprintf(ficlog,"\n");
5820: } /* end j=0 */
1.249 brouard 5821: } /* end j */
1.252 brouard 5822:
1.253 brouard 5823: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 5824: for(i=1, jk=1; i <=nlstate; i++){
5825: for(j=1; j <=nlstate+ndeath; j++){
5826: if(j!=i){
5827: /*ca[0]= k+'a'-1;ca[1]='\0';*/
5828: printf("%1d%1d",i,j);
5829: fprintf(ficparo,"%1d%1d",i,j);
5830: for(k=1; k<=ncovmodel;k++){
5831: /* printf(" %lf",param[i][j][k]); */
5832: /* fprintf(ficparo," %lf",param[i][j][k]); */
5833: p[jk]=pstart[jk];
5834: printf(" %f ",pstart[jk]);
5835: fprintf(ficparo," %f ",pstart[jk]);
5836: jk++;
5837: }
5838: printf("\n");
5839: fprintf(ficparo,"\n");
5840: }
5841: }
5842: }
5843: } /* end mle=-2 */
1.226 brouard 5844: dateintmean=dateintsum/k2cpt;
1.296 brouard 5845: date2dmy(dateintmean,&jintmean,&mintmean,&aintmean);
1.240 brouard 5846:
1.226 brouard 5847: fclose(ficresp);
5848: fclose(ficresphtm);
5849: fclose(ficresphtmfr);
1.283 brouard 5850: free_vector(idq,1,nqfveff);
1.226 brouard 5851: free_vector(meanq,1,nqfveff);
1.284 brouard 5852: free_vector(stdq,1,nqfveff);
1.226 brouard 5853: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 5854: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
5855: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 5856: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5857: free_vector(pospropt,1,nlstate);
5858: free_vector(posprop,1,nlstate);
1.251 brouard 5859: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5860: free_vector(pp,1,nlstate);
5861: /* End of freqsummary */
5862: }
1.126 brouard 5863:
1.268 brouard 5864: /* Simple linear regression */
5865: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
5866:
5867: /* y=a+bx regression */
5868: double sumx = 0.0; /* sum of x */
5869: double sumx2 = 0.0; /* sum of x**2 */
5870: double sumxy = 0.0; /* sum of x * y */
5871: double sumy = 0.0; /* sum of y */
5872: double sumy2 = 0.0; /* sum of y**2 */
5873: double sume2 = 0.0; /* sum of square or residuals */
5874: double yhat;
5875:
5876: double denom=0;
5877: int i;
5878: int ne=*no;
5879:
5880: for ( i=ifi, ne=0;i<=ila;i++) {
5881: if(!isfinite(x[i]) || !isfinite(y[i])){
5882: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5883: continue;
5884: }
5885: ne=ne+1;
5886: sumx += x[i];
5887: sumx2 += x[i]*x[i];
5888: sumxy += x[i] * y[i];
5889: sumy += y[i];
5890: sumy2 += y[i]*y[i];
5891: denom = (ne * sumx2 - sumx*sumx);
5892: /* 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); */
5893: }
5894:
5895: denom = (ne * sumx2 - sumx*sumx);
5896: if (denom == 0) {
5897: // vertical, slope m is infinity
5898: *b = INFINITY;
5899: *a = 0;
5900: if (r) *r = 0;
5901: return 1;
5902: }
5903:
5904: *b = (ne * sumxy - sumx * sumy) / denom;
5905: *a = (sumy * sumx2 - sumx * sumxy) / denom;
5906: if (r!=NULL) {
5907: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
5908: sqrt((sumx2 - sumx*sumx/ne) *
5909: (sumy2 - sumy*sumy/ne));
5910: }
5911: *no=ne;
5912: for ( i=ifi, ne=0;i<=ila;i++) {
5913: if(!isfinite(x[i]) || !isfinite(y[i])){
5914: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5915: continue;
5916: }
5917: ne=ne+1;
5918: yhat = y[i] - *a -*b* x[i];
5919: sume2 += yhat * yhat ;
5920:
5921: denom = (ne * sumx2 - sumx*sumx);
5922: /* 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); */
5923: }
5924: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
5925: *sa= *sb * sqrt(sumx2/ne);
5926:
5927: return 0;
5928: }
5929:
1.126 brouard 5930: /************ Prevalence ********************/
1.227 brouard 5931: 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)
5932: {
5933: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
5934: in each health status at the date of interview (if between dateprev1 and dateprev2).
5935: We still use firstpass and lastpass as another selection.
5936: */
1.126 brouard 5937:
1.227 brouard 5938: int i, m, jk, j1, bool, z1,j, iv;
5939: int mi; /* Effective wave */
5940: int iage;
5941: double agebegin, ageend;
5942:
5943: double **prop;
5944: double posprop;
5945: double y2; /* in fractional years */
5946: int iagemin, iagemax;
5947: int first; /** to stop verbosity which is redirected to log file */
5948:
5949: iagemin= (int) agemin;
5950: iagemax= (int) agemax;
5951: /*pp=vector(1,nlstate);*/
1.251 brouard 5952: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5953: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
5954: j1=0;
1.222 brouard 5955:
1.227 brouard 5956: /*j=cptcoveff;*/
5957: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 5958:
1.288 brouard 5959: first=0;
1.335 brouard 5960: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of simple dummy covariates */
1.227 brouard 5961: for (i=1; i<=nlstate; i++)
1.251 brouard 5962: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 5963: prop[i][iage]=0.0;
5964: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
5965: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
5966: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
5967:
5968: for (i=1; i<=imx; i++) { /* Each individual */
5969: bool=1;
5970: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
5971: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
5972: m=mw[mi][i];
5973: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
5974: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
5975: for (z1=1; z1<=cptcoveff; z1++){
5976: if( Fixed[Tmodelind[z1]]==1){
1.341 brouard 5977: iv= Tvar[Tmodelind[z1]];/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
1.332 brouard 5978: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) /* iv=1 to ntv, right modality */
1.227 brouard 5979: bool=0;
5980: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
1.332 brouard 5981: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) {
1.227 brouard 5982: bool=0;
5983: }
5984: }
5985: if(bool==1){ /* Otherwise we skip that wave/person */
5986: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
5987: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
5988: if(m >=firstpass && m <=lastpass){
5989: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
5990: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
5991: if(agev[m][i]==0) agev[m][i]=iagemax+1;
5992: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 5993: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 5994: 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);
5995: exit(1);
5996: }
5997: if (s[m][i]>0 && s[m][i]<=nlstate) {
5998: /*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]]);*/
5999: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
6000: prop[s[m][i]][iagemax+3] += weight[i];
6001: } /* end valid statuses */
6002: } /* end selection of dates */
6003: } /* end selection of waves */
6004: } /* end bool */
6005: } /* end wave */
6006: } /* end individual */
6007: for(i=iagemin; i <= iagemax+3; i++){
6008: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
6009: posprop += prop[jk][i];
6010: }
6011:
6012: for(jk=1; jk <=nlstate ; jk++){
6013: if( i <= iagemax){
6014: if(posprop>=1.e-5){
6015: probs[i][jk][j1]= prop[jk][i]/posprop;
6016: } else{
1.288 brouard 6017: if(!first){
6018: first=1;
1.266 brouard 6019: 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]);
6020: }else{
1.288 brouard 6021: 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 6022: }
6023: }
6024: }
6025: }/* end jk */
6026: }/* end i */
1.222 brouard 6027: /*} *//* end i1 */
1.227 brouard 6028: } /* end j1 */
1.222 brouard 6029:
1.227 brouard 6030: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
6031: /*free_vector(pp,1,nlstate);*/
1.251 brouard 6032: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 6033: } /* End of prevalence */
1.126 brouard 6034:
6035: /************* Waves Concatenation ***************/
6036:
6037: 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)
6038: {
1.298 brouard 6039: /* 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 6040: Death is a valid wave (if date is known).
6041: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
6042: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
1.298 brouard 6043: and mw[mi+1][i]. dh depends on stepm. s[m][i] exists for any wave from firstpass to lastpass
1.227 brouard 6044: */
1.126 brouard 6045:
1.224 brouard 6046: int i=0, mi=0, m=0, mli=0;
1.126 brouard 6047: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
6048: double sum=0., jmean=0.;*/
1.224 brouard 6049: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 6050: int j, k=0,jk, ju, jl;
6051: double sum=0.;
6052: first=0;
1.214 brouard 6053: firstwo=0;
1.217 brouard 6054: firsthree=0;
1.218 brouard 6055: firstfour=0;
1.164 brouard 6056: jmin=100000;
1.126 brouard 6057: jmax=-1;
6058: jmean=0.;
1.224 brouard 6059:
6060: /* Treating live states */
1.214 brouard 6061: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 6062: mi=0; /* First valid wave */
1.227 brouard 6063: mli=0; /* Last valid wave */
1.309 brouard 6064: m=firstpass; /* Loop on waves */
6065: while(s[m][i] <= nlstate){ /* a live state or unknown state */
1.227 brouard 6066: 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 */
6067: mli=m-1;/* mw[++mi][i]=m-1; */
6068: }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 6069: 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 6070: mli=m;
1.224 brouard 6071: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
6072: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 6073: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 6074: }
1.309 brouard 6075: else{ /* m = lastpass, eventual special issue with warning */
1.224 brouard 6076: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 6077: break;
1.224 brouard 6078: #else
1.317 brouard 6079: 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 6080: if(firsthree == 0){
1.302 brouard 6081: 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 6082: firsthree=1;
1.317 brouard 6083: }else if(firsthree >=1 && firsthree < 10){
6084: 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);
6085: firsthree++;
6086: }else if(firsthree == 10){
6087: printf("Information, too many Information flags: no more reported to log either\n");
6088: fprintf(ficlog,"Information, too many Information flags: no more reported to log either\n");
6089: firsthree++;
6090: }else{
6091: firsthree++;
1.227 brouard 6092: }
1.309 brouard 6093: mw[++mi][i]=m; /* Valid transition with unknown status */
1.227 brouard 6094: mli=m;
6095: }
6096: if(s[m][i]==-2){ /* Vital status is really unknown */
6097: nbwarn++;
1.309 brouard 6098: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified?not a transition */
1.227 brouard 6099: 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);
6100: 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);
6101: }
6102: break;
6103: }
6104: break;
1.224 brouard 6105: #endif
1.227 brouard 6106: }/* End m >= lastpass */
1.126 brouard 6107: }/* end while */
1.224 brouard 6108:
1.227 brouard 6109: /* 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 6110: /* After last pass */
1.224 brouard 6111: /* Treating death states */
1.214 brouard 6112: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 6113: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
6114: /* } */
1.126 brouard 6115: mi++; /* Death is another wave */
6116: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 6117: /* Only death is a correct wave */
1.126 brouard 6118: mw[mi][i]=m;
1.257 brouard 6119: } /* else not in a death state */
1.224 brouard 6120: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 6121: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 6122: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.309 brouard 6123: 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 6124: nbwarn++;
6125: if(firstfiv==0){
1.309 brouard 6126: 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 6127: firstfiv=1;
6128: }else{
1.309 brouard 6129: 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 6130: }
1.309 brouard 6131: s[m][i]=nlstate+1; /* Fixing the status as death. Be careful if multiple death states */
6132: }else{ /* Month of Death occured afer last wave month, potential bias */
1.227 brouard 6133: nberr++;
6134: if(firstwo==0){
1.309 brouard 6135: 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 6136: firstwo=1;
6137: }
1.309 brouard 6138: 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 6139: }
1.257 brouard 6140: }else{ /* if date of interview is unknown */
1.227 brouard 6141: /* death is known but not confirmed by death status at any wave */
6142: if(firstfour==0){
1.309 brouard 6143: 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 6144: firstfour=1;
6145: }
1.309 brouard 6146: 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 6147: }
1.224 brouard 6148: } /* end if date of death is known */
6149: #endif
1.309 brouard 6150: wav[i]=mi; /* mi should be the last effective wave (or mli), */
6151: /* wav[i]=mw[mi][i]; */
1.126 brouard 6152: if(mi==0){
6153: nbwarn++;
6154: if(first==0){
1.227 brouard 6155: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
6156: first=1;
1.126 brouard 6157: }
6158: if(first==1){
1.227 brouard 6159: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 6160: }
6161: } /* end mi==0 */
6162: } /* End individuals */
1.214 brouard 6163: /* wav and mw are no more changed */
1.223 brouard 6164:
1.317 brouard 6165: printf("Information, you have to check %d informations which haven't been logged!\n",firsthree);
6166: fprintf(ficlog,"Information, you have to check %d informations which haven't been logged!\n",firsthree);
6167:
6168:
1.126 brouard 6169: for(i=1; i<=imx; i++){
6170: for(mi=1; mi<wav[i];mi++){
6171: if (stepm <=0)
1.227 brouard 6172: dh[mi][i]=1;
1.126 brouard 6173: else{
1.260 brouard 6174: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 6175: if (agedc[i] < 2*AGESUP) {
6176: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
6177: if(j==0) j=1; /* Survives at least one month after exam */
6178: else if(j<0){
6179: nberr++;
6180: 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]);
6181: j=1; /* Temporary Dangerous patch */
6182: 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);
6183: 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]);
6184: 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);
6185: }
6186: k=k+1;
6187: if (j >= jmax){
6188: jmax=j;
6189: ijmax=i;
6190: }
6191: if (j <= jmin){
6192: jmin=j;
6193: ijmin=i;
6194: }
6195: sum=sum+j;
6196: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
6197: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
6198: }
6199: }
6200: else{
6201: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 6202: /* 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 6203:
1.227 brouard 6204: k=k+1;
6205: if (j >= jmax) {
6206: jmax=j;
6207: ijmax=i;
6208: }
6209: else if (j <= jmin){
6210: jmin=j;
6211: ijmin=i;
6212: }
6213: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
6214: /*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]);*/
6215: if(j<0){
6216: nberr++;
6217: 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]);
6218: 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]);
6219: }
6220: sum=sum+j;
6221: }
6222: jk= j/stepm;
6223: jl= j -jk*stepm;
6224: ju= j -(jk+1)*stepm;
6225: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
6226: if(jl==0){
6227: dh[mi][i]=jk;
6228: bh[mi][i]=0;
6229: }else{ /* We want a negative bias in order to only have interpolation ie
6230: * to avoid the price of an extra matrix product in likelihood */
6231: dh[mi][i]=jk+1;
6232: bh[mi][i]=ju;
6233: }
6234: }else{
6235: if(jl <= -ju){
6236: dh[mi][i]=jk;
6237: bh[mi][i]=jl; /* bias is positive if real duration
6238: * is higher than the multiple of stepm and negative otherwise.
6239: */
6240: }
6241: else{
6242: dh[mi][i]=jk+1;
6243: bh[mi][i]=ju;
6244: }
6245: if(dh[mi][i]==0){
6246: dh[mi][i]=1; /* At least one step */
6247: bh[mi][i]=ju; /* At least one step */
6248: /* 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);*/
6249: }
6250: } /* end if mle */
1.126 brouard 6251: }
6252: } /* end wave */
6253: }
6254: jmean=sum/k;
6255: 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 6256: 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 6257: }
1.126 brouard 6258:
6259: /*********** Tricode ****************************/
1.220 brouard 6260: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 6261: {
6262: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
6263: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
6264: * Boring subroutine which should only output nbcode[Tvar[j]][k]
6265: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
6266: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
6267: */
1.130 brouard 6268:
1.242 brouard 6269: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
6270: int modmaxcovj=0; /* Modality max of covariates j */
6271: int cptcode=0; /* Modality max of covariates j */
6272: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 6273:
6274:
1.242 brouard 6275: /* cptcoveff=0; */
6276: /* *cptcov=0; */
1.126 brouard 6277:
1.242 brouard 6278: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 6279: for (k=1; k <= maxncov; k++)
6280: for(j=1; j<=2; j++)
6281: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 6282:
1.242 brouard 6283: /* Loop on covariates without age and products and no quantitative variable */
1.335 brouard 6284: 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 6285: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
1.343 brouard 6286: /* printf("Testing k=%d, cptcovt=%d\n",k, cptcovt); */
1.339 brouard 6287: if(Dummy[k]==0 && Typevar[k] !=1 && Typevar[k] != 2){ /* Dummy covariate and not age product nor fixed product */
1.242 brouard 6288: switch(Fixed[k]) {
6289: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
1.311 brouard 6290: modmaxcovj=0;
6291: modmincovj=0;
1.242 brouard 6292: 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 6293: /* 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 6294: ij=(int)(covar[Tvar[k]][i]);
6295: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
6296: * If product of Vn*Vm, still boolean *:
6297: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
6298: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
6299: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
6300: modality of the nth covariate of individual i. */
6301: if (ij > modmaxcovj)
6302: modmaxcovj=ij;
6303: else if (ij < modmincovj)
6304: modmincovj=ij;
1.287 brouard 6305: if (ij <0 || ij >1 ){
1.311 brouard 6306: printf("ERROR, IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
6307: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
6308: fflush(ficlog);
6309: exit(1);
1.287 brouard 6310: }
6311: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 6312: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
6313: exit(1);
6314: }else
6315: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
6316: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
6317: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
6318: /* getting the maximum value of the modality of the covariate
6319: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
6320: female ies 1, then modmaxcovj=1.
6321: */
6322: } /* end for loop on individuals i */
6323: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
6324: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
6325: cptcode=modmaxcovj;
6326: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
6327: /*for (i=0; i<=cptcode; i++) {*/
6328: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
6329: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
6330: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
6331: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
6332: if( j != -1){
6333: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
6334: covariate for which somebody answered excluding
6335: undefined. Usually 2: 0 and 1. */
6336: }
6337: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
6338: covariate for which somebody answered including
6339: undefined. Usually 3: -1, 0 and 1. */
6340: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
6341: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
6342: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 6343:
1.242 brouard 6344: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
6345: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
6346: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
6347: /* modmincovj=3; modmaxcovj = 7; */
6348: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
6349: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
6350: /* defining two dummy variables: variables V1_1 and V1_2.*/
6351: /* nbcode[Tvar[j]][ij]=k; */
6352: /* nbcode[Tvar[j]][1]=0; */
6353: /* nbcode[Tvar[j]][2]=1; */
6354: /* nbcode[Tvar[j]][3]=2; */
6355: /* To be continued (not working yet). */
6356: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 6357:
6358: /* 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*/
6359: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
6360: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
6361: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
6362: /*, could be restored in the future */
6363: 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 6364: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
6365: break;
6366: }
6367: ij++;
1.287 brouard 6368: 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 6369: cptcode = ij; /* New max modality for covar j */
6370: } /* end of loop on modality i=-1 to 1 or more */
6371: break;
6372: case 1: /* Testing on varying covariate, could be simple and
6373: * should look at waves or product of fixed *
6374: * varying. No time to test -1, assuming 0 and 1 only */
6375: ij=0;
6376: for(i=0; i<=1;i++){
6377: nbcode[Tvar[k]][++ij]=i;
6378: }
6379: break;
6380: default:
6381: break;
6382: } /* end switch */
6383: } /* end dummy test */
1.342 brouard 6384: if(Dummy[k]==1 && Typevar[k] !=1 && Fixed ==0){ /* Fixed Quantitative covariate and not age product */
1.311 brouard 6385: 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 6386: if(Tvar[k]<=0 || Tvar[k]>=NCOVMAX){
6387: printf("Error k=%d \n",k);
6388: exit(1);
6389: }
1.311 brouard 6390: if(isnan(covar[Tvar[k]][i])){
6391: printf("ERROR, IMaCh doesn't treat fixed quantitative covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
6392: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
6393: fflush(ficlog);
6394: exit(1);
6395: }
6396: }
1.335 brouard 6397: } /* end Quanti */
1.287 brouard 6398: } /* 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 6399:
6400: for (k=-1; k< maxncov; k++) Ndum[k]=0;
6401: /* Look at fixed dummy (single or product) covariates to check empty modalities */
6402: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
6403: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
6404: 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 */
6405: 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 */
6406: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
6407: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
6408:
6409: ij=0;
6410: /* 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 6411: 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 */
6412: /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
1.242 brouard 6413: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
6414: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
1.335 brouard 6415: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy simple and non empty in the model */
6416: /* Typevar[k] =0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
6417: /* 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 6418: /* If product not in single variable we don't print results */
6419: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
1.335 brouard 6420: ++ij;/* V5 + V4 + V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V1, *//* V5 quanti, V2 quanti, V4, V3, V1 dummies */
6421: /* k= 1 2 3 4 5 6 7 8 9 */
6422: /* Tvar[k]= 5 4 3 6 5 2 7 1 1 */
6423: /* ij 1 2 3 */
6424: /* Tvaraff[ij]= 4 3 1 */
6425: /* Tmodelind[ij]=2 3 9 */
6426: /* TmodelInvind[ij]=2 1 1 */
1.242 brouard 6427: 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*/
6428: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
6429: 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 */
6430: if(Fixed[k]!=0)
6431: anyvaryingduminmodel=1;
6432: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
6433: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
6434: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
6435: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
6436: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
6437: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
6438: }
6439: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
6440: /* ij--; */
6441: /* cptcoveff=ij; /\*Number of total covariates*\/ */
1.335 brouard 6442: *cptcov=ij; /* cptcov= Number of total real effective simple dummies (fixed or time arying) effective (used as cptcoveff in other functions)
1.242 brouard 6443: * because they can be excluded from the model and real
6444: * if in the model but excluded because missing values, but how to get k from ij?*/
6445: for(j=ij+1; j<= cptcovt; j++){
6446: Tvaraff[j]=0;
6447: Tmodelind[j]=0;
6448: }
6449: for(j=ntveff+1; j<= cptcovt; j++){
6450: TmodelInvind[j]=0;
6451: }
6452: /* To be sorted */
6453: ;
6454: }
1.126 brouard 6455:
1.145 brouard 6456:
1.126 brouard 6457: /*********** Health Expectancies ****************/
6458:
1.235 brouard 6459: 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 6460:
6461: {
6462: /* Health expectancies, no variances */
1.329 brouard 6463: /* cij is the combination in the list of combination of dummy covariates */
6464: /* strstart is a string of time at start of computing */
1.164 brouard 6465: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 6466: int nhstepma, nstepma; /* Decreasing with age */
6467: double age, agelim, hf;
6468: double ***p3mat;
6469: double eip;
6470:
1.238 brouard 6471: /* pstamp(ficreseij); */
1.126 brouard 6472: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
6473: fprintf(ficreseij,"# Age");
6474: for(i=1; i<=nlstate;i++){
6475: for(j=1; j<=nlstate;j++){
6476: fprintf(ficreseij," e%1d%1d ",i,j);
6477: }
6478: fprintf(ficreseij," e%1d. ",i);
6479: }
6480: fprintf(ficreseij,"\n");
6481:
6482:
6483: if(estepm < stepm){
6484: printf ("Problem %d lower than %d\n",estepm, stepm);
6485: }
6486: else hstepm=estepm;
6487: /* We compute the life expectancy from trapezoids spaced every estepm months
6488: * This is mainly to measure the difference between two models: for example
6489: * if stepm=24 months pijx are given only every 2 years and by summing them
6490: * we are calculating an estimate of the Life Expectancy assuming a linear
6491: * progression in between and thus overestimating or underestimating according
6492: * to the curvature of the survival function. If, for the same date, we
6493: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6494: * to compare the new estimate of Life expectancy with the same linear
6495: * hypothesis. A more precise result, taking into account a more precise
6496: * curvature will be obtained if estepm is as small as stepm. */
6497:
6498: /* For example we decided to compute the life expectancy with the smallest unit */
6499: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6500: nhstepm is the number of hstepm from age to agelim
6501: nstepm is the number of stepm from age to agelin.
1.270 brouard 6502: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 6503: and note for a fixed period like estepm months */
6504: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6505: survival function given by stepm (the optimization length). Unfortunately it
6506: means that if the survival funtion is printed only each two years of age and if
6507: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6508: results. So we changed our mind and took the option of the best precision.
6509: */
6510: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6511:
6512: agelim=AGESUP;
6513: /* If stepm=6 months */
6514: /* Computed by stepm unit matrices, product of hstepm matrices, stored
6515: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
6516:
6517: /* nhstepm age range expressed in number of stepm */
6518: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6519: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6520: /* if (stepm >= YEARM) hstepm=1;*/
6521: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6522: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6523:
6524: for (age=bage; age<=fage; age ++){
6525: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6526: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6527: /* if (stepm >= YEARM) hstepm=1;*/
6528: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
6529:
6530: /* If stepm=6 months */
6531: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6532: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
1.330 brouard 6533: /* 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 6534: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 6535:
6536: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6537:
6538: printf("%d|",(int)age);fflush(stdout);
6539: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6540:
6541: /* Computing expectancies */
6542: for(i=1; i<=nlstate;i++)
6543: for(j=1; j<=nlstate;j++)
6544: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6545: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
6546:
6547: /* 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]);*/
6548:
6549: }
6550:
6551: fprintf(ficreseij,"%3.0f",age );
6552: for(i=1; i<=nlstate;i++){
6553: eip=0;
6554: for(j=1; j<=nlstate;j++){
6555: eip +=eij[i][j][(int)age];
6556: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
6557: }
6558: fprintf(ficreseij,"%9.4f", eip );
6559: }
6560: fprintf(ficreseij,"\n");
6561:
6562: }
6563: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6564: printf("\n");
6565: fprintf(ficlog,"\n");
6566:
6567: }
6568:
1.235 brouard 6569: 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 6570:
6571: {
6572: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 6573: to initial status i, ei. .
1.126 brouard 6574: */
1.336 brouard 6575: /* Very time consuming function, but already optimized with precov */
1.126 brouard 6576: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
6577: int nhstepma, nstepma; /* Decreasing with age */
6578: double age, agelim, hf;
6579: double ***p3matp, ***p3matm, ***varhe;
6580: double **dnewm,**doldm;
6581: double *xp, *xm;
6582: double **gp, **gm;
6583: double ***gradg, ***trgradg;
6584: int theta;
6585:
6586: double eip, vip;
6587:
6588: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
6589: xp=vector(1,npar);
6590: xm=vector(1,npar);
6591: dnewm=matrix(1,nlstate*nlstate,1,npar);
6592: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
6593:
6594: pstamp(ficresstdeij);
6595: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
6596: fprintf(ficresstdeij,"# Age");
6597: for(i=1; i<=nlstate;i++){
6598: for(j=1; j<=nlstate;j++)
6599: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
6600: fprintf(ficresstdeij," e%1d. ",i);
6601: }
6602: fprintf(ficresstdeij,"\n");
6603:
6604: pstamp(ficrescveij);
6605: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
6606: fprintf(ficrescveij,"# Age");
6607: for(i=1; i<=nlstate;i++)
6608: for(j=1; j<=nlstate;j++){
6609: cptj= (j-1)*nlstate+i;
6610: for(i2=1; i2<=nlstate;i2++)
6611: for(j2=1; j2<=nlstate;j2++){
6612: cptj2= (j2-1)*nlstate+i2;
6613: if(cptj2 <= cptj)
6614: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
6615: }
6616: }
6617: fprintf(ficrescveij,"\n");
6618:
6619: if(estepm < stepm){
6620: printf ("Problem %d lower than %d\n",estepm, stepm);
6621: }
6622: else hstepm=estepm;
6623: /* We compute the life expectancy from trapezoids spaced every estepm months
6624: * This is mainly to measure the difference between two models: for example
6625: * if stepm=24 months pijx are given only every 2 years and by summing them
6626: * we are calculating an estimate of the Life Expectancy assuming a linear
6627: * progression in between and thus overestimating or underestimating according
6628: * to the curvature of the survival function. If, for the same date, we
6629: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6630: * to compare the new estimate of Life expectancy with the same linear
6631: * hypothesis. A more precise result, taking into account a more precise
6632: * curvature will be obtained if estepm is as small as stepm. */
6633:
6634: /* For example we decided to compute the life expectancy with the smallest unit */
6635: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6636: nhstepm is the number of hstepm from age to agelim
6637: nstepm is the number of stepm from age to agelin.
6638: Look at hpijx to understand the reason of that which relies in memory size
6639: and note for a fixed period like estepm months */
6640: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6641: survival function given by stepm (the optimization length). Unfortunately it
6642: means that if the survival funtion is printed only each two years of age and if
6643: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6644: results. So we changed our mind and took the option of the best precision.
6645: */
6646: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6647:
6648: /* If stepm=6 months */
6649: /* nhstepm age range expressed in number of stepm */
6650: agelim=AGESUP;
6651: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
6652: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6653: /* if (stepm >= YEARM) hstepm=1;*/
6654: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6655:
6656: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6657: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6658: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
6659: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
6660: gp=matrix(0,nhstepm,1,nlstate*nlstate);
6661: gm=matrix(0,nhstepm,1,nlstate*nlstate);
6662:
6663: for (age=bage; age<=fage; age ++){
6664: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6665: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6666: /* if (stepm >= YEARM) hstepm=1;*/
6667: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 6668:
1.126 brouard 6669: /* If stepm=6 months */
6670: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6671: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
6672:
6673: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 6674:
1.126 brouard 6675: /* Computing Variances of health expectancies */
6676: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
6677: decrease memory allocation */
6678: for(theta=1; theta <=npar; theta++){
6679: for(i=1; i<=npar; i++){
1.222 brouard 6680: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6681: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 6682: }
1.235 brouard 6683: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
6684: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 6685:
1.126 brouard 6686: for(j=1; j<= nlstate; j++){
1.222 brouard 6687: for(i=1; i<=nlstate; i++){
6688: for(h=0; h<=nhstepm-1; h++){
6689: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
6690: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
6691: }
6692: }
1.126 brouard 6693: }
1.218 brouard 6694:
1.126 brouard 6695: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 6696: for(h=0; h<=nhstepm-1; h++){
6697: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
6698: }
1.126 brouard 6699: }/* End theta */
6700:
6701:
6702: for(h=0; h<=nhstepm-1; h++)
6703: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 6704: for(theta=1; theta <=npar; theta++)
6705: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 6706:
1.218 brouard 6707:
1.222 brouard 6708: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 6709: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 6710: varhe[ij][ji][(int)age] =0.;
1.218 brouard 6711:
1.222 brouard 6712: printf("%d|",(int)age);fflush(stdout);
6713: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6714: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 6715: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 6716: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
6717: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
6718: for(ij=1;ij<=nlstate*nlstate;ij++)
6719: for(ji=1;ji<=nlstate*nlstate;ji++)
6720: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 6721: }
6722: }
1.320 brouard 6723: /* if((int)age ==50){ */
6724: /* printf(" age=%d cij=%d nres=%d varhe[%d][%d]=%f ",(int)age, cij, nres, 1,2,varhe[1][2]); */
6725: /* } */
1.126 brouard 6726: /* Computing expectancies */
1.235 brouard 6727: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 6728: for(i=1; i<=nlstate;i++)
6729: for(j=1; j<=nlstate;j++)
1.222 brouard 6730: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6731: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 6732:
1.222 brouard 6733: /* 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 6734:
1.222 brouard 6735: }
1.269 brouard 6736:
6737: /* Standard deviation of expectancies ij */
1.126 brouard 6738: fprintf(ficresstdeij,"%3.0f",age );
6739: for(i=1; i<=nlstate;i++){
6740: eip=0.;
6741: vip=0.;
6742: for(j=1; j<=nlstate;j++){
1.222 brouard 6743: eip += eij[i][j][(int)age];
6744: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
6745: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
6746: 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 6747: }
6748: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
6749: }
6750: fprintf(ficresstdeij,"\n");
1.218 brouard 6751:
1.269 brouard 6752: /* Variance of expectancies ij */
1.126 brouard 6753: fprintf(ficrescveij,"%3.0f",age );
6754: for(i=1; i<=nlstate;i++)
6755: for(j=1; j<=nlstate;j++){
1.222 brouard 6756: cptj= (j-1)*nlstate+i;
6757: for(i2=1; i2<=nlstate;i2++)
6758: for(j2=1; j2<=nlstate;j2++){
6759: cptj2= (j2-1)*nlstate+i2;
6760: if(cptj2 <= cptj)
6761: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
6762: }
1.126 brouard 6763: }
6764: fprintf(ficrescveij,"\n");
1.218 brouard 6765:
1.126 brouard 6766: }
6767: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
6768: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
6769: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
6770: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
6771: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6772: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6773: printf("\n");
6774: fprintf(ficlog,"\n");
1.218 brouard 6775:
1.126 brouard 6776: free_vector(xm,1,npar);
6777: free_vector(xp,1,npar);
6778: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
6779: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
6780: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
6781: }
1.218 brouard 6782:
1.126 brouard 6783: /************ Variance ******************/
1.235 brouard 6784: 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 6785: {
1.279 brouard 6786: /** Variance of health expectancies
6787: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
6788: * double **newm;
6789: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
6790: */
1.218 brouard 6791:
6792: /* int movingaverage(); */
6793: double **dnewm,**doldm;
6794: double **dnewmp,**doldmp;
6795: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 6796: int first=0;
1.218 brouard 6797: int k;
6798: double *xp;
1.279 brouard 6799: double **gp, **gm; /**< for var eij */
6800: double ***gradg, ***trgradg; /**< for var eij */
6801: double **gradgp, **trgradgp; /**< for var p point j */
6802: double *gpp, *gmp; /**< for var p point j */
6803: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 6804: double ***p3mat;
6805: double age,agelim, hf;
6806: /* double ***mobaverage; */
6807: int theta;
6808: char digit[4];
6809: char digitp[25];
6810:
6811: char fileresprobmorprev[FILENAMELENGTH];
6812:
6813: if(popbased==1){
6814: if(mobilav!=0)
6815: strcpy(digitp,"-POPULBASED-MOBILAV_");
6816: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
6817: }
6818: else
6819: strcpy(digitp,"-STABLBASED_");
1.126 brouard 6820:
1.218 brouard 6821: /* if (mobilav!=0) { */
6822: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6823: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
6824: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
6825: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
6826: /* } */
6827: /* } */
6828:
6829: strcpy(fileresprobmorprev,"PRMORPREV-");
6830: sprintf(digit,"%-d",ij);
6831: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
6832: strcat(fileresprobmorprev,digit); /* Tvar to be done */
6833: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
6834: strcat(fileresprobmorprev,fileresu);
6835: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
6836: printf("Problem with resultfile: %s\n", fileresprobmorprev);
6837: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
6838: }
6839: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
6840: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
6841: pstamp(ficresprobmorprev);
6842: 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 6843: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
1.337 brouard 6844:
6845: /* We use TinvDoQresult[nres][resultmodel[nres][j] we sort according to the equation model and the resultline: it is a choice */
6846: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ /\* To be done*\/ */
6847: /* fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
6848: /* } */
6849: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */ /* To be done*/
1.344 brouard 6850: /* fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); */
1.337 brouard 6851: fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 6852: }
1.337 brouard 6853: /* for(j=1;j<=cptcoveff;j++) */
6854: /* fprintf(ficresprobmorprev," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,TnsdVar[Tvaraff[j]])]); */
1.238 brouard 6855: fprintf(ficresprobmorprev,"\n");
6856:
1.218 brouard 6857: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
6858: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6859: fprintf(ficresprobmorprev," p.%-d SE",j);
6860: for(i=1; i<=nlstate;i++)
6861: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
6862: }
6863: fprintf(ficresprobmorprev,"\n");
6864:
6865: fprintf(ficgp,"\n# Routine varevsij");
6866: fprintf(ficgp,"\nunset title \n");
6867: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
6868: 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");
6869: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 6870:
1.218 brouard 6871: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6872: pstamp(ficresvij);
6873: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
6874: if(popbased==1)
6875: 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);
6876: else
6877: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
6878: fprintf(ficresvij,"# Age");
6879: for(i=1; i<=nlstate;i++)
6880: for(j=1; j<=nlstate;j++)
6881: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
6882: fprintf(ficresvij,"\n");
6883:
6884: xp=vector(1,npar);
6885: dnewm=matrix(1,nlstate,1,npar);
6886: doldm=matrix(1,nlstate,1,nlstate);
6887: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
6888: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6889:
6890: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
6891: gpp=vector(nlstate+1,nlstate+ndeath);
6892: gmp=vector(nlstate+1,nlstate+ndeath);
6893: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 6894:
1.218 brouard 6895: if(estepm < stepm){
6896: printf ("Problem %d lower than %d\n",estepm, stepm);
6897: }
6898: else hstepm=estepm;
6899: /* For example we decided to compute the life expectancy with the smallest unit */
6900: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6901: nhstepm is the number of hstepm from age to agelim
6902: nstepm is the number of stepm from age to agelim.
6903: Look at function hpijx to understand why because of memory size limitations,
6904: we decided (b) to get a life expectancy respecting the most precise curvature of the
6905: survival function given by stepm (the optimization length). Unfortunately it
6906: means that if the survival funtion is printed every two years of age and if
6907: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6908: results. So we changed our mind and took the option of the best precision.
6909: */
6910: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6911: agelim = AGESUP;
6912: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6913: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6914: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6915: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6916: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
6917: gp=matrix(0,nhstepm,1,nlstate);
6918: gm=matrix(0,nhstepm,1,nlstate);
6919:
6920:
6921: for(theta=1; theta <=npar; theta++){
6922: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
6923: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6924: }
1.279 brouard 6925: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
6926: * returns into prlim .
1.288 brouard 6927: */
1.242 brouard 6928: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 6929:
6930: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 6931: if (popbased==1) {
6932: if(mobilav ==0){
6933: for(i=1; i<=nlstate;i++)
6934: prlim[i][i]=probs[(int)age][i][ij];
6935: }else{ /* mobilav */
6936: for(i=1; i<=nlstate;i++)
6937: prlim[i][i]=mobaverage[(int)age][i][ij];
6938: }
6939: }
1.295 brouard 6940: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h.
1.279 brouard 6941: */
6942: 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 6943: /**< 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 6944: * at horizon h in state j including mortality.
6945: */
1.218 brouard 6946: for(j=1; j<= nlstate; j++){
6947: for(h=0; h<=nhstepm; h++){
6948: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
6949: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
6950: }
6951: }
1.279 brouard 6952: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 6953: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 6954: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 6955: */
6956: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6957: for(i=1,gpp[j]=0.; i<= nlstate; i++)
6958: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 6959: }
6960:
6961: /* Again with minus shift */
1.218 brouard 6962:
6963: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
6964: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6965:
1.242 brouard 6966: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 6967:
6968: if (popbased==1) {
6969: if(mobilav ==0){
6970: for(i=1; i<=nlstate;i++)
6971: prlim[i][i]=probs[(int)age][i][ij];
6972: }else{ /* mobilav */
6973: for(i=1; i<=nlstate;i++)
6974: prlim[i][i]=mobaverage[(int)age][i][ij];
6975: }
6976: }
6977:
1.235 brouard 6978: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 6979:
6980: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
6981: for(h=0; h<=nhstepm; h++){
6982: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
6983: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
6984: }
6985: }
6986: /* This for computing probability of death (h=1 means
6987: computed over hstepm matrices product = hstepm*stepm months)
6988: as a weighted average of prlim.
6989: */
6990: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6991: for(i=1,gmp[j]=0.; i<= nlstate; i++)
6992: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6993: }
1.279 brouard 6994: /* end shifting computations */
6995:
6996: /**< Computing gradient matrix at horizon h
6997: */
1.218 brouard 6998: for(j=1; j<= nlstate; j++) /* vareij */
6999: for(h=0; h<=nhstepm; h++){
7000: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
7001: }
1.279 brouard 7002: /**< Gradient of overall mortality p.3 (or p.j)
7003: */
7004: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 7005: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
7006: }
7007:
7008: } /* End theta */
1.279 brouard 7009:
7010: /* We got the gradient matrix for each theta and state j */
1.218 brouard 7011: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
7012:
7013: for(h=0; h<=nhstepm; h++) /* veij */
7014: for(j=1; j<=nlstate;j++)
7015: for(theta=1; theta <=npar; theta++)
7016: trgradg[h][j][theta]=gradg[h][theta][j];
7017:
7018: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
7019: for(theta=1; theta <=npar; theta++)
7020: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 7021: /**< as well as its transposed matrix
7022: */
1.218 brouard 7023:
7024: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
7025: for(i=1;i<=nlstate;i++)
7026: for(j=1;j<=nlstate;j++)
7027: vareij[i][j][(int)age] =0.;
1.279 brouard 7028:
7029: /* Computing trgradg by matcov by gradg at age and summing over h
7030: * and k (nhstepm) formula 15 of article
7031: * Lievre-Brouard-Heathcote
7032: */
7033:
1.218 brouard 7034: for(h=0;h<=nhstepm;h++){
7035: for(k=0;k<=nhstepm;k++){
7036: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
7037: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
7038: for(i=1;i<=nlstate;i++)
7039: for(j=1;j<=nlstate;j++)
7040: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
7041: }
7042: }
7043:
1.279 brouard 7044: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
7045: * p.j overall mortality formula 49 but computed directly because
7046: * we compute the grad (wix pijx) instead of grad (pijx),even if
7047: * wix is independent of theta.
7048: */
1.218 brouard 7049: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
7050: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
7051: for(j=nlstate+1;j<=nlstate+ndeath;j++)
7052: for(i=nlstate+1;i<=nlstate+ndeath;i++)
7053: varppt[j][i]=doldmp[j][i];
7054: /* end ppptj */
7055: /* x centered again */
7056:
1.242 brouard 7057: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 7058:
7059: if (popbased==1) {
7060: if(mobilav ==0){
7061: for(i=1; i<=nlstate;i++)
7062: prlim[i][i]=probs[(int)age][i][ij];
7063: }else{ /* mobilav */
7064: for(i=1; i<=nlstate;i++)
7065: prlim[i][i]=mobaverage[(int)age][i][ij];
7066: }
7067: }
7068:
7069: /* This for computing probability of death (h=1 means
7070: computed over hstepm (estepm) matrices product = hstepm*stepm months)
7071: as a weighted average of prlim.
7072: */
1.235 brouard 7073: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 7074: for(j=nlstate+1;j<=nlstate+ndeath;j++){
7075: for(i=1,gmp[j]=0.;i<= nlstate; i++)
7076: gmp[j] += prlim[i][i]*p3mat[i][j][1];
7077: }
7078: /* end probability of death */
7079:
7080: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
7081: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
7082: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
7083: for(i=1; i<=nlstate;i++){
7084: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
7085: }
7086: }
7087: fprintf(ficresprobmorprev,"\n");
7088:
7089: fprintf(ficresvij,"%.0f ",age );
7090: for(i=1; i<=nlstate;i++)
7091: for(j=1; j<=nlstate;j++){
7092: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
7093: }
7094: fprintf(ficresvij,"\n");
7095: free_matrix(gp,0,nhstepm,1,nlstate);
7096: free_matrix(gm,0,nhstepm,1,nlstate);
7097: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
7098: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
7099: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
7100: } /* End age */
7101: free_vector(gpp,nlstate+1,nlstate+ndeath);
7102: free_vector(gmp,nlstate+1,nlstate+ndeath);
7103: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
7104: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
7105: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
7106: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
7107: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
7108: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
7109: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
7110: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
7111: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
7112: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
7113: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
7114: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
7115: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
7116: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
7117: 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);
7118: /* 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 7119: */
1.218 brouard 7120: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
7121: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 7122:
1.218 brouard 7123: free_vector(xp,1,npar);
7124: free_matrix(doldm,1,nlstate,1,nlstate);
7125: free_matrix(dnewm,1,nlstate,1,npar);
7126: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7127: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
7128: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7129: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
7130: fclose(ficresprobmorprev);
7131: fflush(ficgp);
7132: fflush(fichtm);
7133: } /* end varevsij */
1.126 brouard 7134:
7135: /************ Variance of prevlim ******************/
1.269 brouard 7136: 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 7137: {
1.205 brouard 7138: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 7139: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 7140:
1.268 brouard 7141: double **dnewmpar,**doldm;
1.126 brouard 7142: int i, j, nhstepm, hstepm;
7143: double *xp;
7144: double *gp, *gm;
7145: double **gradg, **trgradg;
1.208 brouard 7146: double **mgm, **mgp;
1.126 brouard 7147: double age,agelim;
7148: int theta;
7149:
7150: pstamp(ficresvpl);
1.288 brouard 7151: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 7152: fprintf(ficresvpl,"# Age ");
7153: if(nresult >=1)
7154: fprintf(ficresvpl," Result# ");
1.126 brouard 7155: for(i=1; i<=nlstate;i++)
7156: fprintf(ficresvpl," %1d-%1d",i,i);
7157: fprintf(ficresvpl,"\n");
7158:
7159: xp=vector(1,npar);
1.268 brouard 7160: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 7161: doldm=matrix(1,nlstate,1,nlstate);
7162:
7163: hstepm=1*YEARM; /* Every year of age */
7164: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
7165: agelim = AGESUP;
7166: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
7167: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7168: if (stepm >= YEARM) hstepm=1;
7169: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
7170: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 7171: mgp=matrix(1,npar,1,nlstate);
7172: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 7173: gp=vector(1,nlstate);
7174: gm=vector(1,nlstate);
7175:
7176: for(theta=1; theta <=npar; theta++){
7177: for(i=1; i<=npar; i++){ /* Computes gradient */
7178: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7179: }
1.288 brouard 7180: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
7181: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
7182: /* else */
7183: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 7184: for(i=1;i<=nlstate;i++){
1.126 brouard 7185: gp[i] = prlim[i][i];
1.208 brouard 7186: mgp[theta][i] = prlim[i][i];
7187: }
1.126 brouard 7188: for(i=1; i<=npar; i++) /* Computes gradient */
7189: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 7190: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
7191: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
7192: /* else */
7193: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 7194: for(i=1;i<=nlstate;i++){
1.126 brouard 7195: gm[i] = prlim[i][i];
1.208 brouard 7196: mgm[theta][i] = prlim[i][i];
7197: }
1.126 brouard 7198: for(i=1;i<=nlstate;i++)
7199: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 7200: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 7201: } /* End theta */
7202:
7203: trgradg =matrix(1,nlstate,1,npar);
7204:
7205: for(j=1; j<=nlstate;j++)
7206: for(theta=1; theta <=npar; theta++)
7207: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 7208: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7209: /* printf("\nmgm mgp %d ",(int)age); */
7210: /* for(j=1; j<=nlstate;j++){ */
7211: /* printf(" %d ",j); */
7212: /* for(theta=1; theta <=npar; theta++) */
7213: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
7214: /* printf("\n "); */
7215: /* } */
7216: /* } */
7217: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7218: /* printf("\n gradg %d ",(int)age); */
7219: /* for(j=1; j<=nlstate;j++){ */
7220: /* printf("%d ",j); */
7221: /* for(theta=1; theta <=npar; theta++) */
7222: /* printf("%d %lf ",theta,gradg[theta][j]); */
7223: /* printf("\n "); */
7224: /* } */
7225: /* } */
1.126 brouard 7226:
7227: for(i=1;i<=nlstate;i++)
7228: varpl[i][(int)age] =0.;
1.209 brouard 7229: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 7230: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7231: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 7232: }else{
1.268 brouard 7233: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7234: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 7235: }
1.126 brouard 7236: for(i=1;i<=nlstate;i++)
7237: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
7238:
7239: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 7240: if(nresult >=1)
7241: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 7242: for(i=1; i<=nlstate;i++){
1.126 brouard 7243: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 7244: /* for(j=1;j<=nlstate;j++) */
7245: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
7246: }
1.126 brouard 7247: fprintf(ficresvpl,"\n");
7248: free_vector(gp,1,nlstate);
7249: free_vector(gm,1,nlstate);
1.208 brouard 7250: free_matrix(mgm,1,npar,1,nlstate);
7251: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 7252: free_matrix(gradg,1,npar,1,nlstate);
7253: free_matrix(trgradg,1,nlstate,1,npar);
7254: } /* End age */
7255:
7256: free_vector(xp,1,npar);
7257: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 7258: free_matrix(dnewmpar,1,nlstate,1,nlstate);
7259:
7260: }
7261:
7262:
7263: /************ Variance of backprevalence limit ******************/
1.269 brouard 7264: 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 7265: {
7266: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
7267: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
7268:
7269: double **dnewmpar,**doldm;
7270: int i, j, nhstepm, hstepm;
7271: double *xp;
7272: double *gp, *gm;
7273: double **gradg, **trgradg;
7274: double **mgm, **mgp;
7275: double age,agelim;
7276: int theta;
7277:
7278: pstamp(ficresvbl);
7279: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
7280: fprintf(ficresvbl,"# Age ");
7281: if(nresult >=1)
7282: fprintf(ficresvbl," Result# ");
7283: for(i=1; i<=nlstate;i++)
7284: fprintf(ficresvbl," %1d-%1d",i,i);
7285: fprintf(ficresvbl,"\n");
7286:
7287: xp=vector(1,npar);
7288: dnewmpar=matrix(1,nlstate,1,npar);
7289: doldm=matrix(1,nlstate,1,nlstate);
7290:
7291: hstepm=1*YEARM; /* Every year of age */
7292: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
7293: agelim = AGEINF;
7294: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
7295: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7296: if (stepm >= YEARM) hstepm=1;
7297: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
7298: gradg=matrix(1,npar,1,nlstate);
7299: mgp=matrix(1,npar,1,nlstate);
7300: mgm=matrix(1,npar,1,nlstate);
7301: gp=vector(1,nlstate);
7302: gm=vector(1,nlstate);
7303:
7304: for(theta=1; theta <=npar; theta++){
7305: for(i=1; i<=npar; i++){ /* Computes gradient */
7306: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7307: }
7308: if(mobilavproj > 0 )
7309: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7310: else
7311: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7312: for(i=1;i<=nlstate;i++){
7313: gp[i] = bprlim[i][i];
7314: mgp[theta][i] = bprlim[i][i];
7315: }
7316: for(i=1; i<=npar; i++) /* Computes gradient */
7317: xp[i] = x[i] - (i==theta ?delti[theta]:0);
7318: if(mobilavproj > 0 )
7319: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7320: else
7321: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7322: for(i=1;i<=nlstate;i++){
7323: gm[i] = bprlim[i][i];
7324: mgm[theta][i] = bprlim[i][i];
7325: }
7326: for(i=1;i<=nlstate;i++)
7327: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
7328: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
7329: } /* End theta */
7330:
7331: trgradg =matrix(1,nlstate,1,npar);
7332:
7333: for(j=1; j<=nlstate;j++)
7334: for(theta=1; theta <=npar; theta++)
7335: trgradg[j][theta]=gradg[theta][j];
7336: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7337: /* printf("\nmgm mgp %d ",(int)age); */
7338: /* for(j=1; j<=nlstate;j++){ */
7339: /* printf(" %d ",j); */
7340: /* for(theta=1; theta <=npar; theta++) */
7341: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
7342: /* printf("\n "); */
7343: /* } */
7344: /* } */
7345: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7346: /* printf("\n gradg %d ",(int)age); */
7347: /* for(j=1; j<=nlstate;j++){ */
7348: /* printf("%d ",j); */
7349: /* for(theta=1; theta <=npar; theta++) */
7350: /* printf("%d %lf ",theta,gradg[theta][j]); */
7351: /* printf("\n "); */
7352: /* } */
7353: /* } */
7354:
7355: for(i=1;i<=nlstate;i++)
7356: varbpl[i][(int)age] =0.;
7357: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
7358: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7359: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
7360: }else{
7361: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7362: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
7363: }
7364: for(i=1;i<=nlstate;i++)
7365: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
7366:
7367: fprintf(ficresvbl,"%.0f ",age );
7368: if(nresult >=1)
7369: fprintf(ficresvbl,"%d ",nres );
7370: for(i=1; i<=nlstate;i++)
7371: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
7372: fprintf(ficresvbl,"\n");
7373: free_vector(gp,1,nlstate);
7374: free_vector(gm,1,nlstate);
7375: free_matrix(mgm,1,npar,1,nlstate);
7376: free_matrix(mgp,1,npar,1,nlstate);
7377: free_matrix(gradg,1,npar,1,nlstate);
7378: free_matrix(trgradg,1,nlstate,1,npar);
7379: } /* End age */
7380:
7381: free_vector(xp,1,npar);
7382: free_matrix(doldm,1,nlstate,1,npar);
7383: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 7384:
7385: }
7386:
7387: /************ Variance of one-step probabilities ******************/
7388: 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 7389: {
7390: int i, j=0, k1, l1, tj;
7391: int k2, l2, j1, z1;
7392: int k=0, l;
7393: int first=1, first1, first2;
1.326 brouard 7394: int nres=0; /* New */
1.222 brouard 7395: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
7396: double **dnewm,**doldm;
7397: double *xp;
7398: double *gp, *gm;
7399: double **gradg, **trgradg;
7400: double **mu;
7401: double age, cov[NCOVMAX+1];
7402: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
7403: int theta;
7404: char fileresprob[FILENAMELENGTH];
7405: char fileresprobcov[FILENAMELENGTH];
7406: char fileresprobcor[FILENAMELENGTH];
7407: double ***varpij;
7408:
7409: strcpy(fileresprob,"PROB_");
7410: strcat(fileresprob,fileres);
7411: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
7412: printf("Problem with resultfile: %s\n", fileresprob);
7413: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
7414: }
7415: strcpy(fileresprobcov,"PROBCOV_");
7416: strcat(fileresprobcov,fileresu);
7417: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
7418: printf("Problem with resultfile: %s\n", fileresprobcov);
7419: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
7420: }
7421: strcpy(fileresprobcor,"PROBCOR_");
7422: strcat(fileresprobcor,fileresu);
7423: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
7424: printf("Problem with resultfile: %s\n", fileresprobcor);
7425: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
7426: }
7427: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7428: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7429: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7430: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7431: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7432: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7433: pstamp(ficresprob);
7434: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
7435: fprintf(ficresprob,"# Age");
7436: pstamp(ficresprobcov);
7437: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
7438: fprintf(ficresprobcov,"# Age");
7439: pstamp(ficresprobcor);
7440: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
7441: fprintf(ficresprobcor,"# Age");
1.126 brouard 7442:
7443:
1.222 brouard 7444: for(i=1; i<=nlstate;i++)
7445: for(j=1; j<=(nlstate+ndeath);j++){
7446: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
7447: fprintf(ficresprobcov," p%1d-%1d ",i,j);
7448: fprintf(ficresprobcor," p%1d-%1d ",i,j);
7449: }
7450: /* fprintf(ficresprob,"\n");
7451: fprintf(ficresprobcov,"\n");
7452: fprintf(ficresprobcor,"\n");
7453: */
7454: xp=vector(1,npar);
7455: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7456: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
7457: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
7458: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
7459: first=1;
7460: fprintf(ficgp,"\n# Routine varprob");
7461: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
7462: fprintf(fichtm,"\n");
7463:
1.288 brouard 7464: 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 7465: 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);
7466: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 7467: and drawn. It helps understanding how is the covariance between two incidences.\
7468: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 7469: 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 7470: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
7471: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
7472: standard deviations wide on each axis. <br>\
7473: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
7474: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
7475: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
7476:
1.222 brouard 7477: cov[1]=1;
7478: /* tj=cptcoveff; */
1.225 brouard 7479: tj = (int) pow(2,cptcoveff);
1.222 brouard 7480: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
7481: j1=0;
1.332 brouard 7482:
7483: for(nres=1;nres <=nresult; nres++){ /* For each resultline */
7484: for(j1=1; j1<=tj;j1++){ /* For any combination of dummy covariates, fixed and varying */
1.342 brouard 7485: /* 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 7486: if(tj != 1 && TKresult[nres]!= j1)
7487: continue;
7488:
7489: /* for(j1=1; j1<=tj;j1++){ /\* For each valid combination of covariates or only once*\/ */
7490: /* for(nres=1;nres <=1; nres++){ /\* For each resultline *\/ */
7491: /* /\* for(nres=1;nres <=nresult; nres++){ /\\* For each resultline *\\/ *\/ */
1.222 brouard 7492: if (cptcovn>0) {
1.334 brouard 7493: fprintf(ficresprob, "\n#********** Variable ");
7494: fprintf(ficresprobcov, "\n#********** Variable ");
7495: fprintf(ficgp, "\n#********** Variable ");
7496: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
7497: fprintf(ficresprobcor, "\n#********** Variable ");
7498:
7499: /* Including quantitative variables of the resultline to be done */
7500: for (z1=1; z1<=cptcovs; z1++){ /* Loop on each variable of this resultline */
1.343 brouard 7501: /* printf("Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model); */
1.338 brouard 7502: fprintf(ficlog,"Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model);
7503: /* 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 7504: if(Dummy[modelresult[nres][z1]]==0){/* Dummy variable of the variable in position modelresult in the model corresponding to z1 in resultline */
7505: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed referenced to model equation */
7506: 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 */
7507: 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 */
7508: 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 */
7509: 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 */
7510: 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 */
7511: fprintf(ficresprob,"fixed ");
7512: fprintf(ficresprobcov,"fixed ");
7513: fprintf(ficgp,"fixed ");
7514: fprintf(fichtmcov,"fixed ");
7515: fprintf(ficresprobcor,"fixed ");
7516: }else{
7517: fprintf(ficresprob,"varyi ");
7518: fprintf(ficresprobcov,"varyi ");
7519: fprintf(ficgp,"varyi ");
7520: fprintf(fichtmcov,"varyi ");
7521: fprintf(ficresprobcor,"varyi ");
7522: }
7523: }else if(Dummy[modelresult[nres][z1]]==1){ /* Quanti variable */
7524: /* For each selected (single) quantitative value */
1.337 brouard 7525: fprintf(ficresprob," V%d=%lg ",Tvqresult[nres][z1],Tqresult[nres][z1]);
1.334 brouard 7526: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed */
7527: fprintf(ficresprob,"fixed ");
7528: fprintf(ficresprobcov,"fixed ");
7529: fprintf(ficgp,"fixed ");
7530: fprintf(fichtmcov,"fixed ");
7531: fprintf(ficresprobcor,"fixed ");
7532: }else{
7533: fprintf(ficresprob,"varyi ");
7534: fprintf(ficresprobcov,"varyi ");
7535: fprintf(ficgp,"varyi ");
7536: fprintf(fichtmcov,"varyi ");
7537: fprintf(ficresprobcor,"varyi ");
7538: }
7539: }else{
7540: 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 */
7541: 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 */
7542: exit(1);
7543: }
7544: } /* End loop on variable of this resultline */
7545: /* for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]); */
1.222 brouard 7546: fprintf(ficresprob, "**********\n#\n");
7547: fprintf(ficresprobcov, "**********\n#\n");
7548: fprintf(ficgp, "**********\n#\n");
7549: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
7550: fprintf(ficresprobcor, "**********\n#");
7551: if(invalidvarcomb[j1]){
7552: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
7553: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
7554: continue;
7555: }
7556: }
7557: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
7558: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7559: gp=vector(1,(nlstate)*(nlstate+ndeath));
7560: gm=vector(1,(nlstate)*(nlstate+ndeath));
1.334 brouard 7561: for (age=bage; age<=fage; age ++){ /* Fo each age we feed the model equation with covariates, using precov as in hpxij() ? */
1.222 brouard 7562: cov[2]=age;
7563: if(nagesqr==1)
7564: cov[3]= age*age;
1.334 brouard 7565: /* New code end of combination but for each resultline */
7566: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
7567: if(Typevar[k1]==1){ /* A product with age */
7568: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.326 brouard 7569: }else{
1.334 brouard 7570: cov[2+nagesqr+k1]=precov[nres][k1];
1.326 brouard 7571: }
1.334 brouard 7572: }/* End of loop on model equation */
7573: /* Old code */
7574: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
7575: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)]; *\/ */
7576: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
7577: /* /\* Here comes the value of the covariate 'j1' after renumbering k with single dummy covariates *\/ */
7578: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(j1,TnsdVar[TvarsD[k]])]; */
7579: /* /\*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*\//\* j1 1 2 3 4 */
7580: /* * 1 1 1 1 1 */
7581: /* * 2 2 1 1 1 */
7582: /* * 3 1 2 1 1 */
7583: /* *\/ */
7584: /* /\* nbcode[1][1]=0 nbcode[1][2]=1;*\/ */
7585: /* } */
7586: /* /\* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
7587: /* /\* ) p nbcode[Tvar[Tage[k]]][(1 & (ij-1) >> (k-1))+1] *\/ */
7588: /* /\*for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; *\/ */
7589: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
7590: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
7591: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(j1,TnsdVar[Tvar[Tage[k]]])]*cov[2]; */
7592: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
7593: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
7594: /* 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]); */
7595: /* /\* cov[2+nagesqr+Tage[k]]=meanq[k]/idq[k]*cov[2];/\\* Using the mean of quantitative variable Tvar[Tage[k]] /\\* Tqresult[nres][k]; *\\/ *\/ */
7596: /* /\* exit(1); *\/ */
7597: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
7598: /* } */
7599: /* /\* cov[2+Tage[k]+nagesqr]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
7600: /* } */
7601: /* for (k=1; k<=cptcovprod;k++){/\* For product without age *\/ */
7602: /* if(Dummy[Tvard[k][1]]==0){ */
7603: /* if(Dummy[Tvard[k][2]]==0){ */
7604: /* 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]])]; */
7605: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
7606: /* }else{ /\* Should we use the mean of the quantitative variables? *\/ */
7607: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(j1,TnsdVar[Tvard[k][1]])] * Tqresult[nres][resultmodel[nres][k]]; */
7608: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
7609: /* } */
7610: /* }else{ */
7611: /* if(Dummy[Tvard[k][2]]==0){ */
7612: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(j1,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][TnsdVar[Tvard[k][1]]]; */
7613: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
7614: /* }else{ */
7615: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][TnsdVar[Tvard[k][1]]]* Tqinvresult[nres][TnsdVar[Tvard[k][2]]]; */
7616: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
7617: /* } */
7618: /* } */
7619: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
7620: /* } */
1.326 brouard 7621: /* For each age and combination of dummy covariates we slightly move the parameters of delti in order to get the gradient*/
1.222 brouard 7622: for(theta=1; theta <=npar; theta++){
7623: for(i=1; i<=npar; i++)
7624: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 7625:
1.222 brouard 7626: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 7627:
1.222 brouard 7628: k=0;
7629: for(i=1; i<= (nlstate); i++){
7630: for(j=1; j<=(nlstate+ndeath);j++){
7631: k=k+1;
7632: gp[k]=pmmij[i][j];
7633: }
7634: }
1.220 brouard 7635:
1.222 brouard 7636: for(i=1; i<=npar; i++)
7637: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 7638:
1.222 brouard 7639: pmij(pmmij,cov,ncovmodel,xp,nlstate);
7640: k=0;
7641: for(i=1; i<=(nlstate); i++){
7642: for(j=1; j<=(nlstate+ndeath);j++){
7643: k=k+1;
7644: gm[k]=pmmij[i][j];
7645: }
7646: }
1.220 brouard 7647:
1.222 brouard 7648: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
7649: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
7650: }
1.126 brouard 7651:
1.222 brouard 7652: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
7653: for(theta=1; theta <=npar; theta++)
7654: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 7655:
1.222 brouard 7656: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
7657: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 7658:
1.222 brouard 7659: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 7660:
1.222 brouard 7661: k=0;
7662: for(i=1; i<=(nlstate); i++){
7663: for(j=1; j<=(nlstate+ndeath);j++){
7664: k=k+1;
7665: mu[k][(int) age]=pmmij[i][j];
7666: }
7667: }
7668: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
7669: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
7670: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 7671:
1.222 brouard 7672: /*printf("\n%d ",(int)age);
7673: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7674: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7675: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7676: }*/
1.220 brouard 7677:
1.222 brouard 7678: fprintf(ficresprob,"\n%d ",(int)age);
7679: fprintf(ficresprobcov,"\n%d ",(int)age);
7680: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 7681:
1.222 brouard 7682: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
7683: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
7684: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7685: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
7686: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
7687: }
7688: i=0;
7689: for (k=1; k<=(nlstate);k++){
7690: for (l=1; l<=(nlstate+ndeath);l++){
7691: i++;
7692: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
7693: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
7694: for (j=1; j<=i;j++){
7695: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
7696: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
7697: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
7698: }
7699: }
7700: }/* end of loop for state */
7701: } /* end of loop for age */
7702: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
7703: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
7704: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7705: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7706:
7707: /* Confidence intervalle of pij */
7708: /*
7709: fprintf(ficgp,"\nunset parametric;unset label");
7710: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
7711: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
7712: 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);
7713: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
7714: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
7715: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
7716: */
7717:
7718: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
7719: first1=1;first2=2;
7720: for (k2=1; k2<=(nlstate);k2++){
7721: for (l2=1; l2<=(nlstate+ndeath);l2++){
7722: if(l2==k2) continue;
7723: j=(k2-1)*(nlstate+ndeath)+l2;
7724: for (k1=1; k1<=(nlstate);k1++){
7725: for (l1=1; l1<=(nlstate+ndeath);l1++){
7726: if(l1==k1) continue;
7727: i=(k1-1)*(nlstate+ndeath)+l1;
7728: if(i<=j) continue;
7729: for (age=bage; age<=fage; age ++){
7730: if ((int)age %5==0){
7731: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
7732: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
7733: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
7734: mu1=mu[i][(int) age]/stepm*YEARM ;
7735: mu2=mu[j][(int) age]/stepm*YEARM;
7736: c12=cv12/sqrt(v1*v2);
7737: /* Computing eigen value of matrix of covariance */
7738: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7739: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7740: if ((lc2 <0) || (lc1 <0) ){
7741: if(first2==1){
7742: first1=0;
7743: 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);
7744: }
7745: 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);
7746: /* lc1=fabs(lc1); */ /* If we want to have them positive */
7747: /* lc2=fabs(lc2); */
7748: }
1.220 brouard 7749:
1.222 brouard 7750: /* Eigen vectors */
1.280 brouard 7751: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
7752: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7753: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7754: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
7755: }else
7756: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 7757: /*v21=sqrt(1.-v11*v11); *//* error */
7758: v21=(lc1-v1)/cv12*v11;
7759: v12=-v21;
7760: v22=v11;
7761: tnalp=v21/v11;
7762: if(first1==1){
7763: first1=0;
7764: 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);
7765: }
7766: 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);
7767: /*printf(fignu*/
7768: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
7769: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
7770: if(first==1){
7771: first=0;
7772: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
7773: fprintf(ficgp,"\nset parametric;unset label");
7774: 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);
7775: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 7776: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 7777: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 7778: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 7779: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
7780: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7781: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7782: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
7783: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7784: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7785: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7786: 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 7787: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
7788: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 7789: }else{
7790: first=0;
7791: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
7792: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7793: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7794: 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 7795: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
7796: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 7797: }/* if first */
7798: } /* age mod 5 */
7799: } /* end loop age */
7800: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7801: first=1;
7802: } /*l12 */
7803: } /* k12 */
7804: } /*l1 */
7805: }/* k1 */
1.332 brouard 7806: } /* loop on combination of covariates j1 */
1.326 brouard 7807: } /* loop on nres */
1.222 brouard 7808: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
7809: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
7810: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
7811: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
7812: free_vector(xp,1,npar);
7813: fclose(ficresprob);
7814: fclose(ficresprobcov);
7815: fclose(ficresprobcor);
7816: fflush(ficgp);
7817: fflush(fichtmcov);
7818: }
1.126 brouard 7819:
7820:
7821: /******************* Printing html file ***********/
1.201 brouard 7822: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 7823: int lastpass, int stepm, int weightopt, char model[],\
7824: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.296 brouard 7825: int popforecast, int mobilav, int prevfcast, int mobilavproj, int prevbcast, int estepm , \
7826: double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \
7827: double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){
1.237 brouard 7828: int jj1, k1, i1, cpt, k4, nres;
1.319 brouard 7829: /* In fact some results are already printed in fichtm which is open */
1.126 brouard 7830: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
7831: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
7832: </ul>");
1.319 brouard 7833: /* fprintf(fichtm,"<ul><li> model=1+age+%s\n \ */
7834: /* </ul>", model); */
1.214 brouard 7835: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
7836: 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",
7837: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
1.332 brouard 7838: 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 7839: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
7840: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 7841: fprintf(fichtm,"\
7842: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 7843: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 7844: fprintf(fichtm,"\
1.217 brouard 7845: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
7846: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
7847: fprintf(fichtm,"\
1.288 brouard 7848: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 7849: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 7850: fprintf(fichtm,"\
1.288 brouard 7851: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 7852: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
7853: fprintf(fichtm,"\
1.211 brouard 7854: - (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 7855: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 7856: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 7857: if(prevfcast==1){
7858: fprintf(fichtm,"\
7859: - Prevalence projections by age and states: \
1.201 brouard 7860: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 7861: }
1.126 brouard 7862:
7863:
1.225 brouard 7864: m=pow(2,cptcoveff);
1.222 brouard 7865: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7866:
1.317 brouard 7867: fprintf(fichtm," \n<ul><li><b>Graphs (first order)</b></li><p>");
1.264 brouard 7868:
7869: jj1=0;
7870:
7871: fprintf(fichtm," \n<ul>");
1.337 brouard 7872: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
7873: /* k1=nres; */
1.338 brouard 7874: k1=TKresult[nres];
7875: if(TKresult[nres]==0)k1=1; /* To be checked for no result */
1.337 brouard 7876: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
7877: /* if(m != 1 && TKresult[nres]!= k1) */
7878: /* continue; */
1.264 brouard 7879: jj1++;
7880: if (cptcovn > 0) {
7881: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
1.337 brouard 7882: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
7883: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 7884: }
1.337 brouard 7885: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
7886: /* fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
7887: /* } */
7888: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
7889: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
7890: /* } */
1.264 brouard 7891: fprintf(fichtm,"\">");
7892:
7893: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
7894: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 7895: for (cpt=1; cpt<=cptcovs;cpt++){
7896: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 7897: }
1.337 brouard 7898: /* fprintf(fichtm,"************ Results for covariates"); */
7899: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
7900: /* fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
7901: /* } */
7902: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
7903: /* fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
7904: /* } */
1.264 brouard 7905: if(invalidvarcomb[k1]){
7906: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
7907: continue;
7908: }
7909: fprintf(fichtm,"</a></li>");
7910: } /* cptcovn >0 */
7911: }
1.317 brouard 7912: fprintf(fichtm," \n</ul>");
1.264 brouard 7913:
1.222 brouard 7914: jj1=0;
1.237 brouard 7915:
1.337 brouard 7916: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
7917: /* k1=nres; */
1.338 brouard 7918: k1=TKresult[nres];
7919: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 7920: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
7921: /* if(m != 1 && TKresult[nres]!= k1) */
7922: /* continue; */
1.220 brouard 7923:
1.222 brouard 7924: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7925: jj1++;
7926: if (cptcovn > 0) {
1.264 brouard 7927: fprintf(fichtm,"\n<p><a name=\"rescov");
1.337 brouard 7928: for (cpt=1; cpt<=cptcovs;cpt++){
7929: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 7930: }
1.337 brouard 7931: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
7932: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
7933: /* } */
1.264 brouard 7934: fprintf(fichtm,"\"</a>");
7935:
1.222 brouard 7936: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 7937: for (cpt=1; cpt<=cptcovs;cpt++){
7938: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
7939: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 7940: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
7941: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 7942: }
1.230 brouard 7943: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.338 brouard 7944: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.222 brouard 7945: if(invalidvarcomb[k1]){
7946: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
7947: printf("\nCombination (%d) ignored because no cases \n",k1);
7948: continue;
7949: }
7950: }
7951: /* aij, bij */
1.259 brouard 7952: 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 7953: <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 7954: /* Pij */
1.241 brouard 7955: 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> \
7956: <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 7957: /* Quasi-incidences */
7958: 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 7959: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 7960: 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 7961: 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> \
7962: <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 7963: /* Survival functions (period) in state j */
7964: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 7965: 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);
7966: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
7967: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.222 brouard 7968: }
7969: /* State specific survival functions (period) */
7970: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 7971: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
7972: And probability to be observed in various states (up to %d) being in state %d at different ages. \
1.329 brouard 7973: <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);
7974: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
7975: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.222 brouard 7976: }
1.288 brouard 7977: /* Period (forward stable) prevalence in each health state */
1.222 brouard 7978: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 7979: 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 7980: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
1.329 brouard 7981: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.222 brouard 7982: }
1.296 brouard 7983: if(prevbcast==1){
1.288 brouard 7984: /* Backward prevalence in each health state */
1.222 brouard 7985: for(cpt=1; cpt<=nlstate;cpt++){
1.338 brouard 7986: 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);
7987: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJB_"),subdirf2(optionfilefiname,"PIJB_"));
7988: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.222 brouard 7989: }
1.217 brouard 7990: }
1.222 brouard 7991: if(prevfcast==1){
1.288 brouard 7992: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 7993: for(cpt=1; cpt<=nlstate;cpt++){
1.314 brouard 7994: 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);
7995: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"F_"),subdirf2(optionfilefiname,"F_"));
7996: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",
7997: subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 7998: }
7999: }
1.296 brouard 8000: if(prevbcast==1){
1.268 brouard 8001: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
8002: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 8003: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
8004: 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 \
8005: 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 8006: 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);
8007: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"FB_"),subdirf2(optionfilefiname,"FB_"));
8008: fprintf(fichtm," <img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
1.268 brouard 8009: }
8010: }
1.220 brouard 8011:
1.222 brouard 8012: for(cpt=1; cpt<=nlstate;cpt++) {
1.314 brouard 8013: 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);
8014: fprintf(fichtm," (data from text file <a href=\"%s.txt\"> %s.txt</a>)\n<br>",subdirf2(optionfilefiname,"E_"),subdirf2(optionfilefiname,"E_"));
8015: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres );
1.222 brouard 8016: }
8017: /* } /\* end i1 *\/ */
1.337 brouard 8018: }/* End k1=nres */
1.222 brouard 8019: fprintf(fichtm,"</ul>");
1.126 brouard 8020:
1.222 brouard 8021: fprintf(fichtm,"\
1.126 brouard 8022: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 8023: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 8024: - 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 8025: But because parameters are usually highly correlated (a higher incidence of disability \
8026: and a higher incidence of recovery can give very close observed transition) it might \
8027: be very useful to look not only at linear confidence intervals estimated from the \
8028: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
8029: (parameters) of the logistic regression, it might be more meaningful to visualize the \
8030: covariance matrix of the one-step probabilities. \
8031: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 8032:
1.222 brouard 8033: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
8034: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
8035: fprintf(fichtm,"\
1.126 brouard 8036: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 8037: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 8038:
1.222 brouard 8039: fprintf(fichtm,"\
1.126 brouard 8040: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 8041: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
8042: fprintf(fichtm,"\
1.126 brouard 8043: - 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): \
8044: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 8045: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 8046: fprintf(fichtm,"\
1.126 brouard 8047: - (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): \
8048: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 8049: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 8050: fprintf(fichtm,"\
1.288 brouard 8051: - 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 8052: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
8053: fprintf(fichtm,"\
1.128 brouard 8054: - 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 8055: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
8056: fprintf(fichtm,"\
1.288 brouard 8057: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 8058: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 8059:
8060: /* if(popforecast==1) fprintf(fichtm,"\n */
8061: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
8062: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
8063: /* <br>",fileres,fileres,fileres,fileres); */
8064: /* else */
1.338 brouard 8065: /* 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 8066: fflush(fichtm);
1.126 brouard 8067:
1.225 brouard 8068: m=pow(2,cptcoveff);
1.222 brouard 8069: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 8070:
1.317 brouard 8071: fprintf(fichtm," <ul><li><b>Graphs (second order)</b></li><p>");
8072:
8073: jj1=0;
8074:
8075: fprintf(fichtm," \n<ul>");
1.337 brouard 8076: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8077: /* k1=nres; */
1.338 brouard 8078: k1=TKresult[nres];
1.337 brouard 8079: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
8080: /* if(m != 1 && TKresult[nres]!= k1) */
8081: /* continue; */
1.317 brouard 8082: jj1++;
8083: if (cptcovn > 0) {
8084: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescovsecond");
1.337 brouard 8085: for (cpt=1; cpt<=cptcovs;cpt++){
8086: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8087: }
8088: fprintf(fichtm,"\">");
8089:
8090: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
8091: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 8092: for (cpt=1; cpt<=cptcovs;cpt++){
8093: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8094: }
8095: if(invalidvarcomb[k1]){
8096: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
8097: continue;
8098: }
8099: fprintf(fichtm,"</a></li>");
8100: } /* cptcovn >0 */
1.337 brouard 8101: } /* End nres */
1.317 brouard 8102: fprintf(fichtm," \n</ul>");
8103:
1.222 brouard 8104: jj1=0;
1.237 brouard 8105:
1.241 brouard 8106: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8107: /* k1=nres; */
1.338 brouard 8108: k1=TKresult[nres];
8109: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8110: /* for(k1=1; k1<=m;k1++){ */
8111: /* if(m != 1 && TKresult[nres]!= k1) */
8112: /* continue; */
1.222 brouard 8113: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
8114: jj1++;
1.126 brouard 8115: if (cptcovn > 0) {
1.317 brouard 8116: fprintf(fichtm,"\n<p><a name=\"rescovsecond");
1.337 brouard 8117: for (cpt=1; cpt<=cptcovs;cpt++){
8118: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8119: }
8120: fprintf(fichtm,"\"</a>");
8121:
1.126 brouard 8122: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 8123: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcoveff number of variables */
8124: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
8125: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 8126: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
1.317 brouard 8127: }
1.237 brouard 8128:
1.338 brouard 8129: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.220 brouard 8130:
1.222 brouard 8131: if(invalidvarcomb[k1]){
8132: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
8133: continue;
8134: }
1.337 brouard 8135: } /* If cptcovn >0 */
1.126 brouard 8136: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 8137: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.314 brouard 8138: 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);
8139: fprintf(fichtm," (data from text file <a href=\"%s\">%s</a>)\n <br>",subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
8140: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"V_"), cpt,k1,nres);
1.126 brouard 8141: }
8142: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.314 brouard 8143: health expectancies in each live states (1 to %d). If popbased=1 the smooth (due to the model) \
1.128 brouard 8144: true period expectancies (those weighted with period prevalences are also\
8145: drawn in addition to the population based expectancies computed using\
1.314 brouard 8146: 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);
8147: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>) \n<br>",subdirf2(optionfilefiname,"T_"),subdirf2(optionfilefiname,"T_"));
8148: fprintf(fichtm,"<img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 8149: /* } /\* end i1 *\/ */
1.241 brouard 8150: }/* End nres */
1.222 brouard 8151: fprintf(fichtm,"</ul>");
8152: fflush(fichtm);
1.126 brouard 8153: }
8154:
8155: /******************* Gnuplot file **************/
1.296 brouard 8156: 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 8157:
8158: char dirfileres[132],optfileres[132];
1.264 brouard 8159: char gplotcondition[132], gplotlabel[132];
1.343 brouard 8160: 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 8161: int lv=0, vlv=0, kl=0;
1.130 brouard 8162: int ng=0;
1.201 brouard 8163: int vpopbased;
1.223 brouard 8164: int ioffset; /* variable offset for columns */
1.270 brouard 8165: int iyearc=1; /* variable column for year of projection */
8166: int iagec=1; /* variable column for age of projection */
1.235 brouard 8167: int nres=0; /* Index of resultline */
1.266 brouard 8168: int istart=1; /* For starting graphs in projections */
1.219 brouard 8169:
1.126 brouard 8170: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
8171: /* printf("Problem with file %s",optionfilegnuplot); */
8172: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
8173: /* } */
8174:
8175: /*#ifdef windows */
8176: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 8177: /*#endif */
1.225 brouard 8178: m=pow(2,cptcoveff);
1.126 brouard 8179:
1.274 brouard 8180: /* diagram of the model */
8181: fprintf(ficgp,"\n#Diagram of the model \n");
8182: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
8183: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
8184: 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);
8185:
1.343 brouard 8186: 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 8187: fprintf(ficgp,"\n#show arrow\nunset label\n");
8188: 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);
8189: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
8190: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
8191: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
8192: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
8193:
1.202 brouard 8194: /* Contribution to likelihood */
8195: /* Plot the probability implied in the likelihood */
1.223 brouard 8196: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
8197: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
8198: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
8199: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 8200: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 8201: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
8202: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 8203: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
8204: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
8205: 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));
8206: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
8207: 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));
8208: for (i=1; i<= nlstate ; i ++) {
8209: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
8210: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
8211: 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);
8212: for (j=2; j<= nlstate+ndeath ; j ++) {
8213: 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);
8214: }
8215: fprintf(ficgp,";\nset out; unset ylabel;\n");
8216: }
8217: /* 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 */
8218: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
8219: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
8220: fprintf(ficgp,"\nset out;unset log\n");
8221: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 8222:
1.343 brouard 8223: /* Plot the probability implied in the likelihood by covariate value */
8224: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
8225: /* if(debugILK==1){ */
8226: for(kf=1; kf <= ncovf; kf++){ /* For each simple dummy covariate of the model */
1.347 ! brouard 8227: kvar=Tvar[TvarFind[kf]]; /* variable name */
! 8228: /* k=18+Tvar[TvarFind[kf]];/\*offset because there are 18 columns in the ILK_ file but could be placed else where *\/ */
! 8229: k=18+kf;/*offset because there are 18 columns in the ILK_ file */
1.343 brouard 8230: for (i=1; i<= nlstate ; i ++) {
8231: fprintf(ficgp,"\nset out \"%s-p%dj-%d.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i,kvar);
8232: fprintf(ficgp,"unset log;\n# For each simple dummy covariate of the model \n plot \"%s\"",subdirf(fileresilk));
8233: 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);
8234: for (j=2; j<= nlstate+ndeath ; j ++) {
8235: 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);
8236: }
8237: fprintf(ficgp,";\nset out; unset ylabel;\n");
8238: }
8239: } /* End of each covariate dummy */
8240: for(ncovv=1, iposold=0, kk=0; ncovv <= ncovvt ; ncovv++){
8241: /* Other example V1 + V3 + V5 + age*V1 + age*V3 + age*V5 + V1*V3 + V3*V5 + V1*V5
8242: * kmodel = 1 2 3 4 5 6 7 8 9
8243: * varying 1 2 3 4 5
8244: * ncovv 1 2 3 4 5 6 7 8
8245: * TvarVV[ncovv] V3 5 1 3 3 5 1 5
8246: * TvarVVind[ncovv]=kmodel 2 3 7 7 8 8 9 9
8247: * TvarFind[kmodel] 1 0 0 0 0 0 0 0 0
8248: * kdata ncovcol=[V1 V2] nqv=0 ntv=[V3 V4] nqtv=V5
8249: * Dummy[kmodel] 0 0 1 2 2 3 1 1 1
8250: */
8251: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
8252: kvar=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
8253: /* 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]); */
8254: if(ipos!=iposold){ /* Not a product or first of a product */
8255: /* printf(" %d",ipos); */
8256: /* fprintf(ficresilk," V%d",TvarVV[ncovv]); */
8257: /* printf(" DebugILK ficgp suite ipos=%d != iposold=%d\n", ipos, iposold); */
8258: kk++; /* Position of the ncovv column in ILK_ */
8259: k=18+ncovf+kk; /*offset because there are 18 columns in the ILK_ file plus ncovf fixed covariate */
8260: 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) */
8261: for (i=1; i<= nlstate ; i ++) {
8262: fprintf(ficgp,"\nset out \"%s-p%dj-%d.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i,kvar);
8263: fprintf(ficgp,"unset log;\n# For each simple dummy covariate of the model \n plot \"%s\"",subdirf(fileresilk));
8264:
8265: if(gnuplotversion >=5.2){ /* Former gnuplot versions do not have variable pointsize!! */
8266: /* printf("DebugILK gnuplotversion=%g >=5.2\n",gnuplotversion); */
8267: 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);
8268: for (j=2; j<= nlstate+ndeath ; j ++) {
8269: 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);
8270: }
8271: }else{
8272: /* printf("DebugILK gnuplotversion=%g <5.2\n",gnuplotversion); */
8273: 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);
8274: for (j=2; j<= nlstate+ndeath ; j ++) {
8275: 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);
8276: }
8277: }
8278: fprintf(ficgp,";\nset out; unset ylabel;\n");
8279: }
8280: }/* End if dummy varying */
8281: }else{ /*Product */
8282: /* printf("*"); */
8283: /* fprintf(ficresilk,"*"); */
8284: }
8285: iposold=ipos;
8286: } /* For each time varying covariate */
8287: /* } /\* debugILK==1 *\/ */
8288: /* 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 */
8289: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
8290: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
8291: fprintf(ficgp,"\nset out;unset log\n");
8292: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
8293:
8294:
8295:
1.126 brouard 8296: strcpy(dirfileres,optionfilefiname);
8297: strcpy(optfileres,"vpl");
1.223 brouard 8298: /* 1eme*/
1.238 brouard 8299: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
1.337 brouard 8300: /* for (k1=1; k1<= m ; k1 ++){ /\* For each valid combination of covariate *\/ */
1.236 brouard 8301: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8302: k1=TKresult[nres];
1.338 brouard 8303: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.238 brouard 8304: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.337 brouard 8305: /* if(m != 1 && TKresult[nres]!= k1) */
8306: /* continue; */
1.238 brouard 8307: /* We are interested in selected combination by the resultline */
1.246 brouard 8308: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 8309: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 8310: strcpy(gplotlabel,"(");
1.337 brouard 8311: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8312: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8313: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8314:
8315: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate k get corresponding value lv for combination k1 *\/ */
8316: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the value of the covariate corresponding to k1 combination *\\/ *\/ */
8317: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8318: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8319: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8320: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8321: /* vlv= nbcode[Tvaraff[k]][lv]; /\* vlv is the value of the covariate lv, 0 or 1 *\/ */
8322: /* /\* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv *\/ */
8323: /* /\* printf(" V%d=%d ",Tvaraff[k],vlv); *\/ */
8324: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8325: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8326: /* } */
8327: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8328: /* /\* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); *\/ */
8329: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8330: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.264 brouard 8331: }
8332: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 8333: /* printf("\n#\n"); */
1.238 brouard 8334: fprintf(ficgp,"\n#\n");
8335: if(invalidvarcomb[k1]){
1.260 brouard 8336: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 8337: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8338: continue;
8339: }
1.235 brouard 8340:
1.241 brouard 8341: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
8342: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 8343: /* 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 8344: fprintf(ficgp,"set title \"Alive state %d %s model=1+age+%s\" font \"Helvetica,12\"\n",cpt,gplotlabel,model);
1.260 brouard 8345: 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);
8346: /* 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); */
8347: /* k1-1 error should be nres-1*/
1.238 brouard 8348: for (i=1; i<= nlstate ; i ++) {
8349: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8350: else fprintf(ficgp," %%*lf (%%*lf)");
8351: }
1.288 brouard 8352: 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 8353: for (i=1; i<= nlstate ; i ++) {
8354: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8355: else fprintf(ficgp," %%*lf (%%*lf)");
8356: }
1.260 brouard 8357: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 8358: for (i=1; i<= nlstate ; i ++) {
8359: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8360: else fprintf(ficgp," %%*lf (%%*lf)");
8361: }
1.265 brouard 8362: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
8363:
8364: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
8365: if(cptcoveff ==0){
1.271 brouard 8366: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 8367: }else{
8368: kl=0;
8369: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 8370: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
8371: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.265 brouard 8372: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8373: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8374: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8375: vlv= nbcode[Tvaraff[k]][lv];
8376: kl++;
8377: /* 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 *\/ */
8378: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8379: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8380: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
8381: if(k==cptcoveff){
8382: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
8383: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
8384: }else{
8385: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
8386: kl++;
8387: }
8388: } /* end covariate */
8389: } /* end if no covariate */
8390:
1.296 brouard 8391: if(prevbcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
1.238 brouard 8392: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 8393: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 8394: if(cptcoveff ==0){
1.245 brouard 8395: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 8396: }else{
8397: kl=0;
8398: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 8399: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
8400: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.238 brouard 8401: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8402: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8403: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 8404: /* vlv= nbcode[Tvaraff[k]][lv]; */
8405: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.223 brouard 8406: kl++;
1.238 brouard 8407: /* 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 *\/ */
8408: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8409: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8410: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
8411: if(k==cptcoveff){
1.245 brouard 8412: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 8413: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 8414: }else{
1.332 brouard 8415: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]);
1.238 brouard 8416: kl++;
8417: }
8418: } /* end covariate */
8419: } /* end if no covariate */
1.296 brouard 8420: if(prevbcast == 1){
1.268 brouard 8421: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
8422: /* k1-1 error should be nres-1*/
8423: for (i=1; i<= nlstate ; i ++) {
8424: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8425: else fprintf(ficgp," %%*lf (%%*lf)");
8426: }
1.271 brouard 8427: 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 8428: for (i=1; i<= nlstate ; i ++) {
8429: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8430: else fprintf(ficgp," %%*lf (%%*lf)");
8431: }
1.276 brouard 8432: 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 8433: for (i=1; i<= nlstate ; i ++) {
8434: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8435: else fprintf(ficgp," %%*lf (%%*lf)");
8436: }
1.274 brouard 8437: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 8438: } /* end if backprojcast */
1.296 brouard 8439: } /* end if prevbcast */
1.276 brouard 8440: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
8441: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 8442: } /* nres */
1.337 brouard 8443: /* } /\* k1 *\/ */
1.201 brouard 8444: } /* cpt */
1.235 brouard 8445:
8446:
1.126 brouard 8447: /*2 eme*/
1.337 brouard 8448: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 8449: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8450: k1=TKresult[nres];
1.338 brouard 8451: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8452: /* if(m != 1 && TKresult[nres]!= k1) */
8453: /* continue; */
1.238 brouard 8454: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 8455: strcpy(gplotlabel,"(");
1.337 brouard 8456: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8457: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8458: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8459: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8460: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8461: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8462: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8463: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8464: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8465: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8466: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8467: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8468: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8469: /* } */
8470: /* /\* for(k=1; k <= ncovds; k++){ *\/ */
8471: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8472: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8473: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8474: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 8475: }
1.264 brouard 8476: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8477: fprintf(ficgp,"\n#\n");
1.223 brouard 8478: if(invalidvarcomb[k1]){
8479: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8480: continue;
8481: }
1.219 brouard 8482:
1.241 brouard 8483: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 8484: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 8485: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
8486: if(vpopbased==0){
1.238 brouard 8487: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 8488: }else
1.238 brouard 8489: fprintf(ficgp,"\nreplot ");
8490: for (i=1; i<= nlstate+1 ; i ++) {
8491: k=2*i;
1.261 brouard 8492: 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 8493: for (j=1; j<= nlstate+1 ; j ++) {
8494: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8495: else fprintf(ficgp," %%*lf (%%*lf)");
8496: }
8497: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
8498: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 8499: 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 8500: for (j=1; j<= nlstate+1 ; j ++) {
8501: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8502: else fprintf(ficgp," %%*lf (%%*lf)");
8503: }
8504: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 8505: 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 8506: for (j=1; j<= nlstate+1 ; j ++) {
8507: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8508: else fprintf(ficgp," %%*lf (%%*lf)");
8509: }
8510: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
8511: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
8512: } /* state */
8513: } /* vpopbased */
1.264 brouard 8514: 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 8515: } /* end nres */
1.337 brouard 8516: /* } /\* k1 end 2 eme*\/ */
1.238 brouard 8517:
8518:
8519: /*3eme*/
1.337 brouard 8520: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 8521: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8522: k1=TKresult[nres];
1.338 brouard 8523: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8524: /* if(m != 1 && TKresult[nres]!= k1) */
8525: /* continue; */
1.238 brouard 8526:
1.332 brouard 8527: for (cpt=1; cpt<= nlstate ; cpt ++) { /* Fragile no verification of covariate values */
1.261 brouard 8528: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 8529: strcpy(gplotlabel,"(");
1.337 brouard 8530: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8531: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8532: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8533: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8534: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8535: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8536: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8537: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8538: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8539: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8540: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8541: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8542: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8543: /* } */
8544: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8545: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
8546: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
8547: }
1.264 brouard 8548: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8549: fprintf(ficgp,"\n#\n");
8550: if(invalidvarcomb[k1]){
8551: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8552: continue;
8553: }
8554:
8555: /* k=2+nlstate*(2*cpt-2); */
8556: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 8557: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 8558: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 8559: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 8560: 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 8561: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8562: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8563: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
8564: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8565: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8566: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 8567:
1.238 brouard 8568: */
8569: for (i=1; i< nlstate ; i ++) {
1.261 brouard 8570: 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 8571: /* 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 8572:
1.238 brouard 8573: }
1.261 brouard 8574: 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 8575: }
1.264 brouard 8576: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 8577: } /* end nres */
1.337 brouard 8578: /* } /\* end kl 3eme *\/ */
1.126 brouard 8579:
1.223 brouard 8580: /* 4eme */
1.201 brouard 8581: /* Survival functions (period) from state i in state j by initial state i */
1.337 brouard 8582: /* for (k1=1; k1<=m; k1++){ /\* For each covariate and each value *\/ */
1.238 brouard 8583: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8584: k1=TKresult[nres];
1.338 brouard 8585: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8586: /* if(m != 1 && TKresult[nres]!= k1) */
8587: /* continue; */
1.238 brouard 8588: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 8589: strcpy(gplotlabel,"(");
1.337 brouard 8590: fprintf(ficgp,"\n#\n#\n# Survival functions in state %d : 'LIJ_' files, cov=%d state=%d", cpt, k1, cpt);
8591: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8592: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8593: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8594: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8595: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8596: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8597: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8598: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8599: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8600: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8601: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8602: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8603: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8604: /* } */
8605: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8606: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8607: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 8608: }
1.264 brouard 8609: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8610: fprintf(ficgp,"\n#\n");
8611: if(invalidvarcomb[k1]){
8612: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8613: continue;
1.223 brouard 8614: }
1.238 brouard 8615:
1.241 brouard 8616: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 8617: 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 8618: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8619: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8620: k=3;
8621: for (i=1; i<= nlstate ; i ++){
8622: if(i==1){
8623: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8624: }else{
8625: fprintf(ficgp,", '' ");
8626: }
8627: l=(nlstate+ndeath)*(i-1)+1;
8628: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8629: for (j=2; j<= nlstate+ndeath ; j ++)
8630: fprintf(ficgp,"+$%d",k+l+j-1);
8631: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
8632: } /* nlstate */
1.264 brouard 8633: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8634: } /* end cpt state*/
8635: } /* end nres */
1.337 brouard 8636: /* } /\* end covariate k1 *\/ */
1.238 brouard 8637:
1.220 brouard 8638: /* 5eme */
1.201 brouard 8639: /* Survival functions (period) from state i in state j by final state j */
1.337 brouard 8640: /* for (k1=1; k1<= m ; k1++){ /\* For each covariate combination if any *\/ */
1.238 brouard 8641: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8642: k1=TKresult[nres];
1.338 brouard 8643: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8644: /* if(m != 1 && TKresult[nres]!= k1) */
8645: /* continue; */
1.238 brouard 8646: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 8647: strcpy(gplotlabel,"(");
1.238 brouard 8648: 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 8649: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8650: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8651: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8652: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8653: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8654: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8655: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8656: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8657: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8658: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8659: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8660: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8661: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8662: /* } */
8663: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8664: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8665: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 8666: }
1.264 brouard 8667: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8668: fprintf(ficgp,"\n#\n");
8669: if(invalidvarcomb[k1]){
8670: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8671: continue;
8672: }
1.227 brouard 8673:
1.241 brouard 8674: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 8675: 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 8676: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8677: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8678: k=3;
8679: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8680: if(j==1)
8681: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8682: else
8683: fprintf(ficgp,", '' ");
8684: l=(nlstate+ndeath)*(cpt-1) +j;
8685: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
8686: /* for (i=2; i<= nlstate+ndeath ; i ++) */
8687: /* fprintf(ficgp,"+$%d",k+l+i-1); */
8688: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
8689: } /* nlstate */
8690: fprintf(ficgp,", '' ");
8691: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
8692: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8693: l=(nlstate+ndeath)*(cpt-1) +j;
8694: if(j < nlstate)
8695: fprintf(ficgp,"$%d +",k+l);
8696: else
8697: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
8698: }
1.264 brouard 8699: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8700: } /* end cpt state*/
1.337 brouard 8701: /* } /\* end covariate *\/ */
1.238 brouard 8702: } /* end nres */
1.227 brouard 8703:
1.220 brouard 8704: /* 6eme */
1.202 brouard 8705: /* CV preval stable (period) for each covariate */
1.337 brouard 8706: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8707: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8708: k1=TKresult[nres];
1.338 brouard 8709: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8710: /* if(m != 1 && TKresult[nres]!= k1) */
8711: /* continue; */
1.255 brouard 8712: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 8713: strcpy(gplotlabel,"(");
1.288 brouard 8714: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 8715: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8716: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8717: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8718: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8719: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8720: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8721: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8722: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8723: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8724: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8725: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8726: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8727: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8728: /* } */
8729: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8730: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8731: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 8732: }
1.264 brouard 8733: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8734: fprintf(ficgp,"\n#\n");
1.223 brouard 8735: if(invalidvarcomb[k1]){
1.227 brouard 8736: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8737: continue;
1.223 brouard 8738: }
1.227 brouard 8739:
1.241 brouard 8740: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 8741: 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 8742: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 8743: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 8744: k=3; /* Offset */
1.255 brouard 8745: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 8746: if(i==1)
8747: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8748: else
8749: fprintf(ficgp,", '' ");
1.255 brouard 8750: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 8751: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8752: for (j=2; j<= nlstate ; j ++)
8753: fprintf(ficgp,"+$%d",k+l+j-1);
8754: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 8755: } /* nlstate */
1.264 brouard 8756: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 8757: } /* end cpt state*/
8758: } /* end covariate */
1.227 brouard 8759:
8760:
1.220 brouard 8761: /* 7eme */
1.296 brouard 8762: if(prevbcast == 1){
1.288 brouard 8763: /* CV backward prevalence for each covariate */
1.337 brouard 8764: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8765: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8766: k1=TKresult[nres];
1.338 brouard 8767: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8768: /* if(m != 1 && TKresult[nres]!= k1) */
8769: /* continue; */
1.268 brouard 8770: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 8771: strcpy(gplotlabel,"(");
1.288 brouard 8772: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 8773: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8774: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8775: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8776: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8777: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8778: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8779: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8780: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8781: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8782: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8783: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8784: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8785: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8786: /* } */
8787: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8788: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8789: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 8790: }
1.264 brouard 8791: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 8792: fprintf(ficgp,"\n#\n");
8793: if(invalidvarcomb[k1]){
8794: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8795: continue;
8796: }
8797:
1.241 brouard 8798: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 8799: 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 8800: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 8801: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 8802: k=3; /* Offset */
1.268 brouard 8803: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 8804: if(i==1)
8805: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
8806: else
8807: fprintf(ficgp,", '' ");
8808: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 8809: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.324 brouard 8810: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
8811: /* 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 8812: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 8813: /* for (j=2; j<= nlstate ; j ++) */
8814: /* fprintf(ficgp,"+$%d",k+l+j-1); */
8815: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 8816: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 8817: } /* nlstate */
1.264 brouard 8818: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 8819: } /* end cpt state*/
8820: } /* end covariate */
1.296 brouard 8821: } /* End if prevbcast */
1.218 brouard 8822:
1.223 brouard 8823: /* 8eme */
1.218 brouard 8824: if(prevfcast==1){
1.288 brouard 8825: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 8826:
1.337 brouard 8827: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8828: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8829: k1=TKresult[nres];
1.338 brouard 8830: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8831: /* if(m != 1 && TKresult[nres]!= k1) */
8832: /* continue; */
1.211 brouard 8833: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 8834: strcpy(gplotlabel,"(");
1.288 brouard 8835: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 8836: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8837: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8838: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8839: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
8840: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
8841: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8842: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8843: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8844: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8845: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8846: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8847: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8848: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8849: /* } */
8850: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8851: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8852: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 8853: }
1.264 brouard 8854: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 8855: fprintf(ficgp,"\n#\n");
8856: if(invalidvarcomb[k1]){
8857: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8858: continue;
8859: }
8860:
8861: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 8862: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 8863: 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 8864: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 8865: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 8866:
8867: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
8868: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
8869: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
8870: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 8871: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8872: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8873: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8874: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 8875: if(i==istart){
1.227 brouard 8876: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
8877: }else{
8878: fprintf(ficgp,",\\\n '' ");
8879: }
8880: if(cptcoveff ==0){ /* No covariate */
8881: ioffset=2; /* Age is in 2 */
8882: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8883: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8884: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8885: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8886: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 8887: if(i==nlstate+1){
1.270 brouard 8888: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 8889: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
8890: fprintf(ficgp,",\\\n '' ");
8891: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 8892: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 8893: offyear, \
1.268 brouard 8894: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 8895: }else
1.227 brouard 8896: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
8897: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
8898: }else{ /* more than 2 covariates */
1.270 brouard 8899: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
8900: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8901: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8902: iyearc=ioffset-1;
8903: iagec=ioffset;
1.227 brouard 8904: fprintf(ficgp," u %d:(",ioffset);
8905: kl=0;
8906: strcpy(gplotcondition,"(");
8907: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
1.332 brouard 8908: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8909: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.227 brouard 8910: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8911: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8912: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 8913: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
8914: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.227 brouard 8915: kl++;
8916: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
8917: kl++;
8918: if(k <cptcoveff && cptcoveff>1)
8919: sprintf(gplotcondition+strlen(gplotcondition)," && ");
8920: }
8921: strcpy(gplotcondition+strlen(gplotcondition),")");
8922: /* 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 *\/ */
8923: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8924: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8925: /* '' 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*/
8926: if(i==nlstate+1){
1.270 brouard 8927: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
8928: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 8929: fprintf(ficgp,",\\\n '' ");
1.270 brouard 8930: fprintf(ficgp," u %d:(",iagec);
8931: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
8932: iyearc, iagec, offyear, \
8933: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 8934: /* '' 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 8935: }else{
8936: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
8937: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
8938: }
8939: } /* end if covariate */
8940: } /* nlstate */
1.264 brouard 8941: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 8942: } /* end cpt state*/
8943: } /* end covariate */
8944: } /* End if prevfcast */
1.227 brouard 8945:
1.296 brouard 8946: if(prevbcast==1){
1.268 brouard 8947: /* Back projection from cross-sectional to stable (mixed) for each covariate */
8948:
1.337 brouard 8949: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.268 brouard 8950: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8951: k1=TKresult[nres];
1.338 brouard 8952: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8953: /* if(m != 1 && TKresult[nres]!= k1) */
8954: /* continue; */
1.268 brouard 8955: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
8956: strcpy(gplotlabel,"(");
8957: 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 8958: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8959: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8960: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8961: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
8962: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
8963: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8964: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8965: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8966: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8967: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8968: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8969: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8970: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8971: /* } */
8972: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8973: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8974: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.268 brouard 8975: }
8976: strcpy(gplotlabel+strlen(gplotlabel),")");
8977: fprintf(ficgp,"\n#\n");
8978: if(invalidvarcomb[k1]){
8979: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8980: continue;
8981: }
8982:
8983: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
8984: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
8985: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
8986: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
8987: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8988:
8989: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
8990: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
8991: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
8992: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
8993: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8994: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8995: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8996: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8997: if(i==istart){
8998: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
8999: }else{
9000: fprintf(ficgp,",\\\n '' ");
9001: }
9002: if(cptcoveff ==0){ /* No covariate */
9003: ioffset=2; /* Age is in 2 */
9004: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9005: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9006: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9007: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9008: fprintf(ficgp," u %d:(", ioffset);
9009: if(i==nlstate+1){
1.270 brouard 9010: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 9011: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
9012: fprintf(ficgp,",\\\n '' ");
9013: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 9014: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 9015: offbyear, \
9016: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
9017: }else
9018: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
9019: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
9020: }else{ /* more than 2 covariates */
1.270 brouard 9021: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
9022: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9023: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9024: iyearc=ioffset-1;
9025: iagec=ioffset;
1.268 brouard 9026: fprintf(ficgp," u %d:(",ioffset);
9027: kl=0;
9028: strcpy(gplotcondition,"(");
1.337 brouard 9029: for (k=1; k<=cptcovs; k++){ /* For each covariate k of the resultline, get corresponding value lv for combination k1 */
1.338 brouard 9030: if(Dummy[modelresult[nres][k]]==0){ /* To be verified */
1.337 brouard 9031: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate writing the chain of conditions *\/ */
9032: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9033: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9034: lv=Tvresult[nres][k];
9035: vlv=TinvDoQresult[nres][Tvresult[nres][k]];
9036: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
9037: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
9038: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
9039: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
9040: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9041: kl++;
9042: /* sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); */
9043: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%lg " ,kl,Tvresult[nres][k], kl+1,TinvDoQresult[nres][Tvresult[nres][k]]);
9044: kl++;
1.338 brouard 9045: if(k <cptcovs && cptcovs>1)
1.337 brouard 9046: sprintf(gplotcondition+strlen(gplotcondition)," && ");
9047: }
1.268 brouard 9048: }
9049: strcpy(gplotcondition+strlen(gplotcondition),")");
9050: /* 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 *\/ */
9051: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
9052: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
9053: /* '' 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*/
9054: if(i==nlstate+1){
1.270 brouard 9055: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
9056: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 9057: fprintf(ficgp,",\\\n '' ");
1.270 brouard 9058: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 9059: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 9060: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
9061: iyearc,iagec,offbyear, \
9062: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 9063: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
9064: }else{
9065: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
9066: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
9067: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
9068: }
9069: } /* end if covariate */
9070: } /* nlstate */
9071: fprintf(ficgp,"\nset out; unset label;\n");
9072: } /* end cpt state*/
9073: } /* end covariate */
1.296 brouard 9074: } /* End if prevbcast */
1.268 brouard 9075:
1.227 brouard 9076:
1.238 brouard 9077: /* 9eme writing MLE parameters */
9078: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 9079: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 9080: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 9081: for(k=1; k <=(nlstate+ndeath); k++){
9082: if (k != i) {
1.227 brouard 9083: fprintf(ficgp,"# current state %d\n",k);
9084: for(j=1; j <=ncovmodel; j++){
9085: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
9086: jk++;
9087: }
9088: fprintf(ficgp,"\n");
1.126 brouard 9089: }
9090: }
1.223 brouard 9091: }
1.187 brouard 9092: fprintf(ficgp,"##############\n#\n");
1.227 brouard 9093:
1.145 brouard 9094: /*goto avoid;*/
1.238 brouard 9095: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
9096: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 9097: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
9098: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
9099: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
9100: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
9101: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
9102: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
9103: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
9104: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
9105: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
9106: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
9107: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
9108: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
9109: fprintf(ficgp,"#\n");
1.223 brouard 9110: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 9111: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.338 brouard 9112: fprintf(ficgp,"#model=1+age+%s \n",model);
1.238 brouard 9113: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 brouard 9114: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
1.337 brouard 9115: /* for(k1=1; k1 <=m; k1++) /\* For each combination of covariate *\/ */
1.237 brouard 9116: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9117: /* k1=nres; */
1.338 brouard 9118: k1=TKresult[nres];
9119: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9120: fprintf(ficgp,"\n\n# Resultline k1=%d ",k1);
1.264 brouard 9121: strcpy(gplotlabel,"(");
1.276 brouard 9122: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.337 brouard 9123: for (k=1; k<=cptcovs; k++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
9124: /* for each resultline nres, and position k, Tvresult[nres][k] gives the name of the variable and
9125: TinvDoQresult[nres][Tvresult[nres][k]] gives its value double or integer) */
9126: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9127: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9128: }
9129: /* if(m != 1 && TKresult[nres]!= k1) */
9130: /* continue; */
9131: /* fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1); */
9132: /* strcpy(gplotlabel,"("); */
9133: /* /\*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*\/ */
9134: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
9135: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
9136: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9137: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9138: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9139: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9140: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9141: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9142: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9143: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9144: /* } */
9145: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9146: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9147: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9148: /* } */
1.264 brouard 9149: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 9150: fprintf(ficgp,"\n#\n");
1.264 brouard 9151: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 9152: fprintf(ficgp,"\nset key outside ");
9153: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
9154: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 9155: fprintf(ficgp,"\nset ter svg size 640, 480 ");
9156: if (ng==1){
9157: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
9158: fprintf(ficgp,"\nunset log y");
9159: }else if (ng==2){
9160: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
9161: fprintf(ficgp,"\nset log y");
9162: }else if (ng==3){
9163: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
9164: fprintf(ficgp,"\nset log y");
9165: }else
9166: fprintf(ficgp,"\nunset title ");
9167: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
9168: i=1;
9169: for(k2=1; k2<=nlstate; k2++) {
9170: k3=i;
9171: for(k=1; k<=(nlstate+ndeath); k++) {
9172: if (k != k2){
9173: switch( ng) {
9174: case 1:
9175: if(nagesqr==0)
9176: fprintf(ficgp," p%d+p%d*x",i,i+1);
9177: else /* nagesqr =1 */
9178: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
9179: break;
9180: case 2: /* ng=2 */
9181: if(nagesqr==0)
9182: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
9183: else /* nagesqr =1 */
9184: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
9185: break;
9186: case 3:
9187: if(nagesqr==0)
9188: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
9189: else /* nagesqr =1 */
9190: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
9191: break;
9192: }
9193: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 9194: ijp=1; /* product no age */
9195: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
9196: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 9197: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.329 brouard 9198: switch(Typevar[j]){
9199: case 1:
9200: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
9201: if(j==Tage[ij]) { /* Product by age To be looked at!!*//* Bug valgrind */
9202: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
9203: if(DummyV[j]==0){/* Bug valgrind */
9204: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
9205: }else{ /* quantitative */
9206: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
9207: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9208: }
9209: ij++;
1.268 brouard 9210: }
1.237 brouard 9211: }
1.329 brouard 9212: }
9213: break;
9214: case 2:
9215: if(cptcovprod >0){
9216: if(j==Tprod[ijp]) { /* */
9217: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9218: if(ijp <=cptcovprod) { /* Product */
9219: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
9220: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
9221: /* 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)]); */
9222: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9223: }else{ /* Vn is dummy and Vm is quanti */
9224: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
9225: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9226: }
9227: }else{ /* Vn*Vm Vn is quanti */
9228: if(DummyV[Tvard[ijp][2]]==0){
9229: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
9230: }else{ /* Both quanti */
9231: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9232: }
1.268 brouard 9233: }
1.329 brouard 9234: ijp++;
1.237 brouard 9235: }
1.329 brouard 9236: } /* end Tprod */
9237: }
9238: break;
9239: case 0:
9240: /* simple covariate */
1.264 brouard 9241: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 9242: if(Dummy[j]==0){
9243: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
9244: }else{ /* quantitative */
9245: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 9246: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 9247: }
1.329 brouard 9248: /* end simple */
9249: break;
9250: default:
9251: break;
9252: } /* end switch */
1.237 brouard 9253: } /* end j */
1.329 brouard 9254: }else{ /* k=k2 */
9255: if(ng !=1 ){ /* For logit formula of log p11 is more difficult to get */
9256: fprintf(ficgp," (1.");i=i-ncovmodel;
9257: }else
9258: i=i-ncovmodel;
1.223 brouard 9259: }
1.227 brouard 9260:
1.223 brouard 9261: if(ng != 1){
9262: fprintf(ficgp,")/(1");
1.227 brouard 9263:
1.264 brouard 9264: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 9265: if(nagesqr==0)
1.264 brouard 9266: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 9267: else /* nagesqr =1 */
1.264 brouard 9268: 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 9269:
1.223 brouard 9270: ij=1;
1.329 brouard 9271: ijp=1;
9272: /* for(j=3; j <=ncovmodel-nagesqr; j++){ */
9273: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
9274: switch(Typevar[j]){
9275: case 1:
9276: if(cptcovage >0){
9277: if(j==Tage[ij]) { /* Bug valgrind */
9278: if(ij <=cptcovage) { /* Bug valgrind */
9279: if(DummyV[j]==0){/* Bug valgrind */
9280: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]); */
9281: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,nbcode[Tvar[j]][codtabm(k1,j)]); */
9282: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]);
9283: /* fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);; */
9284: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9285: }else{ /* quantitative */
9286: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
9287: fprintf(ficgp,"+p%d*%f*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
9288: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
9289: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9290: }
9291: ij++;
9292: }
9293: }
9294: }
9295: break;
9296: case 2:
9297: if(cptcovprod >0){
9298: if(j==Tprod[ijp]) { /* */
9299: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9300: if(ijp <=cptcovprod) { /* Product */
9301: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
9302: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
9303: /* 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)]); */
9304: fprintf(ficgp,"+p%d*%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9305: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
9306: }else{ /* Vn is dummy and Vm is quanti */
9307: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
9308: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9309: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9310: }
9311: }else{ /* Vn*Vm Vn is quanti */
9312: if(DummyV[Tvard[ijp][2]]==0){
9313: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
9314: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
9315: }else{ /* Both quanti */
9316: fprintf(ficgp,"+p%d*%f*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9317: /* fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9318: }
9319: }
9320: ijp++;
9321: }
9322: } /* end Tprod */
9323: } /* end if */
9324: break;
9325: case 0:
9326: /* simple covariate */
9327: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
9328: if(Dummy[j]==0){
9329: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
9330: fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]); /* */
9331: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
9332: }else{ /* quantitative */
9333: fprintf(ficgp,"+p%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* */
9334: /* fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* *\/ */
9335: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9336: }
9337: /* end simple */
9338: /* fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);/\* Valgrind bug nbcode *\/ */
9339: break;
9340: default:
9341: break;
9342: } /* end switch */
1.223 brouard 9343: }
9344: fprintf(ficgp,")");
9345: }
9346: fprintf(ficgp,")");
9347: if(ng ==2)
1.276 brouard 9348: 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 9349: else /* ng= 3 */
1.276 brouard 9350: 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 9351: }else{ /* end ng <> 1 */
1.223 brouard 9352: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 9353: 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 9354: }
9355: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
9356: fprintf(ficgp,",");
9357: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
9358: fprintf(ficgp,",");
9359: i=i+ncovmodel;
9360: } /* end k */
9361: } /* end k2 */
1.276 brouard 9362: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
9363: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.337 brouard 9364: } /* end resultline */
1.223 brouard 9365: } /* end ng */
9366: /* avoid: */
9367: fflush(ficgp);
1.126 brouard 9368: } /* end gnuplot */
9369:
9370:
9371: /*************** Moving average **************/
1.219 brouard 9372: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 9373: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 9374:
1.222 brouard 9375: int i, cpt, cptcod;
9376: int modcovmax =1;
9377: int mobilavrange, mob;
9378: int iage=0;
1.288 brouard 9379: int firstA1=0, firstA2=0;
1.222 brouard 9380:
1.266 brouard 9381: double sum=0., sumr=0.;
1.222 brouard 9382: double age;
1.266 brouard 9383: double *sumnewp, *sumnewm, *sumnewmr;
9384: double *agemingood, *agemaxgood;
9385: double *agemingoodr, *agemaxgoodr;
1.222 brouard 9386:
9387:
1.278 brouard 9388: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
9389: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 9390:
9391: sumnewp = vector(1,ncovcombmax);
9392: sumnewm = vector(1,ncovcombmax);
1.266 brouard 9393: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 9394: agemingood = vector(1,ncovcombmax);
1.266 brouard 9395: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 9396: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 9397: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 9398:
9399: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 9400: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 9401: sumnewp[cptcod]=0.;
1.266 brouard 9402: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
9403: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 9404: }
9405: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
9406:
1.266 brouard 9407: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
9408: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 9409: else mobilavrange=mobilav;
9410: for (age=bage; age<=fage; age++)
9411: for (i=1; i<=nlstate;i++)
9412: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
9413: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9414: /* We keep the original values on the extreme ages bage, fage and for
9415: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
9416: we use a 5 terms etc. until the borders are no more concerned.
9417: */
9418: for (mob=3;mob <=mobilavrange;mob=mob+2){
9419: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 9420: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
9421: sumnewm[cptcod]=0.;
9422: for (i=1; i<=nlstate;i++){
1.222 brouard 9423: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
9424: for (cpt=1;cpt<=(mob-1)/2;cpt++){
9425: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
9426: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
9427: }
9428: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 9429: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9430: } /* end i */
9431: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
9432: } /* end cptcod */
1.222 brouard 9433: }/* end age */
9434: }/* end mob */
1.266 brouard 9435: }else{
9436: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 9437: return -1;
1.266 brouard 9438: }
9439:
9440: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 9441: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
9442: if(invalidvarcomb[cptcod]){
9443: printf("\nCombination (%d) ignored because no cases \n",cptcod);
9444: continue;
9445: }
1.219 brouard 9446:
1.266 brouard 9447: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
9448: sumnewm[cptcod]=0.;
9449: sumnewmr[cptcod]=0.;
9450: for (i=1; i<=nlstate;i++){
9451: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9452: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9453: }
9454: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9455: agemingoodr[cptcod]=age;
9456: }
9457: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9458: agemingood[cptcod]=age;
9459: }
9460: } /* age */
9461: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 9462: sumnewm[cptcod]=0.;
1.266 brouard 9463: sumnewmr[cptcod]=0.;
1.222 brouard 9464: for (i=1; i<=nlstate;i++){
9465: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 9466: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9467: }
9468: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9469: agemaxgoodr[cptcod]=age;
1.222 brouard 9470: }
9471: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 9472: agemaxgood[cptcod]=age;
9473: }
9474: } /* age */
9475: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
9476: /* but they will change */
1.288 brouard 9477: firstA1=0;firstA2=0;
1.266 brouard 9478: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
9479: sumnewm[cptcod]=0.;
9480: sumnewmr[cptcod]=0.;
9481: for (i=1; i<=nlstate;i++){
9482: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9483: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9484: }
9485: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
9486: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9487: agemaxgoodr[cptcod]=age; /* age min */
9488: for (i=1; i<=nlstate;i++)
9489: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9490: }else{ /* bad we change the value with the values of good ages */
9491: for (i=1; i<=nlstate;i++){
9492: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
9493: } /* i */
9494: } /* end bad */
9495: }else{
9496: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9497: agemaxgood[cptcod]=age;
9498: }else{ /* bad we change the value with the values of good ages */
9499: for (i=1; i<=nlstate;i++){
9500: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
9501: } /* i */
9502: } /* end bad */
9503: }/* end else */
9504: sum=0.;sumr=0.;
9505: for (i=1; i<=nlstate;i++){
9506: sum+=mobaverage[(int)age][i][cptcod];
9507: sumr+=probs[(int)age][i][cptcod];
9508: }
9509: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 9510: if(!firstA1){
9511: firstA1=1;
9512: 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);
9513: }
9514: 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 9515: } /* end bad */
9516: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
9517: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 9518: if(!firstA2){
9519: firstA2=1;
9520: 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);
9521: }
9522: 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 9523: } /* end bad */
9524: }/* age */
1.266 brouard 9525:
9526: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 9527: sumnewm[cptcod]=0.;
1.266 brouard 9528: sumnewmr[cptcod]=0.;
1.222 brouard 9529: for (i=1; i<=nlstate;i++){
9530: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 9531: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9532: }
9533: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
9534: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
9535: agemingoodr[cptcod]=age;
9536: for (i=1; i<=nlstate;i++)
9537: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9538: }else{ /* bad we change the value with the values of good ages */
9539: for (i=1; i<=nlstate;i++){
9540: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
9541: } /* i */
9542: } /* end bad */
9543: }else{
9544: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9545: agemingood[cptcod]=age;
9546: }else{ /* bad */
9547: for (i=1; i<=nlstate;i++){
9548: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
9549: } /* i */
9550: } /* end bad */
9551: }/* end else */
9552: sum=0.;sumr=0.;
9553: for (i=1; i<=nlstate;i++){
9554: sum+=mobaverage[(int)age][i][cptcod];
9555: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 9556: }
1.266 brouard 9557: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 9558: 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 9559: } /* end bad */
9560: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
9561: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 9562: 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 9563: } /* end bad */
9564: }/* age */
1.266 brouard 9565:
1.222 brouard 9566:
9567: for (age=bage; age<=fage; age++){
1.235 brouard 9568: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 9569: sumnewp[cptcod]=0.;
9570: sumnewm[cptcod]=0.;
9571: for (i=1; i<=nlstate;i++){
9572: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
9573: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9574: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
9575: }
9576: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
9577: }
9578: /* printf("\n"); */
9579: /* } */
1.266 brouard 9580:
1.222 brouard 9581: /* brutal averaging */
1.266 brouard 9582: /* for (i=1; i<=nlstate;i++){ */
9583: /* for (age=1; age<=bage; age++){ */
9584: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
9585: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
9586: /* } */
9587: /* for (age=fage; age<=AGESUP; age++){ */
9588: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
9589: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
9590: /* } */
9591: /* } /\* end i status *\/ */
9592: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
9593: /* for (age=1; age<=AGESUP; age++){ */
9594: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
9595: /* mobaverage[(int)age][i][cptcod]=0.; */
9596: /* } */
9597: /* } */
1.222 brouard 9598: }/* end cptcod */
1.266 brouard 9599: free_vector(agemaxgoodr,1, ncovcombmax);
9600: free_vector(agemaxgood,1, ncovcombmax);
9601: free_vector(agemingood,1, ncovcombmax);
9602: free_vector(agemingoodr,1, ncovcombmax);
9603: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 9604: free_vector(sumnewm,1, ncovcombmax);
9605: free_vector(sumnewp,1, ncovcombmax);
9606: return 0;
9607: }/* End movingaverage */
1.218 brouard 9608:
1.126 brouard 9609:
1.296 brouard 9610:
1.126 brouard 9611: /************** Forecasting ******************/
1.296 brouard 9612: /* 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)*/
9613: 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){
9614: /* dateintemean, mean date of interviews
9615: dateprojd, year, month, day of starting projection
9616: dateprojf date of end of projection;year of end of projection (same day and month as proj1).
1.126 brouard 9617: agemin, agemax range of age
9618: dateprev1 dateprev2 range of dates during which prevalence is computed
9619: */
1.296 brouard 9620: /* double anprojd, mprojd, jprojd; */
9621: /* double anprojf, mprojf, jprojf; */
1.267 brouard 9622: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 9623: double agec; /* generic age */
1.296 brouard 9624: double agelim, ppij, yp,yp1,yp2;
1.126 brouard 9625: double *popeffectif,*popcount;
9626: double ***p3mat;
1.218 brouard 9627: /* double ***mobaverage; */
1.126 brouard 9628: char fileresf[FILENAMELENGTH];
9629:
9630: agelim=AGESUP;
1.211 brouard 9631: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
9632: in each health status at the date of interview (if between dateprev1 and dateprev2).
9633: We still use firstpass and lastpass as another selection.
9634: */
1.214 brouard 9635: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
9636: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 9637:
1.201 brouard 9638: strcpy(fileresf,"F_");
9639: strcat(fileresf,fileresu);
1.126 brouard 9640: if((ficresf=fopen(fileresf,"w"))==NULL) {
9641: printf("Problem with forecast resultfile: %s\n", fileresf);
9642: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
9643: }
1.235 brouard 9644: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
9645: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 9646:
1.225 brouard 9647: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 9648:
9649:
9650: stepsize=(int) (stepm+YEARM-1)/YEARM;
9651: if (stepm<=12) stepsize=1;
9652: if(estepm < stepm){
9653: printf ("Problem %d lower than %d\n",estepm, stepm);
9654: }
1.270 brouard 9655: else{
9656: hstepm=estepm;
9657: }
9658: if(estepm > stepm){ /* Yes every two year */
9659: stepsize=2;
9660: }
1.296 brouard 9661: hstepm=hstepm/stepm;
1.126 brouard 9662:
1.296 brouard 9663:
9664: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
9665: /* fractional in yp1 *\/ */
9666: /* aintmean=yp; */
9667: /* yp2=modf((yp1*12),&yp); */
9668: /* mintmean=yp; */
9669: /* yp1=modf((yp2*30.5),&yp); */
9670: /* jintmean=yp; */
9671: /* if(jintmean==0) jintmean=1; */
9672: /* if(mintmean==0) mintmean=1; */
1.126 brouard 9673:
1.296 brouard 9674:
9675: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */
9676: /* date2dmy(dateprojd,&jprojd, &mprojd, &anprojd); */
9677: /* date2dmy(dateprojf,&jprojf, &mprojf, &anprojf); */
1.227 brouard 9678: i1=pow(2,cptcoveff);
1.126 brouard 9679: if (cptcovn < 1){i1=1;}
9680:
1.296 brouard 9681: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.126 brouard 9682:
9683: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 9684:
1.126 brouard 9685: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 9686: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.332 brouard 9687: 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 9688: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 9689: continue;
1.227 brouard 9690: if(invalidvarcomb[k]){
9691: printf("\nCombination (%d) projection ignored because no cases \n",k);
9692: continue;
9693: }
9694: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
9695: for(j=1;j<=cptcoveff;j++) {
1.332 brouard 9696: /* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); */
9697: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.227 brouard 9698: }
1.235 brouard 9699: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 9700: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 9701: }
1.227 brouard 9702: fprintf(ficresf," yearproj age");
9703: for(j=1; j<=nlstate+ndeath;j++){
9704: for(i=1; i<=nlstate;i++)
9705: fprintf(ficresf," p%d%d",i,j);
9706: fprintf(ficresf," wp.%d",j);
9707: }
1.296 brouard 9708: for (yearp=0; yearp<=(anprojf-anprojd);yearp +=stepsize) {
1.227 brouard 9709: fprintf(ficresf,"\n");
1.296 brouard 9710: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jprojd,mprojd,anprojd+yearp);
1.270 brouard 9711: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
9712: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 9713: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
9714: nhstepm = nhstepm/hstepm;
9715: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9716: oldm=oldms;savm=savms;
1.268 brouard 9717: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 9718: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 9719: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 9720: for (h=0; h<=nhstepm; h++){
9721: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 9722: break;
9723: }
9724: }
9725: fprintf(ficresf,"\n");
9726: for(j=1;j<=cptcoveff;j++)
1.332 brouard 9727: /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Tvaraff not correct *\/ */
9728: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /* TnsdVar[Tvaraff] correct */
1.296 brouard 9729: fprintf(ficresf,"%.f %.f ",anprojd+yearp,agec+h*hstepm/YEARM*stepm);
1.268 brouard 9730:
9731: for(j=1; j<=nlstate+ndeath;j++) {
9732: ppij=0.;
9733: for(i=1; i<=nlstate;i++) {
1.278 brouard 9734: if (mobilav>=1)
9735: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
9736: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
9737: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
9738: }
1.268 brouard 9739: fprintf(ficresf," %.3f", p3mat[i][j][h]);
9740: } /* end i */
9741: fprintf(ficresf," %.3f", ppij);
9742: }/* end j */
1.227 brouard 9743: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9744: } /* end agec */
1.266 brouard 9745: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
9746: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 9747: } /* end yearp */
9748: } /* end k */
1.219 brouard 9749:
1.126 brouard 9750: fclose(ficresf);
1.215 brouard 9751: printf("End of Computing forecasting \n");
9752: fprintf(ficlog,"End of Computing forecasting\n");
9753:
1.126 brouard 9754: }
9755:
1.269 brouard 9756: /************** Back Forecasting ******************/
1.296 brouard 9757: /* 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){ */
9758: 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){
9759: /* back1, year, month, day of starting backprojection
1.267 brouard 9760: agemin, agemax range of age
9761: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 9762: anback2 year of end of backprojection (same day and month as back1).
9763: prevacurrent and prev are prevalences.
1.267 brouard 9764: */
9765: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
9766: double agec; /* generic age */
1.302 brouard 9767: double agelim, ppij, ppi, yp,yp1,yp2; /* ,jintmean,mintmean,aintmean;*/
1.267 brouard 9768: double *popeffectif,*popcount;
9769: double ***p3mat;
9770: /* double ***mobaverage; */
9771: char fileresfb[FILENAMELENGTH];
9772:
1.268 brouard 9773: agelim=AGEINF;
1.267 brouard 9774: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
9775: in each health status at the date of interview (if between dateprev1 and dateprev2).
9776: We still use firstpass and lastpass as another selection.
9777: */
9778: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
9779: /* firstpass, lastpass, stepm, weightopt, model); */
9780:
9781: /*Do we need to compute prevalence again?*/
9782:
9783: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
9784:
9785: strcpy(fileresfb,"FB_");
9786: strcat(fileresfb,fileresu);
9787: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
9788: printf("Problem with back forecast resultfile: %s\n", fileresfb);
9789: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
9790: }
9791: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
9792: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
9793:
9794: if (cptcoveff==0) ncodemax[cptcoveff]=1;
9795:
9796:
9797: stepsize=(int) (stepm+YEARM-1)/YEARM;
9798: if (stepm<=12) stepsize=1;
9799: if(estepm < stepm){
9800: printf ("Problem %d lower than %d\n",estepm, stepm);
9801: }
1.270 brouard 9802: else{
9803: hstepm=estepm;
9804: }
9805: if(estepm >= stepm){ /* Yes every two year */
9806: stepsize=2;
9807: }
1.267 brouard 9808:
9809: hstepm=hstepm/stepm;
1.296 brouard 9810: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
9811: /* fractional in yp1 *\/ */
9812: /* aintmean=yp; */
9813: /* yp2=modf((yp1*12),&yp); */
9814: /* mintmean=yp; */
9815: /* yp1=modf((yp2*30.5),&yp); */
9816: /* jintmean=yp; */
9817: /* if(jintmean==0) jintmean=1; */
9818: /* if(mintmean==0) jintmean=1; */
1.267 brouard 9819:
9820: i1=pow(2,cptcoveff);
9821: if (cptcovn < 1){i1=1;}
9822:
1.296 brouard 9823: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
9824: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 9825:
9826: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
9827:
9828: for(nres=1; nres <= nresult; nres++) /* For each resultline */
9829: for(k=1; k<=i1;k++){
9830: if(i1 != 1 && TKresult[nres]!= k)
9831: continue;
9832: if(invalidvarcomb[k]){
9833: printf("\nCombination (%d) projection ignored because no cases \n",k);
9834: continue;
9835: }
1.268 brouard 9836: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.267 brouard 9837: for(j=1;j<=cptcoveff;j++) {
1.332 brouard 9838: fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.267 brouard 9839: }
9840: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
9841: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
9842: }
9843: fprintf(ficresfb," yearbproj age");
9844: for(j=1; j<=nlstate+ndeath;j++){
9845: for(i=1; i<=nlstate;i++)
1.268 brouard 9846: fprintf(ficresfb," b%d%d",i,j);
9847: fprintf(ficresfb," b.%d",j);
1.267 brouard 9848: }
1.296 brouard 9849: for (yearp=0; yearp>=(anbackf-anbackd);yearp -=stepsize) {
1.267 brouard 9850: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
9851: fprintf(ficresfb,"\n");
1.296 brouard 9852: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jbackd,mbackd,anbackd+yearp);
1.273 brouard 9853: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 9854: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
9855: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 9856: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 9857: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 9858: nhstepm = nhstepm/hstepm;
9859: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9860: oldm=oldms;savm=savms;
1.268 brouard 9861: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 9862: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 9863: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 9864: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
9865: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
9866: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 9867: for (h=0; h<=nhstepm; h++){
1.268 brouard 9868: if (h*hstepm/YEARM*stepm ==-yearp) {
9869: break;
9870: }
9871: }
9872: fprintf(ficresfb,"\n");
9873: for(j=1;j<=cptcoveff;j++)
1.332 brouard 9874: fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.296 brouard 9875: fprintf(ficresfb,"%.f %.f ",anbackd+yearp,agec-h*hstepm/YEARM*stepm);
1.268 brouard 9876: for(i=1; i<=nlstate+ndeath;i++) {
9877: ppij=0.;ppi=0.;
9878: for(j=1; j<=nlstate;j++) {
9879: /* if (mobilav==1) */
1.269 brouard 9880: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
9881: ppi=ppi+prevacurrent[(int)agec][j][k];
9882: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
9883: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 9884: /* else { */
9885: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
9886: /* } */
1.268 brouard 9887: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
9888: } /* end j */
9889: if(ppi <0.99){
9890: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
9891: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
9892: }
9893: fprintf(ficresfb," %.3f", ppij);
9894: }/* end j */
1.267 brouard 9895: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9896: } /* end agec */
9897: } /* end yearp */
9898: } /* end k */
1.217 brouard 9899:
1.267 brouard 9900: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 9901:
1.267 brouard 9902: fclose(ficresfb);
9903: printf("End of Computing Back forecasting \n");
9904: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 9905:
1.267 brouard 9906: }
1.217 brouard 9907:
1.269 brouard 9908: /* Variance of prevalence limit: varprlim */
9909: 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 9910: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 9911:
9912: char fileresvpl[FILENAMELENGTH];
9913: FILE *ficresvpl;
9914: double **oldm, **savm;
9915: double **varpl; /* Variances of prevalence limits by age */
9916: int i1, k, nres, j ;
9917:
9918: strcpy(fileresvpl,"VPL_");
9919: strcat(fileresvpl,fileresu);
9920: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 9921: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 9922: exit(0);
9923: }
1.288 brouard 9924: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
9925: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 9926:
9927: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
9928: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
9929:
9930: i1=pow(2,cptcoveff);
9931: if (cptcovn < 1){i1=1;}
9932:
1.337 brouard 9933: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
9934: k=TKresult[nres];
1.338 brouard 9935: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 9936: /* for(k=1; k<=i1;k++){ /\* We find the combination equivalent to result line values of dummies *\/ */
1.269 brouard 9937: if(i1 != 1 && TKresult[nres]!= k)
9938: continue;
9939: fprintf(ficresvpl,"\n#****** ");
9940: printf("\n#****** ");
9941: fprintf(ficlog,"\n#****** ");
1.337 brouard 9942: for(j=1;j<=cptcovs;j++) {
9943: fprintf(ficresvpl,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
9944: fprintf(ficlog,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
9945: printf("V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
9946: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
9947: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.269 brouard 9948: }
1.337 brouard 9949: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
9950: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
9951: /* fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
9952: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
9953: /* } */
1.269 brouard 9954: fprintf(ficresvpl,"******\n");
9955: printf("******\n");
9956: fprintf(ficlog,"******\n");
9957:
9958: varpl=matrix(1,nlstate,(int) bage, (int) fage);
9959: oldm=oldms;savm=savms;
9960: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
9961: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
9962: /*}*/
9963: }
9964:
9965: fclose(ficresvpl);
1.288 brouard 9966: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
9967: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 9968:
9969: }
9970: /* Variance of back prevalence: varbprlim */
9971: 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){
9972: /*------- Variance of back (stable) prevalence------*/
9973:
9974: char fileresvbl[FILENAMELENGTH];
9975: FILE *ficresvbl;
9976:
9977: double **oldm, **savm;
9978: double **varbpl; /* Variances of back prevalence limits by age */
9979: int i1, k, nres, j ;
9980:
9981: strcpy(fileresvbl,"VBL_");
9982: strcat(fileresvbl,fileresu);
9983: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
9984: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
9985: exit(0);
9986: }
9987: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
9988: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
9989:
9990:
9991: i1=pow(2,cptcoveff);
9992: if (cptcovn < 1){i1=1;}
9993:
1.337 brouard 9994: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
9995: k=TKresult[nres];
1.338 brouard 9996: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 9997: /* for(k=1; k<=i1;k++){ */
9998: /* if(i1 != 1 && TKresult[nres]!= k) */
9999: /* continue; */
1.269 brouard 10000: fprintf(ficresvbl,"\n#****** ");
10001: printf("\n#****** ");
10002: fprintf(ficlog,"\n#****** ");
1.337 brouard 10003: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */
1.338 brouard 10004: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
10005: fprintf(ficresvbl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
10006: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
1.337 brouard 10007: /* for(j=1;j<=cptcoveff;j++) { */
10008: /* fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10009: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10010: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10011: /* } */
10012: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
10013: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10014: /* fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10015: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
1.269 brouard 10016: }
10017: fprintf(ficresvbl,"******\n");
10018: printf("******\n");
10019: fprintf(ficlog,"******\n");
10020:
10021: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
10022: oldm=oldms;savm=savms;
10023:
10024: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
10025: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
10026: /*}*/
10027: }
10028:
10029: fclose(ficresvbl);
10030: printf("done variance-covariance of back prevalence\n");fflush(stdout);
10031: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
10032:
10033: } /* End of varbprlim */
10034:
1.126 brouard 10035: /************** Forecasting *****not tested NB*************/
1.227 brouard 10036: /* 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 10037:
1.227 brouard 10038: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
10039: /* int *popage; */
10040: /* double calagedatem, agelim, kk1, kk2; */
10041: /* double *popeffectif,*popcount; */
10042: /* double ***p3mat,***tabpop,***tabpopprev; */
10043: /* /\* double ***mobaverage; *\/ */
10044: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 10045:
1.227 brouard 10046: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10047: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10048: /* agelim=AGESUP; */
10049: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 10050:
1.227 brouard 10051: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 10052:
10053:
1.227 brouard 10054: /* strcpy(filerespop,"POP_"); */
10055: /* strcat(filerespop,fileresu); */
10056: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
10057: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
10058: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
10059: /* } */
10060: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
10061: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 10062:
1.227 brouard 10063: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 10064:
1.227 brouard 10065: /* /\* if (mobilav!=0) { *\/ */
10066: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
10067: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
10068: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
10069: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
10070: /* /\* } *\/ */
10071: /* /\* } *\/ */
1.126 brouard 10072:
1.227 brouard 10073: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
10074: /* if (stepm<=12) stepsize=1; */
1.126 brouard 10075:
1.227 brouard 10076: /* agelim=AGESUP; */
1.126 brouard 10077:
1.227 brouard 10078: /* hstepm=1; */
10079: /* hstepm=hstepm/stepm; */
1.218 brouard 10080:
1.227 brouard 10081: /* if (popforecast==1) { */
10082: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
10083: /* printf("Problem with population file : %s\n",popfile);exit(0); */
10084: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
10085: /* } */
10086: /* popage=ivector(0,AGESUP); */
10087: /* popeffectif=vector(0,AGESUP); */
10088: /* popcount=vector(0,AGESUP); */
1.126 brouard 10089:
1.227 brouard 10090: /* i=1; */
10091: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 10092:
1.227 brouard 10093: /* imx=i; */
10094: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
10095: /* } */
1.218 brouard 10096:
1.227 brouard 10097: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
10098: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
10099: /* k=k+1; */
10100: /* fprintf(ficrespop,"\n#******"); */
10101: /* for(j=1;j<=cptcoveff;j++) { */
10102: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
10103: /* } */
10104: /* fprintf(ficrespop,"******\n"); */
10105: /* fprintf(ficrespop,"# Age"); */
10106: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
10107: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 10108:
1.227 brouard 10109: /* for (cpt=0; cpt<=0;cpt++) { */
10110: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 10111:
1.227 brouard 10112: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
10113: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
10114: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 10115:
1.227 brouard 10116: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10117: /* oldm=oldms;savm=savms; */
10118: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 10119:
1.227 brouard 10120: /* for (h=0; h<=nhstepm; h++){ */
10121: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
10122: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
10123: /* } */
10124: /* for(j=1; j<=nlstate+ndeath;j++) { */
10125: /* kk1=0.;kk2=0; */
10126: /* for(i=1; i<=nlstate;i++) { */
10127: /* if (mobilav==1) */
10128: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
10129: /* else { */
10130: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
10131: /* } */
10132: /* } */
10133: /* if (h==(int)(calagedatem+12*cpt)){ */
10134: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
10135: /* /\*fprintf(ficrespop," %.3f", kk1); */
10136: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
10137: /* } */
10138: /* } */
10139: /* for(i=1; i<=nlstate;i++){ */
10140: /* kk1=0.; */
10141: /* for(j=1; j<=nlstate;j++){ */
10142: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
10143: /* } */
10144: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
10145: /* } */
1.218 brouard 10146:
1.227 brouard 10147: /* if (h==(int)(calagedatem+12*cpt)) */
10148: /* for(j=1; j<=nlstate;j++) */
10149: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
10150: /* } */
10151: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10152: /* } */
10153: /* } */
1.218 brouard 10154:
1.227 brouard 10155: /* /\******\/ */
1.218 brouard 10156:
1.227 brouard 10157: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
10158: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
10159: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
10160: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
10161: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 10162:
1.227 brouard 10163: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10164: /* oldm=oldms;savm=savms; */
10165: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
10166: /* for (h=0; h<=nhstepm; h++){ */
10167: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
10168: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
10169: /* } */
10170: /* for(j=1; j<=nlstate+ndeath;j++) { */
10171: /* kk1=0.;kk2=0; */
10172: /* for(i=1; i<=nlstate;i++) { */
10173: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
10174: /* } */
10175: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
10176: /* } */
10177: /* } */
10178: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10179: /* } */
10180: /* } */
10181: /* } */
10182: /* } */
1.218 brouard 10183:
1.227 brouard 10184: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 10185:
1.227 brouard 10186: /* if (popforecast==1) { */
10187: /* free_ivector(popage,0,AGESUP); */
10188: /* free_vector(popeffectif,0,AGESUP); */
10189: /* free_vector(popcount,0,AGESUP); */
10190: /* } */
10191: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10192: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10193: /* fclose(ficrespop); */
10194: /* } /\* End of popforecast *\/ */
1.218 brouard 10195:
1.126 brouard 10196: int fileappend(FILE *fichier, char *optionfich)
10197: {
10198: if((fichier=fopen(optionfich,"a"))==NULL) {
10199: printf("Problem with file: %s\n", optionfich);
10200: fprintf(ficlog,"Problem with file: %s\n", optionfich);
10201: return (0);
10202: }
10203: fflush(fichier);
10204: return (1);
10205: }
10206:
10207:
10208: /**************** function prwizard **********************/
10209: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
10210: {
10211:
10212: /* Wizard to print covariance matrix template */
10213:
1.164 brouard 10214: char ca[32], cb[32];
10215: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 10216: int numlinepar;
10217:
10218: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
10219: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
10220: for(i=1; i <=nlstate; i++){
10221: jj=0;
10222: for(j=1; j <=nlstate+ndeath; j++){
10223: if(j==i) continue;
10224: jj++;
10225: /*ca[0]= k+'a'-1;ca[1]='\0';*/
10226: printf("%1d%1d",i,j);
10227: fprintf(ficparo,"%1d%1d",i,j);
10228: for(k=1; k<=ncovmodel;k++){
10229: /* printf(" %lf",param[i][j][k]); */
10230: /* fprintf(ficparo," %lf",param[i][j][k]); */
10231: printf(" 0.");
10232: fprintf(ficparo," 0.");
10233: }
10234: printf("\n");
10235: fprintf(ficparo,"\n");
10236: }
10237: }
10238: printf("# Scales (for hessian or gradient estimation)\n");
10239: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
10240: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
10241: for(i=1; i <=nlstate; i++){
10242: jj=0;
10243: for(j=1; j <=nlstate+ndeath; j++){
10244: if(j==i) continue;
10245: jj++;
10246: fprintf(ficparo,"%1d%1d",i,j);
10247: printf("%1d%1d",i,j);
10248: fflush(stdout);
10249: for(k=1; k<=ncovmodel;k++){
10250: /* printf(" %le",delti3[i][j][k]); */
10251: /* fprintf(ficparo," %le",delti3[i][j][k]); */
10252: printf(" 0.");
10253: fprintf(ficparo," 0.");
10254: }
10255: numlinepar++;
10256: printf("\n");
10257: fprintf(ficparo,"\n");
10258: }
10259: }
10260: printf("# Covariance matrix\n");
10261: /* # 121 Var(a12)\n\ */
10262: /* # 122 Cov(b12,a12) Var(b12)\n\ */
10263: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
10264: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
10265: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
10266: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
10267: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
10268: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
10269: fflush(stdout);
10270: fprintf(ficparo,"# Covariance matrix\n");
10271: /* # 121 Var(a12)\n\ */
10272: /* # 122 Cov(b12,a12) Var(b12)\n\ */
10273: /* # ...\n\ */
10274: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
10275:
10276: for(itimes=1;itimes<=2;itimes++){
10277: jj=0;
10278: for(i=1; i <=nlstate; i++){
10279: for(j=1; j <=nlstate+ndeath; j++){
10280: if(j==i) continue;
10281: for(k=1; k<=ncovmodel;k++){
10282: jj++;
10283: ca[0]= k+'a'-1;ca[1]='\0';
10284: if(itimes==1){
10285: printf("#%1d%1d%d",i,j,k);
10286: fprintf(ficparo,"#%1d%1d%d",i,j,k);
10287: }else{
10288: printf("%1d%1d%d",i,j,k);
10289: fprintf(ficparo,"%1d%1d%d",i,j,k);
10290: /* printf(" %.5le",matcov[i][j]); */
10291: }
10292: ll=0;
10293: for(li=1;li <=nlstate; li++){
10294: for(lj=1;lj <=nlstate+ndeath; lj++){
10295: if(lj==li) continue;
10296: for(lk=1;lk<=ncovmodel;lk++){
10297: ll++;
10298: if(ll<=jj){
10299: cb[0]= lk +'a'-1;cb[1]='\0';
10300: if(ll<jj){
10301: if(itimes==1){
10302: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10303: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10304: }else{
10305: printf(" 0.");
10306: fprintf(ficparo," 0.");
10307: }
10308: }else{
10309: if(itimes==1){
10310: printf(" Var(%s%1d%1d)",ca,i,j);
10311: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
10312: }else{
10313: printf(" 0.");
10314: fprintf(ficparo," 0.");
10315: }
10316: }
10317: }
10318: } /* end lk */
10319: } /* end lj */
10320: } /* end li */
10321: printf("\n");
10322: fprintf(ficparo,"\n");
10323: numlinepar++;
10324: } /* end k*/
10325: } /*end j */
10326: } /* end i */
10327: } /* end itimes */
10328:
10329: } /* end of prwizard */
10330: /******************* Gompertz Likelihood ******************************/
10331: double gompertz(double x[])
10332: {
1.302 brouard 10333: double A=0.0,B=0.,L=0.0,sump=0.,num=0.;
1.126 brouard 10334: int i,n=0; /* n is the size of the sample */
10335:
1.220 brouard 10336: for (i=1;i<=imx ; i++) {
1.126 brouard 10337: sump=sump+weight[i];
10338: /* sump=sump+1;*/
10339: num=num+1;
10340: }
1.302 brouard 10341: L=0.0;
10342: /* agegomp=AGEGOMP; */
1.126 brouard 10343: /* for (i=0; i<=imx; i++)
10344: 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]);*/
10345:
1.302 brouard 10346: for (i=1;i<=imx ; i++) {
10347: /* mu(a)=mu(agecomp)*exp(teta*(age-agegomp))
10348: mu(a)=x[1]*exp(x[2]*(age-agegomp)); x[1] and x[2] are per year.
10349: * L= Product mu(agedeces)exp(-\int_ageexam^agedc mu(u) du ) for a death between agedc (in month)
10350: * and agedc +1 month, cens[i]=0: log(x[1]/YEARM)
10351: * +
10352: * exp(-\int_ageexam^agecens mu(u) du ) when censored, cens[i]=1
10353: */
10354: if (wav[i] > 1 || agedc[i] < AGESUP) {
10355: if (cens[i] == 1){
10356: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
10357: } else if (cens[i] == 0){
1.126 brouard 10358: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
1.302 brouard 10359: +log(x[1]/YEARM) +x[2]*(agedc[i]-agegomp)+log(YEARM);
10360: } else
10361: printf("Gompertz cens[%d] neither 1 nor 0\n",i);
1.126 brouard 10362: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
1.302 brouard 10363: L=L+A*weight[i];
1.126 brouard 10364: /* 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 10365: }
10366: }
1.126 brouard 10367:
1.302 brouard 10368: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
1.126 brouard 10369:
10370: return -2*L*num/sump;
10371: }
10372:
1.136 brouard 10373: #ifdef GSL
10374: /******************* Gompertz_f Likelihood ******************************/
10375: double gompertz_f(const gsl_vector *v, void *params)
10376: {
1.302 brouard 10377: double A=0.,B=0.,LL=0.0,sump=0.,num=0.;
1.136 brouard 10378: double *x= (double *) v->data;
10379: int i,n=0; /* n is the size of the sample */
10380:
10381: for (i=0;i<=imx-1 ; i++) {
10382: sump=sump+weight[i];
10383: /* sump=sump+1;*/
10384: num=num+1;
10385: }
10386:
10387:
10388: /* for (i=0; i<=imx; i++)
10389: 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]);*/
10390: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
10391: for (i=1;i<=imx ; i++)
10392: {
10393: if (cens[i] == 1 && wav[i]>1)
10394: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
10395:
10396: if (cens[i] == 0 && wav[i]>1)
10397: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
10398: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
10399:
10400: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
10401: if (wav[i] > 1 ) { /* ??? */
10402: LL=LL+A*weight[i];
10403: /* 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]);*/
10404: }
10405: }
10406:
10407: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
10408: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
10409:
10410: return -2*LL*num/sump;
10411: }
10412: #endif
10413:
1.126 brouard 10414: /******************* Printing html file ***********/
1.201 brouard 10415: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 10416: int lastpass, int stepm, int weightopt, char model[],\
10417: int imx, double p[],double **matcov,double agemortsup){
10418: int i,k;
10419:
10420: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
10421: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
10422: for (i=1;i<=2;i++)
10423: 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 10424: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 10425: fprintf(fichtm,"</ul>");
10426:
10427: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
10428:
10429: 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>");
10430:
10431: for (k=agegomp;k<(agemortsup-2);k++)
10432: 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]);
10433:
10434:
10435: fflush(fichtm);
10436: }
10437:
10438: /******************* Gnuplot file **************/
1.201 brouard 10439: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 10440:
10441: char dirfileres[132],optfileres[132];
1.164 brouard 10442:
1.126 brouard 10443: int ng;
10444:
10445:
10446: /*#ifdef windows */
10447: fprintf(ficgp,"cd \"%s\" \n",pathc);
10448: /*#endif */
10449:
10450:
10451: strcpy(dirfileres,optionfilefiname);
10452: strcpy(optfileres,"vpl");
1.199 brouard 10453: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 10454: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 10455: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 10456: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 10457: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
10458:
10459: }
10460:
1.136 brouard 10461: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
10462: {
1.126 brouard 10463:
1.136 brouard 10464: /*-------- data file ----------*/
10465: FILE *fic;
10466: char dummy[]=" ";
1.240 brouard 10467: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 10468: int lstra;
1.136 brouard 10469: int linei, month, year,iout;
1.302 brouard 10470: int noffset=0; /* This is the offset if BOM data file */
1.136 brouard 10471: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 10472: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 10473: char *stratrunc;
1.223 brouard 10474:
1.240 brouard 10475: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
10476: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.328 brouard 10477: for(v=1;v<NCOVMAX;v++){
10478: DummyV[v]=0;
10479: FixedV[v]=0;
10480: }
1.126 brouard 10481:
1.240 brouard 10482: for(v=1; v <=ncovcol;v++){
10483: DummyV[v]=0;
10484: FixedV[v]=0;
10485: }
10486: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
10487: DummyV[v]=1;
10488: FixedV[v]=0;
10489: }
10490: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
10491: DummyV[v]=0;
10492: FixedV[v]=1;
10493: }
10494: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
10495: DummyV[v]=1;
10496: FixedV[v]=1;
10497: }
10498: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
10499: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
10500: fprintf(ficlog,"Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
10501: }
1.339 brouard 10502:
10503: ncovcolt=ncovcol+nqv+ntv+nqtv; /* total of covariates in the data, not in the model equation */
10504:
1.136 brouard 10505: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 10506: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
10507: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 10508: }
1.126 brouard 10509:
1.302 brouard 10510: /* Is it a BOM UTF-8 Windows file? */
10511: /* First data line */
10512: linei=0;
10513: while(fgets(line, MAXLINE, fic)) {
10514: noffset=0;
10515: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
10516: {
10517: noffset=noffset+3;
10518: printf("# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);fflush(stdout);
10519: fprintf(ficlog,"# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);
10520: fflush(ficlog); return 1;
10521: }
10522: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
10523: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
10524: {
10525: noffset=noffset+2;
1.304 brouard 10526: 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);
10527: 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 10528: fflush(ficlog); return 1;
10529: }
10530: else if( line[0] == 0 && line[1] == 0)
10531: {
10532: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
10533: noffset=noffset+4;
1.304 brouard 10534: 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);
10535: 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 10536: fflush(ficlog); return 1;
10537: }
10538: } else{
10539: ;/*printf(" Not a BOM file\n");*/
10540: }
10541: /* If line starts with a # it is a comment */
10542: if (line[noffset] == '#') {
10543: linei=linei+1;
10544: break;
10545: }else{
10546: break;
10547: }
10548: }
10549: fclose(fic);
10550: if((fic=fopen(datafile,"r"))==NULL) {
10551: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
10552: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
10553: }
10554: /* Not a Bom file */
10555:
1.136 brouard 10556: i=1;
10557: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
10558: linei=linei+1;
10559: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
10560: if(line[j] == '\t')
10561: line[j] = ' ';
10562: }
10563: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
10564: ;
10565: };
10566: line[j+1]=0; /* Trims blanks at end of line */
10567: if(line[0]=='#'){
10568: fprintf(ficlog,"Comment line\n%s\n",line);
10569: printf("Comment line\n%s\n",line);
10570: continue;
10571: }
10572: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 10573: strcpy(line, linetmp);
1.223 brouard 10574:
10575: /* Loops on waves */
10576: for (j=maxwav;j>=1;j--){
10577: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 10578: cutv(stra, strb, line, ' ');
10579: if(strb[0]=='.') { /* Missing value */
10580: lval=-1;
10581: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
1.341 brouard 10582: cotvar[j][ncovcol+nqv+ntv+iv][i]=-1; /* For performance reasons */
1.238 brouard 10583: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
10584: 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);
10585: 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);
10586: return 1;
10587: }
10588: }else{
10589: errno=0;
10590: /* what_kind_of_number(strb); */
10591: dval=strtod(strb,&endptr);
10592: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
10593: /* if(strb != endptr && *endptr == '\0') */
10594: /* dval=dlval; */
10595: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
10596: if( strb[0]=='\0' || (*endptr != '\0')){
10597: 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);
10598: 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);
10599: return 1;
10600: }
10601: cotqvar[j][iv][i]=dval;
1.341 brouard 10602: cotvar[j][ncovcol+nqv+ntv+iv][i]=dval; /* because cotvar starts now at first ntv */
1.238 brouard 10603: }
10604: strcpy(line,stra);
1.223 brouard 10605: }/* end loop ntqv */
1.225 brouard 10606:
1.223 brouard 10607: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 10608: cutv(stra, strb, line, ' ');
10609: if(strb[0]=='.') { /* Missing value */
10610: lval=-1;
10611: }else{
10612: errno=0;
10613: lval=strtol(strb,&endptr,10);
10614: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
10615: if( strb[0]=='\0' || (*endptr != '\0')){
10616: 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);
10617: 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);
10618: return 1;
10619: }
10620: }
10621: if(lval <-1 || lval >1){
10622: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10623: Should be a value of %d(nth) covariate of wave %d (0 should be the value for the reference and 1\n \
1.223 brouard 10624: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10625: For example, for multinomial values like 1, 2 and 3,\n \
10626: build V1=0 V2=0 for the reference value (1),\n \
10627: V1=1 V2=0 for (2) \n \
1.223 brouard 10628: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10629: output of IMaCh is often meaningless.\n \
1.319 brouard 10630: Exiting.\n",lval,linei, i,line,iv,j);
1.238 brouard 10631: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10632: 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 10633: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10634: For example, for multinomial values like 1, 2 and 3,\n \
10635: build V1=0 V2=0 for the reference value (1),\n \
10636: V1=1 V2=0 for (2) \n \
1.223 brouard 10637: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10638: output of IMaCh is often meaningless.\n \
1.319 brouard 10639: Exiting.\n",lval,linei, i,line,iv,j);fflush(ficlog);
1.238 brouard 10640: return 1;
10641: }
1.341 brouard 10642: cotvar[j][ncovcol+nqv+iv][i]=(double)(lval);
1.238 brouard 10643: strcpy(line,stra);
1.223 brouard 10644: }/* end loop ntv */
1.225 brouard 10645:
1.223 brouard 10646: /* Statuses at wave */
1.137 brouard 10647: cutv(stra, strb, line, ' ');
1.223 brouard 10648: if(strb[0]=='.') { /* Missing value */
1.238 brouard 10649: lval=-1;
1.136 brouard 10650: }else{
1.238 brouard 10651: errno=0;
10652: lval=strtol(strb,&endptr,10);
10653: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
1.347 ! brouard 10654: if( strb[0]=='\0' || (*endptr != '\0' )){
! 10655: 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);
! 10656: 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);
! 10657: return 1;
! 10658: }else if( lval==0 || lval > nlstate+ndeath){
! 10659: 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 %d.\n Fix your data file '%s'! Exiting.\n", strb, linei,i,line,j,nlstate+ndeath, lval, datafile);fflush(stdout);
! 10660: 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 %d.\n Fix your data file '%s'! Exiting.\n", strb, linei,i,line,j,nlstate+ndeath, lval, datafile); fflush(ficlog);
1.238 brouard 10661: return 1;
10662: }
1.136 brouard 10663: }
1.225 brouard 10664:
1.136 brouard 10665: s[j][i]=lval;
1.225 brouard 10666:
1.223 brouard 10667: /* Date of Interview */
1.136 brouard 10668: strcpy(line,stra);
10669: cutv(stra, strb,line,' ');
1.169 brouard 10670: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10671: }
1.169 brouard 10672: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 10673: month=99;
10674: year=9999;
1.136 brouard 10675: }else{
1.225 brouard 10676: 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);
10677: 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);
10678: return 1;
1.136 brouard 10679: }
10680: anint[j][i]= (double) year;
1.302 brouard 10681: mint[j][i]= (double)month;
10682: /* if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){ */
10683: /* 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]); */
10684: /* 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]); */
10685: /* } */
1.136 brouard 10686: strcpy(line,stra);
1.223 brouard 10687: } /* End loop on waves */
1.225 brouard 10688:
1.223 brouard 10689: /* Date of death */
1.136 brouard 10690: cutv(stra, strb,line,' ');
1.169 brouard 10691: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10692: }
1.169 brouard 10693: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 10694: month=99;
10695: year=9999;
10696: }else{
1.141 brouard 10697: 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 10698: 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);
10699: return 1;
1.136 brouard 10700: }
10701: andc[i]=(double) year;
10702: moisdc[i]=(double) month;
10703: strcpy(line,stra);
10704:
1.223 brouard 10705: /* Date of birth */
1.136 brouard 10706: cutv(stra, strb,line,' ');
1.169 brouard 10707: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10708: }
1.169 brouard 10709: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 10710: month=99;
10711: year=9999;
10712: }else{
1.141 brouard 10713: 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);
10714: 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 10715: return 1;
1.136 brouard 10716: }
10717: if (year==9999) {
1.141 brouard 10718: 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);
10719: 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 10720: return 1;
10721:
1.136 brouard 10722: }
10723: annais[i]=(double)(year);
1.302 brouard 10724: moisnais[i]=(double)(month);
10725: for (j=1;j<=maxwav;j++){
10726: if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){
10727: 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]);
10728: 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]);
10729: }
10730: }
10731:
1.136 brouard 10732: strcpy(line,stra);
1.225 brouard 10733:
1.223 brouard 10734: /* Sample weight */
1.136 brouard 10735: cutv(stra, strb,line,' ');
10736: errno=0;
10737: dval=strtod(strb,&endptr);
10738: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 10739: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
10740: 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 10741: fflush(ficlog);
10742: return 1;
10743: }
10744: weight[i]=dval;
10745: strcpy(line,stra);
1.225 brouard 10746:
1.223 brouard 10747: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
10748: cutv(stra, strb, line, ' ');
10749: if(strb[0]=='.') { /* Missing value */
1.225 brouard 10750: lval=-1;
1.311 brouard 10751: coqvar[iv][i]=NAN;
10752: covar[ncovcol+iv][i]=NAN; /* including qvar in standard covar for performance reasons */
1.223 brouard 10753: }else{
1.225 brouard 10754: errno=0;
10755: /* what_kind_of_number(strb); */
10756: dval=strtod(strb,&endptr);
10757: /* if(strb != endptr && *endptr == '\0') */
10758: /* dval=dlval; */
10759: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
10760: if( strb[0]=='\0' || (*endptr != '\0')){
10761: 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);
10762: 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);
10763: return 1;
10764: }
10765: coqvar[iv][i]=dval;
1.226 brouard 10766: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 10767: }
10768: strcpy(line,stra);
10769: }/* end loop nqv */
1.136 brouard 10770:
1.223 brouard 10771: /* Covariate values */
1.136 brouard 10772: for (j=ncovcol;j>=1;j--){
10773: cutv(stra, strb,line,' ');
1.223 brouard 10774: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 10775: lval=-1;
1.136 brouard 10776: }else{
1.225 brouard 10777: errno=0;
10778: lval=strtol(strb,&endptr,10);
10779: if( strb[0]=='\0' || (*endptr != '\0')){
10780: 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);
10781: 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);
10782: return 1;
10783: }
1.136 brouard 10784: }
10785: if(lval <-1 || lval >1){
1.225 brouard 10786: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 10787: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
10788: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 10789: For example, for multinomial values like 1, 2 and 3,\n \
10790: build V1=0 V2=0 for the reference value (1),\n \
10791: V1=1 V2=0 for (2) \n \
1.136 brouard 10792: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 10793: output of IMaCh is often meaningless.\n \
1.136 brouard 10794: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 10795: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 10796: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
10797: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 10798: For example, for multinomial values like 1, 2 and 3,\n \
10799: build V1=0 V2=0 for the reference value (1),\n \
10800: V1=1 V2=0 for (2) \n \
1.136 brouard 10801: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 10802: output of IMaCh is often meaningless.\n \
1.136 brouard 10803: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 10804: return 1;
1.136 brouard 10805: }
10806: covar[j][i]=(double)(lval);
10807: strcpy(line,stra);
10808: }
10809: lstra=strlen(stra);
1.225 brouard 10810:
1.136 brouard 10811: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
10812: stratrunc = &(stra[lstra-9]);
10813: num[i]=atol(stratrunc);
10814: }
10815: else
10816: num[i]=atol(stra);
10817: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
10818: 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;}*/
10819:
10820: i=i+1;
10821: } /* End loop reading data */
1.225 brouard 10822:
1.136 brouard 10823: *imax=i-1; /* Number of individuals */
10824: fclose(fic);
1.225 brouard 10825:
1.136 brouard 10826: return (0);
1.164 brouard 10827: /* endread: */
1.225 brouard 10828: printf("Exiting readdata: ");
10829: fclose(fic);
10830: return (1);
1.223 brouard 10831: }
1.126 brouard 10832:
1.234 brouard 10833: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 10834: char *p1 = *stri, *p2 = *stri;
1.235 brouard 10835: while (*p2 == ' ')
1.234 brouard 10836: p2++;
10837: /* while ((*p1++ = *p2++) !=0) */
10838: /* ; */
10839: /* do */
10840: /* while (*p2 == ' ') */
10841: /* p2++; */
10842: /* while (*p1++ == *p2++); */
10843: *stri=p2;
1.145 brouard 10844: }
10845:
1.330 brouard 10846: int decoderesult( char resultline[], int nres)
1.230 brouard 10847: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
10848: {
1.235 brouard 10849: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 10850: char resultsav[MAXLINE];
1.330 brouard 10851: /* int resultmodel[MAXLINE]; */
1.334 brouard 10852: /* int modelresult[MAXLINE]; */
1.230 brouard 10853: char stra[80], strb[80], strc[80], strd[80],stre[80];
10854:
1.234 brouard 10855: removefirstspace(&resultline);
1.332 brouard 10856: printf("decoderesult:%s\n",resultline);
1.230 brouard 10857:
1.332 brouard 10858: strcpy(resultsav,resultline);
1.342 brouard 10859: /* printf("Decoderesult resultsav=\"%s\" resultline=\"%s\"\n", resultsav, resultline); */
1.230 brouard 10860: if (strlen(resultsav) >1){
1.334 brouard 10861: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' in this resultline */
1.230 brouard 10862: }
1.253 brouard 10863: if(j == 0){ /* Resultline but no = */
10864: TKresult[nres]=0; /* Combination for the nresult and the model */
10865: return (0);
10866: }
1.234 brouard 10867: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
1.334 brouard 10868: 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);
10869: 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 10870: /* return 1;*/
1.234 brouard 10871: }
1.334 brouard 10872: for(k=1; k<=j;k++){ /* Loop on any covariate of the RESULT LINE */
1.234 brouard 10873: if(nbocc(resultsav,'=') >1){
1.318 brouard 10874: 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 10875: /* 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 10876: cutl(strc,strd,strb,'='); /* strb:"V4=1" strc="1" strd="V4" */
1.332 brouard 10877: /* If a blank, then strc="V4=" and strd='\0' */
10878: if(strc[0]=='\0'){
10879: printf("Error in resultline, probably a blank after the \"%s\", \"result:%s\", stra=\"%s\" resultsav=\"%s\"\n",strb,resultline, stra, resultsav);
10880: fprintf(ficlog,"Error in resultline, probably a blank after the \"V%s=\", resultline=%s\n",strb,resultline);
10881: return 1;
10882: }
1.234 brouard 10883: }else
10884: cutl(strc,strd,resultsav,'=');
1.318 brouard 10885: Tvalsel[k]=atof(strc); /* 1 */ /* Tvalsel of k is the float value of the kth covariate appearing in this result line */
1.234 brouard 10886:
1.230 brouard 10887: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
1.318 brouard 10888: 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 10889: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
10890: /* cptcovsel++; */
10891: if (nbocc(stra,'=') >0)
10892: strcpy(resultsav,stra); /* and analyzes it */
10893: }
1.235 brouard 10894: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 10895: /* 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 10896: 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 10897: if(Typevar[k1]==0){ /* Single covariate in model */
10898: /* 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.234 brouard 10899: match=0;
1.318 brouard 10900: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
10901: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 10902: modelresult[nres][k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.318 brouard 10903: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
1.234 brouard 10904: break;
10905: }
10906: }
10907: if(match == 0){
1.338 brouard 10908: 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]);
10909: 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 10910: return 1;
1.234 brouard 10911: }
1.332 brouard 10912: }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*/
10913: /* We feed resultmodel[k1]=k2; */
10914: match=0;
10915: 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 */
10916: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 10917: 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 10918: resultmodel[nres][k1]=k2; /* Added here */
1.342 brouard 10919: /* printf("Decoderesult first modelresult[k2=%d]=%d (k1) V%d*AGE\n",k2,k1,Tvar[k1]); */
1.332 brouard 10920: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
10921: break;
10922: }
10923: }
10924: if(match == 0){
1.338 brouard 10925: 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]);
10926: 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 10927: return 1;
10928: }
10929: }else if(Typevar[k1]==2){ /* Product No age We want to get the position in the resultline of the product in the model line*/
10930: /* resultmodel[nres][of such a Vn * Vm product k1] is not unique, so can't exist, we feed Tvard[k1][1] and [2] */
10931: match=0;
1.342 brouard 10932: /* 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 10933: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
10934: if(Tvardk[k1][1]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
10935: /* modelresult[k2]=k1; */
1.342 brouard 10936: /* printf("Decoderesult first Product modelresult[k2=%d]=%d (k1) V%d * \n",k2,k1,Tvarsel[k2]); */
1.332 brouard 10937: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
10938: }
10939: }
10940: if(match == 0){
1.338 brouard 10941: printf("Error in result line (Product without age first variable): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][1], resultline, model);
10942: fprintf(ficlog,"Error in result line (Product without age first variable): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][1], resultline, model);
1.332 brouard 10943: return 1;
10944: }
10945: match=0;
10946: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
10947: if(Tvardk[k1][2]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
10948: /* modelresult[k2]=k1;*/
1.342 brouard 10949: /* printf("Decoderesult second Product modelresult[k2=%d]=%d (k1) * V%d \n ",k2,k1,Tvarsel[k2]); */
1.332 brouard 10950: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
10951: break;
10952: }
10953: }
10954: if(match == 0){
1.338 brouard 10955: printf("Error in result line (Product without age second variable): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][2], resultline, model);
10956: fprintf(ficlog,"Error in result line (Product without age second variable): V%d is missing in result : %s according to model=1+age+%s\n",Tvardk[k1][2], resultline, model);
1.332 brouard 10957: return 1;
10958: }
10959: }/* End of testing */
1.333 brouard 10960: }/* End loop cptcovt */
1.235 brouard 10961: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 10962: /* Feeds resultmodel[nres][k1]=k2 for single covariate (k1) in the model equation */
1.334 brouard 10963: 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)
10964: * Loop on resultline variables: result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 10965: match=0;
1.318 brouard 10966: 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 10967: if(Typevar[k1]==0){ /* Single only */
1.237 brouard 10968: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.330 brouard 10969: 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 10970: 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 10971: ++match;
10972: }
10973: }
10974: }
10975: if(match == 0){
1.338 brouard 10976: printf("Error in result line: variable V%d is missing in model; result: %s, model=1+age+%s\n",Tvarsel[k2], resultline, model);
10977: 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 10978: return 1;
1.234 brouard 10979: }else if(match > 1){
1.338 brouard 10980: printf("Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
10981: fprintf(ficlog,"Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
1.310 brouard 10982: return 1;
1.234 brouard 10983: }
10984: }
1.334 brouard 10985: /* cptcovres=j /\* Number of variables in the resultline is equal to cptcovs and thus useless *\/ */
1.234 brouard 10986: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 10987: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.330 brouard 10988: /* nres=1st result line: V4=1 V5=25.1 V3=0 V2=8 V1=1 */
10989: /* 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*/
10990: /* nres=2nd result line: V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.235 brouard 10991: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
10992: /* 1 0 0 0 */
10993: /* 2 1 0 0 */
10994: /* 3 0 1 0 */
1.330 brouard 10995: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 (nres=2)*/
1.235 brouard 10996: /* 5 0 0 1 */
1.330 brouard 10997: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 (nres=1)*/
1.235 brouard 10998: /* 7 0 1 1 */
10999: /* 8 1 1 1 */
1.237 brouard 11000: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
11001: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
11002: /* V5*age V5 known which value for nres? */
11003: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.334 brouard 11004: 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.
11005: * loop on position k1 in the MODEL LINE */
1.331 brouard 11006: /* k counting number of combination of single dummies in the equation model */
11007: /* k4 counting single dummies in the equation model */
11008: /* k4q counting single quantitatives in the equation model */
1.344 brouard 11009: 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 11010: /* 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 11011: /* 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 11012: /* Value in the (current nres) resultline of the variable at the k1th position in the model equation resultmodel[nres][k1]= k3 */
1.332 brouard 11013: /* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline */
11014: /* k3 is the position in the nres result line of the k1th variable of the model equation */
11015: /* Tvarsel[k3]: Name of the variable at the k3th position in the result line. */
11016: /* Tvalsel[k3]: Value of the variable at the k3th position in the result line. */
11017: /* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.334 brouard 11018: /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 11019: /* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1.330 brouard 11020: /* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.332 brouard 11021: k3= resultmodel[nres][k1]; /* From position k1 in model get position k3 in result line */
11022: /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
11023: 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 11024: 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 11025: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][Name]=Value; stores the value into the name of the variable. */
1.332 brouard 11026: /* Tinvresult[nres][4]=1 */
1.334 brouard 11027: /* Tresult[nres][k4+1]=Tvalsel[k3];/\* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) *\/ */
11028: Tresult[nres][k3]=Tvalsel[k3];/* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) */
11029: /* Tvresult[nres][k4+1]=(int)Tvarsel[k3];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
11030: Tvresult[nres][k3]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
1.237 brouard 11031: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.334 brouard 11032: precov[nres][k1]=Tvalsel[k3]; /* Value from resultline of the variable at the k1 position in the model */
1.342 brouard 11033: /* 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 11034: k4++;;
1.331 brouard 11035: }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Quantitative and single */
1.330 brouard 11036: /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.332 brouard 11037: /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.330 brouard 11038: /* Tqinvresult[nres][Name of a quantitative variable]= value of the variable in the result line */
1.332 brouard 11039: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 5 =k3q */
11040: k2q=(int)Tvarsel[k3q]; /* Name of variable at k3q th position in the resultline */
11041: /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.334 brouard 11042: /* Tqresult[nres][k4q+1]=Tvalsel[k3q]; /\* Tqresult[nres][1]=25.1 *\/ */
11043: /* Tvresult[nres][k4q+1]=(int)Tvarsel[k3q];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
11044: /* Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /\* Tvqresult[nres][1]=5 *\/ */
11045: Tqresult[nres][k3q]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
11046: Tvresult[nres][k3q]=(int)Tvarsel[k3q];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
11047: Tvqresult[nres][k3q]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
1.237 brouard 11048: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.330 brouard 11049: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.332 brouard 11050: precov[nres][k1]=Tvalsel[k3q];
1.342 brouard 11051: /* 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 11052: k4q++;;
1.331 brouard 11053: }else if( Dummy[k1]==2 ){ /* For dummy with age product */
11054: /* Tvar[k1]; */ /* Age variable */
1.332 brouard 11055: /* Wrong we want the value of variable name Tvar[k1] */
11056:
11057: k3= resultmodel[nres][k1]; /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
1.331 brouard 11058: 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 11059: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][4]=1 */
1.332 brouard 11060: precov[nres][k1]=Tvalsel[k3];
1.342 brouard 11061: /* 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 11062: }else if( Dummy[k1]==3 ){ /* For quant with age product */
1.332 brouard 11063: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 25.1=k3q */
1.331 brouard 11064: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.334 brouard 11065: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* TinvDoQresult[nres][5]=25.1 */
1.332 brouard 11066: precov[nres][k1]=Tvalsel[k3q];
1.342 brouard 11067: /* printf("Decoderesult Quantitative with age nres=%d, k1=%d, precov[nres=%d][k1=%d]=%f Tvar[%d]=V%d V(k2q=%d)= Tvarsel[%d]=%d, Tvalsel[%d]=%f\n",nres, k1, nres, k1,precov[nres][k1], k1, Tvar[k1], k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]); */
1.331 brouard 11068: }else if(Typevar[k1]==2 ){ /* For product quant or dummy (not with age) */
1.332 brouard 11069: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
1.342 brouard 11070: /* 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 11071: }else{
1.332 brouard 11072: printf("Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
11073: fprintf(ficlog,"Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
1.235 brouard 11074: }
11075: }
1.234 brouard 11076:
1.334 brouard 11077: TKresult[nres]=++k; /* Number of combinations of dummies for the nresult and the model =Tvalsel[k3]*pow(2,k4) + 1*/
1.230 brouard 11078: return (0);
11079: }
1.235 brouard 11080:
1.230 brouard 11081: int decodemodel( char model[], int lastobs)
11082: /**< This routine decodes the model and returns:
1.224 brouard 11083: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
11084: * - nagesqr = 1 if age*age in the model, otherwise 0.
11085: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
11086: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
11087: * - cptcovage number of covariates with age*products =2
11088: * - cptcovs number of simple covariates
1.339 brouard 11089: * ncovcolt=ncovcol+nqv+ntv+nqtv total of covariates in the data, not in the model equation
1.224 brouard 11090: * - 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 11091: * which is a new column after the 9 (ncovcol+nqv+ntv+nqtv) variables.
1.319 brouard 11092: * - if k is a product Vn*Vm, covar[k][i] is filled with correct values for each individual
1.224 brouard 11093: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
11094: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
11095: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
11096: */
1.319 brouard 11097: /* 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 11098: {
1.238 brouard 11099: int i, j, k, ks, v;
1.227 brouard 11100: int j1, k1, k2, k3, k4;
1.136 brouard 11101: char modelsav[80];
1.145 brouard 11102: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 11103: char *strpt;
1.136 brouard 11104:
1.145 brouard 11105: /*removespace(model);*/
1.136 brouard 11106: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 11107: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 11108: if (strstr(model,"AGE") !=0){
1.192 brouard 11109: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
11110: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 11111: return 1;
11112: }
1.141 brouard 11113: if (strstr(model,"v") !=0){
1.338 brouard 11114: printf("Error. 'v' must be in upper case 'V' model=1+age+%s ",model);
11115: fprintf(ficlog,"Error. 'v' must be in upper case model=1+age+%s ",model);fflush(ficlog);
1.141 brouard 11116: return 1;
11117: }
1.187 brouard 11118: strcpy(modelsav,model);
11119: if ((strpt=strstr(model,"age*age")) !=0){
1.338 brouard 11120: printf(" strpt=%s, model=1+age+%s\n",strpt, model);
1.187 brouard 11121: if(strpt != model){
1.338 brouard 11122: printf("Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 11123: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 11124: corresponding column of parameters.\n",model);
1.338 brouard 11125: fprintf(ficlog,"Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 11126: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 11127: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 11128: return 1;
1.225 brouard 11129: }
1.187 brouard 11130: nagesqr=1;
11131: if (strstr(model,"+age*age") !=0)
1.234 brouard 11132: substrchaine(modelsav, model, "+age*age");
1.187 brouard 11133: else if (strstr(model,"age*age+") !=0)
1.234 brouard 11134: substrchaine(modelsav, model, "age*age+");
1.187 brouard 11135: else
1.234 brouard 11136: substrchaine(modelsav, model, "age*age");
1.187 brouard 11137: }else
11138: nagesqr=0;
11139: if (strlen(modelsav) >1){
11140: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
11141: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 11142: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 11143: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 11144: * cst, age and age*age
11145: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
11146: /* including age products which are counted in cptcovage.
11147: * but the covariates which are products must be treated
11148: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 11149: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
11150: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 11151:
11152:
1.187 brouard 11153: /* Design
11154: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
11155: * < ncovcol=8 >
11156: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
11157: * k= 1 2 3 4 5 6 7 8
11158: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
1.345 brouard 11159: * covar[k,i], are for fixed covariates, value of kth covariate if not including age for individual i:
1.224 brouard 11160: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
11161: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 11162: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
11163: * Tage[++cptcovage]=k
1.345 brouard 11164: * if products, new covar are created after ncovcol + nqv (quanti fixed) with k1
1.187 brouard 11165: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
11166: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
11167: * 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
11168: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
11169: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
11170: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
1.345 brouard 11171: * < ncovcol=8 8 fixed covariate. Additional starts at 9 (V5*V6) and 10(V7*V8) >
1.187 brouard 11172: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
11173: * k= 1 2 3 4 5 6 7 8 9 10 11 12
1.345 brouard 11174: * Tvard[k]= 2 1 3 3 10 11 8 8 5 6 7 8
11175: * p Tvar[1]@12={2, 1, 3, 3, 9, 10, 8, 8}
1.187 brouard 11176: * p Tprod[1]@2={ 6, 5}
11177: *p Tvard[1][1]@4= {7, 8, 5, 6}
11178: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
11179: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
1.319 brouard 11180: *How to reorganize? Tvars(orted)
1.187 brouard 11181: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
11182: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
11183: * {2, 1, 4, 8, 5, 6, 3, 7}
11184: * Struct []
11185: */
1.225 brouard 11186:
1.187 brouard 11187: /* This loop fills the array Tvar from the string 'model'.*/
11188: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
11189: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
11190: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
11191: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
11192: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
11193: /* k=1 Tvar[1]=2 (from V2) */
11194: /* k=5 Tvar[5] */
11195: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 11196: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 11197: /* } */
1.198 brouard 11198: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 11199: /*
11200: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 11201: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
11202: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
11203: }
1.187 brouard 11204: cptcovage=0;
1.319 brouard 11205: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model line */
11206: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+' cutl from left to right
11207: 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" */
11208: if (nbocc(modelsav,'+')==0)
11209: strcpy(strb,modelsav); /* and analyzes it */
1.234 brouard 11210: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
11211: /*scanf("%d",i);*/
1.319 brouard 11212: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V5*age+ V4+V3*age strb=V3*age */
11213: cutl(strc,strd,strb,'*'); /**< k=1 strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 */
1.234 brouard 11214: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
11215: /* covar is not filled and then is empty */
11216: cptcovprod--;
11217: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
1.319 brouard 11218: Tvar[k]=atoi(stre); /* V2+V1+V5*age+V4+V3*age Tvar[5]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */
1.234 brouard 11219: Typevar[k]=1; /* 1 for age product */
1.319 brouard 11220: cptcovage++; /* Counts the number of covariates which include age as a product */
11221: Tage[cptcovage]=k; /* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
1.234 brouard 11222: /*printf("stre=%s ", stre);*/
11223: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
11224: cptcovprod--;
11225: cutl(stre,strb,strc,'V');
11226: Tvar[k]=atoi(stre);
11227: Typevar[k]=1; /* 1 for age product */
11228: cptcovage++;
11229: Tage[cptcovage]=k;
11230: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
11231: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
11232: cptcovn++;
11233: cptcovprodnoage++;k1++;
11234: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
1.339 brouard 11235: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* ncovcolt+k1; For model-covariate k tells which data-covariate to use but
1.234 brouard 11236: because this model-covariate is a construction we invent a new column
11237: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
1.335 brouard 11238: If already ncovcol=4 and model= V2 + V1 + V1*V4 + age*V3 + V3*V2
1.319 brouard 11239: thus after V4 we invent V5 and V6 because age*V3 will be computed in 4
1.339 brouard 11240: Tvar[3=V1*V4]=4+1=5 Tvar[5=V3*V2]=4 + 2= 6, Tvar[4=age*V3]=3 etc */
1.335 brouard 11241: /* Please remark that the new variables are model dependent */
11242: /* If we have 4 variable but the model uses only 3, like in
11243: * model= V1 + age*V1 + V2 + V3 + age*V2 + age*V3 + V1*V2 + V1*V3
11244: * k= 1 2 3 4 5 6 7 8
11245: * Tvar[k]=1 1 2 3 2 3 (5 6) (and not 4 5 because of V4 missing)
11246: * Tage[kk] [1]= 2 [2]=5 [3]=6 kk=1 to cptcovage=3
11247: * Tvar[Tage[kk]][1]=2 [2]=2 [3]=3
11248: */
1.339 brouard 11249: Typevar[k]=2; /* 2 for product */
1.234 brouard 11250: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
11251: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
1.319 brouard 11252: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 */
1.234 brouard 11253: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
1.330 brouard 11254: Tvardk[k][1] =atoi(strc); /* m 1 for V1*/
1.234 brouard 11255: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
1.330 brouard 11256: Tvardk[k][2] =atoi(stre); /* n 4 for V4*/
1.234 brouard 11257: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
11258: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
11259: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 11260: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 11261: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
1.339 brouard 11262: 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 */
11263: for (i=1; i<=lastobs;i++){/* For fixed product */
1.234 brouard 11264: /* Computes the new covariate which is a product of
11265: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
1.339 brouard 11266: covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
11267: }
11268: } /*End of FixedV */
1.234 brouard 11269: } /* End age is not in the model */
11270: } /* End if model includes a product */
1.319 brouard 11271: else { /* not a product */
1.234 brouard 11272: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
11273: /* scanf("%d",i);*/
11274: cutl(strd,strc,strb,'V');
11275: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
11276: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
11277: Tvar[k]=atoi(strd);
11278: Typevar[k]=0; /* 0 for simple covariates */
11279: }
11280: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 11281: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 11282: scanf("%d",i);*/
1.187 brouard 11283: } /* end of loop + on total covariates */
11284: } /* end if strlen(modelsave == 0) age*age might exist */
11285: } /* end if strlen(model == 0) */
1.136 brouard 11286:
11287: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
11288: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 11289:
1.136 brouard 11290: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 11291: printf("cptcovprod=%d ", cptcovprod);
11292: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
11293: scanf("%d ",i);*/
11294:
11295:
1.230 brouard 11296: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
11297: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 11298: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
11299: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
11300: k = 1 2 3 4 5 6 7 8 9
11301: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
1.319 brouard 11302: Typevar[k]= 0 0 0 2 1 0 2 1 0
1.227 brouard 11303: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
11304: Dummy[k] 1 0 0 0 3 1 1 2 3
11305: Tmodelind[combination of covar]=k;
1.225 brouard 11306: */
11307: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 11308: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 11309: /* 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 11310: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.318 brouard 11311: printf("Model=1+age+%s\n\
1.227 brouard 11312: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
11313: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
11314: 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 11315: fprintf(ficlog,"Model=1+age+%s\n\
1.227 brouard 11316: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
11317: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
11318: 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 11319: for(k=-1;k<=NCOVMAX; k++){ Fixed[k]=0; Dummy[k]=0;}
11320: for(k=1;k<=NCOVMAX; k++){TvarFind[k]=0; TvarVind[k]=0;}
1.343 brouard 11321: for(k=1, ncovf=0, nsd=0, nsq=0, ncovv=0, ncova=0, ncoveff=0, nqfveff=0, ntveff=0, nqtveff=0, ncovvt=0;k<=cptcovt; k++){ /* or cptocvt loop on k from model */
1.234 brouard 11322: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 11323: Fixed[k]= 0;
11324: Dummy[k]= 0;
1.225 brouard 11325: ncoveff++;
1.232 brouard 11326: ncovf++;
1.234 brouard 11327: nsd++;
11328: modell[k].maintype= FTYPE;
11329: TvarsD[nsd]=Tvar[k];
11330: TvarsDind[nsd]=k;
1.330 brouard 11331: TnsdVar[Tvar[k]]=nsd;
1.234 brouard 11332: TvarF[ncovf]=Tvar[k];
11333: TvarFind[ncovf]=k;
11334: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
11335: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.339 brouard 11336: /* }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /\* Product of fixed dummy (<=ncovcol) covariates For a fixed product k is higher than ncovcol *\/ */
11337: }else if( Tposprod[k]>0 && Typevar[k]==2 && FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){ /* Needs a fixed product Product of fixed dummy (<=ncovcol) covariates For a fixed product k is higher than ncovcol */
1.234 brouard 11338: Fixed[k]= 0;
11339: Dummy[k]= 0;
11340: ncoveff++;
11341: ncovf++;
11342: modell[k].maintype= FTYPE;
11343: TvarF[ncovf]=Tvar[k];
1.330 brouard 11344: /* TnsdVar[Tvar[k]]=nsd; */ /* To be done */
1.234 brouard 11345: TvarFind[ncovf]=k;
1.230 brouard 11346: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 11347: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.240 brouard 11348: }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 11349: Fixed[k]= 0;
11350: Dummy[k]= 1;
1.230 brouard 11351: nqfveff++;
1.234 brouard 11352: modell[k].maintype= FTYPE;
11353: modell[k].subtype= FQ;
11354: nsq++;
1.334 brouard 11355: TvarsQ[nsq]=Tvar[k]; /* Gives the variable name (extended to products) of first nsq simple quantitative covariates (fixed or time vary see below */
11356: TvarsQind[nsq]=k; /* Gives the position in the model equation of the first nsq simple quantitative covariates (fixed or time vary) */
1.232 brouard 11357: ncovf++;
1.234 brouard 11358: TvarF[ncovf]=Tvar[k];
11359: TvarFind[ncovf]=k;
1.231 brouard 11360: 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 11361: 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 11362: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.339 brouard 11363: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11364: /* model V1+V3+age*V1+age*V3+V1*V3 */
11365: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11366: ncovvt++;
11367: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
11368: TvarVVind[ncovvt]=k; /* TvarVVind[1]=2 (second position in the model equation */
11369:
1.227 brouard 11370: Fixed[k]= 1;
11371: Dummy[k]= 0;
1.225 brouard 11372: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 11373: modell[k].maintype= VTYPE;
11374: modell[k].subtype= VD;
11375: nsd++;
11376: TvarsD[nsd]=Tvar[k];
11377: TvarsDind[nsd]=k;
1.330 brouard 11378: TnsdVar[Tvar[k]]=nsd; /* To be verified */
1.234 brouard 11379: ncovv++; /* Only simple time varying variables */
11380: TvarV[ncovv]=Tvar[k];
1.242 brouard 11381: 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 11382: 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 */
11383: 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 11384: 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);
11385: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 11386: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.339 brouard 11387: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11388: /* model V1+V3+age*V1+age*V3+V1*V3 */
11389: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11390: ncovvt++;
11391: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
11392: TvarVVind[ncovvt]=k; /* TvarVV[1]=V3 (first time varying in the model equation */
11393:
1.234 brouard 11394: Fixed[k]= 1;
11395: Dummy[k]= 1;
11396: nqtveff++;
11397: modell[k].maintype= VTYPE;
11398: modell[k].subtype= VQ;
11399: ncovv++; /* Only simple time varying variables */
11400: nsq++;
1.334 brouard 11401: 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) */
11402: 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 11403: TvarV[ncovv]=Tvar[k];
1.242 brouard 11404: 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 11405: 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 */
11406: 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 11407: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
11408: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
1.342 brouard 11409: /* printf("Quasi TmodelQind[%d]=%d,Tvar[TmodelQind[%d]]=V%d, ncovcol=%d, nqv=%d, ntv=%d,Tvar[k]- ncovcol-nqv-ntv=%d\n",nqtveff,k,nqtveff,Tvar[k], ncovcol, nqv, ntv, Tvar[k]- ncovcol-nqv-ntv); */
11410: /* printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv); */
1.227 brouard 11411: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 11412: ncova++;
11413: TvarA[ncova]=Tvar[k];
11414: TvarAind[ncova]=k;
1.231 brouard 11415: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 11416: Fixed[k]= 2;
11417: Dummy[k]= 2;
11418: modell[k].maintype= ATYPE;
11419: modell[k].subtype= APFD;
11420: /* ncoveff++; */
1.227 brouard 11421: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 11422: Fixed[k]= 2;
11423: Dummy[k]= 3;
11424: modell[k].maintype= ATYPE;
11425: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
11426: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 11427: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 11428: Fixed[k]= 3;
11429: Dummy[k]= 2;
11430: modell[k].maintype= ATYPE;
11431: modell[k].subtype= APVD; /* Product age * varying dummy */
11432: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 11433: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 11434: Fixed[k]= 3;
11435: Dummy[k]= 3;
11436: modell[k].maintype= ATYPE;
11437: modell[k].subtype= APVQ; /* Product age * varying quantitative */
11438: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 11439: }
1.339 brouard 11440: }else if (Typevar[k] == 2) { /* product Vn * Vm without age, V1+V3+age*V1+age*V3+V1*V3 looking at V1*V3, Typevar={0, 0, 1, 1, 2}, k=5, V1 is fixed, V3 is timevary, V5 is a product */
11441: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11442: /* model V1+V3+age*V1+age*V3+V1*V3 */
11443: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11444: k1=Tposprod[k]; /* Position in the products of product k, Tposprod={0, 0, 0, 0, 1} k1=1 first product but second time varying because of V3 */
11445: ncovvt++;
11446: TvarVV[ncovvt]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */
11447: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
11448: ncovvt++;
11449: TvarVV[ncovvt]=Tvard[k1][2]; /* TvarVV[3]=V3 */
11450: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
11451:
11452:
11453: if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */
11454: if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */
1.240 brouard 11455: Fixed[k]= 1;
11456: Dummy[k]= 0;
11457: modell[k].maintype= FTYPE;
11458: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
11459: ncovf++; /* Fixed variables without age */
11460: TvarF[ncovf]=Tvar[k];
11461: TvarFind[ncovf]=k;
1.339 brouard 11462: }else if(Tvard[k1][2] <=ncovcol+nqv){ /* Vm is quanti fixed */
11463: Fixed[k]= 0; /* Fixed product */
1.240 brouard 11464: Dummy[k]= 1;
11465: modell[k].maintype= FTYPE;
11466: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
11467: ncovf++; /* Varying variables without age */
11468: TvarF[ncovf]=Tvar[k];
11469: TvarFind[ncovf]=k;
1.339 brouard 11470: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is a time varying dummy covariate */
1.240 brouard 11471: Fixed[k]= 1;
11472: Dummy[k]= 0;
11473: modell[k].maintype= VTYPE;
11474: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
11475: ncovv++; /* Varying variables without age */
1.339 brouard 11476: TvarV[ncovv]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */
11477: TvarVind[ncovv]=k;/* TvarVind[1]=5 */
11478: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */
1.240 brouard 11479: Fixed[k]= 1;
11480: Dummy[k]= 1;
11481: modell[k].maintype= VTYPE;
11482: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
11483: ncovv++; /* Varying variables without age */
11484: TvarV[ncovv]=Tvar[k];
11485: TvarVind[ncovv]=k;
11486: }
1.339 brouard 11487: }else if(Tvard[k1][1] <=ncovcol+nqv){ /* Vn is fixed quanti */
11488: if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */
11489: Fixed[k]= 0; /* Fixed product */
1.240 brouard 11490: Dummy[k]= 1;
11491: modell[k].maintype= FTYPE;
11492: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
11493: ncovf++; /* Fixed variables without age */
11494: TvarF[ncovf]=Tvar[k];
11495: TvarFind[ncovf]=k;
1.339 brouard 11496: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is time varying */
1.240 brouard 11497: Fixed[k]= 1;
11498: Dummy[k]= 1;
11499: modell[k].maintype= VTYPE;
11500: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
11501: ncovv++; /* Varying variables without age */
11502: TvarV[ncovv]=Tvar[k];
11503: TvarVind[ncovv]=k;
1.339 brouard 11504: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is time varying quanti */
1.240 brouard 11505: Fixed[k]= 1;
11506: Dummy[k]= 1;
11507: modell[k].maintype= VTYPE;
11508: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
11509: ncovv++; /* Varying variables without age */
11510: TvarV[ncovv]=Tvar[k];
11511: TvarVind[ncovv]=k;
11512: ncovv++; /* Varying variables without age */
11513: TvarV[ncovv]=Tvar[k];
11514: TvarVind[ncovv]=k;
11515: }
1.339 brouard 11516: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ /* Vn is time varying dummy */
1.240 brouard 11517: if(Tvard[k1][2] <=ncovcol){
11518: Fixed[k]= 1;
11519: Dummy[k]= 1;
11520: modell[k].maintype= VTYPE;
11521: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
11522: ncovv++; /* Varying variables without age */
11523: TvarV[ncovv]=Tvar[k];
11524: TvarVind[ncovv]=k;
11525: }else if(Tvard[k1][2] <=ncovcol+nqv){
11526: Fixed[k]= 1;
11527: Dummy[k]= 1;
11528: modell[k].maintype= VTYPE;
11529: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
11530: ncovv++; /* Varying variables without age */
11531: TvarV[ncovv]=Tvar[k];
11532: TvarVind[ncovv]=k;
11533: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
11534: Fixed[k]= 1;
11535: Dummy[k]= 0;
11536: modell[k].maintype= VTYPE;
11537: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
11538: ncovv++; /* Varying variables without age */
11539: TvarV[ncovv]=Tvar[k];
11540: TvarVind[ncovv]=k;
11541: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
11542: Fixed[k]= 1;
11543: Dummy[k]= 1;
11544: modell[k].maintype= VTYPE;
11545: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
11546: ncovv++; /* Varying variables without age */
11547: TvarV[ncovv]=Tvar[k];
11548: TvarVind[ncovv]=k;
11549: }
1.339 brouard 11550: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ /* Vn is time varying quanti */
1.240 brouard 11551: if(Tvard[k1][2] <=ncovcol){
11552: Fixed[k]= 1;
11553: Dummy[k]= 1;
11554: modell[k].maintype= VTYPE;
11555: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
11556: ncovv++; /* Varying variables without age */
11557: TvarV[ncovv]=Tvar[k];
11558: TvarVind[ncovv]=k;
11559: }else if(Tvard[k1][2] <=ncovcol+nqv){
11560: Fixed[k]= 1;
11561: Dummy[k]= 1;
11562: modell[k].maintype= VTYPE;
11563: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
11564: ncovv++; /* Varying variables without age */
11565: TvarV[ncovv]=Tvar[k];
11566: TvarVind[ncovv]=k;
11567: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
11568: Fixed[k]= 1;
11569: Dummy[k]= 1;
11570: modell[k].maintype= VTYPE;
11571: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
11572: ncovv++; /* Varying variables without age */
11573: TvarV[ncovv]=Tvar[k];
11574: TvarVind[ncovv]=k;
11575: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
11576: Fixed[k]= 1;
11577: Dummy[k]= 1;
11578: modell[k].maintype= VTYPE;
11579: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
11580: ncovv++; /* Varying variables without age */
11581: TvarV[ncovv]=Tvar[k];
11582: TvarVind[ncovv]=k;
11583: }
1.227 brouard 11584: }else{
1.240 brouard 11585: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
11586: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
11587: } /*end k1*/
1.225 brouard 11588: }else{
1.226 brouard 11589: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
11590: 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 11591: }
1.342 brouard 11592: /* 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]); */
11593: /* printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype); */
1.227 brouard 11594: 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]);
11595: }
11596: /* Searching for doublons in the model */
11597: for(k1=1; k1<= cptcovt;k1++){
11598: for(k2=1; k2 <k1;k2++){
1.285 brouard 11599: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
11600: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 11601: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
11602: if(Tvar[k1]==Tvar[k2]){
1.338 brouard 11603: 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]);
11604: 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 11605: return(1);
11606: }
11607: }else if (Typevar[k1] ==2){
11608: k3=Tposprod[k1];
11609: k4=Tposprod[k2];
11610: 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 11611: 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]]);
11612: 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 11613: return(1);
11614: }
11615: }
1.227 brouard 11616: }
11617: }
1.225 brouard 11618: }
11619: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
11620: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 11621: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
11622: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 11623: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 11624: /*endread:*/
1.225 brouard 11625: printf("Exiting decodemodel: ");
11626: return (1);
1.136 brouard 11627: }
11628:
1.169 brouard 11629: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 11630: {/* Check ages at death */
1.136 brouard 11631: int i, m;
1.218 brouard 11632: int firstone=0;
11633:
1.136 brouard 11634: for (i=1; i<=imx; i++) {
11635: for(m=2; (m<= maxwav); m++) {
11636: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
11637: anint[m][i]=9999;
1.216 brouard 11638: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
11639: s[m][i]=-1;
1.136 brouard 11640: }
11641: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 11642: *nberr = *nberr + 1;
1.218 brouard 11643: if(firstone == 0){
11644: firstone=1;
1.260 brouard 11645: 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 11646: }
1.262 brouard 11647: 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 11648: s[m][i]=-1; /* Droping the death status */
1.136 brouard 11649: }
11650: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 11651: (*nberr)++;
1.259 brouard 11652: 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 11653: 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 11654: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 11655: }
11656: }
11657: }
11658:
11659: for (i=1; i<=imx; i++) {
11660: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
11661: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 11662: 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 11663: if (s[m][i] >= nlstate+1) {
1.169 brouard 11664: if(agedc[i]>0){
11665: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 11666: agev[m][i]=agedc[i];
1.214 brouard 11667: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 11668: }else {
1.136 brouard 11669: if ((int)andc[i]!=9999){
11670: nbwarn++;
11671: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
11672: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
11673: agev[m][i]=-1;
11674: }
11675: }
1.169 brouard 11676: } /* agedc > 0 */
1.214 brouard 11677: } /* end if */
1.136 brouard 11678: else if(s[m][i] !=9){ /* Standard case, age in fractional
11679: years but with the precision of a month */
11680: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
11681: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
11682: agev[m][i]=1;
11683: else if(agev[m][i] < *agemin){
11684: *agemin=agev[m][i];
11685: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
11686: }
11687: else if(agev[m][i] >*agemax){
11688: *agemax=agev[m][i];
1.156 brouard 11689: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 11690: }
11691: /*agev[m][i]=anint[m][i]-annais[i];*/
11692: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 11693: } /* en if 9*/
1.136 brouard 11694: else { /* =9 */
1.214 brouard 11695: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 11696: agev[m][i]=1;
11697: s[m][i]=-1;
11698: }
11699: }
1.214 brouard 11700: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 11701: agev[m][i]=1;
1.214 brouard 11702: else{
11703: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
11704: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
11705: agev[m][i]=0;
11706: }
11707: } /* End for lastpass */
11708: }
1.136 brouard 11709:
11710: for (i=1; i<=imx; i++) {
11711: for(m=firstpass; (m<=lastpass); m++){
11712: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 11713: (*nberr)++;
1.136 brouard 11714: 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);
11715: 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);
11716: return 1;
11717: }
11718: }
11719: }
11720:
11721: /*for (i=1; i<=imx; i++){
11722: for (m=firstpass; (m<lastpass); m++){
11723: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
11724: }
11725:
11726: }*/
11727:
11728:
1.139 brouard 11729: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
11730: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 11731:
11732: return (0);
1.164 brouard 11733: /* endread:*/
1.136 brouard 11734: printf("Exiting calandcheckages: ");
11735: return (1);
11736: }
11737:
1.172 brouard 11738: #if defined(_MSC_VER)
11739: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
11740: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
11741: //#include "stdafx.h"
11742: //#include <stdio.h>
11743: //#include <tchar.h>
11744: //#include <windows.h>
11745: //#include <iostream>
11746: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
11747:
11748: LPFN_ISWOW64PROCESS fnIsWow64Process;
11749:
11750: BOOL IsWow64()
11751: {
11752: BOOL bIsWow64 = FALSE;
11753:
11754: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
11755: // (HANDLE, PBOOL);
11756:
11757: //LPFN_ISWOW64PROCESS fnIsWow64Process;
11758:
11759: HMODULE module = GetModuleHandle(_T("kernel32"));
11760: const char funcName[] = "IsWow64Process";
11761: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
11762: GetProcAddress(module, funcName);
11763:
11764: if (NULL != fnIsWow64Process)
11765: {
11766: if (!fnIsWow64Process(GetCurrentProcess(),
11767: &bIsWow64))
11768: //throw std::exception("Unknown error");
11769: printf("Unknown error\n");
11770: }
11771: return bIsWow64 != FALSE;
11772: }
11773: #endif
1.177 brouard 11774:
1.191 brouard 11775: void syscompilerinfo(int logged)
1.292 brouard 11776: {
11777: #include <stdint.h>
11778:
11779: /* #include "syscompilerinfo.h"*/
1.185 brouard 11780: /* command line Intel compiler 32bit windows, XP compatible:*/
11781: /* /GS /W3 /Gy
11782: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
11783: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
11784: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 11785: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
11786: */
11787: /* 64 bits */
1.185 brouard 11788: /*
11789: /GS /W3 /Gy
11790: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
11791: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
11792: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
11793: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
11794: /* Optimization are useless and O3 is slower than O2 */
11795: /*
11796: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
11797: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
11798: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
11799: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
11800: */
1.186 brouard 11801: /* Link is */ /* /OUT:"visual studio
1.185 brouard 11802: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
11803: /PDB:"visual studio
11804: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
11805: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
11806: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
11807: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
11808: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
11809: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
11810: uiAccess='false'"
11811: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
11812: /NOLOGO /TLBID:1
11813: */
1.292 brouard 11814:
11815:
1.177 brouard 11816: #if defined __INTEL_COMPILER
1.178 brouard 11817: #if defined(__GNUC__)
11818: struct utsname sysInfo; /* For Intel on Linux and OS/X */
11819: #endif
1.177 brouard 11820: #elif defined(__GNUC__)
1.179 brouard 11821: #ifndef __APPLE__
1.174 brouard 11822: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 11823: #endif
1.177 brouard 11824: struct utsname sysInfo;
1.178 brouard 11825: int cross = CROSS;
11826: if (cross){
11827: printf("Cross-");
1.191 brouard 11828: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 11829: }
1.174 brouard 11830: #endif
11831:
1.191 brouard 11832: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 11833: #if defined(__clang__)
1.191 brouard 11834: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 11835: #endif
11836: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 11837: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 11838: #endif
11839: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 11840: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 11841: #endif
11842: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 11843: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 11844: #endif
11845: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 11846: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 11847: #endif
11848: #if defined(_MSC_VER)
1.191 brouard 11849: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 11850: #endif
11851: #if defined(__PGI)
1.191 brouard 11852: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 11853: #endif
11854: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 11855: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 11856: #endif
1.191 brouard 11857: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 11858:
1.167 brouard 11859: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
11860: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
11861: // Windows (x64 and x86)
1.191 brouard 11862: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 11863: #elif __unix__ // all unices, not all compilers
11864: // Unix
1.191 brouard 11865: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 11866: #elif __linux__
11867: // linux
1.191 brouard 11868: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 11869: #elif __APPLE__
1.174 brouard 11870: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 11871: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 11872: #endif
11873:
11874: /* __MINGW32__ */
11875: /* __CYGWIN__ */
11876: /* __MINGW64__ */
11877: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
11878: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
11879: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
11880: /* _WIN64 // Defined for applications for Win64. */
11881: /* _M_X64 // Defined for compilations that target x64 processors. */
11882: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 11883:
1.167 brouard 11884: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 11885: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 11886: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 11887: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 11888: #else
1.191 brouard 11889: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 11890: #endif
11891:
1.169 brouard 11892: #if defined(__GNUC__)
11893: # if defined(__GNUC_PATCHLEVEL__)
11894: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
11895: + __GNUC_MINOR__ * 100 \
11896: + __GNUC_PATCHLEVEL__)
11897: # else
11898: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
11899: + __GNUC_MINOR__ * 100)
11900: # endif
1.174 brouard 11901: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 11902: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 11903:
11904: if (uname(&sysInfo) != -1) {
11905: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 11906: 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 11907: }
11908: else
11909: perror("uname() error");
1.179 brouard 11910: //#ifndef __INTEL_COMPILER
11911: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 11912: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 11913: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 11914: #endif
1.169 brouard 11915: #endif
1.172 brouard 11916:
1.286 brouard 11917: // void main ()
1.172 brouard 11918: // {
1.169 brouard 11919: #if defined(_MSC_VER)
1.174 brouard 11920: if (IsWow64()){
1.191 brouard 11921: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
11922: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 11923: }
11924: else{
1.191 brouard 11925: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
11926: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 11927: }
1.172 brouard 11928: // printf("\nPress Enter to continue...");
11929: // getchar();
11930: // }
11931:
1.169 brouard 11932: #endif
11933:
1.167 brouard 11934:
1.219 brouard 11935: }
1.136 brouard 11936:
1.219 brouard 11937: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 11938: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.332 brouard 11939: /* Computes the prevalence limit for each combination of the dummy covariates */
1.235 brouard 11940: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 11941: /* double ftolpl = 1.e-10; */
1.180 brouard 11942: double age, agebase, agelim;
1.203 brouard 11943: double tot;
1.180 brouard 11944:
1.202 brouard 11945: strcpy(filerespl,"PL_");
11946: strcat(filerespl,fileresu);
11947: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 11948: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
11949: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 11950: }
1.288 brouard 11951: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
11952: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 11953: pstamp(ficrespl);
1.288 brouard 11954: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 11955: fprintf(ficrespl,"#Age ");
11956: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
11957: fprintf(ficrespl,"\n");
1.180 brouard 11958:
1.219 brouard 11959: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 11960:
1.219 brouard 11961: agebase=ageminpar;
11962: agelim=agemaxpar;
1.180 brouard 11963:
1.227 brouard 11964: /* i1=pow(2,ncoveff); */
1.234 brouard 11965: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 11966: if (cptcovn < 1){i1=1;}
1.180 brouard 11967:
1.337 brouard 11968: /* for(k=1; k<=i1;k++){ /\* For each combination k of dummy covariates in the model *\/ */
1.238 brouard 11969: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 11970: k=TKresult[nres];
1.338 brouard 11971: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 11972: /* if(i1 != 1 && TKresult[nres]!= k) /\* We found the combination k corresponding to the resultline value of dummies *\/ */
11973: /* continue; */
1.235 brouard 11974:
1.238 brouard 11975: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
11976: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
11977: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
11978: /* k=k+1; */
11979: /* to clean */
1.332 brouard 11980: /*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*/
1.238 brouard 11981: fprintf(ficrespl,"#******");
11982: printf("#******");
11983: fprintf(ficlog,"#******");
1.337 brouard 11984: 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 11985: /* fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Here problem for varying dummy*\/ */
1.337 brouard 11986: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11987: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
11988: fprintf(ficrespl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11989: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11990: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
11991: }
11992: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
11993: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
11994: /* fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
11995: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
11996: /* } */
1.238 brouard 11997: fprintf(ficrespl,"******\n");
11998: printf("******\n");
11999: fprintf(ficlog,"******\n");
12000: if(invalidvarcomb[k]){
12001: printf("\nCombination (%d) ignored because no case \n",k);
12002: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
12003: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
12004: continue;
12005: }
1.219 brouard 12006:
1.238 brouard 12007: fprintf(ficrespl,"#Age ");
1.337 brouard 12008: /* for(j=1;j<=cptcoveff;j++) { */
12009: /* fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12010: /* } */
12011: for(j=1;j<=cptcovs;j++) { /* New the quanti variable is added */
12012: fprintf(ficrespl,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12013: }
12014: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
12015: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 12016:
1.238 brouard 12017: for (age=agebase; age<=agelim; age++){
12018: /* for (age=agebase; age<=agebase; age++){ */
1.337 brouard 12019: /**< Computes the prevalence limit in each live state at age x and for covariate combination (k and) nres */
12020: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres); /* Nicely done */
1.238 brouard 12021: fprintf(ficrespl,"%.0f ",age );
1.337 brouard 12022: /* for(j=1;j<=cptcoveff;j++) */
12023: /* fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12024: for(j=1;j<=cptcovs;j++)
12025: fprintf(ficrespl,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12026: tot=0.;
12027: for(i=1; i<=nlstate;i++){
12028: tot += prlim[i][i];
12029: fprintf(ficrespl," %.5f", prlim[i][i]);
12030: }
12031: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
12032: } /* Age */
12033: /* was end of cptcod */
1.337 brouard 12034: } /* nres */
12035: /* } /\* for each combination *\/ */
1.219 brouard 12036: return 0;
1.180 brouard 12037: }
12038:
1.218 brouard 12039: 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 12040: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 12041:
12042: /* Computes the back prevalence limit for any combination of covariate values
12043: * at any age between ageminpar and agemaxpar
12044: */
1.235 brouard 12045: int i, j, k, i1, nres=0 ;
1.217 brouard 12046: /* double ftolpl = 1.e-10; */
12047: double age, agebase, agelim;
12048: double tot;
1.218 brouard 12049: /* double ***mobaverage; */
12050: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 12051:
12052: strcpy(fileresplb,"PLB_");
12053: strcat(fileresplb,fileresu);
12054: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 12055: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
12056: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 12057: }
1.288 brouard 12058: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
12059: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 12060: pstamp(ficresplb);
1.288 brouard 12061: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 12062: fprintf(ficresplb,"#Age ");
12063: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
12064: fprintf(ficresplb,"\n");
12065:
1.218 brouard 12066:
12067: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
12068:
12069: agebase=ageminpar;
12070: agelim=agemaxpar;
12071:
12072:
1.227 brouard 12073: i1=pow(2,cptcoveff);
1.218 brouard 12074: if (cptcovn < 1){i1=1;}
1.227 brouard 12075:
1.238 brouard 12076: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.338 brouard 12077: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
12078: k=TKresult[nres];
12079: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
12080: /* if(i1 != 1 && TKresult[nres]!= k) */
12081: /* continue; */
12082: /* /\*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*\/ */
1.238 brouard 12083: fprintf(ficresplb,"#******");
12084: printf("#******");
12085: fprintf(ficlog,"#******");
1.338 brouard 12086: 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) */
12087: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12088: fprintf(ficresplb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12089: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12090: }
1.338 brouard 12091: /* for(j=1;j<=cptcoveff ;j++) {/\* all covariates *\/ */
12092: /* fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12093: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12094: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12095: /* } */
12096: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
12097: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12098: /* fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12099: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12100: /* } */
1.238 brouard 12101: fprintf(ficresplb,"******\n");
12102: printf("******\n");
12103: fprintf(ficlog,"******\n");
12104: if(invalidvarcomb[k]){
12105: printf("\nCombination (%d) ignored because no cases \n",k);
12106: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
12107: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
12108: continue;
12109: }
1.218 brouard 12110:
1.238 brouard 12111: fprintf(ficresplb,"#Age ");
1.338 brouard 12112: for(j=1;j<=cptcovs;j++) {
12113: fprintf(ficresplb,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12114: }
12115: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
12116: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 12117:
12118:
1.238 brouard 12119: for (age=agebase; age<=agelim; age++){
12120: /* for (age=agebase; age<=agebase; age++){ */
12121: if(mobilavproj > 0){
12122: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
12123: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 12124: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 12125: }else if (mobilavproj == 0){
12126: 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);
12127: 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);
12128: exit(1);
12129: }else{
12130: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 12131: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 12132: /* printf("TOTOT\n"); */
12133: /* exit(1); */
1.238 brouard 12134: }
12135: fprintf(ficresplb,"%.0f ",age );
1.338 brouard 12136: for(j=1;j<=cptcovs;j++)
12137: fprintf(ficresplb,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12138: tot=0.;
12139: for(i=1; i<=nlstate;i++){
12140: tot += bprlim[i][i];
12141: fprintf(ficresplb," %.5f", bprlim[i][i]);
12142: }
12143: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
12144: } /* Age */
12145: /* was end of cptcod */
1.255 brouard 12146: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.338 brouard 12147: /* } /\* end of any combination *\/ */
1.238 brouard 12148: } /* end of nres */
1.218 brouard 12149: /* hBijx(p, bage, fage); */
12150: /* fclose(ficrespijb); */
12151:
12152: return 0;
1.217 brouard 12153: }
1.218 brouard 12154:
1.180 brouard 12155: int hPijx(double *p, int bage, int fage){
12156: /*------------- h Pij x at various ages ------------*/
1.336 brouard 12157: /* to be optimized with precov */
1.180 brouard 12158: int stepsize;
12159: int agelim;
12160: int hstepm;
12161: int nhstepm;
1.235 brouard 12162: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 12163:
12164: double agedeb;
12165: double ***p3mat;
12166:
1.337 brouard 12167: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
12168: if((ficrespij=fopen(filerespij,"w"))==NULL) {
12169: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
12170: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
12171: }
12172: printf("Computing pij: result on file '%s' \n", filerespij);
12173: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
12174:
12175: stepsize=(int) (stepm+YEARM-1)/YEARM;
12176: /*if (stepm<=24) stepsize=2;*/
12177:
12178: agelim=AGESUP;
12179: hstepm=stepsize*YEARM; /* Every year of age */
12180: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
12181:
12182: /* hstepm=1; aff par mois*/
12183: pstamp(ficrespij);
12184: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
12185: i1= pow(2,cptcoveff);
12186: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12187: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
12188: /* k=k+1; */
12189: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
12190: k=TKresult[nres];
1.338 brouard 12191: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12192: /* for(k=1; k<=i1;k++){ */
12193: /* if(i1 != 1 && TKresult[nres]!= k) */
12194: /* continue; */
12195: fprintf(ficrespij,"\n#****** ");
12196: for(j=1;j<=cptcovs;j++){
12197: fprintf(ficrespij," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12198: /* fprintf(ficrespij,"@wV%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12199: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
12200: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12201: /* fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12202: }
12203: fprintf(ficrespij,"******\n");
12204:
12205: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
12206: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
12207: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
12208:
12209: /* nhstepm=nhstepm*YEARM; aff par mois*/
12210:
12211: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12212: oldm=oldms;savm=savms;
12213: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
12214: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
12215: for(i=1; i<=nlstate;i++)
12216: for(j=1; j<=nlstate+ndeath;j++)
12217: fprintf(ficrespij," %1d-%1d",i,j);
12218: fprintf(ficrespij,"\n");
12219: for (h=0; h<=nhstepm; h++){
12220: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
12221: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.183 brouard 12222: for(i=1; i<=nlstate;i++)
12223: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 12224: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.183 brouard 12225: fprintf(ficrespij,"\n");
12226: }
1.337 brouard 12227: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12228: fprintf(ficrespij,"\n");
1.180 brouard 12229: }
1.337 brouard 12230: }
12231: /*}*/
12232: return 0;
1.180 brouard 12233: }
1.218 brouard 12234:
12235: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 12236: /*------------- h Bij x at various ages ------------*/
1.336 brouard 12237: /* To be optimized with precov */
1.217 brouard 12238: int stepsize;
1.218 brouard 12239: /* int agelim; */
12240: int ageminl;
1.217 brouard 12241: int hstepm;
12242: int nhstepm;
1.238 brouard 12243: int h, i, i1, j, k, nres;
1.218 brouard 12244:
1.217 brouard 12245: double agedeb;
12246: double ***p3mat;
1.218 brouard 12247:
12248: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
12249: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
12250: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
12251: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
12252: }
12253: printf("Computing pij back: result on file '%s' \n", filerespijb);
12254: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
12255:
12256: stepsize=(int) (stepm+YEARM-1)/YEARM;
12257: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 12258:
1.218 brouard 12259: /* agelim=AGESUP; */
1.289 brouard 12260: ageminl=AGEINF; /* was 30 */
1.218 brouard 12261: hstepm=stepsize*YEARM; /* Every year of age */
12262: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
12263:
12264: /* hstepm=1; aff par mois*/
12265: pstamp(ficrespijb);
1.255 brouard 12266: 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 12267: i1= pow(2,cptcoveff);
1.218 brouard 12268: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12269: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
12270: /* k=k+1; */
1.238 brouard 12271: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 12272: k=TKresult[nres];
1.338 brouard 12273: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12274: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
12275: /* if(i1 != 1 && TKresult[nres]!= k) */
12276: /* continue; */
12277: fprintf(ficrespijb,"\n#****** ");
12278: for(j=1;j<=cptcovs;j++){
1.338 brouard 12279: fprintf(ficrespijb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.337 brouard 12280: /* for(j=1;j<=cptcoveff;j++) */
12281: /* fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12282: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
12283: /* fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12284: }
12285: fprintf(ficrespijb,"******\n");
12286: if(invalidvarcomb[k]){ /* Is it necessary here? */
12287: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
12288: continue;
12289: }
12290:
12291: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
12292: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
12293: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
12294: 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 */
12295: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 or 28*/
12296:
12297: /* nhstepm=nhstepm*YEARM; aff par mois*/
12298:
12299: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
12300: /* and memory limitations if stepm is small */
12301:
12302: /* oldm=oldms;savm=savms; */
12303: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
12304: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);/* Bug valgrind */
12305: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
12306: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
12307: for(i=1; i<=nlstate;i++)
12308: for(j=1; j<=nlstate+ndeath;j++)
12309: fprintf(ficrespijb," %1d-%1d",i,j);
12310: fprintf(ficrespijb,"\n");
12311: for (h=0; h<=nhstepm; h++){
12312: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
12313: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
12314: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
1.217 brouard 12315: for(i=1; i<=nlstate;i++)
12316: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 12317: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);/* Bug valgrind */
1.217 brouard 12318: fprintf(ficrespijb,"\n");
1.337 brouard 12319: }
12320: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12321: fprintf(ficrespijb,"\n");
12322: } /* end age deb */
12323: /* } /\* end combination *\/ */
1.238 brouard 12324: } /* end nres */
1.218 brouard 12325: return 0;
12326: } /* hBijx */
1.217 brouard 12327:
1.180 brouard 12328:
1.136 brouard 12329: /***********************************************/
12330: /**************** Main Program *****************/
12331: /***********************************************/
12332:
12333: int main(int argc, char *argv[])
12334: {
12335: #ifdef GSL
12336: const gsl_multimin_fminimizer_type *T;
12337: size_t iteri = 0, it;
12338: int rval = GSL_CONTINUE;
12339: int status = GSL_SUCCESS;
12340: double ssval;
12341: #endif
12342: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 12343: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
12344: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 12345: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 12346: int jj, ll, li, lj, lk;
1.136 brouard 12347: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 12348: int num_filled;
1.136 brouard 12349: int itimes;
12350: int NDIM=2;
12351: int vpopbased=0;
1.235 brouard 12352: int nres=0;
1.258 brouard 12353: int endishere=0;
1.277 brouard 12354: int noffset=0;
1.274 brouard 12355: int ncurrv=0; /* Temporary variable */
12356:
1.164 brouard 12357: char ca[32], cb[32];
1.136 brouard 12358: /* FILE *fichtm; *//* Html File */
12359: /* FILE *ficgp;*/ /*Gnuplot File */
12360: struct stat info;
1.191 brouard 12361: double agedeb=0.;
1.194 brouard 12362:
12363: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 12364: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 12365:
1.165 brouard 12366: double fret;
1.191 brouard 12367: double dum=0.; /* Dummy variable */
1.136 brouard 12368: double ***p3mat;
1.218 brouard 12369: /* double ***mobaverage; */
1.319 brouard 12370: double wald;
1.164 brouard 12371:
12372: char line[MAXLINE];
1.197 brouard 12373: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
12374:
1.234 brouard 12375: char modeltemp[MAXLINE];
1.332 brouard 12376: char resultline[MAXLINE], resultlineori[MAXLINE];
1.230 brouard 12377:
1.136 brouard 12378: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 12379: char *tok, *val; /* pathtot */
1.334 brouard 12380: /* int firstobs=1, lastobs=10; /\* nobs = lastobs-firstobs declared globally ;*\/ */
1.195 brouard 12381: int c, h , cpt, c2;
1.191 brouard 12382: int jl=0;
12383: int i1, j1, jk, stepsize=0;
1.194 brouard 12384: int count=0;
12385:
1.164 brouard 12386: int *tab;
1.136 brouard 12387: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.296 brouard 12388: /* double anprojd, mprojd, jprojd; /\* For eventual projections *\/ */
12389: /* double anprojf, mprojf, jprojf; */
12390: /* double jintmean,mintmean,aintmean; */
12391: int prvforecast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
12392: int prvbackcast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
12393: double yrfproj= 10.0; /* Number of years of forward projections */
12394: double yrbproj= 10.0; /* Number of years of backward projections */
12395: int prevbcast=0; /* defined as global for mlikeli and mle, replacing backcast */
1.136 brouard 12396: int mobilav=0,popforecast=0;
1.191 brouard 12397: int hstepm=0, nhstepm=0;
1.136 brouard 12398: int agemortsup;
12399: float sumlpop=0.;
12400: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
12401: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
12402:
1.191 brouard 12403: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 12404: double ftolpl=FTOL;
12405: double **prlim;
1.217 brouard 12406: double **bprlim;
1.317 brouard 12407: double ***param; /* Matrix of parameters, param[i][j][k] param=ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel)
12408: state of origin, state of destination including death, for each covariate: constante, age, and V1 V2 etc. */
1.251 brouard 12409: double ***paramstart; /* Matrix of starting parameter values */
12410: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 12411: double **matcov; /* Matrix of covariance */
1.203 brouard 12412: double **hess; /* Hessian matrix */
1.136 brouard 12413: double ***delti3; /* Scale */
12414: double *delti; /* Scale */
12415: double ***eij, ***vareij;
12416: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 12417:
1.136 brouard 12418: double *epj, vepp;
1.164 brouard 12419:
1.273 brouard 12420: double dateprev1, dateprev2;
1.296 brouard 12421: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0, dateprojd=0, dateprojf=0;
12422: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0, datebackd=0, datebackf=0;
12423:
1.217 brouard 12424:
1.136 brouard 12425: double **ximort;
1.145 brouard 12426: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 12427: int *dcwave;
12428:
1.164 brouard 12429: char z[1]="c";
1.136 brouard 12430:
12431: /*char *strt;*/
12432: char strtend[80];
1.126 brouard 12433:
1.164 brouard 12434:
1.126 brouard 12435: /* setlocale (LC_ALL, ""); */
12436: /* bindtextdomain (PACKAGE, LOCALEDIR); */
12437: /* textdomain (PACKAGE); */
12438: /* setlocale (LC_CTYPE, ""); */
12439: /* setlocale (LC_MESSAGES, ""); */
12440:
12441: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 12442: rstart_time = time(NULL);
12443: /* (void) gettimeofday(&start_time,&tzp);*/
12444: start_time = *localtime(&rstart_time);
1.126 brouard 12445: curr_time=start_time;
1.157 brouard 12446: /*tml = *localtime(&start_time.tm_sec);*/
12447: /* strcpy(strstart,asctime(&tml)); */
12448: strcpy(strstart,asctime(&start_time));
1.126 brouard 12449:
12450: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 12451: /* tp.tm_sec = tp.tm_sec +86400; */
12452: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 12453: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
12454: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
12455: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 12456: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 12457: /* strt=asctime(&tmg); */
12458: /* printf("Time(after) =%s",strstart); */
12459: /* (void) time (&time_value);
12460: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
12461: * tm = *localtime(&time_value);
12462: * strstart=asctime(&tm);
12463: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
12464: */
12465:
12466: nberr=0; /* Number of errors and warnings */
12467: nbwarn=0;
1.184 brouard 12468: #ifdef WIN32
12469: _getcwd(pathcd, size);
12470: #else
1.126 brouard 12471: getcwd(pathcd, size);
1.184 brouard 12472: #endif
1.191 brouard 12473: syscompilerinfo(0);
1.196 brouard 12474: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 12475: if(argc <=1){
12476: printf("\nEnter the parameter file name: ");
1.205 brouard 12477: if(!fgets(pathr,FILENAMELENGTH,stdin)){
12478: printf("ERROR Empty parameter file name\n");
12479: goto end;
12480: }
1.126 brouard 12481: i=strlen(pathr);
12482: if(pathr[i-1]=='\n')
12483: pathr[i-1]='\0';
1.156 brouard 12484: i=strlen(pathr);
1.205 brouard 12485: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 12486: pathr[i-1]='\0';
1.205 brouard 12487: }
12488: i=strlen(pathr);
12489: if( i==0 ){
12490: printf("ERROR Empty parameter file name\n");
12491: goto end;
12492: }
12493: for (tok = pathr; tok != NULL; ){
1.126 brouard 12494: printf("Pathr |%s|\n",pathr);
12495: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
12496: printf("val= |%s| pathr=%s\n",val,pathr);
12497: strcpy (pathtot, val);
12498: if(pathr[0] == '\0') break; /* Dirty */
12499: }
12500: }
1.281 brouard 12501: else if (argc<=2){
12502: strcpy(pathtot,argv[1]);
12503: }
1.126 brouard 12504: else{
12505: strcpy(pathtot,argv[1]);
1.281 brouard 12506: strcpy(z,argv[2]);
12507: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 12508: }
12509: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
12510: /*cygwin_split_path(pathtot,path,optionfile);
12511: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
12512: /* cutv(path,optionfile,pathtot,'\\');*/
12513:
12514: /* Split argv[0], imach program to get pathimach */
12515: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
12516: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
12517: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
12518: /* strcpy(pathimach,argv[0]); */
12519: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
12520: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
12521: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 12522: #ifdef WIN32
12523: _chdir(path); /* Can be a relative path */
12524: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
12525: #else
1.126 brouard 12526: chdir(path); /* Can be a relative path */
1.184 brouard 12527: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
12528: #endif
12529: printf("Current directory %s!\n",pathcd);
1.126 brouard 12530: strcpy(command,"mkdir ");
12531: strcat(command,optionfilefiname);
12532: if((outcmd=system(command)) != 0){
1.169 brouard 12533: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 12534: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
12535: /* fclose(ficlog); */
12536: /* exit(1); */
12537: }
12538: /* if((imk=mkdir(optionfilefiname))<0){ */
12539: /* perror("mkdir"); */
12540: /* } */
12541:
12542: /*-------- arguments in the command line --------*/
12543:
1.186 brouard 12544: /* Main Log file */
1.126 brouard 12545: strcat(filelog, optionfilefiname);
12546: strcat(filelog,".log"); /* */
12547: if((ficlog=fopen(filelog,"w"))==NULL) {
12548: printf("Problem with logfile %s\n",filelog);
12549: goto end;
12550: }
12551: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 12552: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 12553: fprintf(ficlog,"\nEnter the parameter file name: \n");
12554: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
12555: path=%s \n\
12556: optionfile=%s\n\
12557: optionfilext=%s\n\
1.156 brouard 12558: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 12559:
1.197 brouard 12560: syscompilerinfo(1);
1.167 brouard 12561:
1.126 brouard 12562: printf("Local time (at start):%s",strstart);
12563: fprintf(ficlog,"Local time (at start): %s",strstart);
12564: fflush(ficlog);
12565: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 12566: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 12567:
12568: /* */
12569: strcpy(fileres,"r");
12570: strcat(fileres, optionfilefiname);
1.201 brouard 12571: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 12572: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 12573: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 12574:
1.186 brouard 12575: /* Main ---------arguments file --------*/
1.126 brouard 12576:
12577: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 12578: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
12579: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 12580: fflush(ficlog);
1.149 brouard 12581: /* goto end; */
12582: exit(70);
1.126 brouard 12583: }
12584:
12585: strcpy(filereso,"o");
1.201 brouard 12586: strcat(filereso,fileresu);
1.126 brouard 12587: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
12588: printf("Problem with Output resultfile: %s\n", filereso);
12589: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
12590: fflush(ficlog);
12591: goto end;
12592: }
1.278 brouard 12593: /*-------- Rewriting parameter file ----------*/
12594: strcpy(rfileres,"r"); /* "Rparameterfile */
12595: strcat(rfileres,optionfilefiname); /* Parameter file first name */
12596: strcat(rfileres,"."); /* */
12597: strcat(rfileres,optionfilext); /* Other files have txt extension */
12598: if((ficres =fopen(rfileres,"w"))==NULL) {
12599: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
12600: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
12601: fflush(ficlog);
12602: goto end;
12603: }
12604: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 12605:
1.278 brouard 12606:
1.126 brouard 12607: /* Reads comments: lines beginning with '#' */
12608: numlinepar=0;
1.277 brouard 12609: /* Is it a BOM UTF-8 Windows file? */
12610: /* First parameter line */
1.197 brouard 12611: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 12612: noffset=0;
12613: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
12614: {
12615: noffset=noffset+3;
12616: printf("# File is an UTF8 Bom.\n"); // 0xBF
12617: }
1.302 brouard 12618: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
12619: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
1.277 brouard 12620: {
12621: noffset=noffset+2;
12622: printf("# File is an UTF16BE BOM file\n");
12623: }
12624: else if( line[0] == 0 && line[1] == 0)
12625: {
12626: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
12627: noffset=noffset+4;
12628: printf("# File is an UTF16BE BOM file\n");
12629: }
12630: } else{
12631: ;/*printf(" Not a BOM file\n");*/
12632: }
12633:
1.197 brouard 12634: /* If line starts with a # it is a comment */
1.277 brouard 12635: if (line[noffset] == '#') {
1.197 brouard 12636: numlinepar++;
12637: fputs(line,stdout);
12638: fputs(line,ficparo);
1.278 brouard 12639: fputs(line,ficres);
1.197 brouard 12640: fputs(line,ficlog);
12641: continue;
12642: }else
12643: break;
12644: }
12645: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
12646: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
12647: if (num_filled != 5) {
12648: printf("Should be 5 parameters\n");
1.283 brouard 12649: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 12650: }
1.126 brouard 12651: numlinepar++;
1.197 brouard 12652: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 12653: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
12654: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
12655: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 12656: }
12657: /* Second parameter line */
12658: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 12659: /* while(fscanf(ficpar,"%[^\n]", line)) { */
12660: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 12661: if (line[0] == '#') {
12662: numlinepar++;
1.283 brouard 12663: printf("%s",line);
12664: fprintf(ficres,"%s",line);
12665: fprintf(ficparo,"%s",line);
12666: fprintf(ficlog,"%s",line);
1.197 brouard 12667: continue;
12668: }else
12669: break;
12670: }
1.223 brouard 12671: 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", \
12672: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
12673: if (num_filled != 11) {
12674: 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 12675: printf("but line=%s\n",line);
1.283 brouard 12676: 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");
12677: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 12678: }
1.286 brouard 12679: if( lastpass > maxwav){
12680: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
12681: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
12682: fflush(ficlog);
12683: goto end;
12684: }
12685: 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 12686: 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 12687: 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 12688: 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 12689: }
1.203 brouard 12690: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 12691: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 12692: /* Third parameter line */
12693: while(fgets(line, MAXLINE, ficpar)) {
12694: /* If line starts with a # it is a comment */
12695: if (line[0] == '#') {
12696: numlinepar++;
1.283 brouard 12697: printf("%s",line);
12698: fprintf(ficres,"%s",line);
12699: fprintf(ficparo,"%s",line);
12700: fprintf(ficlog,"%s",line);
1.197 brouard 12701: continue;
12702: }else
12703: break;
12704: }
1.201 brouard 12705: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.279 brouard 12706: if (num_filled != 1){
1.302 brouard 12707: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
12708: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
1.197 brouard 12709: model[0]='\0';
12710: goto end;
12711: }
12712: else{
12713: if (model[0]=='+'){
12714: for(i=1; i<=strlen(model);i++)
12715: modeltemp[i-1]=model[i];
1.201 brouard 12716: strcpy(model,modeltemp);
1.197 brouard 12717: }
12718: }
1.338 brouard 12719: /* printf(" model=1+age%s modeltemp= %s, model=1+age+%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 12720: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 12721: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
12722: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
12723: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 12724: }
12725: /* 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); */
12726: /* numlinepar=numlinepar+3; /\* In general *\/ */
12727: /* 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 12728: /* 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); */
12729: /* 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 12730: fflush(ficlog);
1.190 brouard 12731: /* if(model[0]=='#'|| model[0]== '\0'){ */
12732: if(model[0]=='#'){
1.279 brouard 12733: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
12734: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
12735: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 12736: if(mle != -1){
1.279 brouard 12737: 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 12738: exit(1);
12739: }
12740: }
1.126 brouard 12741: while((c=getc(ficpar))=='#' && c!= EOF){
12742: ungetc(c,ficpar);
12743: fgets(line, MAXLINE, ficpar);
12744: numlinepar++;
1.195 brouard 12745: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
12746: z[0]=line[1];
1.342 brouard 12747: }else if(line[1]=='d'){ /* For debugging individual values of covariates in ficresilk */
1.343 brouard 12748: debugILK=1;printf("DebugILK\n");
1.195 brouard 12749: }
12750: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 12751: fputs(line, stdout);
12752: //puts(line);
1.126 brouard 12753: fputs(line,ficparo);
12754: fputs(line,ficlog);
12755: }
12756: ungetc(c,ficpar);
12757:
12758:
1.290 brouard 12759: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
12760: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
12761: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
1.341 brouard 12762: /* if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /\**< Time varying covariate (dummy and quantitative)*\/ */
12763: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs); /**< Might be better */
1.136 brouard 12764: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
12765: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
12766: v1+v2*age+v2*v3 makes cptcovn = 3
12767: */
12768: if (strlen(model)>1)
1.187 brouard 12769: 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 12770: else
1.187 brouard 12771: ncovmodel=2; /* Constant and age */
1.133 brouard 12772: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
12773: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 12774: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
12775: 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);
12776: 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);
12777: fflush(stdout);
12778: fclose (ficlog);
12779: goto end;
12780: }
1.126 brouard 12781: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
12782: delti=delti3[1][1];
12783: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
12784: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 12785: /* We could also provide initial parameters values giving by simple logistic regression
12786: * only one way, that is without matrix product. We will have nlstate maximizations */
12787: /* for(i=1;i<nlstate;i++){ */
12788: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
12789: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
12790: /* } */
1.126 brouard 12791: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 12792: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
12793: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 12794: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12795: fclose (ficparo);
12796: fclose (ficlog);
12797: goto end;
12798: exit(0);
1.220 brouard 12799: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 12800: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 12801: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
12802: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 12803: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
12804: matcov=matrix(1,npar,1,npar);
1.203 brouard 12805: hess=matrix(1,npar,1,npar);
1.220 brouard 12806: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 12807: /* Read guessed parameters */
1.126 brouard 12808: /* Reads comments: lines beginning with '#' */
12809: while((c=getc(ficpar))=='#' && c!= EOF){
12810: ungetc(c,ficpar);
12811: fgets(line, MAXLINE, ficpar);
12812: numlinepar++;
1.141 brouard 12813: fputs(line,stdout);
1.126 brouard 12814: fputs(line,ficparo);
12815: fputs(line,ficlog);
12816: }
12817: ungetc(c,ficpar);
12818:
12819: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 12820: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 12821: for(i=1; i <=nlstate; i++){
1.234 brouard 12822: j=0;
1.126 brouard 12823: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 12824: if(jj==i) continue;
12825: j++;
1.292 brouard 12826: while((c=getc(ficpar))=='#' && c!= EOF){
12827: ungetc(c,ficpar);
12828: fgets(line, MAXLINE, ficpar);
12829: numlinepar++;
12830: fputs(line,stdout);
12831: fputs(line,ficparo);
12832: fputs(line,ficlog);
12833: }
12834: ungetc(c,ficpar);
1.234 brouard 12835: fscanf(ficpar,"%1d%1d",&i1,&j1);
12836: if ((i1 != i) || (j1 != jj)){
12837: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 12838: It might be a problem of design; if ncovcol and the model are correct\n \
12839: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 12840: exit(1);
12841: }
12842: fprintf(ficparo,"%1d%1d",i1,j1);
12843: if(mle==1)
12844: printf("%1d%1d",i,jj);
12845: fprintf(ficlog,"%1d%1d",i,jj);
12846: for(k=1; k<=ncovmodel;k++){
12847: fscanf(ficpar," %lf",¶m[i][j][k]);
12848: if(mle==1){
12849: printf(" %lf",param[i][j][k]);
12850: fprintf(ficlog," %lf",param[i][j][k]);
12851: }
12852: else
12853: fprintf(ficlog," %lf",param[i][j][k]);
12854: fprintf(ficparo," %lf",param[i][j][k]);
12855: }
12856: fscanf(ficpar,"\n");
12857: numlinepar++;
12858: if(mle==1)
12859: printf("\n");
12860: fprintf(ficlog,"\n");
12861: fprintf(ficparo,"\n");
1.126 brouard 12862: }
12863: }
12864: fflush(ficlog);
1.234 brouard 12865:
1.251 brouard 12866: /* Reads parameters values */
1.126 brouard 12867: p=param[1][1];
1.251 brouard 12868: pstart=paramstart[1][1];
1.126 brouard 12869:
12870: /* Reads comments: lines beginning with '#' */
12871: while((c=getc(ficpar))=='#' && c!= EOF){
12872: ungetc(c,ficpar);
12873: fgets(line, MAXLINE, ficpar);
12874: numlinepar++;
1.141 brouard 12875: fputs(line,stdout);
1.126 brouard 12876: fputs(line,ficparo);
12877: fputs(line,ficlog);
12878: }
12879: ungetc(c,ficpar);
12880:
12881: for(i=1; i <=nlstate; i++){
12882: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 12883: fscanf(ficpar,"%1d%1d",&i1,&j1);
12884: if ( (i1-i) * (j1-j) != 0){
12885: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
12886: exit(1);
12887: }
12888: printf("%1d%1d",i,j);
12889: fprintf(ficparo,"%1d%1d",i1,j1);
12890: fprintf(ficlog,"%1d%1d",i1,j1);
12891: for(k=1; k<=ncovmodel;k++){
12892: fscanf(ficpar,"%le",&delti3[i][j][k]);
12893: printf(" %le",delti3[i][j][k]);
12894: fprintf(ficparo," %le",delti3[i][j][k]);
12895: fprintf(ficlog," %le",delti3[i][j][k]);
12896: }
12897: fscanf(ficpar,"\n");
12898: numlinepar++;
12899: printf("\n");
12900: fprintf(ficparo,"\n");
12901: fprintf(ficlog,"\n");
1.126 brouard 12902: }
12903: }
12904: fflush(ficlog);
1.234 brouard 12905:
1.145 brouard 12906: /* Reads covariance matrix */
1.126 brouard 12907: delti=delti3[1][1];
1.220 brouard 12908:
12909:
1.126 brouard 12910: /* 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 12911:
1.126 brouard 12912: /* Reads comments: lines beginning with '#' */
12913: while((c=getc(ficpar))=='#' && c!= EOF){
12914: ungetc(c,ficpar);
12915: fgets(line, MAXLINE, ficpar);
12916: numlinepar++;
1.141 brouard 12917: fputs(line,stdout);
1.126 brouard 12918: fputs(line,ficparo);
12919: fputs(line,ficlog);
12920: }
12921: ungetc(c,ficpar);
1.220 brouard 12922:
1.126 brouard 12923: matcov=matrix(1,npar,1,npar);
1.203 brouard 12924: hess=matrix(1,npar,1,npar);
1.131 brouard 12925: for(i=1; i <=npar; i++)
12926: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 12927:
1.194 brouard 12928: /* Scans npar lines */
1.126 brouard 12929: for(i=1; i <=npar; i++){
1.226 brouard 12930: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 12931: if(count != 3){
1.226 brouard 12932: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 12933: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
12934: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 12935: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 12936: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
12937: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 12938: exit(1);
1.220 brouard 12939: }else{
1.226 brouard 12940: if(mle==1)
12941: printf("%1d%1d%d",i1,j1,jk);
12942: }
12943: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
12944: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 12945: for(j=1; j <=i; j++){
1.226 brouard 12946: fscanf(ficpar," %le",&matcov[i][j]);
12947: if(mle==1){
12948: printf(" %.5le",matcov[i][j]);
12949: }
12950: fprintf(ficlog," %.5le",matcov[i][j]);
12951: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 12952: }
12953: fscanf(ficpar,"\n");
12954: numlinepar++;
12955: if(mle==1)
1.220 brouard 12956: printf("\n");
1.126 brouard 12957: fprintf(ficlog,"\n");
12958: fprintf(ficparo,"\n");
12959: }
1.194 brouard 12960: /* End of read covariance matrix npar lines */
1.126 brouard 12961: for(i=1; i <=npar; i++)
12962: for(j=i+1;j<=npar;j++)
1.226 brouard 12963: matcov[i][j]=matcov[j][i];
1.126 brouard 12964:
12965: if(mle==1)
12966: printf("\n");
12967: fprintf(ficlog,"\n");
12968:
12969: fflush(ficlog);
12970:
12971: } /* End of mle != -3 */
1.218 brouard 12972:
1.186 brouard 12973: /* Main data
12974: */
1.290 brouard 12975: nobs=lastobs-firstobs+1; /* was = lastobs;*/
12976: /* num=lvector(1,n); */
12977: /* moisnais=vector(1,n); */
12978: /* annais=vector(1,n); */
12979: /* moisdc=vector(1,n); */
12980: /* andc=vector(1,n); */
12981: /* weight=vector(1,n); */
12982: /* agedc=vector(1,n); */
12983: /* cod=ivector(1,n); */
12984: /* for(i=1;i<=n;i++){ */
12985: num=lvector(firstobs,lastobs);
12986: moisnais=vector(firstobs,lastobs);
12987: annais=vector(firstobs,lastobs);
12988: moisdc=vector(firstobs,lastobs);
12989: andc=vector(firstobs,lastobs);
12990: weight=vector(firstobs,lastobs);
12991: agedc=vector(firstobs,lastobs);
12992: cod=ivector(firstobs,lastobs);
12993: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 12994: num[i]=0;
12995: moisnais[i]=0;
12996: annais[i]=0;
12997: moisdc[i]=0;
12998: andc[i]=0;
12999: agedc[i]=0;
13000: cod[i]=0;
13001: weight[i]=1.0; /* Equal weights, 1 by default */
13002: }
1.290 brouard 13003: mint=matrix(1,maxwav,firstobs,lastobs);
13004: anint=matrix(1,maxwav,firstobs,lastobs);
1.325 brouard 13005: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
1.336 brouard 13006: /* printf("BUG ncovmodel=%d NCOVMAX=%d 2**ncovmodel=%f BUG\n",ncovmodel,NCOVMAX,pow(2,ncovmodel)); */
1.126 brouard 13007: tab=ivector(1,NCOVMAX);
1.144 brouard 13008: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 13009: 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 13010:
1.136 brouard 13011: /* Reads data from file datafile */
13012: if (readdata(datafile, firstobs, lastobs, &imx)==1)
13013: goto end;
13014:
13015: /* Calculation of the number of parameters from char model */
1.234 brouard 13016: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 13017: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
13018: k=3 V4 Tvar[k=3]= 4 (from V4)
13019: k=2 V1 Tvar[k=2]= 1 (from V1)
13020: k=1 Tvar[1]=2 (from V2)
1.234 brouard 13021: */
13022:
13023: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
13024: TvarsDind=ivector(1,NCOVMAX); /* */
1.330 brouard 13025: TnsdVar=ivector(1,NCOVMAX); /* */
1.335 brouard 13026: /* for(i=1; i<=NCOVMAX;i++) TnsdVar[i]=3; */
1.234 brouard 13027: TvarsD=ivector(1,NCOVMAX); /* */
13028: TvarsQind=ivector(1,NCOVMAX); /* */
13029: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 13030: TvarF=ivector(1,NCOVMAX); /* */
13031: TvarFind=ivector(1,NCOVMAX); /* */
13032: TvarV=ivector(1,NCOVMAX); /* */
13033: TvarVind=ivector(1,NCOVMAX); /* */
13034: TvarA=ivector(1,NCOVMAX); /* */
13035: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 13036: TvarFD=ivector(1,NCOVMAX); /* */
13037: TvarFDind=ivector(1,NCOVMAX); /* */
13038: TvarFQ=ivector(1,NCOVMAX); /* */
13039: TvarFQind=ivector(1,NCOVMAX); /* */
13040: TvarVD=ivector(1,NCOVMAX); /* */
13041: TvarVDind=ivector(1,NCOVMAX); /* */
13042: TvarVQ=ivector(1,NCOVMAX); /* */
13043: TvarVQind=ivector(1,NCOVMAX); /* */
1.339 brouard 13044: TvarVV=ivector(1,NCOVMAX); /* */
13045: TvarVVind=ivector(1,NCOVMAX); /* */
1.231 brouard 13046:
1.230 brouard 13047: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 13048: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 13049: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
13050: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
13051: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.137 brouard 13052: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
13053: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
13054: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
13055: */
13056: /* For model-covariate k tells which data-covariate to use but
13057: because this model-covariate is a construction we invent a new column
13058: ncovcol + k1
13059: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
13060: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 13061: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
13062: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 13063: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
13064: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 13065: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 13066: */
1.145 brouard 13067: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
13068: 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 13069: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
13070: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.330 brouard 13071: Tvardk=imatrix(1,NCOVMAX,1,2);
1.145 brouard 13072: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 13073: 4 covariates (3 plus signs)
13074: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
1.328 brouard 13075: */
13076: for(i=1;i<NCOVMAX;i++)
13077: Tage[i]=0;
1.230 brouard 13078: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 13079: * individual dummy, fixed or varying:
13080: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
13081: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 13082: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
13083: * V1 df, V2 qf, V3 & V4 dv, V5 qv
13084: * Tmodelind[1]@9={9,0,3,2,}*/
13085: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
13086: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 13087: * individual quantitative, fixed or varying:
13088: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
13089: * 3, 1, 0, 0, 0, 0, 0, 0},
13090: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 13091: /* Main decodemodel */
13092:
1.187 brouard 13093:
1.223 brouard 13094: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 13095: goto end;
13096:
1.137 brouard 13097: if((double)(lastobs-imx)/(double)imx > 1.10){
13098: nbwarn++;
13099: 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);
13100: 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);
13101: }
1.136 brouard 13102: /* if(mle==1){*/
1.137 brouard 13103: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
13104: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 13105: }
13106:
13107: /*-calculation of age at interview from date of interview and age at death -*/
13108: agev=matrix(1,maxwav,1,imx);
13109:
13110: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
13111: goto end;
13112:
1.126 brouard 13113:
1.136 brouard 13114: agegomp=(int)agemin;
1.290 brouard 13115: free_vector(moisnais,firstobs,lastobs);
13116: free_vector(annais,firstobs,lastobs);
1.126 brouard 13117: /* free_matrix(mint,1,maxwav,1,n);
13118: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 13119: /* free_vector(moisdc,1,n); */
13120: /* free_vector(andc,1,n); */
1.145 brouard 13121: /* */
13122:
1.126 brouard 13123: wav=ivector(1,imx);
1.214 brouard 13124: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
13125: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
13126: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
13127: 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.*/
13128: bh=imatrix(1,lastpass-firstpass+2,1,imx);
13129: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 13130:
13131: /* Concatenates waves */
1.214 brouard 13132: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
13133: Death is a valid wave (if date is known).
13134: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
13135: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
13136: and mw[mi+1][i]. dh depends on stepm.
13137: */
13138:
1.126 brouard 13139: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 13140: /* Concatenates waves */
1.145 brouard 13141:
1.290 brouard 13142: free_vector(moisdc,firstobs,lastobs);
13143: free_vector(andc,firstobs,lastobs);
1.215 brouard 13144:
1.126 brouard 13145: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
13146: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
13147: ncodemax[1]=1;
1.145 brouard 13148: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 13149: cptcoveff=0;
1.220 brouard 13150: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
1.335 brouard 13151: 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 13152: }
13153:
13154: ncovcombmax=pow(2,cptcoveff);
1.338 brouard 13155: invalidvarcomb=ivector(0, ncovcombmax);
13156: for(i=0;i<ncovcombmax;i++)
1.227 brouard 13157: invalidvarcomb[i]=0;
13158:
1.211 brouard 13159: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 13160: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 13161: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 13162:
1.200 brouard 13163: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 13164: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 13165: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 13166: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
13167: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
13168: * (currently 0 or 1) in the data.
13169: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
13170: * corresponding modality (h,j).
13171: */
13172:
1.145 brouard 13173: h=0;
13174: /*if (cptcovn > 0) */
1.126 brouard 13175: m=pow(2,cptcoveff);
13176:
1.144 brouard 13177: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 13178: * For k=4 covariates, h goes from 1 to m=2**k
13179: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
13180: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.329 brouard 13181: * h\k 1 2 3 4 * h-1\k-1 4 3 2 1
13182: *______________________________ *______________________
13183: * 1 i=1 1 i=1 1 i=1 1 i=1 1 * 0 0 0 0 0
13184: * 2 2 1 1 1 * 1 0 0 0 1
13185: * 3 i=2 1 2 1 1 * 2 0 0 1 0
13186: * 4 2 2 1 1 * 3 0 0 1 1
13187: * 5 i=3 1 i=2 1 2 1 * 4 0 1 0 0
13188: * 6 2 1 2 1 * 5 0 1 0 1
13189: * 7 i=4 1 2 2 1 * 6 0 1 1 0
13190: * 8 2 2 2 1 * 7 0 1 1 1
13191: * 9 i=5 1 i=3 1 i=2 1 2 * 8 1 0 0 0
13192: * 10 2 1 1 2 * 9 1 0 0 1
13193: * 11 i=6 1 2 1 2 * 10 1 0 1 0
13194: * 12 2 2 1 2 * 11 1 0 1 1
13195: * 13 i=7 1 i=4 1 2 2 * 12 1 1 0 0
13196: * 14 2 1 2 2 * 13 1 1 0 1
13197: * 15 i=8 1 2 2 2 * 14 1 1 1 0
13198: * 16 2 2 2 2 * 15 1 1 1 1
13199: */
1.212 brouard 13200: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 13201: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
13202: * and the value of each covariate?
13203: * V1=1, V2=1, V3=2, V4=1 ?
13204: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
13205: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
13206: * In order to get the real value in the data, we use nbcode
13207: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
13208: * We are keeping this crazy system in order to be able (in the future?)
13209: * to have more than 2 values (0 or 1) for a covariate.
13210: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
13211: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
13212: * bbbbbbbb
13213: * 76543210
13214: * h-1 00000101 (6-1=5)
1.219 brouard 13215: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 13216: * &
13217: * 1 00000001 (1)
1.219 brouard 13218: * 00000000 = 1 & ((h-1) >> (k-1))
13219: * +1= 00000001 =1
1.211 brouard 13220: *
13221: * h=14, k=3 => h'=h-1=13, k'=k-1=2
13222: * h' 1101 =2^3+2^2+0x2^1+2^0
13223: * >>k' 11
13224: * & 00000001
13225: * = 00000001
13226: * +1 = 00000010=2 = codtabm(14,3)
13227: * Reverse h=6 and m=16?
13228: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
13229: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
13230: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
13231: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
13232: * V3=decodtabm(14,3,2**4)=2
13233: * h'=13 1101 =2^3+2^2+0x2^1+2^0
13234: *(h-1) >> (j-1) 0011 =13 >> 2
13235: * &1 000000001
13236: * = 000000001
13237: * +1= 000000010 =2
13238: * 2211
13239: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
13240: * V3=2
1.220 brouard 13241: * codtabm and decodtabm are identical
1.211 brouard 13242: */
13243:
1.145 brouard 13244:
13245: free_ivector(Ndum,-1,NCOVMAX);
13246:
13247:
1.126 brouard 13248:
1.186 brouard 13249: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 13250: strcpy(optionfilegnuplot,optionfilefiname);
13251: if(mle==-3)
1.201 brouard 13252: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 13253: strcat(optionfilegnuplot,".gp");
13254:
13255: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
13256: printf("Problem with file %s",optionfilegnuplot);
13257: }
13258: else{
1.204 brouard 13259: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 13260: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 13261: //fprintf(ficgp,"set missing 'NaNq'\n");
13262: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 13263: }
13264: /* fclose(ficgp);*/
1.186 brouard 13265:
13266:
13267: /* Initialisation of --------- index.htm --------*/
1.126 brouard 13268:
13269: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
13270: if(mle==-3)
1.201 brouard 13271: strcat(optionfilehtm,"-MORT_");
1.126 brouard 13272: strcat(optionfilehtm,".htm");
13273: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 13274: printf("Problem with %s \n",optionfilehtm);
13275: exit(0);
1.126 brouard 13276: }
13277:
13278: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
13279: strcat(optionfilehtmcov,"-cov.htm");
13280: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
13281: printf("Problem with %s \n",optionfilehtmcov), exit(0);
13282: }
13283: else{
13284: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
13285: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 13286: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 13287: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
13288: }
13289:
1.335 brouard 13290: fprintf(fichtm,"<html><head>\n<meta charset=\"utf-8\"/><meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n\
13291: <title>IMaCh %s</title></head>\n\
13292: <body><font size=\"7\"><a href=http:/euroreves.ined.fr/imach>IMaCh for Interpolated Markov Chain</a> </font><br>\n\
13293: <font size=\"3\">Sponsored by Copyright (C) 2002-2015 <a href=http://www.ined.fr>INED</a>\
13294: -EUROREVES-Institut de longévité-2013-2022-Japan Society for the Promotion of Sciences 日本学術振興会 \
13295: (<a href=https://www.jsps.go.jp/english/e-grants/>Grant-in-Aid for Scientific Research 25293121</a>) - \
13296: <a href=https://software.intel.com/en-us>Intel Software 2015-2018</a></font><br> \n", optionfilehtm);
13297:
13298: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 13299: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 13300: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.337 brouard 13301: 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 13302: \n\
13303: <hr size=\"2\" color=\"#EC5E5E\">\
13304: <ul><li><h4>Parameter files</h4>\n\
13305: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
13306: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
13307: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
13308: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
13309: - Date and time at start: %s</ul>\n",\
1.335 brouard 13310: version,fullversion,optionfilehtm,optionfilehtm,title,datafile,datafile,firstpass,lastpass,stepm, weightopt, model, \
1.126 brouard 13311: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
13312: fileres,fileres,\
13313: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
13314: fflush(fichtm);
13315:
13316: strcpy(pathr,path);
13317: strcat(pathr,optionfilefiname);
1.184 brouard 13318: #ifdef WIN32
13319: _chdir(optionfilefiname); /* Move to directory named optionfile */
13320: #else
1.126 brouard 13321: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 13322: #endif
13323:
1.126 brouard 13324:
1.220 brouard 13325: /* Calculates basic frequencies. Computes observed prevalence at single age
13326: and for any valid combination of covariates
1.126 brouard 13327: and prints on file fileres'p'. */
1.251 brouard 13328: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 13329: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 13330:
13331: fprintf(fichtm,"\n");
1.286 brouard 13332: 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 13333: ftol, stepm);
13334: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
13335: ncurrv=1;
13336: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
13337: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
13338: ncurrv=i;
13339: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 13340: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 13341: ncurrv=i;
13342: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 13343: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 13344: ncurrv=i;
13345: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
13346: 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", \
13347: nlstate, ndeath, maxwav, mle, weightopt);
13348:
13349: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
13350: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
13351:
13352:
1.317 brouard 13353: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Number of (used) observations=%d <br>\n\
1.126 brouard 13354: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
13355: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 13356: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 13357: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 13358: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
13359: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
13360: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
13361: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 13362:
1.126 brouard 13363: /* For Powell, parameters are in a vector p[] starting at p[1]
13364: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
13365: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
13366:
13367: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 13368: /* For mortality only */
1.126 brouard 13369: if (mle==-3){
1.136 brouard 13370: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 13371: for(i=1;i<=NDIM;i++)
13372: for(j=1;j<=NDIM;j++)
13373: ximort[i][j]=0.;
1.186 brouard 13374: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 13375: cens=ivector(firstobs,lastobs);
13376: ageexmed=vector(firstobs,lastobs);
13377: agecens=vector(firstobs,lastobs);
13378: dcwave=ivector(firstobs,lastobs);
1.223 brouard 13379:
1.126 brouard 13380: for (i=1; i<=imx; i++){
13381: dcwave[i]=-1;
13382: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 13383: if (s[m][i]>nlstate) {
13384: dcwave[i]=m;
13385: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
13386: break;
13387: }
1.126 brouard 13388: }
1.226 brouard 13389:
1.126 brouard 13390: for (i=1; i<=imx; i++) {
13391: if (wav[i]>0){
1.226 brouard 13392: ageexmed[i]=agev[mw[1][i]][i];
13393: j=wav[i];
13394: agecens[i]=1.;
13395:
13396: if (ageexmed[i]> 1 && wav[i] > 0){
13397: agecens[i]=agev[mw[j][i]][i];
13398: cens[i]= 1;
13399: }else if (ageexmed[i]< 1)
13400: cens[i]= -1;
13401: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
13402: cens[i]=0 ;
1.126 brouard 13403: }
13404: else cens[i]=-1;
13405: }
13406:
13407: for (i=1;i<=NDIM;i++) {
13408: for (j=1;j<=NDIM;j++)
1.226 brouard 13409: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 13410: }
13411:
1.302 brouard 13412: p[1]=0.0268; p[NDIM]=0.083;
13413: /* printf("%lf %lf", p[1], p[2]); */
1.126 brouard 13414:
13415:
1.136 brouard 13416: #ifdef GSL
13417: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 13418: #else
1.126 brouard 13419: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 13420: #endif
1.201 brouard 13421: strcpy(filerespow,"POW-MORT_");
13422: strcat(filerespow,fileresu);
1.126 brouard 13423: if((ficrespow=fopen(filerespow,"w"))==NULL) {
13424: printf("Problem with resultfile: %s\n", filerespow);
13425: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
13426: }
1.136 brouard 13427: #ifdef GSL
13428: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 13429: #else
1.126 brouard 13430: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 13431: #endif
1.126 brouard 13432: /* for (i=1;i<=nlstate;i++)
13433: for(j=1;j<=nlstate+ndeath;j++)
13434: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
13435: */
13436: fprintf(ficrespow,"\n");
1.136 brouard 13437: #ifdef GSL
13438: /* gsl starts here */
13439: T = gsl_multimin_fminimizer_nmsimplex;
13440: gsl_multimin_fminimizer *sfm = NULL;
13441: gsl_vector *ss, *x;
13442: gsl_multimin_function minex_func;
13443:
13444: /* Initial vertex size vector */
13445: ss = gsl_vector_alloc (NDIM);
13446:
13447: if (ss == NULL){
13448: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
13449: }
13450: /* Set all step sizes to 1 */
13451: gsl_vector_set_all (ss, 0.001);
13452:
13453: /* Starting point */
1.126 brouard 13454:
1.136 brouard 13455: x = gsl_vector_alloc (NDIM);
13456:
13457: if (x == NULL){
13458: gsl_vector_free(ss);
13459: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
13460: }
13461:
13462: /* Initialize method and iterate */
13463: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 13464: /* gsl_vector_set(x, 0, 0.0268); */
13465: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 13466: gsl_vector_set(x, 0, p[1]);
13467: gsl_vector_set(x, 1, p[2]);
13468:
13469: minex_func.f = &gompertz_f;
13470: minex_func.n = NDIM;
13471: minex_func.params = (void *)&p; /* ??? */
13472:
13473: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
13474: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
13475:
13476: printf("Iterations beginning .....\n\n");
13477: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
13478:
13479: iteri=0;
13480: while (rval == GSL_CONTINUE){
13481: iteri++;
13482: status = gsl_multimin_fminimizer_iterate(sfm);
13483:
13484: if (status) printf("error: %s\n", gsl_strerror (status));
13485: fflush(0);
13486:
13487: if (status)
13488: break;
13489:
13490: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
13491: ssval = gsl_multimin_fminimizer_size (sfm);
13492:
13493: if (rval == GSL_SUCCESS)
13494: printf ("converged to a local maximum at\n");
13495:
13496: printf("%5d ", iteri);
13497: for (it = 0; it < NDIM; it++){
13498: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
13499: }
13500: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
13501: }
13502:
13503: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
13504:
13505: gsl_vector_free(x); /* initial values */
13506: gsl_vector_free(ss); /* inital step size */
13507: for (it=0; it<NDIM; it++){
13508: p[it+1]=gsl_vector_get(sfm->x,it);
13509: fprintf(ficrespow," %.12lf", p[it]);
13510: }
13511: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
13512: #endif
13513: #ifdef POWELL
13514: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
13515: #endif
1.126 brouard 13516: fclose(ficrespow);
13517:
1.203 brouard 13518: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 13519:
13520: for(i=1; i <=NDIM; i++)
13521: for(j=i+1;j<=NDIM;j++)
1.220 brouard 13522: matcov[i][j]=matcov[j][i];
1.126 brouard 13523:
13524: printf("\nCovariance matrix\n ");
1.203 brouard 13525: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 13526: for(i=1; i <=NDIM; i++) {
13527: for(j=1;j<=NDIM;j++){
1.220 brouard 13528: printf("%f ",matcov[i][j]);
13529: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 13530: }
1.203 brouard 13531: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 13532: }
13533:
13534: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 13535: for (i=1;i<=NDIM;i++) {
1.126 brouard 13536: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 13537: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
13538: }
1.302 brouard 13539: lsurv=vector(agegomp,AGESUP);
13540: lpop=vector(agegomp,AGESUP);
13541: tpop=vector(agegomp,AGESUP);
1.126 brouard 13542: lsurv[agegomp]=100000;
13543:
13544: for (k=agegomp;k<=AGESUP;k++) {
13545: agemortsup=k;
13546: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
13547: }
13548:
13549: for (k=agegomp;k<agemortsup;k++)
13550: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
13551:
13552: for (k=agegomp;k<agemortsup;k++){
13553: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
13554: sumlpop=sumlpop+lpop[k];
13555: }
13556:
13557: tpop[agegomp]=sumlpop;
13558: for (k=agegomp;k<(agemortsup-3);k++){
13559: /* tpop[k+1]=2;*/
13560: tpop[k+1]=tpop[k]-lpop[k];
13561: }
13562:
13563:
13564: printf("\nAge lx qx dx Lx Tx e(x)\n");
13565: for (k=agegomp;k<(agemortsup-2);k++)
13566: 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]);
13567:
13568:
13569: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 13570: ageminpar=50;
13571: agemaxpar=100;
1.194 brouard 13572: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
13573: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
13574: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
13575: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
13576: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
13577: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
13578: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 13579: }else{
13580: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
13581: 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 13582: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 13583: }
1.201 brouard 13584: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 13585: stepm, weightopt,\
13586: model,imx,p,matcov,agemortsup);
13587:
1.302 brouard 13588: free_vector(lsurv,agegomp,AGESUP);
13589: free_vector(lpop,agegomp,AGESUP);
13590: free_vector(tpop,agegomp,AGESUP);
1.220 brouard 13591: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 13592: free_ivector(dcwave,firstobs,lastobs);
13593: free_vector(agecens,firstobs,lastobs);
13594: free_vector(ageexmed,firstobs,lastobs);
13595: free_ivector(cens,firstobs,lastobs);
1.220 brouard 13596: #ifdef GSL
1.136 brouard 13597: #endif
1.186 brouard 13598: } /* Endof if mle==-3 mortality only */
1.205 brouard 13599: /* Standard */
13600: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
13601: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
13602: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 13603: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 13604: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
13605: for (k=1; k<=npar;k++)
13606: printf(" %d %8.5f",k,p[k]);
13607: printf("\n");
1.205 brouard 13608: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
13609: /* mlikeli uses func not funcone */
1.247 brouard 13610: /* for(i=1;i<nlstate;i++){ */
13611: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
13612: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
13613: /* } */
1.205 brouard 13614: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
13615: }
13616: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
13617: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
13618: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
13619: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
13620: }
13621: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 13622: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
13623: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
1.335 brouard 13624: /* exit(0); */
1.126 brouard 13625: for (k=1; k<=npar;k++)
13626: printf(" %d %8.5f",k,p[k]);
13627: printf("\n");
13628:
13629: /*--------- results files --------------*/
1.283 brouard 13630: /* 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 13631:
13632:
13633: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 13634: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); /* Printing model equation */
1.126 brouard 13635: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 13636:
13637: printf("#model= 1 + age ");
13638: fprintf(ficres,"#model= 1 + age ");
13639: fprintf(ficlog,"#model= 1 + age ");
13640: fprintf(fichtm,"\n<ul><li> model=1+age+%s\n \
13641: </ul>", model);
13642:
13643: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">\n");
13644: fprintf(fichtm, "<tr><th>Model=</th><th>1</th><th>+ age</th>");
13645: if(nagesqr==1){
13646: printf(" + age*age ");
13647: fprintf(ficres," + age*age ");
13648: fprintf(ficlog," + age*age ");
13649: fprintf(fichtm, "<th>+ age*age</th>");
13650: }
13651: for(j=1;j <=ncovmodel-2;j++){
13652: if(Typevar[j]==0) {
13653: printf(" + V%d ",Tvar[j]);
13654: fprintf(ficres," + V%d ",Tvar[j]);
13655: fprintf(ficlog," + V%d ",Tvar[j]);
13656: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
13657: }else if(Typevar[j]==1) {
13658: printf(" + V%d*age ",Tvar[j]);
13659: fprintf(ficres," + V%d*age ",Tvar[j]);
13660: fprintf(ficlog," + V%d*age ",Tvar[j]);
13661: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
13662: }else if(Typevar[j]==2) {
13663: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13664: fprintf(ficres," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13665: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13666: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13667: }
13668: }
13669: printf("\n");
13670: fprintf(ficres,"\n");
13671: fprintf(ficlog,"\n");
13672: fprintf(fichtm, "</tr>");
13673: fprintf(fichtm, "\n");
13674:
13675:
1.126 brouard 13676: for(i=1,jk=1; i <=nlstate; i++){
13677: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 13678: if (k != i) {
1.319 brouard 13679: fprintf(fichtm, "<tr>");
1.225 brouard 13680: printf("%d%d ",i,k);
13681: fprintf(ficlog,"%d%d ",i,k);
13682: fprintf(ficres,"%1d%1d ",i,k);
1.319 brouard 13683: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 13684: for(j=1; j <=ncovmodel; j++){
13685: printf("%12.7f ",p[jk]);
13686: fprintf(ficlog,"%12.7f ",p[jk]);
13687: fprintf(ficres,"%12.7f ",p[jk]);
1.319 brouard 13688: fprintf(fichtm, "<td>%12.7f</td>",p[jk]);
1.225 brouard 13689: jk++;
13690: }
13691: printf("\n");
13692: fprintf(ficlog,"\n");
13693: fprintf(ficres,"\n");
1.319 brouard 13694: fprintf(fichtm, "</tr>\n");
1.225 brouard 13695: }
1.126 brouard 13696: }
13697: }
1.319 brouard 13698: /* fprintf(fichtm,"</tr>\n"); */
13699: fprintf(fichtm,"</table>\n");
13700: fprintf(fichtm, "\n");
13701:
1.203 brouard 13702: if(mle != 0){
13703: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 13704: ftolhess=ftol; /* Usually correct */
1.203 brouard 13705: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
13706: 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");
13707: 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 13708: 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 13709: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">");
13710: fprintf(fichtm, "\n<tr><th>Model=</th><th>1</th><th>+ age</th>");
13711: if(nagesqr==1){
13712: printf(" + age*age ");
13713: fprintf(ficres," + age*age ");
13714: fprintf(ficlog," + age*age ");
13715: fprintf(fichtm, "<th>+ age*age</th>");
13716: }
13717: for(j=1;j <=ncovmodel-2;j++){
13718: if(Typevar[j]==0) {
13719: printf(" + V%d ",Tvar[j]);
13720: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
13721: }else if(Typevar[j]==1) {
13722: printf(" + V%d*age ",Tvar[j]);
13723: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
13724: }else if(Typevar[j]==2) {
13725: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13726: }
13727: }
13728: fprintf(fichtm, "</tr>\n");
13729:
1.203 brouard 13730: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 13731: for(k=1; k <=(nlstate+ndeath); k++){
13732: if (k != i) {
1.319 brouard 13733: fprintf(fichtm, "<tr valign=top>");
1.225 brouard 13734: printf("%d%d ",i,k);
13735: fprintf(ficlog,"%d%d ",i,k);
1.319 brouard 13736: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 13737: for(j=1; j <=ncovmodel; j++){
1.319 brouard 13738: wald=p[jk]/sqrt(matcov[jk][jk]);
1.324 brouard 13739: 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]));
13740: 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 13741: if(fabs(wald) > 1.96){
1.321 brouard 13742: fprintf(fichtm, "<td><b>%12.7f</b></br> (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
1.319 brouard 13743: }else{
13744: fprintf(fichtm, "<td>%12.7f (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
13745: }
1.324 brouard 13746: fprintf(fichtm,"W=%8.3f</br>",wald);
1.319 brouard 13747: 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 13748: jk++;
13749: }
13750: printf("\n");
13751: fprintf(ficlog,"\n");
1.319 brouard 13752: fprintf(fichtm, "</tr>\n");
1.225 brouard 13753: }
13754: }
1.193 brouard 13755: }
1.203 brouard 13756: } /* end of hesscov and Wald tests */
1.319 brouard 13757: fprintf(fichtm,"</table>\n");
1.225 brouard 13758:
1.203 brouard 13759: /* */
1.126 brouard 13760: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
13761: printf("# Scales (for hessian or gradient estimation)\n");
13762: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
13763: for(i=1,jk=1; i <=nlstate; i++){
13764: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 13765: if (j!=i) {
13766: fprintf(ficres,"%1d%1d",i,j);
13767: printf("%1d%1d",i,j);
13768: fprintf(ficlog,"%1d%1d",i,j);
13769: for(k=1; k<=ncovmodel;k++){
13770: printf(" %.5e",delti[jk]);
13771: fprintf(ficlog," %.5e",delti[jk]);
13772: fprintf(ficres," %.5e",delti[jk]);
13773: jk++;
13774: }
13775: printf("\n");
13776: fprintf(ficlog,"\n");
13777: fprintf(ficres,"\n");
13778: }
1.126 brouard 13779: }
13780: }
13781:
13782: fprintf(ficres,"# Covariance matrix \n# 121 Var(a12)\n# 122 Cov(b12,a12) Var(b12)\n# ...\n# 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n");
1.203 brouard 13783: if(mle >= 1) /* To big for the screen */
1.126 brouard 13784: 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");
13785: 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");
13786: /* # 121 Var(a12)\n\ */
13787: /* # 122 Cov(b12,a12) Var(b12)\n\ */
13788: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
13789: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
13790: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
13791: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
13792: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
13793: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
13794:
13795:
13796: /* Just to have a covariance matrix which will be more understandable
13797: even is we still don't want to manage dictionary of variables
13798: */
13799: for(itimes=1;itimes<=2;itimes++){
13800: jj=0;
13801: for(i=1; i <=nlstate; i++){
1.225 brouard 13802: for(j=1; j <=nlstate+ndeath; j++){
13803: if(j==i) continue;
13804: for(k=1; k<=ncovmodel;k++){
13805: jj++;
13806: ca[0]= k+'a'-1;ca[1]='\0';
13807: if(itimes==1){
13808: if(mle>=1)
13809: printf("#%1d%1d%d",i,j,k);
13810: fprintf(ficlog,"#%1d%1d%d",i,j,k);
13811: fprintf(ficres,"#%1d%1d%d",i,j,k);
13812: }else{
13813: if(mle>=1)
13814: printf("%1d%1d%d",i,j,k);
13815: fprintf(ficlog,"%1d%1d%d",i,j,k);
13816: fprintf(ficres,"%1d%1d%d",i,j,k);
13817: }
13818: ll=0;
13819: for(li=1;li <=nlstate; li++){
13820: for(lj=1;lj <=nlstate+ndeath; lj++){
13821: if(lj==li) continue;
13822: for(lk=1;lk<=ncovmodel;lk++){
13823: ll++;
13824: if(ll<=jj){
13825: cb[0]= lk +'a'-1;cb[1]='\0';
13826: if(ll<jj){
13827: if(itimes==1){
13828: if(mle>=1)
13829: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
13830: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
13831: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
13832: }else{
13833: if(mle>=1)
13834: printf(" %.5e",matcov[jj][ll]);
13835: fprintf(ficlog," %.5e",matcov[jj][ll]);
13836: fprintf(ficres," %.5e",matcov[jj][ll]);
13837: }
13838: }else{
13839: if(itimes==1){
13840: if(mle>=1)
13841: printf(" Var(%s%1d%1d)",ca,i,j);
13842: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
13843: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
13844: }else{
13845: if(mle>=1)
13846: printf(" %.7e",matcov[jj][ll]);
13847: fprintf(ficlog," %.7e",matcov[jj][ll]);
13848: fprintf(ficres," %.7e",matcov[jj][ll]);
13849: }
13850: }
13851: }
13852: } /* end lk */
13853: } /* end lj */
13854: } /* end li */
13855: if(mle>=1)
13856: printf("\n");
13857: fprintf(ficlog,"\n");
13858: fprintf(ficres,"\n");
13859: numlinepar++;
13860: } /* end k*/
13861: } /*end j */
1.126 brouard 13862: } /* end i */
13863: } /* end itimes */
13864:
13865: fflush(ficlog);
13866: fflush(ficres);
1.225 brouard 13867: while(fgets(line, MAXLINE, ficpar)) {
13868: /* If line starts with a # it is a comment */
13869: if (line[0] == '#') {
13870: numlinepar++;
13871: fputs(line,stdout);
13872: fputs(line,ficparo);
13873: fputs(line,ficlog);
1.299 brouard 13874: fputs(line,ficres);
1.225 brouard 13875: continue;
13876: }else
13877: break;
13878: }
13879:
1.209 brouard 13880: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
13881: /* ungetc(c,ficpar); */
13882: /* fgets(line, MAXLINE, ficpar); */
13883: /* fputs(line,stdout); */
13884: /* fputs(line,ficparo); */
13885: /* } */
13886: /* ungetc(c,ficpar); */
1.126 brouard 13887:
13888: estepm=0;
1.209 brouard 13889: 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 13890:
13891: if (num_filled != 6) {
13892: 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);
13893: 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);
13894: goto end;
13895: }
13896: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
13897: }
13898: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
13899: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
13900:
1.209 brouard 13901: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 13902: if (estepm==0 || estepm < stepm) estepm=stepm;
13903: if (fage <= 2) {
13904: bage = ageminpar;
13905: fage = agemaxpar;
13906: }
13907:
13908: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 13909: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
13910: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 13911:
1.186 brouard 13912: /* Other stuffs, more or less useful */
1.254 brouard 13913: while(fgets(line, MAXLINE, ficpar)) {
13914: /* If line starts with a # it is a comment */
13915: if (line[0] == '#') {
13916: numlinepar++;
13917: fputs(line,stdout);
13918: fputs(line,ficparo);
13919: fputs(line,ficlog);
1.299 brouard 13920: fputs(line,ficres);
1.254 brouard 13921: continue;
13922: }else
13923: break;
13924: }
13925:
13926: 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){
13927:
13928: if (num_filled != 7) {
13929: 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);
13930: 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);
13931: goto end;
13932: }
13933: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
13934: 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);
13935: 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);
13936: 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 13937: }
1.254 brouard 13938:
13939: while(fgets(line, MAXLINE, ficpar)) {
13940: /* If line starts with a # it is a comment */
13941: if (line[0] == '#') {
13942: numlinepar++;
13943: fputs(line,stdout);
13944: fputs(line,ficparo);
13945: fputs(line,ficlog);
1.299 brouard 13946: fputs(line,ficres);
1.254 brouard 13947: continue;
13948: }else
13949: break;
1.126 brouard 13950: }
13951:
13952:
13953: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
13954: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
13955:
1.254 brouard 13956: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
13957: if (num_filled != 1) {
13958: 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);
13959: 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);
13960: goto end;
13961: }
13962: printf("pop_based=%d\n",popbased);
13963: fprintf(ficlog,"pop_based=%d\n",popbased);
13964: fprintf(ficparo,"pop_based=%d\n",popbased);
13965: fprintf(ficres,"pop_based=%d\n",popbased);
13966: }
13967:
1.258 brouard 13968: /* Results */
1.332 brouard 13969: /* Value of covariate in each resultine will be compututed (if product) and sorted according to model rank */
13970: /* It is precov[] because we need the varying age in order to compute the real cov[] of the model equation */
13971: precov=matrix(1,MAXRESULTLINESPONE,1,NCOVMAX+1);
1.307 brouard 13972: endishere=0;
1.258 brouard 13973: nresult=0;
1.308 brouard 13974: parameterline=0;
1.258 brouard 13975: do{
13976: if(!fgets(line, MAXLINE, ficpar)){
13977: endishere=1;
1.308 brouard 13978: parameterline=15;
1.258 brouard 13979: }else if (line[0] == '#') {
13980: /* If line starts with a # it is a comment */
1.254 brouard 13981: numlinepar++;
13982: fputs(line,stdout);
13983: fputs(line,ficparo);
13984: fputs(line,ficlog);
1.299 brouard 13985: fputs(line,ficres);
1.254 brouard 13986: continue;
1.258 brouard 13987: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
13988: parameterline=11;
1.296 brouard 13989: else if(sscanf(line,"prevbackcast=%[^\n]\n",modeltemp))
1.258 brouard 13990: parameterline=12;
1.307 brouard 13991: else if(sscanf(line,"result:%[^\n]\n",modeltemp)){
1.258 brouard 13992: parameterline=13;
1.307 brouard 13993: }
1.258 brouard 13994: else{
13995: parameterline=14;
1.254 brouard 13996: }
1.308 brouard 13997: switch (parameterline){ /* =0 only if only comments */
1.258 brouard 13998: case 11:
1.296 brouard 13999: 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)){
14000: 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 14001: 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);
14002: 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);
14003: 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);
14004: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 14005: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
14006: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
1.296 brouard 14007: prvforecast = 1;
14008: }
14009: else if((num_filled=sscanf(line,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",&prevfcast,&yrfproj,&mobilavproj)) !=EOF){/* && (num_filled == 3))*/
1.313 brouard 14010: printf("prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
14011: fprintf(ficlog,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
14012: fprintf(ficres,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
1.296 brouard 14013: prvforecast = 2;
14014: }
14015: else {
14016: 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);
14017: 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);
14018: goto end;
1.258 brouard 14019: }
1.254 brouard 14020: break;
1.258 brouard 14021: case 12:
1.296 brouard 14022: 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)){
14023: 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);
14024: 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);
14025: 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);
14026: 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);
14027: /* day and month of back2 are not used but only year anback2.*/
1.273 brouard 14028: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
14029: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.296 brouard 14030: prvbackcast = 1;
14031: }
14032: else if((num_filled=sscanf(line,"prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",&prevbcast,&yrbproj,&mobilavproj)) ==3){/* && (num_filled == 3))*/
1.313 brouard 14033: printf("prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
14034: fprintf(ficlog,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
14035: fprintf(ficres,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
1.296 brouard 14036: prvbackcast = 2;
14037: }
14038: else {
14039: 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);
14040: 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);
14041: goto end;
1.258 brouard 14042: }
1.230 brouard 14043: break;
1.258 brouard 14044: case 13:
1.332 brouard 14045: num_filled=sscanf(line,"result:%[^\n]\n",resultlineori);
1.307 brouard 14046: nresult++; /* Sum of resultlines */
1.342 brouard 14047: /* printf("Result %d: result:%s\n",nresult, resultlineori); */
1.332 brouard 14048: /* removefirstspace(&resultlineori); */
14049:
14050: if(strstr(resultlineori,"v") !=0){
14051: printf("Error. 'v' must be in upper case 'V' result: %s ",resultlineori);
14052: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultlineori);fflush(ficlog);
14053: return 1;
14054: }
14055: trimbb(resultline, resultlineori); /* Suppressing double blank in the resultline */
1.342 brouard 14056: /* printf("Decoderesult resultline=\"%s\" resultlineori=\"%s\"\n", resultline, resultlineori); */
1.318 brouard 14057: if(nresult > MAXRESULTLINESPONE-1){
14058: 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);
14059: 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 14060: goto end;
14061: }
1.332 brouard 14062:
1.310 brouard 14063: if(!decoderesult(resultline, nresult)){ /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
1.314 brouard 14064: fprintf(ficparo,"result: %s\n",resultline);
14065: fprintf(ficres,"result: %s\n",resultline);
14066: fprintf(ficlog,"result: %s\n",resultline);
1.310 brouard 14067: } else
14068: goto end;
1.307 brouard 14069: break;
14070: case 14:
14071: printf("Error: Unknown command '%s'\n",line);
14072: fprintf(ficlog,"Error: Unknown command '%s'\n",line);
1.314 brouard 14073: if(line[0] == ' ' || line[0] == '\n'){
14074: printf("It should not be an empty line '%s'\n",line);
14075: fprintf(ficlog,"It should not be an empty line '%s'\n",line);
14076: }
1.307 brouard 14077: if(ncovmodel >=2 && nresult==0 ){
14078: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
14079: fprintf(ficlog,"ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 14080: }
1.307 brouard 14081: /* goto end; */
14082: break;
1.308 brouard 14083: case 15:
14084: printf("End of resultlines.\n");
14085: fprintf(ficlog,"End of resultlines.\n");
14086: break;
14087: default: /* parameterline =0 */
1.307 brouard 14088: nresult=1;
14089: decoderesult(".",nresult ); /* No covariate */
1.258 brouard 14090: } /* End switch parameterline */
14091: }while(endishere==0); /* End do */
1.126 brouard 14092:
1.230 brouard 14093: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 14094: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 14095:
14096: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 14097: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 14098: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 14099: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14100: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 14101: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 14102: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14103: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 14104: }else{
1.270 brouard 14105: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
1.296 brouard 14106: /* It seems that anprojd which is computed from the mean year at interview which is known yet because of freqsummary */
14107: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */ /* Done in freqsummary */
14108: if(prvforecast==1){
14109: dateprojd=(jproj1+12*mproj1+365*anproj1)/365;
14110: jprojd=jproj1;
14111: mprojd=mproj1;
14112: anprojd=anproj1;
14113: dateprojf=(jproj2+12*mproj2+365*anproj2)/365;
14114: jprojf=jproj2;
14115: mprojf=mproj2;
14116: anprojf=anproj2;
14117: } else if(prvforecast == 2){
14118: dateprojd=dateintmean;
14119: date2dmy(dateprojd,&jprojd, &mprojd, &anprojd);
14120: dateprojf=dateintmean+yrfproj;
14121: date2dmy(dateprojf,&jprojf, &mprojf, &anprojf);
14122: }
14123: if(prvbackcast==1){
14124: datebackd=(jback1+12*mback1+365*anback1)/365;
14125: jbackd=jback1;
14126: mbackd=mback1;
14127: anbackd=anback1;
14128: datebackf=(jback2+12*mback2+365*anback2)/365;
14129: jbackf=jback2;
14130: mbackf=mback2;
14131: anbackf=anback2;
14132: } else if(prvbackcast == 2){
14133: datebackd=dateintmean;
14134: date2dmy(datebackd,&jbackd, &mbackd, &anbackd);
14135: datebackf=dateintmean-yrbproj;
14136: date2dmy(datebackf,&jbackf, &mbackf, &anbackf);
14137: }
14138:
14139: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage);
1.220 brouard 14140: }
14141: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.296 brouard 14142: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,prevbcast, estepm, \
14143: jprev1,mprev1,anprev1,dateprev1, dateprojd, datebackd,jprev2,mprev2,anprev2,dateprev2,dateprojf, datebackf);
1.220 brouard 14144:
1.225 brouard 14145: /*------------ free_vector -------------*/
14146: /* chdir(path); */
1.220 brouard 14147:
1.215 brouard 14148: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
14149: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
14150: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
14151: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 14152: free_lvector(num,firstobs,lastobs);
14153: free_vector(agedc,firstobs,lastobs);
1.126 brouard 14154: /*free_matrix(covar,0,NCOVMAX,1,n);*/
14155: /*free_matrix(covar,1,NCOVMAX,1,n);*/
14156: fclose(ficparo);
14157: fclose(ficres);
1.220 brouard 14158:
14159:
1.186 brouard 14160: /* Other results (useful)*/
1.220 brouard 14161:
14162:
1.126 brouard 14163: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 14164: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
14165: prlim=matrix(1,nlstate,1,nlstate);
1.332 brouard 14166: /* Computes the prevalence limit for each combination k of the dummy covariates by calling prevalim(k) */
1.209 brouard 14167: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 14168: fclose(ficrespl);
14169:
14170: /*------------- h Pij x at various ages ------------*/
1.180 brouard 14171: /*#include "hpijx.h"*/
1.332 brouard 14172: /** 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?*/
14173: /* calls hpxij with combination k */
1.180 brouard 14174: hPijx(p, bage, fage);
1.145 brouard 14175: fclose(ficrespij);
1.227 brouard 14176:
1.220 brouard 14177: /* ncovcombmax= pow(2,cptcoveff); */
1.332 brouard 14178: /*-------------- Variance of one-step probabilities for a combination ij or for nres ?---*/
1.145 brouard 14179: k=1;
1.126 brouard 14180: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 14181:
1.269 brouard 14182: /* Prevalence for each covariate combination in probs[age][status][cov] */
14183: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
14184: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 14185: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 14186: for(k=1;k<=ncovcombmax;k++)
14187: probs[i][j][k]=0.;
1.269 brouard 14188: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
14189: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 14190: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 14191: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
14192: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 14193: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 14194: for(k=1;k<=ncovcombmax;k++)
14195: mobaverages[i][j][k]=0.;
1.219 brouard 14196: mobaverage=mobaverages;
14197: if (mobilav!=0) {
1.235 brouard 14198: printf("Movingaveraging observed prevalence\n");
1.258 brouard 14199: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 14200: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
14201: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
14202: printf(" Error in movingaverage mobilav=%d\n",mobilav);
14203: }
1.269 brouard 14204: } else if (mobilavproj !=0) {
1.235 brouard 14205: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 14206: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 14207: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
14208: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
14209: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
14210: }
1.269 brouard 14211: }else{
14212: printf("Internal error moving average\n");
14213: fflush(stdout);
14214: exit(1);
1.219 brouard 14215: }
14216: }/* end if moving average */
1.227 brouard 14217:
1.126 brouard 14218: /*---------- Forecasting ------------------*/
1.296 brouard 14219: if(prevfcast==1){
14220: /* /\* if(stepm ==1){*\/ */
14221: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
14222: /*This done previously after freqsummary.*/
14223: /* dateprojd=(jproj1+12*mproj1+365*anproj1)/365; */
14224: /* dateprojf=(jproj2+12*mproj2+365*anproj2)/365; */
14225:
14226: /* } else if (prvforecast==2){ */
14227: /* /\* if(stepm ==1){*\/ */
14228: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
14229: /* } */
14230: /*prevforecast(fileresu, dateintmean, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);*/
14231: prevforecast(fileresu,dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, p, cptcoveff);
1.126 brouard 14232: }
1.269 brouard 14233:
1.296 brouard 14234: /* Prevbcasting */
14235: if(prevbcast==1){
1.219 brouard 14236: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14237: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14238: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14239:
14240: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
14241:
14242: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 14243:
1.219 brouard 14244: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
14245: fclose(ficresplb);
14246:
1.222 brouard 14247: hBijx(p, bage, fage, mobaverage);
14248: fclose(ficrespijb);
1.219 brouard 14249:
1.296 brouard 14250: /* /\* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, *\/ */
14251: /* /\* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); *\/ */
14252: /* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, */
14253: /* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
14254: prevbackforecast(fileresu, mobaverage, dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2,
14255: mobilavproj, bage, fage, firstpass, lastpass, p, cptcoveff);
14256:
14257:
1.269 brouard 14258: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 14259:
14260:
1.269 brouard 14261: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 14262: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
14263: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
14264: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.296 brouard 14265: } /* end Prevbcasting */
1.268 brouard 14266:
1.186 brouard 14267:
14268: /* ------ Other prevalence ratios------------ */
1.126 brouard 14269:
1.215 brouard 14270: free_ivector(wav,1,imx);
14271: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
14272: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
14273: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 14274:
14275:
1.127 brouard 14276: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 14277:
1.201 brouard 14278: strcpy(filerese,"E_");
14279: strcat(filerese,fileresu);
1.126 brouard 14280: if((ficreseij=fopen(filerese,"w"))==NULL) {
14281: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
14282: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
14283: }
1.208 brouard 14284: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
14285: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 14286:
14287: pstamp(ficreseij);
1.219 brouard 14288:
1.235 brouard 14289: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
14290: if (cptcovn < 1){i1=1;}
14291:
14292: for(nres=1; nres <= nresult; nres++) /* For each resultline */
14293: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 14294: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 14295: continue;
1.219 brouard 14296: fprintf(ficreseij,"\n#****** ");
1.235 brouard 14297: printf("\n#****** ");
1.225 brouard 14298: for(j=1;j<=cptcoveff;j++) {
1.332 brouard 14299: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
14300: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.235 brouard 14301: }
14302: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.337 brouard 14303: printf(" V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]); /* TvarsQ[j] gives the name of the jth quantitative (fixed or time v) */
14304: fprintf(ficreseij,"V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]);
1.219 brouard 14305: }
14306: fprintf(ficreseij,"******\n");
1.235 brouard 14307: printf("******\n");
1.219 brouard 14308:
14309: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
14310: oldm=oldms;savm=savms;
1.330 brouard 14311: /* 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 14312: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 14313:
1.219 brouard 14314: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 14315: }
14316: fclose(ficreseij);
1.208 brouard 14317: printf("done evsij\n");fflush(stdout);
14318: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 14319:
1.218 brouard 14320:
1.227 brouard 14321: /*---------- State-specific expectancies and variances ------------*/
1.336 brouard 14322: /* Should be moved in a function */
1.201 brouard 14323: strcpy(filerest,"T_");
14324: strcat(filerest,fileresu);
1.127 brouard 14325: if((ficrest=fopen(filerest,"w"))==NULL) {
14326: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
14327: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
14328: }
1.208 brouard 14329: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
14330: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 14331: strcpy(fileresstde,"STDE_");
14332: strcat(fileresstde,fileresu);
1.126 brouard 14333: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 14334: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
14335: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 14336: }
1.227 brouard 14337: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
14338: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 14339:
1.201 brouard 14340: strcpy(filerescve,"CVE_");
14341: strcat(filerescve,fileresu);
1.126 brouard 14342: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 14343: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
14344: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 14345: }
1.227 brouard 14346: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
14347: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 14348:
1.201 brouard 14349: strcpy(fileresv,"V_");
14350: strcat(fileresv,fileresu);
1.126 brouard 14351: if((ficresvij=fopen(fileresv,"w"))==NULL) {
14352: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
14353: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
14354: }
1.227 brouard 14355: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
14356: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 14357:
1.235 brouard 14358: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
14359: if (cptcovn < 1){i1=1;}
14360:
1.334 brouard 14361: for(nres=1; nres <= nresult; nres++) /* For each resultline, find the combination and output results according to the values of dummies and then quanti. */
14362: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying. For each nres and each value at position k
14363: * we know Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline
14364: * Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline
14365: * and Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
14366: /* */
14367: 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 14368: continue;
1.321 brouard 14369: printf("\n# model %s \n#****** Result for:", model);
14370: fprintf(ficrest,"\n# model %s \n#****** Result for:", model);
14371: fprintf(ficlog,"\n# model %s \n#****** Result for:", model);
1.334 brouard 14372: /* It might not be a good idea to mix dummies and quantitative */
14373: /* 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 *\/ */
14374: 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 */
14375: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /\* Output by variables in the resultline *\/ */
14376: /* Tvaraff[j] is the name of the dummy variable in position j in the equation model:
14377: * Tvaraff[1]@9={4, 3, 0, 0, 0, 0, 0, 0, 0}, in model=V5+V4+V3+V4*V3+V5*age
14378: * (V5 is quanti) V4 and V3 are dummies
14379: * TnsdVar[4] is the position 1 and TnsdVar[3]=2 in codtabm(k,l)(V4 V3)=V4 V3
14380: * l=1 l=2
14381: * k=1 1 1 0 0
14382: * k=2 2 1 1 0
14383: * k=3 [1] [2] 0 1
14384: * k=4 2 2 1 1
14385: * If nres=1 result: V3=1 V4=0 then k=3 and outputs
14386: * If nres=2 result: V4=1 V3=0 then k=2 and outputs
14387: * nres=1 =>k=3 j=1 V4= nbcode[4][codtabm(3,1)=1)=0; j=2 V3= nbcode[3][codtabm(3,2)=2]=1
14388: * nres=2 =>k=2 j=1 V4= nbcode[4][codtabm(2,1)=2)=1; j=2 V3= nbcode[3][codtabm(2,2)=1]=0
14389: */
14390: /* Tvresult[nres][j] Name of the variable at position j in this resultline */
14391: /* Tresult[nres][j] Value of this variable at position j could be a float if quantitative */
14392: /* We give up with the combinations!! */
1.342 brouard 14393: /* if(debugILK) */
14394: /* 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 14395:
14396: 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 14397: /* 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] */
14398: 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 */
14399: 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 */
14400: 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 14401: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
14402: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
14403: }else{
14404: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
14405: }
14406: /* fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14407: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14408: }else if(Dummy[modelresult[nres][j]]==1){ /* Quanti variable */
14409: /* For each selected (single) quantitative value */
1.337 brouard 14410: printf(" V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
14411: fprintf(ficlog," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
14412: fprintf(ficrest," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
1.334 brouard 14413: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
14414: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
14415: }else{
14416: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
14417: }
14418: }else{
14419: 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 */
14420: 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 */
14421: exit(1);
14422: }
1.335 brouard 14423: } /* End loop for each variable in the resultline */
1.334 brouard 14424: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
14425: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /\* Wrong j is not in the equation model *\/ */
14426: /* fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
14427: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
14428: /* } */
1.208 brouard 14429: fprintf(ficrest,"******\n");
1.227 brouard 14430: fprintf(ficlog,"******\n");
14431: printf("******\n");
1.208 brouard 14432:
14433: fprintf(ficresstdeij,"\n#****** ");
14434: fprintf(ficrescveij,"\n#****** ");
1.337 brouard 14435: /* It could have been: for(j=1;j<=cptcoveff;j++) {printf("V=%d=%lg",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);} */
14436: /* But it won't be sorted and depends on how the resultline is ordered */
1.225 brouard 14437: for(j=1;j<=cptcoveff;j++) {
1.334 brouard 14438: fprintf(ficresstdeij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
14439: /* fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14440: /* fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
14441: }
14442: 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 14443: fprintf(ficresstdeij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
14444: fprintf(ficrescveij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
1.235 brouard 14445: }
1.208 brouard 14446: fprintf(ficresstdeij,"******\n");
14447: fprintf(ficrescveij,"******\n");
14448:
14449: fprintf(ficresvij,"\n#****** ");
1.238 brouard 14450: /* pstamp(ficresvij); */
1.225 brouard 14451: for(j=1;j<=cptcoveff;j++)
1.335 brouard 14452: fprintf(ficresvij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
14453: /* fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[TnsdVar[Tvaraff[j]]])]); */
1.235 brouard 14454: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.332 brouard 14455: /* fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); /\* To solve *\/ */
1.337 brouard 14456: fprintf(ficresvij," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /* Solved */
1.235 brouard 14457: }
1.208 brouard 14458: fprintf(ficresvij,"******\n");
14459:
14460: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
14461: oldm=oldms;savm=savms;
1.235 brouard 14462: printf(" cvevsij ");
14463: fprintf(ficlog, " cvevsij ");
14464: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 14465: printf(" end cvevsij \n ");
14466: fprintf(ficlog, " end cvevsij \n ");
14467:
14468: /*
14469: */
14470: /* goto endfree; */
14471:
14472: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
14473: pstamp(ficrest);
14474:
1.269 brouard 14475: epj=vector(1,nlstate+1);
1.208 brouard 14476: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 14477: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
14478: cptcod= 0; /* To be deleted */
14479: printf("varevsij vpopbased=%d \n",vpopbased);
14480: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 14481: 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 14482: 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 ");
14483: if(vpopbased==1)
14484: 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);
14485: else
1.288 brouard 14486: fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n");
1.335 brouard 14487: fprintf(ficrest,"# Age popbased mobilav e.. (std) "); /* Adding covariate values? */
1.227 brouard 14488: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
14489: fprintf(ficrest,"\n");
14490: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 14491: printf("Computing age specific forward period (stable) prevalences in each health state \n");
14492: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 14493: for(age=bage; age <=fage ;age++){
1.235 brouard 14494: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 14495: if (vpopbased==1) {
14496: if(mobilav ==0){
14497: for(i=1; i<=nlstate;i++)
14498: prlim[i][i]=probs[(int)age][i][k];
14499: }else{ /* mobilav */
14500: for(i=1; i<=nlstate;i++)
14501: prlim[i][i]=mobaverage[(int)age][i][k];
14502: }
14503: }
1.219 brouard 14504:
1.227 brouard 14505: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
14506: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
14507: /* printf(" age %4.0f ",age); */
14508: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
14509: for(i=1, epj[j]=0.;i <=nlstate;i++) {
14510: epj[j] += prlim[i][i]*eij[i][j][(int)age];
14511: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
14512: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
14513: }
14514: epj[nlstate+1] +=epj[j];
14515: }
14516: /* printf(" age %4.0f \n",age); */
1.219 brouard 14517:
1.227 brouard 14518: for(i=1, vepp=0.;i <=nlstate;i++)
14519: for(j=1;j <=nlstate;j++)
14520: vepp += vareij[i][j][(int)age];
14521: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
14522: for(j=1;j <=nlstate;j++){
14523: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
14524: }
14525: fprintf(ficrest,"\n");
14526: }
1.208 brouard 14527: } /* End vpopbased */
1.269 brouard 14528: free_vector(epj,1,nlstate+1);
1.208 brouard 14529: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
14530: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 14531: printf("done selection\n");fflush(stdout);
14532: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 14533:
1.335 brouard 14534: } /* End k selection or end covariate selection for nres */
1.227 brouard 14535:
14536: printf("done State-specific expectancies\n");fflush(stdout);
14537: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
14538:
1.335 brouard 14539: /* variance-covariance of forward period prevalence */
1.269 brouard 14540: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 14541:
1.227 brouard 14542:
1.290 brouard 14543: free_vector(weight,firstobs,lastobs);
1.330 brouard 14544: free_imatrix(Tvardk,1,NCOVMAX,1,2);
1.227 brouard 14545: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 14546: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
14547: free_matrix(anint,1,maxwav,firstobs,lastobs);
14548: free_matrix(mint,1,maxwav,firstobs,lastobs);
14549: free_ivector(cod,firstobs,lastobs);
1.227 brouard 14550: free_ivector(tab,1,NCOVMAX);
14551: fclose(ficresstdeij);
14552: fclose(ficrescveij);
14553: fclose(ficresvij);
14554: fclose(ficrest);
14555: fclose(ficpar);
14556:
14557:
1.126 brouard 14558: /*---------- End : free ----------------*/
1.219 brouard 14559: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 14560: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
14561: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 14562: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
14563: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 14564: } /* mle==-3 arrives here for freeing */
1.227 brouard 14565: /* endfree:*/
14566: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
14567: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
14568: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.341 brouard 14569: /* if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs); */
14570: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs);
1.290 brouard 14571: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
14572: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
14573: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 14574: free_matrix(matcov,1,npar,1,npar);
14575: free_matrix(hess,1,npar,1,npar);
14576: /*free_vector(delti,1,npar);*/
14577: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
14578: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 14579: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 14580: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
14581:
14582: free_ivector(ncodemax,1,NCOVMAX);
14583: free_ivector(ncodemaxwundef,1,NCOVMAX);
14584: free_ivector(Dummy,-1,NCOVMAX);
14585: free_ivector(Fixed,-1,NCOVMAX);
1.238 brouard 14586: free_ivector(DummyV,1,NCOVMAX);
14587: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 14588: free_ivector(Typevar,-1,NCOVMAX);
14589: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 14590: free_ivector(TvarsQ,1,NCOVMAX);
14591: free_ivector(TvarsQind,1,NCOVMAX);
14592: free_ivector(TvarsD,1,NCOVMAX);
1.330 brouard 14593: free_ivector(TnsdVar,1,NCOVMAX);
1.234 brouard 14594: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 14595: free_ivector(TvarFD,1,NCOVMAX);
14596: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 14597: free_ivector(TvarF,1,NCOVMAX);
14598: free_ivector(TvarFind,1,NCOVMAX);
14599: free_ivector(TvarV,1,NCOVMAX);
14600: free_ivector(TvarVind,1,NCOVMAX);
14601: free_ivector(TvarA,1,NCOVMAX);
14602: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 14603: free_ivector(TvarFQ,1,NCOVMAX);
14604: free_ivector(TvarFQind,1,NCOVMAX);
14605: free_ivector(TvarVD,1,NCOVMAX);
14606: free_ivector(TvarVDind,1,NCOVMAX);
14607: free_ivector(TvarVQ,1,NCOVMAX);
14608: free_ivector(TvarVQind,1,NCOVMAX);
1.339 brouard 14609: free_ivector(TvarVV,1,NCOVMAX);
14610: free_ivector(TvarVVind,1,NCOVMAX);
14611:
1.230 brouard 14612: free_ivector(Tvarsel,1,NCOVMAX);
14613: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 14614: free_ivector(Tposprod,1,NCOVMAX);
14615: free_ivector(Tprod,1,NCOVMAX);
14616: free_ivector(Tvaraff,1,NCOVMAX);
1.338 brouard 14617: free_ivector(invalidvarcomb,0,ncovcombmax);
1.227 brouard 14618: free_ivector(Tage,1,NCOVMAX);
14619: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 14620: free_ivector(TmodelInvind,1,NCOVMAX);
14621: free_ivector(TmodelInvQind,1,NCOVMAX);
1.332 brouard 14622:
14623: free_matrix(precov, 1,MAXRESULTLINESPONE,1,NCOVMAX+1); /* Could be elsewhere ?*/
14624:
1.227 brouard 14625: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
14626: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 14627: fflush(fichtm);
14628: fflush(ficgp);
14629:
1.227 brouard 14630:
1.126 brouard 14631: if((nberr >0) || (nbwarn>0)){
1.216 brouard 14632: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
14633: 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 14634: }else{
14635: printf("End of Imach\n");
14636: fprintf(ficlog,"End of Imach\n");
14637: }
14638: printf("See log file on %s\n",filelog);
14639: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 14640: /*(void) gettimeofday(&end_time,&tzp);*/
14641: rend_time = time(NULL);
14642: end_time = *localtime(&rend_time);
14643: /* tml = *localtime(&end_time.tm_sec); */
14644: strcpy(strtend,asctime(&end_time));
1.126 brouard 14645: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
14646: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 14647: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 14648:
1.157 brouard 14649: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
14650: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
14651: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 14652: /* printf("Total time was %d uSec.\n", total_usecs);*/
14653: /* if(fileappend(fichtm,optionfilehtm)){ */
14654: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
14655: fclose(fichtm);
14656: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
14657: fclose(fichtmcov);
14658: fclose(ficgp);
14659: fclose(ficlog);
14660: /*------ End -----------*/
1.227 brouard 14661:
1.281 brouard 14662:
14663: /* Executes gnuplot */
1.227 brouard 14664:
14665: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 14666: #ifdef WIN32
1.227 brouard 14667: if (_chdir(pathcd) != 0)
14668: printf("Can't move to directory %s!\n",path);
14669: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 14670: #else
1.227 brouard 14671: if(chdir(pathcd) != 0)
14672: printf("Can't move to directory %s!\n", path);
14673: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 14674: #endif
1.126 brouard 14675: printf("Current directory %s!\n",pathcd);
14676: /*strcat(plotcmd,CHARSEPARATOR);*/
14677: sprintf(plotcmd,"gnuplot");
1.157 brouard 14678: #ifdef _WIN32
1.126 brouard 14679: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
14680: #endif
14681: if(!stat(plotcmd,&info)){
1.158 brouard 14682: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 14683: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 14684: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 14685: }else
14686: strcpy(pplotcmd,plotcmd);
1.157 brouard 14687: #ifdef __unix
1.126 brouard 14688: strcpy(plotcmd,GNUPLOTPROGRAM);
14689: if(!stat(plotcmd,&info)){
1.158 brouard 14690: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 14691: }else
14692: strcpy(pplotcmd,plotcmd);
14693: #endif
14694: }else
14695: strcpy(pplotcmd,plotcmd);
14696:
14697: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 14698: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 brouard 14699: strcpy(pplotcmd,plotcmd);
1.227 brouard 14700:
1.126 brouard 14701: if((outcmd=system(plotcmd)) != 0){
1.292 brouard 14702: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 14703: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 14704: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 brouard 14705: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 14706: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 brouard 14707: strcpy(plotcmd,pplotcmd);
14708: }
1.126 brouard 14709: }
1.158 brouard 14710: printf(" Successful, please wait...");
1.126 brouard 14711: while (z[0] != 'q') {
14712: /* chdir(path); */
1.154 brouard 14713: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 14714: scanf("%s",z);
14715: /* if (z[0] == 'c') system("./imach"); */
14716: if (z[0] == 'e') {
1.158 brouard 14717: #ifdef __APPLE__
1.152 brouard 14718: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 14719: #elif __linux
14720: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 14721: #else
1.152 brouard 14722: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 14723: #endif
14724: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
14725: system(pplotcmd);
1.126 brouard 14726: }
14727: else if (z[0] == 'g') system(plotcmd);
14728: else if (z[0] == 'q') exit(0);
14729: }
1.227 brouard 14730: end:
1.126 brouard 14731: while (z[0] != 'q') {
1.195 brouard 14732: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 14733: scanf("%s",z);
14734: }
1.283 brouard 14735: printf("End\n");
1.282 brouard 14736: exit(0);
1.126 brouard 14737: }
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