Annotation of imach/src/imach.c, revision 1.351
1.351 ! brouard 1: /* $Id: imach.c,v 1.350 2023/04/24 11:38:06 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.351 ! brouard 4: Revision 1.350 2023/04/24 11:38:06 brouard
! 5: *** empty log message ***
! 6:
1.350 brouard 7: Revision 1.349 2023/01/31 09:19:37 brouard
8: Summary: Improvements in models with age*Vn*Vm
9:
1.348 brouard 10: Revision 1.347 2022/09/18 14:36:44 brouard
11: Summary: version 0.99r42
12:
1.347 brouard 13: Revision 1.346 2022/09/16 13:52:36 brouard
14: * src/imach.c (Module): 0.99r41 Was an error when product of timevarying and fixed. Using FixedV[of name] now. Thank you Feinuo
15:
1.346 brouard 16: Revision 1.345 2022/09/16 13:40:11 brouard
17: Summary: Version 0.99r41
18:
19: * imach.c (Module): 0.99r41 Was an error when product of timevarying and fixed. Using FixedV[of name] now. Thank you Feinuo
20:
1.345 brouard 21: Revision 1.344 2022/09/14 19:33:30 brouard
22: Summary: version 0.99r40
23:
24: * imach.c (Module): Fixing names of variables in T_ (thanks to Feinuo)
25:
1.344 brouard 26: Revision 1.343 2022/09/14 14:22:16 brouard
27: Summary: version 0.99r39
28:
29: * imach.c (Module): Version 0.99r39 with colored dummy covariates
30: (fixed or time varying), using new last columns of
31: ILK_parameter.txt file.
32:
1.343 brouard 33: Revision 1.342 2022/09/11 19:54:09 brouard
34: Summary: 0.99r38
35:
36: * imach.c (Module): Adding timevarying products of any kinds,
37: should work before shifting cotvar from ncovcol+nqv columns in
38: order to have a correspondance between the column of cotvar and
39: the id of column.
40: (Module): Some cleaning and adding covariates in ILK.txt
41:
1.342 brouard 42: Revision 1.341 2022/09/11 07:58:42 brouard
43: Summary: Version 0.99r38
44:
45: After adding change in cotvar.
46:
1.341 brouard 47: Revision 1.340 2022/09/11 07:53:11 brouard
48: Summary: Version imach 0.99r37
49:
50: * imach.c (Module): Adding timevarying products of any kinds,
51: should work before shifting cotvar from ncovcol+nqv columns in
52: order to have a correspondance between the column of cotvar and
53: the id of column.
54:
1.340 brouard 55: Revision 1.339 2022/09/09 17:55:22 brouard
56: Summary: version 0.99r37
57:
58: * imach.c (Module): Many improvements for fixing products of fixed
59: timevarying as well as fixed * fixed, and test with quantitative
60: covariate.
61:
1.339 brouard 62: Revision 1.338 2022/09/04 17:40:33 brouard
63: Summary: 0.99r36
64:
65: * imach.c (Module): Now the easy runs i.e. without result or
66: model=1+age only did not work. The defautl combination should be 1
67: and not 0 because everything hasn't been tranformed yet.
68:
1.338 brouard 69: Revision 1.337 2022/09/02 14:26:02 brouard
70: Summary: version 0.99r35
71:
72: * src/imach.c: Version 0.99r35 because it outputs same results with
73: 1+age+V1+V1*age for females and 1+age for females only
74: (education=1 noweight)
75:
1.337 brouard 76: Revision 1.336 2022/08/31 09:52:36 brouard
77: *** empty log message ***
78:
1.336 brouard 79: Revision 1.335 2022/08/31 08:23:16 brouard
80: Summary: improvements...
81:
1.335 brouard 82: Revision 1.334 2022/08/25 09:08:41 brouard
83: Summary: In progress for quantitative
84:
1.334 brouard 85: Revision 1.333 2022/08/21 09:10:30 brouard
86: * src/imach.c (Module): Version 0.99r33 A lot of changes in
87: reassigning covariates: my first idea was that people will always
88: use the first covariate V1 into the model but in fact they are
89: producing data with many covariates and can use an equation model
90: with some of the covariate; it means that in a model V2+V3 instead
91: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
92: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
93: the equation model is restricted to two variables only (V2, V3)
94: and the combination for V2 should be codtabm(k,1) instead of
95: (codtabm(k,2), and the code should be
96: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
97: made. All of these should be simplified once a day like we did in
98: hpxij() for example by using precov[nres] which is computed in
99: decoderesult for each nres of each resultline. Loop should be done
100: on the equation model globally by distinguishing only product with
101: age (which are changing with age) and no more on type of
102: covariates, single dummies, single covariates.
103:
1.333 brouard 104: Revision 1.332 2022/08/21 09:06:25 brouard
105: Summary: Version 0.99r33
106:
107: * src/imach.c (Module): Version 0.99r33 A lot of changes in
108: reassigning covariates: my first idea was that people will always
109: use the first covariate V1 into the model but in fact they are
110: producing data with many covariates and can use an equation model
111: with some of the covariate; it means that in a model V2+V3 instead
112: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
113: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
114: the equation model is restricted to two variables only (V2, V3)
115: and the combination for V2 should be codtabm(k,1) instead of
116: (codtabm(k,2), and the code should be
117: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
118: made. All of these should be simplified once a day like we did in
119: hpxij() for example by using precov[nres] which is computed in
120: decoderesult for each nres of each resultline. Loop should be done
121: on the equation model globally by distinguishing only product with
122: age (which are changing with age) and no more on type of
123: covariates, single dummies, single covariates.
124:
1.332 brouard 125: Revision 1.331 2022/08/07 05:40:09 brouard
126: *** empty log message ***
127:
1.331 brouard 128: Revision 1.330 2022/08/06 07:18:25 brouard
129: Summary: last 0.99r31
130:
131: * imach.c (Module): Version of imach using partly decoderesult to rebuild xpxij function
132:
1.330 brouard 133: Revision 1.329 2022/08/03 17:29:54 brouard
134: * imach.c (Module): Many errors in graphs fixed with Vn*age covariates.
135:
1.329 brouard 136: Revision 1.328 2022/07/27 17:40:48 brouard
137: Summary: valgrind bug fixed by initializing to zero DummyV as well as Tage
138:
1.328 brouard 139: Revision 1.327 2022/07/27 14:47:35 brouard
140: Summary: Still a problem for one-step probabilities in case of quantitative variables
141:
1.327 brouard 142: Revision 1.326 2022/07/26 17:33:55 brouard
143: Summary: some test with nres=1
144:
1.326 brouard 145: Revision 1.325 2022/07/25 14:27:23 brouard
146: Summary: r30
147:
148: * imach.c (Module): Error cptcovn instead of nsd in bmij (was
149: coredumped, revealed by Feiuno, thank you.
150:
1.325 brouard 151: Revision 1.324 2022/07/23 17:44:26 brouard
152: *** empty log message ***
153:
1.324 brouard 154: Revision 1.323 2022/07/22 12:30:08 brouard
155: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
156:
1.323 brouard 157: Revision 1.322 2022/07/22 12:27:48 brouard
158: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
159:
1.322 brouard 160: Revision 1.321 2022/07/22 12:04:24 brouard
161: Summary: r28
162:
163: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
164:
1.321 brouard 165: Revision 1.320 2022/06/02 05:10:11 brouard
166: *** empty log message ***
167:
1.320 brouard 168: Revision 1.319 2022/06/02 04:45:11 brouard
169: * imach.c (Module): Adding the Wald tests from the log to the main
170: htm for better display of the maximum likelihood estimators.
171:
1.319 brouard 172: Revision 1.318 2022/05/24 08:10:59 brouard
173: * imach.c (Module): Some attempts to find a bug of wrong estimates
174: of confidencce intervals with product in the equation modelC
175:
1.318 brouard 176: Revision 1.317 2022/05/15 15:06:23 brouard
177: * imach.c (Module): Some minor improvements
178:
1.317 brouard 179: Revision 1.316 2022/05/11 15:11:31 brouard
180: Summary: r27
181:
1.316 brouard 182: Revision 1.315 2022/05/11 15:06:32 brouard
183: *** empty log message ***
184:
1.315 brouard 185: Revision 1.314 2022/04/13 17:43:09 brouard
186: * imach.c (Module): Adding link to text data files
187:
1.314 brouard 188: Revision 1.313 2022/04/11 15:57:42 brouard
189: * imach.c (Module): Error in rewriting the 'r' file with yearsfproj or yearsbproj fixed
190:
1.313 brouard 191: Revision 1.312 2022/04/05 21:24:39 brouard
192: *** empty log message ***
193:
1.312 brouard 194: Revision 1.311 2022/04/05 21:03:51 brouard
195: Summary: Fixed quantitative covariates
196:
197: Fixed covariates (dummy or quantitative)
198: with missing values have never been allowed but are ERRORS and
199: program quits. Standard deviations of fixed covariates were
200: wrongly computed. Mean and standard deviations of time varying
201: covariates are still not computed.
202:
1.311 brouard 203: Revision 1.310 2022/03/17 08:45:53 brouard
204: Summary: 99r25
205:
206: Improving detection of errors: result lines should be compatible with
207: the model.
208:
1.310 brouard 209: Revision 1.309 2021/05/20 12:39:14 brouard
210: Summary: Version 0.99r24
211:
1.309 brouard 212: Revision 1.308 2021/03/31 13:11:57 brouard
213: Summary: Version 0.99r23
214:
215:
216: * imach.c (Module): Still bugs in the result loop. Thank to Holly Benett
217:
1.308 brouard 218: Revision 1.307 2021/03/08 18:11:32 brouard
219: Summary: 0.99r22 fixed bug on result:
220:
1.307 brouard 221: Revision 1.306 2021/02/20 15:44:02 brouard
222: Summary: Version 0.99r21
223:
224: * imach.c (Module): Fix bug on quitting after result lines!
225: (Module): Version 0.99r21
226:
1.306 brouard 227: Revision 1.305 2021/02/20 15:28:30 brouard
228: * imach.c (Module): Fix bug on quitting after result lines!
229:
1.305 brouard 230: Revision 1.304 2021/02/12 11:34:20 brouard
231: * imach.c (Module): The use of a Windows BOM (huge) file is now an error
232:
1.304 brouard 233: Revision 1.303 2021/02/11 19:50:15 brouard
234: * (Module): imach.c Someone entered 'results:' instead of 'result:'. Now it is an error which is printed.
235:
1.303 brouard 236: Revision 1.302 2020/02/22 21:00:05 brouard
237: * (Module): imach.c Update mle=-3 (for computing Life expectancy
238: and life table from the data without any state)
239:
1.302 brouard 240: Revision 1.301 2019/06/04 13:51:20 brouard
241: Summary: Error in 'r'parameter file backcast yearsbproj instead of yearsfproj
242:
1.301 brouard 243: Revision 1.300 2019/05/22 19:09:45 brouard
244: Summary: version 0.99r19 of May 2019
245:
1.300 brouard 246: Revision 1.299 2019/05/22 18:37:08 brouard
247: Summary: Cleaned 0.99r19
248:
1.299 brouard 249: Revision 1.298 2019/05/22 18:19:56 brouard
250: *** empty log message ***
251:
1.298 brouard 252: Revision 1.297 2019/05/22 17:56:10 brouard
253: Summary: Fix bug by moving date2dmy and nhstepm which gaefin=-1
254:
1.297 brouard 255: Revision 1.296 2019/05/20 13:03:18 brouard
256: Summary: Projection syntax simplified
257:
258:
259: We can now start projections, forward or backward, from the mean date
260: of inteviews up to or down to a number of years of projection:
261: prevforecast=1 yearsfproj=15.3 mobil_average=0
262: or
263: prevforecast=1 starting-proj-date=1/1/2007 final-proj-date=12/31/2017 mobil_average=0
264: or
265: prevbackcast=1 yearsbproj=12.3 mobil_average=1
266: or
267: prevbackcast=1 starting-back-date=1/10/1999 final-back-date=1/1/1985 mobil_average=1
268:
1.296 brouard 269: Revision 1.295 2019/05/18 09:52:50 brouard
270: Summary: doxygen tex bug
271:
1.295 brouard 272: Revision 1.294 2019/05/16 14:54:33 brouard
273: Summary: There was some wrong lines added
274:
1.294 brouard 275: Revision 1.293 2019/05/09 15:17:34 brouard
276: *** empty log message ***
277:
1.293 brouard 278: Revision 1.292 2019/05/09 14:17:20 brouard
279: Summary: Some updates
280:
1.292 brouard 281: Revision 1.291 2019/05/09 13:44:18 brouard
282: Summary: Before ncovmax
283:
1.291 brouard 284: Revision 1.290 2019/05/09 13:39:37 brouard
285: Summary: 0.99r18 unlimited number of individuals
286:
287: 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.
288:
1.290 brouard 289: Revision 1.289 2018/12/13 09:16:26 brouard
290: Summary: Bug for young ages (<-30) will be in r17
291:
1.289 brouard 292: Revision 1.288 2018/05/02 20:58:27 brouard
293: Summary: Some bugs fixed
294:
1.288 brouard 295: Revision 1.287 2018/05/01 17:57:25 brouard
296: Summary: Bug fixed by providing frequencies only for non missing covariates
297:
1.287 brouard 298: Revision 1.286 2018/04/27 14:27:04 brouard
299: Summary: some minor bugs
300:
1.286 brouard 301: Revision 1.285 2018/04/21 21:02:16 brouard
302: Summary: Some bugs fixed, valgrind tested
303:
1.285 brouard 304: Revision 1.284 2018/04/20 05:22:13 brouard
305: Summary: Computing mean and stdeviation of fixed quantitative variables
306:
1.284 brouard 307: Revision 1.283 2018/04/19 14:49:16 brouard
308: Summary: Some minor bugs fixed
309:
1.283 brouard 310: Revision 1.282 2018/02/27 22:50:02 brouard
311: *** empty log message ***
312:
1.282 brouard 313: Revision 1.281 2018/02/27 19:25:23 brouard
314: Summary: Adding second argument for quitting
315:
1.281 brouard 316: Revision 1.280 2018/02/21 07:58:13 brouard
317: Summary: 0.99r15
318:
319: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
320:
1.280 brouard 321: Revision 1.279 2017/07/20 13:35:01 brouard
322: Summary: temporary working
323:
1.279 brouard 324: Revision 1.278 2017/07/19 14:09:02 brouard
325: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
326:
1.278 brouard 327: Revision 1.277 2017/07/17 08:53:49 brouard
328: Summary: BOM files can be read now
329:
1.277 brouard 330: Revision 1.276 2017/06/30 15:48:31 brouard
331: Summary: Graphs improvements
332:
1.276 brouard 333: Revision 1.275 2017/06/30 13:39:33 brouard
334: Summary: Saito's color
335:
1.275 brouard 336: Revision 1.274 2017/06/29 09:47:08 brouard
337: Summary: Version 0.99r14
338:
1.274 brouard 339: Revision 1.273 2017/06/27 11:06:02 brouard
340: Summary: More documentation on projections
341:
1.273 brouard 342: Revision 1.272 2017/06/27 10:22:40 brouard
343: Summary: Color of backprojection changed from 6 to 5(yellow)
344:
1.272 brouard 345: Revision 1.271 2017/06/27 10:17:50 brouard
346: Summary: Some bug with rint
347:
1.271 brouard 348: Revision 1.270 2017/05/24 05:45:29 brouard
349: *** empty log message ***
350:
1.270 brouard 351: Revision 1.269 2017/05/23 08:39:25 brouard
352: Summary: Code into subroutine, cleanings
353:
1.269 brouard 354: Revision 1.268 2017/05/18 20:09:32 brouard
355: Summary: backprojection and confidence intervals of backprevalence
356:
1.268 brouard 357: Revision 1.267 2017/05/13 10:25:05 brouard
358: Summary: temporary save for backprojection
359:
1.267 brouard 360: Revision 1.266 2017/05/13 07:26:12 brouard
361: Summary: Version 0.99r13 (improvements and bugs fixed)
362:
1.266 brouard 363: Revision 1.265 2017/04/26 16:22:11 brouard
364: Summary: imach 0.99r13 Some bugs fixed
365:
1.265 brouard 366: Revision 1.264 2017/04/26 06:01:29 brouard
367: Summary: Labels in graphs
368:
1.264 brouard 369: Revision 1.263 2017/04/24 15:23:15 brouard
370: Summary: to save
371:
1.263 brouard 372: Revision 1.262 2017/04/18 16:48:12 brouard
373: *** empty log message ***
374:
1.262 brouard 375: Revision 1.261 2017/04/05 10:14:09 brouard
376: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
377:
1.261 brouard 378: Revision 1.260 2017/04/04 17:46:59 brouard
379: Summary: Gnuplot indexations fixed (humm)
380:
1.260 brouard 381: Revision 1.259 2017/04/04 13:01:16 brouard
382: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
383:
1.259 brouard 384: Revision 1.258 2017/04/03 10:17:47 brouard
385: Summary: Version 0.99r12
386:
387: Some cleanings, conformed with updated documentation.
388:
1.258 brouard 389: Revision 1.257 2017/03/29 16:53:30 brouard
390: Summary: Temp
391:
1.257 brouard 392: Revision 1.256 2017/03/27 05:50:23 brouard
393: Summary: Temporary
394:
1.256 brouard 395: Revision 1.255 2017/03/08 16:02:28 brouard
396: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
397:
1.255 brouard 398: Revision 1.254 2017/03/08 07:13:00 brouard
399: Summary: Fixing data parameter line
400:
1.254 brouard 401: Revision 1.253 2016/12/15 11:59:41 brouard
402: Summary: 0.99 in progress
403:
1.253 brouard 404: Revision 1.252 2016/09/15 21:15:37 brouard
405: *** empty log message ***
406:
1.252 brouard 407: Revision 1.251 2016/09/15 15:01:13 brouard
408: Summary: not working
409:
1.251 brouard 410: Revision 1.250 2016/09/08 16:07:27 brouard
411: Summary: continue
412:
1.250 brouard 413: Revision 1.249 2016/09/07 17:14:18 brouard
414: Summary: Starting values from frequencies
415:
1.249 brouard 416: Revision 1.248 2016/09/07 14:10:18 brouard
417: *** empty log message ***
418:
1.248 brouard 419: Revision 1.247 2016/09/02 11:11:21 brouard
420: *** empty log message ***
421:
1.247 brouard 422: Revision 1.246 2016/09/02 08:49:22 brouard
423: *** empty log message ***
424:
1.246 brouard 425: Revision 1.245 2016/09/02 07:25:01 brouard
426: *** empty log message ***
427:
1.245 brouard 428: Revision 1.244 2016/09/02 07:17:34 brouard
429: *** empty log message ***
430:
1.244 brouard 431: Revision 1.243 2016/09/02 06:45:35 brouard
432: *** empty log message ***
433:
1.243 brouard 434: Revision 1.242 2016/08/30 15:01:20 brouard
435: Summary: Fixing a lots
436:
1.242 brouard 437: Revision 1.241 2016/08/29 17:17:25 brouard
438: Summary: gnuplot problem in Back projection to fix
439:
1.241 brouard 440: Revision 1.240 2016/08/29 07:53:18 brouard
441: Summary: Better
442:
1.240 brouard 443: Revision 1.239 2016/08/26 15:51:03 brouard
444: Summary: Improvement in Powell output in order to copy and paste
445:
446: Author:
447:
1.239 brouard 448: Revision 1.238 2016/08/26 14:23:35 brouard
449: Summary: Starting tests of 0.99
450:
1.238 brouard 451: Revision 1.237 2016/08/26 09:20:19 brouard
452: Summary: to valgrind
453:
1.237 brouard 454: Revision 1.236 2016/08/25 10:50:18 brouard
455: *** empty log message ***
456:
1.236 brouard 457: Revision 1.235 2016/08/25 06:59:23 brouard
458: *** empty log message ***
459:
1.235 brouard 460: Revision 1.234 2016/08/23 16:51:20 brouard
461: *** empty log message ***
462:
1.234 brouard 463: Revision 1.233 2016/08/23 07:40:50 brouard
464: Summary: not working
465:
1.233 brouard 466: Revision 1.232 2016/08/22 14:20:21 brouard
467: Summary: not working
468:
1.232 brouard 469: Revision 1.231 2016/08/22 07:17:15 brouard
470: Summary: not working
471:
1.231 brouard 472: Revision 1.230 2016/08/22 06:55:53 brouard
473: Summary: Not working
474:
1.230 brouard 475: Revision 1.229 2016/07/23 09:45:53 brouard
476: Summary: Completing for func too
477:
1.229 brouard 478: Revision 1.228 2016/07/22 17:45:30 brouard
479: Summary: Fixing some arrays, still debugging
480:
1.227 brouard 481: Revision 1.226 2016/07/12 18:42:34 brouard
482: Summary: temp
483:
1.226 brouard 484: Revision 1.225 2016/07/12 08:40:03 brouard
485: Summary: saving but not running
486:
1.225 brouard 487: Revision 1.224 2016/07/01 13:16:01 brouard
488: Summary: Fixes
489:
1.224 brouard 490: Revision 1.223 2016/02/19 09:23:35 brouard
491: Summary: temporary
492:
1.223 brouard 493: Revision 1.222 2016/02/17 08:14:50 brouard
494: Summary: Probably last 0.98 stable version 0.98r6
495:
1.222 brouard 496: Revision 1.221 2016/02/15 23:35:36 brouard
497: Summary: minor bug
498:
1.220 brouard 499: Revision 1.219 2016/02/15 00:48:12 brouard
500: *** empty log message ***
501:
1.219 brouard 502: Revision 1.218 2016/02/12 11:29:23 brouard
503: Summary: 0.99 Back projections
504:
1.218 brouard 505: Revision 1.217 2015/12/23 17:18:31 brouard
506: Summary: Experimental backcast
507:
1.217 brouard 508: Revision 1.216 2015/12/18 17:32:11 brouard
509: Summary: 0.98r4 Warning and status=-2
510:
511: Version 0.98r4 is now:
512: - displaying an error when status is -1, date of interview unknown and date of death known;
513: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
514: Older changes concerning s=-2, dating from 2005 have been supersed.
515:
1.216 brouard 516: Revision 1.215 2015/12/16 08:52:24 brouard
517: Summary: 0.98r4 working
518:
1.215 brouard 519: Revision 1.214 2015/12/16 06:57:54 brouard
520: Summary: temporary not working
521:
1.214 brouard 522: Revision 1.213 2015/12/11 18:22:17 brouard
523: Summary: 0.98r4
524:
1.213 brouard 525: Revision 1.212 2015/11/21 12:47:24 brouard
526: Summary: minor typo
527:
1.212 brouard 528: Revision 1.211 2015/11/21 12:41:11 brouard
529: Summary: 0.98r3 with some graph of projected cross-sectional
530:
531: Author: Nicolas Brouard
532:
1.211 brouard 533: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 534: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 535: Summary: Adding ftolpl parameter
536: Author: N Brouard
537:
538: We had difficulties to get smoothed confidence intervals. It was due
539: to the period prevalence which wasn't computed accurately. The inner
540: parameter ftolpl is now an outer parameter of the .imach parameter
541: file after estepm. If ftolpl is small 1.e-4 and estepm too,
542: computation are long.
543:
1.209 brouard 544: Revision 1.208 2015/11/17 14:31:57 brouard
545: Summary: temporary
546:
1.208 brouard 547: Revision 1.207 2015/10/27 17:36:57 brouard
548: *** empty log message ***
549:
1.207 brouard 550: Revision 1.206 2015/10/24 07:14:11 brouard
551: *** empty log message ***
552:
1.206 brouard 553: Revision 1.205 2015/10/23 15:50:53 brouard
554: Summary: 0.98r3 some clarification for graphs on likelihood contributions
555:
1.205 brouard 556: Revision 1.204 2015/10/01 16:20:26 brouard
557: Summary: Some new graphs of contribution to likelihood
558:
1.204 brouard 559: Revision 1.203 2015/09/30 17:45:14 brouard
560: Summary: looking at better estimation of the hessian
561:
562: Also a better criteria for convergence to the period prevalence And
563: therefore adding the number of years needed to converge. (The
564: prevalence in any alive state shold sum to one
565:
1.203 brouard 566: Revision 1.202 2015/09/22 19:45:16 brouard
567: Summary: Adding some overall graph on contribution to likelihood. Might change
568:
1.202 brouard 569: Revision 1.201 2015/09/15 17:34:58 brouard
570: Summary: 0.98r0
571:
572: - Some new graphs like suvival functions
573: - Some bugs fixed like model=1+age+V2.
574:
1.201 brouard 575: Revision 1.200 2015/09/09 16:53:55 brouard
576: Summary: Big bug thanks to Flavia
577:
578: Even model=1+age+V2. did not work anymore
579:
1.200 brouard 580: Revision 1.199 2015/09/07 14:09:23 brouard
581: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
582:
1.199 brouard 583: Revision 1.198 2015/09/03 07:14:39 brouard
584: Summary: 0.98q5 Flavia
585:
1.198 brouard 586: Revision 1.197 2015/09/01 18:24:39 brouard
587: *** empty log message ***
588:
1.197 brouard 589: Revision 1.196 2015/08/18 23:17:52 brouard
590: Summary: 0.98q5
591:
1.196 brouard 592: Revision 1.195 2015/08/18 16:28:39 brouard
593: Summary: Adding a hack for testing purpose
594:
595: After reading the title, ftol and model lines, if the comment line has
596: a q, starting with #q, the answer at the end of the run is quit. It
597: permits to run test files in batch with ctest. The former workaround was
598: $ echo q | imach foo.imach
599:
1.195 brouard 600: Revision 1.194 2015/08/18 13:32:00 brouard
601: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
602:
1.194 brouard 603: Revision 1.193 2015/08/04 07:17:42 brouard
604: Summary: 0.98q4
605:
1.193 brouard 606: Revision 1.192 2015/07/16 16:49:02 brouard
607: Summary: Fixing some outputs
608:
1.192 brouard 609: Revision 1.191 2015/07/14 10:00:33 brouard
610: Summary: Some fixes
611:
1.191 brouard 612: Revision 1.190 2015/05/05 08:51:13 brouard
613: Summary: Adding digits in output parameters (7 digits instead of 6)
614:
615: Fix 1+age+.
616:
1.190 brouard 617: Revision 1.189 2015/04/30 14:45:16 brouard
618: Summary: 0.98q2
619:
1.189 brouard 620: Revision 1.188 2015/04/30 08:27:53 brouard
621: *** empty log message ***
622:
1.188 brouard 623: Revision 1.187 2015/04/29 09:11:15 brouard
624: *** empty log message ***
625:
1.187 brouard 626: Revision 1.186 2015/04/23 12:01:52 brouard
627: Summary: V1*age is working now, version 0.98q1
628:
629: Some codes had been disabled in order to simplify and Vn*age was
630: working in the optimization phase, ie, giving correct MLE parameters,
631: but, as usual, outputs were not correct and program core dumped.
632:
1.186 brouard 633: Revision 1.185 2015/03/11 13:26:42 brouard
634: Summary: Inclusion of compile and links command line for Intel Compiler
635:
1.185 brouard 636: Revision 1.184 2015/03/11 11:52:39 brouard
637: Summary: Back from Windows 8. Intel Compiler
638:
1.184 brouard 639: Revision 1.183 2015/03/10 20:34:32 brouard
640: Summary: 0.98q0, trying with directest, mnbrak fixed
641:
642: We use directest instead of original Powell test; probably no
643: incidence on the results, but better justifications;
644: We fixed Numerical Recipes mnbrak routine which was wrong and gave
645: wrong results.
646:
1.183 brouard 647: Revision 1.182 2015/02/12 08:19:57 brouard
648: Summary: Trying to keep directest which seems simpler and more general
649: Author: Nicolas Brouard
650:
1.182 brouard 651: Revision 1.181 2015/02/11 23:22:24 brouard
652: Summary: Comments on Powell added
653:
654: Author:
655:
1.181 brouard 656: Revision 1.180 2015/02/11 17:33:45 brouard
657: Summary: Finishing move from main to function (hpijx and prevalence_limit)
658:
1.180 brouard 659: Revision 1.179 2015/01/04 09:57:06 brouard
660: Summary: back to OS/X
661:
1.179 brouard 662: Revision 1.178 2015/01/04 09:35:48 brouard
663: *** empty log message ***
664:
1.178 brouard 665: Revision 1.177 2015/01/03 18:40:56 brouard
666: Summary: Still testing ilc32 on OSX
667:
1.177 brouard 668: Revision 1.176 2015/01/03 16:45:04 brouard
669: *** empty log message ***
670:
1.176 brouard 671: Revision 1.175 2015/01/03 16:33:42 brouard
672: *** empty log message ***
673:
1.175 brouard 674: Revision 1.174 2015/01/03 16:15:49 brouard
675: Summary: Still in cross-compilation
676:
1.174 brouard 677: Revision 1.173 2015/01/03 12:06:26 brouard
678: Summary: trying to detect cross-compilation
679:
1.173 brouard 680: Revision 1.172 2014/12/27 12:07:47 brouard
681: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
682:
1.172 brouard 683: Revision 1.171 2014/12/23 13:26:59 brouard
684: Summary: Back from Visual C
685:
686: Still problem with utsname.h on Windows
687:
1.171 brouard 688: Revision 1.170 2014/12/23 11:17:12 brouard
689: Summary: Cleaning some \%% back to %%
690:
691: The escape was mandatory for a specific compiler (which one?), but too many warnings.
692:
1.170 brouard 693: Revision 1.169 2014/12/22 23:08:31 brouard
694: Summary: 0.98p
695:
696: Outputs some informations on compiler used, OS etc. Testing on different platforms.
697:
1.169 brouard 698: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 699: Summary: update
1.169 brouard 700:
1.168 brouard 701: Revision 1.167 2014/12/22 13:50:56 brouard
702: Summary: Testing uname and compiler version and if compiled 32 or 64
703:
704: Testing on Linux 64
705:
1.167 brouard 706: Revision 1.166 2014/12/22 11:40:47 brouard
707: *** empty log message ***
708:
1.166 brouard 709: Revision 1.165 2014/12/16 11:20:36 brouard
710: Summary: After compiling on Visual C
711:
712: * imach.c (Module): Merging 1.61 to 1.162
713:
1.165 brouard 714: Revision 1.164 2014/12/16 10:52:11 brouard
715: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
716:
717: * imach.c (Module): Merging 1.61 to 1.162
718:
1.164 brouard 719: Revision 1.163 2014/12/16 10:30:11 brouard
720: * imach.c (Module): Merging 1.61 to 1.162
721:
1.163 brouard 722: Revision 1.162 2014/09/25 11:43:39 brouard
723: Summary: temporary backup 0.99!
724:
1.162 brouard 725: Revision 1.1 2014/09/16 11:06:58 brouard
726: Summary: With some code (wrong) for nlopt
727:
728: Author:
729:
730: Revision 1.161 2014/09/15 20:41:41 brouard
731: Summary: Problem with macro SQR on Intel compiler
732:
1.161 brouard 733: Revision 1.160 2014/09/02 09:24:05 brouard
734: *** empty log message ***
735:
1.160 brouard 736: Revision 1.159 2014/09/01 10:34:10 brouard
737: Summary: WIN32
738: Author: Brouard
739:
1.159 brouard 740: Revision 1.158 2014/08/27 17:11:51 brouard
741: *** empty log message ***
742:
1.158 brouard 743: Revision 1.157 2014/08/27 16:26:55 brouard
744: Summary: Preparing windows Visual studio version
745: Author: Brouard
746:
747: In order to compile on Visual studio, time.h is now correct and time_t
748: and tm struct should be used. difftime should be used but sometimes I
749: just make the differences in raw time format (time(&now).
750: Trying to suppress #ifdef LINUX
751: Add xdg-open for __linux in order to open default browser.
752:
1.157 brouard 753: Revision 1.156 2014/08/25 20:10:10 brouard
754: *** empty log message ***
755:
1.156 brouard 756: Revision 1.155 2014/08/25 18:32:34 brouard
757: Summary: New compile, minor changes
758: Author: Brouard
759:
1.155 brouard 760: Revision 1.154 2014/06/20 17:32:08 brouard
761: Summary: Outputs now all graphs of convergence to period prevalence
762:
1.154 brouard 763: Revision 1.153 2014/06/20 16:45:46 brouard
764: Summary: If 3 live state, convergence to period prevalence on same graph
765: Author: Brouard
766:
1.153 brouard 767: Revision 1.152 2014/06/18 17:54:09 brouard
768: Summary: open browser, use gnuplot on same dir than imach if not found in the path
769:
1.152 brouard 770: Revision 1.151 2014/06/18 16:43:30 brouard
771: *** empty log message ***
772:
1.151 brouard 773: Revision 1.150 2014/06/18 16:42:35 brouard
774: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
775: Author: brouard
776:
1.150 brouard 777: Revision 1.149 2014/06/18 15:51:14 brouard
778: Summary: Some fixes in parameter files errors
779: Author: Nicolas Brouard
780:
1.149 brouard 781: Revision 1.148 2014/06/17 17:38:48 brouard
782: Summary: Nothing new
783: Author: Brouard
784:
785: Just a new packaging for OS/X version 0.98nS
786:
1.148 brouard 787: Revision 1.147 2014/06/16 10:33:11 brouard
788: *** empty log message ***
789:
1.147 brouard 790: Revision 1.146 2014/06/16 10:20:28 brouard
791: Summary: Merge
792: Author: Brouard
793:
794: Merge, before building revised version.
795:
1.146 brouard 796: Revision 1.145 2014/06/10 21:23:15 brouard
797: Summary: Debugging with valgrind
798: Author: Nicolas Brouard
799:
800: Lot of changes in order to output the results with some covariates
801: After the Edimburgh REVES conference 2014, it seems mandatory to
802: improve the code.
803: No more memory valgrind error but a lot has to be done in order to
804: continue the work of splitting the code into subroutines.
805: Also, decodemodel has been improved. Tricode is still not
806: optimal. nbcode should be improved. Documentation has been added in
807: the source code.
808:
1.144 brouard 809: Revision 1.143 2014/01/26 09:45:38 brouard
810: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
811:
812: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
813: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
814:
1.143 brouard 815: Revision 1.142 2014/01/26 03:57:36 brouard
816: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
817:
818: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
819:
1.142 brouard 820: Revision 1.141 2014/01/26 02:42:01 brouard
821: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
822:
1.141 brouard 823: Revision 1.140 2011/09/02 10:37:54 brouard
824: Summary: times.h is ok with mingw32 now.
825:
1.140 brouard 826: Revision 1.139 2010/06/14 07:50:17 brouard
827: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
828: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
829:
1.139 brouard 830: Revision 1.138 2010/04/30 18:19:40 brouard
831: *** empty log message ***
832:
1.138 brouard 833: Revision 1.137 2010/04/29 18:11:38 brouard
834: (Module): Checking covariates for more complex models
835: than V1+V2. A lot of change to be done. Unstable.
836:
1.137 brouard 837: Revision 1.136 2010/04/26 20:30:53 brouard
838: (Module): merging some libgsl code. Fixing computation
839: of likelione (using inter/intrapolation if mle = 0) in order to
840: get same likelihood as if mle=1.
841: Some cleaning of code and comments added.
842:
1.136 brouard 843: Revision 1.135 2009/10/29 15:33:14 brouard
844: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
845:
1.135 brouard 846: Revision 1.134 2009/10/29 13:18:53 brouard
847: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
848:
1.134 brouard 849: Revision 1.133 2009/07/06 10:21:25 brouard
850: just nforces
851:
1.133 brouard 852: Revision 1.132 2009/07/06 08:22:05 brouard
853: Many tings
854:
1.132 brouard 855: Revision 1.131 2009/06/20 16:22:47 brouard
856: Some dimensions resccaled
857:
1.131 brouard 858: Revision 1.130 2009/05/26 06:44:34 brouard
859: (Module): Max Covariate is now set to 20 instead of 8. A
860: lot of cleaning with variables initialized to 0. Trying to make
861: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
862:
1.130 brouard 863: Revision 1.129 2007/08/31 13:49:27 lievre
864: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
865:
1.129 lievre 866: Revision 1.128 2006/06/30 13:02:05 brouard
867: (Module): Clarifications on computing e.j
868:
1.128 brouard 869: Revision 1.127 2006/04/28 18:11:50 brouard
870: (Module): Yes the sum of survivors was wrong since
871: imach-114 because nhstepm was no more computed in the age
872: loop. Now we define nhstepma in the age loop.
873: (Module): In order to speed up (in case of numerous covariates) we
874: compute health expectancies (without variances) in a first step
875: and then all the health expectancies with variances or standard
876: deviation (needs data from the Hessian matrices) which slows the
877: computation.
878: In the future we should be able to stop the program is only health
879: expectancies and graph are needed without standard deviations.
880:
1.127 brouard 881: Revision 1.126 2006/04/28 17:23:28 brouard
882: (Module): Yes the sum of survivors was wrong since
883: imach-114 because nhstepm was no more computed in the age
884: loop. Now we define nhstepma in the age loop.
885: Version 0.98h
886:
1.126 brouard 887: Revision 1.125 2006/04/04 15:20:31 lievre
888: Errors in calculation of health expectancies. Age was not initialized.
889: Forecasting file added.
890:
891: Revision 1.124 2006/03/22 17:13:53 lievre
892: Parameters are printed with %lf instead of %f (more numbers after the comma).
893: The log-likelihood is printed in the log file
894:
895: Revision 1.123 2006/03/20 10:52:43 brouard
896: * imach.c (Module): <title> changed, corresponds to .htm file
897: name. <head> headers where missing.
898:
899: * imach.c (Module): Weights can have a decimal point as for
900: English (a comma might work with a correct LC_NUMERIC environment,
901: otherwise the weight is truncated).
902: Modification of warning when the covariates values are not 0 or
903: 1.
904: Version 0.98g
905:
906: Revision 1.122 2006/03/20 09:45:41 brouard
907: (Module): Weights can have a decimal point as for
908: English (a comma might work with a correct LC_NUMERIC environment,
909: otherwise the weight is truncated).
910: Modification of warning when the covariates values are not 0 or
911: 1.
912: Version 0.98g
913:
914: Revision 1.121 2006/03/16 17:45:01 lievre
915: * imach.c (Module): Comments concerning covariates added
916:
917: * imach.c (Module): refinements in the computation of lli if
918: status=-2 in order to have more reliable computation if stepm is
919: not 1 month. Version 0.98f
920:
921: Revision 1.120 2006/03/16 15:10:38 lievre
922: (Module): refinements in the computation of lli if
923: status=-2 in order to have more reliable computation if stepm is
924: not 1 month. Version 0.98f
925:
926: Revision 1.119 2006/03/15 17:42:26 brouard
927: (Module): Bug if status = -2, the loglikelihood was
928: computed as likelihood omitting the logarithm. Version O.98e
929:
930: Revision 1.118 2006/03/14 18:20:07 brouard
931: (Module): varevsij Comments added explaining the second
932: table of variances if popbased=1 .
933: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
934: (Module): Function pstamp added
935: (Module): Version 0.98d
936:
937: Revision 1.117 2006/03/14 17:16:22 brouard
938: (Module): varevsij Comments added explaining the second
939: table of variances if popbased=1 .
940: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
941: (Module): Function pstamp added
942: (Module): Version 0.98d
943:
944: Revision 1.116 2006/03/06 10:29:27 brouard
945: (Module): Variance-covariance wrong links and
946: varian-covariance of ej. is needed (Saito).
947:
948: Revision 1.115 2006/02/27 12:17:45 brouard
949: (Module): One freematrix added in mlikeli! 0.98c
950:
951: Revision 1.114 2006/02/26 12:57:58 brouard
952: (Module): Some improvements in processing parameter
953: filename with strsep.
954:
955: Revision 1.113 2006/02/24 14:20:24 brouard
956: (Module): Memory leaks checks with valgrind and:
957: datafile was not closed, some imatrix were not freed and on matrix
958: allocation too.
959:
960: Revision 1.112 2006/01/30 09:55:26 brouard
961: (Module): Back to gnuplot.exe instead of wgnuplot.exe
962:
963: Revision 1.111 2006/01/25 20:38:18 brouard
964: (Module): Lots of cleaning and bugs added (Gompertz)
965: (Module): Comments can be added in data file. Missing date values
966: can be a simple dot '.'.
967:
968: Revision 1.110 2006/01/25 00:51:50 brouard
969: (Module): Lots of cleaning and bugs added (Gompertz)
970:
971: Revision 1.109 2006/01/24 19:37:15 brouard
972: (Module): Comments (lines starting with a #) are allowed in data.
973:
974: Revision 1.108 2006/01/19 18:05:42 lievre
975: Gnuplot problem appeared...
976: To be fixed
977:
978: Revision 1.107 2006/01/19 16:20:37 brouard
979: Test existence of gnuplot in imach path
980:
981: Revision 1.106 2006/01/19 13:24:36 brouard
982: Some cleaning and links added in html output
983:
984: Revision 1.105 2006/01/05 20:23:19 lievre
985: *** empty log message ***
986:
987: Revision 1.104 2005/09/30 16:11:43 lievre
988: (Module): sump fixed, loop imx fixed, and simplifications.
989: (Module): If the status is missing at the last wave but we know
990: that the person is alive, then we can code his/her status as -2
991: (instead of missing=-1 in earlier versions) and his/her
992: contributions to the likelihood is 1 - Prob of dying from last
993: health status (= 1-p13= p11+p12 in the easiest case of somebody in
994: the healthy state at last known wave). Version is 0.98
995:
996: Revision 1.103 2005/09/30 15:54:49 lievre
997: (Module): sump fixed, loop imx fixed, and simplifications.
998:
999: Revision 1.102 2004/09/15 17:31:30 brouard
1000: Add the possibility to read data file including tab characters.
1001:
1002: Revision 1.101 2004/09/15 10:38:38 brouard
1003: Fix on curr_time
1004:
1005: Revision 1.100 2004/07/12 18:29:06 brouard
1006: Add version for Mac OS X. Just define UNIX in Makefile
1007:
1008: Revision 1.99 2004/06/05 08:57:40 brouard
1009: *** empty log message ***
1010:
1011: Revision 1.98 2004/05/16 15:05:56 brouard
1012: New version 0.97 . First attempt to estimate force of mortality
1013: directly from the data i.e. without the need of knowing the health
1014: state at each age, but using a Gompertz model: log u =a + b*age .
1015: This is the basic analysis of mortality and should be done before any
1016: other analysis, in order to test if the mortality estimated from the
1017: cross-longitudinal survey is different from the mortality estimated
1018: from other sources like vital statistic data.
1019:
1020: The same imach parameter file can be used but the option for mle should be -3.
1021:
1.324 brouard 1022: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 1023: former routines in order to include the new code within the former code.
1024:
1025: The output is very simple: only an estimate of the intercept and of
1026: the slope with 95% confident intervals.
1027:
1028: Current limitations:
1029: A) Even if you enter covariates, i.e. with the
1030: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
1031: B) There is no computation of Life Expectancy nor Life Table.
1032:
1033: Revision 1.97 2004/02/20 13:25:42 lievre
1034: Version 0.96d. Population forecasting command line is (temporarily)
1035: suppressed.
1036:
1037: Revision 1.96 2003/07/15 15:38:55 brouard
1038: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
1039: rewritten within the same printf. Workaround: many printfs.
1040:
1041: Revision 1.95 2003/07/08 07:54:34 brouard
1042: * imach.c (Repository):
1043: (Repository): Using imachwizard code to output a more meaningful covariance
1044: matrix (cov(a12,c31) instead of numbers.
1045:
1046: Revision 1.94 2003/06/27 13:00:02 brouard
1047: Just cleaning
1048:
1049: Revision 1.93 2003/06/25 16:33:55 brouard
1050: (Module): On windows (cygwin) function asctime_r doesn't
1051: exist so I changed back to asctime which exists.
1052: (Module): Version 0.96b
1053:
1054: Revision 1.92 2003/06/25 16:30:45 brouard
1055: (Module): On windows (cygwin) function asctime_r doesn't
1056: exist so I changed back to asctime which exists.
1057:
1058: Revision 1.91 2003/06/25 15:30:29 brouard
1059: * imach.c (Repository): Duplicated warning errors corrected.
1060: (Repository): Elapsed time after each iteration is now output. It
1061: helps to forecast when convergence will be reached. Elapsed time
1062: is stamped in powell. We created a new html file for the graphs
1063: concerning matrix of covariance. It has extension -cov.htm.
1064:
1065: Revision 1.90 2003/06/24 12:34:15 brouard
1066: (Module): Some bugs corrected for windows. Also, when
1067: mle=-1 a template is output in file "or"mypar.txt with the design
1068: of the covariance matrix to be input.
1069:
1070: Revision 1.89 2003/06/24 12:30:52 brouard
1071: (Module): Some bugs corrected for windows. Also, when
1072: mle=-1 a template is output in file "or"mypar.txt with the design
1073: of the covariance matrix to be input.
1074:
1075: Revision 1.88 2003/06/23 17:54:56 brouard
1076: * 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.
1077:
1078: Revision 1.87 2003/06/18 12:26:01 brouard
1079: Version 0.96
1080:
1081: Revision 1.86 2003/06/17 20:04:08 brouard
1082: (Module): Change position of html and gnuplot routines and added
1083: routine fileappend.
1084:
1085: Revision 1.85 2003/06/17 13:12:43 brouard
1086: * imach.c (Repository): Check when date of death was earlier that
1087: current date of interview. It may happen when the death was just
1088: prior to the death. In this case, dh was negative and likelihood
1089: was wrong (infinity). We still send an "Error" but patch by
1090: assuming that the date of death was just one stepm after the
1091: interview.
1092: (Repository): Because some people have very long ID (first column)
1093: we changed int to long in num[] and we added a new lvector for
1094: memory allocation. But we also truncated to 8 characters (left
1095: truncation)
1096: (Repository): No more line truncation errors.
1097:
1098: Revision 1.84 2003/06/13 21:44:43 brouard
1099: * imach.c (Repository): Replace "freqsummary" at a correct
1100: place. It differs from routine "prevalence" which may be called
1101: many times. Probs is memory consuming and must be used with
1102: parcimony.
1103: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
1104:
1105: Revision 1.83 2003/06/10 13:39:11 lievre
1106: *** empty log message ***
1107:
1108: Revision 1.82 2003/06/05 15:57:20 brouard
1109: Add log in imach.c and fullversion number is now printed.
1110:
1111: */
1112: /*
1113: Interpolated Markov Chain
1114:
1115: Short summary of the programme:
1116:
1.227 brouard 1117: This program computes Healthy Life Expectancies or State-specific
1118: (if states aren't health statuses) Expectancies from
1119: cross-longitudinal data. Cross-longitudinal data consist in:
1120:
1121: -1- a first survey ("cross") where individuals from different ages
1122: are interviewed on their health status or degree of disability (in
1123: the case of a health survey which is our main interest)
1124:
1125: -2- at least a second wave of interviews ("longitudinal") which
1126: measure each change (if any) in individual health status. Health
1127: expectancies are computed from the time spent in each health state
1128: according to a model. More health states you consider, more time is
1129: necessary to reach the Maximum Likelihood of the parameters involved
1130: in the model. The simplest model is the multinomial logistic model
1131: where pij is the probability to be observed in state j at the second
1132: wave conditional to be observed in state i at the first
1133: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
1134: etc , where 'age' is age and 'sex' is a covariate. If you want to
1135: have a more complex model than "constant and age", you should modify
1136: the program where the markup *Covariates have to be included here
1137: again* invites you to do it. More covariates you add, slower the
1.126 brouard 1138: convergence.
1139:
1140: The advantage of this computer programme, compared to a simple
1141: multinomial logistic model, is clear when the delay between waves is not
1142: identical for each individual. Also, if a individual missed an
1143: intermediate interview, the information is lost, but taken into
1144: account using an interpolation or extrapolation.
1145:
1146: hPijx is the probability to be observed in state i at age x+h
1147: conditional to the observed state i at age x. The delay 'h' can be
1148: split into an exact number (nh*stepm) of unobserved intermediate
1149: states. This elementary transition (by month, quarter,
1150: semester or year) is modelled as a multinomial logistic. The hPx
1151: matrix is simply the matrix product of nh*stepm elementary matrices
1152: and the contribution of each individual to the likelihood is simply
1153: hPijx.
1154:
1155: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 1156: of the life expectancies. It also computes the period (stable) prevalence.
1157:
1158: Back prevalence and projections:
1.227 brouard 1159:
1160: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
1161: double agemaxpar, double ftolpl, int *ncvyearp, double
1162: dateprev1,double dateprev2, int firstpass, int lastpass, int
1163: mobilavproj)
1164:
1165: Computes the back prevalence limit for any combination of
1166: covariate values k at any age between ageminpar and agemaxpar and
1167: returns it in **bprlim. In the loops,
1168:
1169: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
1170: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
1171:
1172: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 1173: Computes for any combination of covariates k and any age between bage and fage
1174: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
1175: oldm=oldms;savm=savms;
1.227 brouard 1176:
1.267 brouard 1177: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 1178: Computes the transition matrix starting at age 'age' over
1179: 'nhstepm*hstepm*stepm' months (i.e. until
1180: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 1181: nhstepm*hstepm matrices.
1182:
1183: Returns p3mat[i][j][h] after calling
1184: p3mat[i][j][h]=matprod2(newm,
1185: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
1186: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
1187: oldm);
1.226 brouard 1188:
1189: Important routines
1190:
1191: - func (or funcone), computes logit (pij) distinguishing
1192: o fixed variables (single or product dummies or quantitative);
1193: o varying variables by:
1194: (1) wave (single, product dummies, quantitative),
1195: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
1196: % fixed dummy (treated) or quantitative (not done because time-consuming);
1197: % varying dummy (not done) or quantitative (not done);
1198: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
1199: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
1200: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
1.325 brouard 1201: o There are 2**cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
1.226 brouard 1202: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 1203:
1.226 brouard 1204:
1205:
1.324 brouard 1206: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
1207: Institut national d'études démographiques, Paris.
1.126 brouard 1208: This software have been partly granted by Euro-REVES, a concerted action
1209: from the European Union.
1210: It is copyrighted identically to a GNU software product, ie programme and
1211: software can be distributed freely for non commercial use. Latest version
1212: can be accessed at http://euroreves.ined.fr/imach .
1213:
1214: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
1215: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
1216:
1217: **********************************************************************/
1218: /*
1219: main
1220: read parameterfile
1221: read datafile
1222: concatwav
1223: freqsummary
1224: if (mle >= 1)
1225: mlikeli
1226: print results files
1227: if mle==1
1228: computes hessian
1229: read end of parameter file: agemin, agemax, bage, fage, estepm
1230: begin-prev-date,...
1231: open gnuplot file
1232: open html file
1.145 brouard 1233: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
1234: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
1235: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
1236: freexexit2 possible for memory heap.
1237:
1238: h Pij x | pij_nom ficrestpij
1239: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
1240: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
1241: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
1242:
1243: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
1244: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
1245: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
1246: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
1247: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
1248:
1.126 brouard 1249: forecasting if prevfcast==1 prevforecast call prevalence()
1250: health expectancies
1251: Variance-covariance of DFLE
1252: prevalence()
1253: movingaverage()
1254: varevsij()
1255: if popbased==1 varevsij(,popbased)
1256: total life expectancies
1257: Variance of period (stable) prevalence
1258: end
1259: */
1260:
1.187 brouard 1261: /* #define DEBUG */
1262: /* #define DEBUGBRENT */
1.203 brouard 1263: /* #define DEBUGLINMIN */
1264: /* #define DEBUGHESS */
1265: #define DEBUGHESSIJ
1.224 brouard 1266: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 1267: #define POWELL /* Instead of NLOPT */
1.224 brouard 1268: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 1269: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
1270: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.319 brouard 1271: /* #define FLATSUP *//* Suppresses directions where likelihood is flat */
1.126 brouard 1272:
1273: #include <math.h>
1274: #include <stdio.h>
1275: #include <stdlib.h>
1276: #include <string.h>
1.226 brouard 1277: #include <ctype.h>
1.159 brouard 1278:
1279: #ifdef _WIN32
1280: #include <io.h>
1.172 brouard 1281: #include <windows.h>
1282: #include <tchar.h>
1.159 brouard 1283: #else
1.126 brouard 1284: #include <unistd.h>
1.159 brouard 1285: #endif
1.126 brouard 1286:
1287: #include <limits.h>
1288: #include <sys/types.h>
1.171 brouard 1289:
1290: #if defined(__GNUC__)
1291: #include <sys/utsname.h> /* Doesn't work on Windows */
1292: #endif
1293:
1.126 brouard 1294: #include <sys/stat.h>
1295: #include <errno.h>
1.159 brouard 1296: /* extern int errno; */
1.126 brouard 1297:
1.157 brouard 1298: /* #ifdef LINUX */
1299: /* #include <time.h> */
1300: /* #include "timeval.h" */
1301: /* #else */
1302: /* #include <sys/time.h> */
1303: /* #endif */
1304:
1.126 brouard 1305: #include <time.h>
1306:
1.136 brouard 1307: #ifdef GSL
1308: #include <gsl/gsl_errno.h>
1309: #include <gsl/gsl_multimin.h>
1310: #endif
1311:
1.167 brouard 1312:
1.162 brouard 1313: #ifdef NLOPT
1314: #include <nlopt.h>
1315: typedef struct {
1316: double (* function)(double [] );
1317: } myfunc_data ;
1318: #endif
1319:
1.126 brouard 1320: /* #include <libintl.h> */
1321: /* #define _(String) gettext (String) */
1322:
1.349 brouard 1323: #define MAXLINE 16384 /* Was 256 and 1024 and 2048. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1324:
1325: #define GNUPLOTPROGRAM "gnuplot"
1.343 brouard 1326: #define GNUPLOTVERSION 5.1
1327: double gnuplotversion=GNUPLOTVERSION;
1.126 brouard 1328: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1.329 brouard 1329: #define FILENAMELENGTH 256
1.126 brouard 1330:
1331: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1332: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1333:
1.349 brouard 1334: #define MAXPARM 216 /**< Maximum number of parameters for the optimization was 128 */
1.144 brouard 1335: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1336:
1337: #define NINTERVMAX 8
1.144 brouard 1338: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1339: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.325 brouard 1340: #define NCOVMAX 30 /**< Maximum number of covariates used in the model, including generated covariates V1*V2 or V1*age */
1.197 brouard 1341: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1342: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1343: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1344: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1345: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1346: /* #define AGESUP 130 */
1.288 brouard 1347: /* #define AGESUP 150 */
1348: #define AGESUP 200
1.268 brouard 1349: #define AGEINF 0
1.218 brouard 1350: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1351: #define AGEBASE 40
1.194 brouard 1352: #define AGEOVERFLOW 1.e20
1.164 brouard 1353: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1354: #ifdef _WIN32
1355: #define DIRSEPARATOR '\\'
1356: #define CHARSEPARATOR "\\"
1357: #define ODIRSEPARATOR '/'
1358: #else
1.126 brouard 1359: #define DIRSEPARATOR '/'
1360: #define CHARSEPARATOR "/"
1361: #define ODIRSEPARATOR '\\'
1362: #endif
1363:
1.351 ! brouard 1364: /* $Id: imach.c,v 1.350 2023/04/24 11:38:06 brouard Exp $ */
1.126 brouard 1365: /* $State: Exp $ */
1.196 brouard 1366: #include "version.h"
1367: char version[]=__IMACH_VERSION__;
1.349 brouard 1368: char copyright[]="January 2023,INED-EUROREVES-Institut de longevite-Japan Society for the Promotion of Science (Grant-in-Aid for Scientific Research 25293121), Intel Software 2015-2020, Nihon University 2021-202, INED 2000-2022";
1.351 ! brouard 1369: char fullversion[]="$Revision: 1.350 $ $Date: 2023/04/24 11:38:06 $";
1.126 brouard 1370: char strstart[80];
1371: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1372: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.342 brouard 1373: int debugILK=0; /* debugILK is set by a #d in a comment line */
1.187 brouard 1374: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.330 brouard 1375: /* Number of covariates model (1)=V2+V1+ V3*age+V2*V4 */
1376: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
1.335 brouard 1377: 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 1378: 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 1379: int cptcovs=0; /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
1380: int cptcovsnq=0; /**< cptcovsnq number of SIMPLE covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1381: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1.349 brouard 1382: int cptcovprodage=0; /**< Number of fixed covariates with age: V3*age or V2*V3*age 1 */
1383: int cptcovprodvage=0; /**< Number of varying covariates with age: V7*age or V7*V6*age */
1384: int cptcovdageprod=0; /**< Number of doubleproducts with age, since 0.99r44 only: age*Vn*Vm for gnuplot printing*/
1.145 brouard 1385: int cptcovprodnoage=0; /**< Number of covariate products without age */
1.335 brouard 1386: 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 1387: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1388: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.339 brouard 1389: int ncovvt=0; /* Total number of effective (wave) varying covariates (dummy or quantitative or products [without age]) in the model */
1.349 brouard 1390: int ncovvta=0; /* +age*V6 + age*V7+ age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 Total number of expandend products [with age]) in the model */
1391: int ncovta=0; /*age*V3*V2 +age*V2+agev3+ageV4 +age*V6 + age*V7+ age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 Total number of expandend products [with age]) in the model */
1392: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (single or product, dummy or quantitative) in the model */
1393: int ncovva=0; /* +age*V6 + age*V7+ge*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 Total number of effective (wave and stepm) varying with age covariates (single or product, dummy or quantitative) in the model */
1.234 brouard 1394: int nsd=0; /**< Total number of single dummy variables (output) */
1395: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1396: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1397: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1398: int ntveff=0; /**< ntveff number of effective time varying variables */
1399: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1400: int cptcov=0; /* Working variable */
1.334 brouard 1401: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs+1 declared globally ;*/
1.290 brouard 1402: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1403: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.302 brouard 1404: int npar=NPARMAX; /* Number of parameters (nlstate+ndeath-1)*nlstate*ncovmodel; */
1.126 brouard 1405: int nlstate=2; /* Number of live states */
1406: int ndeath=1; /* Number of dead states */
1.130 brouard 1407: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.339 brouard 1408: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable*/
1409: int ncovcolt=0; /* ncovcolt=ncovcol+nqv+ntv+nqtv; total of covariates in the data, not in the model equation*/
1.126 brouard 1410: int popbased=0;
1411:
1412: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1413: int maxwav=0; /* Maxim number of waves */
1414: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1415: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1416: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1417: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1418: int mle=1, weightopt=0;
1.126 brouard 1419: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1420: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1421: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1422: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1423: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1424: int selected(int kvar); /* Is covariate kvar selected for printing results */
1425:
1.130 brouard 1426: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1427: double **matprod2(); /* test */
1.126 brouard 1428: double **oldm, **newm, **savm; /* Working pointers to matrices */
1429: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1430: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1431:
1.136 brouard 1432: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1433: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1434: FILE *ficlog, *ficrespow;
1.130 brouard 1435: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1436: double fretone; /* Only one call to likelihood */
1.130 brouard 1437: long ipmx=0; /* Number of contributions */
1.126 brouard 1438: double sw; /* Sum of weights */
1439: char filerespow[FILENAMELENGTH];
1440: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1441: FILE *ficresilk;
1442: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1443: FILE *ficresprobmorprev;
1444: FILE *fichtm, *fichtmcov; /* Html File */
1445: FILE *ficreseij;
1446: char filerese[FILENAMELENGTH];
1447: FILE *ficresstdeij;
1448: char fileresstde[FILENAMELENGTH];
1449: FILE *ficrescveij;
1450: char filerescve[FILENAMELENGTH];
1451: FILE *ficresvij;
1452: char fileresv[FILENAMELENGTH];
1.269 brouard 1453:
1.126 brouard 1454: char title[MAXLINE];
1.234 brouard 1455: char model[MAXLINE]; /**< The model line */
1.217 brouard 1456: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1457: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1458: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1459: char command[FILENAMELENGTH];
1460: int outcmd=0;
1461:
1.217 brouard 1462: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1463: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1464: char filelog[FILENAMELENGTH]; /* Log file */
1465: char filerest[FILENAMELENGTH];
1466: char fileregp[FILENAMELENGTH];
1467: char popfile[FILENAMELENGTH];
1468:
1469: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1470:
1.157 brouard 1471: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1472: /* struct timezone tzp; */
1473: /* extern int gettimeofday(); */
1474: struct tm tml, *gmtime(), *localtime();
1475:
1476: extern time_t time();
1477:
1478: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1479: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1.349 brouard 1480: time_t rlast_btime; /* raw time */
1.157 brouard 1481: struct tm tm;
1482:
1.126 brouard 1483: char strcurr[80], strfor[80];
1484:
1485: char *endptr;
1486: long lval;
1487: double dval;
1488:
1489: #define NR_END 1
1490: #define FREE_ARG char*
1491: #define FTOL 1.0e-10
1492:
1493: #define NRANSI
1.240 brouard 1494: #define ITMAX 200
1495: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1496:
1497: #define TOL 2.0e-4
1498:
1499: #define CGOLD 0.3819660
1500: #define ZEPS 1.0e-10
1501: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1502:
1503: #define GOLD 1.618034
1504: #define GLIMIT 100.0
1505: #define TINY 1.0e-20
1506:
1507: static double maxarg1,maxarg2;
1508: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1509: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1510:
1511: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1512: #define rint(a) floor(a+0.5)
1.166 brouard 1513: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1514: #define mytinydouble 1.0e-16
1.166 brouard 1515: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1516: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1517: /* static double dsqrarg; */
1518: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1519: static double sqrarg;
1520: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1521: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1522: int agegomp= AGEGOMP;
1523:
1524: int imx;
1525: int stepm=1;
1526: /* Stepm, step in month: minimum step interpolation*/
1527:
1528: int estepm;
1529: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1530:
1531: int m,nb;
1532: long *num;
1.197 brouard 1533: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1534: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1535: covariate for which somebody answered excluding
1536: undefined. Usually 2: 0 and 1. */
1537: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1538: covariate for which somebody answered including
1539: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1540: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1541: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1542: double ***mobaverage, ***mobaverages; /* New global variable */
1.332 brouard 1543: 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 1544: double *ageexmed,*agecens;
1545: double dateintmean=0;
1.296 brouard 1546: double anprojd, mprojd, jprojd; /* For eventual projections */
1547: double anprojf, mprojf, jprojf;
1.126 brouard 1548:
1.296 brouard 1549: double anbackd, mbackd, jbackd; /* For eventual backprojections */
1550: double anbackf, mbackf, jbackf;
1551: double jintmean,mintmean,aintmean;
1.126 brouard 1552: double *weight;
1553: int **s; /* Status */
1.141 brouard 1554: double *agedc;
1.145 brouard 1555: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1556: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1557: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1558: double **coqvar; /* Fixed quantitative covariate nqv */
1.341 brouard 1559: double ***cotvar; /* Time varying covariate start at ncovcol + nqv + (1 to ntv) */
1.225 brouard 1560: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1561: double idx;
1562: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.319 brouard 1563: /* Some documentation */
1564: /* Design original data
1565: * V1 V2 V3 V4 V5 V6 V7 V8 Weight ddb ddth d1st s1 V9 V10 V11 V12 s2 V9 V10 V11 V12
1566: * < ncovcol=6 > nqv=2 (V7 V8) dv dv dv qtv dv dv dvv qtv
1567: * ntv=3 nqtv=1
1.330 brouard 1568: * cptcovn number of covariates (not including constant and age or age*age) = number of plus sign + 1 = 10+1=11
1.319 brouard 1569: * For time varying covariate, quanti or dummies
1570: * cotqvar[wav][iv(1 to nqtv)][i]= [1][12][i]=(V12) quanti
1.341 brouard 1571: * cotvar[wav][ncovcol+nqv+ iv(1 to nqtv)][i]= [(1 to nqtv)][i]=(V12) quanti
1.319 brouard 1572: * cotvar[wav][iv(1 to ntv)][i]= [1][1][i]=(V9) dummies at wav 1
1573: * cotvar[wav][iv(1 to ntv)][i]= [1][2][i]=(V10) dummies at wav 1
1.332 brouard 1574: * covar[Vk,i], value of the Vkth fixed covariate dummy or quanti for individual i:
1.319 brouard 1575: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
1576: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 + V9 + V9*age + V10
1577: * k= 1 2 3 4 5 6 7 8 9 10 11
1578: */
1579: /* According to the model, more columns can be added to covar by the product of covariates */
1.318 brouard 1580: /* 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
1581: # States 1=Coresidence, 2 Living alone, 3 Institution
1582: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1583: */
1.349 brouard 1584: /* V5+V4+ V3+V4*V3 +V5*age+V2 +V1*V2+V1*age+V1+V4*V3*age */
1585: /* kmodel 1 2 3 4 5 6 7 8 9 10 */
1586: /*Typevar[k]= 0 0 0 2 1 0 2 1 0 3 *//*0 for simple covariate (dummy, quantitative,*/
1587: /* fixed or varying), 1 for age product, 2 for*/
1588: /* product without age, 3 for age and double product */
1589: /*Dummy[k]= 1 0 0 1 3 1 1 2 0 3 *//*Dummy[k] 0=dummy (0 1), 1 quantitative */
1590: /*(single or product without age), 2 dummy*/
1591: /* with age product, 3 quant with age product*/
1592: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 6 */
1593: /* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */
1594: /*TnsdVar[Tvar] 1 2 3 */
1595: /*Tvaraff[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1596: /*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1597: /*TvarsDind[nsd] 2 3 9 */ /* position K of single dummy cova */
1598: /* nsq 1 2 */ /* Counting single quantit tv */
1599: /* TvarsQ[k] 5 2 */ /* Number of single quantitative cova */
1600: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1601: /* Tprod[i]=k 1 2 */ /* Position in model of the ith prod without age */
1602: /* cptcovage 1 2 3 */ /* Counting cov*age in the model equation */
1603: /* Tage[cptcovage]=k 5 8 10 */ /* Position in the model of ith cov*age */
1.350 brouard 1604: /* model="V2+V3+V4+V6+V7+V6*V2+V7*V2+V6*V3+V7*V3+V6*V4+V7*V4+age*V2+age*V3+age*V4+age*V6+age*V7+age*V6*V2+age*V6*V3+age*V7*V3+age*V6*V4+age*V7*V4\r"*/
1605: /* p Tvard[1][1]@21 = {6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0}*/
1606: /* p Tvard[2][1]@21 = {7, 2, 6, 3, 7, 3, 6, 4, 7, 4, 0 <repeats 11 times>}
1607: /* p Tvardk[1][1]@24 = {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4, 0, 0}*/
1608: /* p Tvardk[1][1]@22 = {0, 0, 0, 0, 0, 0, 0, 0, 6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4, 0, 0} */
1.349 brouard 1609: /* Tvard[1][1]@4={4,3,1,2} V4*V3 V1*V2 */ /* Position in model of the ith prod without age */
1.330 brouard 1610: /* 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 1611: /* 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 1612: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.234 brouard 1613: /* Type */
1614: /* V 1 2 3 4 5 */
1615: /* F F V V V */
1616: /* D Q D D Q */
1617: /* */
1618: int *TvarsD;
1.330 brouard 1619: int *TnsdVar;
1.234 brouard 1620: int *TvarsDind;
1621: int *TvarsQ;
1622: int *TvarsQind;
1623:
1.318 brouard 1624: #define MAXRESULTLINESPONE 10+1
1.235 brouard 1625: int nresult=0;
1.258 brouard 1626: int parameterline=0; /* # of the parameter (type) line */
1.334 brouard 1627: int TKresult[MAXRESULTLINESPONE]; /* TKresult[nres]=k for each resultline nres give the corresponding combination of dummies */
1628: int resultmodel[MAXRESULTLINESPONE][NCOVMAX];/* resultmodel[k1]=k3: k1th position in the model corresponds to the k3 position in the resultline */
1629: int modelresult[MAXRESULTLINESPONE][NCOVMAX];/* modelresult[k3]=k1: k1th position in the model corresponds to the k3 position in the resultline */
1630: int Tresult[MAXRESULTLINESPONE][NCOVMAX];/* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1631: int Tinvresult[MAXRESULTLINESPONE][NCOVMAX];/* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1632: double TinvDoQresult[MAXRESULTLINESPONE][NCOVMAX];/* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.334 brouard 1633: int Tvresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1634: double Tqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.318 brouard 1635: double Tqinvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
1.332 brouard 1636: int Tvqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.318 brouard 1637:
1638: /* 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
1639: # States 1=Coresidence, 2 Living alone, 3 Institution
1640: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1641: */
1.234 brouard 1642: /* 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 1643: 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 */
1644: 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 */
1645: 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 */
1646: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1647: 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 */
1648: 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 1649: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1650: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1651: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1652: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1653: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1654: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1655: 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 */
1656: 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 1657: int *TvarVV; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1658: int *TvarVVind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1.349 brouard 1659: int *TvarVVA; /* We count ncovvt time varying covariates (single or products with age) and put their name into TvarVVA */
1660: int *TvarVVAind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1661: int *TvarAVVA; /* We count ALL ncovta time varying covariates (single or products with age) and put their name into TvarVVA */
1662: int *TvarAVVAind; /* We count ALL ncovta time varying covariates (single or products without age) and put their name into TvarVV */
1.339 brouard 1663: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
1.349 brouard 1664: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age */
1665: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
1666: /* TvarVV={3,1,3,1,3}, for V3 and then the product V1*V3 is decomposed into V1 and V3 */
1667: /* TvarVVind={2,5,5,6,6}, for V3 and then the product V1*V3 is decomposed into V1 and V3 and V1*V3*age into 6,6 */
1.230 brouard 1668: int *Tvarsel; /**< Selected covariates for output */
1669: double *Tvalsel; /**< Selected modality value of covariate for output */
1.349 brouard 1670: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product, 3 age*Vn*Vm */
1.227 brouard 1671: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1672: 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 1673: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1674: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1675: int *Tage;
1.227 brouard 1676: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1677: 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 1678: 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*/
1679: 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 1680: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1681: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1682: int **Tvard;
1.330 brouard 1683: int **Tvardk;
1.227 brouard 1684: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1685: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1686: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1687: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1688: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1689: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1690: double *lsurv, *lpop, *tpop;
1691:
1.231 brouard 1692: #define FD 1; /* Fixed dummy covariate */
1693: #define FQ 2; /* Fixed quantitative covariate */
1694: #define FP 3; /* Fixed product covariate */
1695: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1696: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1697: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1698: #define VD 10; /* Varying dummy covariate */
1699: #define VQ 11; /* Varying quantitative covariate */
1700: #define VP 12; /* Varying product covariate */
1701: #define VPDD 13; /* Varying product dummy*dummy covariate */
1702: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1703: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1704: #define APFD 16; /* Age product * fixed dummy covariate */
1705: #define APFQ 17; /* Age product * fixed quantitative covariate */
1706: #define APVD 18; /* Age product * varying dummy covariate */
1707: #define APVQ 19; /* Age product * varying quantitative covariate */
1708:
1709: #define FTYPE 1; /* Fixed covariate */
1710: #define VTYPE 2; /* Varying covariate (loop in wave) */
1711: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1712:
1713: struct kmodel{
1714: int maintype; /* main type */
1715: int subtype; /* subtype */
1716: };
1717: struct kmodel modell[NCOVMAX];
1718:
1.143 brouard 1719: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1720: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1721:
1722: /**************** split *************************/
1723: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1724: {
1725: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1726: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1727: */
1728: char *ss; /* pointer */
1.186 brouard 1729: int l1=0, l2=0; /* length counters */
1.126 brouard 1730:
1731: l1 = strlen(path ); /* length of path */
1732: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1733: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1734: if ( ss == NULL ) { /* no directory, so determine current directory */
1735: strcpy( name, path ); /* we got the fullname name because no directory */
1736: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1737: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1738: /* get current working directory */
1739: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1740: #ifdef WIN32
1741: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1742: #else
1743: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1744: #endif
1.126 brouard 1745: return( GLOCK_ERROR_GETCWD );
1746: }
1747: /* got dirc from getcwd*/
1748: printf(" DIRC = %s \n",dirc);
1.205 brouard 1749: } else { /* strip directory from path */
1.126 brouard 1750: ss++; /* after this, the filename */
1751: l2 = strlen( ss ); /* length of filename */
1752: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1753: strcpy( name, ss ); /* save file name */
1754: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1755: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1756: printf(" DIRC2 = %s \n",dirc);
1757: }
1758: /* We add a separator at the end of dirc if not exists */
1759: l1 = strlen( dirc ); /* length of directory */
1760: if( dirc[l1-1] != DIRSEPARATOR ){
1761: dirc[l1] = DIRSEPARATOR;
1762: dirc[l1+1] = 0;
1763: printf(" DIRC3 = %s \n",dirc);
1764: }
1765: ss = strrchr( name, '.' ); /* find last / */
1766: if (ss >0){
1767: ss++;
1768: strcpy(ext,ss); /* save extension */
1769: l1= strlen( name);
1770: l2= strlen(ss)+1;
1771: strncpy( finame, name, l1-l2);
1772: finame[l1-l2]= 0;
1773: }
1774:
1775: return( 0 ); /* we're done */
1776: }
1777:
1778:
1779: /******************************************/
1780:
1781: void replace_back_to_slash(char *s, char*t)
1782: {
1783: int i;
1784: int lg=0;
1785: i=0;
1786: lg=strlen(t);
1787: for(i=0; i<= lg; i++) {
1788: (s[i] = t[i]);
1789: if (t[i]== '\\') s[i]='/';
1790: }
1791: }
1792:
1.132 brouard 1793: char *trimbb(char *out, char *in)
1.137 brouard 1794: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1795: char *s;
1796: s=out;
1797: while (*in != '\0'){
1.137 brouard 1798: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1799: in++;
1800: }
1801: *out++ = *in++;
1802: }
1803: *out='\0';
1804: return s;
1805: }
1806:
1.351 ! brouard 1807: char *trimbtab(char *out, char *in)
! 1808: { /* Trim blanks or tabs in line but keeps first blanks if line starts with blanks */
! 1809: char *s;
! 1810: s=out;
! 1811: while (*in != '\0'){
! 1812: while( (*in == ' ' || *in == '\t')){ /* && *(in+1) != '\0'){*/
! 1813: in++;
! 1814: }
! 1815: *out++ = *in++;
! 1816: }
! 1817: *out='\0';
! 1818: return s;
! 1819: }
! 1820:
1.187 brouard 1821: /* char *substrchaine(char *out, char *in, char *chain) */
1822: /* { */
1823: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1824: /* char *s, *t; */
1825: /* t=in;s=out; */
1826: /* while ((*in != *chain) && (*in != '\0')){ */
1827: /* *out++ = *in++; */
1828: /* } */
1829:
1830: /* /\* *in matches *chain *\/ */
1831: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1832: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1833: /* } */
1834: /* in--; chain--; */
1835: /* while ( (*in != '\0')){ */
1836: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1837: /* *out++ = *in++; */
1838: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1839: /* } */
1840: /* *out='\0'; */
1841: /* out=s; */
1842: /* return out; */
1843: /* } */
1844: char *substrchaine(char *out, char *in, char *chain)
1845: {
1846: /* Substract chain 'chain' from 'in', return and output 'out' */
1.349 brouard 1847: /* in="V1+V1*age+age*age+V2", chain="+age*age" out="V1+V1*age+V2" */
1.187 brouard 1848:
1849: char *strloc;
1850:
1.349 brouard 1851: strcpy (out, in); /* out="V1+V1*age+age*age+V2" */
1852: strloc = strstr(out, chain); /* strloc points to out at "+age*age+V2" */
1853: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out); /* strloc=+age*age+V2 chain="+age*age", out="V1+V1*age+age*age+V2" */
1.187 brouard 1854: if(strloc != NULL){
1.349 brouard 1855: /* will affect out */ /* strloc+strlen(chain)=|+V2 = "V1+V1*age+age*age|+V2" */ /* Will also work in Unicodek */
1856: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1); /* move number of bytes corresponding to the length of "+V2" which is 3, plus one is 4 (including the null)*/
1857: /* equivalent to strcpy (strloc, strloc +strlen(chain)) if no overlap; Copies from "+V2" to V1+V1*age+ */
1.187 brouard 1858: }
1.349 brouard 1859: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out); /* strloc=+V2 chain="+age*age", in="V1+V1*age+age*age+V2", out="V1+V1*age+V2" */
1.187 brouard 1860: return out;
1861: }
1862:
1863:
1.145 brouard 1864: char *cutl(char *blocc, char *alocc, char *in, char occ)
1865: {
1.187 brouard 1866: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.349 brouard 1867: and alocc starts after first occurence of char 'occ' : ex cutl(blocc,alocc,"abcdef2ghi2j",'2')
1.310 brouard 1868: gives alocc="abcdef" and blocc="ghi2j".
1.145 brouard 1869: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1870: */
1.160 brouard 1871: char *s, *t;
1.145 brouard 1872: t=in;s=in;
1873: while ((*in != occ) && (*in != '\0')){
1874: *alocc++ = *in++;
1875: }
1876: if( *in == occ){
1877: *(alocc)='\0';
1878: s=++in;
1879: }
1880:
1881: if (s == t) {/* occ not found */
1882: *(alocc-(in-s))='\0';
1883: in=s;
1884: }
1885: while ( *in != '\0'){
1886: *blocc++ = *in++;
1887: }
1888:
1889: *blocc='\0';
1890: return t;
1891: }
1.137 brouard 1892: char *cutv(char *blocc, char *alocc, char *in, char occ)
1893: {
1.187 brouard 1894: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1895: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1896: gives blocc="abcdef2ghi" and alocc="j".
1897: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1898: */
1899: char *s, *t;
1900: t=in;s=in;
1901: while (*in != '\0'){
1902: while( *in == occ){
1903: *blocc++ = *in++;
1904: s=in;
1905: }
1906: *blocc++ = *in++;
1907: }
1908: if (s == t) /* occ not found */
1909: *(blocc-(in-s))='\0';
1910: else
1911: *(blocc-(in-s)-1)='\0';
1912: in=s;
1913: while ( *in != '\0'){
1914: *alocc++ = *in++;
1915: }
1916:
1917: *alocc='\0';
1918: return s;
1919: }
1920:
1.126 brouard 1921: int nbocc(char *s, char occ)
1922: {
1923: int i,j=0;
1924: int lg=20;
1925: i=0;
1926: lg=strlen(s);
1927: for(i=0; i<= lg; i++) {
1.234 brouard 1928: if (s[i] == occ ) j++;
1.126 brouard 1929: }
1930: return j;
1931: }
1932:
1.349 brouard 1933: int nboccstr(char *textin, char *chain)
1934: {
1935: /* Counts the number of occurence of "chain" in string textin */
1936: /* in="+V7*V4+age*V2+age*V3+age*V4" chain="age" */
1937: char *strloc;
1938:
1939: int i,j=0;
1940:
1941: i=0;
1942:
1943: strloc=textin; /* strloc points to "^+V7*V4+age+..." in textin */
1944: for(;;) {
1945: strloc= strstr(strloc,chain); /* strloc points to first character of chain in textin if found. Example strloc points^ to "+V7*V4+^age" in textin */
1946: if(strloc != NULL){
1947: strloc = strloc+strlen(chain); /* strloc points to "+V7*V4+age^" in textin */
1948: j++;
1949: }else
1950: break;
1951: }
1952: return j;
1953:
1954: }
1.137 brouard 1955: /* void cutv(char *u,char *v, char*t, char occ) */
1956: /* { */
1957: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1958: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1959: /* gives u="abcdef2ghi" and v="j" *\/ */
1960: /* int i,lg,j,p=0; */
1961: /* i=0; */
1962: /* lg=strlen(t); */
1963: /* for(j=0; j<=lg-1; j++) { */
1964: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1965: /* } */
1.126 brouard 1966:
1.137 brouard 1967: /* for(j=0; j<p; j++) { */
1968: /* (u[j] = t[j]); */
1969: /* } */
1970: /* u[p]='\0'; */
1.126 brouard 1971:
1.137 brouard 1972: /* for(j=0; j<= lg; j++) { */
1973: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1974: /* } */
1975: /* } */
1.126 brouard 1976:
1.160 brouard 1977: #ifdef _WIN32
1978: char * strsep(char **pp, const char *delim)
1979: {
1980: char *p, *q;
1981:
1982: if ((p = *pp) == NULL)
1983: return 0;
1984: if ((q = strpbrk (p, delim)) != NULL)
1985: {
1986: *pp = q + 1;
1987: *q = '\0';
1988: }
1989: else
1990: *pp = 0;
1991: return p;
1992: }
1993: #endif
1994:
1.126 brouard 1995: /********************** nrerror ********************/
1996:
1997: void nrerror(char error_text[])
1998: {
1999: fprintf(stderr,"ERREUR ...\n");
2000: fprintf(stderr,"%s\n",error_text);
2001: exit(EXIT_FAILURE);
2002: }
2003: /*********************** vector *******************/
2004: double *vector(int nl, int nh)
2005: {
2006: double *v;
2007: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
2008: if (!v) nrerror("allocation failure in vector");
2009: return v-nl+NR_END;
2010: }
2011:
2012: /************************ free vector ******************/
2013: void free_vector(double*v, int nl, int nh)
2014: {
2015: free((FREE_ARG)(v+nl-NR_END));
2016: }
2017:
2018: /************************ivector *******************************/
2019: int *ivector(long nl,long nh)
2020: {
2021: int *v;
2022: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
2023: if (!v) nrerror("allocation failure in ivector");
2024: return v-nl+NR_END;
2025: }
2026:
2027: /******************free ivector **************************/
2028: void free_ivector(int *v, long nl, long nh)
2029: {
2030: free((FREE_ARG)(v+nl-NR_END));
2031: }
2032:
2033: /************************lvector *******************************/
2034: long *lvector(long nl,long nh)
2035: {
2036: long *v;
2037: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
2038: if (!v) nrerror("allocation failure in ivector");
2039: return v-nl+NR_END;
2040: }
2041:
2042: /******************free lvector **************************/
2043: void free_lvector(long *v, long nl, long nh)
2044: {
2045: free((FREE_ARG)(v+nl-NR_END));
2046: }
2047:
2048: /******************* imatrix *******************************/
2049: int **imatrix(long nrl, long nrh, long ncl, long nch)
2050: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
2051: {
2052: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
2053: int **m;
2054:
2055: /* allocate pointers to rows */
2056: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
2057: if (!m) nrerror("allocation failure 1 in matrix()");
2058: m += NR_END;
2059: m -= nrl;
2060:
2061:
2062: /* allocate rows and set pointers to them */
2063: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
2064: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2065: m[nrl] += NR_END;
2066: m[nrl] -= ncl;
2067:
2068: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
2069:
2070: /* return pointer to array of pointers to rows */
2071: return m;
2072: }
2073:
2074: /****************** free_imatrix *************************/
2075: void free_imatrix(m,nrl,nrh,ncl,nch)
2076: int **m;
2077: long nch,ncl,nrh,nrl;
2078: /* free an int matrix allocated by imatrix() */
2079: {
2080: free((FREE_ARG) (m[nrl]+ncl-NR_END));
2081: free((FREE_ARG) (m+nrl-NR_END));
2082: }
2083:
2084: /******************* matrix *******************************/
2085: double **matrix(long nrl, long nrh, long ncl, long nch)
2086: {
2087: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
2088: double **m;
2089:
2090: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
2091: if (!m) nrerror("allocation failure 1 in matrix()");
2092: m += NR_END;
2093: m -= nrl;
2094:
2095: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
2096: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2097: m[nrl] += NR_END;
2098: m[nrl] -= ncl;
2099:
2100: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2101: return m;
1.145 brouard 2102: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
2103: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
2104: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 2105: */
2106: }
2107:
2108: /*************************free matrix ************************/
2109: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
2110: {
2111: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2112: free((FREE_ARG)(m+nrl-NR_END));
2113: }
2114:
2115: /******************* ma3x *******************************/
2116: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
2117: {
2118: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
2119: double ***m;
2120:
2121: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
2122: if (!m) nrerror("allocation failure 1 in matrix()");
2123: m += NR_END;
2124: m -= nrl;
2125:
2126: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
2127: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2128: m[nrl] += NR_END;
2129: m[nrl] -= ncl;
2130:
2131: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2132:
2133: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
2134: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
2135: m[nrl][ncl] += NR_END;
2136: m[nrl][ncl] -= nll;
2137: for (j=ncl+1; j<=nch; j++)
2138: m[nrl][j]=m[nrl][j-1]+nlay;
2139:
2140: for (i=nrl+1; i<=nrh; i++) {
2141: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
2142: for (j=ncl+1; j<=nch; j++)
2143: m[i][j]=m[i][j-1]+nlay;
2144: }
2145: return m;
2146: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
2147: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
2148: */
2149: }
2150:
2151: /*************************free ma3x ************************/
2152: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
2153: {
2154: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
2155: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2156: free((FREE_ARG)(m+nrl-NR_END));
2157: }
2158:
2159: /*************** function subdirf ***********/
2160: char *subdirf(char fileres[])
2161: {
2162: /* Caution optionfilefiname is hidden */
2163: strcpy(tmpout,optionfilefiname);
2164: strcat(tmpout,"/"); /* Add to the right */
2165: strcat(tmpout,fileres);
2166: return tmpout;
2167: }
2168:
2169: /*************** function subdirf2 ***********/
2170: char *subdirf2(char fileres[], char *preop)
2171: {
1.314 brouard 2172: /* Example subdirf2(optionfilefiname,"FB_") with optionfilefiname="texte", result="texte/FB_texte"
2173: Errors in subdirf, 2, 3 while printing tmpout is
1.315 brouard 2174: rewritten within the same printf. Workaround: many printfs */
1.126 brouard 2175: /* Caution optionfilefiname is hidden */
2176: strcpy(tmpout,optionfilefiname);
2177: strcat(tmpout,"/");
2178: strcat(tmpout,preop);
2179: strcat(tmpout,fileres);
2180: return tmpout;
2181: }
2182:
2183: /*************** function subdirf3 ***********/
2184: char *subdirf3(char fileres[], char *preop, char *preop2)
2185: {
2186:
2187: /* Caution optionfilefiname is hidden */
2188: strcpy(tmpout,optionfilefiname);
2189: strcat(tmpout,"/");
2190: strcat(tmpout,preop);
2191: strcat(tmpout,preop2);
2192: strcat(tmpout,fileres);
2193: return tmpout;
2194: }
1.213 brouard 2195:
2196: /*************** function subdirfext ***********/
2197: char *subdirfext(char fileres[], char *preop, char *postop)
2198: {
2199:
2200: strcpy(tmpout,preop);
2201: strcat(tmpout,fileres);
2202: strcat(tmpout,postop);
2203: return tmpout;
2204: }
1.126 brouard 2205:
1.213 brouard 2206: /*************** function subdirfext3 ***********/
2207: char *subdirfext3(char fileres[], char *preop, char *postop)
2208: {
2209:
2210: /* Caution optionfilefiname is hidden */
2211: strcpy(tmpout,optionfilefiname);
2212: strcat(tmpout,"/");
2213: strcat(tmpout,preop);
2214: strcat(tmpout,fileres);
2215: strcat(tmpout,postop);
2216: return tmpout;
2217: }
2218:
1.162 brouard 2219: char *asc_diff_time(long time_sec, char ascdiff[])
2220: {
2221: long sec_left, days, hours, minutes;
2222: days = (time_sec) / (60*60*24);
2223: sec_left = (time_sec) % (60*60*24);
2224: hours = (sec_left) / (60*60) ;
2225: sec_left = (sec_left) %(60*60);
2226: minutes = (sec_left) /60;
2227: sec_left = (sec_left) % (60);
2228: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
2229: return ascdiff;
2230: }
2231:
1.126 brouard 2232: /***************** f1dim *************************/
2233: extern int ncom;
2234: extern double *pcom,*xicom;
2235: extern double (*nrfunc)(double []);
2236:
2237: double f1dim(double x)
2238: {
2239: int j;
2240: double f;
2241: double *xt;
2242:
2243: xt=vector(1,ncom);
2244: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
2245: f=(*nrfunc)(xt);
2246: free_vector(xt,1,ncom);
2247: return f;
2248: }
2249:
2250: /*****************brent *************************/
2251: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 2252: {
2253: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
2254: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
2255: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
2256: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
2257: * returned function value.
2258: */
1.126 brouard 2259: int iter;
2260: double a,b,d,etemp;
1.159 brouard 2261: double fu=0,fv,fw,fx;
1.164 brouard 2262: double ftemp=0.;
1.126 brouard 2263: double p,q,r,tol1,tol2,u,v,w,x,xm;
2264: double e=0.0;
2265:
2266: a=(ax < cx ? ax : cx);
2267: b=(ax > cx ? ax : cx);
2268: x=w=v=bx;
2269: fw=fv=fx=(*f)(x);
2270: for (iter=1;iter<=ITMAX;iter++) {
2271: xm=0.5*(a+b);
2272: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
2273: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
2274: printf(".");fflush(stdout);
2275: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 2276: #ifdef DEBUGBRENT
1.126 brouard 2277: 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);
2278: 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);
2279: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
2280: #endif
2281: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
2282: *xmin=x;
2283: return fx;
2284: }
2285: ftemp=fu;
2286: if (fabs(e) > tol1) {
2287: r=(x-w)*(fx-fv);
2288: q=(x-v)*(fx-fw);
2289: p=(x-v)*q-(x-w)*r;
2290: q=2.0*(q-r);
2291: if (q > 0.0) p = -p;
2292: q=fabs(q);
2293: etemp=e;
2294: e=d;
2295: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 2296: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 2297: else {
1.224 brouard 2298: d=p/q;
2299: u=x+d;
2300: if (u-a < tol2 || b-u < tol2)
2301: d=SIGN(tol1,xm-x);
1.126 brouard 2302: }
2303: } else {
2304: d=CGOLD*(e=(x >= xm ? a-x : b-x));
2305: }
2306: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
2307: fu=(*f)(u);
2308: if (fu <= fx) {
2309: if (u >= x) a=x; else b=x;
2310: SHFT(v,w,x,u)
1.183 brouard 2311: SHFT(fv,fw,fx,fu)
2312: } else {
2313: if (u < x) a=u; else b=u;
2314: if (fu <= fw || w == x) {
1.224 brouard 2315: v=w;
2316: w=u;
2317: fv=fw;
2318: fw=fu;
1.183 brouard 2319: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 2320: v=u;
2321: fv=fu;
1.183 brouard 2322: }
2323: }
1.126 brouard 2324: }
2325: nrerror("Too many iterations in brent");
2326: *xmin=x;
2327: return fx;
2328: }
2329:
2330: /****************** mnbrak ***********************/
2331:
2332: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
2333: double (*func)(double))
1.183 brouard 2334: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
2335: the downhill direction (defined by the function as evaluated at the initial points) and returns
2336: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
2337: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
2338: */
1.126 brouard 2339: double ulim,u,r,q, dum;
2340: double fu;
1.187 brouard 2341:
2342: double scale=10.;
2343: int iterscale=0;
2344:
2345: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
2346: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
2347:
2348:
2349: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
2350: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
2351: /* *bx = *ax - (*ax - *bx)/scale; */
2352: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
2353: /* } */
2354:
1.126 brouard 2355: if (*fb > *fa) {
2356: SHFT(dum,*ax,*bx,dum)
1.183 brouard 2357: SHFT(dum,*fb,*fa,dum)
2358: }
1.126 brouard 2359: *cx=(*bx)+GOLD*(*bx-*ax);
2360: *fc=(*func)(*cx);
1.183 brouard 2361: #ifdef DEBUG
1.224 brouard 2362: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
2363: 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 2364: #endif
1.224 brouard 2365: 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 2366: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 2367: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 2368: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 2369: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
2370: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
2371: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 2372: fu=(*func)(u);
1.163 brouard 2373: #ifdef DEBUG
2374: /* f(x)=A(x-u)**2+f(u) */
2375: double A, fparabu;
2376: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2377: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 2378: 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);
2379: 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 2380: /* And thus,it can be that fu > *fc even if fparabu < *fc */
2381: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
2382: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
2383: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 2384: #endif
1.184 brouard 2385: #ifdef MNBRAKORIGINAL
1.183 brouard 2386: #else
1.191 brouard 2387: /* if (fu > *fc) { */
2388: /* #ifdef DEBUG */
2389: /* printf("mnbrak4 fu > fc \n"); */
2390: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
2391: /* #endif */
2392: /* /\* 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 *\\/ *\/ */
2393: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2394: /* dum=u; /\* Shifting c and u *\/ */
2395: /* u = *cx; */
2396: /* *cx = dum; */
2397: /* dum = fu; */
2398: /* fu = *fc; */
2399: /* *fc =dum; */
2400: /* } else { /\* end *\/ */
2401: /* #ifdef DEBUG */
2402: /* printf("mnbrak3 fu < fc \n"); */
2403: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2404: /* #endif */
2405: /* dum=u; /\* Shifting c and u *\/ */
2406: /* u = *cx; */
2407: /* *cx = dum; */
2408: /* dum = fu; */
2409: /* fu = *fc; */
2410: /* *fc =dum; */
2411: /* } */
1.224 brouard 2412: #ifdef DEBUGMNBRAK
2413: double A, fparabu;
2414: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2415: fparabu= *fa - A*(*ax-u)*(*ax-u);
2416: 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);
2417: 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 2418: #endif
1.191 brouard 2419: dum=u; /* Shifting c and u */
2420: u = *cx;
2421: *cx = dum;
2422: dum = fu;
2423: fu = *fc;
2424: *fc =dum;
1.183 brouard 2425: #endif
1.162 brouard 2426: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2427: #ifdef DEBUG
1.224 brouard 2428: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2429: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2430: #endif
1.126 brouard 2431: fu=(*func)(u);
2432: if (fu < *fc) {
1.183 brouard 2433: #ifdef DEBUG
1.224 brouard 2434: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2435: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2436: #endif
2437: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2438: SHFT(*fb,*fc,fu,(*func)(u))
2439: #ifdef DEBUG
2440: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2441: #endif
2442: }
1.162 brouard 2443: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2444: #ifdef DEBUG
1.224 brouard 2445: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2446: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2447: #endif
1.126 brouard 2448: u=ulim;
2449: fu=(*func)(u);
1.183 brouard 2450: } else { /* u could be left to b (if r > q parabola has a maximum) */
2451: #ifdef DEBUG
1.224 brouard 2452: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2453: 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 2454: #endif
1.126 brouard 2455: u=(*cx)+GOLD*(*cx-*bx);
2456: fu=(*func)(u);
1.224 brouard 2457: #ifdef DEBUG
2458: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2459: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2460: #endif
1.183 brouard 2461: } /* end tests */
1.126 brouard 2462: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2463: SHFT(*fa,*fb,*fc,fu)
2464: #ifdef DEBUG
1.224 brouard 2465: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2466: 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 2467: #endif
2468: } /* 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 2469: }
2470:
2471: /*************** linmin ************************/
1.162 brouard 2472: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2473: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2474: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2475: the value of func at the returned location p . This is actually all accomplished by calling the
2476: routines mnbrak and brent .*/
1.126 brouard 2477: int ncom;
2478: double *pcom,*xicom;
2479: double (*nrfunc)(double []);
2480:
1.224 brouard 2481: #ifdef LINMINORIGINAL
1.126 brouard 2482: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2483: #else
2484: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2485: #endif
1.126 brouard 2486: {
2487: double brent(double ax, double bx, double cx,
2488: double (*f)(double), double tol, double *xmin);
2489: double f1dim(double x);
2490: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2491: double *fc, double (*func)(double));
2492: int j;
2493: double xx,xmin,bx,ax;
2494: double fx,fb,fa;
1.187 brouard 2495:
1.203 brouard 2496: #ifdef LINMINORIGINAL
2497: #else
2498: double scale=10., axs, xxs; /* Scale added for infinity */
2499: #endif
2500:
1.126 brouard 2501: ncom=n;
2502: pcom=vector(1,n);
2503: xicom=vector(1,n);
2504: nrfunc=func;
2505: for (j=1;j<=n;j++) {
2506: pcom[j]=p[j];
1.202 brouard 2507: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2508: }
1.187 brouard 2509:
1.203 brouard 2510: #ifdef LINMINORIGINAL
2511: xx=1.;
2512: #else
2513: axs=0.0;
2514: xxs=1.;
2515: do{
2516: xx= xxs;
2517: #endif
1.187 brouard 2518: ax=0.;
2519: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2520: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2521: /* 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)) */
2522: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2523: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2524: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2525: /* 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 2526: #ifdef LINMINORIGINAL
2527: #else
2528: if (fx != fx){
1.224 brouard 2529: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2530: printf("|");
2531: fprintf(ficlog,"|");
1.203 brouard 2532: #ifdef DEBUGLINMIN
1.224 brouard 2533: 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 2534: #endif
2535: }
1.224 brouard 2536: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2537: #endif
2538:
1.191 brouard 2539: #ifdef DEBUGLINMIN
2540: 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 2541: 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 2542: #endif
1.224 brouard 2543: #ifdef LINMINORIGINAL
2544: #else
1.317 brouard 2545: if(fb == fx){ /* Flat function in the direction */
2546: xmin=xx;
1.224 brouard 2547: *flat=1;
1.317 brouard 2548: }else{
1.224 brouard 2549: *flat=0;
2550: #endif
2551: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2552: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2553: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2554: /* fmin = f(p[j] + xmin * xi[j]) */
2555: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2556: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2557: #ifdef DEBUG
1.224 brouard 2558: 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);
2559: 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);
2560: #endif
2561: #ifdef LINMINORIGINAL
2562: #else
2563: }
1.126 brouard 2564: #endif
1.191 brouard 2565: #ifdef DEBUGLINMIN
2566: printf("linmin end ");
1.202 brouard 2567: fprintf(ficlog,"linmin end ");
1.191 brouard 2568: #endif
1.126 brouard 2569: for (j=1;j<=n;j++) {
1.203 brouard 2570: #ifdef LINMINORIGINAL
2571: xi[j] *= xmin;
2572: #else
2573: #ifdef DEBUGLINMIN
2574: if(xxs <1.0)
2575: printf(" before xi[%d]=%12.8f", j,xi[j]);
2576: #endif
2577: 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) */
2578: #ifdef DEBUGLINMIN
2579: if(xxs <1.0)
2580: 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 );
2581: #endif
2582: #endif
1.187 brouard 2583: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2584: }
1.191 brouard 2585: #ifdef DEBUGLINMIN
1.203 brouard 2586: printf("\n");
1.191 brouard 2587: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2588: 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 2589: for (j=1;j<=n;j++) {
1.202 brouard 2590: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2591: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2592: if(j % ncovmodel == 0){
1.191 brouard 2593: printf("\n");
1.202 brouard 2594: fprintf(ficlog,"\n");
2595: }
1.191 brouard 2596: }
1.203 brouard 2597: #else
1.191 brouard 2598: #endif
1.126 brouard 2599: free_vector(xicom,1,n);
2600: free_vector(pcom,1,n);
2601: }
2602:
2603:
2604: /*************** powell ************************/
1.162 brouard 2605: /*
1.317 brouard 2606: Minimization of a function func of n variables. Input consists in an initial starting point
2607: p[1..n] ; an initial matrix xi[1..n][1..n] whose columns contain the initial set of di-
2608: rections (usually the n unit vectors); and ftol, the fractional tolerance in the function value
2609: such that failure to decrease by more than this amount in one iteration signals doneness. On
1.162 brouard 2610: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2611: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2612: */
1.224 brouard 2613: #ifdef LINMINORIGINAL
2614: #else
2615: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2616: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2617: #endif
1.126 brouard 2618: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2619: double (*func)(double []))
2620: {
1.224 brouard 2621: #ifdef LINMINORIGINAL
2622: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2623: double (*func)(double []));
1.224 brouard 2624: #else
1.241 brouard 2625: void linmin(double p[], double xi[], int n, double *fret,
2626: double (*func)(double []),int *flat);
1.224 brouard 2627: #endif
1.239 brouard 2628: int i,ibig,j,jk,k;
1.126 brouard 2629: double del,t,*pt,*ptt,*xit;
1.181 brouard 2630: double directest;
1.126 brouard 2631: double fp,fptt;
2632: double *xits;
2633: int niterf, itmp;
1.349 brouard 2634: int Bigter=0, nBigterf=1;
2635:
1.126 brouard 2636: pt=vector(1,n);
2637: ptt=vector(1,n);
2638: xit=vector(1,n);
2639: xits=vector(1,n);
2640: *fret=(*func)(p);
2641: for (j=1;j<=n;j++) pt[j]=p[j];
1.338 brouard 2642: rcurr_time = time(NULL);
2643: fp=(*fret); /* Initialisation */
1.126 brouard 2644: for (*iter=1;;++(*iter)) {
2645: ibig=0;
2646: del=0.0;
1.157 brouard 2647: rlast_time=rcurr_time;
1.349 brouard 2648: rlast_btime=rcurr_time;
1.157 brouard 2649: /* (void) gettimeofday(&curr_time,&tzp); */
2650: rcurr_time = time(NULL);
2651: curr_time = *localtime(&rcurr_time);
1.337 brouard 2652: /* 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); */
2653: /* fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f gain=%.12f=%.3g %ld sec. %ld sec.",*iter,*fret, fp-*fret,fp-*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog); */
1.349 brouard 2654: Bigter=(*iter - *iter % ncovmodel)/ncovmodel +1; /* Big iteration, i.e on ncovmodel cycle */
2655: printf("\nPowell iter=%d Big Iter=%d -2*LL=%.12f gain=%.3lg %ld sec. %ld sec.",*iter,Bigter,*fret,fp-*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
2656: fprintf(ficlog,"\nPowell iter=%d Big Iter=%d -2*LL=%.12f gain=%.3lg %ld sec. %ld sec.",*iter,Bigter,*fret,fp-*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
2657: fprintf(ficrespow,"%d %d %.12f %d",*iter,Bigter, *fret,curr_time.tm_sec-start_time.tm_sec);
1.324 brouard 2658: fp=(*fret); /* From former iteration or initial value */
1.192 brouard 2659: for (i=1;i<=n;i++) {
1.126 brouard 2660: fprintf(ficrespow," %.12lf", p[i]);
2661: }
1.239 brouard 2662: fprintf(ficrespow,"\n");fflush(ficrespow);
2663: printf("\n#model= 1 + age ");
2664: fprintf(ficlog,"\n#model= 1 + age ");
2665: if(nagesqr==1){
1.241 brouard 2666: printf(" + age*age ");
2667: fprintf(ficlog," + age*age ");
1.239 brouard 2668: }
2669: for(j=1;j <=ncovmodel-2;j++){
2670: if(Typevar[j]==0) {
2671: printf(" + V%d ",Tvar[j]);
2672: fprintf(ficlog," + V%d ",Tvar[j]);
2673: }else if(Typevar[j]==1) {
2674: printf(" + V%d*age ",Tvar[j]);
2675: fprintf(ficlog," + V%d*age ",Tvar[j]);
2676: }else if(Typevar[j]==2) {
2677: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2678: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 2679: }else if(Typevar[j]==3) {
2680: printf(" + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2681: fprintf(ficlog," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.239 brouard 2682: }
2683: }
1.126 brouard 2684: printf("\n");
1.239 brouard 2685: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2686: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2687: fprintf(ficlog,"\n");
1.239 brouard 2688: for(i=1,jk=1; i <=nlstate; i++){
2689: for(k=1; k <=(nlstate+ndeath); k++){
2690: if (k != i) {
2691: printf("%d%d ",i,k);
2692: fprintf(ficlog,"%d%d ",i,k);
2693: for(j=1; j <=ncovmodel; j++){
2694: printf("%12.7f ",p[jk]);
2695: fprintf(ficlog,"%12.7f ",p[jk]);
2696: jk++;
2697: }
2698: printf("\n");
2699: fprintf(ficlog,"\n");
2700: }
2701: }
2702: }
1.241 brouard 2703: if(*iter <=3 && *iter >1){
1.157 brouard 2704: tml = *localtime(&rcurr_time);
2705: strcpy(strcurr,asctime(&tml));
2706: rforecast_time=rcurr_time;
1.126 brouard 2707: itmp = strlen(strcurr);
2708: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2709: strcurr[itmp-1]='\0';
1.162 brouard 2710: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2711: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.349 brouard 2712: for(nBigterf=1;nBigterf<=31;nBigterf+=10){
2713: niterf=nBigterf*ncovmodel;
2714: /* rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time); */
1.241 brouard 2715: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2716: forecast_time = *localtime(&rforecast_time);
2717: strcpy(strfor,asctime(&forecast_time));
2718: itmp = strlen(strfor);
2719: if(strfor[itmp-1]=='\n')
2720: strfor[itmp-1]='\0';
1.349 brouard 2721: printf(" - if your program needs %d BIG iterations (%d iterations) to converge, convergence will be \n reached in %s i.e.\n on %s (current time is %s);\n",nBigterf, niterf, asc_diff_time(rforecast_time-rcurr_time,tmpout),strfor,strcurr);
2722: fprintf(ficlog," - if your program needs %d BIG iterations (%d iterations) to converge, convergence will be \n reached in %s i.e.\n on %s (current time is %s);\n",nBigterf, niterf, asc_diff_time(rforecast_time-rcurr_time,tmpout),strfor,strcurr);
1.126 brouard 2723: }
2724: }
1.187 brouard 2725: for (i=1;i<=n;i++) { /* For each direction i */
2726: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2727: fptt=(*fret);
2728: #ifdef DEBUG
1.203 brouard 2729: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2730: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2731: #endif
1.203 brouard 2732: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2733: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2734: #ifdef LINMINORIGINAL
1.188 brouard 2735: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2736: #else
2737: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2738: flatdir[i]=flat; /* Function is vanishing in that direction i */
2739: #endif
2740: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2741: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2742: /* because that direction will be replaced unless the gain del is small */
2743: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2744: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2745: /* with the new direction. */
2746: del=fabs(fptt-(*fret));
2747: ibig=i;
1.126 brouard 2748: }
2749: #ifdef DEBUG
2750: printf("%d %.12e",i,(*fret));
2751: fprintf(ficlog,"%d %.12e",i,(*fret));
2752: for (j=1;j<=n;j++) {
1.224 brouard 2753: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2754: printf(" x(%d)=%.12e",j,xit[j]);
2755: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2756: }
2757: for(j=1;j<=n;j++) {
1.225 brouard 2758: printf(" p(%d)=%.12e",j,p[j]);
2759: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2760: }
2761: printf("\n");
2762: fprintf(ficlog,"\n");
2763: #endif
1.187 brouard 2764: } /* end loop on each direction i */
2765: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2766: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2767: /* New value of last point Pn is not computed, P(n-1) */
1.319 brouard 2768: for(j=1;j<=n;j++) {
2769: if(flatdir[j] >0){
2770: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2771: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
1.302 brouard 2772: }
1.319 brouard 2773: /* printf("\n"); */
2774: /* fprintf(ficlog,"\n"); */
2775: }
1.243 brouard 2776: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2777: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2778: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2779: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2780: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2781: /* decreased of more than 3.84 */
2782: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2783: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2784: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2785:
1.188 brouard 2786: /* Starting the program with initial values given by a former maximization will simply change */
2787: /* the scales of the directions and the directions, because the are reset to canonical directions */
2788: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2789: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2790: #ifdef DEBUG
2791: int k[2],l;
2792: k[0]=1;
2793: k[1]=-1;
2794: printf("Max: %.12e",(*func)(p));
2795: fprintf(ficlog,"Max: %.12e",(*func)(p));
2796: for (j=1;j<=n;j++) {
2797: printf(" %.12e",p[j]);
2798: fprintf(ficlog," %.12e",p[j]);
2799: }
2800: printf("\n");
2801: fprintf(ficlog,"\n");
2802: for(l=0;l<=1;l++) {
2803: for (j=1;j<=n;j++) {
2804: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2805: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2806: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2807: }
2808: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2809: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2810: }
2811: #endif
2812:
2813: free_vector(xit,1,n);
2814: free_vector(xits,1,n);
2815: free_vector(ptt,1,n);
2816: free_vector(pt,1,n);
2817: return;
1.192 brouard 2818: } /* enough precision */
1.240 brouard 2819: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2820: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2821: ptt[j]=2.0*p[j]-pt[j];
2822: xit[j]=p[j]-pt[j];
2823: pt[j]=p[j];
2824: }
1.181 brouard 2825: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2826: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2827: if (*iter <=4) {
1.225 brouard 2828: #else
2829: #endif
1.224 brouard 2830: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2831: #else
1.161 brouard 2832: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2833: #endif
1.162 brouard 2834: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2835: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2836: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2837: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2838: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2839: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2840: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2841: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2842: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2843: /* Even if f3 <f1, directest can be negative and t >0 */
2844: /* mu² and del² are equal when f3=f1 */
2845: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2846: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2847: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2848: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2849: #ifdef NRCORIGINAL
2850: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2851: #else
2852: 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 2853: t= t- del*SQR(fp-fptt);
1.183 brouard 2854: #endif
1.202 brouard 2855: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2856: #ifdef DEBUG
1.181 brouard 2857: 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);
2858: 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 2859: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2860: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2861: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2862: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2863: 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);
2864: 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);
2865: #endif
1.183 brouard 2866: #ifdef POWELLORIGINAL
2867: if (t < 0.0) { /* Then we use it for new direction */
2868: #else
1.182 brouard 2869: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2870: 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 2871: 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 2872: 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 2873: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2874: }
1.181 brouard 2875: if (directest < 0.0) { /* Then we use it for new direction */
2876: #endif
1.191 brouard 2877: #ifdef DEBUGLINMIN
1.234 brouard 2878: printf("Before linmin in direction P%d-P0\n",n);
2879: for (j=1;j<=n;j++) {
2880: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2881: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2882: if(j % ncovmodel == 0){
2883: printf("\n");
2884: fprintf(ficlog,"\n");
2885: }
2886: }
1.224 brouard 2887: #endif
2888: #ifdef LINMINORIGINAL
1.234 brouard 2889: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2890: #else
1.234 brouard 2891: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2892: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2893: #endif
1.234 brouard 2894:
1.191 brouard 2895: #ifdef DEBUGLINMIN
1.234 brouard 2896: for (j=1;j<=n;j++) {
2897: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2898: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2899: if(j % ncovmodel == 0){
2900: printf("\n");
2901: fprintf(ficlog,"\n");
2902: }
2903: }
1.224 brouard 2904: #endif
1.234 brouard 2905: for (j=1;j<=n;j++) {
2906: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2907: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2908: }
1.224 brouard 2909: #ifdef LINMINORIGINAL
2910: #else
1.234 brouard 2911: for (j=1, flatd=0;j<=n;j++) {
2912: if(flatdir[j]>0)
2913: flatd++;
2914: }
2915: if(flatd >0){
1.255 brouard 2916: printf("%d flat directions: ",flatd);
2917: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2918: for (j=1;j<=n;j++) {
2919: if(flatdir[j]>0){
2920: printf("%d ",j);
2921: fprintf(ficlog,"%d ",j);
2922: }
2923: }
2924: printf("\n");
2925: fprintf(ficlog,"\n");
1.319 brouard 2926: #ifdef FLATSUP
2927: free_vector(xit,1,n);
2928: free_vector(xits,1,n);
2929: free_vector(ptt,1,n);
2930: free_vector(pt,1,n);
2931: return;
2932: #endif
1.234 brouard 2933: }
1.191 brouard 2934: #endif
1.234 brouard 2935: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2936: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2937:
1.126 brouard 2938: #ifdef DEBUG
1.234 brouard 2939: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2940: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2941: for(j=1;j<=n;j++){
2942: printf(" %lf",xit[j]);
2943: fprintf(ficlog," %lf",xit[j]);
2944: }
2945: printf("\n");
2946: fprintf(ficlog,"\n");
1.126 brouard 2947: #endif
1.192 brouard 2948: } /* end of t or directest negative */
1.224 brouard 2949: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2950: #else
1.234 brouard 2951: } /* end if (fptt < fp) */
1.192 brouard 2952: #endif
1.225 brouard 2953: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2954: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2955: #else
1.224 brouard 2956: #endif
1.234 brouard 2957: } /* loop iteration */
1.126 brouard 2958: }
1.234 brouard 2959:
1.126 brouard 2960: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2961:
1.235 brouard 2962: 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 2963: {
1.338 brouard 2964: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij . Nicely done
1.279 brouard 2965: * (and selected quantitative values in nres)
2966: * by left multiplying the unit
2967: * matrix by transitions matrix until convergence is reached with precision ftolpl
2968: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2969: * Wx is row vector: population in state 1, population in state 2, population dead
2970: * or prevalence in state 1, prevalence in state 2, 0
2971: * newm is the matrix after multiplications, its rows are identical at a factor.
2972: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2973: * Output is prlim.
2974: * Initial matrix pimij
2975: */
1.206 brouard 2976: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2977: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2978: /* 0, 0 , 1} */
2979: /*
2980: * and after some iteration: */
2981: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2982: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2983: /* 0, 0 , 1} */
2984: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2985: /* {0.51571254859325999, 0.4842874514067399, */
2986: /* 0.51326036147820708, 0.48673963852179264} */
2987: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2988:
1.332 brouard 2989: int i, ii,j,k, k1;
1.209 brouard 2990: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2991: /* double **matprod2(); */ /* test */
1.218 brouard 2992: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2993: double **newm;
1.209 brouard 2994: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2995: int ncvloop=0;
1.288 brouard 2996: int first=0;
1.169 brouard 2997:
1.209 brouard 2998: min=vector(1,nlstate);
2999: max=vector(1,nlstate);
3000: meandiff=vector(1,nlstate);
3001:
1.218 brouard 3002: /* Starting with matrix unity */
1.126 brouard 3003: for (ii=1;ii<=nlstate+ndeath;ii++)
3004: for (j=1;j<=nlstate+ndeath;j++){
3005: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3006: }
1.169 brouard 3007:
3008: cov[1]=1.;
3009:
3010: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 3011: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 3012: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 3013: ncvloop++;
1.126 brouard 3014: newm=savm;
3015: /* Covariates have to be included here again */
1.138 brouard 3016: cov[2]=agefin;
1.319 brouard 3017: if(nagesqr==1){
3018: cov[3]= agefin*agefin;
3019: }
1.332 brouard 3020: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
3021: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
3022: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3023: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3024: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
3025: }else{
3026: cov[2+nagesqr+k1]=precov[nres][k1];
3027: }
3028: }/* End of loop on model equation */
3029:
3030: /* Start of old code (replaced by a loop on position in the model equation */
3031: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only of the model *\/ */
3032: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
3033: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; *\/ */
3034: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TnsdVar[TvarsD[k]])]; */
3035: /* /\* model = 1 +age + V1*V3 + age*V1 + V2 + V1 + age*V2 + V3 + V3*age + V1*V2 */
3036: /* * k 1 2 3 4 5 6 7 8 */
3037: /* *cov[] 1 2 3 4 5 6 7 8 9 10 */
3038: /* *TypeVar[k] 2 1 0 0 1 0 1 2 */
3039: /* *Dummy[k] 0 2 0 0 2 0 2 0 */
3040: /* *Tvar[k] 4 1 2 1 2 3 3 5 */
3041: /* *nsd=3 (1) (2) (3) */
3042: /* *TvarsD[nsd] [1]=2 1 3 */
3043: /* *TnsdVar [2]=2 [1]=1 [3]=3 */
3044: /* *TvarsDind[nsd](=k) [1]=3 [2]=4 [3]=6 */
3045: /* *Tage[] [1]=1 [2]=2 [3]=3 */
3046: /* *Tvard[] [1][1]=1 [2][1]=1 */
3047: /* * [1][2]=3 [2][2]=2 */
3048: /* *Tprod[](=k) [1]=1 [2]=8 */
3049: /* *TvarsDp(=Tvar) [1]=1 [2]=2 [3]=3 [4]=5 */
3050: /* *TvarD (=k) [1]=1 [2]=3 [3]=4 [3]=6 [4]=6 */
3051: /* *TvarsDpType */
3052: /* *si model= 1 + age + V3 + V2*age + V2 + V3*age */
3053: /* * nsd=1 (1) (2) */
3054: /* *TvarsD[nsd] 3 2 */
3055: /* *TnsdVar (3)=1 (2)=2 */
3056: /* *TvarsDind[nsd](=k) [1]=1 [2]=3 */
3057: /* *Tage[] [1]=2 [2]= 3 */
3058: /* *\/ */
3059: /* /\* cov[++k1]=nbcode[TvarsD[k]][codtabm(ij,k)]; *\/ */
3060: /* /\* 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)); *\/ */
3061: /* } */
3062: /* for (k=1; k<=nsq;k++) { /\* For single quantitative varying covariates only of the model *\/ */
3063: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3064: /* /\* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline *\/ */
3065: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
3066: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][resultmodel[nres][k1]] */
3067: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
3068: /* /\* 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]); *\/ */
3069: /* } */
3070: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
3071: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
3072: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3073: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
3074: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
3075: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3076: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
3077: /* } */
3078: /* /\* 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]); *\/ */
3079: /* } */
3080: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
3081: /* /\* 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]); *\/ */
3082: /* if(Dummy[Tvard[k][1]]==0){ */
3083: /* if(Dummy[Tvard[k][2]]==0){ */
3084: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3085: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3086: /* }else{ */
3087: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3088: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
3089: /* } */
3090: /* }else{ */
3091: /* if(Dummy[Tvard[k][2]]==0){ */
3092: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3093: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
3094: /* }else{ */
3095: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3096: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
3097: /* } */
3098: /* } */
3099: /* } /\* End product without age *\/ */
3100: /* ENd of old code */
1.138 brouard 3101: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
3102: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
3103: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 3104: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3105: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.319 brouard 3106: /* age and covariate values of ij are in 'cov' */
1.142 brouard 3107: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 3108:
1.126 brouard 3109: savm=oldm;
3110: oldm=newm;
1.209 brouard 3111:
3112: for(j=1; j<=nlstate; j++){
3113: max[j]=0.;
3114: min[j]=1.;
3115: }
3116: for(i=1;i<=nlstate;i++){
3117: sumnew=0;
3118: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
3119: for(j=1; j<=nlstate; j++){
3120: prlim[i][j]= newm[i][j]/(1-sumnew);
3121: max[j]=FMAX(max[j],prlim[i][j]);
3122: min[j]=FMIN(min[j],prlim[i][j]);
3123: }
3124: }
3125:
1.126 brouard 3126: maxmax=0.;
1.209 brouard 3127: for(j=1; j<=nlstate; j++){
3128: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
3129: maxmax=FMAX(maxmax,meandiff[j]);
3130: /* 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 3131: } /* j loop */
1.203 brouard 3132: *ncvyear= (int)age- (int)agefin;
1.208 brouard 3133: /* 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 3134: if(maxmax < ftolpl){
1.209 brouard 3135: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
3136: free_vector(min,1,nlstate);
3137: free_vector(max,1,nlstate);
3138: free_vector(meandiff,1,nlstate);
1.126 brouard 3139: return prlim;
3140: }
1.288 brouard 3141: } /* agefin loop */
1.208 brouard 3142: /* After some age loop it doesn't converge */
1.288 brouard 3143: if(!first){
3144: first=1;
3145: 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 3146: 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);
3147: }else if (first >=1 && first <10){
3148: 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);
3149: first++;
3150: }else if (first ==10){
3151: 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);
3152: 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");
3153: fprintf(ficlog,"Warning: the stable prevalence no convergence; too many cases, giving up noticing, even in log file\n");
3154: first++;
1.288 brouard 3155: }
3156:
1.209 brouard 3157: /* 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); */
3158: free_vector(min,1,nlstate);
3159: free_vector(max,1,nlstate);
3160: free_vector(meandiff,1,nlstate);
1.208 brouard 3161:
1.169 brouard 3162: return prlim; /* should not reach here */
1.126 brouard 3163: }
3164:
1.217 brouard 3165:
3166: /**** Back Prevalence limit (stable or period prevalence) ****************/
3167:
1.218 brouard 3168: /* 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) */
3169: /* 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 3170: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 3171: {
1.264 brouard 3172: /* 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 3173: matrix by transitions matrix until convergence is reached with precision ftolpl */
3174: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
3175: /* Wx is row vector: population in state 1, population in state 2, population dead */
3176: /* or prevalence in state 1, prevalence in state 2, 0 */
3177: /* newm is the matrix after multiplications, its rows are identical at a factor */
3178: /* Initial matrix pimij */
3179: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
3180: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
3181: /* 0, 0 , 1} */
3182: /*
3183: * and after some iteration: */
3184: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
3185: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
3186: /* 0, 0 , 1} */
3187: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
3188: /* {0.51571254859325999, 0.4842874514067399, */
3189: /* 0.51326036147820708, 0.48673963852179264} */
3190: /* If we start from prlim again, prlim tends to a constant matrix */
3191:
1.332 brouard 3192: int i, ii,j,k, k1;
1.247 brouard 3193: int first=0;
1.217 brouard 3194: double *min, *max, *meandiff, maxmax,sumnew=0.;
3195: /* double **matprod2(); */ /* test */
3196: double **out, cov[NCOVMAX+1], **bmij();
3197: double **newm;
1.218 brouard 3198: double **dnewm, **doldm, **dsavm; /* for use */
3199: double **oldm, **savm; /* for use */
3200:
1.217 brouard 3201: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
3202: int ncvloop=0;
3203:
3204: min=vector(1,nlstate);
3205: max=vector(1,nlstate);
3206: meandiff=vector(1,nlstate);
3207:
1.266 brouard 3208: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
3209: oldm=oldms; savm=savms;
3210:
3211: /* Starting with matrix unity */
3212: for (ii=1;ii<=nlstate+ndeath;ii++)
3213: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 3214: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3215: }
3216:
3217: cov[1]=1.;
3218:
3219: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3220: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 3221: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 3222: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
3223: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 3224: ncvloop++;
1.218 brouard 3225: newm=savm; /* oldm should be kept from previous iteration or unity at start */
3226: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 3227: /* Covariates have to be included here again */
3228: cov[2]=agefin;
1.319 brouard 3229: if(nagesqr==1){
1.217 brouard 3230: cov[3]= agefin*agefin;;
1.319 brouard 3231: }
1.332 brouard 3232: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3233: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3234: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.242 brouard 3235: }else{
1.332 brouard 3236: cov[2+nagesqr+k1]=precov[nres][k1];
1.242 brouard 3237: }
1.332 brouard 3238: }/* End of loop on model equation */
3239:
3240: /* Old code */
3241:
3242: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
3243: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
3244: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; */
3245: /* /\* 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)); *\/ */
3246: /* } */
3247: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
3248: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
3249: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
3250: /* /\* /\\* 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])]); *\\/ *\/ */
3251: /* /\* } *\/ */
3252: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
3253: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3254: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
3255: /* /\* 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]); *\/ */
3256: /* } */
3257: /* /\* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; *\/ */
3258: /* /\* for (k=1; k<=cptcovprod;k++) /\\* Useless *\\/ *\/ */
3259: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\\/ *\/ */
3260: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3261: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
3262: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age *\\/ ERROR ???*\/ */
3263: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
3264: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3265: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
3266: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3267: /* } */
3268: /* /\* 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]); *\/ */
3269: /* } */
3270: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
3271: /* /\* 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]); *\/ */
3272: /* if(Dummy[Tvard[k][1]]==0){ */
3273: /* if(Dummy[Tvard[k][2]]==0){ */
3274: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3275: /* }else{ */
3276: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3277: /* } */
3278: /* }else{ */
3279: /* if(Dummy[Tvard[k][2]]==0){ */
3280: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3281: /* }else{ */
3282: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3283: /* } */
3284: /* } */
3285: /* } */
1.217 brouard 3286:
3287: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
3288: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
3289: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
3290: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3291: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 3292: /* ij should be linked to the correct index of cov */
3293: /* age and covariate values ij are in 'cov', but we need to pass
3294: * ij for the observed prevalence at age and status and covariate
3295: * number: prevacurrent[(int)agefin][ii][ij]
3296: */
3297: /* 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 *\/ */
3298: /* 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 *\/ */
3299: 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 3300: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 3301: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
3302: /* for(i=1; i<=nlstate+ndeath; i++) { */
3303: /* printf("%d newm= ",i); */
3304: /* for(j=1;j<=nlstate+ndeath;j++) { */
3305: /* printf("%f ",newm[i][j]); */
3306: /* } */
3307: /* printf("oldm * "); */
3308: /* for(j=1;j<=nlstate+ndeath;j++) { */
3309: /* printf("%f ",oldm[i][j]); */
3310: /* } */
1.268 brouard 3311: /* printf(" bmmij "); */
1.266 brouard 3312: /* for(j=1;j<=nlstate+ndeath;j++) { */
3313: /* printf("%f ",pmmij[i][j]); */
3314: /* } */
3315: /* printf("\n"); */
3316: /* } */
3317: /* } */
1.217 brouard 3318: savm=oldm;
3319: oldm=newm;
1.266 brouard 3320:
1.217 brouard 3321: for(j=1; j<=nlstate; j++){
3322: max[j]=0.;
3323: min[j]=1.;
3324: }
3325: for(j=1; j<=nlstate; j++){
3326: for(i=1;i<=nlstate;i++){
1.234 brouard 3327: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
3328: bprlim[i][j]= newm[i][j];
3329: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
3330: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 3331: }
3332: }
1.218 brouard 3333:
1.217 brouard 3334: maxmax=0.;
3335: for(i=1; i<=nlstate; i++){
1.318 brouard 3336: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column, could be nan! */
1.217 brouard 3337: maxmax=FMAX(maxmax,meandiff[i]);
3338: /* 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 3339: } /* i loop */
1.217 brouard 3340: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 3341: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3342: if(maxmax < ftolpl){
1.220 brouard 3343: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3344: free_vector(min,1,nlstate);
3345: free_vector(max,1,nlstate);
3346: free_vector(meandiff,1,nlstate);
3347: return bprlim;
3348: }
1.288 brouard 3349: } /* agefin loop */
1.217 brouard 3350: /* After some age loop it doesn't converge */
1.288 brouard 3351: if(!first){
1.247 brouard 3352: first=1;
3353: 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\
3354: 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);
3355: }
3356: 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 3357: 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);
3358: /* 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); */
3359: free_vector(min,1,nlstate);
3360: free_vector(max,1,nlstate);
3361: free_vector(meandiff,1,nlstate);
3362:
3363: return bprlim; /* should not reach here */
3364: }
3365:
1.126 brouard 3366: /*************** transition probabilities ***************/
3367:
3368: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
3369: {
1.138 brouard 3370: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 3371: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 3372: model to the ncovmodel covariates (including constant and age).
3373: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3374: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3375: ncth covariate in the global vector x is given by the formula:
3376: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3377: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3378: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3379: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 3380: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 3381: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 3382: Sum on j ps[i][j] should equal to 1.
1.138 brouard 3383: */
3384: double s1, lnpijopii;
1.126 brouard 3385: /*double t34;*/
1.164 brouard 3386: int i,j, nc, ii, jj;
1.126 brouard 3387:
1.223 brouard 3388: for(i=1; i<= nlstate; i++){
3389: for(j=1; j<i;j++){
3390: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3391: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3392: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3393: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3394: }
3395: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3396: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3397: }
3398: for(j=i+1; j<=nlstate+ndeath;j++){
3399: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3400: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3401: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3402: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3403: }
3404: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3405: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3406: }
3407: }
1.218 brouard 3408:
1.223 brouard 3409: for(i=1; i<= nlstate; i++){
3410: s1=0;
3411: for(j=1; j<i; j++){
1.339 brouard 3412: /* printf("debug1 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 3413: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3414: }
3415: for(j=i+1; j<=nlstate+ndeath; j++){
1.339 brouard 3416: /* printf("debug2 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 3417: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3418: }
3419: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3420: ps[i][i]=1./(s1+1.);
3421: /* Computing other pijs */
3422: for(j=1; j<i; j++)
1.325 brouard 3423: ps[i][j]= exp(ps[i][j])*ps[i][i];/* Bug valgrind */
1.223 brouard 3424: for(j=i+1; j<=nlstate+ndeath; j++)
3425: ps[i][j]= exp(ps[i][j])*ps[i][i];
3426: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3427: } /* end i */
1.218 brouard 3428:
1.223 brouard 3429: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3430: for(jj=1; jj<= nlstate+ndeath; jj++){
3431: ps[ii][jj]=0;
3432: ps[ii][ii]=1;
3433: }
3434: }
1.294 brouard 3435:
3436:
1.223 brouard 3437: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3438: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3439: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3440: /* } */
3441: /* printf("\n "); */
3442: /* } */
3443: /* printf("\n ");printf("%lf ",cov[2]);*/
3444: /*
3445: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 3446: goto end;*/
1.266 brouard 3447: return ps; /* Pointer is unchanged since its call */
1.126 brouard 3448: }
3449:
1.218 brouard 3450: /*************** backward transition probabilities ***************/
3451:
3452: /* 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 ) */
3453: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
3454: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
3455: {
1.302 brouard 3456: /* 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 3457: * 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 3458: */
1.218 brouard 3459: int i, ii, j,k;
1.222 brouard 3460:
3461: double **out, **pmij();
3462: double sumnew=0.;
1.218 brouard 3463: double agefin;
1.292 brouard 3464: 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 3465: double **dnewm, **dsavm, **doldm;
3466: double **bbmij;
3467:
1.218 brouard 3468: doldm=ddoldms; /* global pointers */
1.222 brouard 3469: dnewm=ddnewms;
3470: dsavm=ddsavms;
1.318 brouard 3471:
3472: /* Debug */
3473: /* printf("Bmij ij=%d, cov[2}=%f\n", ij, cov[2]); */
1.222 brouard 3474: agefin=cov[2];
1.268 brouard 3475: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 3476: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 3477: the observed prevalence (with this covariate ij) at beginning of transition */
3478: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 3479:
3480: /* P_x */
1.325 brouard 3481: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm *//* Bug valgrind */
1.268 brouard 3482: /* outputs pmmij which is a stochastic matrix in row */
3483:
3484: /* Diag(w_x) */
1.292 brouard 3485: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 3486: sumnew=0.;
1.269 brouard 3487: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 3488: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.297 brouard 3489: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 3490: sumnew+=prevacurrent[(int)agefin][ii][ij];
3491: }
3492: if(sumnew >0.01){ /* At least some value in the prevalence */
3493: for (ii=1;ii<=nlstate+ndeath;ii++){
3494: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 3495: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 3496: }
3497: }else{
3498: for (ii=1;ii<=nlstate+ndeath;ii++){
3499: for (j=1;j<=nlstate+ndeath;j++)
3500: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
3501: }
3502: /* if(sumnew <0.9){ */
3503: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3504: /* } */
3505: }
3506: k3=0.0; /* We put the last diagonal to 0 */
3507: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3508: doldm[ii][ii]= k3;
3509: }
3510: /* End doldm, At the end doldm is diag[(w_i)] */
3511:
1.292 brouard 3512: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
3513: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 3514:
1.292 brouard 3515: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 3516: /* 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 3517: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3518: sumnew=0.;
1.222 brouard 3519: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3520: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3521: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3522: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3523: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3524: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3525: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3526: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3527: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3528: /* }else */
1.268 brouard 3529: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3530: } /*End ii */
3531: } /* 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 */
3532:
1.292 brouard 3533: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 3534: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3535: /* end bmij */
1.266 brouard 3536: return ps; /*pointer is unchanged */
1.218 brouard 3537: }
1.217 brouard 3538: /*************** transition probabilities ***************/
3539:
1.218 brouard 3540: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3541: {
3542: /* According to parameters values stored in x and the covariate's values stored in cov,
3543: computes the probability to be observed in state j being in state i by appying the
3544: model to the ncovmodel covariates (including constant and age).
3545: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3546: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3547: ncth covariate in the global vector x is given by the formula:
3548: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3549: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3550: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3551: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3552: Outputs ps[i][j] the probability to be observed in j being in j according to
3553: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3554: */
3555: double s1, lnpijopii;
3556: /*double t34;*/
3557: int i,j, nc, ii, jj;
3558:
1.234 brouard 3559: for(i=1; i<= nlstate; i++){
3560: for(j=1; j<i;j++){
3561: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3562: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3563: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3564: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3565: }
3566: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3567: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3568: }
3569: for(j=i+1; j<=nlstate+ndeath;j++){
3570: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3571: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3572: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3573: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3574: }
3575: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3576: }
3577: }
3578:
3579: for(i=1; i<= nlstate; i++){
3580: s1=0;
3581: for(j=1; j<i; j++){
3582: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3583: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3584: }
3585: for(j=i+1; j<=nlstate+ndeath; j++){
3586: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3587: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3588: }
3589: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3590: ps[i][i]=1./(s1+1.);
3591: /* Computing other pijs */
3592: for(j=1; j<i; j++)
3593: ps[i][j]= exp(ps[i][j])*ps[i][i];
3594: for(j=i+1; j<=nlstate+ndeath; j++)
3595: ps[i][j]= exp(ps[i][j])*ps[i][i];
3596: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3597: } /* end i */
3598:
3599: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3600: for(jj=1; jj<= nlstate+ndeath; jj++){
3601: ps[ii][jj]=0;
3602: ps[ii][ii]=1;
3603: }
3604: }
1.296 brouard 3605: /* Added for prevbcast */ /* Transposed matrix too */
1.234 brouard 3606: for(jj=1; jj<= nlstate+ndeath; jj++){
3607: s1=0.;
3608: for(ii=1; ii<= nlstate+ndeath; ii++){
3609: s1+=ps[ii][jj];
3610: }
3611: for(ii=1; ii<= nlstate; ii++){
3612: ps[ii][jj]=ps[ii][jj]/s1;
3613: }
3614: }
3615: /* Transposition */
3616: for(jj=1; jj<= nlstate+ndeath; jj++){
3617: for(ii=jj; ii<= nlstate+ndeath; ii++){
3618: s1=ps[ii][jj];
3619: ps[ii][jj]=ps[jj][ii];
3620: ps[jj][ii]=s1;
3621: }
3622: }
3623: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3624: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3625: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3626: /* } */
3627: /* printf("\n "); */
3628: /* } */
3629: /* printf("\n ");printf("%lf ",cov[2]);*/
3630: /*
3631: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3632: goto end;*/
3633: return ps;
1.217 brouard 3634: }
3635:
3636:
1.126 brouard 3637: /**************** Product of 2 matrices ******************/
3638:
1.145 brouard 3639: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3640: {
3641: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3642: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3643: /* in, b, out are matrice of pointers which should have been initialized
3644: before: only the contents of out is modified. The function returns
3645: a pointer to pointers identical to out */
1.145 brouard 3646: int i, j, k;
1.126 brouard 3647: for(i=nrl; i<= nrh; i++)
1.145 brouard 3648: for(k=ncolol; k<=ncoloh; k++){
3649: out[i][k]=0.;
3650: for(j=ncl; j<=nch; j++)
3651: out[i][k] +=in[i][j]*b[j][k];
3652: }
1.126 brouard 3653: return out;
3654: }
3655:
3656:
3657: /************* Higher Matrix Product ***************/
3658:
1.235 brouard 3659: 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 3660: {
1.336 brouard 3661: /* Already optimized with precov.
3662: 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 3663: 'nhstepm*hstepm*stepm' months (i.e. until
3664: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3665: nhstepm*hstepm matrices.
3666: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3667: (typically every 2 years instead of every month which is too big
3668: for the memory).
3669: Model is determined by parameters x and covariates have to be
3670: included manually here.
3671:
3672: */
3673:
1.330 brouard 3674: int i, j, d, h, k, k1;
1.131 brouard 3675: double **out, cov[NCOVMAX+1];
1.126 brouard 3676: double **newm;
1.187 brouard 3677: double agexact;
1.214 brouard 3678: double agebegin, ageend;
1.126 brouard 3679:
3680: /* Hstepm could be zero and should return the unit matrix */
3681: for (i=1;i<=nlstate+ndeath;i++)
3682: for (j=1;j<=nlstate+ndeath;j++){
3683: oldm[i][j]=(i==j ? 1.0 : 0.0);
3684: po[i][j][0]=(i==j ? 1.0 : 0.0);
3685: }
3686: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3687: for(h=1; h <=nhstepm; h++){
3688: for(d=1; d <=hstepm; d++){
3689: newm=savm;
3690: /* Covariates have to be included here again */
3691: cov[1]=1.;
1.214 brouard 3692: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3693: cov[2]=agexact;
1.319 brouard 3694: if(nagesqr==1){
1.227 brouard 3695: cov[3]= agexact*agexact;
1.319 brouard 3696: }
1.330 brouard 3697: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
3698: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
3699: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3700: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3701: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
3702: }else{
3703: cov[2+nagesqr+k1]=precov[nres][k1];
3704: }
3705: }/* End of loop on model equation */
3706: /* Old code */
3707: /* if( Dummy[k1]==0 && Typevar[k1]==0 ){ /\* Single dummy *\/ */
3708: /* /\* V(Tvarsel)=Tvalsel=Tresult[nres][pos](value); V(Tvresult[nres][pos] (variable): V(variable)=value) *\/ */
3709: /* /\* for (k=1; k<=nsd;k++) { /\\* For single dummy covariates only *\\/ *\/ */
3710: /* /\* /\\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\\/ *\/ */
3711: /* /\* codtabm(ij,k) (1 & (ij-1) >> (k-1))+1 *\/ */
3712: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3713: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3714: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
3715: /* /\* nsd 1 2 3 *\/ /\* Counting single dummies covar fixed or tv *\/ */
3716: /* /\*TvarsD[nsd] 4 3 1 *\/ /\* ID of single dummy cova fixed or timevary*\/ */
3717: /* /\*TvarsDind[k] 2 3 9 *\/ /\* position K of single dummy cova *\/ */
3718: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];or [codtabm(ij,TnsdVar[TvarsD[k]] *\/ */
3719: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
3720: /* /\* 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]])); *\/ */
3721: /* 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); */
3722: /* printf("hpxij new Dummy precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3723: /* }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /\* Single quantitative variables *\/ */
3724: /* /\* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline *\/ */
3725: /* cov[2+nagesqr+k1]=Tqresult[nres][resultmodel[nres][k1]]; */
3726: /* /\* for (k=1; k<=nsq;k++) { /\\* For single varying covariates only *\\/ *\/ */
3727: /* /\* /\\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\\/ *\/ */
3728: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
3729: /* 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]]); */
3730: /* printf("hpxij new Quanti precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3731: /* }else if( Dummy[k1]==2 ){ /\* For dummy with age product *\/ */
3732: /* /\* Tvar[k1] Variable in the age product age*V1 is 1 *\/ */
3733: /* /\* [Tinvresult[nres][V1] is its value in the resultline nres *\/ */
3734: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvar[k1]]*cov[2]; */
3735: /* 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]); */
3736: /* printf("hpxij new Dummy with age product precov[nres=%d][k1=%d]=%.4f * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
3737:
3738: /* /\* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; *\/ */
3739: /* /\* for (k=1; k<=cptcovage;k++){ /\\* For product with age V1+V1*age +V4 +age*V3 *\\/ *\/ */
3740: /* /\* 1+2 Tage[1]=2 TVar[2]=1 Dummy[2]=2, Tage[2]=4 TVar[4]=3 Dummy[4]=3 quant*\/ */
3741: /* /\* *\/ */
1.330 brouard 3742: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3743: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3744: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
1.332 brouard 3745: /* /\*cptcovage=2 1 2 *\/ */
3746: /* /\*Tage[k]= 5 8 *\/ */
3747: /* }else if( Dummy[k1]==3 ){ /\* For quant with age product *\/ */
3748: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
3749: /* 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]]); */
3750: /* printf("hpxij new Quanti with age product precov[nres=%d][k1=%d] * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
3751: /* /\* if(Dummy[Tage[k]]== 2){ /\\* dummy with age *\\/ *\/ */
3752: /* /\* /\\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\\* dummy with age *\\\/ *\\/ *\/ */
3753: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\\/ *\/ */
3754: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\\/ *\/ */
3755: /* /\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\/ */
3756: /* /\* 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); *\/ */
3757: /* /\* } else if(Dummy[Tage[k]]== 3){ /\\* quantitative with age *\\/ *\/ */
3758: /* /\* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; *\/ */
3759: /* /\* } *\/ */
3760: /* /\* 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]); *\/ */
3761: /* }else if(Typevar[k1]==2 ){ /\* For product (not with age) *\/ */
3762: /* /\* for (k=1; k<=cptcovprod;k++){ /\\* For product without age *\\/ *\/ */
3763: /* /\* /\\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\\/ *\/ */
3764: /* /\* /\\* k 1 2 3 4 5 6 7 8 9 *\\/ *\/ */
3765: /* /\* /\\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\\/ *\/ */
3766: /* /\* /\\*cptcovprod=1 1 2 *\\/ *\/ */
3767: /* /\* /\\*Tprod[]= 4 7 *\\/ *\/ */
3768: /* /\* /\\*Tvard[][1] 4 1 *\\/ *\/ */
3769: /* /\* /\\*Tvard[][2] 3 2 *\\/ *\/ */
1.330 brouard 3770:
1.332 brouard 3771: /* /\* 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])]); *\/ */
3772: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3773: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]]; */
3774: /* 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]]); */
3775: /* printf("hpxij new Product no age product precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3776:
3777: /* /\* if(Dummy[Tvardk[k1][1]]==0){ *\/ */
3778: /* /\* if(Dummy[Tvardk[k1][2]]==0){ /\\* Product of dummies *\\/ *\/ */
3779: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3780: /* /\* cov[2+nagesqr+k1]=Tinvresult[nres][Tvardk[k1][1]] * Tinvresult[nres][Tvardk[k1][2]]; *\/ */
3781: /* /\* 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]])]; *\/ */
3782: /* /\* }else{ /\\* Product of dummy by quantitative *\\/ *\/ */
3783: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,TnsdVar[Tvard[k][1]])] * Tqresult[nres][k]; *\/ */
3784: /* /\* cov[2+nagesqr+k1]=Tresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]]; *\/ */
3785: /* /\* } *\/ */
3786: /* /\* }else{ /\\* Product of quantitative by...*\\/ *\/ */
3787: /* /\* if(Dummy[Tvard[k][2]]==0){ /\\* quant by dummy *\\/ *\/ */
3788: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][Tvard[k][1]]; *\\/ *\/ */
3789: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
3790: /* /\* }else{ /\\* Product of two quant *\\/ *\/ */
3791: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\\/ *\/ */
3792: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
3793: /* /\* } *\/ */
3794: /* /\* }/\\*end of products quantitative *\\/ *\/ */
3795: /* }/\*end of products *\/ */
3796: /* } /\* End of loop on model equation *\/ */
1.235 brouard 3797: /* for (k=1; k<=cptcovn;k++) */
3798: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3799: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3800: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3801: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3802: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3803:
3804:
1.126 brouard 3805: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3806: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.319 brouard 3807: /* right multiplication of oldm by the current matrix */
1.126 brouard 3808: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3809: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3810: /* if((int)age == 70){ */
3811: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3812: /* for(i=1; i<=nlstate+ndeath; i++) { */
3813: /* printf("%d pmmij ",i); */
3814: /* for(j=1;j<=nlstate+ndeath;j++) { */
3815: /* printf("%f ",pmmij[i][j]); */
3816: /* } */
3817: /* printf(" oldm "); */
3818: /* for(j=1;j<=nlstate+ndeath;j++) { */
3819: /* printf("%f ",oldm[i][j]); */
3820: /* } */
3821: /* printf("\n"); */
3822: /* } */
3823: /* } */
1.126 brouard 3824: savm=oldm;
3825: oldm=newm;
3826: }
3827: for(i=1; i<=nlstate+ndeath; i++)
3828: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3829: po[i][j][h]=newm[i][j];
3830: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3831: }
1.128 brouard 3832: /*printf("h=%d ",h);*/
1.126 brouard 3833: } /* end h */
1.267 brouard 3834: /* printf("\n H=%d \n",h); */
1.126 brouard 3835: return po;
3836: }
3837:
1.217 brouard 3838: /************* Higher Back Matrix Product ***************/
1.218 brouard 3839: /* 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 3840: 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 3841: {
1.332 brouard 3842: /* For dummy covariates given in each resultline (for historical, computes the corresponding combination ij),
3843: computes the transition matrix starting at age 'age' over
1.217 brouard 3844: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3845: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3846: nhstepm*hstepm matrices.
3847: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3848: (typically every 2 years instead of every month which is too big
1.217 brouard 3849: for the memory).
1.218 brouard 3850: Model is determined by parameters x and covariates have to be
1.266 brouard 3851: included manually here. Then we use a call to bmij(x and cov)
3852: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3853: */
1.217 brouard 3854:
1.332 brouard 3855: int i, j, d, h, k, k1;
1.266 brouard 3856: double **out, cov[NCOVMAX+1], **bmij();
3857: double **newm, ***newmm;
1.217 brouard 3858: double agexact;
3859: double agebegin, ageend;
1.222 brouard 3860: double **oldm, **savm;
1.217 brouard 3861:
1.266 brouard 3862: newmm=po; /* To be saved */
3863: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3864: /* Hstepm could be zero and should return the unit matrix */
3865: for (i=1;i<=nlstate+ndeath;i++)
3866: for (j=1;j<=nlstate+ndeath;j++){
3867: oldm[i][j]=(i==j ? 1.0 : 0.0);
3868: po[i][j][0]=(i==j ? 1.0 : 0.0);
3869: }
3870: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3871: for(h=1; h <=nhstepm; h++){
3872: for(d=1; d <=hstepm; d++){
3873: newm=savm;
3874: /* Covariates have to be included here again */
3875: cov[1]=1.;
1.271 brouard 3876: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3877: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
1.318 brouard 3878: /* Debug */
3879: /* printf("hBxij age=%lf, agexact=%lf\n", age, agexact); */
1.217 brouard 3880: cov[2]=agexact;
1.332 brouard 3881: if(nagesqr==1){
1.222 brouard 3882: cov[3]= agexact*agexact;
1.332 brouard 3883: }
3884: /** New code */
3885: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3886: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3887: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.325 brouard 3888: }else{
1.332 brouard 3889: cov[2+nagesqr+k1]=precov[nres][k1];
1.325 brouard 3890: }
1.332 brouard 3891: }/* End of loop on model equation */
3892: /** End of new code */
3893: /** This was old code */
3894: /* for (k=1; k<=nsd;k++){ /\* For single dummy covariates only *\//\* cptcovn error *\/ */
3895: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
3896: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
3897: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])];/\* Bug valgrind *\/ */
3898: /* /\* 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)); *\/ */
3899: /* } */
3900: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
3901: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3902: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
3903: /* /\* 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]); *\/ */
3904: /* } */
3905: /* for (k=1; k<=cptcovage;k++){ /\* Should start at cptcovn+1 *\//\* For product with age *\/ */
3906: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age error!!!*\\/ *\/ */
3907: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
3908: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3909: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
3910: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3911: /* } */
3912: /* /\* 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]); *\/ */
3913: /* } */
3914: /* for (k=1; k<=cptcovprod;k++){ /\* Useless because included in cptcovn *\/ */
3915: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])]*nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3916: /* if(Dummy[Tvard[k][1]]==0){ */
3917: /* if(Dummy[Tvard[k][2]]==0){ */
3918: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][1])]; */
3919: /* }else{ */
3920: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3921: /* } */
3922: /* }else{ */
3923: /* if(Dummy[Tvard[k][2]]==0){ */
3924: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3925: /* }else{ */
3926: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3927: /* } */
3928: /* } */
3929: /* } */
3930: /* /\*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*\/ */
3931: /* /\*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*\/ */
3932: /** End of old code */
3933:
1.218 brouard 3934: /* Careful transposed matrix */
1.266 brouard 3935: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3936: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3937: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3938: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.325 brouard 3939: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);/* Bug valgrind */
1.217 brouard 3940: /* if((int)age == 70){ */
3941: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3942: /* for(i=1; i<=nlstate+ndeath; i++) { */
3943: /* printf("%d pmmij ",i); */
3944: /* for(j=1;j<=nlstate+ndeath;j++) { */
3945: /* printf("%f ",pmmij[i][j]); */
3946: /* } */
3947: /* printf(" oldm "); */
3948: /* for(j=1;j<=nlstate+ndeath;j++) { */
3949: /* printf("%f ",oldm[i][j]); */
3950: /* } */
3951: /* printf("\n"); */
3952: /* } */
3953: /* } */
3954: savm=oldm;
3955: oldm=newm;
3956: }
3957: for(i=1; i<=nlstate+ndeath; i++)
3958: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3959: po[i][j][h]=newm[i][j];
1.268 brouard 3960: /* if(h==nhstepm) */
3961: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3962: }
1.268 brouard 3963: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3964: } /* end h */
1.268 brouard 3965: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3966: return po;
3967: }
3968:
3969:
1.162 brouard 3970: #ifdef NLOPT
3971: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3972: double fret;
3973: double *xt;
3974: int j;
3975: myfunc_data *d2 = (myfunc_data *) pd;
3976: /* xt = (p1-1); */
3977: xt=vector(1,n);
3978: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3979:
3980: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3981: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3982: printf("Function = %.12lf ",fret);
3983: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3984: printf("\n");
3985: free_vector(xt,1,n);
3986: return fret;
3987: }
3988: #endif
1.126 brouard 3989:
3990: /*************** log-likelihood *************/
3991: double func( double *x)
3992: {
1.336 brouard 3993: int i, ii, j, k, mi, d, kk, kf=0;
1.226 brouard 3994: int ioffset=0;
1.339 brouard 3995: int ipos=0,iposold=0,ncovv=0;
3996:
1.340 brouard 3997: double cotvarv, cotvarvold;
1.226 brouard 3998: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3999: double **out;
4000: double lli; /* Individual log likelihood */
4001: int s1, s2;
1.228 brouard 4002: 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 4003:
1.226 brouard 4004: double bbh, survp;
4005: double agexact;
1.336 brouard 4006: double agebegin, ageend;
1.226 brouard 4007: /*extern weight */
4008: /* We are differentiating ll according to initial status */
4009: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
4010: /*for(i=1;i<imx;i++)
4011: printf(" %d\n",s[4][i]);
4012: */
1.162 brouard 4013:
1.226 brouard 4014: ++countcallfunc;
1.162 brouard 4015:
1.226 brouard 4016: cov[1]=1.;
1.126 brouard 4017:
1.226 brouard 4018: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 4019: ioffset=0;
1.226 brouard 4020: if(mle==1){
4021: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4022: /* Computes the values of the ncovmodel covariates of the model
4023: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
4024: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
4025: to be observed in j being in i according to the model.
4026: */
1.243 brouard 4027: ioffset=2+nagesqr ;
1.233 brouard 4028: /* Fixed */
1.345 brouard 4029: for (kf=1; kf<=ncovf;kf++){ /* For each fixed covariate dummy or quant or prod */
1.319 brouard 4030: /* # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi */
4031: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
4032: /* 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 4033: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.336 brouard 4034: 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 4035: /* V1*V2 (7) TvarFind[2]=7, TvarFind[3]=9 */
1.234 brouard 4036: }
1.226 brouard 4037: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
1.319 brouard 4038: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
1.226 brouard 4039: has been calculated etc */
4040: /* For an individual i, wav[i] gives the number of effective waves */
4041: /* We compute the contribution to Likelihood of each effective transition
4042: mw[mi][i] is real wave of the mi th effectve wave */
4043: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
4044: s2=s[mw[mi+1][i]][i];
1.341 brouard 4045: 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 4046: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
4047: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
4048: */
1.336 brouard 4049: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
4050: /* Wave varying (but not age varying) */
1.339 brouard 4051: /* 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*\/ */
4052: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; but where is the crossproduct? *\/ */
4053: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
4054: /* } */
1.340 brouard 4055: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age )*/
4056: itv=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
4057: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
1.345 brouard 4058: if(FixedV[itv]!=0){ /* Not a fixed covariate */
1.341 brouard 4059: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]][i]; /* cotvar[wav][ncovcol+nqv+iv][i] */
1.340 brouard 4060: }else{ /* fixed covariate */
1.345 brouard 4061: 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 4062: }
1.339 brouard 4063: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 brouard 4064: cotvarvold=cotvarv;
4065: }else{ /* A second product */
4066: cotvarv=cotvarv*cotvarvold;
1.339 brouard 4067: }
4068: iposold=ipos;
1.340 brouard 4069: cov[ioffset+ipos]=cotvarv;
1.234 brouard 4070: }
1.339 brouard 4071: /* for products of time varying to be done */
1.234 brouard 4072: for (ii=1;ii<=nlstate+ndeath;ii++)
4073: for (j=1;j<=nlstate+ndeath;j++){
4074: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4075: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4076: }
1.336 brouard 4077:
4078: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4079: 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 4080: for(d=0; d<dh[mi][i]; d++){
4081: newm=savm;
4082: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4083: cov[2]=agexact;
4084: if(nagesqr==1)
4085: cov[3]= agexact*agexact; /* Should be changed here */
1.349 brouard 4086: /* for (kk=1; kk<=cptcovage;kk++) { */
4087: /* if(!FixedV[Tvar[Tage[kk]]]) */
4088: /* cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /\* Tage[kk] gives the data-covariate associated with age *\/ */
4089: /* else */
4090: /* 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) *\/ */
4091: /* } */
4092: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
4093: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
4094: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4095: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
4096: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
4097: }else{ /* fixed covariate */
4098: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
4099: }
4100: if(ipos!=iposold){ /* Not a product or first of a product */
4101: cotvarvold=cotvarv;
4102: }else{ /* A second product */
4103: cotvarv=cotvarv*cotvarvold;
4104: }
4105: iposold=ipos;
4106: cov[ioffset+ipos]=cotvarv*agexact;
4107: /* For products */
1.234 brouard 4108: }
1.349 brouard 4109:
1.234 brouard 4110: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4111: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4112: savm=oldm;
4113: oldm=newm;
4114: } /* end mult */
4115:
4116: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
4117: /* But now since version 0.9 we anticipate for bias at large stepm.
4118: * If stepm is larger than one month (smallest stepm) and if the exact delay
4119: * (in months) between two waves is not a multiple of stepm, we rounded to
4120: * the nearest (and in case of equal distance, to the lowest) interval but now
4121: * we keep into memory the bias bh[mi][i] and also the previous matrix product
4122: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
4123: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 4124: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
4125: * -stepm/2 to stepm/2 .
4126: * For stepm=1 the results are the same as for previous versions of Imach.
4127: * For stepm > 1 the results are less biased than in previous versions.
4128: */
1.234 brouard 4129: s1=s[mw[mi][i]][i];
4130: s2=s[mw[mi+1][i]][i];
4131: bbh=(double)bh[mi][i]/(double)stepm;
4132: /* bias bh is positive if real duration
4133: * is higher than the multiple of stepm and negative otherwise.
4134: */
4135: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
4136: if( s2 > nlstate){
4137: /* i.e. if s2 is a death state and if the date of death is known
4138: then the contribution to the likelihood is the probability to
4139: die between last step unit time and current step unit time,
4140: which is also equal to probability to die before dh
4141: minus probability to die before dh-stepm .
4142: In version up to 0.92 likelihood was computed
4143: as if date of death was unknown. Death was treated as any other
4144: health state: the date of the interview describes the actual state
4145: and not the date of a change in health state. The former idea was
4146: to consider that at each interview the state was recorded
4147: (healthy, disable or death) and IMaCh was corrected; but when we
4148: introduced the exact date of death then we should have modified
4149: the contribution of an exact death to the likelihood. This new
4150: contribution is smaller and very dependent of the step unit
4151: stepm. It is no more the probability to die between last interview
4152: and month of death but the probability to survive from last
4153: interview up to one month before death multiplied by the
4154: probability to die within a month. Thanks to Chris
4155: Jackson for correcting this bug. Former versions increased
4156: mortality artificially. The bad side is that we add another loop
4157: which slows down the processing. The difference can be up to 10%
4158: lower mortality.
4159: */
4160: /* If, at the beginning of the maximization mostly, the
4161: cumulative probability or probability to be dead is
4162: constant (ie = 1) over time d, the difference is equal to
4163: 0. out[s1][3] = savm[s1][3]: probability, being at state
4164: s1 at precedent wave, to be dead a month before current
4165: wave is equal to probability, being at state s1 at
4166: precedent wave, to be dead at mont of the current
4167: wave. Then the observed probability (that this person died)
4168: is null according to current estimated parameter. In fact,
4169: it should be very low but not zero otherwise the log go to
4170: infinity.
4171: */
1.183 brouard 4172: /* #ifdef INFINITYORIGINAL */
4173: /* lli=log(out[s1][s2] - savm[s1][s2]); */
4174: /* #else */
4175: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
4176: /* lli=log(mytinydouble); */
4177: /* else */
4178: /* lli=log(out[s1][s2] - savm[s1][s2]); */
4179: /* #endif */
1.226 brouard 4180: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4181:
1.226 brouard 4182: } else if ( s2==-1 ) { /* alive */
4183: for (j=1,survp=0. ; j<=nlstate; j++)
4184: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4185: /*survp += out[s1][j]; */
4186: lli= log(survp);
4187: }
1.336 brouard 4188: /* else if (s2==-4) { */
4189: /* for (j=3,survp=0. ; j<=nlstate; j++) */
4190: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
4191: /* lli= log(survp); */
4192: /* } */
4193: /* else if (s2==-5) { */
4194: /* for (j=1,survp=0. ; j<=2; j++) */
4195: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
4196: /* lli= log(survp); */
4197: /* } */
1.226 brouard 4198: else{
4199: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4200: /* 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 */
4201: }
4202: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
4203: /*if(lli ==000.0)*/
1.340 brouard 4204: /* 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 4205: ipmx +=1;
4206: sw += weight[i];
4207: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4208: /* if (lli < log(mytinydouble)){ */
4209: /* 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); */
4210: /* 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]); */
4211: /* } */
4212: } /* end of wave */
4213: } /* end of individual */
4214: } else if(mle==2){
4215: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.319 brouard 4216: ioffset=2+nagesqr ;
4217: for (k=1; k<=ncovf;k++)
4218: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];
1.226 brouard 4219: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 4220: for(k=1; k <= ncovv ; k++){
1.341 brouard 4221: 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 4222: }
1.226 brouard 4223: for (ii=1;ii<=nlstate+ndeath;ii++)
4224: for (j=1;j<=nlstate+ndeath;j++){
4225: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4226: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4227: }
4228: for(d=0; d<=dh[mi][i]; d++){
4229: newm=savm;
4230: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4231: cov[2]=agexact;
4232: if(nagesqr==1)
4233: cov[3]= agexact*agexact;
4234: for (kk=1; kk<=cptcovage;kk++) {
4235: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4236: }
4237: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4238: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4239: savm=oldm;
4240: oldm=newm;
4241: } /* end mult */
4242:
4243: s1=s[mw[mi][i]][i];
4244: s2=s[mw[mi+1][i]][i];
4245: bbh=(double)bh[mi][i]/(double)stepm;
4246: 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 */
4247: ipmx +=1;
4248: sw += weight[i];
4249: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4250: } /* end of wave */
4251: } /* end of individual */
4252: } else if(mle==3){ /* exponential inter-extrapolation */
4253: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4254: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4255: for(mi=1; mi<= wav[i]-1; mi++){
4256: for (ii=1;ii<=nlstate+ndeath;ii++)
4257: for (j=1;j<=nlstate+ndeath;j++){
4258: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4259: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4260: }
4261: for(d=0; d<dh[mi][i]; d++){
4262: newm=savm;
4263: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4264: cov[2]=agexact;
4265: if(nagesqr==1)
4266: cov[3]= agexact*agexact;
4267: for (kk=1; kk<=cptcovage;kk++) {
1.340 brouard 4268: if(!FixedV[Tvar[Tage[kk]]])
4269: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
4270: else
1.341 brouard 4271: 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 4272: }
4273: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4274: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4275: savm=oldm;
4276: oldm=newm;
4277: } /* end mult */
4278:
4279: s1=s[mw[mi][i]][i];
4280: s2=s[mw[mi+1][i]][i];
4281: bbh=(double)bh[mi][i]/(double)stepm;
4282: 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 */
4283: ipmx +=1;
4284: sw += weight[i];
4285: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4286: } /* end of wave */
4287: } /* end of individual */
4288: }else if (mle==4){ /* ml=4 no inter-extrapolation */
4289: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4290: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4291: for(mi=1; mi<= wav[i]-1; mi++){
4292: for (ii=1;ii<=nlstate+ndeath;ii++)
4293: for (j=1;j<=nlstate+ndeath;j++){
4294: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4295: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4296: }
4297: for(d=0; d<dh[mi][i]; d++){
4298: newm=savm;
4299: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4300: cov[2]=agexact;
4301: if(nagesqr==1)
4302: cov[3]= agexact*agexact;
4303: for (kk=1; kk<=cptcovage;kk++) {
4304: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4305: }
1.126 brouard 4306:
1.226 brouard 4307: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4308: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4309: savm=oldm;
4310: oldm=newm;
4311: } /* end mult */
4312:
4313: s1=s[mw[mi][i]][i];
4314: s2=s[mw[mi+1][i]][i];
4315: if( s2 > nlstate){
4316: lli=log(out[s1][s2] - savm[s1][s2]);
4317: } else if ( s2==-1 ) { /* alive */
4318: for (j=1,survp=0. ; j<=nlstate; j++)
4319: survp += out[s1][j];
4320: lli= log(survp);
4321: }else{
4322: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4323: }
4324: ipmx +=1;
4325: sw += weight[i];
4326: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.343 brouard 4327: /* 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 4328: } /* end of wave */
4329: } /* end of individual */
4330: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
4331: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4332: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4333: for(mi=1; mi<= wav[i]-1; mi++){
4334: for (ii=1;ii<=nlstate+ndeath;ii++)
4335: for (j=1;j<=nlstate+ndeath;j++){
4336: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4337: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4338: }
4339: for(d=0; d<dh[mi][i]; d++){
4340: newm=savm;
4341: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4342: cov[2]=agexact;
4343: if(nagesqr==1)
4344: cov[3]= agexact*agexact;
4345: for (kk=1; kk<=cptcovage;kk++) {
1.340 brouard 4346: if(!FixedV[Tvar[Tage[kk]]])
4347: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
4348: else
1.341 brouard 4349: 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 4350: }
1.126 brouard 4351:
1.226 brouard 4352: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4353: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4354: savm=oldm;
4355: oldm=newm;
4356: } /* end mult */
4357:
4358: s1=s[mw[mi][i]][i];
4359: s2=s[mw[mi+1][i]][i];
4360: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4361: ipmx +=1;
4362: sw += weight[i];
4363: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4364: /*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]);*/
4365: } /* end of wave */
4366: } /* end of individual */
4367: } /* End of if */
4368: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
4369: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
4370: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4371: return -l;
1.126 brouard 4372: }
4373:
4374: /*************** log-likelihood *************/
4375: double funcone( double *x)
4376: {
1.228 brouard 4377: /* Same as func but slower because of a lot of printf and if */
1.349 brouard 4378: int i, ii, j, k, mi, d, kk, kv=0, kf=0;
1.228 brouard 4379: int ioffset=0;
1.339 brouard 4380: int ipos=0,iposold=0,ncovv=0;
4381:
1.340 brouard 4382: double cotvarv, cotvarvold;
1.131 brouard 4383: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 4384: double **out;
4385: double lli; /* Individual log likelihood */
4386: double llt;
4387: int s1, s2;
1.228 brouard 4388: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
4389:
1.126 brouard 4390: double bbh, survp;
1.187 brouard 4391: double agexact;
1.214 brouard 4392: double agebegin, ageend;
1.126 brouard 4393: /*extern weight */
4394: /* We are differentiating ll according to initial status */
4395: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
4396: /*for(i=1;i<imx;i++)
4397: printf(" %d\n",s[4][i]);
4398: */
4399: cov[1]=1.;
4400:
4401: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 4402: ioffset=0;
4403: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.336 brouard 4404: /* Computes the values of the ncovmodel covariates of the model
4405: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
4406: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
4407: to be observed in j being in i according to the model.
4408: */
1.243 brouard 4409: /* ioffset=2+nagesqr+cptcovage; */
4410: ioffset=2+nagesqr;
1.232 brouard 4411: /* Fixed */
1.224 brouard 4412: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 4413: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
1.349 brouard 4414: for (kf=1; kf<=ncovf;kf++){ /* V2 + V3 + V4 Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */
1.339 brouard 4415: /* printf("Debug3 TvarFind[%d]=%d",kf, TvarFind[kf]); */
4416: /* printf(" Tvar[TvarFind[kf]]=%d", Tvar[TvarFind[kf]]); */
4417: /* printf(" i=%d covar[Tvar[TvarFind[kf]]][i]=%f\n",i,covar[Tvar[TvarFind[kf]]][i]); */
1.335 brouard 4418: 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 4419: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
4420: /* cov[2+6]=covar[Tvar[6]][i]; */
4421: /* cov[2+6]=covar[2][i]; V2 */
4422: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
4423: /* cov[2+7]=covar[Tvar[7]][i]; */
4424: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
4425: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
4426: /* cov[2+9]=covar[Tvar[9]][i]; */
4427: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 4428: }
1.336 brouard 4429: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
4430: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
4431: has been calculated etc */
4432: /* For an individual i, wav[i] gives the number of effective waves */
4433: /* We compute the contribution to Likelihood of each effective transition
4434: mw[mi][i] is real wave of the mi th effectve wave */
4435: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
4436: s2=s[mw[mi+1][i]][i];
1.341 brouard 4437: And the iv th varying covariate in the DATA is the cotvar[mw[mi+1][i]][ncovcol+nqv+iv][i]
1.336 brouard 4438: */
4439: /* This part may be useless now because everythin should be in covar */
1.232 brouard 4440: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
4441: /* 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?)*\/ */
4442: /* } */
1.231 brouard 4443: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
4444: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
4445: /* } */
1.225 brouard 4446:
1.233 brouard 4447:
4448: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.339 brouard 4449: /* 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 */
4450: /* for(k=1; k <= ncovv ; k++){ /\* Varying covariates (single and product but no age )*\/ */
4451: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; *\/ */
4452: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
4453: /* } */
4454:
4455: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
4456: /* model V1+V3+age*V1+age*V3+V1*V3 */
4457: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
4458: /* TvarVV[1]=V3 (first time varying in the model equation, TvarVV[2]=V1 (in V1*V3) TvarVV[3]=3(V3) */
4459: /* We need the position of the time varying or product in the model */
4460: /* 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 */
4461: /* TvarVV gives the variable name */
1.340 brouard 4462: /* Other example V1 + V3 + V5 + age*V1 + age*V3 + age*V5 + V1*V3 + V3*V5 + V1*V5
4463: * k= 1 2 3 4 5 6 7 8 9
4464: * varying 1 2 3 4 5
4465: * ncovv 1 2 3 4 5 6 7 8
1.343 brouard 4466: * TvarVV[ncovv] V3 5 1 3 3 5 1 5
1.340 brouard 4467: * TvarVVind 2 3 7 7 8 8 9 9
4468: * TvarFind[k] 1 0 0 0 0 0 0 0 0
4469: */
1.345 brouard 4470: /* Other model ncovcol=5 nqv=0 ntv=3 nqtv=0 nlstate=3
1.349 brouard 4471: * V2 V3 V4 are fixed V6 V7 are timevarying so V8 and V5 are not in the model and product column will start at 9 Tvar[(v6*V2)6]=9
1.345 brouard 4472: * FixedV[ncovcol+qv+ntv+nqtv] V5
1.349 brouard 4473: * 3 V1 V2 V3 V4 V5 V6 V7 V8 V3*V2 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
4474: * 0 0 0 0 0 1 1 1 0, 0, 1,1, 1, 0, 1, 0, 1, 0, 1, 0}
4475: * 3 0 0 0 0 0 1 1 1 0, 1 1 1 1 1}
4476: * model= V2 + V3 + V4 + V6 + V7 + V6*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
4477: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
4478: * +age*V6*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4479: * model2= V2 + V3 + V4 + V6 + V7 + V3*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
4480: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
4481: * +age*V3*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4482: * model3= V2 + V3 + V4 + V6 + V7 + age*V3*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
4483: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
4484: * +V3*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4485: * kmodel 1 2 3 4 5 6 7 8 9 10 11
4486: * 12 13 14 15 16
4487: * 17 18 19 20 21
4488: * Tvar[kmodel] 2 3 4 6 7 9 10 11 12 13 14
4489: * 2 3 4 6 7
4490: * 9 11 12 13 14
4491: * cptcovage=5+5 total of covariates with age
4492: * Tage[cptcovage] age*V2=12 13 14 15 16
4493: *1 17 18 19 20 21 gives the position in model of covariates associated with age
4494: *3 Tage[cptcovage] age*V3*V2=6
4495: *3 age*V2=12 13 14 15 16
4496: *3 age*V6*V3=18 19 20 21
4497: * Tvar[Tage[cptcovage]] Tvar[12]=2 3 4 6 Tvar[16]=7(age*V7)
4498: * Tvar[17]age*V6*V2=9 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14
4499: * 2 Tvar[17]age*V3*V2=9 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14
4500: * 3 Tvar[Tage[cptcovage]] Tvar[6]=9 Tvar[12]=2 3 4 6 Tvar[16]=7(age*V7)
4501: * 3 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14
4502: * 3 Tage[cptcovage] age*V3*V2=6 age*V2=12 age*V3 13 14 15 16
4503: * age*V6*V3=18 19 20 21 gives the position in model of covariates associated with age
4504: * 3 Tvar[17]age*V3*V2=9 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14
4505: * Tvar= {2, 3, 4, 6, 7,
4506: * 9, 10, 11, 12, 13, 14,
4507: * Tvar[12]=2, 3, 4, 6, 7,
4508: * Tvar[17]=9, 11, 12, 13, 14}
4509: * Typevar[1]@21 = {0, 0, 0, 0, 0,
4510: * 2, 2, 2, 2, 2, 2,
4511: * 3 3, 2, 2, 2, 2, 2,
4512: * 1, 1, 1, 1, 1,
4513: * 3, 3, 3, 3, 3}
4514: * 3 2, 3, 3, 3, 3}
4515: * p Tposprod[1]@21 {0, 0, 0, 0, 0, 1, 2, 3, 4, 5, 6, 0, 0, 0, 0, 0, 1, 3, 4, 5, 6} Id of the prod at position k in the model
4516: * p Tprod[1]@21 {6, 7, 8, 9, 10, 11, 0 <repeats 15 times>}
4517: * 3 Tposprod[1]@21 {0, 0, 0, 0, 0, 1, 2, 3, 4, 5, 6, 0, 0, 0, 0, 0, 1, 3, 4, 5, 6}
4518: * 3 Tprod[1]@21 {17, 7, 8, 9, 10, 11, 0 <repeats 15 times>}
4519: * cptcovprod=11 (6+5)
4520: * FixedV[Tvar[Tage[cptcovage]]]] FixedV[2]=0 FixedV[3]=0 0 1 (age*V7)Tvar[16]=1 FixedV[absolute] not [kmodel]
4521: * FixedV[Tvar[17]=FixedV[age*V6*V2]=FixedV[9]=1 1 1 1 1
4522: * 3 FixedV[Tvar[17]=FixedV[age*V3*V2]=FixedV[9]=0 [11]=1 1 1 1
4523: * FixedV[] V1=0 V2=0 V3=0 v4=0 V5=0 V6=1 V7=1 v8=1 OK then model dependent
4524: * 9=1 [V7*V2]=[10]=1 11=1 12=1 13=1 14=1
4525: * 3 9=0 [V7*V2]=[10]=1 11=1 12=1 13=1 14=1
4526: * cptcovdageprod=5 for gnuplot printing
4527: * cptcovprodvage=6
4528: * ncova=15 1 2 3 4 5
4529: * 6 7 8 9 10 11 12 13 14 15
4530: * TvarA 2 3 4 6 7
4531: * 6 2 6 7 7 3 6 4 7 4
4532: * TvaAind 12 12 13 13 14 14 15 15 16 16
1.345 brouard 4533: * ncovf 1 2 3
1.349 brouard 4534: * V6 V7 V6*V2 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
4535: * ncovvt=14 1 2 3 4 5 6 7 8 9 10 11 12 13 14
4536: * TvarVV[1]@14 = itv {V6=6, 7, V6*V2=6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
4537: * TvarVVind[1]@14= {4, 5, 6, 6, 7, 7, 8, 8, 9, 9, 10, 10, 11, 11}
4538: * 3 ncovvt=12 V6 V7 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
4539: * 3 TvarVV[1]@12 = itv {6, 7, V7*V2=7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
4540: * 3 1 2 3 4 5 6 7 8 9 10 11 12
4541: * TvarVVind[1]@12= {V6 is in k=4, 5, 7,(4isV2)=7, 8, 8, 9, 9, 10,10, 11,11}TvarVVind[12]=k=11
4542: * TvarV 6, 7, 9, 10, 11, 12, 13, 14
4543: * 3 cptcovprodvage=6
4544: * 3 ncovta=15 +age*V3*V2+age*V2+agev3+ageV4 +age*V6 + age*V7 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4545: * 3 TvarAVVA[1]@15= itva 3 2 2 3 4 6 7 6 3 7 3 6 4 7 4
4546: * 3 ncovta 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
4547: * TvarAVVAind[1]@15= V3 is in k=2 1 1 2 3 4 5 4,2 5,2, 4,3 5 3}TvarVVAind[]
4548: * TvarAVVAind[1]@15= V3 is in k=6 6 12 13 14 15 16 18 18 19,19, 20,20 21,21}TvarVVAind[]
4549: * 3 ncovvta=10 +age*V6 + age*V7 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4550: * 3 we want to compute =cotvar[mw[mi][i]][TvarVVA[ncovva]][i] at position TvarVVAind[ncovva]
4551: * 3 TvarVVA[1]@10= itva 6 7 6 3 7 3 6 4 7 4
4552: * 3 ncovva 1 2 3 4 5 6 7 8 9 10
4553: * TvarVVAind[1]@10= V6 is in k=4 5 8,8 9, 9, 10,10 11 11}TvarVVAind[]
4554: * TvarVVAind[1]@10= 15 16 18,18 19,19, 20,20 21 21}TvarVVAind[]
4555: * TvarVA V3*V2=6 6 , 1, 2, 11, 12, 13, 14
1.345 brouard 4556: * TvarFind[1]@14= {1, 2, 3, 0 <repeats 12 times>}
1.349 brouard 4557: * Tvar[1]@21= {2, 3, 4, 6, 7, 9, 10, 11, 12, 13, 14,
4558: * 2, 3, 4, 6, 7,
4559: * 6, 8, 9, 10, 11}
1.345 brouard 4560: * TvarFind[itv] 0 0 0
4561: * FixedV[itv] 1 1 1 0 1 0 1 0 1 0 0
4562: * Tvar[TvarFind[ncovf]]=[1]=2 [2]=3 [4]=4
4563: * Tvar[TvarFind[itv]] [0]=? ?ncovv 1 à ncovvt]
4564: * Not a fixed cotvar[mw][itv][i] 6 7 6 2 7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
1.349 brouard 4565: * fixed covar[itv] [6] [7] [6][2]
1.345 brouard 4566: */
4567:
1.349 brouard 4568: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* V6 V7 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4 Time varying covariates (single and extended product but no age) including individual from products, product is computed dynamically */
4569: itv=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, or fixed covariate of a varying product after exploding product Vn*Vm into Vn and then Vm */
1.340 brouard 4570: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
1.345 brouard 4571: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
4572: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
4573: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
1.340 brouard 4574: }else{ /* fixed covariate */
1.345 brouard 4575: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
1.349 brouard 4576: cotvarv=covar[itv][i]; /* Good: In V6*V3, 3 is fixed at position of the data */
1.340 brouard 4577: }
1.339 brouard 4578: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 brouard 4579: cotvarvold=cotvarv;
4580: }else{ /* A second product */
4581: cotvarv=cotvarv*cotvarvold;
1.339 brouard 4582: }
4583: iposold=ipos;
1.340 brouard 4584: cov[ioffset+ipos]=cotvarv;
1.339 brouard 4585: /* For products */
4586: }
4587: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates single *\/ */
4588: /* iv=TvarVDind[itv]; /\* iv, position in the model equation of time varying covariate itv *\/ */
4589: /* /\* "V1+V3+age*V1+age*V3+V1*V3" with V3 time varying *\/ */
4590: /* /\* 1 2 3 4 5 *\/ */
4591: /* /\*itv 1 *\/ */
4592: /* /\* TvarVInd[1]= 2 *\/ */
4593: /* /\* iv= Tvar[Tmodelind[itv]]-ncovcol-nqv; /\\* Counting the # varying covariate from 1 to ntveff *\\/ *\/ */
4594: /* /\* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; *\/ */
4595: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; *\/ */
4596: /* /\* k=ioffset-2-nagesqr-cptcovage+itv; /\\* position in simple model *\\/ *\/ */
4597: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; *\/ */
4598: /* cov[ioffset+iv]=cotvar[mw[mi][i]][itv][i]; */
4599: /* /\* 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]); *\/ */
4600: /* } */
1.232 brouard 4601: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 4602: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4603: /* /\* 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]); *\/ */
4604: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 4605: /* } */
1.126 brouard 4606: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 4607: for (j=1;j<=nlstate+ndeath;j++){
4608: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4609: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4610: }
1.214 brouard 4611:
4612: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4613: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
4614: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 4615: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 4616: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
4617: and mw[mi+1][i]. dh depends on stepm.*/
4618: newm=savm;
1.247 brouard 4619: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 4620: cov[2]=agexact;
4621: if(nagesqr==1)
4622: cov[3]= agexact*agexact;
1.349 brouard 4623: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
4624: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
4625: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4626: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
4627: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
4628: /* printf("DEBUG ncovva=%d, Varying TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4629: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
4630: }else{ /* fixed covariate */
4631: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
4632: /* printf("DEBUG ncovva=%d, Fixed TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4633: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
4634: }
4635: if(ipos!=iposold){ /* Not a product or first of a product */
4636: cotvarvold=cotvarv;
4637: }else{ /* A second product */
4638: /* printf("DEBUG * \n"); */
4639: cotvarv=cotvarv*cotvarvold;
4640: }
4641: iposold=ipos;
4642: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
4643: cov[ioffset+ipos]=cotvarv*agexact;
4644: /* For products */
1.242 brouard 4645: }
1.349 brouard 4646:
1.242 brouard 4647: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
4648: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
4649: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4650: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4651: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
4652: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
4653: savm=oldm;
4654: oldm=newm;
1.126 brouard 4655: } /* end mult */
1.336 brouard 4656: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
4657: /* But now since version 0.9 we anticipate for bias at large stepm.
4658: * If stepm is larger than one month (smallest stepm) and if the exact delay
4659: * (in months) between two waves is not a multiple of stepm, we rounded to
4660: * the nearest (and in case of equal distance, to the lowest) interval but now
4661: * we keep into memory the bias bh[mi][i] and also the previous matrix product
4662: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
4663: * probability in order to take into account the bias as a fraction of the way
4664: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
4665: * -stepm/2 to stepm/2 .
4666: * For stepm=1 the results are the same as for previous versions of Imach.
4667: * For stepm > 1 the results are less biased than in previous versions.
4668: */
1.126 brouard 4669: s1=s[mw[mi][i]][i];
4670: s2=s[mw[mi+1][i]][i];
1.217 brouard 4671: /* if(s2==-1){ */
1.268 brouard 4672: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 4673: /* /\* exit(1); *\/ */
4674: /* } */
1.126 brouard 4675: bbh=(double)bh[mi][i]/(double)stepm;
4676: /* bias is positive if real duration
4677: * is higher than the multiple of stepm and negative otherwise.
4678: */
4679: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 4680: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4681: } else if ( s2==-1 ) { /* alive */
1.242 brouard 4682: for (j=1,survp=0. ; j<=nlstate; j++)
4683: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4684: lli= log(survp);
1.126 brouard 4685: }else if (mle==1){
1.242 brouard 4686: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 4687: } else if(mle==2){
1.242 brouard 4688: 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 4689: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 4690: 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 4691: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 4692: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 4693: } else{ /* mle=0 back to 1 */
1.242 brouard 4694: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4695: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 4696: } /* End of if */
4697: ipmx +=1;
4698: sw += weight[i];
4699: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.342 brouard 4700: /* Printing covariates values for each contribution for checking */
1.343 brouard 4701: /* 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 4702: if(globpr){
1.246 brouard 4703: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 4704: %11.6f %11.6f %11.6f ", \
1.242 brouard 4705: 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 4706: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.343 brouard 4707: /* printf("%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\ */
4708: /* %11.6f %11.6f %11.6f ", \ */
4709: /* num[i], agebegin, ageend, i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],weight[i]*gipmx/gsw, */
4710: /* 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2])); */
1.242 brouard 4711: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
4712: llt +=ll[k]*gipmx/gsw;
4713: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
1.335 brouard 4714: /* printf(" %10.6f",-ll[k]*gipmx/gsw); */
1.242 brouard 4715: }
1.343 brouard 4716: fprintf(ficresilk," %10.6f ", -llt);
1.335 brouard 4717: /* printf(" %10.6f\n", -llt); */
1.342 brouard 4718: /* if(debugILK){ /\* debugILK is set by a #d in a comment line *\/ */
1.343 brouard 4719: /* fprintf(ficresilk,"%09ld ", num[i]); */ /* not necessary */
4720: for (kf=1; kf<=ncovf;kf++){ /* Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */
4721: fprintf(ficresilk," %g",covar[Tvar[TvarFind[kf]]][i]);
4722: }
4723: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age) including individual from products */
4724: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4725: if(ipos!=iposold){ /* Not a product or first of a product */
4726: fprintf(ficresilk," %g",cov[ioffset+ipos]);
4727: /* printf(" %g",cov[ioffset+ipos]); */
4728: }else{
4729: fprintf(ficresilk,"*");
4730: /* printf("*"); */
1.342 brouard 4731: }
1.343 brouard 4732: iposold=ipos;
4733: }
1.349 brouard 4734: /* for (kk=1; kk<=cptcovage;kk++) { */
4735: /* if(!FixedV[Tvar[Tage[kk]]]){ */
4736: /* fprintf(ficresilk," %g*age",covar[Tvar[Tage[kk]]][i]); */
4737: /* /\* printf(" %g*age",covar[Tvar[Tage[kk]]][i]); *\/ */
4738: /* }else{ */
4739: /* fprintf(ficresilk," %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */
4740: /* /\* printf(" %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/\\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\\/ *\/ */
4741: /* } */
4742: /* } */
4743: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
4744: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
4745: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4746: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
4747: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
4748: /* printf("DEBUG ncovva=%d, Varying TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4749: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
4750: }else{ /* fixed covariate */
4751: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
4752: /* printf("DEBUG ncovva=%d, Fixed TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4753: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
4754: }
4755: if(ipos!=iposold){ /* Not a product or first of a product */
4756: cotvarvold=cotvarv;
4757: }else{ /* A second product */
4758: /* printf("DEBUG * \n"); */
4759: cotvarv=cotvarv*cotvarvold;
1.342 brouard 4760: }
1.349 brouard 4761: cotvarv=cotvarv*agexact;
4762: fprintf(ficresilk," %g*age",cotvarv);
4763: iposold=ipos;
4764: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
4765: cov[ioffset+ipos]=cotvarv;
4766: /* For products */
1.343 brouard 4767: }
4768: /* printf("\n"); */
1.342 brouard 4769: /* } /\* End debugILK *\/ */
4770: fprintf(ficresilk,"\n");
4771: } /* End if globpr */
1.335 brouard 4772: } /* end of wave */
4773: } /* end of individual */
4774: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
1.232 brouard 4775: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
1.335 brouard 4776: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4777: if(globpr==0){ /* First time we count the contributions and weights */
4778: gipmx=ipmx;
4779: gsw=sw;
4780: }
1.343 brouard 4781: return -l;
1.126 brouard 4782: }
4783:
4784:
4785: /*************** function likelione ***********/
1.292 brouard 4786: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 4787: {
4788: /* This routine should help understanding what is done with
4789: the selection of individuals/waves and
4790: to check the exact contribution to the likelihood.
4791: Plotting could be done.
1.342 brouard 4792: */
4793: void pstamp(FILE *ficres);
1.343 brouard 4794: int k, kf, kk, kvar, ncovv, iposold, ipos;
1.126 brouard 4795:
4796: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 4797: strcpy(fileresilk,"ILK_");
1.202 brouard 4798: strcat(fileresilk,fileresu);
1.126 brouard 4799: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
4800: printf("Problem with resultfile: %s\n", fileresilk);
4801: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
4802: }
1.342 brouard 4803: pstamp(ficresilk);fprintf(ficresilk,"# model=1+age+%s\n",model);
1.214 brouard 4804: 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");
4805: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 4806: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
4807: for(k=1; k<=nlstate; k++)
4808: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
1.342 brouard 4809: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total) ");
4810:
4811: /* if(debugILK){ /\* debugILK is set by a #d in a comment line *\/ */
4812: for(kf=1;kf <= ncovf; kf++){
4813: fprintf(ficresilk,"V%d",Tvar[TvarFind[kf]]);
4814: /* printf("V%d",Tvar[TvarFind[kf]]); */
4815: }
4816: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){
1.343 brouard 4817: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
1.342 brouard 4818: if(ipos!=iposold){ /* Not a product or first of a product */
4819: /* printf(" %d",ipos); */
4820: fprintf(ficresilk," V%d",TvarVV[ncovv]);
4821: }else{
4822: /* printf("*"); */
4823: fprintf(ficresilk,"*");
1.343 brouard 4824: }
1.342 brouard 4825: iposold=ipos;
4826: }
4827: for (kk=1; kk<=cptcovage;kk++) {
4828: if(!FixedV[Tvar[Tage[kk]]]){
4829: /* printf(" %d*age(Fixed)",Tvar[Tage[kk]]); */
4830: fprintf(ficresilk," %d*age(Fixed)",Tvar[Tage[kk]]);
4831: }else{
4832: fprintf(ficresilk," %d*age(Varying)",Tvar[Tage[kk]]);/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
4833: /* printf(" %d*age(Varying)",Tvar[Tage[kk]]);/\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */
4834: }
4835: }
4836: /* } /\* End if debugILK *\/ */
4837: /* printf("\n"); */
4838: fprintf(ficresilk,"\n");
4839: } /* End glogpri */
1.126 brouard 4840:
1.292 brouard 4841: *fretone=(*func)(p);
1.126 brouard 4842: if(*globpri !=0){
4843: fclose(ficresilk);
1.205 brouard 4844: if (mle ==0)
4845: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
4846: else if(mle >=1)
4847: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
4848: 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 4849: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 4850:
1.207 brouard 4851: 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 4852: <img src=\"%s-ori.png\">\n",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4853: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.343 brouard 4854: <img src=\"%s-dest.png\">\n",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
4855:
4856: for (k=1; k<= nlstate ; k++) {
4857: 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 \
4858: <img src=\"%s-p%dj.png\">\n",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
4859: for(kf=1; kf <= ncovf; kf++){ /* For each simple dummy covariate of the model */
1.350 brouard 4860: kvar=Tvar[TvarFind[kf]]; /* variable */
4861: 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): ",k,k,Tvar[TvarFind[kf]],Tvar[TvarFind[kf]],Tvar[TvarFind[kf]]);
4862: fprintf(fichtm,"<a href=\"%s-p%dj-%d.png\">%s-p%dj-%d.png</a><br>",subdirf2(optionfilefiname,"ILK_"),k,kvar,subdirf2(optionfilefiname,"ILK_"),k,kvar);
4863: fprintf(fichtm,"<img src=\"%s-p%dj-%d.png\">",subdirf2(optionfilefiname,"ILK_"),k,Tvar[TvarFind[kf]]);
1.343 brouard 4864: }
4865: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Loop on the time varying extended covariates (with extension of Vn*Vm */
4866: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
4867: kvar=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
4868: /* 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]); */
4869: if(ipos!=iposold){ /* Not a product or first of a product */
4870: /* fprintf(ficresilk," V%d",TvarVV[ncovv]); */
4871: /* printf(" DebugILK fichtm ipos=%d != iposold=%d\n", ipos, iposold); */
4872: 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) */
4873: 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> \
4874: <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);
4875: } /* End only for dummies time varying (single?) */
4876: }else{ /* Useless product */
4877: /* printf("*"); */
4878: /* fprintf(ficresilk,"*"); */
4879: }
4880: iposold=ipos;
4881: } /* For each time varying covariate */
4882: } /* End loop on states */
4883:
4884: /* if(debugILK){ */
4885: /* for(kf=1; kf <= ncovf; kf++){ /\* For each simple dummy covariate of the model *\/ */
4886: /* /\* kvar=Tvar[TvarFind[kf]]; *\/ /\* variable *\/ */
4887: /* for (k=1; k<= nlstate ; k++) { */
4888: /* 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> \ */
4889: /* <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]]); */
4890: /* } */
4891: /* } */
4892: /* for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /\* Loop on the time varying extended covariates (with extension of Vn*Vm *\/ */
4893: /* ipos=TvarVVind[ncovv]; /\* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate *\/ */
4894: /* kvar=TvarVV[ncovv]; /\* TvarVV={3, 1, 3} gives the name of each varying covariate *\/ */
4895: /* /\* 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]); *\/ */
4896: /* if(ipos!=iposold){ /\* Not a product or first of a product *\/ */
4897: /* /\* fprintf(ficresilk," V%d",TvarVV[ncovv]); *\/ */
4898: /* /\* printf(" DebugILK fichtm ipos=%d != iposold=%d\n", ipos, iposold); *\/ */
4899: /* 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) *\/ */
4900: /* for (k=1; k<= nlstate ; k++) { */
4901: /* 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> \ */
4902: /* <img src=\"%s-p%dj-%d.png\">",k,k,kvar,kvar,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,kvar); */
4903: /* } /\* End state *\/ */
4904: /* } /\* End only for dummies time varying (single?) *\/ */
4905: /* }else{ /\* Useless product *\/ */
4906: /* /\* printf("*"); *\/ */
4907: /* /\* fprintf(ficresilk,"*"); *\/ */
4908: /* } */
4909: /* iposold=ipos; */
4910: /* } /\* For each time varying covariate *\/ */
4911: /* }/\* End debugILK *\/ */
1.207 brouard 4912: fflush(fichtm);
1.343 brouard 4913: }/* End globpri */
1.126 brouard 4914: return;
4915: }
4916:
4917:
4918: /*********** Maximum Likelihood Estimation ***************/
4919:
4920: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
4921: {
1.319 brouard 4922: int i,j,k, jk, jkk=0, iter=0;
1.126 brouard 4923: double **xi;
4924: double fret;
4925: double fretone; /* Only one call to likelihood */
4926: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 4927:
4928: #ifdef NLOPT
4929: int creturn;
4930: nlopt_opt opt;
4931: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
4932: double *lb;
4933: double minf; /* the minimum objective value, upon return */
4934: double * p1; /* Shifted parameters from 0 instead of 1 */
4935: myfunc_data dinst, *d = &dinst;
4936: #endif
4937:
4938:
1.126 brouard 4939: xi=matrix(1,npar,1,npar);
4940: for (i=1;i<=npar;i++)
4941: for (j=1;j<=npar;j++)
4942: xi[i][j]=(i==j ? 1.0 : 0.0);
4943: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 4944: strcpy(filerespow,"POW_");
1.126 brouard 4945: strcat(filerespow,fileres);
4946: if((ficrespow=fopen(filerespow,"w"))==NULL) {
4947: printf("Problem with resultfile: %s\n", filerespow);
4948: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
4949: }
4950: fprintf(ficrespow,"# Powell\n# iter -2*LL");
4951: for (i=1;i<=nlstate;i++)
4952: for(j=1;j<=nlstate+ndeath;j++)
4953: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
4954: fprintf(ficrespow,"\n");
1.162 brouard 4955: #ifdef POWELL
1.319 brouard 4956: #ifdef LINMINORIGINAL
4957: #else /* LINMINORIGINAL */
4958:
4959: flatdir=ivector(1,npar);
4960: for (j=1;j<=npar;j++) flatdir[j]=0;
4961: #endif /*LINMINORIGINAL */
4962:
4963: #ifdef FLATSUP
4964: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4965: /* reorganizing p by suppressing flat directions */
4966: for(i=1, jk=1; i <=nlstate; i++){
4967: for(k=1; k <=(nlstate+ndeath); k++){
4968: if (k != i) {
4969: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4970: if(flatdir[jk]==1){
4971: printf(" To be skipped %d%d flatdir[%d]=%d ",i,k,jk, flatdir[jk]);
4972: }
4973: for(j=1; j <=ncovmodel; j++){
4974: printf("%12.7f ",p[jk]);
4975: jk++;
4976: }
4977: printf("\n");
4978: }
4979: }
4980: }
4981: /* skipping */
4982: /* for(i=1, jk=1, jkk=1;(flatdir[jk]==0)&& (i <=nlstate); i++){ */
4983: for(i=1, jk=1, jkk=1;i <=nlstate; i++){
4984: for(k=1; k <=(nlstate+ndeath); k++){
4985: if (k != i) {
4986: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4987: if(flatdir[jk]==1){
4988: printf(" To be skipped %d%d flatdir[%d]=%d jk=%d p[%d] ",i,k,jk, flatdir[jk],jk, jk);
4989: for(j=1; j <=ncovmodel; jk++,j++){
4990: printf(" p[%d]=%12.7f",jk, p[jk]);
4991: /*q[jjk]=p[jk];*/
4992: }
4993: }else{
4994: printf(" To be kept %d%d flatdir[%d]=%d jk=%d q[%d]=p[%d] ",i,k,jk, flatdir[jk],jk, jkk, jk);
4995: for(j=1; j <=ncovmodel; jk++,jkk++,j++){
4996: printf(" p[%d]=%12.7f=q[%d]",jk, p[jk],jkk);
4997: /*q[jjk]=p[jk];*/
4998: }
4999: }
5000: printf("\n");
5001: }
5002: fflush(stdout);
5003: }
5004: }
5005: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
5006: #else /* FLATSUP */
1.126 brouard 5007: powell(p,xi,npar,ftol,&iter,&fret,func);
1.319 brouard 5008: #endif /* FLATSUP */
5009:
5010: #ifdef LINMINORIGINAL
5011: #else
5012: free_ivector(flatdir,1,npar);
5013: #endif /* LINMINORIGINAL*/
5014: #endif /* POWELL */
1.126 brouard 5015:
1.162 brouard 5016: #ifdef NLOPT
5017: #ifdef NEWUOA
5018: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
5019: #else
5020: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
5021: #endif
5022: lb=vector(0,npar-1);
5023: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
5024: nlopt_set_lower_bounds(opt, lb);
5025: nlopt_set_initial_step1(opt, 0.1);
5026:
5027: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
5028: d->function = func;
5029: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
5030: nlopt_set_min_objective(opt, myfunc, d);
5031: nlopt_set_xtol_rel(opt, ftol);
5032: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
5033: printf("nlopt failed! %d\n",creturn);
5034: }
5035: else {
5036: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
5037: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
5038: iter=1; /* not equal */
5039: }
5040: nlopt_destroy(opt);
5041: #endif
1.319 brouard 5042: #ifdef FLATSUP
5043: /* npared = npar -flatd/ncovmodel; */
5044: /* xired= matrix(1,npared,1,npared); */
5045: /* paramred= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); */
5046: /* powell(pred,xired,npared,ftol,&iter,&fret,flatdir,func); */
5047: /* free_matrix(xire,1,npared,1,npared); */
5048: #else /* FLATSUP */
5049: #endif /* FLATSUP */
1.126 brouard 5050: free_matrix(xi,1,npar,1,npar);
5051: fclose(ficrespow);
1.203 brouard 5052: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
5053: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 5054: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 5055:
5056: }
5057:
5058: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 5059: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 5060: {
5061: double **a,**y,*x,pd;
1.203 brouard 5062: /* double **hess; */
1.164 brouard 5063: int i, j;
1.126 brouard 5064: int *indx;
5065:
5066: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 5067: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 5068: void lubksb(double **a, int npar, int *indx, double b[]) ;
5069: void ludcmp(double **a, int npar, int *indx, double *d) ;
5070: double gompertz(double p[]);
1.203 brouard 5071: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 5072:
5073: printf("\nCalculation of the hessian matrix. Wait...\n");
5074: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
5075: for (i=1;i<=npar;i++){
1.203 brouard 5076: printf("%d-",i);fflush(stdout);
5077: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 5078:
5079: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
5080:
5081: /* printf(" %f ",p[i]);
5082: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
5083: }
5084:
5085: for (i=1;i<=npar;i++) {
5086: for (j=1;j<=npar;j++) {
5087: if (j>i) {
1.203 brouard 5088: printf(".%d-%d",i,j);fflush(stdout);
5089: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
5090: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 5091:
5092: hess[j][i]=hess[i][j];
5093: /*printf(" %lf ",hess[i][j]);*/
5094: }
5095: }
5096: }
5097: printf("\n");
5098: fprintf(ficlog,"\n");
5099:
5100: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
5101: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
5102:
5103: a=matrix(1,npar,1,npar);
5104: y=matrix(1,npar,1,npar);
5105: x=vector(1,npar);
5106: indx=ivector(1,npar);
5107: for (i=1;i<=npar;i++)
5108: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
5109: ludcmp(a,npar,indx,&pd);
5110:
5111: for (j=1;j<=npar;j++) {
5112: for (i=1;i<=npar;i++) x[i]=0;
5113: x[j]=1;
5114: lubksb(a,npar,indx,x);
5115: for (i=1;i<=npar;i++){
5116: matcov[i][j]=x[i];
5117: }
5118: }
5119:
5120: printf("\n#Hessian matrix#\n");
5121: fprintf(ficlog,"\n#Hessian matrix#\n");
5122: for (i=1;i<=npar;i++) {
5123: for (j=1;j<=npar;j++) {
1.203 brouard 5124: printf("%.6e ",hess[i][j]);
5125: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 5126: }
5127: printf("\n");
5128: fprintf(ficlog,"\n");
5129: }
5130:
1.203 brouard 5131: /* printf("\n#Covariance matrix#\n"); */
5132: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
5133: /* for (i=1;i<=npar;i++) { */
5134: /* for (j=1;j<=npar;j++) { */
5135: /* printf("%.6e ",matcov[i][j]); */
5136: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
5137: /* } */
5138: /* printf("\n"); */
5139: /* fprintf(ficlog,"\n"); */
5140: /* } */
5141:
1.126 brouard 5142: /* Recompute Inverse */
1.203 brouard 5143: /* for (i=1;i<=npar;i++) */
5144: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
5145: /* ludcmp(a,npar,indx,&pd); */
5146:
5147: /* printf("\n#Hessian matrix recomputed#\n"); */
5148:
5149: /* for (j=1;j<=npar;j++) { */
5150: /* for (i=1;i<=npar;i++) x[i]=0; */
5151: /* x[j]=1; */
5152: /* lubksb(a,npar,indx,x); */
5153: /* for (i=1;i<=npar;i++){ */
5154: /* y[i][j]=x[i]; */
5155: /* printf("%.3e ",y[i][j]); */
5156: /* fprintf(ficlog,"%.3e ",y[i][j]); */
5157: /* } */
5158: /* printf("\n"); */
5159: /* fprintf(ficlog,"\n"); */
5160: /* } */
5161:
5162: /* Verifying the inverse matrix */
5163: #ifdef DEBUGHESS
5164: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 5165:
1.203 brouard 5166: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
5167: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 5168:
5169: for (j=1;j<=npar;j++) {
5170: for (i=1;i<=npar;i++){
1.203 brouard 5171: printf("%.2f ",y[i][j]);
5172: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 5173: }
5174: printf("\n");
5175: fprintf(ficlog,"\n");
5176: }
1.203 brouard 5177: #endif
1.126 brouard 5178:
5179: free_matrix(a,1,npar,1,npar);
5180: free_matrix(y,1,npar,1,npar);
5181: free_vector(x,1,npar);
5182: free_ivector(indx,1,npar);
1.203 brouard 5183: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 5184:
5185:
5186: }
5187:
5188: /*************** hessian matrix ****************/
5189: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 5190: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 5191: int i;
5192: int l=1, lmax=20;
1.203 brouard 5193: double k1,k2, res, fx;
1.132 brouard 5194: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 5195: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
5196: int k=0,kmax=10;
5197: double l1;
5198:
5199: fx=func(x);
5200: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 5201: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 5202: l1=pow(10,l);
5203: delts=delt;
5204: for(k=1 ; k <kmax; k=k+1){
5205: delt = delta*(l1*k);
5206: p2[theta]=x[theta] +delt;
1.145 brouard 5207: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 5208: p2[theta]=x[theta]-delt;
5209: k2=func(p2)-fx;
5210: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 5211: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 5212:
1.203 brouard 5213: #ifdef DEBUGHESSII
1.126 brouard 5214: 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);
5215: 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);
5216: #endif
5217: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
5218: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
5219: k=kmax;
5220: }
5221: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 5222: k=kmax; l=lmax*10;
1.126 brouard 5223: }
5224: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
5225: delts=delt;
5226: }
1.203 brouard 5227: } /* End loop k */
1.126 brouard 5228: }
5229: delti[theta]=delts;
5230: return res;
5231:
5232: }
5233:
1.203 brouard 5234: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 5235: {
5236: int i;
1.164 brouard 5237: int l=1, lmax=20;
1.126 brouard 5238: double k1,k2,k3,k4,res,fx;
1.132 brouard 5239: double p2[MAXPARM+1];
1.203 brouard 5240: int k, kmax=1;
5241: double v1, v2, cv12, lc1, lc2;
1.208 brouard 5242:
5243: int firstime=0;
1.203 brouard 5244:
1.126 brouard 5245: fx=func(x);
1.203 brouard 5246: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 5247: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 5248: p2[thetai]=x[thetai]+delti[thetai]*k;
5249: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 5250: k1=func(p2)-fx;
5251:
1.203 brouard 5252: p2[thetai]=x[thetai]+delti[thetai]*k;
5253: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 5254: k2=func(p2)-fx;
5255:
1.203 brouard 5256: p2[thetai]=x[thetai]-delti[thetai]*k;
5257: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 5258: k3=func(p2)-fx;
5259:
1.203 brouard 5260: p2[thetai]=x[thetai]-delti[thetai]*k;
5261: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 5262: k4=func(p2)-fx;
1.203 brouard 5263: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
5264: if(k1*k2*k3*k4 <0.){
1.208 brouard 5265: firstime=1;
1.203 brouard 5266: kmax=kmax+10;
1.208 brouard 5267: }
5268: if(kmax >=10 || firstime ==1){
1.246 brouard 5269: 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);
5270: 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 5271: 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);
5272: 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);
5273: }
5274: #ifdef DEBUGHESSIJ
5275: v1=hess[thetai][thetai];
5276: v2=hess[thetaj][thetaj];
5277: cv12=res;
5278: /* Computing eigen value of Hessian matrix */
5279: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
5280: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
5281: if ((lc2 <0) || (lc1 <0) ){
5282: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
5283: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
5284: 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);
5285: 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);
5286: }
1.126 brouard 5287: #endif
5288: }
5289: return res;
5290: }
5291:
1.203 brouard 5292: /* Not done yet: Was supposed to fix if not exactly at the maximum */
5293: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
5294: /* { */
5295: /* int i; */
5296: /* int l=1, lmax=20; */
5297: /* double k1,k2,k3,k4,res,fx; */
5298: /* double p2[MAXPARM+1]; */
5299: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
5300: /* int k=0,kmax=10; */
5301: /* double l1; */
5302:
5303: /* fx=func(x); */
5304: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
5305: /* l1=pow(10,l); */
5306: /* delts=delt; */
5307: /* for(k=1 ; k <kmax; k=k+1){ */
5308: /* delt = delti*(l1*k); */
5309: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
5310: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
5311: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
5312: /* k1=func(p2)-fx; */
5313:
5314: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
5315: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
5316: /* k2=func(p2)-fx; */
5317:
5318: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
5319: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
5320: /* k3=func(p2)-fx; */
5321:
5322: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
5323: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
5324: /* k4=func(p2)-fx; */
5325: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
5326: /* #ifdef DEBUGHESSIJ */
5327: /* 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); */
5328: /* 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); */
5329: /* #endif */
5330: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
5331: /* k=kmax; */
5332: /* } */
5333: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
5334: /* k=kmax; l=lmax*10; */
5335: /* } */
5336: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
5337: /* delts=delt; */
5338: /* } */
5339: /* } /\* End loop k *\/ */
5340: /* } */
5341: /* delti[theta]=delts; */
5342: /* return res; */
5343: /* } */
5344:
5345:
1.126 brouard 5346: /************** Inverse of matrix **************/
5347: void ludcmp(double **a, int n, int *indx, double *d)
5348: {
5349: int i,imax,j,k;
5350: double big,dum,sum,temp;
5351: double *vv;
5352:
5353: vv=vector(1,n);
5354: *d=1.0;
5355: for (i=1;i<=n;i++) {
5356: big=0.0;
5357: for (j=1;j<=n;j++)
5358: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 5359: if (big == 0.0){
5360: printf(" Singular Hessian matrix at row %d:\n",i);
5361: for (j=1;j<=n;j++) {
5362: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
5363: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
5364: }
5365: fflush(ficlog);
5366: fclose(ficlog);
5367: nrerror("Singular matrix in routine ludcmp");
5368: }
1.126 brouard 5369: vv[i]=1.0/big;
5370: }
5371: for (j=1;j<=n;j++) {
5372: for (i=1;i<j;i++) {
5373: sum=a[i][j];
5374: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
5375: a[i][j]=sum;
5376: }
5377: big=0.0;
5378: for (i=j;i<=n;i++) {
5379: sum=a[i][j];
5380: for (k=1;k<j;k++)
5381: sum -= a[i][k]*a[k][j];
5382: a[i][j]=sum;
5383: if ( (dum=vv[i]*fabs(sum)) >= big) {
5384: big=dum;
5385: imax=i;
5386: }
5387: }
5388: if (j != imax) {
5389: for (k=1;k<=n;k++) {
5390: dum=a[imax][k];
5391: a[imax][k]=a[j][k];
5392: a[j][k]=dum;
5393: }
5394: *d = -(*d);
5395: vv[imax]=vv[j];
5396: }
5397: indx[j]=imax;
5398: if (a[j][j] == 0.0) a[j][j]=TINY;
5399: if (j != n) {
5400: dum=1.0/(a[j][j]);
5401: for (i=j+1;i<=n;i++) a[i][j] *= dum;
5402: }
5403: }
5404: free_vector(vv,1,n); /* Doesn't work */
5405: ;
5406: }
5407:
5408: void lubksb(double **a, int n, int *indx, double b[])
5409: {
5410: int i,ii=0,ip,j;
5411: double sum;
5412:
5413: for (i=1;i<=n;i++) {
5414: ip=indx[i];
5415: sum=b[ip];
5416: b[ip]=b[i];
5417: if (ii)
5418: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
5419: else if (sum) ii=i;
5420: b[i]=sum;
5421: }
5422: for (i=n;i>=1;i--) {
5423: sum=b[i];
5424: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
5425: b[i]=sum/a[i][i];
5426: }
5427: }
5428:
5429: void pstamp(FILE *fichier)
5430: {
1.196 brouard 5431: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 5432: }
5433:
1.297 brouard 5434: void date2dmy(double date,double *day, double *month, double *year){
5435: double yp=0., yp1=0., yp2=0.;
5436:
5437: yp1=modf(date,&yp);/* extracts integral of date in yp and
5438: fractional in yp1 */
5439: *year=yp;
5440: yp2=modf((yp1*12),&yp);
5441: *month=yp;
5442: yp1=modf((yp2*30.5),&yp);
5443: *day=yp;
5444: if(*day==0) *day=1;
5445: if(*month==0) *month=1;
5446: }
5447:
1.253 brouard 5448:
5449:
1.126 brouard 5450: /************ Frequencies ********************/
1.251 brouard 5451: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 5452: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
5453: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 5454: { /* Some frequencies as well as proposing some starting values */
1.332 brouard 5455: /* Frequencies of any combination of dummy covariate used in the model equation */
1.265 brouard 5456: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 5457: int iind=0, iage=0;
5458: int mi; /* Effective wave */
5459: int first;
5460: double ***freq; /* Frequencies */
1.268 brouard 5461: 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 */
5462: 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 5463: double *meanq, *stdq, *idq;
1.226 brouard 5464: double **meanqt;
5465: double *pp, **prop, *posprop, *pospropt;
5466: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
5467: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
5468: double agebegin, ageend;
5469:
5470: pp=vector(1,nlstate);
1.251 brouard 5471: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 5472: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
5473: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
5474: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
5475: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 5476: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 5477: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 5478: meanqt=matrix(1,lastpass,1,nqtveff);
5479: strcpy(fileresp,"P_");
5480: strcat(fileresp,fileresu);
5481: /*strcat(fileresphtm,fileresu);*/
5482: if((ficresp=fopen(fileresp,"w"))==NULL) {
5483: printf("Problem with prevalence resultfile: %s\n", fileresp);
5484: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
5485: exit(0);
5486: }
1.240 brouard 5487:
1.226 brouard 5488: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
5489: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
5490: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
5491: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
5492: fflush(ficlog);
5493: exit(70);
5494: }
5495: else{
5496: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 5497: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 5498: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 5499: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
5500: }
1.319 brouard 5501: 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 5502:
1.226 brouard 5503: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
5504: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
5505: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
5506: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
5507: fflush(ficlog);
5508: exit(70);
1.240 brouard 5509: } else{
1.226 brouard 5510: 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 5511: ,<hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 5512: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 5513: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
5514: }
1.319 brouard 5515: 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 5516:
1.253 brouard 5517: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
5518: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 5519: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 5520: j1=0;
1.126 brouard 5521:
1.227 brouard 5522: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
1.335 brouard 5523: j=cptcoveff; /* Only simple dummy covariates used in the model */
1.330 brouard 5524: /* j=cptcovn; /\* Only dummy covariates of the model *\/ */
1.226 brouard 5525: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 5526:
5527:
1.226 brouard 5528: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
5529: reference=low_education V1=0,V2=0
5530: med_educ V1=1 V2=0,
5531: high_educ V1=0 V2=1
1.330 brouard 5532: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcovn
1.226 brouard 5533: */
1.249 brouard 5534: dateintsum=0;
5535: k2cpt=0;
5536:
1.253 brouard 5537: if(cptcoveff == 0 )
1.265 brouard 5538: nl=1; /* Constant and age model only */
1.253 brouard 5539: else
5540: nl=2;
1.265 brouard 5541:
5542: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
5543: /* Loop on nj=1 or 2 if dummy covariates j!=0
1.335 brouard 5544: * Loop on j1(1 to 2**cptcoveff) covariate combination
1.265 brouard 5545: * freq[s1][s2][iage] =0.
5546: * Loop on iind
5547: * ++freq[s1][s2][iage] weighted
5548: * end iind
5549: * if covariate and j!0
5550: * headers Variable on one line
5551: * endif cov j!=0
5552: * header of frequency table by age
5553: * Loop on age
5554: * pp[s1]+=freq[s1][s2][iage] weighted
5555: * pos+=freq[s1][s2][iage] weighted
5556: * Loop on s1 initial state
5557: * fprintf(ficresp
5558: * end s1
5559: * end age
5560: * if j!=0 computes starting values
5561: * end compute starting values
5562: * end j1
5563: * end nl
5564: */
1.253 brouard 5565: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
5566: if(nj==1)
5567: j=0; /* First pass for the constant */
1.265 brouard 5568: else{
1.335 brouard 5569: 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 5570: }
1.251 brouard 5571: first=1;
1.332 brouard 5572: 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 5573: posproptt=0.;
1.330 brouard 5574: /*printf("cptcovn=%d Tvaraff=%d", cptcovn,Tvaraff[1]);
1.251 brouard 5575: scanf("%d", i);*/
5576: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 5577: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 5578: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 5579: freq[i][s2][m]=0;
1.251 brouard 5580:
5581: for (i=1; i<=nlstate; i++) {
1.240 brouard 5582: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 5583: prop[i][m]=0;
5584: posprop[i]=0;
5585: pospropt[i]=0;
5586: }
1.283 brouard 5587: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 5588: idq[z1]=0.;
5589: meanq[z1]=0.;
5590: stdq[z1]=0.;
1.283 brouard 5591: }
5592: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 5593: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 5594: /* meanqt[m][z1]=0.; */
5595: /* } */
5596: /* } */
1.251 brouard 5597: /* dateintsum=0; */
5598: /* k2cpt=0; */
5599:
1.265 brouard 5600: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 5601: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
5602: bool=1;
5603: if(j !=0){
5604: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
1.335 brouard 5605: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
5606: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
1.251 brouard 5607: /* if(Tvaraff[z1] ==-20){ */
5608: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
5609: /* }else if(Tvaraff[z1] ==-10){ */
5610: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
1.330 brouard 5611: /* }else */ /* TODO TODO codtabm(j1,z1) or codtabm(j1,Tvaraff[z1]]z1)*/
1.335 brouard 5612: /* 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); */
5613: if(Tvaraff[z1]<1 || Tvaraff[z1]>=NCOVMAX)
1.338 brouard 5614: printf("Error Tvaraff[z1]=%d<1 or >=%d, cptcoveff=%d model=1+age+%s\n",Tvaraff[z1],NCOVMAX, cptcoveff, model);
1.332 brouard 5615: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]){ /* for combination j1 of covariates */
1.265 brouard 5616: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 5617: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
1.332 brouard 5618: /* 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", */
5619: /* bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),*/
5620: /* j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
1.251 brouard 5621: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
5622: } /* Onlyf fixed */
5623: } /* end z1 */
1.335 brouard 5624: } /* cptcoveff > 0 */
1.251 brouard 5625: } /* end any */
5626: }/* end j==0 */
1.265 brouard 5627: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 5628: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 5629: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 5630: m=mw[mi][iind];
5631: if(j!=0){
5632: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
1.335 brouard 5633: for (z1=1; z1<=cptcoveff; z1++) {
1.251 brouard 5634: if( Fixed[Tmodelind[z1]]==1){
1.341 brouard 5635: /* iv= Tvar[Tmodelind[z1]]-ncovcol-nqv; /\* Good *\/ */
5636: iv= Tvar[Tmodelind[z1]]; /* Good *//* because cotvar starts now at first at ncovcol+nqv+ntv */
1.332 brouard 5637: 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 5638: value is -1, we don't select. It differs from the
5639: constant and age model which counts them. */
5640: bool=0; /* not selected */
5641: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
1.334 brouard 5642: /* i1=Tvaraff[z1]; */
5643: /* i2=TnsdVar[i1]; */
5644: /* i3=nbcode[i1][i2]; */
5645: /* i4=covar[i1][iind]; */
5646: /* if(i4 != i3){ */
5647: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) { /* Bug valgrind */
1.251 brouard 5648: bool=0;
5649: }
5650: }
5651: }
5652: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
5653: } /* end j==0 */
5654: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 5655: if(bool==1){ /*Selected */
1.251 brouard 5656: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
5657: and mw[mi+1][iind]. dh depends on stepm. */
5658: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
5659: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
5660: if(m >=firstpass && m <=lastpass){
5661: k2=anint[m][iind]+(mint[m][iind]/12.);
5662: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
5663: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
5664: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
5665: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
5666: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
5667: if (m<lastpass) {
5668: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
5669: /* 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]); */
5670: if(s[m][iind]==-1)
5671: 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.));
5672: 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 5673: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean on known values only */
5674: if(!isnan(covar[ncovcol+z1][iind])){
1.332 brouard 5675: idq[z1]=idq[z1]+weight[iind];
5676: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
5677: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; *//*error*/
5678: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
1.311 brouard 5679: }
1.284 brouard 5680: }
1.251 brouard 5681: /* if((int)agev[m][iind] == 55) */
5682: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
5683: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
5684: 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 5685: }
1.251 brouard 5686: } /* end if between passes */
5687: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
5688: dateintsum=dateintsum+k2; /* on all covariates ?*/
5689: k2cpt++;
5690: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 5691: }
1.251 brouard 5692: }else{
5693: bool=1;
5694: }/* end bool 2 */
5695: } /* end m */
1.284 brouard 5696: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
5697: /* idq[z1]=idq[z1]+weight[iind]; */
5698: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
5699: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
5700: /* } */
1.251 brouard 5701: } /* end bool */
5702: } /* end iind = 1 to imx */
1.319 brouard 5703: /* prop[s][age] is fed for any initial and valid live state as well as
1.251 brouard 5704: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
5705:
5706:
5707: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.335 brouard 5708: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
1.265 brouard 5709: pstamp(ficresp);
1.335 brouard 5710: if (cptcoveff>0 && j!=0){
1.265 brouard 5711: pstamp(ficresp);
1.251 brouard 5712: printf( "\n#********** Variable ");
5713: fprintf(ficresp, "\n#********** Variable ");
5714: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
5715: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
5716: fprintf(ficlog, "\n#********** Variable ");
1.340 brouard 5717: for (z1=1; z1<=cptcoveff; z1++){
1.251 brouard 5718: if(!FixedV[Tvaraff[z1]]){
1.330 brouard 5719: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5720: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5721: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5722: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5723: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.250 brouard 5724: }else{
1.330 brouard 5725: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5726: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5727: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5728: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5729: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.251 brouard 5730: }
5731: }
5732: printf( "**********\n#");
5733: fprintf(ficresp, "**********\n#");
5734: fprintf(ficresphtm, "**********</h3>\n");
5735: fprintf(ficresphtmfr, "**********</h3>\n");
5736: fprintf(ficlog, "**********\n");
5737: }
1.284 brouard 5738: /*
5739: Printing means of quantitative variables if any
5740: */
5741: for (z1=1; z1<= nqfveff; z1++) {
1.311 brouard 5742: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.3g (weighted) individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.312 brouard 5743: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
1.284 brouard 5744: if(weightopt==1){
5745: printf(" Weighted mean and standard deviation of");
5746: fprintf(ficlog," Weighted mean and standard deviation of");
5747: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
5748: }
1.311 brouard 5749: /* mu = \frac{w x}{\sum w}
5750: var = \frac{\sum w (x-mu)^2}{\sum w} = \frac{w x^2}{\sum w} - mu^2
5751: */
5752: 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]));
5753: 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]));
5754: 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 5755: }
5756: /* for (z1=1; z1<= nqtveff; z1++) { */
5757: /* for(m=1;m<=lastpass;m++){ */
5758: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
5759: /* } */
5760: /* } */
1.283 brouard 5761:
1.251 brouard 5762: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.335 brouard 5763: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
1.265 brouard 5764: fprintf(ficresp, " Age");
1.335 brouard 5765: if(nj==2) for (z1=1; z1<=cptcoveff; z1++) {
5766: 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]]);
5767: fprintf(ficresp, " V%d=%d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5768: }
1.251 brouard 5769: for(i=1; i<=nlstate;i++) {
1.335 brouard 5770: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 5771: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
5772: }
1.335 brouard 5773: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 5774: fprintf(ficresphtm, "\n");
5775:
5776: /* Header of frequency table by age */
5777: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
5778: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 5779: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 5780: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5781: if(s2!=0 && m!=0)
5782: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 5783: }
1.226 brouard 5784: }
1.251 brouard 5785: fprintf(ficresphtmfr, "\n");
5786:
5787: /* For each age */
5788: for(iage=iagemin; iage <= iagemax+3; iage++){
5789: fprintf(ficresphtm,"<tr>");
5790: if(iage==iagemax+1){
5791: fprintf(ficlog,"1");
5792: fprintf(ficresphtmfr,"<tr><th>0</th> ");
5793: }else if(iage==iagemax+2){
5794: fprintf(ficlog,"0");
5795: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
5796: }else if(iage==iagemax+3){
5797: fprintf(ficlog,"Total");
5798: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
5799: }else{
1.240 brouard 5800: if(first==1){
1.251 brouard 5801: first=0;
5802: printf("See log file for details...\n");
5803: }
5804: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
5805: fprintf(ficlog,"Age %d", iage);
5806: }
1.265 brouard 5807: for(s1=1; s1 <=nlstate ; s1++){
5808: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
5809: pp[s1] += freq[s1][m][iage];
1.251 brouard 5810: }
1.265 brouard 5811: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5812: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 5813: pos += freq[s1][m][iage];
5814: if(pp[s1]>=1.e-10){
1.251 brouard 5815: if(first==1){
1.265 brouard 5816: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5817: }
1.265 brouard 5818: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5819: }else{
5820: if(first==1)
1.265 brouard 5821: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
5822: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 5823: }
5824: }
5825:
1.265 brouard 5826: for(s1=1; s1 <=nlstate ; s1++){
5827: /* posprop[s1]=0; */
5828: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
5829: pp[s1] += freq[s1][m][iage];
5830: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
5831:
5832: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
5833: pos += pp[s1]; /* pos is the total number of transitions until this age */
5834: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
5835: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5836: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
5837: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5838: }
5839:
5840: /* Writing ficresp */
1.335 brouard 5841: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5842: if( iage <= iagemax){
5843: fprintf(ficresp," %d",iage);
5844: }
5845: }else if( nj==2){
5846: if( iage <= iagemax){
5847: fprintf(ficresp," %d",iage);
1.335 brouard 5848: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.265 brouard 5849: }
1.240 brouard 5850: }
1.265 brouard 5851: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 5852: if(pos>=1.e-5){
1.251 brouard 5853: if(first==1)
1.265 brouard 5854: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
5855: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 5856: }else{
5857: if(first==1)
1.265 brouard 5858: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
5859: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 5860: }
5861: if( iage <= iagemax){
5862: if(pos>=1.e-5){
1.335 brouard 5863: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5864: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5865: }else if( nj==2){
5866: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5867: }
5868: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5869: /*probs[iage][s1][j1]= pp[s1]/pos;*/
5870: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
5871: } else{
1.335 brouard 5872: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
1.265 brouard 5873: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 5874: }
1.240 brouard 5875: }
1.265 brouard 5876: pospropt[s1] +=posprop[s1];
5877: } /* end loop s1 */
1.251 brouard 5878: /* pospropt=0.; */
1.265 brouard 5879: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 5880: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5881: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 5882: if(first==1){
1.265 brouard 5883: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5884: }
1.265 brouard 5885: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
5886: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5887: }
1.265 brouard 5888: if(s1!=0 && m!=0)
5889: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 5890: }
1.265 brouard 5891: } /* end loop s1 */
1.251 brouard 5892: posproptt=0.;
1.265 brouard 5893: for(s1=1; s1 <=nlstate; s1++){
5894: posproptt += pospropt[s1];
1.251 brouard 5895: }
5896: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 5897: fprintf(ficresphtm,"</tr>\n");
1.335 brouard 5898: if((cptcoveff==0 && nj==1)|| nj==2 ) {
1.265 brouard 5899: if(iage <= iagemax)
5900: fprintf(ficresp,"\n");
1.240 brouard 5901: }
1.251 brouard 5902: if(first==1)
5903: printf("Others in log...\n");
5904: fprintf(ficlog,"\n");
5905: } /* end loop age iage */
1.265 brouard 5906:
1.251 brouard 5907: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 5908: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5909: if(posproptt < 1.e-5){
1.265 brouard 5910: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 5911: }else{
1.265 brouard 5912: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 5913: }
1.226 brouard 5914: }
1.251 brouard 5915: fprintf(ficresphtm,"</tr>\n");
5916: fprintf(ficresphtm,"</table>\n");
5917: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 5918: if(posproptt < 1.e-5){
1.251 brouard 5919: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
5920: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 5921: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
5922: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 5923: invalidvarcomb[j1]=1;
1.226 brouard 5924: }else{
1.338 brouard 5925: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced (or no resultline).</p>",j1);
1.251 brouard 5926: invalidvarcomb[j1]=0;
1.226 brouard 5927: }
1.251 brouard 5928: fprintf(ficresphtmfr,"</table>\n");
5929: fprintf(ficlog,"\n");
5930: if(j!=0){
5931: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 5932: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5933: for(k=1; k <=(nlstate+ndeath); k++){
5934: if (k != i) {
1.265 brouard 5935: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 5936: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 5937: if(j1==1){ /* All dummy covariates to zero */
5938: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
5939: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 5940: printf("%d%d ",i,k);
5941: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5942: 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]));
5943: 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]));
5944: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 5945: }
1.253 brouard 5946: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
5947: for(iage=iagemin; iage <= iagemax+3; iage++){
5948: x[iage]= (double)iage;
5949: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 5950: /* 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 5951: }
1.268 brouard 5952: /* Some are not finite, but linreg will ignore these ages */
5953: no=0;
1.253 brouard 5954: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 5955: pstart[s1]=b;
5956: pstart[s1-1]=a;
1.252 brouard 5957: }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 */
5958: 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]);
5959: 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 5960: 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 5961: printf("%d%d ",i,k);
5962: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5963: 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 5964: }else{ /* Other cases, like quantitative fixed or varying covariates */
5965: ;
5966: }
5967: /* printf("%12.7f )", param[i][jj][k]); */
5968: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5969: s1++;
1.251 brouard 5970: } /* end jj */
5971: } /* end k!= i */
5972: } /* end k */
1.265 brouard 5973: } /* end i, s1 */
1.251 brouard 5974: } /* end j !=0 */
5975: } /* end selected combination of covariate j1 */
5976: if(j==0){ /* We can estimate starting values from the occurences in each case */
5977: printf("#Freqsummary: Starting values for the constants:\n");
5978: fprintf(ficlog,"\n");
1.265 brouard 5979: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5980: for(k=1; k <=(nlstate+ndeath); k++){
5981: if (k != i) {
5982: printf("%d%d ",i,k);
5983: fprintf(ficlog,"%d%d ",i,k);
5984: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 5985: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 5986: if(jj==1){ /* Age has to be done */
1.265 brouard 5987: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
5988: 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]));
5989: 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 5990: }
5991: /* printf("%12.7f )", param[i][jj][k]); */
5992: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5993: s1++;
1.250 brouard 5994: }
1.251 brouard 5995: printf("\n");
5996: fprintf(ficlog,"\n");
1.250 brouard 5997: }
5998: }
1.284 brouard 5999: } /* end of state i */
1.251 brouard 6000: printf("#Freqsummary\n");
6001: fprintf(ficlog,"\n");
1.265 brouard 6002: for(s1=-1; s1 <=nlstate+ndeath; s1++){
6003: for(s2=-1; s2 <=nlstate+ndeath; s2++){
6004: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
6005: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
6006: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
6007: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
6008: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
6009: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 6010: /* } */
6011: }
1.265 brouard 6012: } /* end loop s1 */
1.251 brouard 6013:
6014: printf("\n");
6015: fprintf(ficlog,"\n");
6016: } /* end j=0 */
1.249 brouard 6017: } /* end j */
1.252 brouard 6018:
1.253 brouard 6019: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 6020: for(i=1, jk=1; i <=nlstate; i++){
6021: for(j=1; j <=nlstate+ndeath; j++){
6022: if(j!=i){
6023: /*ca[0]= k+'a'-1;ca[1]='\0';*/
6024: printf("%1d%1d",i,j);
6025: fprintf(ficparo,"%1d%1d",i,j);
6026: for(k=1; k<=ncovmodel;k++){
6027: /* printf(" %lf",param[i][j][k]); */
6028: /* fprintf(ficparo," %lf",param[i][j][k]); */
6029: p[jk]=pstart[jk];
6030: printf(" %f ",pstart[jk]);
6031: fprintf(ficparo," %f ",pstart[jk]);
6032: jk++;
6033: }
6034: printf("\n");
6035: fprintf(ficparo,"\n");
6036: }
6037: }
6038: }
6039: } /* end mle=-2 */
1.226 brouard 6040: dateintmean=dateintsum/k2cpt;
1.296 brouard 6041: date2dmy(dateintmean,&jintmean,&mintmean,&aintmean);
1.240 brouard 6042:
1.226 brouard 6043: fclose(ficresp);
6044: fclose(ficresphtm);
6045: fclose(ficresphtmfr);
1.283 brouard 6046: free_vector(idq,1,nqfveff);
1.226 brouard 6047: free_vector(meanq,1,nqfveff);
1.284 brouard 6048: free_vector(stdq,1,nqfveff);
1.226 brouard 6049: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 6050: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
6051: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 6052: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 6053: free_vector(pospropt,1,nlstate);
6054: free_vector(posprop,1,nlstate);
1.251 brouard 6055: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 6056: free_vector(pp,1,nlstate);
6057: /* End of freqsummary */
6058: }
1.126 brouard 6059:
1.268 brouard 6060: /* Simple linear regression */
6061: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
6062:
6063: /* y=a+bx regression */
6064: double sumx = 0.0; /* sum of x */
6065: double sumx2 = 0.0; /* sum of x**2 */
6066: double sumxy = 0.0; /* sum of x * y */
6067: double sumy = 0.0; /* sum of y */
6068: double sumy2 = 0.0; /* sum of y**2 */
6069: double sume2 = 0.0; /* sum of square or residuals */
6070: double yhat;
6071:
6072: double denom=0;
6073: int i;
6074: int ne=*no;
6075:
6076: for ( i=ifi, ne=0;i<=ila;i++) {
6077: if(!isfinite(x[i]) || !isfinite(y[i])){
6078: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
6079: continue;
6080: }
6081: ne=ne+1;
6082: sumx += x[i];
6083: sumx2 += x[i]*x[i];
6084: sumxy += x[i] * y[i];
6085: sumy += y[i];
6086: sumy2 += y[i]*y[i];
6087: denom = (ne * sumx2 - sumx*sumx);
6088: /* 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); */
6089: }
6090:
6091: denom = (ne * sumx2 - sumx*sumx);
6092: if (denom == 0) {
6093: // vertical, slope m is infinity
6094: *b = INFINITY;
6095: *a = 0;
6096: if (r) *r = 0;
6097: return 1;
6098: }
6099:
6100: *b = (ne * sumxy - sumx * sumy) / denom;
6101: *a = (sumy * sumx2 - sumx * sumxy) / denom;
6102: if (r!=NULL) {
6103: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
6104: sqrt((sumx2 - sumx*sumx/ne) *
6105: (sumy2 - sumy*sumy/ne));
6106: }
6107: *no=ne;
6108: for ( i=ifi, ne=0;i<=ila;i++) {
6109: if(!isfinite(x[i]) || !isfinite(y[i])){
6110: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
6111: continue;
6112: }
6113: ne=ne+1;
6114: yhat = y[i] - *a -*b* x[i];
6115: sume2 += yhat * yhat ;
6116:
6117: denom = (ne * sumx2 - sumx*sumx);
6118: /* 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); */
6119: }
6120: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
6121: *sa= *sb * sqrt(sumx2/ne);
6122:
6123: return 0;
6124: }
6125:
1.126 brouard 6126: /************ Prevalence ********************/
1.227 brouard 6127: 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)
6128: {
6129: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
6130: in each health status at the date of interview (if between dateprev1 and dateprev2).
6131: We still use firstpass and lastpass as another selection.
6132: */
1.126 brouard 6133:
1.227 brouard 6134: int i, m, jk, j1, bool, z1,j, iv;
6135: int mi; /* Effective wave */
6136: int iage;
6137: double agebegin, ageend;
6138:
6139: double **prop;
6140: double posprop;
6141: double y2; /* in fractional years */
6142: int iagemin, iagemax;
6143: int first; /** to stop verbosity which is redirected to log file */
6144:
6145: iagemin= (int) agemin;
6146: iagemax= (int) agemax;
6147: /*pp=vector(1,nlstate);*/
1.251 brouard 6148: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 6149: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
6150: j1=0;
1.222 brouard 6151:
1.227 brouard 6152: /*j=cptcoveff;*/
6153: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 6154:
1.288 brouard 6155: first=0;
1.335 brouard 6156: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of simple dummy covariates */
1.227 brouard 6157: for (i=1; i<=nlstate; i++)
1.251 brouard 6158: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 6159: prop[i][iage]=0.0;
6160: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
6161: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
6162: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
6163:
6164: for (i=1; i<=imx; i++) { /* Each individual */
6165: bool=1;
6166: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
6167: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
6168: m=mw[mi][i];
6169: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
6170: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
6171: for (z1=1; z1<=cptcoveff; z1++){
6172: if( Fixed[Tmodelind[z1]]==1){
1.341 brouard 6173: iv= Tvar[Tmodelind[z1]];/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
1.332 brouard 6174: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) /* iv=1 to ntv, right modality */
1.227 brouard 6175: bool=0;
6176: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
1.332 brouard 6177: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) {
1.227 brouard 6178: bool=0;
6179: }
6180: }
6181: if(bool==1){ /* Otherwise we skip that wave/person */
6182: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
6183: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
6184: if(m >=firstpass && m <=lastpass){
6185: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
6186: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
6187: if(agev[m][i]==0) agev[m][i]=iagemax+1;
6188: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 6189: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 6190: 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);
6191: exit(1);
6192: }
6193: if (s[m][i]>0 && s[m][i]<=nlstate) {
6194: /*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]]);*/
6195: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
6196: prop[s[m][i]][iagemax+3] += weight[i];
6197: } /* end valid statuses */
6198: } /* end selection of dates */
6199: } /* end selection of waves */
6200: } /* end bool */
6201: } /* end wave */
6202: } /* end individual */
6203: for(i=iagemin; i <= iagemax+3; i++){
6204: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
6205: posprop += prop[jk][i];
6206: }
6207:
6208: for(jk=1; jk <=nlstate ; jk++){
6209: if( i <= iagemax){
6210: if(posprop>=1.e-5){
6211: probs[i][jk][j1]= prop[jk][i]/posprop;
6212: } else{
1.288 brouard 6213: if(!first){
6214: first=1;
1.266 brouard 6215: 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]);
6216: }else{
1.288 brouard 6217: 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 6218: }
6219: }
6220: }
6221: }/* end jk */
6222: }/* end i */
1.222 brouard 6223: /*} *//* end i1 */
1.227 brouard 6224: } /* end j1 */
1.222 brouard 6225:
1.227 brouard 6226: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
6227: /*free_vector(pp,1,nlstate);*/
1.251 brouard 6228: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 6229: } /* End of prevalence */
1.126 brouard 6230:
6231: /************* Waves Concatenation ***************/
6232:
6233: 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)
6234: {
1.298 brouard 6235: /* 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 6236: Death is a valid wave (if date is known).
6237: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
6238: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
1.298 brouard 6239: and mw[mi+1][i]. dh depends on stepm. s[m][i] exists for any wave from firstpass to lastpass
1.227 brouard 6240: */
1.126 brouard 6241:
1.224 brouard 6242: int i=0, mi=0, m=0, mli=0;
1.126 brouard 6243: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
6244: double sum=0., jmean=0.;*/
1.224 brouard 6245: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 6246: int j, k=0,jk, ju, jl;
6247: double sum=0.;
6248: first=0;
1.214 brouard 6249: firstwo=0;
1.217 brouard 6250: firsthree=0;
1.218 brouard 6251: firstfour=0;
1.164 brouard 6252: jmin=100000;
1.126 brouard 6253: jmax=-1;
6254: jmean=0.;
1.224 brouard 6255:
6256: /* Treating live states */
1.214 brouard 6257: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 6258: mi=0; /* First valid wave */
1.227 brouard 6259: mli=0; /* Last valid wave */
1.309 brouard 6260: m=firstpass; /* Loop on waves */
6261: while(s[m][i] <= nlstate){ /* a live state or unknown state */
1.227 brouard 6262: 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 */
6263: mli=m-1;/* mw[++mi][i]=m-1; */
6264: }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 6265: 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 6266: mli=m;
1.224 brouard 6267: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
6268: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 6269: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 6270: }
1.309 brouard 6271: else{ /* m = lastpass, eventual special issue with warning */
1.224 brouard 6272: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 6273: break;
1.224 brouard 6274: #else
1.317 brouard 6275: 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 6276: if(firsthree == 0){
1.302 brouard 6277: 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 6278: firsthree=1;
1.317 brouard 6279: }else if(firsthree >=1 && firsthree < 10){
6280: 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);
6281: firsthree++;
6282: }else if(firsthree == 10){
6283: printf("Information, too many Information flags: no more reported to log either\n");
6284: fprintf(ficlog,"Information, too many Information flags: no more reported to log either\n");
6285: firsthree++;
6286: }else{
6287: firsthree++;
1.227 brouard 6288: }
1.309 brouard 6289: mw[++mi][i]=m; /* Valid transition with unknown status */
1.227 brouard 6290: mli=m;
6291: }
6292: if(s[m][i]==-2){ /* Vital status is really unknown */
6293: nbwarn++;
1.309 brouard 6294: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified?not a transition */
1.227 brouard 6295: 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);
6296: 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);
6297: }
6298: break;
6299: }
6300: break;
1.224 brouard 6301: #endif
1.227 brouard 6302: }/* End m >= lastpass */
1.126 brouard 6303: }/* end while */
1.224 brouard 6304:
1.227 brouard 6305: /* 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 6306: /* After last pass */
1.224 brouard 6307: /* Treating death states */
1.214 brouard 6308: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 6309: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
6310: /* } */
1.126 brouard 6311: mi++; /* Death is another wave */
6312: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 6313: /* Only death is a correct wave */
1.126 brouard 6314: mw[mi][i]=m;
1.257 brouard 6315: } /* else not in a death state */
1.224 brouard 6316: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 6317: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 6318: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.309 brouard 6319: 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 6320: nbwarn++;
6321: if(firstfiv==0){
1.309 brouard 6322: 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 6323: firstfiv=1;
6324: }else{
1.309 brouard 6325: 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 6326: }
1.309 brouard 6327: s[m][i]=nlstate+1; /* Fixing the status as death. Be careful if multiple death states */
6328: }else{ /* Month of Death occured afer last wave month, potential bias */
1.227 brouard 6329: nberr++;
6330: if(firstwo==0){
1.309 brouard 6331: 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 6332: firstwo=1;
6333: }
1.309 brouard 6334: 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 6335: }
1.257 brouard 6336: }else{ /* if date of interview is unknown */
1.227 brouard 6337: /* death is known but not confirmed by death status at any wave */
6338: if(firstfour==0){
1.309 brouard 6339: 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 6340: firstfour=1;
6341: }
1.309 brouard 6342: 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 6343: }
1.224 brouard 6344: } /* end if date of death is known */
6345: #endif
1.309 brouard 6346: wav[i]=mi; /* mi should be the last effective wave (or mli), */
6347: /* wav[i]=mw[mi][i]; */
1.126 brouard 6348: if(mi==0){
6349: nbwarn++;
6350: if(first==0){
1.227 brouard 6351: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
6352: first=1;
1.126 brouard 6353: }
6354: if(first==1){
1.227 brouard 6355: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 6356: }
6357: } /* end mi==0 */
6358: } /* End individuals */
1.214 brouard 6359: /* wav and mw are no more changed */
1.223 brouard 6360:
1.317 brouard 6361: printf("Information, you have to check %d informations which haven't been logged!\n",firsthree);
6362: fprintf(ficlog,"Information, you have to check %d informations which haven't been logged!\n",firsthree);
6363:
6364:
1.126 brouard 6365: for(i=1; i<=imx; i++){
6366: for(mi=1; mi<wav[i];mi++){
6367: if (stepm <=0)
1.227 brouard 6368: dh[mi][i]=1;
1.126 brouard 6369: else{
1.260 brouard 6370: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 6371: if (agedc[i] < 2*AGESUP) {
6372: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
6373: if(j==0) j=1; /* Survives at least one month after exam */
6374: else if(j<0){
6375: nberr++;
6376: 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]);
6377: j=1; /* Temporary Dangerous patch */
6378: 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);
6379: 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]);
6380: 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);
6381: }
6382: k=k+1;
6383: if (j >= jmax){
6384: jmax=j;
6385: ijmax=i;
6386: }
6387: if (j <= jmin){
6388: jmin=j;
6389: ijmin=i;
6390: }
6391: sum=sum+j;
6392: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
6393: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
6394: }
6395: }
6396: else{
6397: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 6398: /* 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 6399:
1.227 brouard 6400: k=k+1;
6401: if (j >= jmax) {
6402: jmax=j;
6403: ijmax=i;
6404: }
6405: else if (j <= jmin){
6406: jmin=j;
6407: ijmin=i;
6408: }
6409: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
6410: /*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]);*/
6411: if(j<0){
6412: nberr++;
6413: 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]);
6414: 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]);
6415: }
6416: sum=sum+j;
6417: }
6418: jk= j/stepm;
6419: jl= j -jk*stepm;
6420: ju= j -(jk+1)*stepm;
6421: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
6422: if(jl==0){
6423: dh[mi][i]=jk;
6424: bh[mi][i]=0;
6425: }else{ /* We want a negative bias in order to only have interpolation ie
6426: * to avoid the price of an extra matrix product in likelihood */
6427: dh[mi][i]=jk+1;
6428: bh[mi][i]=ju;
6429: }
6430: }else{
6431: if(jl <= -ju){
6432: dh[mi][i]=jk;
6433: bh[mi][i]=jl; /* bias is positive if real duration
6434: * is higher than the multiple of stepm and negative otherwise.
6435: */
6436: }
6437: else{
6438: dh[mi][i]=jk+1;
6439: bh[mi][i]=ju;
6440: }
6441: if(dh[mi][i]==0){
6442: dh[mi][i]=1; /* At least one step */
6443: bh[mi][i]=ju; /* At least one step */
6444: /* 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);*/
6445: }
6446: } /* end if mle */
1.126 brouard 6447: }
6448: } /* end wave */
6449: }
6450: jmean=sum/k;
6451: 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 6452: 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 6453: }
1.126 brouard 6454:
6455: /*********** Tricode ****************************/
1.220 brouard 6456: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 6457: {
6458: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
6459: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
6460: * Boring subroutine which should only output nbcode[Tvar[j]][k]
6461: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
6462: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
6463: */
1.130 brouard 6464:
1.242 brouard 6465: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
6466: int modmaxcovj=0; /* Modality max of covariates j */
6467: int cptcode=0; /* Modality max of covariates j */
6468: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 6469:
6470:
1.242 brouard 6471: /* cptcoveff=0; */
6472: /* *cptcov=0; */
1.126 brouard 6473:
1.242 brouard 6474: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 6475: for (k=1; k <= maxncov; k++)
6476: for(j=1; j<=2; j++)
6477: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 6478:
1.242 brouard 6479: /* Loop on covariates without age and products and no quantitative variable */
1.335 brouard 6480: 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 6481: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
1.343 brouard 6482: /* printf("Testing k=%d, cptcovt=%d\n",k, cptcovt); */
1.349 brouard 6483: if(Dummy[k]==0 && Typevar[k] !=1 && Typevar[k] != 3 && Typevar[k] != 2){ /* Dummy covariate and not age product nor fixed product */
1.242 brouard 6484: switch(Fixed[k]) {
6485: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
1.311 brouard 6486: modmaxcovj=0;
6487: modmincovj=0;
1.242 brouard 6488: 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 6489: /* 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 6490: ij=(int)(covar[Tvar[k]][i]);
6491: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
6492: * If product of Vn*Vm, still boolean *:
6493: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
6494: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
6495: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
6496: modality of the nth covariate of individual i. */
6497: if (ij > modmaxcovj)
6498: modmaxcovj=ij;
6499: else if (ij < modmincovj)
6500: modmincovj=ij;
1.287 brouard 6501: if (ij <0 || ij >1 ){
1.311 brouard 6502: printf("ERROR, IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
6503: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
6504: fflush(ficlog);
6505: exit(1);
1.287 brouard 6506: }
6507: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 6508: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
6509: exit(1);
6510: }else
6511: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
6512: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
6513: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
6514: /* getting the maximum value of the modality of the covariate
6515: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
6516: female ies 1, then modmaxcovj=1.
6517: */
6518: } /* end for loop on individuals i */
6519: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
6520: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
6521: cptcode=modmaxcovj;
6522: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
6523: /*for (i=0; i<=cptcode; i++) {*/
6524: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
6525: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
6526: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
6527: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
6528: if( j != -1){
6529: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
6530: covariate for which somebody answered excluding
6531: undefined. Usually 2: 0 and 1. */
6532: }
6533: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
6534: covariate for which somebody answered including
6535: undefined. Usually 3: -1, 0 and 1. */
6536: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
6537: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
6538: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 6539:
1.242 brouard 6540: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
6541: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
6542: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
6543: /* modmincovj=3; modmaxcovj = 7; */
6544: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
6545: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
6546: /* defining two dummy variables: variables V1_1 and V1_2.*/
6547: /* nbcode[Tvar[j]][ij]=k; */
6548: /* nbcode[Tvar[j]][1]=0; */
6549: /* nbcode[Tvar[j]][2]=1; */
6550: /* nbcode[Tvar[j]][3]=2; */
6551: /* To be continued (not working yet). */
6552: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 6553:
6554: /* 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*/
6555: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
6556: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
6557: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
6558: /*, could be restored in the future */
6559: 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 6560: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
6561: break;
6562: }
6563: ij++;
1.287 brouard 6564: 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 6565: cptcode = ij; /* New max modality for covar j */
6566: } /* end of loop on modality i=-1 to 1 or more */
6567: break;
6568: case 1: /* Testing on varying covariate, could be simple and
6569: * should look at waves or product of fixed *
6570: * varying. No time to test -1, assuming 0 and 1 only */
6571: ij=0;
6572: for(i=0; i<=1;i++){
6573: nbcode[Tvar[k]][++ij]=i;
6574: }
6575: break;
6576: default:
6577: break;
6578: } /* end switch */
6579: } /* end dummy test */
1.349 brouard 6580: if(Dummy[k]==1 && Typevar[k] !=1 && Typevar[k] !=3 && Fixed ==0){ /* Fixed Quantitative covariate and not age product */
1.311 brouard 6581: 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 6582: if(Tvar[k]<=0 || Tvar[k]>=NCOVMAX){
6583: printf("Error k=%d \n",k);
6584: exit(1);
6585: }
1.311 brouard 6586: if(isnan(covar[Tvar[k]][i])){
6587: printf("ERROR, IMaCh doesn't treat fixed quantitative covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
6588: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
6589: fflush(ficlog);
6590: exit(1);
6591: }
6592: }
1.335 brouard 6593: } /* end Quanti */
1.287 brouard 6594: } /* 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 6595:
6596: for (k=-1; k< maxncov; k++) Ndum[k]=0;
6597: /* Look at fixed dummy (single or product) covariates to check empty modalities */
6598: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
6599: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
6600: 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 */
6601: 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 */
6602: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
6603: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
6604:
6605: ij=0;
6606: /* 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 6607: 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 */
6608: /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
1.242 brouard 6609: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
6610: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
1.335 brouard 6611: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy simple and non empty in the model */
6612: /* Typevar[k] =0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
6613: /* 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 6614: /* If product not in single variable we don't print results */
6615: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
1.335 brouard 6616: ++ij;/* V5 + V4 + V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V1, *//* V5 quanti, V2 quanti, V4, V3, V1 dummies */
6617: /* k= 1 2 3 4 5 6 7 8 9 */
6618: /* Tvar[k]= 5 4 3 6 5 2 7 1 1 */
6619: /* ij 1 2 3 */
6620: /* Tvaraff[ij]= 4 3 1 */
6621: /* Tmodelind[ij]=2 3 9 */
6622: /* TmodelInvind[ij]=2 1 1 */
1.242 brouard 6623: 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*/
6624: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
6625: 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 */
6626: if(Fixed[k]!=0)
6627: anyvaryingduminmodel=1;
6628: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
6629: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
6630: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
6631: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
6632: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
6633: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
6634: }
6635: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
6636: /* ij--; */
6637: /* cptcoveff=ij; /\*Number of total covariates*\/ */
1.335 brouard 6638: *cptcov=ij; /* cptcov= Number of total real effective simple dummies (fixed or time arying) effective (used as cptcoveff in other functions)
1.242 brouard 6639: * because they can be excluded from the model and real
6640: * if in the model but excluded because missing values, but how to get k from ij?*/
6641: for(j=ij+1; j<= cptcovt; j++){
6642: Tvaraff[j]=0;
6643: Tmodelind[j]=0;
6644: }
6645: for(j=ntveff+1; j<= cptcovt; j++){
6646: TmodelInvind[j]=0;
6647: }
6648: /* To be sorted */
6649: ;
6650: }
1.126 brouard 6651:
1.145 brouard 6652:
1.126 brouard 6653: /*********** Health Expectancies ****************/
6654:
1.235 brouard 6655: 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 6656:
6657: {
6658: /* Health expectancies, no variances */
1.329 brouard 6659: /* cij is the combination in the list of combination of dummy covariates */
6660: /* strstart is a string of time at start of computing */
1.164 brouard 6661: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 6662: int nhstepma, nstepma; /* Decreasing with age */
6663: double age, agelim, hf;
6664: double ***p3mat;
6665: double eip;
6666:
1.238 brouard 6667: /* pstamp(ficreseij); */
1.126 brouard 6668: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
6669: fprintf(ficreseij,"# Age");
6670: for(i=1; i<=nlstate;i++){
6671: for(j=1; j<=nlstate;j++){
6672: fprintf(ficreseij," e%1d%1d ",i,j);
6673: }
6674: fprintf(ficreseij," e%1d. ",i);
6675: }
6676: fprintf(ficreseij,"\n");
6677:
6678:
6679: if(estepm < stepm){
6680: printf ("Problem %d lower than %d\n",estepm, stepm);
6681: }
6682: else hstepm=estepm;
6683: /* We compute the life expectancy from trapezoids spaced every estepm months
6684: * This is mainly to measure the difference between two models: for example
6685: * if stepm=24 months pijx are given only every 2 years and by summing them
6686: * we are calculating an estimate of the Life Expectancy assuming a linear
6687: * progression in between and thus overestimating or underestimating according
6688: * to the curvature of the survival function. If, for the same date, we
6689: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6690: * to compare the new estimate of Life expectancy with the same linear
6691: * hypothesis. A more precise result, taking into account a more precise
6692: * curvature will be obtained if estepm is as small as stepm. */
6693:
6694: /* For example we decided to compute the life expectancy with the smallest unit */
6695: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6696: nhstepm is the number of hstepm from age to agelim
6697: nstepm is the number of stepm from age to agelin.
1.270 brouard 6698: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 6699: and note for a fixed period like estepm months */
6700: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6701: survival function given by stepm (the optimization length). Unfortunately it
6702: means that if the survival funtion is printed only each two years of age and if
6703: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6704: results. So we changed our mind and took the option of the best precision.
6705: */
6706: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6707:
6708: agelim=AGESUP;
6709: /* If stepm=6 months */
6710: /* Computed by stepm unit matrices, product of hstepm matrices, stored
6711: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
6712:
6713: /* nhstepm age range expressed in number of stepm */
6714: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6715: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6716: /* if (stepm >= YEARM) hstepm=1;*/
6717: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6718: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6719:
6720: for (age=bage; age<=fage; age ++){
6721: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6722: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6723: /* if (stepm >= YEARM) hstepm=1;*/
6724: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
6725:
6726: /* If stepm=6 months */
6727: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6728: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
1.330 brouard 6729: /* 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 6730: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 6731:
6732: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6733:
6734: printf("%d|",(int)age);fflush(stdout);
6735: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6736:
6737: /* Computing expectancies */
6738: for(i=1; i<=nlstate;i++)
6739: for(j=1; j<=nlstate;j++)
6740: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6741: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
6742:
6743: /* 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]);*/
6744:
6745: }
6746:
6747: fprintf(ficreseij,"%3.0f",age );
6748: for(i=1; i<=nlstate;i++){
6749: eip=0;
6750: for(j=1; j<=nlstate;j++){
6751: eip +=eij[i][j][(int)age];
6752: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
6753: }
6754: fprintf(ficreseij,"%9.4f", eip );
6755: }
6756: fprintf(ficreseij,"\n");
6757:
6758: }
6759: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6760: printf("\n");
6761: fprintf(ficlog,"\n");
6762:
6763: }
6764:
1.235 brouard 6765: 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 6766:
6767: {
6768: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 6769: to initial status i, ei. .
1.126 brouard 6770: */
1.336 brouard 6771: /* Very time consuming function, but already optimized with precov */
1.126 brouard 6772: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
6773: int nhstepma, nstepma; /* Decreasing with age */
6774: double age, agelim, hf;
6775: double ***p3matp, ***p3matm, ***varhe;
6776: double **dnewm,**doldm;
6777: double *xp, *xm;
6778: double **gp, **gm;
6779: double ***gradg, ***trgradg;
6780: int theta;
6781:
6782: double eip, vip;
6783:
6784: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
6785: xp=vector(1,npar);
6786: xm=vector(1,npar);
6787: dnewm=matrix(1,nlstate*nlstate,1,npar);
6788: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
6789:
6790: pstamp(ficresstdeij);
6791: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
6792: fprintf(ficresstdeij,"# Age");
6793: for(i=1; i<=nlstate;i++){
6794: for(j=1; j<=nlstate;j++)
6795: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
6796: fprintf(ficresstdeij," e%1d. ",i);
6797: }
6798: fprintf(ficresstdeij,"\n");
6799:
6800: pstamp(ficrescveij);
6801: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
6802: fprintf(ficrescveij,"# Age");
6803: for(i=1; i<=nlstate;i++)
6804: for(j=1; j<=nlstate;j++){
6805: cptj= (j-1)*nlstate+i;
6806: for(i2=1; i2<=nlstate;i2++)
6807: for(j2=1; j2<=nlstate;j2++){
6808: cptj2= (j2-1)*nlstate+i2;
6809: if(cptj2 <= cptj)
6810: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
6811: }
6812: }
6813: fprintf(ficrescveij,"\n");
6814:
6815: if(estepm < stepm){
6816: printf ("Problem %d lower than %d\n",estepm, stepm);
6817: }
6818: else hstepm=estepm;
6819: /* We compute the life expectancy from trapezoids spaced every estepm months
6820: * This is mainly to measure the difference between two models: for example
6821: * if stepm=24 months pijx are given only every 2 years and by summing them
6822: * we are calculating an estimate of the Life Expectancy assuming a linear
6823: * progression in between and thus overestimating or underestimating according
6824: * to the curvature of the survival function. If, for the same date, we
6825: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6826: * to compare the new estimate of Life expectancy with the same linear
6827: * hypothesis. A more precise result, taking into account a more precise
6828: * curvature will be obtained if estepm is as small as stepm. */
6829:
6830: /* For example we decided to compute the life expectancy with the smallest unit */
6831: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6832: nhstepm is the number of hstepm from age to agelim
6833: nstepm is the number of stepm from age to agelin.
6834: Look at hpijx to understand the reason of that which relies in memory size
6835: and note for a fixed period like estepm months */
6836: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6837: survival function given by stepm (the optimization length). Unfortunately it
6838: means that if the survival funtion is printed only each two years of age and if
6839: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6840: results. So we changed our mind and took the option of the best precision.
6841: */
6842: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6843:
6844: /* If stepm=6 months */
6845: /* nhstepm age range expressed in number of stepm */
6846: agelim=AGESUP;
6847: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
6848: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6849: /* if (stepm >= YEARM) hstepm=1;*/
6850: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6851:
6852: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6853: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6854: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
6855: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
6856: gp=matrix(0,nhstepm,1,nlstate*nlstate);
6857: gm=matrix(0,nhstepm,1,nlstate*nlstate);
6858:
6859: for (age=bage; age<=fage; age ++){
6860: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6861: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6862: /* if (stepm >= YEARM) hstepm=1;*/
6863: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 6864:
1.126 brouard 6865: /* If stepm=6 months */
6866: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6867: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
6868:
6869: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 6870:
1.126 brouard 6871: /* Computing Variances of health expectancies */
6872: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
6873: decrease memory allocation */
6874: for(theta=1; theta <=npar; theta++){
6875: for(i=1; i<=npar; i++){
1.222 brouard 6876: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6877: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 6878: }
1.235 brouard 6879: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
6880: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 6881:
1.126 brouard 6882: for(j=1; j<= nlstate; j++){
1.222 brouard 6883: for(i=1; i<=nlstate; i++){
6884: for(h=0; h<=nhstepm-1; h++){
6885: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
6886: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
6887: }
6888: }
1.126 brouard 6889: }
1.218 brouard 6890:
1.126 brouard 6891: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 6892: for(h=0; h<=nhstepm-1; h++){
6893: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
6894: }
1.126 brouard 6895: }/* End theta */
6896:
6897:
6898: for(h=0; h<=nhstepm-1; h++)
6899: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 6900: for(theta=1; theta <=npar; theta++)
6901: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 6902:
1.218 brouard 6903:
1.222 brouard 6904: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 6905: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 6906: varhe[ij][ji][(int)age] =0.;
1.218 brouard 6907:
1.222 brouard 6908: printf("%d|",(int)age);fflush(stdout);
6909: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6910: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 6911: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 6912: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
6913: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
6914: for(ij=1;ij<=nlstate*nlstate;ij++)
6915: for(ji=1;ji<=nlstate*nlstate;ji++)
6916: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 6917: }
6918: }
1.320 brouard 6919: /* if((int)age ==50){ */
6920: /* printf(" age=%d cij=%d nres=%d varhe[%d][%d]=%f ",(int)age, cij, nres, 1,2,varhe[1][2]); */
6921: /* } */
1.126 brouard 6922: /* Computing expectancies */
1.235 brouard 6923: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 6924: for(i=1; i<=nlstate;i++)
6925: for(j=1; j<=nlstate;j++)
1.222 brouard 6926: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6927: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 6928:
1.222 brouard 6929: /* 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 6930:
1.222 brouard 6931: }
1.269 brouard 6932:
6933: /* Standard deviation of expectancies ij */
1.126 brouard 6934: fprintf(ficresstdeij,"%3.0f",age );
6935: for(i=1; i<=nlstate;i++){
6936: eip=0.;
6937: vip=0.;
6938: for(j=1; j<=nlstate;j++){
1.222 brouard 6939: eip += eij[i][j][(int)age];
6940: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
6941: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
6942: 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 6943: }
6944: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
6945: }
6946: fprintf(ficresstdeij,"\n");
1.218 brouard 6947:
1.269 brouard 6948: /* Variance of expectancies ij */
1.126 brouard 6949: fprintf(ficrescveij,"%3.0f",age );
6950: for(i=1; i<=nlstate;i++)
6951: for(j=1; j<=nlstate;j++){
1.222 brouard 6952: cptj= (j-1)*nlstate+i;
6953: for(i2=1; i2<=nlstate;i2++)
6954: for(j2=1; j2<=nlstate;j2++){
6955: cptj2= (j2-1)*nlstate+i2;
6956: if(cptj2 <= cptj)
6957: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
6958: }
1.126 brouard 6959: }
6960: fprintf(ficrescveij,"\n");
1.218 brouard 6961:
1.126 brouard 6962: }
6963: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
6964: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
6965: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
6966: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
6967: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6968: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6969: printf("\n");
6970: fprintf(ficlog,"\n");
1.218 brouard 6971:
1.126 brouard 6972: free_vector(xm,1,npar);
6973: free_vector(xp,1,npar);
6974: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
6975: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
6976: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
6977: }
1.218 brouard 6978:
1.126 brouard 6979: /************ Variance ******************/
1.235 brouard 6980: 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 6981: {
1.279 brouard 6982: /** Variance of health expectancies
6983: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
6984: * double **newm;
6985: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
6986: */
1.218 brouard 6987:
6988: /* int movingaverage(); */
6989: double **dnewm,**doldm;
6990: double **dnewmp,**doldmp;
6991: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 6992: int first=0;
1.218 brouard 6993: int k;
6994: double *xp;
1.279 brouard 6995: double **gp, **gm; /**< for var eij */
6996: double ***gradg, ***trgradg; /**< for var eij */
6997: double **gradgp, **trgradgp; /**< for var p point j */
6998: double *gpp, *gmp; /**< for var p point j */
6999: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 7000: double ***p3mat;
7001: double age,agelim, hf;
7002: /* double ***mobaverage; */
7003: int theta;
7004: char digit[4];
7005: char digitp[25];
7006:
7007: char fileresprobmorprev[FILENAMELENGTH];
7008:
7009: if(popbased==1){
7010: if(mobilav!=0)
7011: strcpy(digitp,"-POPULBASED-MOBILAV_");
7012: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
7013: }
7014: else
7015: strcpy(digitp,"-STABLBASED_");
1.126 brouard 7016:
1.218 brouard 7017: /* if (mobilav!=0) { */
7018: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
7019: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
7020: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
7021: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
7022: /* } */
7023: /* } */
7024:
7025: strcpy(fileresprobmorprev,"PRMORPREV-");
7026: sprintf(digit,"%-d",ij);
7027: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
7028: strcat(fileresprobmorprev,digit); /* Tvar to be done */
7029: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
7030: strcat(fileresprobmorprev,fileresu);
7031: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
7032: printf("Problem with resultfile: %s\n", fileresprobmorprev);
7033: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
7034: }
7035: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
7036: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
7037: pstamp(ficresprobmorprev);
7038: 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 7039: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
1.337 brouard 7040:
7041: /* We use TinvDoQresult[nres][resultmodel[nres][j] we sort according to the equation model and the resultline: it is a choice */
7042: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ /\* To be done*\/ */
7043: /* fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
7044: /* } */
7045: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */ /* To be done*/
1.344 brouard 7046: /* fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); */
1.337 brouard 7047: fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 7048: }
1.337 brouard 7049: /* for(j=1;j<=cptcoveff;j++) */
7050: /* fprintf(ficresprobmorprev," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,TnsdVar[Tvaraff[j]])]); */
1.238 brouard 7051: fprintf(ficresprobmorprev,"\n");
7052:
1.218 brouard 7053: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
7054: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
7055: fprintf(ficresprobmorprev," p.%-d SE",j);
7056: for(i=1; i<=nlstate;i++)
7057: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
7058: }
7059: fprintf(ficresprobmorprev,"\n");
7060:
7061: fprintf(ficgp,"\n# Routine varevsij");
7062: fprintf(ficgp,"\nunset title \n");
7063: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
7064: 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");
7065: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 7066:
1.218 brouard 7067: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7068: pstamp(ficresvij);
7069: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
7070: if(popbased==1)
7071: 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);
7072: else
7073: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
7074: fprintf(ficresvij,"# Age");
7075: for(i=1; i<=nlstate;i++)
7076: for(j=1; j<=nlstate;j++)
7077: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
7078: fprintf(ficresvij,"\n");
7079:
7080: xp=vector(1,npar);
7081: dnewm=matrix(1,nlstate,1,npar);
7082: doldm=matrix(1,nlstate,1,nlstate);
7083: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
7084: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7085:
7086: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
7087: gpp=vector(nlstate+1,nlstate+ndeath);
7088: gmp=vector(nlstate+1,nlstate+ndeath);
7089: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 7090:
1.218 brouard 7091: if(estepm < stepm){
7092: printf ("Problem %d lower than %d\n",estepm, stepm);
7093: }
7094: else hstepm=estepm;
7095: /* For example we decided to compute the life expectancy with the smallest unit */
7096: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
7097: nhstepm is the number of hstepm from age to agelim
7098: nstepm is the number of stepm from age to agelim.
7099: Look at function hpijx to understand why because of memory size limitations,
7100: we decided (b) to get a life expectancy respecting the most precise curvature of the
7101: survival function given by stepm (the optimization length). Unfortunately it
7102: means that if the survival funtion is printed every two years of age and if
7103: you sum them up and add 1 year (area under the trapezoids) you won't get the same
7104: results. So we changed our mind and took the option of the best precision.
7105: */
7106: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
7107: agelim = AGESUP;
7108: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
7109: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7110: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
7111: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
7112: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
7113: gp=matrix(0,nhstepm,1,nlstate);
7114: gm=matrix(0,nhstepm,1,nlstate);
7115:
7116:
7117: for(theta=1; theta <=npar; theta++){
7118: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
7119: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7120: }
1.279 brouard 7121: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
7122: * returns into prlim .
1.288 brouard 7123: */
1.242 brouard 7124: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 7125:
7126: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 7127: if (popbased==1) {
7128: if(mobilav ==0){
7129: for(i=1; i<=nlstate;i++)
7130: prlim[i][i]=probs[(int)age][i][ij];
7131: }else{ /* mobilav */
7132: for(i=1; i<=nlstate;i++)
7133: prlim[i][i]=mobaverage[(int)age][i][ij];
7134: }
7135: }
1.295 brouard 7136: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h.
1.279 brouard 7137: */
7138: 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 7139: /**< 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 7140: * at horizon h in state j including mortality.
7141: */
1.218 brouard 7142: for(j=1; j<= nlstate; j++){
7143: for(h=0; h<=nhstepm; h++){
7144: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
7145: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
7146: }
7147: }
1.279 brouard 7148: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 7149: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 7150: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 7151: */
7152: for(j=nlstate+1;j<=nlstate+ndeath;j++){
7153: for(i=1,gpp[j]=0.; i<= nlstate; i++)
7154: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 7155: }
7156:
7157: /* Again with minus shift */
1.218 brouard 7158:
7159: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
7160: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 7161:
1.242 brouard 7162: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 7163:
7164: if (popbased==1) {
7165: if(mobilav ==0){
7166: for(i=1; i<=nlstate;i++)
7167: prlim[i][i]=probs[(int)age][i][ij];
7168: }else{ /* mobilav */
7169: for(i=1; i<=nlstate;i++)
7170: prlim[i][i]=mobaverage[(int)age][i][ij];
7171: }
7172: }
7173:
1.235 brouard 7174: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 7175:
7176: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
7177: for(h=0; h<=nhstepm; h++){
7178: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
7179: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
7180: }
7181: }
7182: /* This for computing probability of death (h=1 means
7183: computed over hstepm matrices product = hstepm*stepm months)
7184: as a weighted average of prlim.
7185: */
7186: for(j=nlstate+1;j<=nlstate+ndeath;j++){
7187: for(i=1,gmp[j]=0.; i<= nlstate; i++)
7188: gmp[j] += prlim[i][i]*p3mat[i][j][1];
7189: }
1.279 brouard 7190: /* end shifting computations */
7191:
7192: /**< Computing gradient matrix at horizon h
7193: */
1.218 brouard 7194: for(j=1; j<= nlstate; j++) /* vareij */
7195: for(h=0; h<=nhstepm; h++){
7196: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
7197: }
1.279 brouard 7198: /**< Gradient of overall mortality p.3 (or p.j)
7199: */
7200: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 7201: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
7202: }
7203:
7204: } /* End theta */
1.279 brouard 7205:
7206: /* We got the gradient matrix for each theta and state j */
1.218 brouard 7207: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
7208:
7209: for(h=0; h<=nhstepm; h++) /* veij */
7210: for(j=1; j<=nlstate;j++)
7211: for(theta=1; theta <=npar; theta++)
7212: trgradg[h][j][theta]=gradg[h][theta][j];
7213:
7214: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
7215: for(theta=1; theta <=npar; theta++)
7216: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 7217: /**< as well as its transposed matrix
7218: */
1.218 brouard 7219:
7220: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
7221: for(i=1;i<=nlstate;i++)
7222: for(j=1;j<=nlstate;j++)
7223: vareij[i][j][(int)age] =0.;
1.279 brouard 7224:
7225: /* Computing trgradg by matcov by gradg at age and summing over h
7226: * and k (nhstepm) formula 15 of article
7227: * Lievre-Brouard-Heathcote
7228: */
7229:
1.218 brouard 7230: for(h=0;h<=nhstepm;h++){
7231: for(k=0;k<=nhstepm;k++){
7232: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
7233: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
7234: for(i=1;i<=nlstate;i++)
7235: for(j=1;j<=nlstate;j++)
7236: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
7237: }
7238: }
7239:
1.279 brouard 7240: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
7241: * p.j overall mortality formula 49 but computed directly because
7242: * we compute the grad (wix pijx) instead of grad (pijx),even if
7243: * wix is independent of theta.
7244: */
1.218 brouard 7245: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
7246: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
7247: for(j=nlstate+1;j<=nlstate+ndeath;j++)
7248: for(i=nlstate+1;i<=nlstate+ndeath;i++)
7249: varppt[j][i]=doldmp[j][i];
7250: /* end ppptj */
7251: /* x centered again */
7252:
1.242 brouard 7253: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 7254:
7255: if (popbased==1) {
7256: if(mobilav ==0){
7257: for(i=1; i<=nlstate;i++)
7258: prlim[i][i]=probs[(int)age][i][ij];
7259: }else{ /* mobilav */
7260: for(i=1; i<=nlstate;i++)
7261: prlim[i][i]=mobaverage[(int)age][i][ij];
7262: }
7263: }
7264:
7265: /* This for computing probability of death (h=1 means
7266: computed over hstepm (estepm) matrices product = hstepm*stepm months)
7267: as a weighted average of prlim.
7268: */
1.235 brouard 7269: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 7270: for(j=nlstate+1;j<=nlstate+ndeath;j++){
7271: for(i=1,gmp[j]=0.;i<= nlstate; i++)
7272: gmp[j] += prlim[i][i]*p3mat[i][j][1];
7273: }
7274: /* end probability of death */
7275:
7276: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
7277: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
7278: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
7279: for(i=1; i<=nlstate;i++){
7280: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
7281: }
7282: }
7283: fprintf(ficresprobmorprev,"\n");
7284:
7285: fprintf(ficresvij,"%.0f ",age );
7286: for(i=1; i<=nlstate;i++)
7287: for(j=1; j<=nlstate;j++){
7288: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
7289: }
7290: fprintf(ficresvij,"\n");
7291: free_matrix(gp,0,nhstepm,1,nlstate);
7292: free_matrix(gm,0,nhstepm,1,nlstate);
7293: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
7294: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
7295: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
7296: } /* End age */
7297: free_vector(gpp,nlstate+1,nlstate+ndeath);
7298: free_vector(gmp,nlstate+1,nlstate+ndeath);
7299: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
7300: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
7301: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
7302: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
7303: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
7304: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
7305: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
7306: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
7307: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
7308: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
7309: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
7310: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
7311: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
7312: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
7313: 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);
7314: /* 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 7315: */
1.218 brouard 7316: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
7317: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 7318:
1.218 brouard 7319: free_vector(xp,1,npar);
7320: free_matrix(doldm,1,nlstate,1,nlstate);
7321: free_matrix(dnewm,1,nlstate,1,npar);
7322: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7323: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
7324: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7325: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
7326: fclose(ficresprobmorprev);
7327: fflush(ficgp);
7328: fflush(fichtm);
7329: } /* end varevsij */
1.126 brouard 7330:
7331: /************ Variance of prevlim ******************/
1.269 brouard 7332: 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 7333: {
1.205 brouard 7334: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 7335: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 7336:
1.268 brouard 7337: double **dnewmpar,**doldm;
1.126 brouard 7338: int i, j, nhstepm, hstepm;
7339: double *xp;
7340: double *gp, *gm;
7341: double **gradg, **trgradg;
1.208 brouard 7342: double **mgm, **mgp;
1.126 brouard 7343: double age,agelim;
7344: int theta;
7345:
7346: pstamp(ficresvpl);
1.288 brouard 7347: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 7348: fprintf(ficresvpl,"# Age ");
7349: if(nresult >=1)
7350: fprintf(ficresvpl," Result# ");
1.126 brouard 7351: for(i=1; i<=nlstate;i++)
7352: fprintf(ficresvpl," %1d-%1d",i,i);
7353: fprintf(ficresvpl,"\n");
7354:
7355: xp=vector(1,npar);
1.268 brouard 7356: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 7357: doldm=matrix(1,nlstate,1,nlstate);
7358:
7359: hstepm=1*YEARM; /* Every year of age */
7360: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
7361: agelim = AGESUP;
7362: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
7363: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7364: if (stepm >= YEARM) hstepm=1;
7365: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
7366: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 7367: mgp=matrix(1,npar,1,nlstate);
7368: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 7369: gp=vector(1,nlstate);
7370: gm=vector(1,nlstate);
7371:
7372: for(theta=1; theta <=npar; theta++){
7373: for(i=1; i<=npar; i++){ /* Computes gradient */
7374: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7375: }
1.288 brouard 7376: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
7377: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
7378: /* else */
7379: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 7380: for(i=1;i<=nlstate;i++){
1.126 brouard 7381: gp[i] = prlim[i][i];
1.208 brouard 7382: mgp[theta][i] = prlim[i][i];
7383: }
1.126 brouard 7384: for(i=1; i<=npar; i++) /* Computes gradient */
7385: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 7386: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
7387: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
7388: /* else */
7389: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 7390: for(i=1;i<=nlstate;i++){
1.126 brouard 7391: gm[i] = prlim[i][i];
1.208 brouard 7392: mgm[theta][i] = prlim[i][i];
7393: }
1.126 brouard 7394: for(i=1;i<=nlstate;i++)
7395: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 7396: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 7397: } /* End theta */
7398:
7399: trgradg =matrix(1,nlstate,1,npar);
7400:
7401: for(j=1; j<=nlstate;j++)
7402: for(theta=1; theta <=npar; theta++)
7403: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 7404: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7405: /* printf("\nmgm mgp %d ",(int)age); */
7406: /* for(j=1; j<=nlstate;j++){ */
7407: /* printf(" %d ",j); */
7408: /* for(theta=1; theta <=npar; theta++) */
7409: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
7410: /* printf("\n "); */
7411: /* } */
7412: /* } */
7413: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7414: /* printf("\n gradg %d ",(int)age); */
7415: /* for(j=1; j<=nlstate;j++){ */
7416: /* printf("%d ",j); */
7417: /* for(theta=1; theta <=npar; theta++) */
7418: /* printf("%d %lf ",theta,gradg[theta][j]); */
7419: /* printf("\n "); */
7420: /* } */
7421: /* } */
1.126 brouard 7422:
7423: for(i=1;i<=nlstate;i++)
7424: varpl[i][(int)age] =0.;
1.209 brouard 7425: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 7426: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7427: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 7428: }else{
1.268 brouard 7429: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7430: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 7431: }
1.126 brouard 7432: for(i=1;i<=nlstate;i++)
7433: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
7434:
7435: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 7436: if(nresult >=1)
7437: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 7438: for(i=1; i<=nlstate;i++){
1.126 brouard 7439: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 7440: /* for(j=1;j<=nlstate;j++) */
7441: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
7442: }
1.126 brouard 7443: fprintf(ficresvpl,"\n");
7444: free_vector(gp,1,nlstate);
7445: free_vector(gm,1,nlstate);
1.208 brouard 7446: free_matrix(mgm,1,npar,1,nlstate);
7447: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 7448: free_matrix(gradg,1,npar,1,nlstate);
7449: free_matrix(trgradg,1,nlstate,1,npar);
7450: } /* End age */
7451:
7452: free_vector(xp,1,npar);
7453: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 7454: free_matrix(dnewmpar,1,nlstate,1,nlstate);
7455:
7456: }
7457:
7458:
7459: /************ Variance of backprevalence limit ******************/
1.269 brouard 7460: 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 7461: {
7462: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
7463: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
7464:
7465: double **dnewmpar,**doldm;
7466: int i, j, nhstepm, hstepm;
7467: double *xp;
7468: double *gp, *gm;
7469: double **gradg, **trgradg;
7470: double **mgm, **mgp;
7471: double age,agelim;
7472: int theta;
7473:
7474: pstamp(ficresvbl);
7475: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
7476: fprintf(ficresvbl,"# Age ");
7477: if(nresult >=1)
7478: fprintf(ficresvbl," Result# ");
7479: for(i=1; i<=nlstate;i++)
7480: fprintf(ficresvbl," %1d-%1d",i,i);
7481: fprintf(ficresvbl,"\n");
7482:
7483: xp=vector(1,npar);
7484: dnewmpar=matrix(1,nlstate,1,npar);
7485: doldm=matrix(1,nlstate,1,nlstate);
7486:
7487: hstepm=1*YEARM; /* Every year of age */
7488: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
7489: agelim = AGEINF;
7490: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
7491: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7492: if (stepm >= YEARM) hstepm=1;
7493: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
7494: gradg=matrix(1,npar,1,nlstate);
7495: mgp=matrix(1,npar,1,nlstate);
7496: mgm=matrix(1,npar,1,nlstate);
7497: gp=vector(1,nlstate);
7498: gm=vector(1,nlstate);
7499:
7500: for(theta=1; theta <=npar; theta++){
7501: for(i=1; i<=npar; i++){ /* Computes gradient */
7502: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7503: }
7504: if(mobilavproj > 0 )
7505: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7506: else
7507: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7508: for(i=1;i<=nlstate;i++){
7509: gp[i] = bprlim[i][i];
7510: mgp[theta][i] = bprlim[i][i];
7511: }
7512: for(i=1; i<=npar; i++) /* Computes gradient */
7513: xp[i] = x[i] - (i==theta ?delti[theta]:0);
7514: if(mobilavproj > 0 )
7515: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7516: else
7517: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7518: for(i=1;i<=nlstate;i++){
7519: gm[i] = bprlim[i][i];
7520: mgm[theta][i] = bprlim[i][i];
7521: }
7522: for(i=1;i<=nlstate;i++)
7523: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
7524: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
7525: } /* End theta */
7526:
7527: trgradg =matrix(1,nlstate,1,npar);
7528:
7529: for(j=1; j<=nlstate;j++)
7530: for(theta=1; theta <=npar; theta++)
7531: trgradg[j][theta]=gradg[theta][j];
7532: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7533: /* printf("\nmgm mgp %d ",(int)age); */
7534: /* for(j=1; j<=nlstate;j++){ */
7535: /* printf(" %d ",j); */
7536: /* for(theta=1; theta <=npar; theta++) */
7537: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
7538: /* printf("\n "); */
7539: /* } */
7540: /* } */
7541: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7542: /* printf("\n gradg %d ",(int)age); */
7543: /* for(j=1; j<=nlstate;j++){ */
7544: /* printf("%d ",j); */
7545: /* for(theta=1; theta <=npar; theta++) */
7546: /* printf("%d %lf ",theta,gradg[theta][j]); */
7547: /* printf("\n "); */
7548: /* } */
7549: /* } */
7550:
7551: for(i=1;i<=nlstate;i++)
7552: varbpl[i][(int)age] =0.;
7553: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
7554: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7555: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
7556: }else{
7557: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7558: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
7559: }
7560: for(i=1;i<=nlstate;i++)
7561: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
7562:
7563: fprintf(ficresvbl,"%.0f ",age );
7564: if(nresult >=1)
7565: fprintf(ficresvbl,"%d ",nres );
7566: for(i=1; i<=nlstate;i++)
7567: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
7568: fprintf(ficresvbl,"\n");
7569: free_vector(gp,1,nlstate);
7570: free_vector(gm,1,nlstate);
7571: free_matrix(mgm,1,npar,1,nlstate);
7572: free_matrix(mgp,1,npar,1,nlstate);
7573: free_matrix(gradg,1,npar,1,nlstate);
7574: free_matrix(trgradg,1,nlstate,1,npar);
7575: } /* End age */
7576:
7577: free_vector(xp,1,npar);
7578: free_matrix(doldm,1,nlstate,1,npar);
7579: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 7580:
7581: }
7582:
7583: /************ Variance of one-step probabilities ******************/
7584: 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 7585: {
7586: int i, j=0, k1, l1, tj;
7587: int k2, l2, j1, z1;
7588: int k=0, l;
7589: int first=1, first1, first2;
1.326 brouard 7590: int nres=0; /* New */
1.222 brouard 7591: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
7592: double **dnewm,**doldm;
7593: double *xp;
7594: double *gp, *gm;
7595: double **gradg, **trgradg;
7596: double **mu;
7597: double age, cov[NCOVMAX+1];
7598: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
7599: int theta;
7600: char fileresprob[FILENAMELENGTH];
7601: char fileresprobcov[FILENAMELENGTH];
7602: char fileresprobcor[FILENAMELENGTH];
7603: double ***varpij;
7604:
7605: strcpy(fileresprob,"PROB_");
7606: strcat(fileresprob,fileres);
7607: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
7608: printf("Problem with resultfile: %s\n", fileresprob);
7609: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
7610: }
7611: strcpy(fileresprobcov,"PROBCOV_");
7612: strcat(fileresprobcov,fileresu);
7613: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
7614: printf("Problem with resultfile: %s\n", fileresprobcov);
7615: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
7616: }
7617: strcpy(fileresprobcor,"PROBCOR_");
7618: strcat(fileresprobcor,fileresu);
7619: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
7620: printf("Problem with resultfile: %s\n", fileresprobcor);
7621: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
7622: }
7623: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7624: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7625: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7626: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7627: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7628: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7629: pstamp(ficresprob);
7630: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
7631: fprintf(ficresprob,"# Age");
7632: pstamp(ficresprobcov);
7633: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
7634: fprintf(ficresprobcov,"# Age");
7635: pstamp(ficresprobcor);
7636: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
7637: fprintf(ficresprobcor,"# Age");
1.126 brouard 7638:
7639:
1.222 brouard 7640: for(i=1; i<=nlstate;i++)
7641: for(j=1; j<=(nlstate+ndeath);j++){
7642: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
7643: fprintf(ficresprobcov," p%1d-%1d ",i,j);
7644: fprintf(ficresprobcor," p%1d-%1d ",i,j);
7645: }
7646: /* fprintf(ficresprob,"\n");
7647: fprintf(ficresprobcov,"\n");
7648: fprintf(ficresprobcor,"\n");
7649: */
7650: xp=vector(1,npar);
7651: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7652: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
7653: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
7654: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
7655: first=1;
7656: fprintf(ficgp,"\n# Routine varprob");
7657: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
7658: fprintf(fichtm,"\n");
7659:
1.288 brouard 7660: 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 7661: 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);
7662: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 7663: and drawn. It helps understanding how is the covariance between two incidences.\
7664: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 7665: 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 7666: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
7667: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
7668: standard deviations wide on each axis. <br>\
7669: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
7670: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
7671: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
7672:
1.222 brouard 7673: cov[1]=1;
7674: /* tj=cptcoveff; */
1.225 brouard 7675: tj = (int) pow(2,cptcoveff);
1.222 brouard 7676: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
7677: j1=0;
1.332 brouard 7678:
7679: for(nres=1;nres <=nresult; nres++){ /* For each resultline */
7680: for(j1=1; j1<=tj;j1++){ /* For any combination of dummy covariates, fixed and varying */
1.342 brouard 7681: /* 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 7682: if(tj != 1 && TKresult[nres]!= j1)
7683: continue;
7684:
7685: /* for(j1=1; j1<=tj;j1++){ /\* For each valid combination of covariates or only once*\/ */
7686: /* for(nres=1;nres <=1; nres++){ /\* For each resultline *\/ */
7687: /* /\* for(nres=1;nres <=nresult; nres++){ /\\* For each resultline *\\/ *\/ */
1.222 brouard 7688: if (cptcovn>0) {
1.334 brouard 7689: fprintf(ficresprob, "\n#********** Variable ");
7690: fprintf(ficresprobcov, "\n#********** Variable ");
7691: fprintf(ficgp, "\n#********** Variable ");
7692: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
7693: fprintf(ficresprobcor, "\n#********** Variable ");
7694:
7695: /* Including quantitative variables of the resultline to be done */
7696: for (z1=1; z1<=cptcovs; z1++){ /* Loop on each variable of this resultline */
1.343 brouard 7697: /* printf("Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model); */
1.338 brouard 7698: fprintf(ficlog,"Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model);
7699: /* 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 7700: if(Dummy[modelresult[nres][z1]]==0){/* Dummy variable of the variable in position modelresult in the model corresponding to z1 in resultline */
7701: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed referenced to model equation */
7702: 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 */
7703: 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 */
7704: 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 */
7705: 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 */
7706: 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 */
7707: fprintf(ficresprob,"fixed ");
7708: fprintf(ficresprobcov,"fixed ");
7709: fprintf(ficgp,"fixed ");
7710: fprintf(fichtmcov,"fixed ");
7711: fprintf(ficresprobcor,"fixed ");
7712: }else{
7713: fprintf(ficresprob,"varyi ");
7714: fprintf(ficresprobcov,"varyi ");
7715: fprintf(ficgp,"varyi ");
7716: fprintf(fichtmcov,"varyi ");
7717: fprintf(ficresprobcor,"varyi ");
7718: }
7719: }else if(Dummy[modelresult[nres][z1]]==1){ /* Quanti variable */
7720: /* For each selected (single) quantitative value */
1.337 brouard 7721: fprintf(ficresprob," V%d=%lg ",Tvqresult[nres][z1],Tqresult[nres][z1]);
1.334 brouard 7722: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed */
7723: fprintf(ficresprob,"fixed ");
7724: fprintf(ficresprobcov,"fixed ");
7725: fprintf(ficgp,"fixed ");
7726: fprintf(fichtmcov,"fixed ");
7727: fprintf(ficresprobcor,"fixed ");
7728: }else{
7729: fprintf(ficresprob,"varyi ");
7730: fprintf(ficresprobcov,"varyi ");
7731: fprintf(ficgp,"varyi ");
7732: fprintf(fichtmcov,"varyi ");
7733: fprintf(ficresprobcor,"varyi ");
7734: }
7735: }else{
7736: 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 */
7737: 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 */
7738: exit(1);
7739: }
7740: } /* End loop on variable of this resultline */
7741: /* for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]); */
1.222 brouard 7742: fprintf(ficresprob, "**********\n#\n");
7743: fprintf(ficresprobcov, "**********\n#\n");
7744: fprintf(ficgp, "**********\n#\n");
7745: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
7746: fprintf(ficresprobcor, "**********\n#");
7747: if(invalidvarcomb[j1]){
7748: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
7749: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
7750: continue;
7751: }
7752: }
7753: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
7754: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7755: gp=vector(1,(nlstate)*(nlstate+ndeath));
7756: gm=vector(1,(nlstate)*(nlstate+ndeath));
1.334 brouard 7757: for (age=bage; age<=fage; age ++){ /* Fo each age we feed the model equation with covariates, using precov as in hpxij() ? */
1.222 brouard 7758: cov[2]=age;
7759: if(nagesqr==1)
7760: cov[3]= age*age;
1.334 brouard 7761: /* New code end of combination but for each resultline */
7762: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 7763: if(Typevar[k1]==1 || Typevar[k1] ==3){ /* A product with age */
1.334 brouard 7764: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.326 brouard 7765: }else{
1.334 brouard 7766: cov[2+nagesqr+k1]=precov[nres][k1];
1.326 brouard 7767: }
1.334 brouard 7768: }/* End of loop on model equation */
7769: /* Old code */
7770: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
7771: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)]; *\/ */
7772: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
7773: /* /\* Here comes the value of the covariate 'j1' after renumbering k with single dummy covariates *\/ */
7774: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(j1,TnsdVar[TvarsD[k]])]; */
7775: /* /\*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*\//\* j1 1 2 3 4 */
7776: /* * 1 1 1 1 1 */
7777: /* * 2 2 1 1 1 */
7778: /* * 3 1 2 1 1 */
7779: /* *\/ */
7780: /* /\* nbcode[1][1]=0 nbcode[1][2]=1;*\/ */
7781: /* } */
7782: /* /\* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
7783: /* /\* ) p nbcode[Tvar[Tage[k]]][(1 & (ij-1) >> (k-1))+1] *\/ */
7784: /* /\*for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; *\/ */
7785: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
7786: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
7787: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(j1,TnsdVar[Tvar[Tage[k]]])]*cov[2]; */
7788: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
7789: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
7790: /* 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]); */
7791: /* /\* cov[2+nagesqr+Tage[k]]=meanq[k]/idq[k]*cov[2];/\\* Using the mean of quantitative variable Tvar[Tage[k]] /\\* Tqresult[nres][k]; *\\/ *\/ */
7792: /* /\* exit(1); *\/ */
7793: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
7794: /* } */
7795: /* /\* cov[2+Tage[k]+nagesqr]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
7796: /* } */
7797: /* for (k=1; k<=cptcovprod;k++){/\* For product without age *\/ */
7798: /* if(Dummy[Tvard[k][1]]==0){ */
7799: /* if(Dummy[Tvard[k][2]]==0){ */
7800: /* 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]])]; */
7801: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
7802: /* }else{ /\* Should we use the mean of the quantitative variables? *\/ */
7803: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(j1,TnsdVar[Tvard[k][1]])] * Tqresult[nres][resultmodel[nres][k]]; */
7804: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
7805: /* } */
7806: /* }else{ */
7807: /* if(Dummy[Tvard[k][2]]==0){ */
7808: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(j1,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][TnsdVar[Tvard[k][1]]]; */
7809: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
7810: /* }else{ */
7811: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][TnsdVar[Tvard[k][1]]]* Tqinvresult[nres][TnsdVar[Tvard[k][2]]]; */
7812: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
7813: /* } */
7814: /* } */
7815: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
7816: /* } */
1.326 brouard 7817: /* For each age and combination of dummy covariates we slightly move the parameters of delti in order to get the gradient*/
1.222 brouard 7818: for(theta=1; theta <=npar; theta++){
7819: for(i=1; i<=npar; i++)
7820: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 7821:
1.222 brouard 7822: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 7823:
1.222 brouard 7824: k=0;
7825: for(i=1; i<= (nlstate); i++){
7826: for(j=1; j<=(nlstate+ndeath);j++){
7827: k=k+1;
7828: gp[k]=pmmij[i][j];
7829: }
7830: }
1.220 brouard 7831:
1.222 brouard 7832: for(i=1; i<=npar; i++)
7833: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 7834:
1.222 brouard 7835: pmij(pmmij,cov,ncovmodel,xp,nlstate);
7836: k=0;
7837: for(i=1; i<=(nlstate); i++){
7838: for(j=1; j<=(nlstate+ndeath);j++){
7839: k=k+1;
7840: gm[k]=pmmij[i][j];
7841: }
7842: }
1.220 brouard 7843:
1.222 brouard 7844: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
7845: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
7846: }
1.126 brouard 7847:
1.222 brouard 7848: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
7849: for(theta=1; theta <=npar; theta++)
7850: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 7851:
1.222 brouard 7852: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
7853: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 7854:
1.222 brouard 7855: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 7856:
1.222 brouard 7857: k=0;
7858: for(i=1; i<=(nlstate); i++){
7859: for(j=1; j<=(nlstate+ndeath);j++){
7860: k=k+1;
7861: mu[k][(int) age]=pmmij[i][j];
7862: }
7863: }
7864: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
7865: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
7866: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 7867:
1.222 brouard 7868: /*printf("\n%d ",(int)age);
7869: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7870: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7871: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7872: }*/
1.220 brouard 7873:
1.222 brouard 7874: fprintf(ficresprob,"\n%d ",(int)age);
7875: fprintf(ficresprobcov,"\n%d ",(int)age);
7876: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 7877:
1.222 brouard 7878: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
7879: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
7880: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7881: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
7882: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
7883: }
7884: i=0;
7885: for (k=1; k<=(nlstate);k++){
7886: for (l=1; l<=(nlstate+ndeath);l++){
7887: i++;
7888: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
7889: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
7890: for (j=1; j<=i;j++){
7891: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
7892: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
7893: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
7894: }
7895: }
7896: }/* end of loop for state */
7897: } /* end of loop for age */
7898: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
7899: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
7900: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7901: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7902:
7903: /* Confidence intervalle of pij */
7904: /*
7905: fprintf(ficgp,"\nunset parametric;unset label");
7906: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
7907: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
7908: 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);
7909: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
7910: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
7911: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
7912: */
7913:
7914: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
7915: first1=1;first2=2;
7916: for (k2=1; k2<=(nlstate);k2++){
7917: for (l2=1; l2<=(nlstate+ndeath);l2++){
7918: if(l2==k2) continue;
7919: j=(k2-1)*(nlstate+ndeath)+l2;
7920: for (k1=1; k1<=(nlstate);k1++){
7921: for (l1=1; l1<=(nlstate+ndeath);l1++){
7922: if(l1==k1) continue;
7923: i=(k1-1)*(nlstate+ndeath)+l1;
7924: if(i<=j) continue;
7925: for (age=bage; age<=fage; age ++){
7926: if ((int)age %5==0){
7927: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
7928: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
7929: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
7930: mu1=mu[i][(int) age]/stepm*YEARM ;
7931: mu2=mu[j][(int) age]/stepm*YEARM;
7932: c12=cv12/sqrt(v1*v2);
7933: /* Computing eigen value of matrix of covariance */
7934: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7935: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7936: if ((lc2 <0) || (lc1 <0) ){
7937: if(first2==1){
7938: first1=0;
7939: 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);
7940: }
7941: 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);
7942: /* lc1=fabs(lc1); */ /* If we want to have them positive */
7943: /* lc2=fabs(lc2); */
7944: }
1.220 brouard 7945:
1.222 brouard 7946: /* Eigen vectors */
1.280 brouard 7947: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
7948: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7949: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7950: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
7951: }else
7952: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 7953: /*v21=sqrt(1.-v11*v11); *//* error */
7954: v21=(lc1-v1)/cv12*v11;
7955: v12=-v21;
7956: v22=v11;
7957: tnalp=v21/v11;
7958: if(first1==1){
7959: first1=0;
7960: 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);
7961: }
7962: 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);
7963: /*printf(fignu*/
7964: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
7965: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
7966: if(first==1){
7967: first=0;
7968: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
7969: fprintf(ficgp,"\nset parametric;unset label");
7970: 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);
7971: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 7972: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 7973: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 7974: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 7975: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
7976: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7977: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7978: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
7979: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7980: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7981: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7982: 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 7983: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
7984: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 7985: }else{
7986: first=0;
7987: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
7988: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7989: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7990: 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 7991: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
7992: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 7993: }/* if first */
7994: } /* age mod 5 */
7995: } /* end loop age */
7996: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7997: first=1;
7998: } /*l12 */
7999: } /* k12 */
8000: } /*l1 */
8001: }/* k1 */
1.332 brouard 8002: } /* loop on combination of covariates j1 */
1.326 brouard 8003: } /* loop on nres */
1.222 brouard 8004: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
8005: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
8006: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
8007: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
8008: free_vector(xp,1,npar);
8009: fclose(ficresprob);
8010: fclose(ficresprobcov);
8011: fclose(ficresprobcor);
8012: fflush(ficgp);
8013: fflush(fichtmcov);
8014: }
1.126 brouard 8015:
8016:
8017: /******************* Printing html file ***********/
1.201 brouard 8018: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 8019: int lastpass, int stepm, int weightopt, char model[],\
8020: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.296 brouard 8021: int popforecast, int mobilav, int prevfcast, int mobilavproj, int prevbcast, int estepm , \
8022: double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \
8023: double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){
1.237 brouard 8024: int jj1, k1, i1, cpt, k4, nres;
1.319 brouard 8025: /* In fact some results are already printed in fichtm which is open */
1.126 brouard 8026: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
8027: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
8028: </ul>");
1.319 brouard 8029: /* fprintf(fichtm,"<ul><li> model=1+age+%s\n \ */
8030: /* </ul>", model); */
1.214 brouard 8031: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
8032: 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",
8033: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
1.332 brouard 8034: 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 8035: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
8036: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 8037: fprintf(fichtm,"\
8038: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 8039: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 8040: fprintf(fichtm,"\
1.217 brouard 8041: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
8042: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
8043: fprintf(fichtm,"\
1.288 brouard 8044: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 8045: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 8046: fprintf(fichtm,"\
1.288 brouard 8047: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 8048: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
8049: fprintf(fichtm,"\
1.211 brouard 8050: - (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 8051: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 8052: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 8053: if(prevfcast==1){
8054: fprintf(fichtm,"\
8055: - Prevalence projections by age and states: \
1.201 brouard 8056: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 8057: }
1.126 brouard 8058:
8059:
1.225 brouard 8060: m=pow(2,cptcoveff);
1.222 brouard 8061: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 8062:
1.317 brouard 8063: fprintf(fichtm," \n<ul><li><b>Graphs (first order)</b></li><p>");
1.264 brouard 8064:
8065: jj1=0;
8066:
8067: fprintf(fichtm," \n<ul>");
1.337 brouard 8068: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8069: /* k1=nres; */
1.338 brouard 8070: k1=TKresult[nres];
8071: if(TKresult[nres]==0)k1=1; /* To be checked for no result */
1.337 brouard 8072: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
8073: /* if(m != 1 && TKresult[nres]!= k1) */
8074: /* continue; */
1.264 brouard 8075: jj1++;
8076: if (cptcovn > 0) {
8077: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
1.337 brouard 8078: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
8079: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 8080: }
1.337 brouard 8081: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
8082: /* fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
8083: /* } */
8084: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8085: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8086: /* } */
1.264 brouard 8087: fprintf(fichtm,"\">");
8088:
8089: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
8090: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 8091: for (cpt=1; cpt<=cptcovs;cpt++){
8092: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 8093: }
1.337 brouard 8094: /* fprintf(fichtm,"************ Results for covariates"); */
8095: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
8096: /* fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
8097: /* } */
8098: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8099: /* fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8100: /* } */
1.264 brouard 8101: if(invalidvarcomb[k1]){
8102: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
8103: continue;
8104: }
8105: fprintf(fichtm,"</a></li>");
8106: } /* cptcovn >0 */
8107: }
1.317 brouard 8108: fprintf(fichtm," \n</ul>");
1.264 brouard 8109:
1.222 brouard 8110: jj1=0;
1.237 brouard 8111:
1.337 brouard 8112: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8113: /* k1=nres; */
1.338 brouard 8114: k1=TKresult[nres];
8115: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8116: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
8117: /* if(m != 1 && TKresult[nres]!= k1) */
8118: /* continue; */
1.220 brouard 8119:
1.222 brouard 8120: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
8121: jj1++;
8122: if (cptcovn > 0) {
1.264 brouard 8123: fprintf(fichtm,"\n<p><a name=\"rescov");
1.337 brouard 8124: for (cpt=1; cpt<=cptcovs;cpt++){
8125: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 8126: }
1.337 brouard 8127: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8128: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8129: /* } */
1.264 brouard 8130: fprintf(fichtm,"\"</a>");
8131:
1.222 brouard 8132: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 8133: for (cpt=1; cpt<=cptcovs;cpt++){
8134: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
8135: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 8136: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
8137: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 8138: }
1.230 brouard 8139: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.338 brouard 8140: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.222 brouard 8141: if(invalidvarcomb[k1]){
8142: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
8143: printf("\nCombination (%d) ignored because no cases \n",k1);
8144: continue;
8145: }
8146: }
8147: /* aij, bij */
1.259 brouard 8148: 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 8149: <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 8150: /* Pij */
1.241 brouard 8151: 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> \
8152: <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 8153: /* Quasi-incidences */
8154: 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 8155: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 8156: 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 8157: 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> \
8158: <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 8159: /* Survival functions (period) in state j */
8160: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 8161: 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);
8162: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
8163: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.222 brouard 8164: }
8165: /* State specific survival functions (period) */
8166: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 8167: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
8168: And probability to be observed in various states (up to %d) being in state %d at different ages. \
1.329 brouard 8169: <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);
8170: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
8171: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.222 brouard 8172: }
1.288 brouard 8173: /* Period (forward stable) prevalence in each health state */
1.222 brouard 8174: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 8175: 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 8176: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
1.329 brouard 8177: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.222 brouard 8178: }
1.296 brouard 8179: if(prevbcast==1){
1.288 brouard 8180: /* Backward prevalence in each health state */
1.222 brouard 8181: for(cpt=1; cpt<=nlstate;cpt++){
1.338 brouard 8182: 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);
8183: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJB_"),subdirf2(optionfilefiname,"PIJB_"));
8184: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.222 brouard 8185: }
1.217 brouard 8186: }
1.222 brouard 8187: if(prevfcast==1){
1.288 brouard 8188: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 8189: for(cpt=1; cpt<=nlstate;cpt++){
1.314 brouard 8190: 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);
8191: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"F_"),subdirf2(optionfilefiname,"F_"));
8192: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",
8193: subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 8194: }
8195: }
1.296 brouard 8196: if(prevbcast==1){
1.268 brouard 8197: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
8198: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 8199: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
8200: 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 \
8201: 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 8202: 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);
8203: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"FB_"),subdirf2(optionfilefiname,"FB_"));
8204: fprintf(fichtm," <img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
1.268 brouard 8205: }
8206: }
1.220 brouard 8207:
1.222 brouard 8208: for(cpt=1; cpt<=nlstate;cpt++) {
1.314 brouard 8209: 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);
8210: fprintf(fichtm," (data from text file <a href=\"%s.txt\"> %s.txt</a>)\n<br>",subdirf2(optionfilefiname,"E_"),subdirf2(optionfilefiname,"E_"));
8211: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres );
1.222 brouard 8212: }
8213: /* } /\* end i1 *\/ */
1.337 brouard 8214: }/* End k1=nres */
1.222 brouard 8215: fprintf(fichtm,"</ul>");
1.126 brouard 8216:
1.222 brouard 8217: fprintf(fichtm,"\
1.126 brouard 8218: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 8219: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 8220: - 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 8221: But because parameters are usually highly correlated (a higher incidence of disability \
8222: and a higher incidence of recovery can give very close observed transition) it might \
8223: be very useful to look not only at linear confidence intervals estimated from the \
8224: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
8225: (parameters) of the logistic regression, it might be more meaningful to visualize the \
8226: covariance matrix of the one-step probabilities. \
8227: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 8228:
1.222 brouard 8229: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
8230: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
8231: fprintf(fichtm,"\
1.126 brouard 8232: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 8233: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 8234:
1.222 brouard 8235: fprintf(fichtm,"\
1.126 brouard 8236: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 8237: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
8238: fprintf(fichtm,"\
1.126 brouard 8239: - 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): \
8240: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 8241: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 8242: fprintf(fichtm,"\
1.126 brouard 8243: - (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): \
8244: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 8245: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 8246: fprintf(fichtm,"\
1.288 brouard 8247: - 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 8248: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
8249: fprintf(fichtm,"\
1.128 brouard 8250: - 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 8251: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
8252: fprintf(fichtm,"\
1.288 brouard 8253: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 8254: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 8255:
8256: /* if(popforecast==1) fprintf(fichtm,"\n */
8257: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
8258: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
8259: /* <br>",fileres,fileres,fileres,fileres); */
8260: /* else */
1.338 brouard 8261: /* 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 8262: fflush(fichtm);
1.126 brouard 8263:
1.225 brouard 8264: m=pow(2,cptcoveff);
1.222 brouard 8265: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 8266:
1.317 brouard 8267: fprintf(fichtm," <ul><li><b>Graphs (second order)</b></li><p>");
8268:
8269: jj1=0;
8270:
8271: fprintf(fichtm," \n<ul>");
1.337 brouard 8272: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8273: /* k1=nres; */
1.338 brouard 8274: k1=TKresult[nres];
1.337 brouard 8275: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
8276: /* if(m != 1 && TKresult[nres]!= k1) */
8277: /* continue; */
1.317 brouard 8278: jj1++;
8279: if (cptcovn > 0) {
8280: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescovsecond");
1.337 brouard 8281: for (cpt=1; cpt<=cptcovs;cpt++){
8282: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8283: }
8284: fprintf(fichtm,"\">");
8285:
8286: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
8287: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 8288: for (cpt=1; cpt<=cptcovs;cpt++){
8289: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8290: }
8291: if(invalidvarcomb[k1]){
8292: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
8293: continue;
8294: }
8295: fprintf(fichtm,"</a></li>");
8296: } /* cptcovn >0 */
1.337 brouard 8297: } /* End nres */
1.317 brouard 8298: fprintf(fichtm," \n</ul>");
8299:
1.222 brouard 8300: jj1=0;
1.237 brouard 8301:
1.241 brouard 8302: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8303: /* k1=nres; */
1.338 brouard 8304: k1=TKresult[nres];
8305: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8306: /* for(k1=1; k1<=m;k1++){ */
8307: /* if(m != 1 && TKresult[nres]!= k1) */
8308: /* continue; */
1.222 brouard 8309: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
8310: jj1++;
1.126 brouard 8311: if (cptcovn > 0) {
1.317 brouard 8312: fprintf(fichtm,"\n<p><a name=\"rescovsecond");
1.337 brouard 8313: for (cpt=1; cpt<=cptcovs;cpt++){
8314: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8315: }
8316: fprintf(fichtm,"\"</a>");
8317:
1.126 brouard 8318: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 8319: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcoveff number of variables */
8320: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
8321: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 8322: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
1.317 brouard 8323: }
1.237 brouard 8324:
1.338 brouard 8325: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.220 brouard 8326:
1.222 brouard 8327: if(invalidvarcomb[k1]){
8328: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
8329: continue;
8330: }
1.337 brouard 8331: } /* If cptcovn >0 */
1.126 brouard 8332: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 8333: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.314 brouard 8334: 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);
8335: fprintf(fichtm," (data from text file <a href=\"%s\">%s</a>)\n <br>",subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
8336: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"V_"), cpt,k1,nres);
1.126 brouard 8337: }
8338: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.314 brouard 8339: health expectancies in each live states (1 to %d). If popbased=1 the smooth (due to the model) \
1.128 brouard 8340: true period expectancies (those weighted with period prevalences are also\
8341: drawn in addition to the population based expectancies computed using\
1.314 brouard 8342: 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);
8343: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>) \n<br>",subdirf2(optionfilefiname,"T_"),subdirf2(optionfilefiname,"T_"));
8344: fprintf(fichtm,"<img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 8345: /* } /\* end i1 *\/ */
1.241 brouard 8346: }/* End nres */
1.222 brouard 8347: fprintf(fichtm,"</ul>");
8348: fflush(fichtm);
1.126 brouard 8349: }
8350:
8351: /******************* Gnuplot file **************/
1.296 brouard 8352: 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 8353:
8354: char dirfileres[132],optfileres[132];
1.264 brouard 8355: char gplotcondition[132], gplotlabel[132];
1.343 brouard 8356: 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 8357: int lv=0, vlv=0, kl=0;
1.130 brouard 8358: int ng=0;
1.201 brouard 8359: int vpopbased;
1.223 brouard 8360: int ioffset; /* variable offset for columns */
1.270 brouard 8361: int iyearc=1; /* variable column for year of projection */
8362: int iagec=1; /* variable column for age of projection */
1.235 brouard 8363: int nres=0; /* Index of resultline */
1.266 brouard 8364: int istart=1; /* For starting graphs in projections */
1.219 brouard 8365:
1.126 brouard 8366: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
8367: /* printf("Problem with file %s",optionfilegnuplot); */
8368: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
8369: /* } */
8370:
8371: /*#ifdef windows */
8372: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 8373: /*#endif */
1.225 brouard 8374: m=pow(2,cptcoveff);
1.126 brouard 8375:
1.274 brouard 8376: /* diagram of the model */
8377: fprintf(ficgp,"\n#Diagram of the model \n");
8378: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
8379: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
8380: 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);
8381:
1.343 brouard 8382: 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 8383: fprintf(ficgp,"\n#show arrow\nunset label\n");
8384: 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);
8385: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
8386: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
8387: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
8388: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
8389:
1.202 brouard 8390: /* Contribution to likelihood */
8391: /* Plot the probability implied in the likelihood */
1.223 brouard 8392: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
8393: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
8394: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
8395: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 8396: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 8397: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
8398: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 8399: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
8400: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
8401: 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));
8402: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
8403: 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));
8404: for (i=1; i<= nlstate ; i ++) {
8405: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
8406: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
8407: 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);
8408: for (j=2; j<= nlstate+ndeath ; j ++) {
8409: 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);
8410: }
8411: fprintf(ficgp,";\nset out; unset ylabel;\n");
8412: }
8413: /* 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 */
8414: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
8415: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
8416: fprintf(ficgp,"\nset out;unset log\n");
8417: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 8418:
1.343 brouard 8419: /* Plot the probability implied in the likelihood by covariate value */
8420: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
8421: /* if(debugILK==1){ */
8422: for(kf=1; kf <= ncovf; kf++){ /* For each simple dummy covariate of the model */
1.347 brouard 8423: kvar=Tvar[TvarFind[kf]]; /* variable name */
8424: /* k=18+Tvar[TvarFind[kf]];/\*offset because there are 18 columns in the ILK_ file but could be placed else where *\/ */
1.350 brouard 8425: /* k=18+kf;/\*offset because there are 18 columns in the ILK_ file *\/ */
8426: k=19+kf;/*offset because there are 19 columns in the ILK_ file */
1.343 brouard 8427: for (i=1; i<= nlstate ; i ++) {
8428: fprintf(ficgp,"\nset out \"%s-p%dj-%d.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i,kvar);
8429: fprintf(ficgp,"unset log;\n# For each simple dummy covariate of the model \n plot \"%s\"",subdirf(fileresilk));
1.348 brouard 8430: if(gnuplotversion >=5.2){ /* Former gnuplot versions do not have variable pointsize!! */
8431: 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);
8432: for (j=2; j<= nlstate+ndeath ; j ++) {
8433: 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);
8434: }
8435: }else{
8436: 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);
8437: for (j=2; j<= nlstate+ndeath ; j ++) {
8438: 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);
8439: }
1.343 brouard 8440: }
8441: fprintf(ficgp,";\nset out; unset ylabel;\n");
8442: }
8443: } /* End of each covariate dummy */
8444: for(ncovv=1, iposold=0, kk=0; ncovv <= ncovvt ; ncovv++){
8445: /* Other example V1 + V3 + V5 + age*V1 + age*V3 + age*V5 + V1*V3 + V3*V5 + V1*V5
8446: * kmodel = 1 2 3 4 5 6 7 8 9
8447: * varying 1 2 3 4 5
8448: * ncovv 1 2 3 4 5 6 7 8
8449: * TvarVV[ncovv] V3 5 1 3 3 5 1 5
8450: * TvarVVind[ncovv]=kmodel 2 3 7 7 8 8 9 9
8451: * TvarFind[kmodel] 1 0 0 0 0 0 0 0 0
8452: * kdata ncovcol=[V1 V2] nqv=0 ntv=[V3 V4] nqtv=V5
8453: * Dummy[kmodel] 0 0 1 2 2 3 1 1 1
8454: */
8455: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
8456: kvar=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
8457: /* 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]); */
8458: if(ipos!=iposold){ /* Not a product or first of a product */
8459: /* printf(" %d",ipos); */
8460: /* fprintf(ficresilk," V%d",TvarVV[ncovv]); */
8461: /* printf(" DebugILK ficgp suite ipos=%d != iposold=%d\n", ipos, iposold); */
8462: kk++; /* Position of the ncovv column in ILK_ */
8463: k=18+ncovf+kk; /*offset because there are 18 columns in the ILK_ file plus ncovf fixed covariate */
8464: 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) */
8465: for (i=1; i<= nlstate ; i ++) {
8466: fprintf(ficgp,"\nset out \"%s-p%dj-%d.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i,kvar);
8467: fprintf(ficgp,"unset log;\n# For each simple dummy covariate of the model \n plot \"%s\"",subdirf(fileresilk));
8468:
1.348 brouard 8469: /* printf("Before DebugILK gnuplotversion=%g >=5.2\n",gnuplotversion); */
1.343 brouard 8470: if(gnuplotversion >=5.2){ /* Former gnuplot versions do not have variable pointsize!! */
8471: /* printf("DebugILK gnuplotversion=%g >=5.2\n",gnuplotversion); */
8472: 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);
8473: for (j=2; j<= nlstate+ndeath ; j ++) {
8474: 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);
8475: }
8476: }else{
8477: /* printf("DebugILK gnuplotversion=%g <5.2\n",gnuplotversion); */
8478: 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);
8479: for (j=2; j<= nlstate+ndeath ; j ++) {
8480: 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);
8481: }
8482: }
8483: fprintf(ficgp,";\nset out; unset ylabel;\n");
8484: }
8485: }/* End if dummy varying */
8486: }else{ /*Product */
8487: /* printf("*"); */
8488: /* fprintf(ficresilk,"*"); */
8489: }
8490: iposold=ipos;
8491: } /* For each time varying covariate */
8492: /* } /\* debugILK==1 *\/ */
8493: /* 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 */
8494: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
8495: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
8496: fprintf(ficgp,"\nset out;unset log\n");
8497: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
8498:
8499:
8500:
1.126 brouard 8501: strcpy(dirfileres,optionfilefiname);
8502: strcpy(optfileres,"vpl");
1.223 brouard 8503: /* 1eme*/
1.238 brouard 8504: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
1.337 brouard 8505: /* for (k1=1; k1<= m ; k1 ++){ /\* For each valid combination of covariate *\/ */
1.236 brouard 8506: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8507: k1=TKresult[nres];
1.338 brouard 8508: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.238 brouard 8509: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.337 brouard 8510: /* if(m != 1 && TKresult[nres]!= k1) */
8511: /* continue; */
1.238 brouard 8512: /* We are interested in selected combination by the resultline */
1.246 brouard 8513: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 8514: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 8515: strcpy(gplotlabel,"(");
1.337 brouard 8516: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8517: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8518: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8519:
8520: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate k get corresponding value lv for combination k1 *\/ */
8521: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the value of the covariate corresponding to k1 combination *\\/ *\/ */
8522: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8523: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8524: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8525: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8526: /* vlv= nbcode[Tvaraff[k]][lv]; /\* vlv is the value of the covariate lv, 0 or 1 *\/ */
8527: /* /\* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv *\/ */
8528: /* /\* printf(" V%d=%d ",Tvaraff[k],vlv); *\/ */
8529: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8530: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8531: /* } */
8532: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8533: /* /\* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); *\/ */
8534: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8535: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.264 brouard 8536: }
8537: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 8538: /* printf("\n#\n"); */
1.238 brouard 8539: fprintf(ficgp,"\n#\n");
8540: if(invalidvarcomb[k1]){
1.260 brouard 8541: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 8542: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8543: continue;
8544: }
1.235 brouard 8545:
1.241 brouard 8546: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
8547: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 8548: /* 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 8549: fprintf(ficgp,"set title \"Alive state %d %s model=1+age+%s\" font \"Helvetica,12\"\n",cpt,gplotlabel,model);
1.260 brouard 8550: 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);
8551: /* 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); */
8552: /* k1-1 error should be nres-1*/
1.238 brouard 8553: for (i=1; i<= nlstate ; i ++) {
8554: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8555: else fprintf(ficgp," %%*lf (%%*lf)");
8556: }
1.288 brouard 8557: 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 8558: for (i=1; i<= nlstate ; i ++) {
8559: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8560: else fprintf(ficgp," %%*lf (%%*lf)");
8561: }
1.260 brouard 8562: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 8563: for (i=1; i<= nlstate ; i ++) {
8564: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8565: else fprintf(ficgp," %%*lf (%%*lf)");
8566: }
1.265 brouard 8567: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
8568:
8569: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
8570: if(cptcoveff ==0){
1.271 brouard 8571: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 8572: }else{
8573: kl=0;
8574: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 8575: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
8576: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.265 brouard 8577: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8578: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8579: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8580: vlv= nbcode[Tvaraff[k]][lv];
8581: kl++;
8582: /* 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 *\/ */
8583: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8584: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8585: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
8586: if(k==cptcoveff){
8587: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
8588: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
8589: }else{
8590: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
8591: kl++;
8592: }
8593: } /* end covariate */
8594: } /* end if no covariate */
8595:
1.296 brouard 8596: if(prevbcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
1.238 brouard 8597: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 8598: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 8599: if(cptcoveff ==0){
1.245 brouard 8600: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 8601: }else{
8602: kl=0;
8603: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 8604: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
8605: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.238 brouard 8606: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8607: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8608: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 8609: /* vlv= nbcode[Tvaraff[k]][lv]; */
8610: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.223 brouard 8611: kl++;
1.238 brouard 8612: /* 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 *\/ */
8613: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8614: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8615: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
8616: if(k==cptcoveff){
1.245 brouard 8617: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 8618: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 8619: }else{
1.332 brouard 8620: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]);
1.238 brouard 8621: kl++;
8622: }
8623: } /* end covariate */
8624: } /* end if no covariate */
1.296 brouard 8625: if(prevbcast == 1){
1.268 brouard 8626: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
8627: /* k1-1 error should be nres-1*/
8628: for (i=1; i<= nlstate ; i ++) {
8629: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8630: else fprintf(ficgp," %%*lf (%%*lf)");
8631: }
1.271 brouard 8632: 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 8633: for (i=1; i<= nlstate ; i ++) {
8634: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8635: else fprintf(ficgp," %%*lf (%%*lf)");
8636: }
1.276 brouard 8637: 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 8638: for (i=1; i<= nlstate ; i ++) {
8639: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8640: else fprintf(ficgp," %%*lf (%%*lf)");
8641: }
1.274 brouard 8642: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 8643: } /* end if backprojcast */
1.296 brouard 8644: } /* end if prevbcast */
1.276 brouard 8645: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
8646: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 8647: } /* nres */
1.337 brouard 8648: /* } /\* k1 *\/ */
1.201 brouard 8649: } /* cpt */
1.235 brouard 8650:
8651:
1.126 brouard 8652: /*2 eme*/
1.337 brouard 8653: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 8654: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8655: k1=TKresult[nres];
1.338 brouard 8656: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8657: /* if(m != 1 && TKresult[nres]!= k1) */
8658: /* continue; */
1.238 brouard 8659: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 8660: strcpy(gplotlabel,"(");
1.337 brouard 8661: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8662: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8663: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8664: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8665: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8666: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8667: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8668: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8669: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8670: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8671: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8672: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8673: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8674: /* } */
8675: /* /\* for(k=1; k <= ncovds; k++){ *\/ */
8676: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8677: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8678: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8679: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 8680: }
1.264 brouard 8681: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8682: fprintf(ficgp,"\n#\n");
1.223 brouard 8683: if(invalidvarcomb[k1]){
8684: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8685: continue;
8686: }
1.219 brouard 8687:
1.241 brouard 8688: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 8689: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 8690: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
8691: if(vpopbased==0){
1.238 brouard 8692: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 8693: }else
1.238 brouard 8694: fprintf(ficgp,"\nreplot ");
8695: for (i=1; i<= nlstate+1 ; i ++) {
8696: k=2*i;
1.261 brouard 8697: 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 8698: for (j=1; j<= nlstate+1 ; j ++) {
8699: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8700: else fprintf(ficgp," %%*lf (%%*lf)");
8701: }
8702: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
8703: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 8704: 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 8705: for (j=1; j<= nlstate+1 ; j ++) {
8706: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8707: else fprintf(ficgp," %%*lf (%%*lf)");
8708: }
8709: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 8710: 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 8711: for (j=1; j<= nlstate+1 ; j ++) {
8712: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8713: else fprintf(ficgp," %%*lf (%%*lf)");
8714: }
8715: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
8716: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
8717: } /* state */
8718: } /* vpopbased */
1.264 brouard 8719: 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 8720: } /* end nres */
1.337 brouard 8721: /* } /\* k1 end 2 eme*\/ */
1.238 brouard 8722:
8723:
8724: /*3eme*/
1.337 brouard 8725: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 8726: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8727: k1=TKresult[nres];
1.338 brouard 8728: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8729: /* if(m != 1 && TKresult[nres]!= k1) */
8730: /* continue; */
1.238 brouard 8731:
1.332 brouard 8732: for (cpt=1; cpt<= nlstate ; cpt ++) { /* Fragile no verification of covariate values */
1.261 brouard 8733: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 8734: strcpy(gplotlabel,"(");
1.337 brouard 8735: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8736: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8737: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8738: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8739: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8740: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8741: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8742: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8743: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8744: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8745: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8746: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8747: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8748: /* } */
8749: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8750: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
8751: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
8752: }
1.264 brouard 8753: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8754: fprintf(ficgp,"\n#\n");
8755: if(invalidvarcomb[k1]){
8756: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8757: continue;
8758: }
8759:
8760: /* k=2+nlstate*(2*cpt-2); */
8761: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 8762: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 8763: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 8764: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 8765: 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 8766: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8767: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8768: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
8769: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8770: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8771: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 8772:
1.238 brouard 8773: */
8774: for (i=1; i< nlstate ; i ++) {
1.261 brouard 8775: 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 8776: /* 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 8777:
1.238 brouard 8778: }
1.261 brouard 8779: 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 8780: }
1.264 brouard 8781: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 8782: } /* end nres */
1.337 brouard 8783: /* } /\* end kl 3eme *\/ */
1.126 brouard 8784:
1.223 brouard 8785: /* 4eme */
1.201 brouard 8786: /* Survival functions (period) from state i in state j by initial state i */
1.337 brouard 8787: /* for (k1=1; k1<=m; k1++){ /\* For each covariate and each value *\/ */
1.238 brouard 8788: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8789: k1=TKresult[nres];
1.338 brouard 8790: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8791: /* if(m != 1 && TKresult[nres]!= k1) */
8792: /* continue; */
1.238 brouard 8793: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 8794: strcpy(gplotlabel,"(");
1.337 brouard 8795: fprintf(ficgp,"\n#\n#\n# Survival functions in state %d : 'LIJ_' files, cov=%d state=%d", cpt, k1, cpt);
8796: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8797: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8798: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8799: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8800: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8801: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8802: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8803: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8804: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8805: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8806: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8807: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8808: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8809: /* } */
8810: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8811: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8812: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 8813: }
1.264 brouard 8814: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8815: fprintf(ficgp,"\n#\n");
8816: if(invalidvarcomb[k1]){
8817: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8818: continue;
1.223 brouard 8819: }
1.238 brouard 8820:
1.241 brouard 8821: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 8822: 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 8823: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8824: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8825: k=3;
8826: for (i=1; i<= nlstate ; i ++){
8827: if(i==1){
8828: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8829: }else{
8830: fprintf(ficgp,", '' ");
8831: }
8832: l=(nlstate+ndeath)*(i-1)+1;
8833: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8834: for (j=2; j<= nlstate+ndeath ; j ++)
8835: fprintf(ficgp,"+$%d",k+l+j-1);
8836: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
8837: } /* nlstate */
1.264 brouard 8838: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8839: } /* end cpt state*/
8840: } /* end nres */
1.337 brouard 8841: /* } /\* end covariate k1 *\/ */
1.238 brouard 8842:
1.220 brouard 8843: /* 5eme */
1.201 brouard 8844: /* Survival functions (period) from state i in state j by final state j */
1.337 brouard 8845: /* for (k1=1; k1<= m ; k1++){ /\* For each covariate combination if any *\/ */
1.238 brouard 8846: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8847: k1=TKresult[nres];
1.338 brouard 8848: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8849: /* if(m != 1 && TKresult[nres]!= k1) */
8850: /* continue; */
1.238 brouard 8851: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 8852: strcpy(gplotlabel,"(");
1.238 brouard 8853: 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 8854: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8855: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8856: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8857: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8858: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8859: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8860: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8861: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8862: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8863: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8864: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8865: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8866: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8867: /* } */
8868: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8869: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8870: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 8871: }
1.264 brouard 8872: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8873: fprintf(ficgp,"\n#\n");
8874: if(invalidvarcomb[k1]){
8875: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8876: continue;
8877: }
1.227 brouard 8878:
1.241 brouard 8879: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 8880: 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 8881: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8882: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8883: k=3;
8884: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8885: if(j==1)
8886: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8887: else
8888: fprintf(ficgp,", '' ");
8889: l=(nlstate+ndeath)*(cpt-1) +j;
8890: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
8891: /* for (i=2; i<= nlstate+ndeath ; i ++) */
8892: /* fprintf(ficgp,"+$%d",k+l+i-1); */
8893: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
8894: } /* nlstate */
8895: fprintf(ficgp,", '' ");
8896: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
8897: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8898: l=(nlstate+ndeath)*(cpt-1) +j;
8899: if(j < nlstate)
8900: fprintf(ficgp,"$%d +",k+l);
8901: else
8902: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
8903: }
1.264 brouard 8904: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8905: } /* end cpt state*/
1.337 brouard 8906: /* } /\* end covariate *\/ */
1.238 brouard 8907: } /* end nres */
1.227 brouard 8908:
1.220 brouard 8909: /* 6eme */
1.202 brouard 8910: /* CV preval stable (period) for each covariate */
1.337 brouard 8911: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8912: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8913: k1=TKresult[nres];
1.338 brouard 8914: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8915: /* if(m != 1 && TKresult[nres]!= k1) */
8916: /* continue; */
1.255 brouard 8917: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 8918: strcpy(gplotlabel,"(");
1.288 brouard 8919: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 8920: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8921: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8922: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8923: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8924: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8925: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8926: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8927: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8928: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8929: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8930: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8931: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8932: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8933: /* } */
8934: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8935: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8936: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 8937: }
1.264 brouard 8938: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8939: fprintf(ficgp,"\n#\n");
1.223 brouard 8940: if(invalidvarcomb[k1]){
1.227 brouard 8941: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8942: continue;
1.223 brouard 8943: }
1.227 brouard 8944:
1.241 brouard 8945: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 8946: 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 8947: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 8948: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 8949: k=3; /* Offset */
1.255 brouard 8950: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 8951: if(i==1)
8952: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8953: else
8954: fprintf(ficgp,", '' ");
1.255 brouard 8955: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 8956: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8957: for (j=2; j<= nlstate ; j ++)
8958: fprintf(ficgp,"+$%d",k+l+j-1);
8959: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 8960: } /* nlstate */
1.264 brouard 8961: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 8962: } /* end cpt state*/
8963: } /* end covariate */
1.227 brouard 8964:
8965:
1.220 brouard 8966: /* 7eme */
1.296 brouard 8967: if(prevbcast == 1){
1.288 brouard 8968: /* CV backward prevalence for each covariate */
1.337 brouard 8969: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8970: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8971: k1=TKresult[nres];
1.338 brouard 8972: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8973: /* if(m != 1 && TKresult[nres]!= k1) */
8974: /* continue; */
1.268 brouard 8975: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 8976: strcpy(gplotlabel,"(");
1.288 brouard 8977: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 8978: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8979: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8980: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8981: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8982: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8983: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8984: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8985: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8986: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8987: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8988: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8989: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8990: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8991: /* } */
8992: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8993: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8994: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 8995: }
1.264 brouard 8996: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 8997: fprintf(ficgp,"\n#\n");
8998: if(invalidvarcomb[k1]){
8999: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
9000: continue;
9001: }
9002:
1.241 brouard 9003: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 9004: 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 9005: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 9006: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 9007: k=3; /* Offset */
1.268 brouard 9008: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 9009: if(i==1)
9010: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
9011: else
9012: fprintf(ficgp,", '' ");
9013: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 9014: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.324 brouard 9015: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
9016: /* 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 9017: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 9018: /* for (j=2; j<= nlstate ; j ++) */
9019: /* fprintf(ficgp,"+$%d",k+l+j-1); */
9020: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 9021: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 9022: } /* nlstate */
1.264 brouard 9023: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 9024: } /* end cpt state*/
9025: } /* end covariate */
1.296 brouard 9026: } /* End if prevbcast */
1.218 brouard 9027:
1.223 brouard 9028: /* 8eme */
1.218 brouard 9029: if(prevfcast==1){
1.288 brouard 9030: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 9031:
1.337 brouard 9032: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 9033: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9034: k1=TKresult[nres];
1.338 brouard 9035: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9036: /* if(m != 1 && TKresult[nres]!= k1) */
9037: /* continue; */
1.211 brouard 9038: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 9039: strcpy(gplotlabel,"(");
1.288 brouard 9040: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 9041: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
9042: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9043: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9044: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
9045: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
9046: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
9047: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9048: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9049: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9050: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9051: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9052: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9053: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9054: /* } */
9055: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9056: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9057: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 9058: }
1.264 brouard 9059: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 9060: fprintf(ficgp,"\n#\n");
9061: if(invalidvarcomb[k1]){
9062: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
9063: continue;
9064: }
9065:
9066: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 9067: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 9068: 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 9069: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 9070: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 9071:
9072: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
9073: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
9074: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
9075: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 9076: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9077: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9078: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9079: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 9080: if(i==istart){
1.227 brouard 9081: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
9082: }else{
9083: fprintf(ficgp,",\\\n '' ");
9084: }
9085: if(cptcoveff ==0){ /* No covariate */
9086: ioffset=2; /* Age is in 2 */
9087: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9088: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9089: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9090: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9091: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 9092: if(i==nlstate+1){
1.270 brouard 9093: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 9094: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
9095: fprintf(ficgp,",\\\n '' ");
9096: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 9097: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 9098: offyear, \
1.268 brouard 9099: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 9100: }else
1.227 brouard 9101: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
9102: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
9103: }else{ /* more than 2 covariates */
1.270 brouard 9104: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
9105: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9106: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9107: iyearc=ioffset-1;
9108: iagec=ioffset;
1.227 brouard 9109: fprintf(ficgp," u %d:(",ioffset);
9110: kl=0;
9111: strcpy(gplotcondition,"(");
1.351 ! brouard 9112: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate writing the chain of conditions *\/ */
1.332 brouard 9113: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
1.351 ! brouard 9114: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
! 9115: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
! 9116: lv=Tvresult[nres][k];
! 9117: vlv=TinvDoQresult[nres][Tvresult[nres][k]];
1.227 brouard 9118: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
9119: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
9120: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 9121: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
1.351 ! brouard 9122: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
1.227 brouard 9123: kl++;
1.351 ! brouard 9124: /* sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); */
! 9125: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,lv, kl+1, vlv );
1.227 brouard 9126: kl++;
1.351 ! brouard 9127: if(k <cptcovs && cptcovs>1)
1.227 brouard 9128: sprintf(gplotcondition+strlen(gplotcondition)," && ");
9129: }
9130: strcpy(gplotcondition+strlen(gplotcondition),")");
9131: /* 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 *\/ */
9132: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
9133: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
9134: /* '' 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*/
9135: if(i==nlstate+1){
1.270 brouard 9136: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
9137: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 9138: fprintf(ficgp,",\\\n '' ");
1.270 brouard 9139: fprintf(ficgp," u %d:(",iagec);
9140: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
9141: iyearc, iagec, offyear, \
9142: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 9143: /* '' 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 9144: }else{
9145: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
9146: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
9147: }
9148: } /* end if covariate */
9149: } /* nlstate */
1.264 brouard 9150: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 9151: } /* end cpt state*/
9152: } /* end covariate */
9153: } /* End if prevfcast */
1.227 brouard 9154:
1.296 brouard 9155: if(prevbcast==1){
1.268 brouard 9156: /* Back projection from cross-sectional to stable (mixed) for each covariate */
9157:
1.337 brouard 9158: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.268 brouard 9159: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9160: k1=TKresult[nres];
1.338 brouard 9161: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9162: /* if(m != 1 && TKresult[nres]!= k1) */
9163: /* continue; */
1.268 brouard 9164: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
9165: strcpy(gplotlabel,"(");
9166: 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 9167: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
9168: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9169: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9170: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
9171: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
9172: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9173: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9174: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9175: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9176: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9177: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9178: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9179: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9180: /* } */
9181: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9182: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9183: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.268 brouard 9184: }
9185: strcpy(gplotlabel+strlen(gplotlabel),")");
9186: fprintf(ficgp,"\n#\n");
9187: if(invalidvarcomb[k1]){
9188: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
9189: continue;
9190: }
9191:
9192: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
9193: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
9194: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
9195: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
9196: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
9197:
9198: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
9199: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
9200: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
9201: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
9202: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9203: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9204: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9205: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9206: if(i==istart){
9207: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
9208: }else{
9209: fprintf(ficgp,",\\\n '' ");
9210: }
1.351 ! brouard 9211: /* if(cptcoveff ==0){ /\* No covariate *\/ */
! 9212: if(cptcovs ==0){ /* No covariate */
1.268 brouard 9213: ioffset=2; /* Age is in 2 */
9214: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9215: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9216: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9217: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9218: fprintf(ficgp," u %d:(", ioffset);
9219: if(i==nlstate+1){
1.270 brouard 9220: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 9221: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
9222: fprintf(ficgp,",\\\n '' ");
9223: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 9224: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 9225: offbyear, \
9226: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
9227: }else
9228: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
9229: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
9230: }else{ /* more than 2 covariates */
1.270 brouard 9231: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
9232: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9233: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9234: iyearc=ioffset-1;
9235: iagec=ioffset;
1.268 brouard 9236: fprintf(ficgp," u %d:(",ioffset);
9237: kl=0;
9238: strcpy(gplotcondition,"(");
1.337 brouard 9239: for (k=1; k<=cptcovs; k++){ /* For each covariate k of the resultline, get corresponding value lv for combination k1 */
1.338 brouard 9240: if(Dummy[modelresult[nres][k]]==0){ /* To be verified */
1.337 brouard 9241: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate writing the chain of conditions *\/ */
9242: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9243: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9244: lv=Tvresult[nres][k];
9245: vlv=TinvDoQresult[nres][Tvresult[nres][k]];
9246: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
9247: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
9248: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
9249: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
9250: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9251: kl++;
9252: /* sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); */
9253: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%lg " ,kl,Tvresult[nres][k], kl+1,TinvDoQresult[nres][Tvresult[nres][k]]);
9254: kl++;
1.338 brouard 9255: if(k <cptcovs && cptcovs>1)
1.337 brouard 9256: sprintf(gplotcondition+strlen(gplotcondition)," && ");
9257: }
1.268 brouard 9258: }
9259: strcpy(gplotcondition+strlen(gplotcondition),")");
9260: /* 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 *\/ */
9261: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
9262: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
9263: /* '' 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*/
9264: if(i==nlstate+1){
1.270 brouard 9265: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
9266: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 9267: fprintf(ficgp,",\\\n '' ");
1.270 brouard 9268: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 9269: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 9270: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
9271: iyearc,iagec,offbyear, \
9272: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 9273: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
9274: }else{
9275: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
9276: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
9277: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
9278: }
9279: } /* end if covariate */
9280: } /* nlstate */
9281: fprintf(ficgp,"\nset out; unset label;\n");
9282: } /* end cpt state*/
9283: } /* end covariate */
1.296 brouard 9284: } /* End if prevbcast */
1.268 brouard 9285:
1.227 brouard 9286:
1.238 brouard 9287: /* 9eme writing MLE parameters */
9288: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 9289: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 9290: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 9291: for(k=1; k <=(nlstate+ndeath); k++){
9292: if (k != i) {
1.227 brouard 9293: fprintf(ficgp,"# current state %d\n",k);
9294: for(j=1; j <=ncovmodel; j++){
9295: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
9296: jk++;
9297: }
9298: fprintf(ficgp,"\n");
1.126 brouard 9299: }
9300: }
1.223 brouard 9301: }
1.187 brouard 9302: fprintf(ficgp,"##############\n#\n");
1.227 brouard 9303:
1.145 brouard 9304: /*goto avoid;*/
1.238 brouard 9305: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
9306: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 9307: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
9308: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
9309: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
9310: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
9311: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
9312: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
9313: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
9314: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
9315: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
9316: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
9317: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
9318: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
9319: fprintf(ficgp,"#\n");
1.223 brouard 9320: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 9321: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.338 brouard 9322: fprintf(ficgp,"#model=1+age+%s \n",model);
1.238 brouard 9323: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.351 ! brouard 9324: /* fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/\* to be checked *\/ */
! 9325: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcovs,m);/* to be checked */
1.337 brouard 9326: /* for(k1=1; k1 <=m; k1++) /\* For each combination of covariate *\/ */
1.237 brouard 9327: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9328: /* k1=nres; */
1.338 brouard 9329: k1=TKresult[nres];
9330: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9331: fprintf(ficgp,"\n\n# Resultline k1=%d ",k1);
1.264 brouard 9332: strcpy(gplotlabel,"(");
1.276 brouard 9333: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.337 brouard 9334: for (k=1; k<=cptcovs; k++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
9335: /* for each resultline nres, and position k, Tvresult[nres][k] gives the name of the variable and
9336: TinvDoQresult[nres][Tvresult[nres][k]] gives its value double or integer) */
9337: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9338: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9339: }
9340: /* if(m != 1 && TKresult[nres]!= k1) */
9341: /* continue; */
9342: /* fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1); */
9343: /* strcpy(gplotlabel,"("); */
9344: /* /\*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*\/ */
9345: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
9346: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
9347: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9348: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9349: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9350: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9351: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9352: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9353: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9354: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9355: /* } */
9356: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9357: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9358: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9359: /* } */
1.264 brouard 9360: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 9361: fprintf(ficgp,"\n#\n");
1.264 brouard 9362: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 9363: fprintf(ficgp,"\nset key outside ");
9364: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
9365: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 9366: fprintf(ficgp,"\nset ter svg size 640, 480 ");
9367: if (ng==1){
9368: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
9369: fprintf(ficgp,"\nunset log y");
9370: }else if (ng==2){
9371: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
9372: fprintf(ficgp,"\nset log y");
9373: }else if (ng==3){
9374: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
9375: fprintf(ficgp,"\nset log y");
9376: }else
9377: fprintf(ficgp,"\nunset title ");
9378: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
9379: i=1;
9380: for(k2=1; k2<=nlstate; k2++) {
9381: k3=i;
9382: for(k=1; k<=(nlstate+ndeath); k++) {
9383: if (k != k2){
9384: switch( ng) {
9385: case 1:
9386: if(nagesqr==0)
9387: fprintf(ficgp," p%d+p%d*x",i,i+1);
9388: else /* nagesqr =1 */
9389: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
9390: break;
9391: case 2: /* ng=2 */
9392: if(nagesqr==0)
9393: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
9394: else /* nagesqr =1 */
9395: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
9396: break;
9397: case 3:
9398: if(nagesqr==0)
9399: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
9400: else /* nagesqr =1 */
9401: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
9402: break;
9403: }
9404: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 9405: ijp=1; /* product no age */
9406: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
9407: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 9408: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.329 brouard 9409: switch(Typevar[j]){
9410: case 1:
9411: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
9412: if(j==Tage[ij]) { /* Product by age To be looked at!!*//* Bug valgrind */
9413: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
9414: if(DummyV[j]==0){/* Bug valgrind */
9415: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
9416: }else{ /* quantitative */
9417: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
9418: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9419: }
9420: ij++;
1.268 brouard 9421: }
1.237 brouard 9422: }
1.329 brouard 9423: }
9424: break;
9425: case 2:
9426: if(cptcovprod >0){
9427: if(j==Tprod[ijp]) { /* */
9428: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9429: if(ijp <=cptcovprod) { /* Product */
9430: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
9431: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
9432: /* 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)]); */
9433: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9434: }else{ /* Vn is dummy and Vm is quanti */
9435: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
9436: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9437: }
9438: }else{ /* Vn*Vm Vn is quanti */
9439: if(DummyV[Tvard[ijp][2]]==0){
9440: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
9441: }else{ /* Both quanti */
9442: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9443: }
1.268 brouard 9444: }
1.329 brouard 9445: ijp++;
1.237 brouard 9446: }
1.329 brouard 9447: } /* end Tprod */
9448: }
9449: break;
1.349 brouard 9450: case 3:
9451: if(cptcovdageprod >0){
9452: /* if(j==Tprod[ijp]) { */ /* not necessary */
9453: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
1.350 brouard 9454: if(ijp <=cptcovprod) { /* Product Vn*Vm and age*VN*Vm*/
9455: if(DummyV[Tvardk[ijp][1]]==0){/* Vn is dummy */
9456: if(DummyV[Tvardk[ijp][2]]==0){/* Vn and Vm are dummy */
1.349 brouard 9457: /* 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)]); */
9458: fprintf(ficgp,"+p%d*%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9459: }else{ /* Vn is dummy and Vm is quanti */
9460: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
1.350 brouard 9461: fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvardk[ijp][1]],Tqinvresult[nres][Tvardk[ijp][2]]);
1.349 brouard 9462: }
1.350 brouard 9463: }else{ /* age* Vn*Vm Vn is quanti HERE */
1.349 brouard 9464: if(DummyV[Tvard[ijp][2]]==0){
1.350 brouard 9465: fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvardk[ijp][2]],Tqinvresult[nres][Tvardk[ijp][1]]);
1.349 brouard 9466: }else{ /* Both quanti */
1.350 brouard 9467: fprintf(ficgp,"+p%d*%f*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvardk[ijp][1]],Tqinvresult[nres][Tvardk[ijp][2]]);
1.349 brouard 9468: }
9469: }
9470: ijp++;
9471: }
9472: /* } */ /* end Tprod */
9473: }
9474: break;
1.329 brouard 9475: case 0:
9476: /* simple covariate */
1.264 brouard 9477: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 9478: if(Dummy[j]==0){
9479: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
9480: }else{ /* quantitative */
9481: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 9482: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 9483: }
1.329 brouard 9484: /* end simple */
9485: break;
9486: default:
9487: break;
9488: } /* end switch */
1.237 brouard 9489: } /* end j */
1.329 brouard 9490: }else{ /* k=k2 */
9491: if(ng !=1 ){ /* For logit formula of log p11 is more difficult to get */
9492: fprintf(ficgp," (1.");i=i-ncovmodel;
9493: }else
9494: i=i-ncovmodel;
1.223 brouard 9495: }
1.227 brouard 9496:
1.223 brouard 9497: if(ng != 1){
9498: fprintf(ficgp,")/(1");
1.227 brouard 9499:
1.264 brouard 9500: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 9501: if(nagesqr==0)
1.264 brouard 9502: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 9503: else /* nagesqr =1 */
1.264 brouard 9504: 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 9505:
1.223 brouard 9506: ij=1;
1.329 brouard 9507: ijp=1;
9508: /* for(j=3; j <=ncovmodel-nagesqr; j++){ */
9509: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
9510: switch(Typevar[j]){
9511: case 1:
9512: if(cptcovage >0){
9513: if(j==Tage[ij]) { /* Bug valgrind */
9514: if(ij <=cptcovage) { /* Bug valgrind */
9515: if(DummyV[j]==0){/* Bug valgrind */
9516: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]); */
9517: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,nbcode[Tvar[j]][codtabm(k1,j)]); */
9518: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]);
9519: /* fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);; */
9520: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9521: }else{ /* quantitative */
9522: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
9523: fprintf(ficgp,"+p%d*%f*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
9524: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
9525: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9526: }
9527: ij++;
9528: }
9529: }
9530: }
9531: break;
9532: case 2:
9533: if(cptcovprod >0){
9534: if(j==Tprod[ijp]) { /* */
9535: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9536: if(ijp <=cptcovprod) { /* Product */
9537: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
9538: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
9539: /* 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)]); */
9540: fprintf(ficgp,"+p%d*%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9541: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
9542: }else{ /* Vn is dummy and Vm is quanti */
9543: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
9544: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9545: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9546: }
9547: }else{ /* Vn*Vm Vn is quanti */
9548: if(DummyV[Tvard[ijp][2]]==0){
9549: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
9550: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
9551: }else{ /* Both quanti */
9552: fprintf(ficgp,"+p%d*%f*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9553: /* fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9554: }
9555: }
9556: ijp++;
9557: }
9558: } /* end Tprod */
9559: } /* end if */
9560: break;
1.349 brouard 9561: case 3:
9562: if(cptcovdageprod >0){
9563: /* if(j==Tprod[ijp]) { /\* *\/ */
9564: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9565: if(ijp <=cptcovprod) { /* Product */
1.350 brouard 9566: if(DummyV[Tvardk[ijp][1]]==0){/* Vn is dummy */
9567: if(DummyV[Tvardk[ijp][2]]==0){/* Vn and Vm are dummy */
1.349 brouard 9568: /* 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)]); */
1.350 brouard 9569: fprintf(ficgp,"+p%d*%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvardk[ijp][1]],Tinvresult[nres][Tvardk[ijp][2]]);
1.349 brouard 9570: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
9571: }else{ /* Vn is dummy and Vm is quanti */
9572: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
1.350 brouard 9573: fprintf(ficgp,"+p%d*%d*%f*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvardk[ijp][1]],Tqinvresult[nres][Tvardk[ijp][2]]);
1.349 brouard 9574: /* fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9575: }
9576: }else{ /* Vn*Vm Vn is quanti */
1.350 brouard 9577: if(DummyV[Tvardk[ijp][2]]==0){
9578: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvardk[ijp][2]],Tqinvresult[nres][Tvardk[ijp][1]]);
1.349 brouard 9579: /* fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
9580: }else{ /* Both quanti */
1.350 brouard 9581: fprintf(ficgp,"+p%d*%f*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvardk[ijp][1]],Tqinvresult[nres][Tvardk[ijp][2]]);
1.349 brouard 9582: /* fprintf(ficgp,"+p%d*%f*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9583: }
9584: }
9585: ijp++;
9586: }
9587: /* } /\* end Tprod *\/ */
9588: } /* end if */
9589: break;
1.329 brouard 9590: case 0:
9591: /* simple covariate */
9592: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
9593: if(Dummy[j]==0){
9594: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
9595: fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]); /* */
9596: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
9597: }else{ /* quantitative */
9598: fprintf(ficgp,"+p%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* */
9599: /* fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* *\/ */
9600: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9601: }
9602: /* end simple */
9603: /* fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);/\* Valgrind bug nbcode *\/ */
9604: break;
9605: default:
9606: break;
9607: } /* end switch */
1.223 brouard 9608: }
9609: fprintf(ficgp,")");
9610: }
9611: fprintf(ficgp,")");
9612: if(ng ==2)
1.276 brouard 9613: 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 9614: else /* ng= 3 */
1.276 brouard 9615: 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 9616: }else{ /* end ng <> 1 */
1.223 brouard 9617: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 9618: 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 9619: }
9620: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
9621: fprintf(ficgp,",");
9622: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
9623: fprintf(ficgp,",");
9624: i=i+ncovmodel;
9625: } /* end k */
9626: } /* end k2 */
1.276 brouard 9627: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
9628: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.337 brouard 9629: } /* end resultline */
1.223 brouard 9630: } /* end ng */
9631: /* avoid: */
9632: fflush(ficgp);
1.126 brouard 9633: } /* end gnuplot */
9634:
9635:
9636: /*************** Moving average **************/
1.219 brouard 9637: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 9638: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 9639:
1.222 brouard 9640: int i, cpt, cptcod;
9641: int modcovmax =1;
9642: int mobilavrange, mob;
9643: int iage=0;
1.288 brouard 9644: int firstA1=0, firstA2=0;
1.222 brouard 9645:
1.266 brouard 9646: double sum=0., sumr=0.;
1.222 brouard 9647: double age;
1.266 brouard 9648: double *sumnewp, *sumnewm, *sumnewmr;
9649: double *agemingood, *agemaxgood;
9650: double *agemingoodr, *agemaxgoodr;
1.222 brouard 9651:
9652:
1.278 brouard 9653: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
9654: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 9655:
9656: sumnewp = vector(1,ncovcombmax);
9657: sumnewm = vector(1,ncovcombmax);
1.266 brouard 9658: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 9659: agemingood = vector(1,ncovcombmax);
1.266 brouard 9660: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 9661: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 9662: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 9663:
9664: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 9665: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 9666: sumnewp[cptcod]=0.;
1.266 brouard 9667: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
9668: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 9669: }
9670: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
9671:
1.266 brouard 9672: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
9673: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 9674: else mobilavrange=mobilav;
9675: for (age=bage; age<=fage; age++)
9676: for (i=1; i<=nlstate;i++)
9677: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
9678: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9679: /* We keep the original values on the extreme ages bage, fage and for
9680: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
9681: we use a 5 terms etc. until the borders are no more concerned.
9682: */
9683: for (mob=3;mob <=mobilavrange;mob=mob+2){
9684: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 9685: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
9686: sumnewm[cptcod]=0.;
9687: for (i=1; i<=nlstate;i++){
1.222 brouard 9688: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
9689: for (cpt=1;cpt<=(mob-1)/2;cpt++){
9690: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
9691: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
9692: }
9693: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 9694: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9695: } /* end i */
9696: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
9697: } /* end cptcod */
1.222 brouard 9698: }/* end age */
9699: }/* end mob */
1.266 brouard 9700: }else{
9701: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 9702: return -1;
1.266 brouard 9703: }
9704:
9705: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 9706: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
9707: if(invalidvarcomb[cptcod]){
9708: printf("\nCombination (%d) ignored because no cases \n",cptcod);
9709: continue;
9710: }
1.219 brouard 9711:
1.266 brouard 9712: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
9713: sumnewm[cptcod]=0.;
9714: sumnewmr[cptcod]=0.;
9715: for (i=1; i<=nlstate;i++){
9716: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9717: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9718: }
9719: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9720: agemingoodr[cptcod]=age;
9721: }
9722: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9723: agemingood[cptcod]=age;
9724: }
9725: } /* age */
9726: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 9727: sumnewm[cptcod]=0.;
1.266 brouard 9728: sumnewmr[cptcod]=0.;
1.222 brouard 9729: for (i=1; i<=nlstate;i++){
9730: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 9731: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9732: }
9733: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9734: agemaxgoodr[cptcod]=age;
1.222 brouard 9735: }
9736: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 9737: agemaxgood[cptcod]=age;
9738: }
9739: } /* age */
9740: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
9741: /* but they will change */
1.288 brouard 9742: firstA1=0;firstA2=0;
1.266 brouard 9743: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
9744: sumnewm[cptcod]=0.;
9745: sumnewmr[cptcod]=0.;
9746: for (i=1; i<=nlstate;i++){
9747: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9748: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9749: }
9750: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
9751: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9752: agemaxgoodr[cptcod]=age; /* age min */
9753: for (i=1; i<=nlstate;i++)
9754: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9755: }else{ /* bad we change the value with the values of good ages */
9756: for (i=1; i<=nlstate;i++){
9757: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
9758: } /* i */
9759: } /* end bad */
9760: }else{
9761: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9762: agemaxgood[cptcod]=age;
9763: }else{ /* bad we change the value with the values of good ages */
9764: for (i=1; i<=nlstate;i++){
9765: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
9766: } /* i */
9767: } /* end bad */
9768: }/* end else */
9769: sum=0.;sumr=0.;
9770: for (i=1; i<=nlstate;i++){
9771: sum+=mobaverage[(int)age][i][cptcod];
9772: sumr+=probs[(int)age][i][cptcod];
9773: }
9774: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 9775: if(!firstA1){
9776: firstA1=1;
9777: 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);
9778: }
9779: 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 9780: } /* end bad */
9781: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
9782: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 9783: if(!firstA2){
9784: firstA2=1;
9785: 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);
9786: }
9787: 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 9788: } /* end bad */
9789: }/* age */
1.266 brouard 9790:
9791: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 9792: sumnewm[cptcod]=0.;
1.266 brouard 9793: sumnewmr[cptcod]=0.;
1.222 brouard 9794: for (i=1; i<=nlstate;i++){
9795: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 9796: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9797: }
9798: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
9799: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
9800: agemingoodr[cptcod]=age;
9801: for (i=1; i<=nlstate;i++)
9802: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9803: }else{ /* bad we change the value with the values of good ages */
9804: for (i=1; i<=nlstate;i++){
9805: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
9806: } /* i */
9807: } /* end bad */
9808: }else{
9809: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9810: agemingood[cptcod]=age;
9811: }else{ /* bad */
9812: for (i=1; i<=nlstate;i++){
9813: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
9814: } /* i */
9815: } /* end bad */
9816: }/* end else */
9817: sum=0.;sumr=0.;
9818: for (i=1; i<=nlstate;i++){
9819: sum+=mobaverage[(int)age][i][cptcod];
9820: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 9821: }
1.266 brouard 9822: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 9823: 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 9824: } /* end bad */
9825: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
9826: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 9827: 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 9828: } /* end bad */
9829: }/* age */
1.266 brouard 9830:
1.222 brouard 9831:
9832: for (age=bage; age<=fage; age++){
1.235 brouard 9833: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 9834: sumnewp[cptcod]=0.;
9835: sumnewm[cptcod]=0.;
9836: for (i=1; i<=nlstate;i++){
9837: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
9838: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9839: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
9840: }
9841: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
9842: }
9843: /* printf("\n"); */
9844: /* } */
1.266 brouard 9845:
1.222 brouard 9846: /* brutal averaging */
1.266 brouard 9847: /* for (i=1; i<=nlstate;i++){ */
9848: /* for (age=1; age<=bage; age++){ */
9849: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
9850: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
9851: /* } */
9852: /* for (age=fage; age<=AGESUP; age++){ */
9853: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
9854: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
9855: /* } */
9856: /* } /\* end i status *\/ */
9857: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
9858: /* for (age=1; age<=AGESUP; age++){ */
9859: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
9860: /* mobaverage[(int)age][i][cptcod]=0.; */
9861: /* } */
9862: /* } */
1.222 brouard 9863: }/* end cptcod */
1.266 brouard 9864: free_vector(agemaxgoodr,1, ncovcombmax);
9865: free_vector(agemaxgood,1, ncovcombmax);
9866: free_vector(agemingood,1, ncovcombmax);
9867: free_vector(agemingoodr,1, ncovcombmax);
9868: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 9869: free_vector(sumnewm,1, ncovcombmax);
9870: free_vector(sumnewp,1, ncovcombmax);
9871: return 0;
9872: }/* End movingaverage */
1.218 brouard 9873:
1.126 brouard 9874:
1.296 brouard 9875:
1.126 brouard 9876: /************** Forecasting ******************/
1.296 brouard 9877: /* 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)*/
9878: 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){
9879: /* dateintemean, mean date of interviews
9880: dateprojd, year, month, day of starting projection
9881: dateprojf date of end of projection;year of end of projection (same day and month as proj1).
1.126 brouard 9882: agemin, agemax range of age
9883: dateprev1 dateprev2 range of dates during which prevalence is computed
9884: */
1.296 brouard 9885: /* double anprojd, mprojd, jprojd; */
9886: /* double anprojf, mprojf, jprojf; */
1.267 brouard 9887: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 9888: double agec; /* generic age */
1.296 brouard 9889: double agelim, ppij, yp,yp1,yp2;
1.126 brouard 9890: double *popeffectif,*popcount;
9891: double ***p3mat;
1.218 brouard 9892: /* double ***mobaverage; */
1.126 brouard 9893: char fileresf[FILENAMELENGTH];
9894:
9895: agelim=AGESUP;
1.211 brouard 9896: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
9897: in each health status at the date of interview (if between dateprev1 and dateprev2).
9898: We still use firstpass and lastpass as another selection.
9899: */
1.214 brouard 9900: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
9901: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 9902:
1.201 brouard 9903: strcpy(fileresf,"F_");
9904: strcat(fileresf,fileresu);
1.126 brouard 9905: if((ficresf=fopen(fileresf,"w"))==NULL) {
9906: printf("Problem with forecast resultfile: %s\n", fileresf);
9907: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
9908: }
1.235 brouard 9909: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
9910: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 9911:
1.225 brouard 9912: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 9913:
9914:
9915: stepsize=(int) (stepm+YEARM-1)/YEARM;
9916: if (stepm<=12) stepsize=1;
9917: if(estepm < stepm){
9918: printf ("Problem %d lower than %d\n",estepm, stepm);
9919: }
1.270 brouard 9920: else{
9921: hstepm=estepm;
9922: }
9923: if(estepm > stepm){ /* Yes every two year */
9924: stepsize=2;
9925: }
1.296 brouard 9926: hstepm=hstepm/stepm;
1.126 brouard 9927:
1.296 brouard 9928:
9929: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
9930: /* fractional in yp1 *\/ */
9931: /* aintmean=yp; */
9932: /* yp2=modf((yp1*12),&yp); */
9933: /* mintmean=yp; */
9934: /* yp1=modf((yp2*30.5),&yp); */
9935: /* jintmean=yp; */
9936: /* if(jintmean==0) jintmean=1; */
9937: /* if(mintmean==0) mintmean=1; */
1.126 brouard 9938:
1.296 brouard 9939:
9940: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */
9941: /* date2dmy(dateprojd,&jprojd, &mprojd, &anprojd); */
9942: /* date2dmy(dateprojf,&jprojf, &mprojf, &anprojf); */
1.351 ! brouard 9943: /* i1=pow(2,cptcoveff); */
! 9944: /* if (cptcovn < 1){i1=1;} */
1.126 brouard 9945:
1.296 brouard 9946: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.126 brouard 9947:
9948: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 9949:
1.126 brouard 9950: /* if (h==(int)(YEARM*yearp)){ */
1.351 ! brouard 9951: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
! 9952: k=TKresult[nres];
! 9953: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
! 9954: /* 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) *\/ */
! 9955: /* if(i1 != 1 && TKresult[nres]!= k) */
! 9956: /* continue; */
! 9957: /* if(invalidvarcomb[k]){ */
! 9958: /* printf("\nCombination (%d) projection ignored because no cases \n",k); */
! 9959: /* continue; */
! 9960: /* } */
1.227 brouard 9961: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
1.351 ! brouard 9962: for(j=1;j<=cptcovs;j++){
! 9963: /* for(j=1;j<=cptcoveff;j++) { */
! 9964: /* /\* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); *\/ */
! 9965: /* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
! 9966: /* } */
! 9967: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
! 9968: /* fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
! 9969: /* } */
! 9970: fprintf(ficresf," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.235 brouard 9971: }
1.351 ! brouard 9972:
1.227 brouard 9973: fprintf(ficresf," yearproj age");
9974: for(j=1; j<=nlstate+ndeath;j++){
9975: for(i=1; i<=nlstate;i++)
9976: fprintf(ficresf," p%d%d",i,j);
9977: fprintf(ficresf," wp.%d",j);
9978: }
1.296 brouard 9979: for (yearp=0; yearp<=(anprojf-anprojd);yearp +=stepsize) {
1.227 brouard 9980: fprintf(ficresf,"\n");
1.296 brouard 9981: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jprojd,mprojd,anprojd+yearp);
1.270 brouard 9982: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
9983: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 9984: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
9985: nhstepm = nhstepm/hstepm;
9986: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9987: oldm=oldms;savm=savms;
1.268 brouard 9988: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 9989: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 9990: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 9991: for (h=0; h<=nhstepm; h++){
9992: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 9993: break;
9994: }
9995: }
9996: fprintf(ficresf,"\n");
1.351 ! brouard 9997: /* for(j=1;j<=cptcoveff;j++) */
! 9998: for(j=1;j<=cptcovs;j++)
! 9999: fprintf(ficresf,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.332 brouard 10000: /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Tvaraff not correct *\/ */
1.351 ! brouard 10001: /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /\* TnsdVar[Tvaraff] correct *\/ */
1.296 brouard 10002: fprintf(ficresf,"%.f %.f ",anprojd+yearp,agec+h*hstepm/YEARM*stepm);
1.268 brouard 10003:
10004: for(j=1; j<=nlstate+ndeath;j++) {
10005: ppij=0.;
10006: for(i=1; i<=nlstate;i++) {
1.278 brouard 10007: if (mobilav>=1)
10008: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
10009: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
10010: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
10011: }
1.268 brouard 10012: fprintf(ficresf," %.3f", p3mat[i][j][h]);
10013: } /* end i */
10014: fprintf(ficresf," %.3f", ppij);
10015: }/* end j */
1.227 brouard 10016: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10017: } /* end agec */
1.266 brouard 10018: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
10019: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 10020: } /* end yearp */
10021: } /* end k */
1.219 brouard 10022:
1.126 brouard 10023: fclose(ficresf);
1.215 brouard 10024: printf("End of Computing forecasting \n");
10025: fprintf(ficlog,"End of Computing forecasting\n");
10026:
1.126 brouard 10027: }
10028:
1.269 brouard 10029: /************** Back Forecasting ******************/
1.296 brouard 10030: /* 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){ */
10031: 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){
10032: /* back1, year, month, day of starting backprojection
1.267 brouard 10033: agemin, agemax range of age
10034: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 10035: anback2 year of end of backprojection (same day and month as back1).
10036: prevacurrent and prev are prevalences.
1.267 brouard 10037: */
10038: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
10039: double agec; /* generic age */
1.302 brouard 10040: double agelim, ppij, ppi, yp,yp1,yp2; /* ,jintmean,mintmean,aintmean;*/
1.267 brouard 10041: double *popeffectif,*popcount;
10042: double ***p3mat;
10043: /* double ***mobaverage; */
10044: char fileresfb[FILENAMELENGTH];
10045:
1.268 brouard 10046: agelim=AGEINF;
1.267 brouard 10047: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
10048: in each health status at the date of interview (if between dateprev1 and dateprev2).
10049: We still use firstpass and lastpass as another selection.
10050: */
10051: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
10052: /* firstpass, lastpass, stepm, weightopt, model); */
10053:
10054: /*Do we need to compute prevalence again?*/
10055:
10056: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
10057:
10058: strcpy(fileresfb,"FB_");
10059: strcat(fileresfb,fileresu);
10060: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
10061: printf("Problem with back forecast resultfile: %s\n", fileresfb);
10062: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
10063: }
10064: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
10065: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
10066:
10067: if (cptcoveff==0) ncodemax[cptcoveff]=1;
10068:
10069:
10070: stepsize=(int) (stepm+YEARM-1)/YEARM;
10071: if (stepm<=12) stepsize=1;
10072: if(estepm < stepm){
10073: printf ("Problem %d lower than %d\n",estepm, stepm);
10074: }
1.270 brouard 10075: else{
10076: hstepm=estepm;
10077: }
10078: if(estepm >= stepm){ /* Yes every two year */
10079: stepsize=2;
10080: }
1.267 brouard 10081:
10082: hstepm=hstepm/stepm;
1.296 brouard 10083: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
10084: /* fractional in yp1 *\/ */
10085: /* aintmean=yp; */
10086: /* yp2=modf((yp1*12),&yp); */
10087: /* mintmean=yp; */
10088: /* yp1=modf((yp2*30.5),&yp); */
10089: /* jintmean=yp; */
10090: /* if(jintmean==0) jintmean=1; */
10091: /* if(mintmean==0) jintmean=1; */
1.267 brouard 10092:
1.351 ! brouard 10093: /* i1=pow(2,cptcoveff); */
! 10094: /* if (cptcovn < 1){i1=1;} */
1.267 brouard 10095:
1.296 brouard 10096: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
10097: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 10098:
10099: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
10100:
1.351 ! brouard 10101: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
! 10102: k=TKresult[nres];
! 10103: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
! 10104: /* for(k=1; k<=i1;k++){ */
! 10105: /* if(i1 != 1 && TKresult[nres]!= k) */
! 10106: /* continue; */
! 10107: /* if(invalidvarcomb[k]){ */
! 10108: /* printf("\nCombination (%d) projection ignored because no cases \n",k); */
! 10109: /* continue; */
! 10110: /* } */
1.268 brouard 10111: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.351 ! brouard 10112: for(j=1;j<=cptcovs;j++){
! 10113: /* for(j=1;j<=cptcoveff;j++) { */
! 10114: /* fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
! 10115: /* } */
! 10116: fprintf(ficresfb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.267 brouard 10117: }
1.351 ! brouard 10118: /* fprintf(ficrespij,"******\n"); */
! 10119: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
! 10120: /* fprintf(ficresfb," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
! 10121: /* } */
1.267 brouard 10122: fprintf(ficresfb," yearbproj age");
10123: for(j=1; j<=nlstate+ndeath;j++){
10124: for(i=1; i<=nlstate;i++)
1.268 brouard 10125: fprintf(ficresfb," b%d%d",i,j);
10126: fprintf(ficresfb," b.%d",j);
1.267 brouard 10127: }
1.296 brouard 10128: for (yearp=0; yearp>=(anbackf-anbackd);yearp -=stepsize) {
1.267 brouard 10129: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
10130: fprintf(ficresfb,"\n");
1.296 brouard 10131: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jbackd,mbackd,anbackd+yearp);
1.273 brouard 10132: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 10133: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
10134: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 10135: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 10136: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 10137: nhstepm = nhstepm/hstepm;
10138: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10139: oldm=oldms;savm=savms;
1.268 brouard 10140: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 10141: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 10142: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 10143: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
10144: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
10145: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 10146: for (h=0; h<=nhstepm; h++){
1.268 brouard 10147: if (h*hstepm/YEARM*stepm ==-yearp) {
10148: break;
10149: }
10150: }
10151: fprintf(ficresfb,"\n");
1.351 ! brouard 10152: /* for(j=1;j<=cptcoveff;j++) */
! 10153: for(j=1;j<=cptcovs;j++)
! 10154: fprintf(ficresfb,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
! 10155: /* fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.296 brouard 10156: fprintf(ficresfb,"%.f %.f ",anbackd+yearp,agec-h*hstepm/YEARM*stepm);
1.268 brouard 10157: for(i=1; i<=nlstate+ndeath;i++) {
10158: ppij=0.;ppi=0.;
10159: for(j=1; j<=nlstate;j++) {
10160: /* if (mobilav==1) */
1.269 brouard 10161: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
10162: ppi=ppi+prevacurrent[(int)agec][j][k];
10163: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
10164: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 10165: /* else { */
10166: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
10167: /* } */
1.268 brouard 10168: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
10169: } /* end j */
10170: if(ppi <0.99){
10171: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
10172: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
10173: }
10174: fprintf(ficresfb," %.3f", ppij);
10175: }/* end j */
1.267 brouard 10176: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10177: } /* end agec */
10178: } /* end yearp */
10179: } /* end k */
1.217 brouard 10180:
1.267 brouard 10181: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 10182:
1.267 brouard 10183: fclose(ficresfb);
10184: printf("End of Computing Back forecasting \n");
10185: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 10186:
1.267 brouard 10187: }
1.217 brouard 10188:
1.269 brouard 10189: /* Variance of prevalence limit: varprlim */
10190: 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 10191: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 10192:
10193: char fileresvpl[FILENAMELENGTH];
10194: FILE *ficresvpl;
10195: double **oldm, **savm;
10196: double **varpl; /* Variances of prevalence limits by age */
10197: int i1, k, nres, j ;
10198:
10199: strcpy(fileresvpl,"VPL_");
10200: strcat(fileresvpl,fileresu);
10201: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 10202: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 10203: exit(0);
10204: }
1.288 brouard 10205: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
10206: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 10207:
10208: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
10209: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
10210:
10211: i1=pow(2,cptcoveff);
10212: if (cptcovn < 1){i1=1;}
10213:
1.337 brouard 10214: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10215: k=TKresult[nres];
1.338 brouard 10216: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 10217: /* for(k=1; k<=i1;k++){ /\* We find the combination equivalent to result line values of dummies *\/ */
1.269 brouard 10218: if(i1 != 1 && TKresult[nres]!= k)
10219: continue;
10220: fprintf(ficresvpl,"\n#****** ");
10221: printf("\n#****** ");
10222: fprintf(ficlog,"\n#****** ");
1.337 brouard 10223: for(j=1;j<=cptcovs;j++) {
10224: fprintf(ficresvpl,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10225: fprintf(ficlog,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10226: printf("V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10227: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10228: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.269 brouard 10229: }
1.337 brouard 10230: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
10231: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10232: /* fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10233: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10234: /* } */
1.269 brouard 10235: fprintf(ficresvpl,"******\n");
10236: printf("******\n");
10237: fprintf(ficlog,"******\n");
10238:
10239: varpl=matrix(1,nlstate,(int) bage, (int) fage);
10240: oldm=oldms;savm=savms;
10241: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
10242: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
10243: /*}*/
10244: }
10245:
10246: fclose(ficresvpl);
1.288 brouard 10247: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
10248: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 10249:
10250: }
10251: /* Variance of back prevalence: varbprlim */
10252: 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){
10253: /*------- Variance of back (stable) prevalence------*/
10254:
10255: char fileresvbl[FILENAMELENGTH];
10256: FILE *ficresvbl;
10257:
10258: double **oldm, **savm;
10259: double **varbpl; /* Variances of back prevalence limits by age */
10260: int i1, k, nres, j ;
10261:
10262: strcpy(fileresvbl,"VBL_");
10263: strcat(fileresvbl,fileresu);
10264: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
10265: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
10266: exit(0);
10267: }
10268: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
10269: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
10270:
10271:
10272: i1=pow(2,cptcoveff);
10273: if (cptcovn < 1){i1=1;}
10274:
1.337 brouard 10275: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10276: k=TKresult[nres];
1.338 brouard 10277: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 10278: /* for(k=1; k<=i1;k++){ */
10279: /* if(i1 != 1 && TKresult[nres]!= k) */
10280: /* continue; */
1.269 brouard 10281: fprintf(ficresvbl,"\n#****** ");
10282: printf("\n#****** ");
10283: fprintf(ficlog,"\n#****** ");
1.337 brouard 10284: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */
1.338 brouard 10285: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
10286: fprintf(ficresvbl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
10287: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
1.337 brouard 10288: /* for(j=1;j<=cptcoveff;j++) { */
10289: /* fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10290: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10291: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10292: /* } */
10293: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
10294: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10295: /* fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10296: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
1.269 brouard 10297: }
10298: fprintf(ficresvbl,"******\n");
10299: printf("******\n");
10300: fprintf(ficlog,"******\n");
10301:
10302: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
10303: oldm=oldms;savm=savms;
10304:
10305: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
10306: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
10307: /*}*/
10308: }
10309:
10310: fclose(ficresvbl);
10311: printf("done variance-covariance of back prevalence\n");fflush(stdout);
10312: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
10313:
10314: } /* End of varbprlim */
10315:
1.126 brouard 10316: /************** Forecasting *****not tested NB*************/
1.227 brouard 10317: /* 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 10318:
1.227 brouard 10319: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
10320: /* int *popage; */
10321: /* double calagedatem, agelim, kk1, kk2; */
10322: /* double *popeffectif,*popcount; */
10323: /* double ***p3mat,***tabpop,***tabpopprev; */
10324: /* /\* double ***mobaverage; *\/ */
10325: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 10326:
1.227 brouard 10327: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10328: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10329: /* agelim=AGESUP; */
10330: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 10331:
1.227 brouard 10332: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 10333:
10334:
1.227 brouard 10335: /* strcpy(filerespop,"POP_"); */
10336: /* strcat(filerespop,fileresu); */
10337: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
10338: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
10339: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
10340: /* } */
10341: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
10342: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 10343:
1.227 brouard 10344: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 10345:
1.227 brouard 10346: /* /\* if (mobilav!=0) { *\/ */
10347: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
10348: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
10349: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
10350: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
10351: /* /\* } *\/ */
10352: /* /\* } *\/ */
1.126 brouard 10353:
1.227 brouard 10354: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
10355: /* if (stepm<=12) stepsize=1; */
1.126 brouard 10356:
1.227 brouard 10357: /* agelim=AGESUP; */
1.126 brouard 10358:
1.227 brouard 10359: /* hstepm=1; */
10360: /* hstepm=hstepm/stepm; */
1.218 brouard 10361:
1.227 brouard 10362: /* if (popforecast==1) { */
10363: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
10364: /* printf("Problem with population file : %s\n",popfile);exit(0); */
10365: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
10366: /* } */
10367: /* popage=ivector(0,AGESUP); */
10368: /* popeffectif=vector(0,AGESUP); */
10369: /* popcount=vector(0,AGESUP); */
1.126 brouard 10370:
1.227 brouard 10371: /* i=1; */
10372: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 10373:
1.227 brouard 10374: /* imx=i; */
10375: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
10376: /* } */
1.218 brouard 10377:
1.227 brouard 10378: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
10379: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
10380: /* k=k+1; */
10381: /* fprintf(ficrespop,"\n#******"); */
10382: /* for(j=1;j<=cptcoveff;j++) { */
10383: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
10384: /* } */
10385: /* fprintf(ficrespop,"******\n"); */
10386: /* fprintf(ficrespop,"# Age"); */
10387: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
10388: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 10389:
1.227 brouard 10390: /* for (cpt=0; cpt<=0;cpt++) { */
10391: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 10392:
1.227 brouard 10393: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
10394: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
10395: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 10396:
1.227 brouard 10397: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10398: /* oldm=oldms;savm=savms; */
10399: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 10400:
1.227 brouard 10401: /* for (h=0; h<=nhstepm; h++){ */
10402: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
10403: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
10404: /* } */
10405: /* for(j=1; j<=nlstate+ndeath;j++) { */
10406: /* kk1=0.;kk2=0; */
10407: /* for(i=1; i<=nlstate;i++) { */
10408: /* if (mobilav==1) */
10409: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
10410: /* else { */
10411: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
10412: /* } */
10413: /* } */
10414: /* if (h==(int)(calagedatem+12*cpt)){ */
10415: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
10416: /* /\*fprintf(ficrespop," %.3f", kk1); */
10417: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
10418: /* } */
10419: /* } */
10420: /* for(i=1; i<=nlstate;i++){ */
10421: /* kk1=0.; */
10422: /* for(j=1; j<=nlstate;j++){ */
10423: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
10424: /* } */
10425: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
10426: /* } */
1.218 brouard 10427:
1.227 brouard 10428: /* if (h==(int)(calagedatem+12*cpt)) */
10429: /* for(j=1; j<=nlstate;j++) */
10430: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
10431: /* } */
10432: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10433: /* } */
10434: /* } */
1.218 brouard 10435:
1.227 brouard 10436: /* /\******\/ */
1.218 brouard 10437:
1.227 brouard 10438: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
10439: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
10440: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
10441: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
10442: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 10443:
1.227 brouard 10444: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10445: /* oldm=oldms;savm=savms; */
10446: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
10447: /* for (h=0; h<=nhstepm; h++){ */
10448: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
10449: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
10450: /* } */
10451: /* for(j=1; j<=nlstate+ndeath;j++) { */
10452: /* kk1=0.;kk2=0; */
10453: /* for(i=1; i<=nlstate;i++) { */
10454: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
10455: /* } */
10456: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
10457: /* } */
10458: /* } */
10459: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10460: /* } */
10461: /* } */
10462: /* } */
10463: /* } */
1.218 brouard 10464:
1.227 brouard 10465: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 10466:
1.227 brouard 10467: /* if (popforecast==1) { */
10468: /* free_ivector(popage,0,AGESUP); */
10469: /* free_vector(popeffectif,0,AGESUP); */
10470: /* free_vector(popcount,0,AGESUP); */
10471: /* } */
10472: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10473: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10474: /* fclose(ficrespop); */
10475: /* } /\* End of popforecast *\/ */
1.218 brouard 10476:
1.126 brouard 10477: int fileappend(FILE *fichier, char *optionfich)
10478: {
10479: if((fichier=fopen(optionfich,"a"))==NULL) {
10480: printf("Problem with file: %s\n", optionfich);
10481: fprintf(ficlog,"Problem with file: %s\n", optionfich);
10482: return (0);
10483: }
10484: fflush(fichier);
10485: return (1);
10486: }
10487:
10488:
10489: /**************** function prwizard **********************/
10490: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
10491: {
10492:
10493: /* Wizard to print covariance matrix template */
10494:
1.164 brouard 10495: char ca[32], cb[32];
10496: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 10497: int numlinepar;
10498:
10499: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
10500: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
10501: for(i=1; i <=nlstate; i++){
10502: jj=0;
10503: for(j=1; j <=nlstate+ndeath; j++){
10504: if(j==i) continue;
10505: jj++;
10506: /*ca[0]= k+'a'-1;ca[1]='\0';*/
10507: printf("%1d%1d",i,j);
10508: fprintf(ficparo,"%1d%1d",i,j);
10509: for(k=1; k<=ncovmodel;k++){
10510: /* printf(" %lf",param[i][j][k]); */
10511: /* fprintf(ficparo," %lf",param[i][j][k]); */
10512: printf(" 0.");
10513: fprintf(ficparo," 0.");
10514: }
10515: printf("\n");
10516: fprintf(ficparo,"\n");
10517: }
10518: }
10519: printf("# Scales (for hessian or gradient estimation)\n");
10520: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
10521: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
10522: for(i=1; i <=nlstate; i++){
10523: jj=0;
10524: for(j=1; j <=nlstate+ndeath; j++){
10525: if(j==i) continue;
10526: jj++;
10527: fprintf(ficparo,"%1d%1d",i,j);
10528: printf("%1d%1d",i,j);
10529: fflush(stdout);
10530: for(k=1; k<=ncovmodel;k++){
10531: /* printf(" %le",delti3[i][j][k]); */
10532: /* fprintf(ficparo," %le",delti3[i][j][k]); */
10533: printf(" 0.");
10534: fprintf(ficparo," 0.");
10535: }
10536: numlinepar++;
10537: printf("\n");
10538: fprintf(ficparo,"\n");
10539: }
10540: }
10541: printf("# Covariance matrix\n");
10542: /* # 121 Var(a12)\n\ */
10543: /* # 122 Cov(b12,a12) Var(b12)\n\ */
10544: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
10545: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
10546: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
10547: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
10548: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
10549: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
10550: fflush(stdout);
10551: fprintf(ficparo,"# Covariance matrix\n");
10552: /* # 121 Var(a12)\n\ */
10553: /* # 122 Cov(b12,a12) Var(b12)\n\ */
10554: /* # ...\n\ */
10555: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
10556:
10557: for(itimes=1;itimes<=2;itimes++){
10558: jj=0;
10559: for(i=1; i <=nlstate; i++){
10560: for(j=1; j <=nlstate+ndeath; j++){
10561: if(j==i) continue;
10562: for(k=1; k<=ncovmodel;k++){
10563: jj++;
10564: ca[0]= k+'a'-1;ca[1]='\0';
10565: if(itimes==1){
10566: printf("#%1d%1d%d",i,j,k);
10567: fprintf(ficparo,"#%1d%1d%d",i,j,k);
10568: }else{
10569: printf("%1d%1d%d",i,j,k);
10570: fprintf(ficparo,"%1d%1d%d",i,j,k);
10571: /* printf(" %.5le",matcov[i][j]); */
10572: }
10573: ll=0;
10574: for(li=1;li <=nlstate; li++){
10575: for(lj=1;lj <=nlstate+ndeath; lj++){
10576: if(lj==li) continue;
10577: for(lk=1;lk<=ncovmodel;lk++){
10578: ll++;
10579: if(ll<=jj){
10580: cb[0]= lk +'a'-1;cb[1]='\0';
10581: if(ll<jj){
10582: if(itimes==1){
10583: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10584: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10585: }else{
10586: printf(" 0.");
10587: fprintf(ficparo," 0.");
10588: }
10589: }else{
10590: if(itimes==1){
10591: printf(" Var(%s%1d%1d)",ca,i,j);
10592: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
10593: }else{
10594: printf(" 0.");
10595: fprintf(ficparo," 0.");
10596: }
10597: }
10598: }
10599: } /* end lk */
10600: } /* end lj */
10601: } /* end li */
10602: printf("\n");
10603: fprintf(ficparo,"\n");
10604: numlinepar++;
10605: } /* end k*/
10606: } /*end j */
10607: } /* end i */
10608: } /* end itimes */
10609:
10610: } /* end of prwizard */
10611: /******************* Gompertz Likelihood ******************************/
10612: double gompertz(double x[])
10613: {
1.302 brouard 10614: double A=0.0,B=0.,L=0.0,sump=0.,num=0.;
1.126 brouard 10615: int i,n=0; /* n is the size of the sample */
10616:
1.220 brouard 10617: for (i=1;i<=imx ; i++) {
1.126 brouard 10618: sump=sump+weight[i];
10619: /* sump=sump+1;*/
10620: num=num+1;
10621: }
1.302 brouard 10622: L=0.0;
10623: /* agegomp=AGEGOMP; */
1.126 brouard 10624: /* for (i=0; i<=imx; i++)
10625: 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]);*/
10626:
1.302 brouard 10627: for (i=1;i<=imx ; i++) {
10628: /* mu(a)=mu(agecomp)*exp(teta*(age-agegomp))
10629: mu(a)=x[1]*exp(x[2]*(age-agegomp)); x[1] and x[2] are per year.
10630: * L= Product mu(agedeces)exp(-\int_ageexam^agedc mu(u) du ) for a death between agedc (in month)
10631: * and agedc +1 month, cens[i]=0: log(x[1]/YEARM)
10632: * +
10633: * exp(-\int_ageexam^agecens mu(u) du ) when censored, cens[i]=1
10634: */
10635: if (wav[i] > 1 || agedc[i] < AGESUP) {
10636: if (cens[i] == 1){
10637: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
10638: } else if (cens[i] == 0){
1.126 brouard 10639: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
1.302 brouard 10640: +log(x[1]/YEARM) +x[2]*(agedc[i]-agegomp)+log(YEARM);
10641: } else
10642: printf("Gompertz cens[%d] neither 1 nor 0\n",i);
1.126 brouard 10643: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
1.302 brouard 10644: L=L+A*weight[i];
1.126 brouard 10645: /* 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 10646: }
10647: }
1.126 brouard 10648:
1.302 brouard 10649: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
1.126 brouard 10650:
10651: return -2*L*num/sump;
10652: }
10653:
1.136 brouard 10654: #ifdef GSL
10655: /******************* Gompertz_f Likelihood ******************************/
10656: double gompertz_f(const gsl_vector *v, void *params)
10657: {
1.302 brouard 10658: double A=0.,B=0.,LL=0.0,sump=0.,num=0.;
1.136 brouard 10659: double *x= (double *) v->data;
10660: int i,n=0; /* n is the size of the sample */
10661:
10662: for (i=0;i<=imx-1 ; i++) {
10663: sump=sump+weight[i];
10664: /* sump=sump+1;*/
10665: num=num+1;
10666: }
10667:
10668:
10669: /* for (i=0; i<=imx; i++)
10670: 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]);*/
10671: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
10672: for (i=1;i<=imx ; i++)
10673: {
10674: if (cens[i] == 1 && wav[i]>1)
10675: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
10676:
10677: if (cens[i] == 0 && wav[i]>1)
10678: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
10679: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
10680:
10681: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
10682: if (wav[i] > 1 ) { /* ??? */
10683: LL=LL+A*weight[i];
10684: /* 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]);*/
10685: }
10686: }
10687:
10688: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
10689: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
10690:
10691: return -2*LL*num/sump;
10692: }
10693: #endif
10694:
1.126 brouard 10695: /******************* Printing html file ***********/
1.201 brouard 10696: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 10697: int lastpass, int stepm, int weightopt, char model[],\
10698: int imx, double p[],double **matcov,double agemortsup){
10699: int i,k;
10700:
10701: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
10702: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
10703: for (i=1;i<=2;i++)
10704: 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 10705: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 10706: fprintf(fichtm,"</ul>");
10707:
10708: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
10709:
10710: 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>");
10711:
10712: for (k=agegomp;k<(agemortsup-2);k++)
10713: 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]);
10714:
10715:
10716: fflush(fichtm);
10717: }
10718:
10719: /******************* Gnuplot file **************/
1.201 brouard 10720: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 10721:
10722: char dirfileres[132],optfileres[132];
1.164 brouard 10723:
1.126 brouard 10724: int ng;
10725:
10726:
10727: /*#ifdef windows */
10728: fprintf(ficgp,"cd \"%s\" \n",pathc);
10729: /*#endif */
10730:
10731:
10732: strcpy(dirfileres,optionfilefiname);
10733: strcpy(optfileres,"vpl");
1.199 brouard 10734: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 10735: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 10736: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 10737: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 10738: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
10739:
10740: }
10741:
1.136 brouard 10742: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
10743: {
1.126 brouard 10744:
1.136 brouard 10745: /*-------- data file ----------*/
10746: FILE *fic;
10747: char dummy[]=" ";
1.240 brouard 10748: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 10749: int lstra;
1.136 brouard 10750: int linei, month, year,iout;
1.302 brouard 10751: int noffset=0; /* This is the offset if BOM data file */
1.136 brouard 10752: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 10753: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 10754: char *stratrunc;
1.223 brouard 10755:
1.349 brouard 10756: /* DummyV=ivector(-1,NCOVMAX); /\* 1 to 3 *\/ */
10757: /* FixedV=ivector(-1,NCOVMAX); /\* 1 to 3 *\/ */
1.339 brouard 10758:
10759: ncovcolt=ncovcol+nqv+ntv+nqtv; /* total of covariates in the data, not in the model equation */
10760:
1.136 brouard 10761: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 10762: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
10763: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 10764: }
1.126 brouard 10765:
1.302 brouard 10766: /* Is it a BOM UTF-8 Windows file? */
10767: /* First data line */
10768: linei=0;
10769: while(fgets(line, MAXLINE, fic)) {
10770: noffset=0;
10771: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
10772: {
10773: noffset=noffset+3;
10774: printf("# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);fflush(stdout);
10775: fprintf(ficlog,"# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);
10776: fflush(ficlog); return 1;
10777: }
10778: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
10779: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
10780: {
10781: noffset=noffset+2;
1.304 brouard 10782: 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);
10783: 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 10784: fflush(ficlog); return 1;
10785: }
10786: else if( line[0] == 0 && line[1] == 0)
10787: {
10788: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
10789: noffset=noffset+4;
1.304 brouard 10790: 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);
10791: 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 10792: fflush(ficlog); return 1;
10793: }
10794: } else{
10795: ;/*printf(" Not a BOM file\n");*/
10796: }
10797: /* If line starts with a # it is a comment */
10798: if (line[noffset] == '#') {
10799: linei=linei+1;
10800: break;
10801: }else{
10802: break;
10803: }
10804: }
10805: fclose(fic);
10806: if((fic=fopen(datafile,"r"))==NULL) {
10807: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
10808: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
10809: }
10810: /* Not a Bom file */
10811:
1.136 brouard 10812: i=1;
10813: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
10814: linei=linei+1;
10815: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
10816: if(line[j] == '\t')
10817: line[j] = ' ';
10818: }
10819: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
10820: ;
10821: };
10822: line[j+1]=0; /* Trims blanks at end of line */
10823: if(line[0]=='#'){
10824: fprintf(ficlog,"Comment line\n%s\n",line);
10825: printf("Comment line\n%s\n",line);
10826: continue;
10827: }
10828: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 10829: strcpy(line, linetmp);
1.223 brouard 10830:
10831: /* Loops on waves */
10832: for (j=maxwav;j>=1;j--){
10833: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 10834: cutv(stra, strb, line, ' ');
10835: if(strb[0]=='.') { /* Missing value */
10836: lval=-1;
10837: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
1.341 brouard 10838: cotvar[j][ncovcol+nqv+ntv+iv][i]=-1; /* For performance reasons */
1.238 brouard 10839: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
10840: 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);
10841: 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);
10842: return 1;
10843: }
10844: }else{
10845: errno=0;
10846: /* what_kind_of_number(strb); */
10847: dval=strtod(strb,&endptr);
10848: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
10849: /* if(strb != endptr && *endptr == '\0') */
10850: /* dval=dlval; */
10851: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
10852: if( strb[0]=='\0' || (*endptr != '\0')){
10853: 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);
10854: 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);
10855: return 1;
10856: }
10857: cotqvar[j][iv][i]=dval;
1.341 brouard 10858: cotvar[j][ncovcol+nqv+ntv+iv][i]=dval; /* because cotvar starts now at first ntv */
1.238 brouard 10859: }
10860: strcpy(line,stra);
1.223 brouard 10861: }/* end loop ntqv */
1.225 brouard 10862:
1.223 brouard 10863: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 10864: cutv(stra, strb, line, ' ');
10865: if(strb[0]=='.') { /* Missing value */
10866: lval=-1;
10867: }else{
10868: errno=0;
10869: lval=strtol(strb,&endptr,10);
10870: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
10871: if( strb[0]=='\0' || (*endptr != '\0')){
10872: 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);
10873: 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);
10874: return 1;
10875: }
10876: }
10877: if(lval <-1 || lval >1){
10878: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10879: 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 10880: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10881: For example, for multinomial values like 1, 2 and 3,\n \
10882: build V1=0 V2=0 for the reference value (1),\n \
10883: V1=1 V2=0 for (2) \n \
1.223 brouard 10884: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10885: output of IMaCh is often meaningless.\n \
1.319 brouard 10886: Exiting.\n",lval,linei, i,line,iv,j);
1.238 brouard 10887: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10888: 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 10889: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10890: For example, for multinomial values like 1, 2 and 3,\n \
10891: build V1=0 V2=0 for the reference value (1),\n \
10892: V1=1 V2=0 for (2) \n \
1.223 brouard 10893: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10894: output of IMaCh is often meaningless.\n \
1.319 brouard 10895: Exiting.\n",lval,linei, i,line,iv,j);fflush(ficlog);
1.238 brouard 10896: return 1;
10897: }
1.341 brouard 10898: cotvar[j][ncovcol+nqv+iv][i]=(double)(lval);
1.238 brouard 10899: strcpy(line,stra);
1.223 brouard 10900: }/* end loop ntv */
1.225 brouard 10901:
1.223 brouard 10902: /* Statuses at wave */
1.137 brouard 10903: cutv(stra, strb, line, ' ');
1.223 brouard 10904: if(strb[0]=='.') { /* Missing value */
1.238 brouard 10905: lval=-1;
1.136 brouard 10906: }else{
1.238 brouard 10907: errno=0;
10908: lval=strtol(strb,&endptr,10);
10909: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
1.347 brouard 10910: if( strb[0]=='\0' || (*endptr != '\0' )){
10911: 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);
10912: 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);
10913: return 1;
10914: }else if( lval==0 || lval > nlstate+ndeath){
1.348 brouard 10915: printf("Error in data around '%s' at line number %d for individual %d, '%s'\n Should be a state at wave %d. A state should be 1 to %d and not %ld.\n Fix your data file '%s'! Exiting.\n", strb, linei,i,line,j,nlstate+ndeath, lval, datafile);fflush(stdout);
10916: fprintf(ficlog,"Error in data around '%s' at line number %d for individual %d, '%s'\n Should be a state at wave %d. A state should be 1 to %d and not %ld.\n Fix your data file '%s'! Exiting.\n", strb, linei,i,line,j,nlstate+ndeath, lval, datafile); fflush(ficlog);
1.238 brouard 10917: return 1;
10918: }
1.136 brouard 10919: }
1.225 brouard 10920:
1.136 brouard 10921: s[j][i]=lval;
1.225 brouard 10922:
1.223 brouard 10923: /* Date of Interview */
1.136 brouard 10924: strcpy(line,stra);
10925: cutv(stra, strb,line,' ');
1.169 brouard 10926: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10927: }
1.169 brouard 10928: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 10929: month=99;
10930: year=9999;
1.136 brouard 10931: }else{
1.225 brouard 10932: 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);
10933: 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);
10934: return 1;
1.136 brouard 10935: }
10936: anint[j][i]= (double) year;
1.302 brouard 10937: mint[j][i]= (double)month;
10938: /* if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){ */
10939: /* 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]); */
10940: /* 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]); */
10941: /* } */
1.136 brouard 10942: strcpy(line,stra);
1.223 brouard 10943: } /* End loop on waves */
1.225 brouard 10944:
1.223 brouard 10945: /* Date of death */
1.136 brouard 10946: cutv(stra, strb,line,' ');
1.169 brouard 10947: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10948: }
1.169 brouard 10949: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 10950: month=99;
10951: year=9999;
10952: }else{
1.141 brouard 10953: 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 10954: 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);
10955: return 1;
1.136 brouard 10956: }
10957: andc[i]=(double) year;
10958: moisdc[i]=(double) month;
10959: strcpy(line,stra);
10960:
1.223 brouard 10961: /* Date of birth */
1.136 brouard 10962: cutv(stra, strb,line,' ');
1.169 brouard 10963: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10964: }
1.169 brouard 10965: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 10966: month=99;
10967: year=9999;
10968: }else{
1.141 brouard 10969: 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);
10970: 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 10971: return 1;
1.136 brouard 10972: }
10973: if (year==9999) {
1.141 brouard 10974: 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);
10975: 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 10976: return 1;
10977:
1.136 brouard 10978: }
10979: annais[i]=(double)(year);
1.302 brouard 10980: moisnais[i]=(double)(month);
10981: for (j=1;j<=maxwav;j++){
10982: if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){
10983: 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]);
10984: 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]);
10985: }
10986: }
10987:
1.136 brouard 10988: strcpy(line,stra);
1.225 brouard 10989:
1.223 brouard 10990: /* Sample weight */
1.136 brouard 10991: cutv(stra, strb,line,' ');
10992: errno=0;
10993: dval=strtod(strb,&endptr);
10994: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 10995: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
10996: 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 10997: fflush(ficlog);
10998: return 1;
10999: }
11000: weight[i]=dval;
11001: strcpy(line,stra);
1.225 brouard 11002:
1.223 brouard 11003: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
11004: cutv(stra, strb, line, ' ');
11005: if(strb[0]=='.') { /* Missing value */
1.225 brouard 11006: lval=-1;
1.311 brouard 11007: coqvar[iv][i]=NAN;
11008: covar[ncovcol+iv][i]=NAN; /* including qvar in standard covar for performance reasons */
1.223 brouard 11009: }else{
1.225 brouard 11010: errno=0;
11011: /* what_kind_of_number(strb); */
11012: dval=strtod(strb,&endptr);
11013: /* if(strb != endptr && *endptr == '\0') */
11014: /* dval=dlval; */
11015: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
11016: if( strb[0]=='\0' || (*endptr != '\0')){
11017: 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);
11018: 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);
11019: return 1;
11020: }
11021: coqvar[iv][i]=dval;
1.226 brouard 11022: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 11023: }
11024: strcpy(line,stra);
11025: }/* end loop nqv */
1.136 brouard 11026:
1.223 brouard 11027: /* Covariate values */
1.136 brouard 11028: for (j=ncovcol;j>=1;j--){
11029: cutv(stra, strb,line,' ');
1.223 brouard 11030: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 11031: lval=-1;
1.136 brouard 11032: }else{
1.225 brouard 11033: errno=0;
11034: lval=strtol(strb,&endptr,10);
11035: if( strb[0]=='\0' || (*endptr != '\0')){
11036: 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);
11037: 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);
11038: return 1;
11039: }
1.136 brouard 11040: }
11041: if(lval <-1 || lval >1){
1.225 brouard 11042: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 11043: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
11044: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 11045: For example, for multinomial values like 1, 2 and 3,\n \
11046: build V1=0 V2=0 for the reference value (1),\n \
11047: V1=1 V2=0 for (2) \n \
1.136 brouard 11048: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 11049: output of IMaCh is often meaningless.\n \
1.136 brouard 11050: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 11051: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 11052: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
11053: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 11054: For example, for multinomial values like 1, 2 and 3,\n \
11055: build V1=0 V2=0 for the reference value (1),\n \
11056: V1=1 V2=0 for (2) \n \
1.136 brouard 11057: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 11058: output of IMaCh is often meaningless.\n \
1.136 brouard 11059: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 11060: return 1;
1.136 brouard 11061: }
11062: covar[j][i]=(double)(lval);
11063: strcpy(line,stra);
11064: }
11065: lstra=strlen(stra);
1.225 brouard 11066:
1.136 brouard 11067: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
11068: stratrunc = &(stra[lstra-9]);
11069: num[i]=atol(stratrunc);
11070: }
11071: else
11072: num[i]=atol(stra);
11073: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
11074: 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;}*/
11075:
11076: i=i+1;
11077: } /* End loop reading data */
1.225 brouard 11078:
1.136 brouard 11079: *imax=i-1; /* Number of individuals */
11080: fclose(fic);
1.225 brouard 11081:
1.136 brouard 11082: return (0);
1.164 brouard 11083: /* endread: */
1.225 brouard 11084: printf("Exiting readdata: ");
11085: fclose(fic);
11086: return (1);
1.223 brouard 11087: }
1.126 brouard 11088:
1.234 brouard 11089: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 11090: char *p1 = *stri, *p2 = *stri;
1.235 brouard 11091: while (*p2 == ' ')
1.234 brouard 11092: p2++;
11093: /* while ((*p1++ = *p2++) !=0) */
11094: /* ; */
11095: /* do */
11096: /* while (*p2 == ' ') */
11097: /* p2++; */
11098: /* while (*p1++ == *p2++); */
11099: *stri=p2;
1.145 brouard 11100: }
11101:
1.330 brouard 11102: int decoderesult( char resultline[], int nres)
1.230 brouard 11103: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
11104: {
1.235 brouard 11105: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 11106: char resultsav[MAXLINE];
1.330 brouard 11107: /* int resultmodel[MAXLINE]; */
1.334 brouard 11108: /* int modelresult[MAXLINE]; */
1.230 brouard 11109: char stra[80], strb[80], strc[80], strd[80],stre[80];
11110:
1.234 brouard 11111: removefirstspace(&resultline);
1.332 brouard 11112: printf("decoderesult:%s\n",resultline);
1.230 brouard 11113:
1.332 brouard 11114: strcpy(resultsav,resultline);
1.342 brouard 11115: /* printf("Decoderesult resultsav=\"%s\" resultline=\"%s\"\n", resultsav, resultline); */
1.230 brouard 11116: if (strlen(resultsav) >1){
1.334 brouard 11117: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' in this resultline */
1.230 brouard 11118: }
1.253 brouard 11119: if(j == 0){ /* Resultline but no = */
11120: TKresult[nres]=0; /* Combination for the nresult and the model */
11121: return (0);
11122: }
1.234 brouard 11123: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
1.334 brouard 11124: 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);
11125: 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 11126: /* return 1;*/
1.234 brouard 11127: }
1.334 brouard 11128: for(k=1; k<=j;k++){ /* Loop on any covariate of the RESULT LINE */
1.234 brouard 11129: if(nbocc(resultsav,'=') >1){
1.318 brouard 11130: 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 11131: /* 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 11132: cutl(strc,strd,strb,'='); /* strb:"V4=1" strc="1" strd="V4" */
1.332 brouard 11133: /* If a blank, then strc="V4=" and strd='\0' */
11134: if(strc[0]=='\0'){
11135: printf("Error in resultline, probably a blank after the \"%s\", \"result:%s\", stra=\"%s\" resultsav=\"%s\"\n",strb,resultline, stra, resultsav);
11136: fprintf(ficlog,"Error in resultline, probably a blank after the \"V%s=\", resultline=%s\n",strb,resultline);
11137: return 1;
11138: }
1.234 brouard 11139: }else
11140: cutl(strc,strd,resultsav,'=');
1.318 brouard 11141: Tvalsel[k]=atof(strc); /* 1 */ /* Tvalsel of k is the float value of the kth covariate appearing in this result line */
1.234 brouard 11142:
1.230 brouard 11143: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
1.318 brouard 11144: 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 11145: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
11146: /* cptcovsel++; */
11147: if (nbocc(stra,'=') >0)
11148: strcpy(resultsav,stra); /* and analyzes it */
11149: }
1.235 brouard 11150: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 11151: /* 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 11152: 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 11153: if(Typevar[k1]==0){ /* Single covariate in model */
11154: /* 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.234 brouard 11155: match=0;
1.318 brouard 11156: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
11157: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 11158: modelresult[nres][k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.318 brouard 11159: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
1.234 brouard 11160: break;
11161: }
11162: }
11163: if(match == 0){
1.338 brouard 11164: 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]);
11165: 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 11166: return 1;
1.234 brouard 11167: }
1.332 brouard 11168: }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*/
11169: /* We feed resultmodel[k1]=k2; */
11170: match=0;
11171: 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 */
11172: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 11173: 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 11174: resultmodel[nres][k1]=k2; /* Added here */
1.342 brouard 11175: /* printf("Decoderesult first modelresult[k2=%d]=%d (k1) V%d*AGE\n",k2,k1,Tvar[k1]); */
1.332 brouard 11176: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
11177: break;
11178: }
11179: }
11180: if(match == 0){
1.338 brouard 11181: 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]);
11182: 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 11183: return 1;
11184: }
1.349 brouard 11185: }else if(Typevar[k1]==2 || Typevar[k1]==3){ /* Product with or without age. We want to get the position in the resultline of the product in the model line*/
1.332 brouard 11186: /* resultmodel[nres][of such a Vn * Vm product k1] is not unique, so can't exist, we feed Tvard[k1][1] and [2] */
11187: match=0;
1.342 brouard 11188: /* 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 11189: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
11190: if(Tvardk[k1][1]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
11191: /* modelresult[k2]=k1; */
1.342 brouard 11192: /* printf("Decoderesult first Product modelresult[k2=%d]=%d (k1) V%d * \n",k2,k1,Tvarsel[k2]); */
1.332 brouard 11193: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
11194: }
11195: }
11196: if(match == 0){
1.349 brouard 11197: printf("Error in result line (Product without age first variable or double product with age): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][1], resultline, model);
11198: fprintf(ficlog,"Error in result line (Product without age first variable or double product with age): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][1], resultline, model);
1.332 brouard 11199: return 1;
11200: }
11201: match=0;
11202: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
11203: if(Tvardk[k1][2]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
11204: /* modelresult[k2]=k1;*/
1.342 brouard 11205: /* printf("Decoderesult second Product modelresult[k2=%d]=%d (k1) * V%d \n ",k2,k1,Tvarsel[k2]); */
1.332 brouard 11206: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
11207: break;
11208: }
11209: }
11210: if(match == 0){
1.349 brouard 11211: printf("Error in result line (Product without age second variable or double product with age): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][2], resultline, model);
11212: fprintf(ficlog,"Error in result line (Product without age second variable or double product with age): V%d is missing in result : %s according to model=1+age+%s\n",Tvardk[k1][2], resultline, model);
1.332 brouard 11213: return 1;
11214: }
11215: }/* End of testing */
1.333 brouard 11216: }/* End loop cptcovt */
1.235 brouard 11217: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 11218: /* Feeds resultmodel[nres][k1]=k2 for single covariate (k1) in the model equation */
1.334 brouard 11219: 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)
11220: * Loop on resultline variables: result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 11221: match=0;
1.318 brouard 11222: 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 11223: if(Typevar[k1]==0){ /* Single only */
1.349 brouard 11224: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 What if a product? */
1.330 brouard 11225: 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 11226: 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 11227: ++match;
11228: }
11229: }
11230: }
11231: if(match == 0){
1.338 brouard 11232: printf("Error in result line: variable V%d is missing in model; result: %s, model=1+age+%s\n",Tvarsel[k2], resultline, model);
11233: 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 11234: return 1;
1.234 brouard 11235: }else if(match > 1){
1.338 brouard 11236: printf("Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
11237: fprintf(ficlog,"Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
1.310 brouard 11238: return 1;
1.234 brouard 11239: }
11240: }
1.334 brouard 11241: /* cptcovres=j /\* Number of variables in the resultline is equal to cptcovs and thus useless *\/ */
1.234 brouard 11242: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 11243: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.330 brouard 11244: /* nres=1st result line: V4=1 V5=25.1 V3=0 V2=8 V1=1 */
11245: /* 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*/
11246: /* nres=2nd result line: V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.235 brouard 11247: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
11248: /* 1 0 0 0 */
11249: /* 2 1 0 0 */
11250: /* 3 0 1 0 */
1.330 brouard 11251: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 (nres=2)*/
1.235 brouard 11252: /* 5 0 0 1 */
1.330 brouard 11253: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 (nres=1)*/
1.235 brouard 11254: /* 7 0 1 1 */
11255: /* 8 1 1 1 */
1.237 brouard 11256: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
11257: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
11258: /* V5*age V5 known which value for nres? */
11259: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.334 brouard 11260: 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.
11261: * loop on position k1 in the MODEL LINE */
1.331 brouard 11262: /* k counting number of combination of single dummies in the equation model */
11263: /* k4 counting single dummies in the equation model */
11264: /* k4q counting single quantitatives in the equation model */
1.344 brouard 11265: 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 11266: /* 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 11267: /* 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 11268: /* Value in the (current nres) resultline of the variable at the k1th position in the model equation resultmodel[nres][k1]= k3 */
1.332 brouard 11269: /* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline */
11270: /* k3 is the position in the nres result line of the k1th variable of the model equation */
11271: /* Tvarsel[k3]: Name of the variable at the k3th position in the result line. */
11272: /* Tvalsel[k3]: Value of the variable at the k3th position in the result line. */
11273: /* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.334 brouard 11274: /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 11275: /* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1.330 brouard 11276: /* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.332 brouard 11277: k3= resultmodel[nres][k1]; /* From position k1 in model get position k3 in result line */
11278: /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
11279: 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 11280: 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 11281: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][Name]=Value; stores the value into the name of the variable. */
1.332 brouard 11282: /* Tinvresult[nres][4]=1 */
1.334 brouard 11283: /* Tresult[nres][k4+1]=Tvalsel[k3];/\* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) *\/ */
11284: Tresult[nres][k3]=Tvalsel[k3];/* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) */
11285: /* Tvresult[nres][k4+1]=(int)Tvarsel[k3];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
11286: Tvresult[nres][k3]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
1.237 brouard 11287: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.334 brouard 11288: precov[nres][k1]=Tvalsel[k3]; /* Value from resultline of the variable at the k1 position in the model */
1.342 brouard 11289: /* 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 11290: k4++;;
1.331 brouard 11291: }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Quantitative and single */
1.330 brouard 11292: /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.332 brouard 11293: /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.330 brouard 11294: /* Tqinvresult[nres][Name of a quantitative variable]= value of the variable in the result line */
1.332 brouard 11295: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 5 =k3q */
11296: k2q=(int)Tvarsel[k3q]; /* Name of variable at k3q th position in the resultline */
11297: /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.334 brouard 11298: /* Tqresult[nres][k4q+1]=Tvalsel[k3q]; /\* Tqresult[nres][1]=25.1 *\/ */
11299: /* Tvresult[nres][k4q+1]=(int)Tvarsel[k3q];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
11300: /* Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /\* Tvqresult[nres][1]=5 *\/ */
11301: Tqresult[nres][k3q]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
11302: Tvresult[nres][k3q]=(int)Tvarsel[k3q];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
11303: Tvqresult[nres][k3q]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
1.237 brouard 11304: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.330 brouard 11305: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.332 brouard 11306: precov[nres][k1]=Tvalsel[k3q];
1.342 brouard 11307: /* 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 11308: k4q++;;
1.350 brouard 11309: }else if( Dummy[k1]==2 ){ /* For dummy with age product "V2+V3+V4+V6+V7+V6*V2+V7*V2+V6*V3+V7*V3+V6*V4+V7*V4+age*V2+age*V3+age*V4+age*V6+age*V7+age*V6*V2+age*V6*V3+age*V7*V3+age*V6*V4+age*V7*V4\r"*/
11310: /* Tvar[k1]; */ /* Age variable */ /* 17 age*V6*V2 ?*/
1.332 brouard 11311: /* Wrong we want the value of variable name Tvar[k1] */
1.350 brouard 11312: if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
11313: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
11314: /* 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]]); */
11315: }else{
11316: k3= resultmodel[nres][k1]; /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
11317: 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)*/
11318: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][4]=1 */
11319: precov[nres][k1]=Tvalsel[k3];
11320: }
1.342 brouard 11321: /* 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 11322: }else if( Dummy[k1]==3 ){ /* For quant with age product */
1.350 brouard 11323: if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
11324: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
11325: /* 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]]); */
11326: }else{
11327: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 25.1=k3q */
11328: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
11329: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* TinvDoQresult[nres][5]=25.1 */
11330: precov[nres][k1]=Tvalsel[k3q];
11331: }
1.342 brouard 11332: /* printf("Decoderesult Quantitative with age nres=%d, k1=%d, precov[nres=%d][k1=%d]=%f Tvar[%d]=V%d V(k2q=%d)= Tvarsel[%d]=%d, Tvalsel[%d]=%f\n",nres, k1, nres, k1,precov[nres][k1], k1, Tvar[k1], k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]); */
1.349 brouard 11333: }else if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
1.332 brouard 11334: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
1.342 brouard 11335: /* 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 11336: }else{
1.332 brouard 11337: printf("Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
11338: fprintf(ficlog,"Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
1.235 brouard 11339: }
11340: }
1.234 brouard 11341:
1.334 brouard 11342: TKresult[nres]=++k; /* Number of combinations of dummies for the nresult and the model =Tvalsel[k3]*pow(2,k4) + 1*/
1.230 brouard 11343: return (0);
11344: }
1.235 brouard 11345:
1.230 brouard 11346: int decodemodel( char model[], int lastobs)
11347: /**< This routine decodes the model and returns:
1.224 brouard 11348: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
11349: * - nagesqr = 1 if age*age in the model, otherwise 0.
11350: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
11351: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
11352: * - cptcovage number of covariates with age*products =2
11353: * - cptcovs number of simple covariates
1.339 brouard 11354: * ncovcolt=ncovcol+nqv+ntv+nqtv total of covariates in the data, not in the model equation
1.224 brouard 11355: * - 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 11356: * which is a new column after the 9 (ncovcol+nqv+ntv+nqtv) variables.
1.319 brouard 11357: * - if k is a product Vn*Vm, covar[k][i] is filled with correct values for each individual
1.224 brouard 11358: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
11359: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
11360: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
11361: */
1.319 brouard 11362: /* 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 11363: {
1.238 brouard 11364: int i, j, k, ks, v;
1.349 brouard 11365: int n,m;
11366: int j1, k1, k11, k12, k2, k3, k4;
11367: char modelsav[300];
11368: char stra[300], strb[300], strc[300], strd[300],stre[300],strf[300];
1.187 brouard 11369: char *strpt;
1.349 brouard 11370: int **existcomb;
11371:
11372: existcomb=imatrix(1,NCOVMAX,1,NCOVMAX);
11373: for(i=1;i<=NCOVMAX;i++)
11374: for(j=1;j<=NCOVMAX;j++)
11375: existcomb[i][j]=0;
11376:
1.145 brouard 11377: /*removespace(model);*/
1.136 brouard 11378: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.349 brouard 11379: j=0, j1=0, k1=0, k12=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 11380: if (strstr(model,"AGE") !=0){
1.192 brouard 11381: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
11382: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 11383: return 1;
11384: }
1.141 brouard 11385: if (strstr(model,"v") !=0){
1.338 brouard 11386: printf("Error. 'v' must be in upper case 'V' model=1+age+%s ",model);
11387: fprintf(ficlog,"Error. 'v' must be in upper case model=1+age+%s ",model);fflush(ficlog);
1.141 brouard 11388: return 1;
11389: }
1.187 brouard 11390: strcpy(modelsav,model);
11391: if ((strpt=strstr(model,"age*age")) !=0){
1.338 brouard 11392: printf(" strpt=%s, model=1+age+%s\n",strpt, model);
1.187 brouard 11393: if(strpt != model){
1.338 brouard 11394: printf("Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 11395: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 11396: corresponding column of parameters.\n",model);
1.338 brouard 11397: fprintf(ficlog,"Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 11398: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 11399: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 11400: return 1;
1.225 brouard 11401: }
1.187 brouard 11402: nagesqr=1;
11403: if (strstr(model,"+age*age") !=0)
1.234 brouard 11404: substrchaine(modelsav, model, "+age*age");
1.187 brouard 11405: else if (strstr(model,"age*age+") !=0)
1.234 brouard 11406: substrchaine(modelsav, model, "age*age+");
1.187 brouard 11407: else
1.234 brouard 11408: substrchaine(modelsav, model, "age*age");
1.187 brouard 11409: }else
11410: nagesqr=0;
1.349 brouard 11411: if (strlen(modelsav) >1){ /* V2 +V3 +V4 +V6 +V7 +V6*V2 +V7*V2 +V6*V3 +V7*V3 +V6*V4 +V7*V4 +age*V2 +age*V3 +age*V4 +age*V6 +age*V7 +age*V6*V2 +V7*V2 +age*V6*V3 +age*V7*V3 +age*V6*V4 +age*V7*V4 */
1.187 brouard 11412: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
11413: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.351 ! brouard 11414: cptcovs=0; /**< Number of simple covariates V1 +V1*age +V3 +V3*V4 +age*age => V1 + V3 =4+1-3=2 Wrong */
1.187 brouard 11415: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 11416: * cst, age and age*age
11417: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
11418: /* including age products which are counted in cptcovage.
11419: * but the covariates which are products must be treated
11420: * separately: ncovn=4- 2=2 (V1+V3). */
1.349 brouard 11421: cptcovprod=0; /**< Number of products V1*V2 +v3*age = 2 */
11422: cptcovdageprod=0; /* Number of doouble products with age age*Vn*VM or Vn*age*Vm or Vn*Vm*age */
1.187 brouard 11423: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.349 brouard 11424: cptcovprodage=0;
11425: /* cptcovprodage=nboccstr(modelsav,"age");*/
1.225 brouard 11426:
1.187 brouard 11427: /* Design
11428: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
11429: * < ncovcol=8 >
11430: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
11431: * k= 1 2 3 4 5 6 7 8
11432: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
1.345 brouard 11433: * covar[k,i], are for fixed covariates, value of kth covariate if not including age for individual i:
1.224 brouard 11434: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
11435: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 11436: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
11437: * Tage[++cptcovage]=k
1.345 brouard 11438: * if products, new covar are created after ncovcol + nqv (quanti fixed) with k1
1.187 brouard 11439: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
11440: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
11441: * 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
11442: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
11443: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
11444: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
1.345 brouard 11445: * < ncovcol=8 8 fixed covariate. Additional starts at 9 (V5*V6) and 10(V7*V8) >
1.187 brouard 11446: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
11447: * k= 1 2 3 4 5 6 7 8 9 10 11 12
1.345 brouard 11448: * Tvard[k]= 2 1 3 3 10 11 8 8 5 6 7 8
11449: * p Tvar[1]@12={2, 1, 3, 3, 9, 10, 8, 8}
1.187 brouard 11450: * p Tprod[1]@2={ 6, 5}
11451: *p Tvard[1][1]@4= {7, 8, 5, 6}
11452: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
11453: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
1.319 brouard 11454: *How to reorganize? Tvars(orted)
1.187 brouard 11455: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
11456: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
11457: * {2, 1, 4, 8, 5, 6, 3, 7}
11458: * Struct []
11459: */
1.225 brouard 11460:
1.187 brouard 11461: /* This loop fills the array Tvar from the string 'model'.*/
11462: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
11463: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
11464: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
11465: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
11466: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
11467: /* k=1 Tvar[1]=2 (from V2) */
11468: /* k=5 Tvar[5] */
11469: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 11470: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 11471: /* } */
1.198 brouard 11472: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 11473: /*
11474: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 11475: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
11476: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
11477: }
1.187 brouard 11478: cptcovage=0;
1.351 ! brouard 11479:
! 11480: /* First loop in order to calculate */
! 11481: /* for age*VN*Vm
! 11482: * Provides, Typevar[k], Tage[cptcovage], existcomb[n][m], FixedV[ncovcolt+k12]
! 11483: * Tprod[k1]=k Tposprod[k]=k1; Tvard[k1][1] =m;
! 11484: */
! 11485: /* Needs FixedV[Tvardk[k][1]] */
! 11486: /* For others:
! 11487: * Sets Typevar[k];
! 11488: * Tvar[k]=ncovcol+nqv+ntv+nqtv+k11;
! 11489: * Tposprod[k]=k11;
! 11490: * Tprod[k11]=k;
! 11491: * Tvardk[k][1] =m;
! 11492: * Needs FixedV[Tvardk[k][1]] == 0
! 11493: */
! 11494:
1.319 brouard 11495: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model line */
11496: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+' cutl from left to right
11497: 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" */
11498: if (nbocc(modelsav,'+')==0)
11499: strcpy(strb,modelsav); /* and analyzes it */
1.234 brouard 11500: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
11501: /*scanf("%d",i);*/
1.349 brouard 11502: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V5*age+ V4+V3*age strb=V3*age OR double product with age strb=age*V6*V2 or V6*V2*age or V6*age*V2 */
11503: cutl(strc,strd,strb,'*'); /**< k=1 strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 OR strb=age*V6*V2 strc=V6*V2 strd=age OR c=V2*age OR c=age*V2 */
11504: if(strchr(strc,'*')) { /**< Model with age and DOUBLE product: allowed since 0.99r44, strc=V6*V2 or V2*age or age*V2, strd=age or V6 or V6 */
11505: Typevar[k]=3; /* 3 for age and double product age*Vn*Vm varying of fixed */
11506: if(strstr(strc,"age")!=0) { /* It means that strc=V2*age or age*V2 and thus that strd=Vn */
11507: cutl(stre,strf,strc,'*') ; /* strf=age or Vm, stre=Vm or age. If strc=V6*V2 then strf=V6 and stre=V2 */
11508: strcpy(strc,strb); /* save strb(=age*Vn*Vm) into strc */
11509: /* We want strb=Vn*Vm */
11510: if(strcmp(strf,"age")==0){ /* strf is "age" so that stre=Vm =V2 . */
11511: strcpy(strb,strd);
11512: strcat(strb,"*");
11513: strcat(strb,stre);
11514: }else{ /* strf=Vm If strf=V6 then stre=V2 */
11515: strcpy(strb,strf);
11516: strcat(strb,"*");
11517: strcat(strb,stre);
11518: strcpy(strd,strb); /* in order for strd to not be "age" for next test (will be Vn*Vm */
11519: }
1.351 ! brouard 11520: /* printf("DEBUG FIXED k=%d, Tage[k]=%d, Tvar[Tage[k]=%d,FixedV[Tvar[Tage[k]]]=%d\n",k,Tage[k],Tvar[Tage[k]],FixedV[Tvar[Tage[k]]]); */
! 11521: /* FixedV[Tvar[Tage[k]]]=0; /\* HERY not sure if V7*V4*age Fixed might not exist yet*\/ */
1.349 brouard 11522: }else{ /* strc=Vn*Vm (and strd=age) and should be strb=Vn*Vm but want to keep original strb double product */
11523: strcpy(stre,strb); /* save full b in stre */
11524: strcpy(strb,strc); /* save short c in new short b for next block strb=Vn*Vm*/
11525: strcpy(strf,strc); /* save short c in new short f */
11526: cutl(strc,strd,strf,'*'); /* We get strd=Vn and strc=Vm for next block (strb=Vn*Vm)*/
11527: /* strcpy(strc,stre);*/ /* save full e in c for future */
11528: }
11529: cptcovdageprod++; /* double product with age Which product is it? */
11530: /* strcpy(strb,strc); /\* strb was age*V6*V2 or V6*V2*age or V6*age*V2 IS now V6*V2 or V2*age or age*V2 *\/ */
11531: /* cutl(strc,strd,strb,'*'); /\* strd= V6 or V2 or age and strc= V2 or age or V2 *\/ */
1.234 brouard 11532: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
1.349 brouard 11533: n=atoi(stre);
1.234 brouard 11534: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
1.349 brouard 11535: m=atoi(strc);
11536: cptcovage++; /* Counts the number of covariates which include age as a product */
11537: Tage[cptcovage]=k; /* For age*V3*V2 gives the position in model of covariates associated with age Tage[1]=6 HERY too*/
11538: if(existcomb[n][m] == 0){
11539: /* r /home/brouard/Documents/Recherches/REVES/Zachary/Zach-2022/Feinuo_Sun/Feinuo-threeway/femV12V15_3wayintNBe.imach */
11540: printf("Warning in model combination V%d*V%d should exist in the model before adding V%d*V%d*age !\n",n,m,n,m);
11541: fprintf(ficlog,"Warning in model combination V%d*V%d should exist in the model before adding V%d*V%d*age !\n",n,m,n,m);
11542: fflush(ficlog);
11543: k1++; /* The combination Vn*Vm will be in the model so we create it at k1 */
11544: k12++;
11545: existcomb[n][m]=k1;
11546: existcomb[m][n]=k1;
11547: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1;
11548: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2+ age*V6*V3 Gives the k position of the k1 double product Vn*Vm or age*Vn*Vm*/
11549: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 Gives the k1 double product Vn*Vm or age*Vn*Vm at the k position */
11550: Tvard[k1][1] =m; /* m 1 for V1*/
11551: Tvardk[k][1] =m; /* m 1 for V1*/
11552: Tvard[k1][2] =n; /* n 4 for V4*/
11553: Tvardk[k][2] =n; /* n 4 for V4*/
1.351 ! brouard 11554: /* Tvar[Tage[cptcovage]]=k1;*/ /* Tvar[6=age*V3*V2]=9 (new fixed covariate) */ /* We don't know about Fixed yet HERE */
1.349 brouard 11555: 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 */
11556: for (i=1; i<=lastobs;i++){/* For fixed product */
11557: /* Computes the new covariate which is a product of
11558: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
11559: covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
11560: }
11561: cptcovprodage++; /* Counting the number of fixed covariate with age */
11562: FixedV[ncovcolt+k12]=0; /* We expand Vn*Vm */
11563: k12++;
11564: FixedV[ncovcolt+k12]=0;
11565: }else{ /*End of FixedV */
11566: cptcovprodvage++; /* Counting the number of varying covariate with age */
11567: FixedV[ncovcolt+k12]=1; /* We expand Vn*Vm */
11568: k12++;
11569: FixedV[ncovcolt+k12]=1;
11570: }
11571: }else{ /* k1 Vn*Vm already exists */
11572: k11=existcomb[n][m];
11573: Tposprod[k]=k11; /* OK */
11574: Tvar[k]=Tvar[Tprod[k11]]; /* HERY */
11575: Tvardk[k][1]=m;
11576: Tvardk[k][2]=n;
11577: 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 */
11578: /*cptcovage++;*/ /* Counts the number of covariates which include age as a product */
11579: cptcovprodage++; /* Counting the number of fixed covariate with age */
11580: /*Tage[cptcovage]=k;*/ /* For age*V3*V2 Tage[1]=V3*V3=9 HERY too*/
11581: Tvar[Tage[cptcovage]]=k1;
11582: FixedV[ncovcolt+k12]=0; /* We expand Vn*Vm */
11583: k12++;
11584: FixedV[ncovcolt+k12]=0;
11585: }else{ /* Already exists but time varying (and age) */
11586: /*cptcovage++;*/ /* Counts the number of covariates which include age as a product */
11587: /*Tage[cptcovage]=k;*/ /* For age*V3*V2 Tage[1]=V3*V3=9 HERY too*/
11588: /* Tvar[Tage[cptcovage]]=k1; */
11589: cptcovprodvage++;
11590: FixedV[ncovcolt+k12]=1; /* We expand Vn*Vm */
11591: k12++;
11592: FixedV[ncovcolt+k12]=1;
11593: }
11594: }
11595: /* Tage[cptcovage]=k; /\* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
11596: /* Tvar[k]=k11; /\* HERY *\/ */
11597: } else {/* simple product strb=age*Vn so that c=Vn and d=age, or strb=Vn*age so that c=age and d=Vn, or b=Vn*Vm so that c=Vm and d=Vn */
11598: cptcovprod++;
11599: if (strcmp(strc,"age")==0) { /**< Model includes age: strb= Vn*age c=age d=Vn*/
11600: /* covar is not filled and then is empty */
11601: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
11602: 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 */
11603: Typevar[k]=1; /* 1 for age product */
11604: cptcovage++; /* Counts the number of covariates which include age as a product */
11605: Tage[cptcovage]=k; /* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
11606: if( FixedV[Tvar[k]] == 0){
11607: cptcovprodage++; /* Counting the number of fixed covariate with age */
11608: }else{
11609: cptcovprodvage++; /* Counting the number of fixedvarying covariate with age */
11610: }
11611: /*printf("stre=%s ", stre);*/
11612: } else if (strcmp(strd,"age")==0) { /* strb= age*Vn c=Vn */
11613: cutl(stre,strb,strc,'V');
11614: Tvar[k]=atoi(stre);
11615: Typevar[k]=1; /* 1 for age product */
11616: cptcovage++;
11617: Tage[cptcovage]=k;
11618: if( FixedV[Tvar[k]] == 0){
11619: cptcovprodage++; /* Counting the number of fixed covariate with age */
11620: }else{
11621: cptcovprodvage++; /* Counting the number of fixedvarying covariate with age */
1.339 brouard 11622: }
1.349 brouard 11623: }else{ /* for product Vn*Vm */
11624: Typevar[k]=2; /* 2 for product Vn*Vm */
11625: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
11626: n=atoi(stre);
11627: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
11628: m=atoi(strc);
11629: k1++;
11630: cptcovprodnoage++;
11631: if(existcomb[n][m] != 0 || existcomb[m][n] != 0){
11632: printf("Warning in model combination V%d*V%d already exists in the model in position k1=%d!\n",n,m,existcomb[n][m]);
11633: fprintf(ficlog,"Warning in model combination V%d*V%d already exists in the model in position k1=%d!\n",n,m,existcomb[n][m]);
11634: fflush(ficlog);
11635: k11=existcomb[n][m];
11636: Tvar[k]=ncovcol+nqv+ntv+nqtv+k11;
11637: Tposprod[k]=k11;
11638: Tprod[k11]=k;
11639: Tvardk[k][1] =m; /* m 1 for V1*/
11640: /* Tvard[k11][1] =m; /\* n 4 for V4*\/ */
11641: Tvardk[k][2] =n; /* n 4 for V4*/
11642: /* Tvard[k11][2] =n; /\* n 4 for V4*\/ */
11643: }else{ /* combination Vn*Vm doesn't exist we create it (no age)*/
11644: existcomb[n][m]=k1;
11645: existcomb[m][n]=k1;
11646: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* ncovcolt+k1; For model-covariate k tells which data-covariate to use but
11647: because this model-covariate is a construction we invent a new column
11648: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
11649: If already ncovcol=4 and model= V2 + V1 + V1*V4 + age*V3 + V3*V2
11650: thus after V4 we invent V5 and V6 because age*V3 will be computed in 4
11651: Tvar[3=V1*V4]=4+1=5 Tvar[5=V3*V2]=4 + 2= 6, Tvar[4=age*V3]=3 etc */
11652: /* Please remark that the new variables are model dependent */
11653: /* If we have 4 variable but the model uses only 3, like in
11654: * model= V1 + age*V1 + V2 + V3 + age*V2 + age*V3 + V1*V2 + V1*V3
11655: * k= 1 2 3 4 5 6 7 8
11656: * Tvar[k]=1 1 2 3 2 3 (5 6) (and not 4 5 because of V4 missing)
11657: * Tage[kk] [1]= 2 [2]=5 [3]=6 kk=1 to cptcovage=3
11658: * Tvar[Tage[kk]][1]=2 [2]=2 [3]=3
11659: */
11660: /* We need to feed some variables like TvarVV, but later on next loop because of ncovv (k2) is not correct */
11661: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 +V6*V2*age */
11662: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 */
11663: Tvard[k1][1] =m; /* m 1 for V1*/
11664: Tvardk[k][1] =m; /* m 1 for V1*/
11665: Tvard[k1][2] =n; /* n 4 for V4*/
11666: Tvardk[k][2] =n; /* n 4 for V4*/
11667: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
11668: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
11669: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
11670: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
11671: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
11672: 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 */
11673: for (i=1; i<=lastobs;i++){/* For fixed product */
11674: /* Computes the new covariate which is a product of
11675: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
11676: covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
11677: }
11678: /* TvarVV[k2]=n; */
11679: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11680: /* TvarVV[k2+1]=m; */
11681: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11682: }else{ /* not FixedV */
11683: /* TvarVV[k2]=n; */
11684: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11685: /* TvarVV[k2+1]=m; */
11686: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11687: }
11688: } /* End of creation of Vn*Vm if not created by age*Vn*Vm earlier */
11689: } /* End of product Vn*Vm */
11690: } /* End of age*double product or simple product */
11691: }else { /* not a product */
1.234 brouard 11692: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
11693: /* scanf("%d",i);*/
11694: cutl(strd,strc,strb,'V');
11695: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
11696: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
11697: Tvar[k]=atoi(strd);
11698: Typevar[k]=0; /* 0 for simple covariates */
11699: }
11700: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 11701: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 11702: scanf("%d",i);*/
1.187 brouard 11703: } /* end of loop + on total covariates */
1.351 ! brouard 11704:
! 11705:
1.187 brouard 11706: } /* end if strlen(modelsave == 0) age*age might exist */
11707: } /* end if strlen(model == 0) */
1.349 brouard 11708: cptcovs=cptcovt - cptcovdageprod - cptcovprod;/**< Number of simple covariates V1 +V1*age +V3 +V3*V4 +age*age + age*v4*V3=> V1 + V3 =4+1-3=2 */
11709:
1.136 brouard 11710: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
11711: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 11712:
1.136 brouard 11713: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 11714: printf("cptcovprod=%d ", cptcovprod);
11715: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
11716: scanf("%d ",i);*/
11717:
11718:
1.230 brouard 11719: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
11720: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 11721: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
11722: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
11723: k = 1 2 3 4 5 6 7 8 9
11724: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
1.319 brouard 11725: Typevar[k]= 0 0 0 2 1 0 2 1 0
1.227 brouard 11726: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
11727: Dummy[k] 1 0 0 0 3 1 1 2 3
11728: Tmodelind[combination of covar]=k;
1.225 brouard 11729: */
11730: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 11731: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 11732: /* 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 11733: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.318 brouard 11734: printf("Model=1+age+%s\n\
1.349 brouard 11735: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product, 3 for double product with age \n\
1.227 brouard 11736: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
11737: 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 11738: fprintf(ficlog,"Model=1+age+%s\n\
1.349 brouard 11739: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product, 3 for double product with age \n\
1.227 brouard 11740: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
11741: 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 11742: for(k=-1;k<=NCOVMAX; k++){ Fixed[k]=0; Dummy[k]=0;}
11743: for(k=1;k<=NCOVMAX; k++){TvarFind[k]=0; TvarVind[k]=0;}
1.351 ! brouard 11744:
! 11745:
! 11746: /* Second loop for calculating Fixed[k], Dummy[k]*/
! 11747:
! 11748:
1.349 brouard 11749: for(k=1, ncovf=0, nsd=0, nsq=0, ncovv=0,ncovva=0,ncovvta=0, ncova=0, ncoveff=0, nqfveff=0, ntveff=0, nqtveff=0, ncovvt=0;k<=cptcovt; k++){ /* or cptocvt loop on k from model */
1.234 brouard 11750: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 11751: Fixed[k]= 0;
11752: Dummy[k]= 0;
1.225 brouard 11753: ncoveff++;
1.232 brouard 11754: ncovf++;
1.234 brouard 11755: nsd++;
11756: modell[k].maintype= FTYPE;
11757: TvarsD[nsd]=Tvar[k];
11758: TvarsDind[nsd]=k;
1.330 brouard 11759: TnsdVar[Tvar[k]]=nsd;
1.234 brouard 11760: TvarF[ncovf]=Tvar[k];
11761: TvarFind[ncovf]=k;
11762: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
11763: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.339 brouard 11764: /* }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /\* Product of fixed dummy (<=ncovcol) covariates For a fixed product k is higher than ncovcol *\/ */
1.240 brouard 11765: }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 11766: Fixed[k]= 0;
11767: Dummy[k]= 1;
1.230 brouard 11768: nqfveff++;
1.234 brouard 11769: modell[k].maintype= FTYPE;
11770: modell[k].subtype= FQ;
11771: nsq++;
1.334 brouard 11772: TvarsQ[nsq]=Tvar[k]; /* Gives the variable name (extended to products) of first nsq simple quantitative covariates (fixed or time vary see below */
11773: TvarsQind[nsq]=k; /* Gives the position in the model equation of the first nsq simple quantitative covariates (fixed or time vary) */
1.232 brouard 11774: ncovf++;
1.234 brouard 11775: TvarF[ncovf]=Tvar[k];
11776: TvarFind[ncovf]=k;
1.231 brouard 11777: 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 11778: 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 11779: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.339 brouard 11780: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11781: /* model V1+V3+age*V1+age*V3+V1*V3 */
11782: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11783: ncovvt++;
11784: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
11785: TvarVVind[ncovvt]=k; /* TvarVVind[1]=2 (second position in the model equation */
11786:
1.227 brouard 11787: Fixed[k]= 1;
11788: Dummy[k]= 0;
1.225 brouard 11789: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 11790: modell[k].maintype= VTYPE;
11791: modell[k].subtype= VD;
11792: nsd++;
11793: TvarsD[nsd]=Tvar[k];
11794: TvarsDind[nsd]=k;
1.330 brouard 11795: TnsdVar[Tvar[k]]=nsd; /* To be verified */
1.234 brouard 11796: ncovv++; /* Only simple time varying variables */
11797: TvarV[ncovv]=Tvar[k];
1.242 brouard 11798: 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 11799: 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 */
11800: 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 11801: 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);
11802: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 11803: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.339 brouard 11804: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11805: /* model V1+V3+age*V1+age*V3+V1*V3 */
11806: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11807: ncovvt++;
11808: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
11809: TvarVVind[ncovvt]=k; /* TvarVV[1]=V3 (first time varying in the model equation */
11810:
1.234 brouard 11811: Fixed[k]= 1;
11812: Dummy[k]= 1;
11813: nqtveff++;
11814: modell[k].maintype= VTYPE;
11815: modell[k].subtype= VQ;
11816: ncovv++; /* Only simple time varying variables */
11817: nsq++;
1.334 brouard 11818: 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) */
11819: 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 11820: TvarV[ncovv]=Tvar[k];
1.242 brouard 11821: 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 11822: 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 */
11823: 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 11824: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
11825: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
1.349 brouard 11826: /* printf("Quasi TmodelQind[%d]=%d,Tvar[TmodelQind[%d]]=V%d, ncovcol=%d, nqv=%d, ntv=%Ad,Tvar[k]- ncovcol-nqv-ntv=%d\n",nqtveff,k,nqtveff,Tvar[k], ncovcol, nqv, ntv, Tvar[k]- ncovcol-nqv-ntv); */
1.342 brouard 11827: /* printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv); */
1.227 brouard 11828: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 11829: ncova++;
11830: TvarA[ncova]=Tvar[k];
11831: TvarAind[ncova]=k;
1.349 brouard 11832: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
11833: /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
1.231 brouard 11834: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 11835: Fixed[k]= 2;
11836: Dummy[k]= 2;
11837: modell[k].maintype= ATYPE;
11838: modell[k].subtype= APFD;
1.349 brouard 11839: ncovta++;
11840: TvarAVVA[ncovta]=Tvar[k]; /* (2)age*V3 */
11841: TvarAVVAind[ncovta]=k;
1.240 brouard 11842: /* ncoveff++; */
1.227 brouard 11843: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 11844: Fixed[k]= 2;
11845: Dummy[k]= 3;
11846: modell[k].maintype= ATYPE;
11847: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
1.349 brouard 11848: ncovta++;
11849: TvarAVVA[ncovta]=Tvar[k]; /* */
11850: TvarAVVAind[ncovta]=k;
1.240 brouard 11851: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 11852: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 11853: Fixed[k]= 3;
11854: Dummy[k]= 2;
11855: modell[k].maintype= ATYPE;
11856: modell[k].subtype= APVD; /* Product age * varying dummy */
1.349 brouard 11857: ncovva++;
11858: TvarVVA[ncovva]=Tvar[k]; /* (1)+age*V6 + (2)age*V7 */
11859: TvarVVAind[ncovva]=k;
11860: ncovta++;
11861: TvarAVVA[ncovta]=Tvar[k]; /* */
11862: TvarAVVAind[ncovta]=k;
1.240 brouard 11863: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 11864: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 11865: Fixed[k]= 3;
11866: Dummy[k]= 3;
11867: modell[k].maintype= ATYPE;
11868: modell[k].subtype= APVQ; /* Product age * varying quantitative */
1.349 brouard 11869: ncovva++;
11870: TvarVVA[ncovva]=Tvar[k]; /* */
11871: TvarVVAind[ncovva]=k;
11872: ncovta++;
11873: TvarAVVA[ncovta]=Tvar[k]; /* (1)+age*V6 + (2)age*V7 */
11874: TvarAVVAind[ncovta]=k;
1.240 brouard 11875: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 11876: }
1.349 brouard 11877: }else if( Tposprod[k]>0 && Typevar[k]==2){ /* Detects if fixed product no age Vm*Vn */
11878: printf("MEMORY ERRORR k=%d Tposprod[k]=%d, Typevar[k]=%d\n ",k, Tposprod[k], Typevar[k]);
11879: if(FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){ /* Needs a fixed product Product of fixed dummy (<=ncovcol) covariates For a fixed product k is higher than ncovcol V3*V2 */
11880: printf("MEMORY ERRORR k=%d Tvardk[k][1]=%d, Tvardk[k][2]=%d, FixedV[Tvardk[k][1]]=%d,FixedV[Tvardk[k][2]]=%d\n ",k,Tvardk[k][1],Tvardk[k][2],FixedV[Tvardk[k][1]],FixedV[Tvardk[k][2]]);
11881: Fixed[k]= 0;
11882: Dummy[k]= 0;
11883: ncoveff++;
11884: ncovf++;
11885: /* ncovv++; */
11886: /* TvarVV[ncovv]=Tvardk[k][1]; */
11887: /* FixedV[ncovcolt+ncovv]=0; /\* or FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11888: /* ncovv++; */
11889: /* TvarVV[ncovv]=Tvardk[k][2]; */
11890: /* FixedV[ncovcolt+ncovv]=0; /\* or FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11891: modell[k].maintype= FTYPE;
11892: TvarF[ncovf]=Tvar[k];
11893: /* TnsdVar[Tvar[k]]=nsd; */ /* To be done */
11894: TvarFind[ncovf]=k;
11895: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
11896: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
11897: }else{/* product varying Vn * Vm without age, V1+V3+age*V1+age*V3+V1*V3 looking at V1*V3, Typevar={0, 0, 1, 1, 2}, k=5, V1 is fixed, V3 is timevary, V5 is a product */
11898: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11899: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age*/
11900: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11901: k1=Tposprod[k]; /* Position in the products of product k, Tposprod={0, 0, 0, 0, 1, 1} k1=1 first product but second time varying because of V3 */
11902: ncovvt++;
11903: TvarVV[ncovvt]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */
11904: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
11905: ncovvt++;
11906: TvarVV[ncovvt]=Tvard[k1][2]; /* TvarVV[3]=V3 */
11907: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
11908:
11909: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
11910: /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
11911:
11912: if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */
11913: if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */
11914: Fixed[k]= 1;
11915: Dummy[k]= 0;
11916: modell[k].maintype= FTYPE;
11917: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
11918: ncovf++; /* Fixed variables without age */
11919: TvarF[ncovf]=Tvar[k];
11920: TvarFind[ncovf]=k;
11921: }else if(Tvard[k1][2] <=ncovcol+nqv){ /* Vm is quanti fixed */
11922: Fixed[k]= 0; /* Fixed product */
11923: Dummy[k]= 1;
11924: modell[k].maintype= FTYPE;
11925: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
11926: ncovf++; /* Varying variables without age */
11927: TvarF[ncovf]=Tvar[k];
11928: TvarFind[ncovf]=k;
11929: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is a time varying dummy covariate */
11930: Fixed[k]= 1;
11931: Dummy[k]= 0;
11932: modell[k].maintype= VTYPE;
11933: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
11934: ncovv++; /* Varying variables without age */
11935: TvarV[ncovv]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */
11936: TvarVind[ncovv]=k;/* TvarVind[1]=5 */
11937: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */
11938: Fixed[k]= 1;
11939: Dummy[k]= 1;
11940: modell[k].maintype= VTYPE;
11941: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
11942: ncovv++; /* Varying variables without age */
11943: TvarV[ncovv]=Tvar[k];
11944: TvarVind[ncovv]=k;
11945: }
11946: }else if(Tvard[k1][1] <=ncovcol+nqv){ /* Vn is fixed quanti */
11947: if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */
11948: Fixed[k]= 0; /* Fixed product */
11949: Dummy[k]= 1;
11950: modell[k].maintype= FTYPE;
11951: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
11952: ncovf++; /* Fixed variables without age */
11953: TvarF[ncovf]=Tvar[k];
11954: TvarFind[ncovf]=k;
11955: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is time varying */
11956: Fixed[k]= 1;
11957: Dummy[k]= 1;
11958: modell[k].maintype= VTYPE;
11959: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
11960: ncovv++; /* Varying variables without age */
11961: TvarV[ncovv]=Tvar[k];
11962: TvarVind[ncovv]=k;
11963: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is time varying quanti */
11964: Fixed[k]= 1;
11965: Dummy[k]= 1;
11966: modell[k].maintype= VTYPE;
11967: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
11968: ncovv++; /* Varying variables without age */
11969: TvarV[ncovv]=Tvar[k];
11970: TvarVind[ncovv]=k;
11971: ncovv++; /* Varying variables without age */
11972: TvarV[ncovv]=Tvar[k];
11973: TvarVind[ncovv]=k;
11974: }
11975: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ /* Vn is time varying dummy */
11976: if(Tvard[k1][2] <=ncovcol){
11977: Fixed[k]= 1;
11978: Dummy[k]= 1;
11979: modell[k].maintype= VTYPE;
11980: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
11981: ncovv++; /* Varying variables without age */
11982: TvarV[ncovv]=Tvar[k];
11983: TvarVind[ncovv]=k;
11984: }else if(Tvard[k1][2] <=ncovcol+nqv){
11985: Fixed[k]= 1;
11986: Dummy[k]= 1;
11987: modell[k].maintype= VTYPE;
11988: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
11989: ncovv++; /* Varying variables without age */
11990: TvarV[ncovv]=Tvar[k];
11991: TvarVind[ncovv]=k;
11992: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
11993: Fixed[k]= 1;
11994: Dummy[k]= 0;
11995: modell[k].maintype= VTYPE;
11996: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
11997: ncovv++; /* Varying variables without age */
11998: TvarV[ncovv]=Tvar[k];
11999: TvarVind[ncovv]=k;
12000: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
12001: Fixed[k]= 1;
12002: Dummy[k]= 1;
12003: modell[k].maintype= VTYPE;
12004: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
12005: ncovv++; /* Varying variables without age */
12006: TvarV[ncovv]=Tvar[k];
12007: TvarVind[ncovv]=k;
12008: }
12009: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ /* Vn is time varying quanti */
12010: if(Tvard[k1][2] <=ncovcol){
12011: Fixed[k]= 1;
12012: Dummy[k]= 1;
12013: modell[k].maintype= VTYPE;
12014: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
12015: ncovv++; /* Varying variables without age */
12016: TvarV[ncovv]=Tvar[k];
12017: TvarVind[ncovv]=k;
12018: }else if(Tvard[k1][2] <=ncovcol+nqv){
12019: Fixed[k]= 1;
12020: Dummy[k]= 1;
12021: modell[k].maintype= VTYPE;
12022: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
12023: ncovv++; /* Varying variables without age */
12024: TvarV[ncovv]=Tvar[k];
12025: TvarVind[ncovv]=k;
12026: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
12027: Fixed[k]= 1;
12028: Dummy[k]= 1;
12029: modell[k].maintype= VTYPE;
12030: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
12031: ncovv++; /* Varying variables without age */
12032: TvarV[ncovv]=Tvar[k];
12033: TvarVind[ncovv]=k;
12034: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
12035: Fixed[k]= 1;
12036: Dummy[k]= 1;
12037: modell[k].maintype= VTYPE;
12038: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
12039: ncovv++; /* Varying variables without age */
12040: TvarV[ncovv]=Tvar[k];
12041: TvarVind[ncovv]=k;
12042: }
12043: }else{
12044: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12045: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12046: } /*end k1*/
12047: }
12048: }else if(Typevar[k] == 3){ /* product Vn * Vm with age, V1+V3+age*V1+age*V3+V1*V3 looking at V1*V3, Typevar={0, 0, 1, 1, 2}, k=5, V1 is fixed, V3 is timevary, V5 is a product */
1.339 brouard 12049: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
1.349 brouard 12050: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age*/
12051: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
12052: k1=Tposprod[k]; /* Position in the products of product k, Tposprod={0, 0, 0, 0, 1, 1} k1=1 first product but second time varying because of V3 */
12053: ncova++;
12054: TvarA[ncova]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */
12055: TvarAind[ncova]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
12056: ncova++;
12057: TvarA[ncova]=Tvard[k1][2]; /* TvarVV[3]=V3 */
12058: TvarAind[ncova]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
1.339 brouard 12059:
1.349 brouard 12060: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
12061: /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
12062: if( FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){
12063: ncovta++;
12064: TvarAVVA[ncovta]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12065: TvarAVVAind[ncovta]=k;
12066: ncovta++;
12067: TvarAVVA[ncovta]=Tvard[k1][2]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12068: TvarAVVAind[ncovta]=k;
12069: }else{
12070: ncovva++; /* HERY reached */
12071: TvarVVA[ncovva]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12072: TvarVVAind[ncovva]=k;
12073: ncovva++;
12074: TvarVVA[ncovva]=Tvard[k1][2]; /* */
12075: TvarVVAind[ncovva]=k;
12076: ncovta++;
12077: TvarAVVA[ncovta]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12078: TvarAVVAind[ncovta]=k;
12079: ncovta++;
12080: TvarAVVA[ncovta]=Tvard[k1][2]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12081: TvarAVVAind[ncovta]=k;
12082: }
1.339 brouard 12083: if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */
12084: if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */
1.349 brouard 12085: Fixed[k]= 2;
12086: Dummy[k]= 2;
1.240 brouard 12087: modell[k].maintype= FTYPE;
12088: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
1.349 brouard 12089: /* TvarF[ncova]=Tvar[k]; /\* Problem to solve *\/ */
12090: /* TvarFind[ncova]=k; */
1.339 brouard 12091: }else if(Tvard[k1][2] <=ncovcol+nqv){ /* Vm is quanti fixed */
1.349 brouard 12092: Fixed[k]= 2; /* Fixed product */
12093: Dummy[k]= 3;
1.240 brouard 12094: modell[k].maintype= FTYPE;
12095: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
1.349 brouard 12096: /* TvarF[ncova]=Tvar[k]; */
12097: /* TvarFind[ncova]=k; */
1.339 brouard 12098: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is a time varying dummy covariate */
1.349 brouard 12099: Fixed[k]= 3;
12100: Dummy[k]= 2;
1.240 brouard 12101: modell[k].maintype= VTYPE;
12102: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
1.349 brouard 12103: TvarV[ncova]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */
12104: TvarVind[ncova]=k;/* TvarVind[1]=5 */
1.339 brouard 12105: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */
1.349 brouard 12106: Fixed[k]= 3;
12107: Dummy[k]= 3;
1.240 brouard 12108: modell[k].maintype= VTYPE;
12109: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
1.349 brouard 12110: /* ncovv++; /\* Varying variables without age *\/ */
12111: /* TvarV[ncovv]=Tvar[k]; */
12112: /* TvarVind[ncovv]=k; */
1.240 brouard 12113: }
1.339 brouard 12114: }else if(Tvard[k1][1] <=ncovcol+nqv){ /* Vn is fixed quanti */
12115: if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */
1.349 brouard 12116: Fixed[k]= 2; /* Fixed product */
12117: Dummy[k]= 2;
1.240 brouard 12118: modell[k].maintype= FTYPE;
12119: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
1.349 brouard 12120: /* ncova++; /\* Fixed variables with age *\/ */
12121: /* TvarF[ncovf]=Tvar[k]; */
12122: /* TvarFind[ncovf]=k; */
1.339 brouard 12123: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is time varying */
1.349 brouard 12124: Fixed[k]= 2;
12125: Dummy[k]= 3;
1.240 brouard 12126: modell[k].maintype= VTYPE;
12127: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
1.349 brouard 12128: /* ncova++; /\* Varying variables with age *\/ */
12129: /* TvarV[ncova]=Tvar[k]; */
12130: /* TvarVind[ncova]=k; */
1.339 brouard 12131: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is time varying quanti */
1.349 brouard 12132: Fixed[k]= 3;
12133: Dummy[k]= 2;
1.240 brouard 12134: modell[k].maintype= VTYPE;
12135: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
1.349 brouard 12136: ncova++; /* Varying variables without age */
12137: TvarV[ncova]=Tvar[k];
12138: TvarVind[ncova]=k;
12139: /* ncova++; /\* Varying variables without age *\/ */
12140: /* TvarV[ncova]=Tvar[k]; */
12141: /* TvarVind[ncova]=k; */
1.240 brouard 12142: }
1.339 brouard 12143: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ /* Vn is time varying dummy */
1.240 brouard 12144: if(Tvard[k1][2] <=ncovcol){
1.349 brouard 12145: Fixed[k]= 2;
12146: Dummy[k]= 2;
1.240 brouard 12147: modell[k].maintype= VTYPE;
12148: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
1.349 brouard 12149: /* ncova++; /\* Varying variables with age *\/ */
12150: /* TvarV[ncova]=Tvar[k]; */
12151: /* TvarVind[ncova]=k; */
1.240 brouard 12152: }else if(Tvard[k1][2] <=ncovcol+nqv){
1.349 brouard 12153: Fixed[k]= 2;
12154: Dummy[k]= 3;
1.240 brouard 12155: modell[k].maintype= VTYPE;
12156: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
1.349 brouard 12157: /* ncova++; /\* Varying variables with age *\/ */
12158: /* TvarV[ncova]=Tvar[k]; */
12159: /* TvarVind[ncova]=k; */
1.240 brouard 12160: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
1.349 brouard 12161: Fixed[k]= 3;
12162: Dummy[k]= 2;
1.240 brouard 12163: modell[k].maintype= VTYPE;
12164: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
1.349 brouard 12165: /* ncova++; /\* Varying variables with age *\/ */
12166: /* TvarV[ncova]=Tvar[k]; */
12167: /* TvarVind[ncova]=k; */
1.240 brouard 12168: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
1.349 brouard 12169: Fixed[k]= 3;
12170: Dummy[k]= 3;
1.240 brouard 12171: modell[k].maintype= VTYPE;
12172: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
1.349 brouard 12173: /* ncova++; /\* Varying variables with age *\/ */
12174: /* TvarV[ncova]=Tvar[k]; */
12175: /* TvarVind[ncova]=k; */
1.240 brouard 12176: }
1.339 brouard 12177: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ /* Vn is time varying quanti */
1.240 brouard 12178: if(Tvard[k1][2] <=ncovcol){
1.349 brouard 12179: Fixed[k]= 2;
12180: Dummy[k]= 2;
1.240 brouard 12181: modell[k].maintype= VTYPE;
12182: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
1.349 brouard 12183: /* ncova++; /\* Varying variables with age *\/ */
12184: /* TvarV[ncova]=Tvar[k]; */
12185: /* TvarVind[ncova]=k; */
1.240 brouard 12186: }else if(Tvard[k1][2] <=ncovcol+nqv){
1.349 brouard 12187: Fixed[k]= 2;
12188: Dummy[k]= 3;
1.240 brouard 12189: modell[k].maintype= VTYPE;
12190: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
1.349 brouard 12191: /* ncova++; /\* Varying variables with age *\/ */
12192: /* TvarV[ncova]=Tvar[k]; */
12193: /* TvarVind[ncova]=k; */
1.240 brouard 12194: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
1.349 brouard 12195: Fixed[k]= 3;
12196: Dummy[k]= 2;
1.240 brouard 12197: modell[k].maintype= VTYPE;
12198: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
1.349 brouard 12199: /* ncova++; /\* Varying variables with age *\/ */
12200: /* TvarV[ncova]=Tvar[k]; */
12201: /* TvarVind[ncova]=k; */
1.240 brouard 12202: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
1.349 brouard 12203: Fixed[k]= 3;
12204: Dummy[k]= 3;
1.240 brouard 12205: modell[k].maintype= VTYPE;
12206: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
1.349 brouard 12207: /* ncova++; /\* Varying variables with age *\/ */
12208: /* TvarV[ncova]=Tvar[k]; */
12209: /* TvarVind[ncova]=k; */
1.240 brouard 12210: }
1.227 brouard 12211: }else{
1.240 brouard 12212: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12213: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12214: } /*end k1*/
1.349 brouard 12215: } else{
1.226 brouard 12216: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
12217: 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 12218: }
1.342 brouard 12219: /* 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]); */
12220: /* printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype); */
1.227 brouard 12221: 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]);
12222: }
1.349 brouard 12223: ncovvta=ncovva;
1.227 brouard 12224: /* Searching for doublons in the model */
12225: for(k1=1; k1<= cptcovt;k1++){
12226: for(k2=1; k2 <k1;k2++){
1.285 brouard 12227: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
12228: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 12229: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
12230: if(Tvar[k1]==Tvar[k2]){
1.338 brouard 12231: 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]);
12232: 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 12233: return(1);
12234: }
12235: }else if (Typevar[k1] ==2){
12236: k3=Tposprod[k1];
12237: k4=Tposprod[k2];
12238: 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 12239: 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]]);
12240: 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 12241: return(1);
12242: }
12243: }
1.227 brouard 12244: }
12245: }
1.225 brouard 12246: }
12247: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
12248: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 12249: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
12250: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.349 brouard 12251:
12252: free_imatrix(existcomb,1,NCOVMAX,1,NCOVMAX);
1.137 brouard 12253: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 12254: /*endread:*/
1.225 brouard 12255: printf("Exiting decodemodel: ");
12256: return (1);
1.136 brouard 12257: }
12258:
1.169 brouard 12259: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 12260: {/* Check ages at death */
1.136 brouard 12261: int i, m;
1.218 brouard 12262: int firstone=0;
12263:
1.136 brouard 12264: for (i=1; i<=imx; i++) {
12265: for(m=2; (m<= maxwav); m++) {
12266: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
12267: anint[m][i]=9999;
1.216 brouard 12268: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
12269: s[m][i]=-1;
1.136 brouard 12270: }
12271: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 12272: *nberr = *nberr + 1;
1.218 brouard 12273: if(firstone == 0){
12274: firstone=1;
1.260 brouard 12275: 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 12276: }
1.262 brouard 12277: 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 12278: s[m][i]=-1; /* Droping the death status */
1.136 brouard 12279: }
12280: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 12281: (*nberr)++;
1.259 brouard 12282: 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 12283: 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 12284: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 12285: }
12286: }
12287: }
12288:
12289: for (i=1; i<=imx; i++) {
12290: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
12291: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 12292: 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 12293: if (s[m][i] >= nlstate+1) {
1.169 brouard 12294: if(agedc[i]>0){
12295: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 12296: agev[m][i]=agedc[i];
1.214 brouard 12297: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 12298: }else {
1.136 brouard 12299: if ((int)andc[i]!=9999){
12300: nbwarn++;
12301: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
12302: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
12303: agev[m][i]=-1;
12304: }
12305: }
1.169 brouard 12306: } /* agedc > 0 */
1.214 brouard 12307: } /* end if */
1.136 brouard 12308: else if(s[m][i] !=9){ /* Standard case, age in fractional
12309: years but with the precision of a month */
12310: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
12311: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
12312: agev[m][i]=1;
12313: else if(agev[m][i] < *agemin){
12314: *agemin=agev[m][i];
12315: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
12316: }
12317: else if(agev[m][i] >*agemax){
12318: *agemax=agev[m][i];
1.156 brouard 12319: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 12320: }
12321: /*agev[m][i]=anint[m][i]-annais[i];*/
12322: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 12323: } /* en if 9*/
1.136 brouard 12324: else { /* =9 */
1.214 brouard 12325: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 12326: agev[m][i]=1;
12327: s[m][i]=-1;
12328: }
12329: }
1.214 brouard 12330: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 12331: agev[m][i]=1;
1.214 brouard 12332: else{
12333: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
12334: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
12335: agev[m][i]=0;
12336: }
12337: } /* End for lastpass */
12338: }
1.136 brouard 12339:
12340: for (i=1; i<=imx; i++) {
12341: for(m=firstpass; (m<=lastpass); m++){
12342: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 12343: (*nberr)++;
1.136 brouard 12344: 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);
12345: 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);
12346: return 1;
12347: }
12348: }
12349: }
12350:
12351: /*for (i=1; i<=imx; i++){
12352: for (m=firstpass; (m<lastpass); m++){
12353: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
12354: }
12355:
12356: }*/
12357:
12358:
1.139 brouard 12359: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
12360: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 12361:
12362: return (0);
1.164 brouard 12363: /* endread:*/
1.136 brouard 12364: printf("Exiting calandcheckages: ");
12365: return (1);
12366: }
12367:
1.172 brouard 12368: #if defined(_MSC_VER)
12369: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
12370: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
12371: //#include "stdafx.h"
12372: //#include <stdio.h>
12373: //#include <tchar.h>
12374: //#include <windows.h>
12375: //#include <iostream>
12376: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
12377:
12378: LPFN_ISWOW64PROCESS fnIsWow64Process;
12379:
12380: BOOL IsWow64()
12381: {
12382: BOOL bIsWow64 = FALSE;
12383:
12384: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
12385: // (HANDLE, PBOOL);
12386:
12387: //LPFN_ISWOW64PROCESS fnIsWow64Process;
12388:
12389: HMODULE module = GetModuleHandle(_T("kernel32"));
12390: const char funcName[] = "IsWow64Process";
12391: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
12392: GetProcAddress(module, funcName);
12393:
12394: if (NULL != fnIsWow64Process)
12395: {
12396: if (!fnIsWow64Process(GetCurrentProcess(),
12397: &bIsWow64))
12398: //throw std::exception("Unknown error");
12399: printf("Unknown error\n");
12400: }
12401: return bIsWow64 != FALSE;
12402: }
12403: #endif
1.177 brouard 12404:
1.191 brouard 12405: void syscompilerinfo(int logged)
1.292 brouard 12406: {
12407: #include <stdint.h>
12408:
12409: /* #include "syscompilerinfo.h"*/
1.185 brouard 12410: /* command line Intel compiler 32bit windows, XP compatible:*/
12411: /* /GS /W3 /Gy
12412: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
12413: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
12414: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 12415: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
12416: */
12417: /* 64 bits */
1.185 brouard 12418: /*
12419: /GS /W3 /Gy
12420: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
12421: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
12422: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
12423: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
12424: /* Optimization are useless and O3 is slower than O2 */
12425: /*
12426: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
12427: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
12428: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
12429: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
12430: */
1.186 brouard 12431: /* Link is */ /* /OUT:"visual studio
1.185 brouard 12432: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
12433: /PDB:"visual studio
12434: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
12435: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
12436: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
12437: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
12438: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
12439: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
12440: uiAccess='false'"
12441: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
12442: /NOLOGO /TLBID:1
12443: */
1.292 brouard 12444:
12445:
1.177 brouard 12446: #if defined __INTEL_COMPILER
1.178 brouard 12447: #if defined(__GNUC__)
12448: struct utsname sysInfo; /* For Intel on Linux and OS/X */
12449: #endif
1.177 brouard 12450: #elif defined(__GNUC__)
1.179 brouard 12451: #ifndef __APPLE__
1.174 brouard 12452: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 12453: #endif
1.177 brouard 12454: struct utsname sysInfo;
1.178 brouard 12455: int cross = CROSS;
12456: if (cross){
12457: printf("Cross-");
1.191 brouard 12458: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 12459: }
1.174 brouard 12460: #endif
12461:
1.191 brouard 12462: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 12463: #if defined(__clang__)
1.191 brouard 12464: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 12465: #endif
12466: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 12467: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 12468: #endif
12469: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 12470: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 12471: #endif
12472: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 12473: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 12474: #endif
12475: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 12476: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 12477: #endif
12478: #if defined(_MSC_VER)
1.191 brouard 12479: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 12480: #endif
12481: #if defined(__PGI)
1.191 brouard 12482: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 12483: #endif
12484: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 12485: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 12486: #endif
1.191 brouard 12487: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 12488:
1.167 brouard 12489: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
12490: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
12491: // Windows (x64 and x86)
1.191 brouard 12492: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 12493: #elif __unix__ // all unices, not all compilers
12494: // Unix
1.191 brouard 12495: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 12496: #elif __linux__
12497: // linux
1.191 brouard 12498: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 12499: #elif __APPLE__
1.174 brouard 12500: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 12501: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 12502: #endif
12503:
12504: /* __MINGW32__ */
12505: /* __CYGWIN__ */
12506: /* __MINGW64__ */
12507: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
12508: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
12509: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
12510: /* _WIN64 // Defined for applications for Win64. */
12511: /* _M_X64 // Defined for compilations that target x64 processors. */
12512: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 12513:
1.167 brouard 12514: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 12515: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 12516: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 12517: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 12518: #else
1.191 brouard 12519: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 12520: #endif
12521:
1.169 brouard 12522: #if defined(__GNUC__)
12523: # if defined(__GNUC_PATCHLEVEL__)
12524: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
12525: + __GNUC_MINOR__ * 100 \
12526: + __GNUC_PATCHLEVEL__)
12527: # else
12528: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
12529: + __GNUC_MINOR__ * 100)
12530: # endif
1.174 brouard 12531: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 12532: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 12533:
12534: if (uname(&sysInfo) != -1) {
12535: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 12536: 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 12537: }
12538: else
12539: perror("uname() error");
1.179 brouard 12540: //#ifndef __INTEL_COMPILER
12541: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 12542: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 12543: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 12544: #endif
1.169 brouard 12545: #endif
1.172 brouard 12546:
1.286 brouard 12547: // void main ()
1.172 brouard 12548: // {
1.169 brouard 12549: #if defined(_MSC_VER)
1.174 brouard 12550: if (IsWow64()){
1.191 brouard 12551: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
12552: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 12553: }
12554: else{
1.191 brouard 12555: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
12556: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 12557: }
1.172 brouard 12558: // printf("\nPress Enter to continue...");
12559: // getchar();
12560: // }
12561:
1.169 brouard 12562: #endif
12563:
1.167 brouard 12564:
1.219 brouard 12565: }
1.136 brouard 12566:
1.219 brouard 12567: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 12568: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.332 brouard 12569: /* Computes the prevalence limit for each combination of the dummy covariates */
1.235 brouard 12570: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 12571: /* double ftolpl = 1.e-10; */
1.180 brouard 12572: double age, agebase, agelim;
1.203 brouard 12573: double tot;
1.180 brouard 12574:
1.202 brouard 12575: strcpy(filerespl,"PL_");
12576: strcat(filerespl,fileresu);
12577: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 12578: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
12579: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 12580: }
1.288 brouard 12581: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
12582: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 12583: pstamp(ficrespl);
1.288 brouard 12584: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 12585: fprintf(ficrespl,"#Age ");
12586: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
12587: fprintf(ficrespl,"\n");
1.180 brouard 12588:
1.219 brouard 12589: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 12590:
1.219 brouard 12591: agebase=ageminpar;
12592: agelim=agemaxpar;
1.180 brouard 12593:
1.227 brouard 12594: /* i1=pow(2,ncoveff); */
1.234 brouard 12595: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 12596: if (cptcovn < 1){i1=1;}
1.180 brouard 12597:
1.337 brouard 12598: /* for(k=1; k<=i1;k++){ /\* For each combination k of dummy covariates in the model *\/ */
1.238 brouard 12599: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 12600: k=TKresult[nres];
1.338 brouard 12601: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12602: /* if(i1 != 1 && TKresult[nres]!= k) /\* We found the combination k corresponding to the resultline value of dummies *\/ */
12603: /* continue; */
1.235 brouard 12604:
1.238 brouard 12605: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12606: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
12607: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
12608: /* k=k+1; */
12609: /* to clean */
1.332 brouard 12610: /*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*/
1.238 brouard 12611: fprintf(ficrespl,"#******");
12612: printf("#******");
12613: fprintf(ficlog,"#******");
1.337 brouard 12614: 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 12615: /* fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Here problem for varying dummy*\/ */
1.337 brouard 12616: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12617: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12618: fprintf(ficrespl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12619: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12620: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12621: }
12622: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
12623: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12624: /* fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12625: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12626: /* } */
1.238 brouard 12627: fprintf(ficrespl,"******\n");
12628: printf("******\n");
12629: fprintf(ficlog,"******\n");
12630: if(invalidvarcomb[k]){
12631: printf("\nCombination (%d) ignored because no case \n",k);
12632: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
12633: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
12634: continue;
12635: }
1.219 brouard 12636:
1.238 brouard 12637: fprintf(ficrespl,"#Age ");
1.337 brouard 12638: /* for(j=1;j<=cptcoveff;j++) { */
12639: /* fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12640: /* } */
12641: for(j=1;j<=cptcovs;j++) { /* New the quanti variable is added */
12642: fprintf(ficrespl,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12643: }
12644: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
12645: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 12646:
1.238 brouard 12647: for (age=agebase; age<=agelim; age++){
12648: /* for (age=agebase; age<=agebase; age++){ */
1.337 brouard 12649: /**< Computes the prevalence limit in each live state at age x and for covariate combination (k and) nres */
12650: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres); /* Nicely done */
1.238 brouard 12651: fprintf(ficrespl,"%.0f ",age );
1.337 brouard 12652: /* for(j=1;j<=cptcoveff;j++) */
12653: /* fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12654: for(j=1;j<=cptcovs;j++)
12655: fprintf(ficrespl,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12656: tot=0.;
12657: for(i=1; i<=nlstate;i++){
12658: tot += prlim[i][i];
12659: fprintf(ficrespl," %.5f", prlim[i][i]);
12660: }
12661: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
12662: } /* Age */
12663: /* was end of cptcod */
1.337 brouard 12664: } /* nres */
12665: /* } /\* for each combination *\/ */
1.219 brouard 12666: return 0;
1.180 brouard 12667: }
12668:
1.218 brouard 12669: 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 12670: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 12671:
12672: /* Computes the back prevalence limit for any combination of covariate values
12673: * at any age between ageminpar and agemaxpar
12674: */
1.235 brouard 12675: int i, j, k, i1, nres=0 ;
1.217 brouard 12676: /* double ftolpl = 1.e-10; */
12677: double age, agebase, agelim;
12678: double tot;
1.218 brouard 12679: /* double ***mobaverage; */
12680: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 12681:
12682: strcpy(fileresplb,"PLB_");
12683: strcat(fileresplb,fileresu);
12684: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 12685: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
12686: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 12687: }
1.288 brouard 12688: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
12689: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 12690: pstamp(ficresplb);
1.288 brouard 12691: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 12692: fprintf(ficresplb,"#Age ");
12693: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
12694: fprintf(ficresplb,"\n");
12695:
1.218 brouard 12696:
12697: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
12698:
12699: agebase=ageminpar;
12700: agelim=agemaxpar;
12701:
12702:
1.227 brouard 12703: i1=pow(2,cptcoveff);
1.218 brouard 12704: if (cptcovn < 1){i1=1;}
1.227 brouard 12705:
1.238 brouard 12706: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.338 brouard 12707: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
12708: k=TKresult[nres];
12709: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
12710: /* if(i1 != 1 && TKresult[nres]!= k) */
12711: /* continue; */
12712: /* /\*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*\/ */
1.238 brouard 12713: fprintf(ficresplb,"#******");
12714: printf("#******");
12715: fprintf(ficlog,"#******");
1.338 brouard 12716: 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) */
12717: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12718: fprintf(ficresplb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12719: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12720: }
1.338 brouard 12721: /* for(j=1;j<=cptcoveff ;j++) {/\* all covariates *\/ */
12722: /* fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12723: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12724: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12725: /* } */
12726: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
12727: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12728: /* fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12729: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12730: /* } */
1.238 brouard 12731: fprintf(ficresplb,"******\n");
12732: printf("******\n");
12733: fprintf(ficlog,"******\n");
12734: if(invalidvarcomb[k]){
12735: printf("\nCombination (%d) ignored because no cases \n",k);
12736: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
12737: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
12738: continue;
12739: }
1.218 brouard 12740:
1.238 brouard 12741: fprintf(ficresplb,"#Age ");
1.338 brouard 12742: for(j=1;j<=cptcovs;j++) {
12743: fprintf(ficresplb,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12744: }
12745: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
12746: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 12747:
12748:
1.238 brouard 12749: for (age=agebase; age<=agelim; age++){
12750: /* for (age=agebase; age<=agebase; age++){ */
12751: if(mobilavproj > 0){
12752: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
12753: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 12754: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 12755: }else if (mobilavproj == 0){
12756: 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);
12757: 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);
12758: exit(1);
12759: }else{
12760: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 12761: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 12762: /* printf("TOTOT\n"); */
12763: /* exit(1); */
1.238 brouard 12764: }
12765: fprintf(ficresplb,"%.0f ",age );
1.338 brouard 12766: for(j=1;j<=cptcovs;j++)
12767: fprintf(ficresplb,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12768: tot=0.;
12769: for(i=1; i<=nlstate;i++){
12770: tot += bprlim[i][i];
12771: fprintf(ficresplb," %.5f", bprlim[i][i]);
12772: }
12773: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
12774: } /* Age */
12775: /* was end of cptcod */
1.255 brouard 12776: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.338 brouard 12777: /* } /\* end of any combination *\/ */
1.238 brouard 12778: } /* end of nres */
1.218 brouard 12779: /* hBijx(p, bage, fage); */
12780: /* fclose(ficrespijb); */
12781:
12782: return 0;
1.217 brouard 12783: }
1.218 brouard 12784:
1.180 brouard 12785: int hPijx(double *p, int bage, int fage){
12786: /*------------- h Pij x at various ages ------------*/
1.336 brouard 12787: /* to be optimized with precov */
1.180 brouard 12788: int stepsize;
12789: int agelim;
12790: int hstepm;
12791: int nhstepm;
1.235 brouard 12792: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 12793:
12794: double agedeb;
12795: double ***p3mat;
12796:
1.337 brouard 12797: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
12798: if((ficrespij=fopen(filerespij,"w"))==NULL) {
12799: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
12800: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
12801: }
12802: printf("Computing pij: result on file '%s' \n", filerespij);
12803: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
12804:
12805: stepsize=(int) (stepm+YEARM-1)/YEARM;
12806: /*if (stepm<=24) stepsize=2;*/
12807:
12808: agelim=AGESUP;
12809: hstepm=stepsize*YEARM; /* Every year of age */
12810: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
12811:
12812: /* hstepm=1; aff par mois*/
12813: pstamp(ficrespij);
12814: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
12815: i1= pow(2,cptcoveff);
12816: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12817: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
12818: /* k=k+1; */
12819: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
12820: k=TKresult[nres];
1.338 brouard 12821: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12822: /* for(k=1; k<=i1;k++){ */
12823: /* if(i1 != 1 && TKresult[nres]!= k) */
12824: /* continue; */
12825: fprintf(ficrespij,"\n#****** ");
12826: for(j=1;j<=cptcovs;j++){
12827: fprintf(ficrespij," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12828: /* fprintf(ficrespij,"@wV%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12829: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
12830: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12831: /* fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12832: }
12833: fprintf(ficrespij,"******\n");
12834:
12835: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
12836: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
12837: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
12838:
12839: /* nhstepm=nhstepm*YEARM; aff par mois*/
12840:
12841: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12842: oldm=oldms;savm=savms;
12843: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
12844: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
12845: for(i=1; i<=nlstate;i++)
12846: for(j=1; j<=nlstate+ndeath;j++)
12847: fprintf(ficrespij," %1d-%1d",i,j);
12848: fprintf(ficrespij,"\n");
12849: for (h=0; h<=nhstepm; h++){
12850: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
12851: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.183 brouard 12852: for(i=1; i<=nlstate;i++)
12853: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 12854: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.183 brouard 12855: fprintf(ficrespij,"\n");
12856: }
1.337 brouard 12857: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12858: fprintf(ficrespij,"\n");
1.180 brouard 12859: }
1.337 brouard 12860: }
12861: /*}*/
12862: return 0;
1.180 brouard 12863: }
1.218 brouard 12864:
12865: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 12866: /*------------- h Bij x at various ages ------------*/
1.336 brouard 12867: /* To be optimized with precov */
1.217 brouard 12868: int stepsize;
1.218 brouard 12869: /* int agelim; */
12870: int ageminl;
1.217 brouard 12871: int hstepm;
12872: int nhstepm;
1.238 brouard 12873: int h, i, i1, j, k, nres;
1.218 brouard 12874:
1.217 brouard 12875: double agedeb;
12876: double ***p3mat;
1.218 brouard 12877:
12878: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
12879: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
12880: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
12881: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
12882: }
12883: printf("Computing pij back: result on file '%s' \n", filerespijb);
12884: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
12885:
12886: stepsize=(int) (stepm+YEARM-1)/YEARM;
12887: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 12888:
1.218 brouard 12889: /* agelim=AGESUP; */
1.289 brouard 12890: ageminl=AGEINF; /* was 30 */
1.218 brouard 12891: hstepm=stepsize*YEARM; /* Every year of age */
12892: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
12893:
12894: /* hstepm=1; aff par mois*/
12895: pstamp(ficrespijb);
1.255 brouard 12896: 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 12897: i1= pow(2,cptcoveff);
1.218 brouard 12898: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12899: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
12900: /* k=k+1; */
1.238 brouard 12901: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 12902: k=TKresult[nres];
1.338 brouard 12903: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12904: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
12905: /* if(i1 != 1 && TKresult[nres]!= k) */
12906: /* continue; */
12907: fprintf(ficrespijb,"\n#****** ");
12908: for(j=1;j<=cptcovs;j++){
1.338 brouard 12909: fprintf(ficrespijb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.337 brouard 12910: /* for(j=1;j<=cptcoveff;j++) */
12911: /* fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12912: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
12913: /* fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12914: }
12915: fprintf(ficrespijb,"******\n");
12916: if(invalidvarcomb[k]){ /* Is it necessary here? */
12917: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
12918: continue;
12919: }
12920:
12921: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
12922: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
12923: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
12924: 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 */
12925: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 or 28*/
12926:
12927: /* nhstepm=nhstepm*YEARM; aff par mois*/
12928:
12929: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
12930: /* and memory limitations if stepm is small */
12931:
12932: /* oldm=oldms;savm=savms; */
12933: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
12934: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);/* Bug valgrind */
12935: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
12936: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
12937: for(i=1; i<=nlstate;i++)
12938: for(j=1; j<=nlstate+ndeath;j++)
12939: fprintf(ficrespijb," %1d-%1d",i,j);
12940: fprintf(ficrespijb,"\n");
12941: for (h=0; h<=nhstepm; h++){
12942: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
12943: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
12944: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
1.217 brouard 12945: for(i=1; i<=nlstate;i++)
12946: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 12947: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);/* Bug valgrind */
1.217 brouard 12948: fprintf(ficrespijb,"\n");
1.337 brouard 12949: }
12950: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12951: fprintf(ficrespijb,"\n");
12952: } /* end age deb */
12953: /* } /\* end combination *\/ */
1.238 brouard 12954: } /* end nres */
1.218 brouard 12955: return 0;
12956: } /* hBijx */
1.217 brouard 12957:
1.180 brouard 12958:
1.136 brouard 12959: /***********************************************/
12960: /**************** Main Program *****************/
12961: /***********************************************/
12962:
12963: int main(int argc, char *argv[])
12964: {
12965: #ifdef GSL
12966: const gsl_multimin_fminimizer_type *T;
12967: size_t iteri = 0, it;
12968: int rval = GSL_CONTINUE;
12969: int status = GSL_SUCCESS;
12970: double ssval;
12971: #endif
12972: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 12973: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
12974: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 12975: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 12976: int jj, ll, li, lj, lk;
1.136 brouard 12977: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 12978: int num_filled;
1.136 brouard 12979: int itimes;
12980: int NDIM=2;
12981: int vpopbased=0;
1.235 brouard 12982: int nres=0;
1.258 brouard 12983: int endishere=0;
1.277 brouard 12984: int noffset=0;
1.274 brouard 12985: int ncurrv=0; /* Temporary variable */
12986:
1.164 brouard 12987: char ca[32], cb[32];
1.136 brouard 12988: /* FILE *fichtm; *//* Html File */
12989: /* FILE *ficgp;*/ /*Gnuplot File */
12990: struct stat info;
1.191 brouard 12991: double agedeb=0.;
1.194 brouard 12992:
12993: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 12994: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 12995:
1.165 brouard 12996: double fret;
1.191 brouard 12997: double dum=0.; /* Dummy variable */
1.136 brouard 12998: double ***p3mat;
1.218 brouard 12999: /* double ***mobaverage; */
1.319 brouard 13000: double wald;
1.164 brouard 13001:
1.351 ! brouard 13002: char line[MAXLINE], linetmp[MAXLINE];
1.197 brouard 13003: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
13004:
1.234 brouard 13005: char modeltemp[MAXLINE];
1.332 brouard 13006: char resultline[MAXLINE], resultlineori[MAXLINE];
1.230 brouard 13007:
1.136 brouard 13008: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 13009: char *tok, *val; /* pathtot */
1.334 brouard 13010: /* int firstobs=1, lastobs=10; /\* nobs = lastobs-firstobs declared globally ;*\/ */
1.195 brouard 13011: int c, h , cpt, c2;
1.191 brouard 13012: int jl=0;
13013: int i1, j1, jk, stepsize=0;
1.194 brouard 13014: int count=0;
13015:
1.164 brouard 13016: int *tab;
1.136 brouard 13017: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.296 brouard 13018: /* double anprojd, mprojd, jprojd; /\* For eventual projections *\/ */
13019: /* double anprojf, mprojf, jprojf; */
13020: /* double jintmean,mintmean,aintmean; */
13021: int prvforecast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
13022: int prvbackcast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
13023: double yrfproj= 10.0; /* Number of years of forward projections */
13024: double yrbproj= 10.0; /* Number of years of backward projections */
13025: int prevbcast=0; /* defined as global for mlikeli and mle, replacing backcast */
1.136 brouard 13026: int mobilav=0,popforecast=0;
1.191 brouard 13027: int hstepm=0, nhstepm=0;
1.136 brouard 13028: int agemortsup;
13029: float sumlpop=0.;
13030: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
13031: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
13032:
1.191 brouard 13033: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 13034: double ftolpl=FTOL;
13035: double **prlim;
1.217 brouard 13036: double **bprlim;
1.317 brouard 13037: double ***param; /* Matrix of parameters, param[i][j][k] param=ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel)
13038: state of origin, state of destination including death, for each covariate: constante, age, and V1 V2 etc. */
1.251 brouard 13039: double ***paramstart; /* Matrix of starting parameter values */
13040: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 13041: double **matcov; /* Matrix of covariance */
1.203 brouard 13042: double **hess; /* Hessian matrix */
1.136 brouard 13043: double ***delti3; /* Scale */
13044: double *delti; /* Scale */
13045: double ***eij, ***vareij;
13046: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 13047:
1.136 brouard 13048: double *epj, vepp;
1.164 brouard 13049:
1.273 brouard 13050: double dateprev1, dateprev2;
1.296 brouard 13051: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0, dateprojd=0, dateprojf=0;
13052: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0, datebackd=0, datebackf=0;
13053:
1.217 brouard 13054:
1.136 brouard 13055: double **ximort;
1.145 brouard 13056: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 13057: int *dcwave;
13058:
1.164 brouard 13059: char z[1]="c";
1.136 brouard 13060:
13061: /*char *strt;*/
13062: char strtend[80];
1.126 brouard 13063:
1.164 brouard 13064:
1.126 brouard 13065: /* setlocale (LC_ALL, ""); */
13066: /* bindtextdomain (PACKAGE, LOCALEDIR); */
13067: /* textdomain (PACKAGE); */
13068: /* setlocale (LC_CTYPE, ""); */
13069: /* setlocale (LC_MESSAGES, ""); */
13070:
13071: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 13072: rstart_time = time(NULL);
13073: /* (void) gettimeofday(&start_time,&tzp);*/
13074: start_time = *localtime(&rstart_time);
1.126 brouard 13075: curr_time=start_time;
1.157 brouard 13076: /*tml = *localtime(&start_time.tm_sec);*/
13077: /* strcpy(strstart,asctime(&tml)); */
13078: strcpy(strstart,asctime(&start_time));
1.126 brouard 13079:
13080: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 13081: /* tp.tm_sec = tp.tm_sec +86400; */
13082: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 13083: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
13084: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
13085: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 13086: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 13087: /* strt=asctime(&tmg); */
13088: /* printf("Time(after) =%s",strstart); */
13089: /* (void) time (&time_value);
13090: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
13091: * tm = *localtime(&time_value);
13092: * strstart=asctime(&tm);
13093: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
13094: */
13095:
13096: nberr=0; /* Number of errors and warnings */
13097: nbwarn=0;
1.184 brouard 13098: #ifdef WIN32
13099: _getcwd(pathcd, size);
13100: #else
1.126 brouard 13101: getcwd(pathcd, size);
1.184 brouard 13102: #endif
1.191 brouard 13103: syscompilerinfo(0);
1.196 brouard 13104: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 13105: if(argc <=1){
13106: printf("\nEnter the parameter file name: ");
1.205 brouard 13107: if(!fgets(pathr,FILENAMELENGTH,stdin)){
13108: printf("ERROR Empty parameter file name\n");
13109: goto end;
13110: }
1.126 brouard 13111: i=strlen(pathr);
13112: if(pathr[i-1]=='\n')
13113: pathr[i-1]='\0';
1.156 brouard 13114: i=strlen(pathr);
1.205 brouard 13115: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 13116: pathr[i-1]='\0';
1.205 brouard 13117: }
13118: i=strlen(pathr);
13119: if( i==0 ){
13120: printf("ERROR Empty parameter file name\n");
13121: goto end;
13122: }
13123: for (tok = pathr; tok != NULL; ){
1.126 brouard 13124: printf("Pathr |%s|\n",pathr);
13125: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
13126: printf("val= |%s| pathr=%s\n",val,pathr);
13127: strcpy (pathtot, val);
13128: if(pathr[0] == '\0') break; /* Dirty */
13129: }
13130: }
1.281 brouard 13131: else if (argc<=2){
13132: strcpy(pathtot,argv[1]);
13133: }
1.126 brouard 13134: else{
13135: strcpy(pathtot,argv[1]);
1.281 brouard 13136: strcpy(z,argv[2]);
13137: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 13138: }
13139: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
13140: /*cygwin_split_path(pathtot,path,optionfile);
13141: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
13142: /* cutv(path,optionfile,pathtot,'\\');*/
13143:
13144: /* Split argv[0], imach program to get pathimach */
13145: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
13146: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
13147: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
13148: /* strcpy(pathimach,argv[0]); */
13149: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
13150: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
13151: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 13152: #ifdef WIN32
13153: _chdir(path); /* Can be a relative path */
13154: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
13155: #else
1.126 brouard 13156: chdir(path); /* Can be a relative path */
1.184 brouard 13157: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
13158: #endif
13159: printf("Current directory %s!\n",pathcd);
1.126 brouard 13160: strcpy(command,"mkdir ");
13161: strcat(command,optionfilefiname);
13162: if((outcmd=system(command)) != 0){
1.169 brouard 13163: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 13164: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
13165: /* fclose(ficlog); */
13166: /* exit(1); */
13167: }
13168: /* if((imk=mkdir(optionfilefiname))<0){ */
13169: /* perror("mkdir"); */
13170: /* } */
13171:
13172: /*-------- arguments in the command line --------*/
13173:
1.186 brouard 13174: /* Main Log file */
1.126 brouard 13175: strcat(filelog, optionfilefiname);
13176: strcat(filelog,".log"); /* */
13177: if((ficlog=fopen(filelog,"w"))==NULL) {
13178: printf("Problem with logfile %s\n",filelog);
13179: goto end;
13180: }
13181: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 13182: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 13183: fprintf(ficlog,"\nEnter the parameter file name: \n");
13184: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
13185: path=%s \n\
13186: optionfile=%s\n\
13187: optionfilext=%s\n\
1.156 brouard 13188: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 13189:
1.197 brouard 13190: syscompilerinfo(1);
1.167 brouard 13191:
1.126 brouard 13192: printf("Local time (at start):%s",strstart);
13193: fprintf(ficlog,"Local time (at start): %s",strstart);
13194: fflush(ficlog);
13195: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 13196: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 13197:
13198: /* */
13199: strcpy(fileres,"r");
13200: strcat(fileres, optionfilefiname);
1.201 brouard 13201: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 13202: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 13203: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 13204:
1.186 brouard 13205: /* Main ---------arguments file --------*/
1.126 brouard 13206:
13207: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 13208: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
13209: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 13210: fflush(ficlog);
1.149 brouard 13211: /* goto end; */
13212: exit(70);
1.126 brouard 13213: }
13214:
13215: strcpy(filereso,"o");
1.201 brouard 13216: strcat(filereso,fileresu);
1.126 brouard 13217: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
13218: printf("Problem with Output resultfile: %s\n", filereso);
13219: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
13220: fflush(ficlog);
13221: goto end;
13222: }
1.278 brouard 13223: /*-------- Rewriting parameter file ----------*/
13224: strcpy(rfileres,"r"); /* "Rparameterfile */
13225: strcat(rfileres,optionfilefiname); /* Parameter file first name */
13226: strcat(rfileres,"."); /* */
13227: strcat(rfileres,optionfilext); /* Other files have txt extension */
13228: if((ficres =fopen(rfileres,"w"))==NULL) {
13229: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
13230: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
13231: fflush(ficlog);
13232: goto end;
13233: }
13234: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 13235:
1.278 brouard 13236:
1.126 brouard 13237: /* Reads comments: lines beginning with '#' */
13238: numlinepar=0;
1.277 brouard 13239: /* Is it a BOM UTF-8 Windows file? */
13240: /* First parameter line */
1.197 brouard 13241: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 13242: noffset=0;
13243: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
13244: {
13245: noffset=noffset+3;
13246: printf("# File is an UTF8 Bom.\n"); // 0xBF
13247: }
1.302 brouard 13248: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
13249: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
1.277 brouard 13250: {
13251: noffset=noffset+2;
13252: printf("# File is an UTF16BE BOM file\n");
13253: }
13254: else if( line[0] == 0 && line[1] == 0)
13255: {
13256: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
13257: noffset=noffset+4;
13258: printf("# File is an UTF16BE BOM file\n");
13259: }
13260: } else{
13261: ;/*printf(" Not a BOM file\n");*/
13262: }
13263:
1.197 brouard 13264: /* If line starts with a # it is a comment */
1.277 brouard 13265: if (line[noffset] == '#') {
1.197 brouard 13266: numlinepar++;
13267: fputs(line,stdout);
13268: fputs(line,ficparo);
1.278 brouard 13269: fputs(line,ficres);
1.197 brouard 13270: fputs(line,ficlog);
13271: continue;
13272: }else
13273: break;
13274: }
13275: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
13276: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
13277: if (num_filled != 5) {
13278: printf("Should be 5 parameters\n");
1.283 brouard 13279: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 13280: }
1.126 brouard 13281: numlinepar++;
1.197 brouard 13282: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 13283: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
13284: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
13285: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 13286: }
13287: /* Second parameter line */
13288: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 13289: /* while(fscanf(ficpar,"%[^\n]", line)) { */
13290: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 13291: if (line[0] == '#') {
13292: numlinepar++;
1.283 brouard 13293: printf("%s",line);
13294: fprintf(ficres,"%s",line);
13295: fprintf(ficparo,"%s",line);
13296: fprintf(ficlog,"%s",line);
1.197 brouard 13297: continue;
13298: }else
13299: break;
13300: }
1.223 brouard 13301: 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", \
13302: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
13303: if (num_filled != 11) {
13304: 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 13305: printf("but line=%s\n",line);
1.283 brouard 13306: 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");
13307: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 13308: }
1.286 brouard 13309: if( lastpass > maxwav){
13310: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
13311: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
13312: fflush(ficlog);
13313: goto end;
13314: }
13315: 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 13316: 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 13317: 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 13318: 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 13319: }
1.203 brouard 13320: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 13321: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 13322: /* Third parameter line */
13323: while(fgets(line, MAXLINE, ficpar)) {
13324: /* If line starts with a # it is a comment */
13325: if (line[0] == '#') {
13326: numlinepar++;
1.283 brouard 13327: printf("%s",line);
13328: fprintf(ficres,"%s",line);
13329: fprintf(ficparo,"%s",line);
13330: fprintf(ficlog,"%s",line);
1.197 brouard 13331: continue;
13332: }else
13333: break;
13334: }
1.351 ! brouard 13335: if((num_filled=sscanf(line,"model=%[^.\n]", model)) !=EOF){ /* Every character after model but dot and return */
! 13336: if (num_filled != 1){
! 13337: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
! 13338: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
! 13339: model[0]='\0';
! 13340: goto end;
! 13341: }else{
! 13342: trimbtab(linetmp,line); /* Trims multiple blanks in line */
! 13343: strcpy(line, linetmp);
! 13344: }
! 13345: }
! 13346: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){ /* Every character after 1+age but dot and return */
1.279 brouard 13347: if (num_filled != 1){
1.302 brouard 13348: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
13349: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
1.197 brouard 13350: model[0]='\0';
13351: goto end;
13352: }
13353: else{
13354: if (model[0]=='+'){
13355: for(i=1; i<=strlen(model);i++)
13356: modeltemp[i-1]=model[i];
1.201 brouard 13357: strcpy(model,modeltemp);
1.197 brouard 13358: }
13359: }
1.338 brouard 13360: /* printf(" model=1+age%s modeltemp= %s, model=1+age+%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 13361: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 13362: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
13363: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
13364: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 13365: }
13366: /* 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); */
13367: /* numlinepar=numlinepar+3; /\* In general *\/ */
13368: /* 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 13369: /* 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); */
13370: /* 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 13371: fflush(ficlog);
1.190 brouard 13372: /* if(model[0]=='#'|| model[0]== '\0'){ */
13373: if(model[0]=='#'){
1.279 brouard 13374: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
13375: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
13376: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 13377: if(mle != -1){
1.279 brouard 13378: 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 13379: exit(1);
13380: }
13381: }
1.126 brouard 13382: while((c=getc(ficpar))=='#' && c!= EOF){
13383: ungetc(c,ficpar);
13384: fgets(line, MAXLINE, ficpar);
13385: numlinepar++;
1.195 brouard 13386: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
13387: z[0]=line[1];
1.342 brouard 13388: }else if(line[1]=='d'){ /* For debugging individual values of covariates in ficresilk */
1.343 brouard 13389: debugILK=1;printf("DebugILK\n");
1.195 brouard 13390: }
13391: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 13392: fputs(line, stdout);
13393: //puts(line);
1.126 brouard 13394: fputs(line,ficparo);
13395: fputs(line,ficlog);
13396: }
13397: ungetc(c,ficpar);
13398:
13399:
1.290 brouard 13400: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
13401: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
13402: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
1.341 brouard 13403: /* if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /\**< Time varying covariate (dummy and quantitative)*\/ */
13404: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs); /**< Might be better */
1.136 brouard 13405: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
13406: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
13407: v1+v2*age+v2*v3 makes cptcovn = 3
13408: */
13409: if (strlen(model)>1)
1.187 brouard 13410: 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 13411: else
1.187 brouard 13412: ncovmodel=2; /* Constant and age */
1.133 brouard 13413: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
13414: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 13415: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
13416: 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);
13417: 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);
13418: fflush(stdout);
13419: fclose (ficlog);
13420: goto end;
13421: }
1.126 brouard 13422: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
13423: delti=delti3[1][1];
13424: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
13425: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 13426: /* We could also provide initial parameters values giving by simple logistic regression
13427: * only one way, that is without matrix product. We will have nlstate maximizations */
13428: /* for(i=1;i<nlstate;i++){ */
13429: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
13430: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
13431: /* } */
1.126 brouard 13432: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 13433: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
13434: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 13435: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
13436: fclose (ficparo);
13437: fclose (ficlog);
13438: goto end;
13439: exit(0);
1.220 brouard 13440: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 13441: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 13442: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
13443: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 13444: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
13445: matcov=matrix(1,npar,1,npar);
1.203 brouard 13446: hess=matrix(1,npar,1,npar);
1.220 brouard 13447: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 13448: /* Read guessed parameters */
1.126 brouard 13449: /* Reads comments: lines beginning with '#' */
13450: while((c=getc(ficpar))=='#' && c!= EOF){
13451: ungetc(c,ficpar);
13452: fgets(line, MAXLINE, ficpar);
13453: numlinepar++;
1.141 brouard 13454: fputs(line,stdout);
1.126 brouard 13455: fputs(line,ficparo);
13456: fputs(line,ficlog);
13457: }
13458: ungetc(c,ficpar);
13459:
13460: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 13461: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 13462: for(i=1; i <=nlstate; i++){
1.234 brouard 13463: j=0;
1.126 brouard 13464: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 13465: if(jj==i) continue;
13466: j++;
1.292 brouard 13467: while((c=getc(ficpar))=='#' && c!= EOF){
13468: ungetc(c,ficpar);
13469: fgets(line, MAXLINE, ficpar);
13470: numlinepar++;
13471: fputs(line,stdout);
13472: fputs(line,ficparo);
13473: fputs(line,ficlog);
13474: }
13475: ungetc(c,ficpar);
1.234 brouard 13476: fscanf(ficpar,"%1d%1d",&i1,&j1);
13477: if ((i1 != i) || (j1 != jj)){
13478: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 13479: It might be a problem of design; if ncovcol and the model are correct\n \
13480: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 13481: exit(1);
13482: }
13483: fprintf(ficparo,"%1d%1d",i1,j1);
13484: if(mle==1)
13485: printf("%1d%1d",i,jj);
13486: fprintf(ficlog,"%1d%1d",i,jj);
13487: for(k=1; k<=ncovmodel;k++){
13488: fscanf(ficpar," %lf",¶m[i][j][k]);
13489: if(mle==1){
13490: printf(" %lf",param[i][j][k]);
13491: fprintf(ficlog," %lf",param[i][j][k]);
13492: }
13493: else
13494: fprintf(ficlog," %lf",param[i][j][k]);
13495: fprintf(ficparo," %lf",param[i][j][k]);
13496: }
13497: fscanf(ficpar,"\n");
13498: numlinepar++;
13499: if(mle==1)
13500: printf("\n");
13501: fprintf(ficlog,"\n");
13502: fprintf(ficparo,"\n");
1.126 brouard 13503: }
13504: }
13505: fflush(ficlog);
1.234 brouard 13506:
1.251 brouard 13507: /* Reads parameters values */
1.126 brouard 13508: p=param[1][1];
1.251 brouard 13509: pstart=paramstart[1][1];
1.126 brouard 13510:
13511: /* Reads comments: lines beginning with '#' */
13512: while((c=getc(ficpar))=='#' && c!= EOF){
13513: ungetc(c,ficpar);
13514: fgets(line, MAXLINE, ficpar);
13515: numlinepar++;
1.141 brouard 13516: fputs(line,stdout);
1.126 brouard 13517: fputs(line,ficparo);
13518: fputs(line,ficlog);
13519: }
13520: ungetc(c,ficpar);
13521:
13522: for(i=1; i <=nlstate; i++){
13523: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 13524: fscanf(ficpar,"%1d%1d",&i1,&j1);
13525: if ( (i1-i) * (j1-j) != 0){
13526: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
13527: exit(1);
13528: }
13529: printf("%1d%1d",i,j);
13530: fprintf(ficparo,"%1d%1d",i1,j1);
13531: fprintf(ficlog,"%1d%1d",i1,j1);
13532: for(k=1; k<=ncovmodel;k++){
13533: fscanf(ficpar,"%le",&delti3[i][j][k]);
13534: printf(" %le",delti3[i][j][k]);
13535: fprintf(ficparo," %le",delti3[i][j][k]);
13536: fprintf(ficlog," %le",delti3[i][j][k]);
13537: }
13538: fscanf(ficpar,"\n");
13539: numlinepar++;
13540: printf("\n");
13541: fprintf(ficparo,"\n");
13542: fprintf(ficlog,"\n");
1.126 brouard 13543: }
13544: }
13545: fflush(ficlog);
1.234 brouard 13546:
1.145 brouard 13547: /* Reads covariance matrix */
1.126 brouard 13548: delti=delti3[1][1];
1.220 brouard 13549:
13550:
1.126 brouard 13551: /* 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 13552:
1.126 brouard 13553: /* Reads comments: lines beginning with '#' */
13554: while((c=getc(ficpar))=='#' && c!= EOF){
13555: ungetc(c,ficpar);
13556: fgets(line, MAXLINE, ficpar);
13557: numlinepar++;
1.141 brouard 13558: fputs(line,stdout);
1.126 brouard 13559: fputs(line,ficparo);
13560: fputs(line,ficlog);
13561: }
13562: ungetc(c,ficpar);
1.220 brouard 13563:
1.126 brouard 13564: matcov=matrix(1,npar,1,npar);
1.203 brouard 13565: hess=matrix(1,npar,1,npar);
1.131 brouard 13566: for(i=1; i <=npar; i++)
13567: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 13568:
1.194 brouard 13569: /* Scans npar lines */
1.126 brouard 13570: for(i=1; i <=npar; i++){
1.226 brouard 13571: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 13572: if(count != 3){
1.226 brouard 13573: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 13574: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
13575: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 13576: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 13577: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
13578: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 13579: exit(1);
1.220 brouard 13580: }else{
1.226 brouard 13581: if(mle==1)
13582: printf("%1d%1d%d",i1,j1,jk);
13583: }
13584: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
13585: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 13586: for(j=1; j <=i; j++){
1.226 brouard 13587: fscanf(ficpar," %le",&matcov[i][j]);
13588: if(mle==1){
13589: printf(" %.5le",matcov[i][j]);
13590: }
13591: fprintf(ficlog," %.5le",matcov[i][j]);
13592: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 13593: }
13594: fscanf(ficpar,"\n");
13595: numlinepar++;
13596: if(mle==1)
1.220 brouard 13597: printf("\n");
1.126 brouard 13598: fprintf(ficlog,"\n");
13599: fprintf(ficparo,"\n");
13600: }
1.194 brouard 13601: /* End of read covariance matrix npar lines */
1.126 brouard 13602: for(i=1; i <=npar; i++)
13603: for(j=i+1;j<=npar;j++)
1.226 brouard 13604: matcov[i][j]=matcov[j][i];
1.126 brouard 13605:
13606: if(mle==1)
13607: printf("\n");
13608: fprintf(ficlog,"\n");
13609:
13610: fflush(ficlog);
13611:
13612: } /* End of mle != -3 */
1.218 brouard 13613:
1.186 brouard 13614: /* Main data
13615: */
1.290 brouard 13616: nobs=lastobs-firstobs+1; /* was = lastobs;*/
13617: /* num=lvector(1,n); */
13618: /* moisnais=vector(1,n); */
13619: /* annais=vector(1,n); */
13620: /* moisdc=vector(1,n); */
13621: /* andc=vector(1,n); */
13622: /* weight=vector(1,n); */
13623: /* agedc=vector(1,n); */
13624: /* cod=ivector(1,n); */
13625: /* for(i=1;i<=n;i++){ */
13626: num=lvector(firstobs,lastobs);
13627: moisnais=vector(firstobs,lastobs);
13628: annais=vector(firstobs,lastobs);
13629: moisdc=vector(firstobs,lastobs);
13630: andc=vector(firstobs,lastobs);
13631: weight=vector(firstobs,lastobs);
13632: agedc=vector(firstobs,lastobs);
13633: cod=ivector(firstobs,lastobs);
13634: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 13635: num[i]=0;
13636: moisnais[i]=0;
13637: annais[i]=0;
13638: moisdc[i]=0;
13639: andc[i]=0;
13640: agedc[i]=0;
13641: cod[i]=0;
13642: weight[i]=1.0; /* Equal weights, 1 by default */
13643: }
1.290 brouard 13644: mint=matrix(1,maxwav,firstobs,lastobs);
13645: anint=matrix(1,maxwav,firstobs,lastobs);
1.325 brouard 13646: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
1.336 brouard 13647: /* printf("BUG ncovmodel=%d NCOVMAX=%d 2**ncovmodel=%f BUG\n",ncovmodel,NCOVMAX,pow(2,ncovmodel)); */
1.126 brouard 13648: tab=ivector(1,NCOVMAX);
1.144 brouard 13649: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 13650: 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 13651:
1.136 brouard 13652: /* Reads data from file datafile */
13653: if (readdata(datafile, firstobs, lastobs, &imx)==1)
13654: goto end;
13655:
13656: /* Calculation of the number of parameters from char model */
1.234 brouard 13657: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 13658: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
13659: k=3 V4 Tvar[k=3]= 4 (from V4)
13660: k=2 V1 Tvar[k=2]= 1 (from V1)
13661: k=1 Tvar[1]=2 (from V2)
1.234 brouard 13662: */
13663:
13664: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
13665: TvarsDind=ivector(1,NCOVMAX); /* */
1.330 brouard 13666: TnsdVar=ivector(1,NCOVMAX); /* */
1.335 brouard 13667: /* for(i=1; i<=NCOVMAX;i++) TnsdVar[i]=3; */
1.234 brouard 13668: TvarsD=ivector(1,NCOVMAX); /* */
13669: TvarsQind=ivector(1,NCOVMAX); /* */
13670: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 13671: TvarF=ivector(1,NCOVMAX); /* */
13672: TvarFind=ivector(1,NCOVMAX); /* */
13673: TvarV=ivector(1,NCOVMAX); /* */
13674: TvarVind=ivector(1,NCOVMAX); /* */
13675: TvarA=ivector(1,NCOVMAX); /* */
13676: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 13677: TvarFD=ivector(1,NCOVMAX); /* */
13678: TvarFDind=ivector(1,NCOVMAX); /* */
13679: TvarFQ=ivector(1,NCOVMAX); /* */
13680: TvarFQind=ivector(1,NCOVMAX); /* */
13681: TvarVD=ivector(1,NCOVMAX); /* */
13682: TvarVDind=ivector(1,NCOVMAX); /* */
13683: TvarVQ=ivector(1,NCOVMAX); /* */
13684: TvarVQind=ivector(1,NCOVMAX); /* */
1.339 brouard 13685: TvarVV=ivector(1,NCOVMAX); /* */
13686: TvarVVind=ivector(1,NCOVMAX); /* */
1.349 brouard 13687: TvarVVA=ivector(1,NCOVMAX); /* */
13688: TvarVVAind=ivector(1,NCOVMAX); /* */
13689: TvarAVVA=ivector(1,NCOVMAX); /* */
13690: TvarAVVAind=ivector(1,NCOVMAX); /* */
1.231 brouard 13691:
1.230 brouard 13692: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 13693: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 13694: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
13695: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
13696: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.349 brouard 13697: DummyV=ivector(-1,NCOVMAX); /* 1 to 3 */
13698: FixedV=ivector(-1,NCOVMAX); /* 1 to 3 */
13699:
1.137 brouard 13700: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
13701: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
13702: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
13703: */
13704: /* For model-covariate k tells which data-covariate to use but
13705: because this model-covariate is a construction we invent a new column
13706: ncovcol + k1
13707: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
13708: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 13709: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
13710: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 13711: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
13712: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 13713: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 13714: */
1.145 brouard 13715: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
13716: 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 13717: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
13718: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.351 ! brouard 13719: Tvardk=imatrix(0,NCOVMAX,1,2);
1.145 brouard 13720: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 13721: 4 covariates (3 plus signs)
13722: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
1.328 brouard 13723: */
13724: for(i=1;i<NCOVMAX;i++)
13725: Tage[i]=0;
1.230 brouard 13726: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 13727: * individual dummy, fixed or varying:
13728: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
13729: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 13730: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
13731: * V1 df, V2 qf, V3 & V4 dv, V5 qv
13732: * Tmodelind[1]@9={9,0,3,2,}*/
13733: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
13734: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 13735: * individual quantitative, fixed or varying:
13736: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
13737: * 3, 1, 0, 0, 0, 0, 0, 0},
13738: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.349 brouard 13739:
13740: /* Probably useless zeroes */
13741: for(i=1;i<NCOVMAX;i++){
13742: DummyV[i]=0;
13743: FixedV[i]=0;
13744: }
13745:
13746: for(i=1; i <=ncovcol;i++){
13747: DummyV[i]=0;
13748: FixedV[i]=0;
13749: }
13750: for(i=ncovcol+1; i <=ncovcol+nqv;i++){
13751: DummyV[i]=1;
13752: FixedV[i]=0;
13753: }
13754: for(i=ncovcol+nqv+1; i <=ncovcol+nqv+ntv;i++){
13755: DummyV[i]=0;
13756: FixedV[i]=1;
13757: }
13758: for(i=ncovcol+nqv+ntv+1; i <=ncovcol+nqv+ntv+nqtv;i++){
13759: DummyV[i]=1;
13760: FixedV[i]=1;
13761: }
13762: for(i=1; i <=ncovcol+nqv+ntv+nqtv;i++){
13763: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",i,i,DummyV[i],i,FixedV[i]);
13764: fprintf(ficlog,"Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",i,i,DummyV[i],i,FixedV[i]);
13765: }
13766:
13767:
13768:
1.186 brouard 13769: /* Main decodemodel */
13770:
1.187 brouard 13771:
1.223 brouard 13772: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 13773: goto end;
13774:
1.137 brouard 13775: if((double)(lastobs-imx)/(double)imx > 1.10){
13776: nbwarn++;
13777: 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);
13778: 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);
13779: }
1.136 brouard 13780: /* if(mle==1){*/
1.137 brouard 13781: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
13782: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 13783: }
13784:
13785: /*-calculation of age at interview from date of interview and age at death -*/
13786: agev=matrix(1,maxwav,1,imx);
13787:
13788: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
13789: goto end;
13790:
1.126 brouard 13791:
1.136 brouard 13792: agegomp=(int)agemin;
1.290 brouard 13793: free_vector(moisnais,firstobs,lastobs);
13794: free_vector(annais,firstobs,lastobs);
1.126 brouard 13795: /* free_matrix(mint,1,maxwav,1,n);
13796: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 13797: /* free_vector(moisdc,1,n); */
13798: /* free_vector(andc,1,n); */
1.145 brouard 13799: /* */
13800:
1.126 brouard 13801: wav=ivector(1,imx);
1.214 brouard 13802: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
13803: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
13804: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
13805: 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.*/
13806: bh=imatrix(1,lastpass-firstpass+2,1,imx);
13807: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 13808:
13809: /* Concatenates waves */
1.214 brouard 13810: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
13811: Death is a valid wave (if date is known).
13812: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
13813: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
13814: and mw[mi+1][i]. dh depends on stepm.
13815: */
13816:
1.126 brouard 13817: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 13818: /* Concatenates waves */
1.145 brouard 13819:
1.290 brouard 13820: free_vector(moisdc,firstobs,lastobs);
13821: free_vector(andc,firstobs,lastobs);
1.215 brouard 13822:
1.126 brouard 13823: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
13824: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
13825: ncodemax[1]=1;
1.145 brouard 13826: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 13827: cptcoveff=0;
1.220 brouard 13828: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
1.335 brouard 13829: 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 13830: }
13831:
13832: ncovcombmax=pow(2,cptcoveff);
1.338 brouard 13833: invalidvarcomb=ivector(0, ncovcombmax);
13834: for(i=0;i<ncovcombmax;i++)
1.227 brouard 13835: invalidvarcomb[i]=0;
13836:
1.211 brouard 13837: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 13838: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 13839: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 13840:
1.200 brouard 13841: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 13842: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 13843: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 13844: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
13845: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
13846: * (currently 0 or 1) in the data.
13847: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
13848: * corresponding modality (h,j).
13849: */
13850:
1.145 brouard 13851: h=0;
13852: /*if (cptcovn > 0) */
1.126 brouard 13853: m=pow(2,cptcoveff);
13854:
1.144 brouard 13855: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 13856: * For k=4 covariates, h goes from 1 to m=2**k
13857: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
13858: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.329 brouard 13859: * h\k 1 2 3 4 * h-1\k-1 4 3 2 1
13860: *______________________________ *______________________
13861: * 1 i=1 1 i=1 1 i=1 1 i=1 1 * 0 0 0 0 0
13862: * 2 2 1 1 1 * 1 0 0 0 1
13863: * 3 i=2 1 2 1 1 * 2 0 0 1 0
13864: * 4 2 2 1 1 * 3 0 0 1 1
13865: * 5 i=3 1 i=2 1 2 1 * 4 0 1 0 0
13866: * 6 2 1 2 1 * 5 0 1 0 1
13867: * 7 i=4 1 2 2 1 * 6 0 1 1 0
13868: * 8 2 2 2 1 * 7 0 1 1 1
13869: * 9 i=5 1 i=3 1 i=2 1 2 * 8 1 0 0 0
13870: * 10 2 1 1 2 * 9 1 0 0 1
13871: * 11 i=6 1 2 1 2 * 10 1 0 1 0
13872: * 12 2 2 1 2 * 11 1 0 1 1
13873: * 13 i=7 1 i=4 1 2 2 * 12 1 1 0 0
13874: * 14 2 1 2 2 * 13 1 1 0 1
13875: * 15 i=8 1 2 2 2 * 14 1 1 1 0
13876: * 16 2 2 2 2 * 15 1 1 1 1
13877: */
1.212 brouard 13878: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 13879: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
13880: * and the value of each covariate?
13881: * V1=1, V2=1, V3=2, V4=1 ?
13882: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
13883: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
13884: * In order to get the real value in the data, we use nbcode
13885: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
13886: * We are keeping this crazy system in order to be able (in the future?)
13887: * to have more than 2 values (0 or 1) for a covariate.
13888: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
13889: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
13890: * bbbbbbbb
13891: * 76543210
13892: * h-1 00000101 (6-1=5)
1.219 brouard 13893: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 13894: * &
13895: * 1 00000001 (1)
1.219 brouard 13896: * 00000000 = 1 & ((h-1) >> (k-1))
13897: * +1= 00000001 =1
1.211 brouard 13898: *
13899: * h=14, k=3 => h'=h-1=13, k'=k-1=2
13900: * h' 1101 =2^3+2^2+0x2^1+2^0
13901: * >>k' 11
13902: * & 00000001
13903: * = 00000001
13904: * +1 = 00000010=2 = codtabm(14,3)
13905: * Reverse h=6 and m=16?
13906: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
13907: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
13908: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
13909: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
13910: * V3=decodtabm(14,3,2**4)=2
13911: * h'=13 1101 =2^3+2^2+0x2^1+2^0
13912: *(h-1) >> (j-1) 0011 =13 >> 2
13913: * &1 000000001
13914: * = 000000001
13915: * +1= 000000010 =2
13916: * 2211
13917: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
13918: * V3=2
1.220 brouard 13919: * codtabm and decodtabm are identical
1.211 brouard 13920: */
13921:
1.145 brouard 13922:
13923: free_ivector(Ndum,-1,NCOVMAX);
13924:
13925:
1.126 brouard 13926:
1.186 brouard 13927: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 13928: strcpy(optionfilegnuplot,optionfilefiname);
13929: if(mle==-3)
1.201 brouard 13930: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 13931: strcat(optionfilegnuplot,".gp");
13932:
13933: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
13934: printf("Problem with file %s",optionfilegnuplot);
13935: }
13936: else{
1.204 brouard 13937: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 13938: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 13939: //fprintf(ficgp,"set missing 'NaNq'\n");
13940: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 13941: }
13942: /* fclose(ficgp);*/
1.186 brouard 13943:
13944:
13945: /* Initialisation of --------- index.htm --------*/
1.126 brouard 13946:
13947: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
13948: if(mle==-3)
1.201 brouard 13949: strcat(optionfilehtm,"-MORT_");
1.126 brouard 13950: strcat(optionfilehtm,".htm");
13951: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 13952: printf("Problem with %s \n",optionfilehtm);
13953: exit(0);
1.126 brouard 13954: }
13955:
13956: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
13957: strcat(optionfilehtmcov,"-cov.htm");
13958: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
13959: printf("Problem with %s \n",optionfilehtmcov), exit(0);
13960: }
13961: else{
13962: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
13963: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 13964: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 13965: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
13966: }
13967:
1.335 brouard 13968: fprintf(fichtm,"<html><head>\n<meta charset=\"utf-8\"/><meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n\
13969: <title>IMaCh %s</title></head>\n\
13970: <body><font size=\"7\"><a href=http:/euroreves.ined.fr/imach>IMaCh for Interpolated Markov Chain</a> </font><br>\n\
13971: <font size=\"3\">Sponsored by Copyright (C) 2002-2015 <a href=http://www.ined.fr>INED</a>\
13972: -EUROREVES-Institut de longévité-2013-2022-Japan Society for the Promotion of Sciences 日本学術振興会 \
13973: (<a href=https://www.jsps.go.jp/english/e-grants/>Grant-in-Aid for Scientific Research 25293121</a>) - \
13974: <a href=https://software.intel.com/en-us>Intel Software 2015-2018</a></font><br> \n", optionfilehtm);
13975:
13976: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 13977: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 13978: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.337 brouard 13979: 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 13980: \n\
13981: <hr size=\"2\" color=\"#EC5E5E\">\
13982: <ul><li><h4>Parameter files</h4>\n\
13983: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
13984: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
13985: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
13986: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
13987: - Date and time at start: %s</ul>\n",\
1.335 brouard 13988: version,fullversion,optionfilehtm,optionfilehtm,title,datafile,datafile,firstpass,lastpass,stepm, weightopt, model, \
1.126 brouard 13989: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
13990: fileres,fileres,\
13991: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
13992: fflush(fichtm);
13993:
13994: strcpy(pathr,path);
13995: strcat(pathr,optionfilefiname);
1.184 brouard 13996: #ifdef WIN32
13997: _chdir(optionfilefiname); /* Move to directory named optionfile */
13998: #else
1.126 brouard 13999: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 14000: #endif
14001:
1.126 brouard 14002:
1.220 brouard 14003: /* Calculates basic frequencies. Computes observed prevalence at single age
14004: and for any valid combination of covariates
1.126 brouard 14005: and prints on file fileres'p'. */
1.251 brouard 14006: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 14007: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 14008:
14009: fprintf(fichtm,"\n");
1.286 brouard 14010: 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 14011: ftol, stepm);
14012: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
14013: ncurrv=1;
14014: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
14015: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
14016: ncurrv=i;
14017: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 14018: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 14019: ncurrv=i;
14020: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 14021: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 14022: ncurrv=i;
14023: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
14024: 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", \
14025: nlstate, ndeath, maxwav, mle, weightopt);
14026:
14027: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
14028: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
14029:
14030:
1.317 brouard 14031: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Number of (used) observations=%d <br>\n\
1.126 brouard 14032: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
14033: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 14034: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 14035: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 14036: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
14037: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
14038: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
14039: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 14040:
1.126 brouard 14041: /* For Powell, parameters are in a vector p[] starting at p[1]
14042: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
14043: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
14044:
14045: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 14046: /* For mortality only */
1.126 brouard 14047: if (mle==-3){
1.136 brouard 14048: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 14049: for(i=1;i<=NDIM;i++)
14050: for(j=1;j<=NDIM;j++)
14051: ximort[i][j]=0.;
1.186 brouard 14052: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 14053: cens=ivector(firstobs,lastobs);
14054: ageexmed=vector(firstobs,lastobs);
14055: agecens=vector(firstobs,lastobs);
14056: dcwave=ivector(firstobs,lastobs);
1.223 brouard 14057:
1.126 brouard 14058: for (i=1; i<=imx; i++){
14059: dcwave[i]=-1;
14060: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 14061: if (s[m][i]>nlstate) {
14062: dcwave[i]=m;
14063: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
14064: break;
14065: }
1.126 brouard 14066: }
1.226 brouard 14067:
1.126 brouard 14068: for (i=1; i<=imx; i++) {
14069: if (wav[i]>0){
1.226 brouard 14070: ageexmed[i]=agev[mw[1][i]][i];
14071: j=wav[i];
14072: agecens[i]=1.;
14073:
14074: if (ageexmed[i]> 1 && wav[i] > 0){
14075: agecens[i]=agev[mw[j][i]][i];
14076: cens[i]= 1;
14077: }else if (ageexmed[i]< 1)
14078: cens[i]= -1;
14079: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
14080: cens[i]=0 ;
1.126 brouard 14081: }
14082: else cens[i]=-1;
14083: }
14084:
14085: for (i=1;i<=NDIM;i++) {
14086: for (j=1;j<=NDIM;j++)
1.226 brouard 14087: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 14088: }
14089:
1.302 brouard 14090: p[1]=0.0268; p[NDIM]=0.083;
14091: /* printf("%lf %lf", p[1], p[2]); */
1.126 brouard 14092:
14093:
1.136 brouard 14094: #ifdef GSL
14095: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 14096: #else
1.126 brouard 14097: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 14098: #endif
1.201 brouard 14099: strcpy(filerespow,"POW-MORT_");
14100: strcat(filerespow,fileresu);
1.126 brouard 14101: if((ficrespow=fopen(filerespow,"w"))==NULL) {
14102: printf("Problem with resultfile: %s\n", filerespow);
14103: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
14104: }
1.136 brouard 14105: #ifdef GSL
14106: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 14107: #else
1.126 brouard 14108: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 14109: #endif
1.126 brouard 14110: /* for (i=1;i<=nlstate;i++)
14111: for(j=1;j<=nlstate+ndeath;j++)
14112: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
14113: */
14114: fprintf(ficrespow,"\n");
1.136 brouard 14115: #ifdef GSL
14116: /* gsl starts here */
14117: T = gsl_multimin_fminimizer_nmsimplex;
14118: gsl_multimin_fminimizer *sfm = NULL;
14119: gsl_vector *ss, *x;
14120: gsl_multimin_function minex_func;
14121:
14122: /* Initial vertex size vector */
14123: ss = gsl_vector_alloc (NDIM);
14124:
14125: if (ss == NULL){
14126: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
14127: }
14128: /* Set all step sizes to 1 */
14129: gsl_vector_set_all (ss, 0.001);
14130:
14131: /* Starting point */
1.126 brouard 14132:
1.136 brouard 14133: x = gsl_vector_alloc (NDIM);
14134:
14135: if (x == NULL){
14136: gsl_vector_free(ss);
14137: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
14138: }
14139:
14140: /* Initialize method and iterate */
14141: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 14142: /* gsl_vector_set(x, 0, 0.0268); */
14143: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 14144: gsl_vector_set(x, 0, p[1]);
14145: gsl_vector_set(x, 1, p[2]);
14146:
14147: minex_func.f = &gompertz_f;
14148: minex_func.n = NDIM;
14149: minex_func.params = (void *)&p; /* ??? */
14150:
14151: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
14152: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
14153:
14154: printf("Iterations beginning .....\n\n");
14155: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
14156:
14157: iteri=0;
14158: while (rval == GSL_CONTINUE){
14159: iteri++;
14160: status = gsl_multimin_fminimizer_iterate(sfm);
14161:
14162: if (status) printf("error: %s\n", gsl_strerror (status));
14163: fflush(0);
14164:
14165: if (status)
14166: break;
14167:
14168: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
14169: ssval = gsl_multimin_fminimizer_size (sfm);
14170:
14171: if (rval == GSL_SUCCESS)
14172: printf ("converged to a local maximum at\n");
14173:
14174: printf("%5d ", iteri);
14175: for (it = 0; it < NDIM; it++){
14176: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
14177: }
14178: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
14179: }
14180:
14181: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
14182:
14183: gsl_vector_free(x); /* initial values */
14184: gsl_vector_free(ss); /* inital step size */
14185: for (it=0; it<NDIM; it++){
14186: p[it+1]=gsl_vector_get(sfm->x,it);
14187: fprintf(ficrespow," %.12lf", p[it]);
14188: }
14189: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
14190: #endif
14191: #ifdef POWELL
14192: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
14193: #endif
1.126 brouard 14194: fclose(ficrespow);
14195:
1.203 brouard 14196: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 14197:
14198: for(i=1; i <=NDIM; i++)
14199: for(j=i+1;j<=NDIM;j++)
1.220 brouard 14200: matcov[i][j]=matcov[j][i];
1.126 brouard 14201:
14202: printf("\nCovariance matrix\n ");
1.203 brouard 14203: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 14204: for(i=1; i <=NDIM; i++) {
14205: for(j=1;j<=NDIM;j++){
1.220 brouard 14206: printf("%f ",matcov[i][j]);
14207: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 14208: }
1.203 brouard 14209: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 14210: }
14211:
14212: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 14213: for (i=1;i<=NDIM;i++) {
1.126 brouard 14214: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 14215: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
14216: }
1.302 brouard 14217: lsurv=vector(agegomp,AGESUP);
14218: lpop=vector(agegomp,AGESUP);
14219: tpop=vector(agegomp,AGESUP);
1.126 brouard 14220: lsurv[agegomp]=100000;
14221:
14222: for (k=agegomp;k<=AGESUP;k++) {
14223: agemortsup=k;
14224: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
14225: }
14226:
14227: for (k=agegomp;k<agemortsup;k++)
14228: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
14229:
14230: for (k=agegomp;k<agemortsup;k++){
14231: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
14232: sumlpop=sumlpop+lpop[k];
14233: }
14234:
14235: tpop[agegomp]=sumlpop;
14236: for (k=agegomp;k<(agemortsup-3);k++){
14237: /* tpop[k+1]=2;*/
14238: tpop[k+1]=tpop[k]-lpop[k];
14239: }
14240:
14241:
14242: printf("\nAge lx qx dx Lx Tx e(x)\n");
14243: for (k=agegomp;k<(agemortsup-2);k++)
14244: 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]);
14245:
14246:
14247: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 14248: ageminpar=50;
14249: agemaxpar=100;
1.194 brouard 14250: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
14251: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
14252: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14253: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
14254: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
14255: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14256: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 14257: }else{
14258: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
14259: 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 14260: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 14261: }
1.201 brouard 14262: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 14263: stepm, weightopt,\
14264: model,imx,p,matcov,agemortsup);
14265:
1.302 brouard 14266: free_vector(lsurv,agegomp,AGESUP);
14267: free_vector(lpop,agegomp,AGESUP);
14268: free_vector(tpop,agegomp,AGESUP);
1.220 brouard 14269: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 14270: free_ivector(dcwave,firstobs,lastobs);
14271: free_vector(agecens,firstobs,lastobs);
14272: free_vector(ageexmed,firstobs,lastobs);
14273: free_ivector(cens,firstobs,lastobs);
1.220 brouard 14274: #ifdef GSL
1.136 brouard 14275: #endif
1.186 brouard 14276: } /* Endof if mle==-3 mortality only */
1.205 brouard 14277: /* Standard */
14278: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
14279: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
14280: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 14281: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 14282: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
14283: for (k=1; k<=npar;k++)
14284: printf(" %d %8.5f",k,p[k]);
14285: printf("\n");
1.205 brouard 14286: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
14287: /* mlikeli uses func not funcone */
1.247 brouard 14288: /* for(i=1;i<nlstate;i++){ */
14289: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
14290: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
14291: /* } */
1.205 brouard 14292: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
14293: }
14294: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
14295: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
14296: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
14297: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
14298: }
14299: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 14300: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
14301: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
1.335 brouard 14302: /* exit(0); */
1.126 brouard 14303: for (k=1; k<=npar;k++)
14304: printf(" %d %8.5f",k,p[k]);
14305: printf("\n");
14306:
14307: /*--------- results files --------------*/
1.283 brouard 14308: /* 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 14309:
14310:
14311: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 14312: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); /* Printing model equation */
1.126 brouard 14313: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 14314:
14315: printf("#model= 1 + age ");
14316: fprintf(ficres,"#model= 1 + age ");
14317: fprintf(ficlog,"#model= 1 + age ");
14318: fprintf(fichtm,"\n<ul><li> model=1+age+%s\n \
14319: </ul>", model);
14320:
14321: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">\n");
14322: fprintf(fichtm, "<tr><th>Model=</th><th>1</th><th>+ age</th>");
14323: if(nagesqr==1){
14324: printf(" + age*age ");
14325: fprintf(ficres," + age*age ");
14326: fprintf(ficlog," + age*age ");
14327: fprintf(fichtm, "<th>+ age*age</th>");
14328: }
14329: for(j=1;j <=ncovmodel-2;j++){
14330: if(Typevar[j]==0) {
14331: printf(" + V%d ",Tvar[j]);
14332: fprintf(ficres," + V%d ",Tvar[j]);
14333: fprintf(ficlog," + V%d ",Tvar[j]);
14334: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
14335: }else if(Typevar[j]==1) {
14336: printf(" + V%d*age ",Tvar[j]);
14337: fprintf(ficres," + V%d*age ",Tvar[j]);
14338: fprintf(ficlog," + V%d*age ",Tvar[j]);
14339: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
14340: }else if(Typevar[j]==2) {
14341: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14342: fprintf(ficres," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14343: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14344: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 14345: }else if(Typevar[j]==3) { /* TO VERIFY */
14346: printf(" + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14347: fprintf(ficres," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14348: fprintf(ficlog," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14349: fprintf(fichtm, "<th>+ V%d*V%d*age</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.319 brouard 14350: }
14351: }
14352: printf("\n");
14353: fprintf(ficres,"\n");
14354: fprintf(ficlog,"\n");
14355: fprintf(fichtm, "</tr>");
14356: fprintf(fichtm, "\n");
14357:
14358:
1.126 brouard 14359: for(i=1,jk=1; i <=nlstate; i++){
14360: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 14361: if (k != i) {
1.319 brouard 14362: fprintf(fichtm, "<tr>");
1.225 brouard 14363: printf("%d%d ",i,k);
14364: fprintf(ficlog,"%d%d ",i,k);
14365: fprintf(ficres,"%1d%1d ",i,k);
1.319 brouard 14366: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 14367: for(j=1; j <=ncovmodel; j++){
14368: printf("%12.7f ",p[jk]);
14369: fprintf(ficlog,"%12.7f ",p[jk]);
14370: fprintf(ficres,"%12.7f ",p[jk]);
1.319 brouard 14371: fprintf(fichtm, "<td>%12.7f</td>",p[jk]);
1.225 brouard 14372: jk++;
14373: }
14374: printf("\n");
14375: fprintf(ficlog,"\n");
14376: fprintf(ficres,"\n");
1.319 brouard 14377: fprintf(fichtm, "</tr>\n");
1.225 brouard 14378: }
1.126 brouard 14379: }
14380: }
1.319 brouard 14381: /* fprintf(fichtm,"</tr>\n"); */
14382: fprintf(fichtm,"</table>\n");
14383: fprintf(fichtm, "\n");
14384:
1.203 brouard 14385: if(mle != 0){
14386: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 14387: ftolhess=ftol; /* Usually correct */
1.203 brouard 14388: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
14389: 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");
14390: 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 14391: 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 14392: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">");
14393: fprintf(fichtm, "\n<tr><th>Model=</th><th>1</th><th>+ age</th>");
14394: if(nagesqr==1){
14395: printf(" + age*age ");
14396: fprintf(ficres," + age*age ");
14397: fprintf(ficlog," + age*age ");
14398: fprintf(fichtm, "<th>+ age*age</th>");
14399: }
14400: for(j=1;j <=ncovmodel-2;j++){
14401: if(Typevar[j]==0) {
14402: printf(" + V%d ",Tvar[j]);
14403: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
14404: }else if(Typevar[j]==1) {
14405: printf(" + V%d*age ",Tvar[j]);
14406: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
14407: }else if(Typevar[j]==2) {
14408: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 14409: }else if(Typevar[j]==3) { /* TO VERIFY */
14410: fprintf(fichtm, "<th>+ V%d*V%d*age</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.319 brouard 14411: }
14412: }
14413: fprintf(fichtm, "</tr>\n");
14414:
1.203 brouard 14415: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 14416: for(k=1; k <=(nlstate+ndeath); k++){
14417: if (k != i) {
1.319 brouard 14418: fprintf(fichtm, "<tr valign=top>");
1.225 brouard 14419: printf("%d%d ",i,k);
14420: fprintf(ficlog,"%d%d ",i,k);
1.319 brouard 14421: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 14422: for(j=1; j <=ncovmodel; j++){
1.319 brouard 14423: wald=p[jk]/sqrt(matcov[jk][jk]);
1.324 brouard 14424: 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]));
14425: 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 14426: if(fabs(wald) > 1.96){
1.321 brouard 14427: fprintf(fichtm, "<td><b>%12.7f</b></br> (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
1.319 brouard 14428: }else{
14429: fprintf(fichtm, "<td>%12.7f (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
14430: }
1.324 brouard 14431: fprintf(fichtm,"W=%8.3f</br>",wald);
1.319 brouard 14432: 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 14433: jk++;
14434: }
14435: printf("\n");
14436: fprintf(ficlog,"\n");
1.319 brouard 14437: fprintf(fichtm, "</tr>\n");
1.225 brouard 14438: }
14439: }
1.193 brouard 14440: }
1.203 brouard 14441: } /* end of hesscov and Wald tests */
1.319 brouard 14442: fprintf(fichtm,"</table>\n");
1.225 brouard 14443:
1.203 brouard 14444: /* */
1.126 brouard 14445: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
14446: printf("# Scales (for hessian or gradient estimation)\n");
14447: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
14448: for(i=1,jk=1; i <=nlstate; i++){
14449: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 14450: if (j!=i) {
14451: fprintf(ficres,"%1d%1d",i,j);
14452: printf("%1d%1d",i,j);
14453: fprintf(ficlog,"%1d%1d",i,j);
14454: for(k=1; k<=ncovmodel;k++){
14455: printf(" %.5e",delti[jk]);
14456: fprintf(ficlog," %.5e",delti[jk]);
14457: fprintf(ficres," %.5e",delti[jk]);
14458: jk++;
14459: }
14460: printf("\n");
14461: fprintf(ficlog,"\n");
14462: fprintf(ficres,"\n");
14463: }
1.126 brouard 14464: }
14465: }
14466:
14467: fprintf(ficres,"# Covariance matrix \n# 121 Var(a12)\n# 122 Cov(b12,a12) Var(b12)\n# ...\n# 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n");
1.349 brouard 14468: if(mle >= 1) /* Too big for the screen */
1.126 brouard 14469: 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");
14470: 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");
14471: /* # 121 Var(a12)\n\ */
14472: /* # 122 Cov(b12,a12) Var(b12)\n\ */
14473: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
14474: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
14475: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
14476: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
14477: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
14478: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
14479:
14480:
14481: /* Just to have a covariance matrix which will be more understandable
14482: even is we still don't want to manage dictionary of variables
14483: */
14484: for(itimes=1;itimes<=2;itimes++){
14485: jj=0;
14486: for(i=1; i <=nlstate; i++){
1.225 brouard 14487: for(j=1; j <=nlstate+ndeath; j++){
14488: if(j==i) continue;
14489: for(k=1; k<=ncovmodel;k++){
14490: jj++;
14491: ca[0]= k+'a'-1;ca[1]='\0';
14492: if(itimes==1){
14493: if(mle>=1)
14494: printf("#%1d%1d%d",i,j,k);
14495: fprintf(ficlog,"#%1d%1d%d",i,j,k);
14496: fprintf(ficres,"#%1d%1d%d",i,j,k);
14497: }else{
14498: if(mle>=1)
14499: printf("%1d%1d%d",i,j,k);
14500: fprintf(ficlog,"%1d%1d%d",i,j,k);
14501: fprintf(ficres,"%1d%1d%d",i,j,k);
14502: }
14503: ll=0;
14504: for(li=1;li <=nlstate; li++){
14505: for(lj=1;lj <=nlstate+ndeath; lj++){
14506: if(lj==li) continue;
14507: for(lk=1;lk<=ncovmodel;lk++){
14508: ll++;
14509: if(ll<=jj){
14510: cb[0]= lk +'a'-1;cb[1]='\0';
14511: if(ll<jj){
14512: if(itimes==1){
14513: if(mle>=1)
14514: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
14515: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
14516: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
14517: }else{
14518: if(mle>=1)
14519: printf(" %.5e",matcov[jj][ll]);
14520: fprintf(ficlog," %.5e",matcov[jj][ll]);
14521: fprintf(ficres," %.5e",matcov[jj][ll]);
14522: }
14523: }else{
14524: if(itimes==1){
14525: if(mle>=1)
14526: printf(" Var(%s%1d%1d)",ca,i,j);
14527: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
14528: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
14529: }else{
14530: if(mle>=1)
14531: printf(" %.7e",matcov[jj][ll]);
14532: fprintf(ficlog," %.7e",matcov[jj][ll]);
14533: fprintf(ficres," %.7e",matcov[jj][ll]);
14534: }
14535: }
14536: }
14537: } /* end lk */
14538: } /* end lj */
14539: } /* end li */
14540: if(mle>=1)
14541: printf("\n");
14542: fprintf(ficlog,"\n");
14543: fprintf(ficres,"\n");
14544: numlinepar++;
14545: } /* end k*/
14546: } /*end j */
1.126 brouard 14547: } /* end i */
14548: } /* end itimes */
14549:
14550: fflush(ficlog);
14551: fflush(ficres);
1.225 brouard 14552: while(fgets(line, MAXLINE, ficpar)) {
14553: /* If line starts with a # it is a comment */
14554: if (line[0] == '#') {
14555: numlinepar++;
14556: fputs(line,stdout);
14557: fputs(line,ficparo);
14558: fputs(line,ficlog);
1.299 brouard 14559: fputs(line,ficres);
1.225 brouard 14560: continue;
14561: }else
14562: break;
14563: }
14564:
1.209 brouard 14565: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
14566: /* ungetc(c,ficpar); */
14567: /* fgets(line, MAXLINE, ficpar); */
14568: /* fputs(line,stdout); */
14569: /* fputs(line,ficparo); */
14570: /* } */
14571: /* ungetc(c,ficpar); */
1.126 brouard 14572:
14573: estepm=0;
1.209 brouard 14574: 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 14575:
14576: if (num_filled != 6) {
14577: 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);
14578: 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);
14579: goto end;
14580: }
14581: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
14582: }
14583: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
14584: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
14585:
1.209 brouard 14586: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 14587: if (estepm==0 || estepm < stepm) estepm=stepm;
14588: if (fage <= 2) {
14589: bage = ageminpar;
14590: fage = agemaxpar;
14591: }
14592:
14593: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 14594: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
14595: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 14596:
1.186 brouard 14597: /* Other stuffs, more or less useful */
1.254 brouard 14598: while(fgets(line, MAXLINE, ficpar)) {
14599: /* If line starts with a # it is a comment */
14600: if (line[0] == '#') {
14601: numlinepar++;
14602: fputs(line,stdout);
14603: fputs(line,ficparo);
14604: fputs(line,ficlog);
1.299 brouard 14605: fputs(line,ficres);
1.254 brouard 14606: continue;
14607: }else
14608: break;
14609: }
14610:
14611: 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){
14612:
14613: if (num_filled != 7) {
14614: 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);
14615: 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);
14616: goto end;
14617: }
14618: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
14619: 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);
14620: 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);
14621: 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 14622: }
1.254 brouard 14623:
14624: while(fgets(line, MAXLINE, ficpar)) {
14625: /* If line starts with a # it is a comment */
14626: if (line[0] == '#') {
14627: numlinepar++;
14628: fputs(line,stdout);
14629: fputs(line,ficparo);
14630: fputs(line,ficlog);
1.299 brouard 14631: fputs(line,ficres);
1.254 brouard 14632: continue;
14633: }else
14634: break;
1.126 brouard 14635: }
14636:
14637:
14638: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
14639: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
14640:
1.254 brouard 14641: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
14642: if (num_filled != 1) {
14643: 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);
14644: 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);
14645: goto end;
14646: }
14647: printf("pop_based=%d\n",popbased);
14648: fprintf(ficlog,"pop_based=%d\n",popbased);
14649: fprintf(ficparo,"pop_based=%d\n",popbased);
14650: fprintf(ficres,"pop_based=%d\n",popbased);
14651: }
14652:
1.258 brouard 14653: /* Results */
1.332 brouard 14654: /* Value of covariate in each resultine will be compututed (if product) and sorted according to model rank */
14655: /* It is precov[] because we need the varying age in order to compute the real cov[] of the model equation */
14656: precov=matrix(1,MAXRESULTLINESPONE,1,NCOVMAX+1);
1.307 brouard 14657: endishere=0;
1.258 brouard 14658: nresult=0;
1.308 brouard 14659: parameterline=0;
1.258 brouard 14660: do{
14661: if(!fgets(line, MAXLINE, ficpar)){
14662: endishere=1;
1.308 brouard 14663: parameterline=15;
1.258 brouard 14664: }else if (line[0] == '#') {
14665: /* If line starts with a # it is a comment */
1.254 brouard 14666: numlinepar++;
14667: fputs(line,stdout);
14668: fputs(line,ficparo);
14669: fputs(line,ficlog);
1.299 brouard 14670: fputs(line,ficres);
1.254 brouard 14671: continue;
1.258 brouard 14672: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
14673: parameterline=11;
1.296 brouard 14674: else if(sscanf(line,"prevbackcast=%[^\n]\n",modeltemp))
1.258 brouard 14675: parameterline=12;
1.307 brouard 14676: else if(sscanf(line,"result:%[^\n]\n",modeltemp)){
1.258 brouard 14677: parameterline=13;
1.307 brouard 14678: }
1.258 brouard 14679: else{
14680: parameterline=14;
1.254 brouard 14681: }
1.308 brouard 14682: switch (parameterline){ /* =0 only if only comments */
1.258 brouard 14683: case 11:
1.296 brouard 14684: 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)){
14685: 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 14686: 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);
14687: 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);
14688: 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);
14689: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 14690: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
14691: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
1.296 brouard 14692: prvforecast = 1;
14693: }
14694: else if((num_filled=sscanf(line,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",&prevfcast,&yrfproj,&mobilavproj)) !=EOF){/* && (num_filled == 3))*/
1.313 brouard 14695: printf("prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
14696: fprintf(ficlog,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
14697: fprintf(ficres,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
1.296 brouard 14698: prvforecast = 2;
14699: }
14700: else {
14701: 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);
14702: 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);
14703: goto end;
1.258 brouard 14704: }
1.254 brouard 14705: break;
1.258 brouard 14706: case 12:
1.296 brouard 14707: 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)){
14708: 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);
14709: 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);
14710: 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);
14711: 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);
14712: /* day and month of back2 are not used but only year anback2.*/
1.273 brouard 14713: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
14714: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.296 brouard 14715: prvbackcast = 1;
14716: }
14717: else if((num_filled=sscanf(line,"prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",&prevbcast,&yrbproj,&mobilavproj)) ==3){/* && (num_filled == 3))*/
1.313 brouard 14718: printf("prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
14719: fprintf(ficlog,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
14720: fprintf(ficres,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
1.296 brouard 14721: prvbackcast = 2;
14722: }
14723: else {
14724: 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);
14725: 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);
14726: goto end;
1.258 brouard 14727: }
1.230 brouard 14728: break;
1.258 brouard 14729: case 13:
1.332 brouard 14730: num_filled=sscanf(line,"result:%[^\n]\n",resultlineori);
1.307 brouard 14731: nresult++; /* Sum of resultlines */
1.342 brouard 14732: /* printf("Result %d: result:%s\n",nresult, resultlineori); */
1.332 brouard 14733: /* removefirstspace(&resultlineori); */
14734:
14735: if(strstr(resultlineori,"v") !=0){
14736: printf("Error. 'v' must be in upper case 'V' result: %s ",resultlineori);
14737: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultlineori);fflush(ficlog);
14738: return 1;
14739: }
14740: trimbb(resultline, resultlineori); /* Suppressing double blank in the resultline */
1.342 brouard 14741: /* printf("Decoderesult resultline=\"%s\" resultlineori=\"%s\"\n", resultline, resultlineori); */
1.318 brouard 14742: if(nresult > MAXRESULTLINESPONE-1){
14743: 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);
14744: 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 14745: goto end;
14746: }
1.332 brouard 14747:
1.310 brouard 14748: if(!decoderesult(resultline, nresult)){ /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
1.314 brouard 14749: fprintf(ficparo,"result: %s\n",resultline);
14750: fprintf(ficres,"result: %s\n",resultline);
14751: fprintf(ficlog,"result: %s\n",resultline);
1.310 brouard 14752: } else
14753: goto end;
1.307 brouard 14754: break;
14755: case 14:
14756: printf("Error: Unknown command '%s'\n",line);
14757: fprintf(ficlog,"Error: Unknown command '%s'\n",line);
1.314 brouard 14758: if(line[0] == ' ' || line[0] == '\n'){
14759: printf("It should not be an empty line '%s'\n",line);
14760: fprintf(ficlog,"It should not be an empty line '%s'\n",line);
14761: }
1.307 brouard 14762: if(ncovmodel >=2 && nresult==0 ){
14763: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
14764: fprintf(ficlog,"ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 14765: }
1.307 brouard 14766: /* goto end; */
14767: break;
1.308 brouard 14768: case 15:
14769: printf("End of resultlines.\n");
14770: fprintf(ficlog,"End of resultlines.\n");
14771: break;
14772: default: /* parameterline =0 */
1.307 brouard 14773: nresult=1;
14774: decoderesult(".",nresult ); /* No covariate */
1.258 brouard 14775: } /* End switch parameterline */
14776: }while(endishere==0); /* End do */
1.126 brouard 14777:
1.230 brouard 14778: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 14779: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 14780:
14781: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 14782: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 14783: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 14784: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14785: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 14786: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 14787: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14788: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 14789: }else{
1.270 brouard 14790: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
1.296 brouard 14791: /* It seems that anprojd which is computed from the mean year at interview which is known yet because of freqsummary */
14792: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */ /* Done in freqsummary */
14793: if(prvforecast==1){
14794: dateprojd=(jproj1+12*mproj1+365*anproj1)/365;
14795: jprojd=jproj1;
14796: mprojd=mproj1;
14797: anprojd=anproj1;
14798: dateprojf=(jproj2+12*mproj2+365*anproj2)/365;
14799: jprojf=jproj2;
14800: mprojf=mproj2;
14801: anprojf=anproj2;
14802: } else if(prvforecast == 2){
14803: dateprojd=dateintmean;
14804: date2dmy(dateprojd,&jprojd, &mprojd, &anprojd);
14805: dateprojf=dateintmean+yrfproj;
14806: date2dmy(dateprojf,&jprojf, &mprojf, &anprojf);
14807: }
14808: if(prvbackcast==1){
14809: datebackd=(jback1+12*mback1+365*anback1)/365;
14810: jbackd=jback1;
14811: mbackd=mback1;
14812: anbackd=anback1;
14813: datebackf=(jback2+12*mback2+365*anback2)/365;
14814: jbackf=jback2;
14815: mbackf=mback2;
14816: anbackf=anback2;
14817: } else if(prvbackcast == 2){
14818: datebackd=dateintmean;
14819: date2dmy(datebackd,&jbackd, &mbackd, &anbackd);
14820: datebackf=dateintmean-yrbproj;
14821: date2dmy(datebackf,&jbackf, &mbackf, &anbackf);
14822: }
14823:
1.350 brouard 14824: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage);/* HERE valgrind Tvard*/
1.220 brouard 14825: }
14826: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.296 brouard 14827: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,prevbcast, estepm, \
14828: jprev1,mprev1,anprev1,dateprev1, dateprojd, datebackd,jprev2,mprev2,anprev2,dateprev2,dateprojf, datebackf);
1.220 brouard 14829:
1.225 brouard 14830: /*------------ free_vector -------------*/
14831: /* chdir(path); */
1.220 brouard 14832:
1.215 brouard 14833: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
14834: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
14835: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
14836: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 14837: free_lvector(num,firstobs,lastobs);
14838: free_vector(agedc,firstobs,lastobs);
1.126 brouard 14839: /*free_matrix(covar,0,NCOVMAX,1,n);*/
14840: /*free_matrix(covar,1,NCOVMAX,1,n);*/
14841: fclose(ficparo);
14842: fclose(ficres);
1.220 brouard 14843:
14844:
1.186 brouard 14845: /* Other results (useful)*/
1.220 brouard 14846:
14847:
1.126 brouard 14848: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 14849: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
14850: prlim=matrix(1,nlstate,1,nlstate);
1.332 brouard 14851: /* Computes the prevalence limit for each combination k of the dummy covariates by calling prevalim(k) */
1.209 brouard 14852: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 14853: fclose(ficrespl);
14854:
14855: /*------------- h Pij x at various ages ------------*/
1.180 brouard 14856: /*#include "hpijx.h"*/
1.332 brouard 14857: /** 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?*/
14858: /* calls hpxij with combination k */
1.180 brouard 14859: hPijx(p, bage, fage);
1.145 brouard 14860: fclose(ficrespij);
1.227 brouard 14861:
1.220 brouard 14862: /* ncovcombmax= pow(2,cptcoveff); */
1.332 brouard 14863: /*-------------- Variance of one-step probabilities for a combination ij or for nres ?---*/
1.145 brouard 14864: k=1;
1.126 brouard 14865: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 14866:
1.269 brouard 14867: /* Prevalence for each covariate combination in probs[age][status][cov] */
14868: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
14869: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 14870: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 14871: for(k=1;k<=ncovcombmax;k++)
14872: probs[i][j][k]=0.;
1.269 brouard 14873: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
14874: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 14875: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 14876: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
14877: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 14878: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 14879: for(k=1;k<=ncovcombmax;k++)
14880: mobaverages[i][j][k]=0.;
1.219 brouard 14881: mobaverage=mobaverages;
14882: if (mobilav!=0) {
1.235 brouard 14883: printf("Movingaveraging observed prevalence\n");
1.258 brouard 14884: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 14885: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
14886: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
14887: printf(" Error in movingaverage mobilav=%d\n",mobilav);
14888: }
1.269 brouard 14889: } else if (mobilavproj !=0) {
1.235 brouard 14890: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 14891: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 14892: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
14893: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
14894: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
14895: }
1.269 brouard 14896: }else{
14897: printf("Internal error moving average\n");
14898: fflush(stdout);
14899: exit(1);
1.219 brouard 14900: }
14901: }/* end if moving average */
1.227 brouard 14902:
1.126 brouard 14903: /*---------- Forecasting ------------------*/
1.296 brouard 14904: if(prevfcast==1){
14905: /* /\* if(stepm ==1){*\/ */
14906: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
14907: /*This done previously after freqsummary.*/
14908: /* dateprojd=(jproj1+12*mproj1+365*anproj1)/365; */
14909: /* dateprojf=(jproj2+12*mproj2+365*anproj2)/365; */
14910:
14911: /* } else if (prvforecast==2){ */
14912: /* /\* if(stepm ==1){*\/ */
14913: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
14914: /* } */
14915: /*prevforecast(fileresu, dateintmean, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);*/
14916: prevforecast(fileresu,dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, p, cptcoveff);
1.126 brouard 14917: }
1.269 brouard 14918:
1.296 brouard 14919: /* Prevbcasting */
14920: if(prevbcast==1){
1.219 brouard 14921: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14922: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14923: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14924:
14925: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
14926:
14927: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 14928:
1.219 brouard 14929: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
14930: fclose(ficresplb);
14931:
1.222 brouard 14932: hBijx(p, bage, fage, mobaverage);
14933: fclose(ficrespijb);
1.219 brouard 14934:
1.296 brouard 14935: /* /\* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, *\/ */
14936: /* /\* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); *\/ */
14937: /* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, */
14938: /* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
14939: prevbackforecast(fileresu, mobaverage, dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2,
14940: mobilavproj, bage, fage, firstpass, lastpass, p, cptcoveff);
14941:
14942:
1.269 brouard 14943: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 14944:
14945:
1.269 brouard 14946: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 14947: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
14948: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
14949: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.296 brouard 14950: } /* end Prevbcasting */
1.268 brouard 14951:
1.186 brouard 14952:
14953: /* ------ Other prevalence ratios------------ */
1.126 brouard 14954:
1.215 brouard 14955: free_ivector(wav,1,imx);
14956: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
14957: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
14958: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 14959:
14960:
1.127 brouard 14961: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 14962:
1.201 brouard 14963: strcpy(filerese,"E_");
14964: strcat(filerese,fileresu);
1.126 brouard 14965: if((ficreseij=fopen(filerese,"w"))==NULL) {
14966: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
14967: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
14968: }
1.208 brouard 14969: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
14970: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 14971:
14972: pstamp(ficreseij);
1.219 brouard 14973:
1.351 ! brouard 14974: /* i1=pow(2,cptcoveff); /\* Number of combination of dummy covariates *\/ */
! 14975: /* if (cptcovn < 1){i1=1;} */
1.235 brouard 14976:
1.351 ! brouard 14977: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
! 14978: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
! 14979: /* if(i1 != 1 && TKresult[nres]!= k) */
! 14980: /* continue; */
1.219 brouard 14981: fprintf(ficreseij,"\n#****** ");
1.235 brouard 14982: printf("\n#****** ");
1.351 ! brouard 14983: for(j=1;j<=cptcovs;j++){
! 14984: /* for(j=1;j<=cptcoveff;j++) { */
! 14985: /* fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
! 14986: fprintf(ficreseij," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
! 14987: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
! 14988: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.235 brouard 14989: }
14990: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.337 brouard 14991: printf(" V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]); /* TvarsQ[j] gives the name of the jth quantitative (fixed or time v) */
14992: fprintf(ficreseij,"V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]);
1.219 brouard 14993: }
14994: fprintf(ficreseij,"******\n");
1.235 brouard 14995: printf("******\n");
1.219 brouard 14996:
14997: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
14998: oldm=oldms;savm=savms;
1.330 brouard 14999: /* 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 15000: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 15001:
1.219 brouard 15002: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 15003: }
15004: fclose(ficreseij);
1.208 brouard 15005: printf("done evsij\n");fflush(stdout);
15006: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 15007:
1.218 brouard 15008:
1.227 brouard 15009: /*---------- State-specific expectancies and variances ------------*/
1.336 brouard 15010: /* Should be moved in a function */
1.201 brouard 15011: strcpy(filerest,"T_");
15012: strcat(filerest,fileresu);
1.127 brouard 15013: if((ficrest=fopen(filerest,"w"))==NULL) {
15014: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
15015: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
15016: }
1.208 brouard 15017: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
15018: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 15019: strcpy(fileresstde,"STDE_");
15020: strcat(fileresstde,fileresu);
1.126 brouard 15021: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 15022: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
15023: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 15024: }
1.227 brouard 15025: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
15026: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 15027:
1.201 brouard 15028: strcpy(filerescve,"CVE_");
15029: strcat(filerescve,fileresu);
1.126 brouard 15030: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 15031: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
15032: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 15033: }
1.227 brouard 15034: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
15035: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 15036:
1.201 brouard 15037: strcpy(fileresv,"V_");
15038: strcat(fileresv,fileresu);
1.126 brouard 15039: if((ficresvij=fopen(fileresv,"w"))==NULL) {
15040: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
15041: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
15042: }
1.227 brouard 15043: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
15044: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 15045:
1.235 brouard 15046: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
15047: if (cptcovn < 1){i1=1;}
15048:
1.334 brouard 15049: for(nres=1; nres <= nresult; nres++) /* For each resultline, find the combination and output results according to the values of dummies and then quanti. */
15050: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying. For each nres and each value at position k
15051: * we know Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline
15052: * Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline
15053: * and Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
15054: /* */
15055: 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 15056: continue;
1.350 brouard 15057: printf("\n# model %s \n#****** Result for:", model); /* HERE model is empty */
1.321 brouard 15058: fprintf(ficrest,"\n# model %s \n#****** Result for:", model);
15059: fprintf(ficlog,"\n# model %s \n#****** Result for:", model);
1.334 brouard 15060: /* It might not be a good idea to mix dummies and quantitative */
15061: /* 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 *\/ */
15062: 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 */
15063: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /\* Output by variables in the resultline *\/ */
15064: /* Tvaraff[j] is the name of the dummy variable in position j in the equation model:
15065: * Tvaraff[1]@9={4, 3, 0, 0, 0, 0, 0, 0, 0}, in model=V5+V4+V3+V4*V3+V5*age
15066: * (V5 is quanti) V4 and V3 are dummies
15067: * TnsdVar[4] is the position 1 and TnsdVar[3]=2 in codtabm(k,l)(V4 V3)=V4 V3
15068: * l=1 l=2
15069: * k=1 1 1 0 0
15070: * k=2 2 1 1 0
15071: * k=3 [1] [2] 0 1
15072: * k=4 2 2 1 1
15073: * If nres=1 result: V3=1 V4=0 then k=3 and outputs
15074: * If nres=2 result: V4=1 V3=0 then k=2 and outputs
15075: * nres=1 =>k=3 j=1 V4= nbcode[4][codtabm(3,1)=1)=0; j=2 V3= nbcode[3][codtabm(3,2)=2]=1
15076: * nres=2 =>k=2 j=1 V4= nbcode[4][codtabm(2,1)=2)=1; j=2 V3= nbcode[3][codtabm(2,2)=1]=0
15077: */
15078: /* Tvresult[nres][j] Name of the variable at position j in this resultline */
15079: /* Tresult[nres][j] Value of this variable at position j could be a float if quantitative */
15080: /* We give up with the combinations!! */
1.342 brouard 15081: /* if(debugILK) */
15082: /* 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 15083:
15084: 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 15085: /* 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] */
15086: 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 */
15087: 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 */
15088: 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 15089: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
15090: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
15091: }else{
15092: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
15093: }
15094: /* fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15095: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15096: }else if(Dummy[modelresult[nres][j]]==1){ /* Quanti variable */
15097: /* For each selected (single) quantitative value */
1.337 brouard 15098: printf(" V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
15099: fprintf(ficlog," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
15100: fprintf(ficrest," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
1.334 brouard 15101: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
15102: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
15103: }else{
15104: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
15105: }
15106: }else{
15107: 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 */
15108: 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 */
15109: exit(1);
15110: }
1.335 brouard 15111: } /* End loop for each variable in the resultline */
1.334 brouard 15112: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
15113: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /\* Wrong j is not in the equation model *\/ */
15114: /* fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
15115: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
15116: /* } */
1.208 brouard 15117: fprintf(ficrest,"******\n");
1.227 brouard 15118: fprintf(ficlog,"******\n");
15119: printf("******\n");
1.208 brouard 15120:
15121: fprintf(ficresstdeij,"\n#****** ");
15122: fprintf(ficrescveij,"\n#****** ");
1.337 brouard 15123: /* It could have been: for(j=1;j<=cptcoveff;j++) {printf("V=%d=%lg",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);} */
15124: /* But it won't be sorted and depends on how the resultline is ordered */
1.225 brouard 15125: for(j=1;j<=cptcoveff;j++) {
1.334 brouard 15126: fprintf(ficresstdeij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
15127: /* fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15128: /* fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15129: }
15130: 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 15131: fprintf(ficresstdeij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
15132: fprintf(ficrescveij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
1.235 brouard 15133: }
1.208 brouard 15134: fprintf(ficresstdeij,"******\n");
15135: fprintf(ficrescveij,"******\n");
15136:
15137: fprintf(ficresvij,"\n#****** ");
1.238 brouard 15138: /* pstamp(ficresvij); */
1.225 brouard 15139: for(j=1;j<=cptcoveff;j++)
1.335 brouard 15140: fprintf(ficresvij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
15141: /* fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[TnsdVar[Tvaraff[j]]])]); */
1.235 brouard 15142: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.332 brouard 15143: /* fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); /\* To solve *\/ */
1.337 brouard 15144: fprintf(ficresvij," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /* Solved */
1.235 brouard 15145: }
1.208 brouard 15146: fprintf(ficresvij,"******\n");
15147:
15148: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
15149: oldm=oldms;savm=savms;
1.235 brouard 15150: printf(" cvevsij ");
15151: fprintf(ficlog, " cvevsij ");
15152: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 15153: printf(" end cvevsij \n ");
15154: fprintf(ficlog, " end cvevsij \n ");
15155:
15156: /*
15157: */
15158: /* goto endfree; */
15159:
15160: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
15161: pstamp(ficrest);
15162:
1.269 brouard 15163: epj=vector(1,nlstate+1);
1.208 brouard 15164: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 15165: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
15166: cptcod= 0; /* To be deleted */
15167: printf("varevsij vpopbased=%d \n",vpopbased);
15168: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 15169: 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 15170: 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 ");
15171: if(vpopbased==1)
15172: 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);
15173: else
1.288 brouard 15174: fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n");
1.335 brouard 15175: fprintf(ficrest,"# Age popbased mobilav e.. (std) "); /* Adding covariate values? */
1.227 brouard 15176: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
15177: fprintf(ficrest,"\n");
15178: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 15179: printf("Computing age specific forward period (stable) prevalences in each health state \n");
15180: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 15181: for(age=bage; age <=fage ;age++){
1.235 brouard 15182: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 15183: if (vpopbased==1) {
15184: if(mobilav ==0){
15185: for(i=1; i<=nlstate;i++)
15186: prlim[i][i]=probs[(int)age][i][k];
15187: }else{ /* mobilav */
15188: for(i=1; i<=nlstate;i++)
15189: prlim[i][i]=mobaverage[(int)age][i][k];
15190: }
15191: }
1.219 brouard 15192:
1.227 brouard 15193: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
15194: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
15195: /* printf(" age %4.0f ",age); */
15196: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
15197: for(i=1, epj[j]=0.;i <=nlstate;i++) {
15198: epj[j] += prlim[i][i]*eij[i][j][(int)age];
15199: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
15200: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
15201: }
15202: epj[nlstate+1] +=epj[j];
15203: }
15204: /* printf(" age %4.0f \n",age); */
1.219 brouard 15205:
1.227 brouard 15206: for(i=1, vepp=0.;i <=nlstate;i++)
15207: for(j=1;j <=nlstate;j++)
15208: vepp += vareij[i][j][(int)age];
15209: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
15210: for(j=1;j <=nlstate;j++){
15211: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
15212: }
15213: fprintf(ficrest,"\n");
15214: }
1.208 brouard 15215: } /* End vpopbased */
1.269 brouard 15216: free_vector(epj,1,nlstate+1);
1.208 brouard 15217: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
15218: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 15219: printf("done selection\n");fflush(stdout);
15220: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 15221:
1.335 brouard 15222: } /* End k selection or end covariate selection for nres */
1.227 brouard 15223:
15224: printf("done State-specific expectancies\n");fflush(stdout);
15225: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
15226:
1.335 brouard 15227: /* variance-covariance of forward period prevalence */
1.269 brouard 15228: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 15229:
1.227 brouard 15230:
1.290 brouard 15231: free_vector(weight,firstobs,lastobs);
1.351 ! brouard 15232: free_imatrix(Tvardk,0,NCOVMAX,1,2);
1.227 brouard 15233: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 15234: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
15235: free_matrix(anint,1,maxwav,firstobs,lastobs);
15236: free_matrix(mint,1,maxwav,firstobs,lastobs);
15237: free_ivector(cod,firstobs,lastobs);
1.227 brouard 15238: free_ivector(tab,1,NCOVMAX);
15239: fclose(ficresstdeij);
15240: fclose(ficrescveij);
15241: fclose(ficresvij);
15242: fclose(ficrest);
15243: fclose(ficpar);
15244:
15245:
1.126 brouard 15246: /*---------- End : free ----------------*/
1.219 brouard 15247: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 15248: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
15249: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 15250: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
15251: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 15252: } /* mle==-3 arrives here for freeing */
1.227 brouard 15253: /* endfree:*/
15254: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
15255: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
15256: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.341 brouard 15257: /* if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs); */
15258: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs);
1.290 brouard 15259: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
15260: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
15261: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 15262: free_matrix(matcov,1,npar,1,npar);
15263: free_matrix(hess,1,npar,1,npar);
15264: /*free_vector(delti,1,npar);*/
15265: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
15266: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 15267: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 15268: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
15269:
15270: free_ivector(ncodemax,1,NCOVMAX);
15271: free_ivector(ncodemaxwundef,1,NCOVMAX);
15272: free_ivector(Dummy,-1,NCOVMAX);
15273: free_ivector(Fixed,-1,NCOVMAX);
1.349 brouard 15274: free_ivector(DummyV,-1,NCOVMAX);
15275: free_ivector(FixedV,-1,NCOVMAX);
1.227 brouard 15276: free_ivector(Typevar,-1,NCOVMAX);
15277: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 15278: free_ivector(TvarsQ,1,NCOVMAX);
15279: free_ivector(TvarsQind,1,NCOVMAX);
15280: free_ivector(TvarsD,1,NCOVMAX);
1.330 brouard 15281: free_ivector(TnsdVar,1,NCOVMAX);
1.234 brouard 15282: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 15283: free_ivector(TvarFD,1,NCOVMAX);
15284: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 15285: free_ivector(TvarF,1,NCOVMAX);
15286: free_ivector(TvarFind,1,NCOVMAX);
15287: free_ivector(TvarV,1,NCOVMAX);
15288: free_ivector(TvarVind,1,NCOVMAX);
15289: free_ivector(TvarA,1,NCOVMAX);
15290: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 15291: free_ivector(TvarFQ,1,NCOVMAX);
15292: free_ivector(TvarFQind,1,NCOVMAX);
15293: free_ivector(TvarVD,1,NCOVMAX);
15294: free_ivector(TvarVDind,1,NCOVMAX);
15295: free_ivector(TvarVQ,1,NCOVMAX);
15296: free_ivector(TvarVQind,1,NCOVMAX);
1.349 brouard 15297: free_ivector(TvarAVVA,1,NCOVMAX);
15298: free_ivector(TvarAVVAind,1,NCOVMAX);
15299: free_ivector(TvarVVA,1,NCOVMAX);
15300: free_ivector(TvarVVAind,1,NCOVMAX);
1.339 brouard 15301: free_ivector(TvarVV,1,NCOVMAX);
15302: free_ivector(TvarVVind,1,NCOVMAX);
15303:
1.230 brouard 15304: free_ivector(Tvarsel,1,NCOVMAX);
15305: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 15306: free_ivector(Tposprod,1,NCOVMAX);
15307: free_ivector(Tprod,1,NCOVMAX);
15308: free_ivector(Tvaraff,1,NCOVMAX);
1.338 brouard 15309: free_ivector(invalidvarcomb,0,ncovcombmax);
1.227 brouard 15310: free_ivector(Tage,1,NCOVMAX);
15311: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 15312: free_ivector(TmodelInvind,1,NCOVMAX);
15313: free_ivector(TmodelInvQind,1,NCOVMAX);
1.332 brouard 15314:
15315: free_matrix(precov, 1,MAXRESULTLINESPONE,1,NCOVMAX+1); /* Could be elsewhere ?*/
15316:
1.227 brouard 15317: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
15318: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 15319: fflush(fichtm);
15320: fflush(ficgp);
15321:
1.227 brouard 15322:
1.126 brouard 15323: if((nberr >0) || (nbwarn>0)){
1.216 brouard 15324: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
15325: 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 15326: }else{
15327: printf("End of Imach\n");
15328: fprintf(ficlog,"End of Imach\n");
15329: }
15330: printf("See log file on %s\n",filelog);
15331: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 15332: /*(void) gettimeofday(&end_time,&tzp);*/
15333: rend_time = time(NULL);
15334: end_time = *localtime(&rend_time);
15335: /* tml = *localtime(&end_time.tm_sec); */
15336: strcpy(strtend,asctime(&end_time));
1.126 brouard 15337: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
15338: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 15339: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 15340:
1.157 brouard 15341: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
15342: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
15343: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 15344: /* printf("Total time was %d uSec.\n", total_usecs);*/
15345: /* if(fileappend(fichtm,optionfilehtm)){ */
15346: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
15347: fclose(fichtm);
15348: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
15349: fclose(fichtmcov);
15350: fclose(ficgp);
15351: fclose(ficlog);
15352: /*------ End -----------*/
1.227 brouard 15353:
1.281 brouard 15354:
15355: /* Executes gnuplot */
1.227 brouard 15356:
15357: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 15358: #ifdef WIN32
1.227 brouard 15359: if (_chdir(pathcd) != 0)
15360: printf("Can't move to directory %s!\n",path);
15361: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 15362: #else
1.227 brouard 15363: if(chdir(pathcd) != 0)
15364: printf("Can't move to directory %s!\n", path);
15365: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 15366: #endif
1.126 brouard 15367: printf("Current directory %s!\n",pathcd);
15368: /*strcat(plotcmd,CHARSEPARATOR);*/
15369: sprintf(plotcmd,"gnuplot");
1.157 brouard 15370: #ifdef _WIN32
1.126 brouard 15371: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
15372: #endif
15373: if(!stat(plotcmd,&info)){
1.158 brouard 15374: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 15375: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 15376: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 15377: }else
15378: strcpy(pplotcmd,plotcmd);
1.157 brouard 15379: #ifdef __unix
1.126 brouard 15380: strcpy(plotcmd,GNUPLOTPROGRAM);
15381: if(!stat(plotcmd,&info)){
1.158 brouard 15382: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 15383: }else
15384: strcpy(pplotcmd,plotcmd);
15385: #endif
15386: }else
15387: strcpy(pplotcmd,plotcmd);
15388:
15389: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 15390: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 brouard 15391: strcpy(pplotcmd,plotcmd);
1.227 brouard 15392:
1.126 brouard 15393: if((outcmd=system(plotcmd)) != 0){
1.292 brouard 15394: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 15395: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 15396: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 brouard 15397: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 15398: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 brouard 15399: strcpy(plotcmd,pplotcmd);
15400: }
1.126 brouard 15401: }
1.158 brouard 15402: printf(" Successful, please wait...");
1.126 brouard 15403: while (z[0] != 'q') {
15404: /* chdir(path); */
1.154 brouard 15405: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 15406: scanf("%s",z);
15407: /* if (z[0] == 'c') system("./imach"); */
15408: if (z[0] == 'e') {
1.158 brouard 15409: #ifdef __APPLE__
1.152 brouard 15410: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 15411: #elif __linux
15412: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 15413: #else
1.152 brouard 15414: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 15415: #endif
15416: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
15417: system(pplotcmd);
1.126 brouard 15418: }
15419: else if (z[0] == 'g') system(plotcmd);
15420: else if (z[0] == 'q') exit(0);
15421: }
1.227 brouard 15422: end:
1.126 brouard 15423: while (z[0] != 'q') {
1.195 brouard 15424: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 15425: scanf("%s",z);
15426: }
1.283 brouard 15427: printf("End\n");
1.282 brouard 15428: exit(0);
1.126 brouard 15429: }
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