Annotation of imach/src/imach.c, revision 1.350
1.350 ! brouard 1: /* $Id: imach.c,v 1.349 2023/01/31 09:19:37 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.350 ! brouard 4: Revision 1.349 2023/01/31 09:19:37 brouard
! 5: Summary: Improvements in models with age*Vn*Vm
! 6:
1.348 brouard 7: Revision 1.347 2022/09/18 14:36:44 brouard
8: Summary: version 0.99r42
9:
1.347 brouard 10: Revision 1.346 2022/09/16 13:52:36 brouard
11: * src/imach.c (Module): 0.99r41 Was an error when product of timevarying and fixed. Using FixedV[of name] now. Thank you Feinuo
12:
1.346 brouard 13: Revision 1.345 2022/09/16 13:40:11 brouard
14: Summary: Version 0.99r41
15:
16: * imach.c (Module): 0.99r41 Was an error when product of timevarying and fixed. Using FixedV[of name] now. Thank you Feinuo
17:
1.345 brouard 18: Revision 1.344 2022/09/14 19:33:30 brouard
19: Summary: version 0.99r40
20:
21: * imach.c (Module): Fixing names of variables in T_ (thanks to Feinuo)
22:
1.344 brouard 23: Revision 1.343 2022/09/14 14:22:16 brouard
24: Summary: version 0.99r39
25:
26: * imach.c (Module): Version 0.99r39 with colored dummy covariates
27: (fixed or time varying), using new last columns of
28: ILK_parameter.txt file.
29:
1.343 brouard 30: Revision 1.342 2022/09/11 19:54:09 brouard
31: Summary: 0.99r38
32:
33: * imach.c (Module): Adding timevarying products of any kinds,
34: should work before shifting cotvar from ncovcol+nqv columns in
35: order to have a correspondance between the column of cotvar and
36: the id of column.
37: (Module): Some cleaning and adding covariates in ILK.txt
38:
1.342 brouard 39: Revision 1.341 2022/09/11 07:58:42 brouard
40: Summary: Version 0.99r38
41:
42: After adding change in cotvar.
43:
1.341 brouard 44: Revision 1.340 2022/09/11 07:53:11 brouard
45: Summary: Version imach 0.99r37
46:
47: * imach.c (Module): Adding timevarying products of any kinds,
48: should work before shifting cotvar from ncovcol+nqv columns in
49: order to have a correspondance between the column of cotvar and
50: the id of column.
51:
1.340 brouard 52: Revision 1.339 2022/09/09 17:55:22 brouard
53: Summary: version 0.99r37
54:
55: * imach.c (Module): Many improvements for fixing products of fixed
56: timevarying as well as fixed * fixed, and test with quantitative
57: covariate.
58:
1.339 brouard 59: Revision 1.338 2022/09/04 17:40:33 brouard
60: Summary: 0.99r36
61:
62: * imach.c (Module): Now the easy runs i.e. without result or
63: model=1+age only did not work. The defautl combination should be 1
64: and not 0 because everything hasn't been tranformed yet.
65:
1.338 brouard 66: Revision 1.337 2022/09/02 14:26:02 brouard
67: Summary: version 0.99r35
68:
69: * src/imach.c: Version 0.99r35 because it outputs same results with
70: 1+age+V1+V1*age for females and 1+age for females only
71: (education=1 noweight)
72:
1.337 brouard 73: Revision 1.336 2022/08/31 09:52:36 brouard
74: *** empty log message ***
75:
1.336 brouard 76: Revision 1.335 2022/08/31 08:23:16 brouard
77: Summary: improvements...
78:
1.335 brouard 79: Revision 1.334 2022/08/25 09:08:41 brouard
80: Summary: In progress for quantitative
81:
1.334 brouard 82: Revision 1.333 2022/08/21 09:10:30 brouard
83: * src/imach.c (Module): Version 0.99r33 A lot of changes in
84: reassigning covariates: my first idea was that people will always
85: use the first covariate V1 into the model but in fact they are
86: producing data with many covariates and can use an equation model
87: with some of the covariate; it means that in a model V2+V3 instead
88: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
89: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
90: the equation model is restricted to two variables only (V2, V3)
91: and the combination for V2 should be codtabm(k,1) instead of
92: (codtabm(k,2), and the code should be
93: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
94: made. All of these should be simplified once a day like we did in
95: hpxij() for example by using precov[nres] which is computed in
96: decoderesult for each nres of each resultline. Loop should be done
97: on the equation model globally by distinguishing only product with
98: age (which are changing with age) and no more on type of
99: covariates, single dummies, single covariates.
100:
1.333 brouard 101: Revision 1.332 2022/08/21 09:06:25 brouard
102: Summary: Version 0.99r33
103:
104: * src/imach.c (Module): Version 0.99r33 A lot of changes in
105: reassigning covariates: my first idea was that people will always
106: use the first covariate V1 into the model but in fact they are
107: producing data with many covariates and can use an equation model
108: with some of the covariate; it means that in a model V2+V3 instead
109: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
110: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
111: the equation model is restricted to two variables only (V2, V3)
112: and the combination for V2 should be codtabm(k,1) instead of
113: (codtabm(k,2), and the code should be
114: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
115: made. All of these should be simplified once a day like we did in
116: hpxij() for example by using precov[nres] which is computed in
117: decoderesult for each nres of each resultline. Loop should be done
118: on the equation model globally by distinguishing only product with
119: age (which are changing with age) and no more on type of
120: covariates, single dummies, single covariates.
121:
1.332 brouard 122: Revision 1.331 2022/08/07 05:40:09 brouard
123: *** empty log message ***
124:
1.331 brouard 125: Revision 1.330 2022/08/06 07:18:25 brouard
126: Summary: last 0.99r31
127:
128: * imach.c (Module): Version of imach using partly decoderesult to rebuild xpxij function
129:
1.330 brouard 130: Revision 1.329 2022/08/03 17:29:54 brouard
131: * imach.c (Module): Many errors in graphs fixed with Vn*age covariates.
132:
1.329 brouard 133: Revision 1.328 2022/07/27 17:40:48 brouard
134: Summary: valgrind bug fixed by initializing to zero DummyV as well as Tage
135:
1.328 brouard 136: Revision 1.327 2022/07/27 14:47:35 brouard
137: Summary: Still a problem for one-step probabilities in case of quantitative variables
138:
1.327 brouard 139: Revision 1.326 2022/07/26 17:33:55 brouard
140: Summary: some test with nres=1
141:
1.326 brouard 142: Revision 1.325 2022/07/25 14:27:23 brouard
143: Summary: r30
144:
145: * imach.c (Module): Error cptcovn instead of nsd in bmij (was
146: coredumped, revealed by Feiuno, thank you.
147:
1.325 brouard 148: Revision 1.324 2022/07/23 17:44:26 brouard
149: *** empty log message ***
150:
1.324 brouard 151: Revision 1.323 2022/07/22 12:30:08 brouard
152: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
153:
1.323 brouard 154: Revision 1.322 2022/07/22 12:27:48 brouard
155: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
156:
1.322 brouard 157: Revision 1.321 2022/07/22 12:04:24 brouard
158: Summary: r28
159:
160: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
161:
1.321 brouard 162: Revision 1.320 2022/06/02 05:10:11 brouard
163: *** empty log message ***
164:
1.320 brouard 165: Revision 1.319 2022/06/02 04:45:11 brouard
166: * imach.c (Module): Adding the Wald tests from the log to the main
167: htm for better display of the maximum likelihood estimators.
168:
1.319 brouard 169: Revision 1.318 2022/05/24 08:10:59 brouard
170: * imach.c (Module): Some attempts to find a bug of wrong estimates
171: of confidencce intervals with product in the equation modelC
172:
1.318 brouard 173: Revision 1.317 2022/05/15 15:06:23 brouard
174: * imach.c (Module): Some minor improvements
175:
1.317 brouard 176: Revision 1.316 2022/05/11 15:11:31 brouard
177: Summary: r27
178:
1.316 brouard 179: Revision 1.315 2022/05/11 15:06:32 brouard
180: *** empty log message ***
181:
1.315 brouard 182: Revision 1.314 2022/04/13 17:43:09 brouard
183: * imach.c (Module): Adding link to text data files
184:
1.314 brouard 185: Revision 1.313 2022/04/11 15:57:42 brouard
186: * imach.c (Module): Error in rewriting the 'r' file with yearsfproj or yearsbproj fixed
187:
1.313 brouard 188: Revision 1.312 2022/04/05 21:24:39 brouard
189: *** empty log message ***
190:
1.312 brouard 191: Revision 1.311 2022/04/05 21:03:51 brouard
192: Summary: Fixed quantitative covariates
193:
194: Fixed covariates (dummy or quantitative)
195: with missing values have never been allowed but are ERRORS and
196: program quits. Standard deviations of fixed covariates were
197: wrongly computed. Mean and standard deviations of time varying
198: covariates are still not computed.
199:
1.311 brouard 200: Revision 1.310 2022/03/17 08:45:53 brouard
201: Summary: 99r25
202:
203: Improving detection of errors: result lines should be compatible with
204: the model.
205:
1.310 brouard 206: Revision 1.309 2021/05/20 12:39:14 brouard
207: Summary: Version 0.99r24
208:
1.309 brouard 209: Revision 1.308 2021/03/31 13:11:57 brouard
210: Summary: Version 0.99r23
211:
212:
213: * imach.c (Module): Still bugs in the result loop. Thank to Holly Benett
214:
1.308 brouard 215: Revision 1.307 2021/03/08 18:11:32 brouard
216: Summary: 0.99r22 fixed bug on result:
217:
1.307 brouard 218: Revision 1.306 2021/02/20 15:44:02 brouard
219: Summary: Version 0.99r21
220:
221: * imach.c (Module): Fix bug on quitting after result lines!
222: (Module): Version 0.99r21
223:
1.306 brouard 224: Revision 1.305 2021/02/20 15:28:30 brouard
225: * imach.c (Module): Fix bug on quitting after result lines!
226:
1.305 brouard 227: Revision 1.304 2021/02/12 11:34:20 brouard
228: * imach.c (Module): The use of a Windows BOM (huge) file is now an error
229:
1.304 brouard 230: Revision 1.303 2021/02/11 19:50:15 brouard
231: * (Module): imach.c Someone entered 'results:' instead of 'result:'. Now it is an error which is printed.
232:
1.303 brouard 233: Revision 1.302 2020/02/22 21:00:05 brouard
234: * (Module): imach.c Update mle=-3 (for computing Life expectancy
235: and life table from the data without any state)
236:
1.302 brouard 237: Revision 1.301 2019/06/04 13:51:20 brouard
238: Summary: Error in 'r'parameter file backcast yearsbproj instead of yearsfproj
239:
1.301 brouard 240: Revision 1.300 2019/05/22 19:09:45 brouard
241: Summary: version 0.99r19 of May 2019
242:
1.300 brouard 243: Revision 1.299 2019/05/22 18:37:08 brouard
244: Summary: Cleaned 0.99r19
245:
1.299 brouard 246: Revision 1.298 2019/05/22 18:19:56 brouard
247: *** empty log message ***
248:
1.298 brouard 249: Revision 1.297 2019/05/22 17:56:10 brouard
250: Summary: Fix bug by moving date2dmy and nhstepm which gaefin=-1
251:
1.297 brouard 252: Revision 1.296 2019/05/20 13:03:18 brouard
253: Summary: Projection syntax simplified
254:
255:
256: We can now start projections, forward or backward, from the mean date
257: of inteviews up to or down to a number of years of projection:
258: prevforecast=1 yearsfproj=15.3 mobil_average=0
259: or
260: prevforecast=1 starting-proj-date=1/1/2007 final-proj-date=12/31/2017 mobil_average=0
261: or
262: prevbackcast=1 yearsbproj=12.3 mobil_average=1
263: or
264: prevbackcast=1 starting-back-date=1/10/1999 final-back-date=1/1/1985 mobil_average=1
265:
1.296 brouard 266: Revision 1.295 2019/05/18 09:52:50 brouard
267: Summary: doxygen tex bug
268:
1.295 brouard 269: Revision 1.294 2019/05/16 14:54:33 brouard
270: Summary: There was some wrong lines added
271:
1.294 brouard 272: Revision 1.293 2019/05/09 15:17:34 brouard
273: *** empty log message ***
274:
1.293 brouard 275: Revision 1.292 2019/05/09 14:17:20 brouard
276: Summary: Some updates
277:
1.292 brouard 278: Revision 1.291 2019/05/09 13:44:18 brouard
279: Summary: Before ncovmax
280:
1.291 brouard 281: Revision 1.290 2019/05/09 13:39:37 brouard
282: Summary: 0.99r18 unlimited number of individuals
283:
284: 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.
285:
1.290 brouard 286: Revision 1.289 2018/12/13 09:16:26 brouard
287: Summary: Bug for young ages (<-30) will be in r17
288:
1.289 brouard 289: Revision 1.288 2018/05/02 20:58:27 brouard
290: Summary: Some bugs fixed
291:
1.288 brouard 292: Revision 1.287 2018/05/01 17:57:25 brouard
293: Summary: Bug fixed by providing frequencies only for non missing covariates
294:
1.287 brouard 295: Revision 1.286 2018/04/27 14:27:04 brouard
296: Summary: some minor bugs
297:
1.286 brouard 298: Revision 1.285 2018/04/21 21:02:16 brouard
299: Summary: Some bugs fixed, valgrind tested
300:
1.285 brouard 301: Revision 1.284 2018/04/20 05:22:13 brouard
302: Summary: Computing mean and stdeviation of fixed quantitative variables
303:
1.284 brouard 304: Revision 1.283 2018/04/19 14:49:16 brouard
305: Summary: Some minor bugs fixed
306:
1.283 brouard 307: Revision 1.282 2018/02/27 22:50:02 brouard
308: *** empty log message ***
309:
1.282 brouard 310: Revision 1.281 2018/02/27 19:25:23 brouard
311: Summary: Adding second argument for quitting
312:
1.281 brouard 313: Revision 1.280 2018/02/21 07:58:13 brouard
314: Summary: 0.99r15
315:
316: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
317:
1.280 brouard 318: Revision 1.279 2017/07/20 13:35:01 brouard
319: Summary: temporary working
320:
1.279 brouard 321: Revision 1.278 2017/07/19 14:09:02 brouard
322: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
323:
1.278 brouard 324: Revision 1.277 2017/07/17 08:53:49 brouard
325: Summary: BOM files can be read now
326:
1.277 brouard 327: Revision 1.276 2017/06/30 15:48:31 brouard
328: Summary: Graphs improvements
329:
1.276 brouard 330: Revision 1.275 2017/06/30 13:39:33 brouard
331: Summary: Saito's color
332:
1.275 brouard 333: Revision 1.274 2017/06/29 09:47:08 brouard
334: Summary: Version 0.99r14
335:
1.274 brouard 336: Revision 1.273 2017/06/27 11:06:02 brouard
337: Summary: More documentation on projections
338:
1.273 brouard 339: Revision 1.272 2017/06/27 10:22:40 brouard
340: Summary: Color of backprojection changed from 6 to 5(yellow)
341:
1.272 brouard 342: Revision 1.271 2017/06/27 10:17:50 brouard
343: Summary: Some bug with rint
344:
1.271 brouard 345: Revision 1.270 2017/05/24 05:45:29 brouard
346: *** empty log message ***
347:
1.270 brouard 348: Revision 1.269 2017/05/23 08:39:25 brouard
349: Summary: Code into subroutine, cleanings
350:
1.269 brouard 351: Revision 1.268 2017/05/18 20:09:32 brouard
352: Summary: backprojection and confidence intervals of backprevalence
353:
1.268 brouard 354: Revision 1.267 2017/05/13 10:25:05 brouard
355: Summary: temporary save for backprojection
356:
1.267 brouard 357: Revision 1.266 2017/05/13 07:26:12 brouard
358: Summary: Version 0.99r13 (improvements and bugs fixed)
359:
1.266 brouard 360: Revision 1.265 2017/04/26 16:22:11 brouard
361: Summary: imach 0.99r13 Some bugs fixed
362:
1.265 brouard 363: Revision 1.264 2017/04/26 06:01:29 brouard
364: Summary: Labels in graphs
365:
1.264 brouard 366: Revision 1.263 2017/04/24 15:23:15 brouard
367: Summary: to save
368:
1.263 brouard 369: Revision 1.262 2017/04/18 16:48:12 brouard
370: *** empty log message ***
371:
1.262 brouard 372: Revision 1.261 2017/04/05 10:14:09 brouard
373: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
374:
1.261 brouard 375: Revision 1.260 2017/04/04 17:46:59 brouard
376: Summary: Gnuplot indexations fixed (humm)
377:
1.260 brouard 378: Revision 1.259 2017/04/04 13:01:16 brouard
379: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
380:
1.259 brouard 381: Revision 1.258 2017/04/03 10:17:47 brouard
382: Summary: Version 0.99r12
383:
384: Some cleanings, conformed with updated documentation.
385:
1.258 brouard 386: Revision 1.257 2017/03/29 16:53:30 brouard
387: Summary: Temp
388:
1.257 brouard 389: Revision 1.256 2017/03/27 05:50:23 brouard
390: Summary: Temporary
391:
1.256 brouard 392: Revision 1.255 2017/03/08 16:02:28 brouard
393: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
394:
1.255 brouard 395: Revision 1.254 2017/03/08 07:13:00 brouard
396: Summary: Fixing data parameter line
397:
1.254 brouard 398: Revision 1.253 2016/12/15 11:59:41 brouard
399: Summary: 0.99 in progress
400:
1.253 brouard 401: Revision 1.252 2016/09/15 21:15:37 brouard
402: *** empty log message ***
403:
1.252 brouard 404: Revision 1.251 2016/09/15 15:01:13 brouard
405: Summary: not working
406:
1.251 brouard 407: Revision 1.250 2016/09/08 16:07:27 brouard
408: Summary: continue
409:
1.250 brouard 410: Revision 1.249 2016/09/07 17:14:18 brouard
411: Summary: Starting values from frequencies
412:
1.249 brouard 413: Revision 1.248 2016/09/07 14:10:18 brouard
414: *** empty log message ***
415:
1.248 brouard 416: Revision 1.247 2016/09/02 11:11:21 brouard
417: *** empty log message ***
418:
1.247 brouard 419: Revision 1.246 2016/09/02 08:49:22 brouard
420: *** empty log message ***
421:
1.246 brouard 422: Revision 1.245 2016/09/02 07:25:01 brouard
423: *** empty log message ***
424:
1.245 brouard 425: Revision 1.244 2016/09/02 07:17:34 brouard
426: *** empty log message ***
427:
1.244 brouard 428: Revision 1.243 2016/09/02 06:45:35 brouard
429: *** empty log message ***
430:
1.243 brouard 431: Revision 1.242 2016/08/30 15:01:20 brouard
432: Summary: Fixing a lots
433:
1.242 brouard 434: Revision 1.241 2016/08/29 17:17:25 brouard
435: Summary: gnuplot problem in Back projection to fix
436:
1.241 brouard 437: Revision 1.240 2016/08/29 07:53:18 brouard
438: Summary: Better
439:
1.240 brouard 440: Revision 1.239 2016/08/26 15:51:03 brouard
441: Summary: Improvement in Powell output in order to copy and paste
442:
443: Author:
444:
1.239 brouard 445: Revision 1.238 2016/08/26 14:23:35 brouard
446: Summary: Starting tests of 0.99
447:
1.238 brouard 448: Revision 1.237 2016/08/26 09:20:19 brouard
449: Summary: to valgrind
450:
1.237 brouard 451: Revision 1.236 2016/08/25 10:50:18 brouard
452: *** empty log message ***
453:
1.236 brouard 454: Revision 1.235 2016/08/25 06:59:23 brouard
455: *** empty log message ***
456:
1.235 brouard 457: Revision 1.234 2016/08/23 16:51:20 brouard
458: *** empty log message ***
459:
1.234 brouard 460: Revision 1.233 2016/08/23 07:40:50 brouard
461: Summary: not working
462:
1.233 brouard 463: Revision 1.232 2016/08/22 14:20:21 brouard
464: Summary: not working
465:
1.232 brouard 466: Revision 1.231 2016/08/22 07:17:15 brouard
467: Summary: not working
468:
1.231 brouard 469: Revision 1.230 2016/08/22 06:55:53 brouard
470: Summary: Not working
471:
1.230 brouard 472: Revision 1.229 2016/07/23 09:45:53 brouard
473: Summary: Completing for func too
474:
1.229 brouard 475: Revision 1.228 2016/07/22 17:45:30 brouard
476: Summary: Fixing some arrays, still debugging
477:
1.227 brouard 478: Revision 1.226 2016/07/12 18:42:34 brouard
479: Summary: temp
480:
1.226 brouard 481: Revision 1.225 2016/07/12 08:40:03 brouard
482: Summary: saving but not running
483:
1.225 brouard 484: Revision 1.224 2016/07/01 13:16:01 brouard
485: Summary: Fixes
486:
1.224 brouard 487: Revision 1.223 2016/02/19 09:23:35 brouard
488: Summary: temporary
489:
1.223 brouard 490: Revision 1.222 2016/02/17 08:14:50 brouard
491: Summary: Probably last 0.98 stable version 0.98r6
492:
1.222 brouard 493: Revision 1.221 2016/02/15 23:35:36 brouard
494: Summary: minor bug
495:
1.220 brouard 496: Revision 1.219 2016/02/15 00:48:12 brouard
497: *** empty log message ***
498:
1.219 brouard 499: Revision 1.218 2016/02/12 11:29:23 brouard
500: Summary: 0.99 Back projections
501:
1.218 brouard 502: Revision 1.217 2015/12/23 17:18:31 brouard
503: Summary: Experimental backcast
504:
1.217 brouard 505: Revision 1.216 2015/12/18 17:32:11 brouard
506: Summary: 0.98r4 Warning and status=-2
507:
508: Version 0.98r4 is now:
509: - displaying an error when status is -1, date of interview unknown and date of death known;
510: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
511: Older changes concerning s=-2, dating from 2005 have been supersed.
512:
1.216 brouard 513: Revision 1.215 2015/12/16 08:52:24 brouard
514: Summary: 0.98r4 working
515:
1.215 brouard 516: Revision 1.214 2015/12/16 06:57:54 brouard
517: Summary: temporary not working
518:
1.214 brouard 519: Revision 1.213 2015/12/11 18:22:17 brouard
520: Summary: 0.98r4
521:
1.213 brouard 522: Revision 1.212 2015/11/21 12:47:24 brouard
523: Summary: minor typo
524:
1.212 brouard 525: Revision 1.211 2015/11/21 12:41:11 brouard
526: Summary: 0.98r3 with some graph of projected cross-sectional
527:
528: Author: Nicolas Brouard
529:
1.211 brouard 530: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 531: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 532: Summary: Adding ftolpl parameter
533: Author: N Brouard
534:
535: We had difficulties to get smoothed confidence intervals. It was due
536: to the period prevalence which wasn't computed accurately. The inner
537: parameter ftolpl is now an outer parameter of the .imach parameter
538: file after estepm. If ftolpl is small 1.e-4 and estepm too,
539: computation are long.
540:
1.209 brouard 541: Revision 1.208 2015/11/17 14:31:57 brouard
542: Summary: temporary
543:
1.208 brouard 544: Revision 1.207 2015/10/27 17:36:57 brouard
545: *** empty log message ***
546:
1.207 brouard 547: Revision 1.206 2015/10/24 07:14:11 brouard
548: *** empty log message ***
549:
1.206 brouard 550: Revision 1.205 2015/10/23 15:50:53 brouard
551: Summary: 0.98r3 some clarification for graphs on likelihood contributions
552:
1.205 brouard 553: Revision 1.204 2015/10/01 16:20:26 brouard
554: Summary: Some new graphs of contribution to likelihood
555:
1.204 brouard 556: Revision 1.203 2015/09/30 17:45:14 brouard
557: Summary: looking at better estimation of the hessian
558:
559: Also a better criteria for convergence to the period prevalence And
560: therefore adding the number of years needed to converge. (The
561: prevalence in any alive state shold sum to one
562:
1.203 brouard 563: Revision 1.202 2015/09/22 19:45:16 brouard
564: Summary: Adding some overall graph on contribution to likelihood. Might change
565:
1.202 brouard 566: Revision 1.201 2015/09/15 17:34:58 brouard
567: Summary: 0.98r0
568:
569: - Some new graphs like suvival functions
570: - Some bugs fixed like model=1+age+V2.
571:
1.201 brouard 572: Revision 1.200 2015/09/09 16:53:55 brouard
573: Summary: Big bug thanks to Flavia
574:
575: Even model=1+age+V2. did not work anymore
576:
1.200 brouard 577: Revision 1.199 2015/09/07 14:09:23 brouard
578: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
579:
1.199 brouard 580: Revision 1.198 2015/09/03 07:14:39 brouard
581: Summary: 0.98q5 Flavia
582:
1.198 brouard 583: Revision 1.197 2015/09/01 18:24:39 brouard
584: *** empty log message ***
585:
1.197 brouard 586: Revision 1.196 2015/08/18 23:17:52 brouard
587: Summary: 0.98q5
588:
1.196 brouard 589: Revision 1.195 2015/08/18 16:28:39 brouard
590: Summary: Adding a hack for testing purpose
591:
592: After reading the title, ftol and model lines, if the comment line has
593: a q, starting with #q, the answer at the end of the run is quit. It
594: permits to run test files in batch with ctest. The former workaround was
595: $ echo q | imach foo.imach
596:
1.195 brouard 597: Revision 1.194 2015/08/18 13:32:00 brouard
598: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
599:
1.194 brouard 600: Revision 1.193 2015/08/04 07:17:42 brouard
601: Summary: 0.98q4
602:
1.193 brouard 603: Revision 1.192 2015/07/16 16:49:02 brouard
604: Summary: Fixing some outputs
605:
1.192 brouard 606: Revision 1.191 2015/07/14 10:00:33 brouard
607: Summary: Some fixes
608:
1.191 brouard 609: Revision 1.190 2015/05/05 08:51:13 brouard
610: Summary: Adding digits in output parameters (7 digits instead of 6)
611:
612: Fix 1+age+.
613:
1.190 brouard 614: Revision 1.189 2015/04/30 14:45:16 brouard
615: Summary: 0.98q2
616:
1.189 brouard 617: Revision 1.188 2015/04/30 08:27:53 brouard
618: *** empty log message ***
619:
1.188 brouard 620: Revision 1.187 2015/04/29 09:11:15 brouard
621: *** empty log message ***
622:
1.187 brouard 623: Revision 1.186 2015/04/23 12:01:52 brouard
624: Summary: V1*age is working now, version 0.98q1
625:
626: Some codes had been disabled in order to simplify and Vn*age was
627: working in the optimization phase, ie, giving correct MLE parameters,
628: but, as usual, outputs were not correct and program core dumped.
629:
1.186 brouard 630: Revision 1.185 2015/03/11 13:26:42 brouard
631: Summary: Inclusion of compile and links command line for Intel Compiler
632:
1.185 brouard 633: Revision 1.184 2015/03/11 11:52:39 brouard
634: Summary: Back from Windows 8. Intel Compiler
635:
1.184 brouard 636: Revision 1.183 2015/03/10 20:34:32 brouard
637: Summary: 0.98q0, trying with directest, mnbrak fixed
638:
639: We use directest instead of original Powell test; probably no
640: incidence on the results, but better justifications;
641: We fixed Numerical Recipes mnbrak routine which was wrong and gave
642: wrong results.
643:
1.183 brouard 644: Revision 1.182 2015/02/12 08:19:57 brouard
645: Summary: Trying to keep directest which seems simpler and more general
646: Author: Nicolas Brouard
647:
1.182 brouard 648: Revision 1.181 2015/02/11 23:22:24 brouard
649: Summary: Comments on Powell added
650:
651: Author:
652:
1.181 brouard 653: Revision 1.180 2015/02/11 17:33:45 brouard
654: Summary: Finishing move from main to function (hpijx and prevalence_limit)
655:
1.180 brouard 656: Revision 1.179 2015/01/04 09:57:06 brouard
657: Summary: back to OS/X
658:
1.179 brouard 659: Revision 1.178 2015/01/04 09:35:48 brouard
660: *** empty log message ***
661:
1.178 brouard 662: Revision 1.177 2015/01/03 18:40:56 brouard
663: Summary: Still testing ilc32 on OSX
664:
1.177 brouard 665: Revision 1.176 2015/01/03 16:45:04 brouard
666: *** empty log message ***
667:
1.176 brouard 668: Revision 1.175 2015/01/03 16:33:42 brouard
669: *** empty log message ***
670:
1.175 brouard 671: Revision 1.174 2015/01/03 16:15:49 brouard
672: Summary: Still in cross-compilation
673:
1.174 brouard 674: Revision 1.173 2015/01/03 12:06:26 brouard
675: Summary: trying to detect cross-compilation
676:
1.173 brouard 677: Revision 1.172 2014/12/27 12:07:47 brouard
678: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
679:
1.172 brouard 680: Revision 1.171 2014/12/23 13:26:59 brouard
681: Summary: Back from Visual C
682:
683: Still problem with utsname.h on Windows
684:
1.171 brouard 685: Revision 1.170 2014/12/23 11:17:12 brouard
686: Summary: Cleaning some \%% back to %%
687:
688: The escape was mandatory for a specific compiler (which one?), but too many warnings.
689:
1.170 brouard 690: Revision 1.169 2014/12/22 23:08:31 brouard
691: Summary: 0.98p
692:
693: Outputs some informations on compiler used, OS etc. Testing on different platforms.
694:
1.169 brouard 695: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 696: Summary: update
1.169 brouard 697:
1.168 brouard 698: Revision 1.167 2014/12/22 13:50:56 brouard
699: Summary: Testing uname and compiler version and if compiled 32 or 64
700:
701: Testing on Linux 64
702:
1.167 brouard 703: Revision 1.166 2014/12/22 11:40:47 brouard
704: *** empty log message ***
705:
1.166 brouard 706: Revision 1.165 2014/12/16 11:20:36 brouard
707: Summary: After compiling on Visual C
708:
709: * imach.c (Module): Merging 1.61 to 1.162
710:
1.165 brouard 711: Revision 1.164 2014/12/16 10:52:11 brouard
712: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
713:
714: * imach.c (Module): Merging 1.61 to 1.162
715:
1.164 brouard 716: Revision 1.163 2014/12/16 10:30:11 brouard
717: * imach.c (Module): Merging 1.61 to 1.162
718:
1.163 brouard 719: Revision 1.162 2014/09/25 11:43:39 brouard
720: Summary: temporary backup 0.99!
721:
1.162 brouard 722: Revision 1.1 2014/09/16 11:06:58 brouard
723: Summary: With some code (wrong) for nlopt
724:
725: Author:
726:
727: Revision 1.161 2014/09/15 20:41:41 brouard
728: Summary: Problem with macro SQR on Intel compiler
729:
1.161 brouard 730: Revision 1.160 2014/09/02 09:24:05 brouard
731: *** empty log message ***
732:
1.160 brouard 733: Revision 1.159 2014/09/01 10:34:10 brouard
734: Summary: WIN32
735: Author: Brouard
736:
1.159 brouard 737: Revision 1.158 2014/08/27 17:11:51 brouard
738: *** empty log message ***
739:
1.158 brouard 740: Revision 1.157 2014/08/27 16:26:55 brouard
741: Summary: Preparing windows Visual studio version
742: Author: Brouard
743:
744: In order to compile on Visual studio, time.h is now correct and time_t
745: and tm struct should be used. difftime should be used but sometimes I
746: just make the differences in raw time format (time(&now).
747: Trying to suppress #ifdef LINUX
748: Add xdg-open for __linux in order to open default browser.
749:
1.157 brouard 750: Revision 1.156 2014/08/25 20:10:10 brouard
751: *** empty log message ***
752:
1.156 brouard 753: Revision 1.155 2014/08/25 18:32:34 brouard
754: Summary: New compile, minor changes
755: Author: Brouard
756:
1.155 brouard 757: Revision 1.154 2014/06/20 17:32:08 brouard
758: Summary: Outputs now all graphs of convergence to period prevalence
759:
1.154 brouard 760: Revision 1.153 2014/06/20 16:45:46 brouard
761: Summary: If 3 live state, convergence to period prevalence on same graph
762: Author: Brouard
763:
1.153 brouard 764: Revision 1.152 2014/06/18 17:54:09 brouard
765: Summary: open browser, use gnuplot on same dir than imach if not found in the path
766:
1.152 brouard 767: Revision 1.151 2014/06/18 16:43:30 brouard
768: *** empty log message ***
769:
1.151 brouard 770: Revision 1.150 2014/06/18 16:42:35 brouard
771: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
772: Author: brouard
773:
1.150 brouard 774: Revision 1.149 2014/06/18 15:51:14 brouard
775: Summary: Some fixes in parameter files errors
776: Author: Nicolas Brouard
777:
1.149 brouard 778: Revision 1.148 2014/06/17 17:38:48 brouard
779: Summary: Nothing new
780: Author: Brouard
781:
782: Just a new packaging for OS/X version 0.98nS
783:
1.148 brouard 784: Revision 1.147 2014/06/16 10:33:11 brouard
785: *** empty log message ***
786:
1.147 brouard 787: Revision 1.146 2014/06/16 10:20:28 brouard
788: Summary: Merge
789: Author: Brouard
790:
791: Merge, before building revised version.
792:
1.146 brouard 793: Revision 1.145 2014/06/10 21:23:15 brouard
794: Summary: Debugging with valgrind
795: Author: Nicolas Brouard
796:
797: Lot of changes in order to output the results with some covariates
798: After the Edimburgh REVES conference 2014, it seems mandatory to
799: improve the code.
800: No more memory valgrind error but a lot has to be done in order to
801: continue the work of splitting the code into subroutines.
802: Also, decodemodel has been improved. Tricode is still not
803: optimal. nbcode should be improved. Documentation has been added in
804: the source code.
805:
1.144 brouard 806: Revision 1.143 2014/01/26 09:45:38 brouard
807: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
808:
809: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
810: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
811:
1.143 brouard 812: Revision 1.142 2014/01/26 03:57:36 brouard
813: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
814:
815: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
816:
1.142 brouard 817: Revision 1.141 2014/01/26 02:42:01 brouard
818: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
819:
1.141 brouard 820: Revision 1.140 2011/09/02 10:37:54 brouard
821: Summary: times.h is ok with mingw32 now.
822:
1.140 brouard 823: Revision 1.139 2010/06/14 07:50:17 brouard
824: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
825: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
826:
1.139 brouard 827: Revision 1.138 2010/04/30 18:19:40 brouard
828: *** empty log message ***
829:
1.138 brouard 830: Revision 1.137 2010/04/29 18:11:38 brouard
831: (Module): Checking covariates for more complex models
832: than V1+V2. A lot of change to be done. Unstable.
833:
1.137 brouard 834: Revision 1.136 2010/04/26 20:30:53 brouard
835: (Module): merging some libgsl code. Fixing computation
836: of likelione (using inter/intrapolation if mle = 0) in order to
837: get same likelihood as if mle=1.
838: Some cleaning of code and comments added.
839:
1.136 brouard 840: Revision 1.135 2009/10/29 15:33:14 brouard
841: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
842:
1.135 brouard 843: Revision 1.134 2009/10/29 13:18:53 brouard
844: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
845:
1.134 brouard 846: Revision 1.133 2009/07/06 10:21:25 brouard
847: just nforces
848:
1.133 brouard 849: Revision 1.132 2009/07/06 08:22:05 brouard
850: Many tings
851:
1.132 brouard 852: Revision 1.131 2009/06/20 16:22:47 brouard
853: Some dimensions resccaled
854:
1.131 brouard 855: Revision 1.130 2009/05/26 06:44:34 brouard
856: (Module): Max Covariate is now set to 20 instead of 8. A
857: lot of cleaning with variables initialized to 0. Trying to make
858: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
859:
1.130 brouard 860: Revision 1.129 2007/08/31 13:49:27 lievre
861: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
862:
1.129 lievre 863: Revision 1.128 2006/06/30 13:02:05 brouard
864: (Module): Clarifications on computing e.j
865:
1.128 brouard 866: Revision 1.127 2006/04/28 18:11:50 brouard
867: (Module): Yes the sum of survivors was wrong since
868: imach-114 because nhstepm was no more computed in the age
869: loop. Now we define nhstepma in the age loop.
870: (Module): In order to speed up (in case of numerous covariates) we
871: compute health expectancies (without variances) in a first step
872: and then all the health expectancies with variances or standard
873: deviation (needs data from the Hessian matrices) which slows the
874: computation.
875: In the future we should be able to stop the program is only health
876: expectancies and graph are needed without standard deviations.
877:
1.127 brouard 878: Revision 1.126 2006/04/28 17:23:28 brouard
879: (Module): Yes the sum of survivors was wrong since
880: imach-114 because nhstepm was no more computed in the age
881: loop. Now we define nhstepma in the age loop.
882: Version 0.98h
883:
1.126 brouard 884: Revision 1.125 2006/04/04 15:20:31 lievre
885: Errors in calculation of health expectancies. Age was not initialized.
886: Forecasting file added.
887:
888: Revision 1.124 2006/03/22 17:13:53 lievre
889: Parameters are printed with %lf instead of %f (more numbers after the comma).
890: The log-likelihood is printed in the log file
891:
892: Revision 1.123 2006/03/20 10:52:43 brouard
893: * imach.c (Module): <title> changed, corresponds to .htm file
894: name. <head> headers where missing.
895:
896: * imach.c (Module): Weights can have a decimal point as for
897: English (a comma might work with a correct LC_NUMERIC environment,
898: otherwise the weight is truncated).
899: Modification of warning when the covariates values are not 0 or
900: 1.
901: Version 0.98g
902:
903: Revision 1.122 2006/03/20 09:45:41 brouard
904: (Module): Weights can have a decimal point as for
905: English (a comma might work with a correct LC_NUMERIC environment,
906: otherwise the weight is truncated).
907: Modification of warning when the covariates values are not 0 or
908: 1.
909: Version 0.98g
910:
911: Revision 1.121 2006/03/16 17:45:01 lievre
912: * imach.c (Module): Comments concerning covariates added
913:
914: * imach.c (Module): refinements in the computation of lli if
915: status=-2 in order to have more reliable computation if stepm is
916: not 1 month. Version 0.98f
917:
918: Revision 1.120 2006/03/16 15:10:38 lievre
919: (Module): refinements in the computation of lli if
920: status=-2 in order to have more reliable computation if stepm is
921: not 1 month. Version 0.98f
922:
923: Revision 1.119 2006/03/15 17:42:26 brouard
924: (Module): Bug if status = -2, the loglikelihood was
925: computed as likelihood omitting the logarithm. Version O.98e
926:
927: Revision 1.118 2006/03/14 18:20:07 brouard
928: (Module): varevsij Comments added explaining the second
929: table of variances if popbased=1 .
930: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
931: (Module): Function pstamp added
932: (Module): Version 0.98d
933:
934: Revision 1.117 2006/03/14 17:16:22 brouard
935: (Module): varevsij Comments added explaining the second
936: table of variances if popbased=1 .
937: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
938: (Module): Function pstamp added
939: (Module): Version 0.98d
940:
941: Revision 1.116 2006/03/06 10:29:27 brouard
942: (Module): Variance-covariance wrong links and
943: varian-covariance of ej. is needed (Saito).
944:
945: Revision 1.115 2006/02/27 12:17:45 brouard
946: (Module): One freematrix added in mlikeli! 0.98c
947:
948: Revision 1.114 2006/02/26 12:57:58 brouard
949: (Module): Some improvements in processing parameter
950: filename with strsep.
951:
952: Revision 1.113 2006/02/24 14:20:24 brouard
953: (Module): Memory leaks checks with valgrind and:
954: datafile was not closed, some imatrix were not freed and on matrix
955: allocation too.
956:
957: Revision 1.112 2006/01/30 09:55:26 brouard
958: (Module): Back to gnuplot.exe instead of wgnuplot.exe
959:
960: Revision 1.111 2006/01/25 20:38:18 brouard
961: (Module): Lots of cleaning and bugs added (Gompertz)
962: (Module): Comments can be added in data file. Missing date values
963: can be a simple dot '.'.
964:
965: Revision 1.110 2006/01/25 00:51:50 brouard
966: (Module): Lots of cleaning and bugs added (Gompertz)
967:
968: Revision 1.109 2006/01/24 19:37:15 brouard
969: (Module): Comments (lines starting with a #) are allowed in data.
970:
971: Revision 1.108 2006/01/19 18:05:42 lievre
972: Gnuplot problem appeared...
973: To be fixed
974:
975: Revision 1.107 2006/01/19 16:20:37 brouard
976: Test existence of gnuplot in imach path
977:
978: Revision 1.106 2006/01/19 13:24:36 brouard
979: Some cleaning and links added in html output
980:
981: Revision 1.105 2006/01/05 20:23:19 lievre
982: *** empty log message ***
983:
984: Revision 1.104 2005/09/30 16:11:43 lievre
985: (Module): sump fixed, loop imx fixed, and simplifications.
986: (Module): If the status is missing at the last wave but we know
987: that the person is alive, then we can code his/her status as -2
988: (instead of missing=-1 in earlier versions) and his/her
989: contributions to the likelihood is 1 - Prob of dying from last
990: health status (= 1-p13= p11+p12 in the easiest case of somebody in
991: the healthy state at last known wave). Version is 0.98
992:
993: Revision 1.103 2005/09/30 15:54:49 lievre
994: (Module): sump fixed, loop imx fixed, and simplifications.
995:
996: Revision 1.102 2004/09/15 17:31:30 brouard
997: Add the possibility to read data file including tab characters.
998:
999: Revision 1.101 2004/09/15 10:38:38 brouard
1000: Fix on curr_time
1001:
1002: Revision 1.100 2004/07/12 18:29:06 brouard
1003: Add version for Mac OS X. Just define UNIX in Makefile
1004:
1005: Revision 1.99 2004/06/05 08:57:40 brouard
1006: *** empty log message ***
1007:
1008: Revision 1.98 2004/05/16 15:05:56 brouard
1009: New version 0.97 . First attempt to estimate force of mortality
1010: directly from the data i.e. without the need of knowing the health
1011: state at each age, but using a Gompertz model: log u =a + b*age .
1012: This is the basic analysis of mortality and should be done before any
1013: other analysis, in order to test if the mortality estimated from the
1014: cross-longitudinal survey is different from the mortality estimated
1015: from other sources like vital statistic data.
1016:
1017: The same imach parameter file can be used but the option for mle should be -3.
1018:
1.324 brouard 1019: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 1020: former routines in order to include the new code within the former code.
1021:
1022: The output is very simple: only an estimate of the intercept and of
1023: the slope with 95% confident intervals.
1024:
1025: Current limitations:
1026: A) Even if you enter covariates, i.e. with the
1027: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
1028: B) There is no computation of Life Expectancy nor Life Table.
1029:
1030: Revision 1.97 2004/02/20 13:25:42 lievre
1031: Version 0.96d. Population forecasting command line is (temporarily)
1032: suppressed.
1033:
1034: Revision 1.96 2003/07/15 15:38:55 brouard
1035: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
1036: rewritten within the same printf. Workaround: many printfs.
1037:
1038: Revision 1.95 2003/07/08 07:54:34 brouard
1039: * imach.c (Repository):
1040: (Repository): Using imachwizard code to output a more meaningful covariance
1041: matrix (cov(a12,c31) instead of numbers.
1042:
1043: Revision 1.94 2003/06/27 13:00:02 brouard
1044: Just cleaning
1045:
1046: Revision 1.93 2003/06/25 16:33:55 brouard
1047: (Module): On windows (cygwin) function asctime_r doesn't
1048: exist so I changed back to asctime which exists.
1049: (Module): Version 0.96b
1050:
1051: Revision 1.92 2003/06/25 16:30:45 brouard
1052: (Module): On windows (cygwin) function asctime_r doesn't
1053: exist so I changed back to asctime which exists.
1054:
1055: Revision 1.91 2003/06/25 15:30:29 brouard
1056: * imach.c (Repository): Duplicated warning errors corrected.
1057: (Repository): Elapsed time after each iteration is now output. It
1058: helps to forecast when convergence will be reached. Elapsed time
1059: is stamped in powell. We created a new html file for the graphs
1060: concerning matrix of covariance. It has extension -cov.htm.
1061:
1062: Revision 1.90 2003/06/24 12:34:15 brouard
1063: (Module): Some bugs corrected for windows. Also, when
1064: mle=-1 a template is output in file "or"mypar.txt with the design
1065: of the covariance matrix to be input.
1066:
1067: Revision 1.89 2003/06/24 12:30:52 brouard
1068: (Module): Some bugs corrected for windows. Also, when
1069: mle=-1 a template is output in file "or"mypar.txt with the design
1070: of the covariance matrix to be input.
1071:
1072: Revision 1.88 2003/06/23 17:54:56 brouard
1073: * 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.
1074:
1075: Revision 1.87 2003/06/18 12:26:01 brouard
1076: Version 0.96
1077:
1078: Revision 1.86 2003/06/17 20:04:08 brouard
1079: (Module): Change position of html and gnuplot routines and added
1080: routine fileappend.
1081:
1082: Revision 1.85 2003/06/17 13:12:43 brouard
1083: * imach.c (Repository): Check when date of death was earlier that
1084: current date of interview. It may happen when the death was just
1085: prior to the death. In this case, dh was negative and likelihood
1086: was wrong (infinity). We still send an "Error" but patch by
1087: assuming that the date of death was just one stepm after the
1088: interview.
1089: (Repository): Because some people have very long ID (first column)
1090: we changed int to long in num[] and we added a new lvector for
1091: memory allocation. But we also truncated to 8 characters (left
1092: truncation)
1093: (Repository): No more line truncation errors.
1094:
1095: Revision 1.84 2003/06/13 21:44:43 brouard
1096: * imach.c (Repository): Replace "freqsummary" at a correct
1097: place. It differs from routine "prevalence" which may be called
1098: many times. Probs is memory consuming and must be used with
1099: parcimony.
1100: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
1101:
1102: Revision 1.83 2003/06/10 13:39:11 lievre
1103: *** empty log message ***
1104:
1105: Revision 1.82 2003/06/05 15:57:20 brouard
1106: Add log in imach.c and fullversion number is now printed.
1107:
1108: */
1109: /*
1110: Interpolated Markov Chain
1111:
1112: Short summary of the programme:
1113:
1.227 brouard 1114: This program computes Healthy Life Expectancies or State-specific
1115: (if states aren't health statuses) Expectancies from
1116: cross-longitudinal data. Cross-longitudinal data consist in:
1117:
1118: -1- a first survey ("cross") where individuals from different ages
1119: are interviewed on their health status or degree of disability (in
1120: the case of a health survey which is our main interest)
1121:
1122: -2- at least a second wave of interviews ("longitudinal") which
1123: measure each change (if any) in individual health status. Health
1124: expectancies are computed from the time spent in each health state
1125: according to a model. More health states you consider, more time is
1126: necessary to reach the Maximum Likelihood of the parameters involved
1127: in the model. The simplest model is the multinomial logistic model
1128: where pij is the probability to be observed in state j at the second
1129: wave conditional to be observed in state i at the first
1130: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
1131: etc , where 'age' is age and 'sex' is a covariate. If you want to
1132: have a more complex model than "constant and age", you should modify
1133: the program where the markup *Covariates have to be included here
1134: again* invites you to do it. More covariates you add, slower the
1.126 brouard 1135: convergence.
1136:
1137: The advantage of this computer programme, compared to a simple
1138: multinomial logistic model, is clear when the delay between waves is not
1139: identical for each individual. Also, if a individual missed an
1140: intermediate interview, the information is lost, but taken into
1141: account using an interpolation or extrapolation.
1142:
1143: hPijx is the probability to be observed in state i at age x+h
1144: conditional to the observed state i at age x. The delay 'h' can be
1145: split into an exact number (nh*stepm) of unobserved intermediate
1146: states. This elementary transition (by month, quarter,
1147: semester or year) is modelled as a multinomial logistic. The hPx
1148: matrix is simply the matrix product of nh*stepm elementary matrices
1149: and the contribution of each individual to the likelihood is simply
1150: hPijx.
1151:
1152: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 1153: of the life expectancies. It also computes the period (stable) prevalence.
1154:
1155: Back prevalence and projections:
1.227 brouard 1156:
1157: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
1158: double agemaxpar, double ftolpl, int *ncvyearp, double
1159: dateprev1,double dateprev2, int firstpass, int lastpass, int
1160: mobilavproj)
1161:
1162: Computes the back prevalence limit for any combination of
1163: covariate values k at any age between ageminpar and agemaxpar and
1164: returns it in **bprlim. In the loops,
1165:
1166: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
1167: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
1168:
1169: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 1170: Computes for any combination of covariates k and any age between bage and fage
1171: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
1172: oldm=oldms;savm=savms;
1.227 brouard 1173:
1.267 brouard 1174: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 1175: Computes the transition matrix starting at age 'age' over
1176: 'nhstepm*hstepm*stepm' months (i.e. until
1177: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 1178: nhstepm*hstepm matrices.
1179:
1180: Returns p3mat[i][j][h] after calling
1181: p3mat[i][j][h]=matprod2(newm,
1182: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
1183: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
1184: oldm);
1.226 brouard 1185:
1186: Important routines
1187:
1188: - func (or funcone), computes logit (pij) distinguishing
1189: o fixed variables (single or product dummies or quantitative);
1190: o varying variables by:
1191: (1) wave (single, product dummies, quantitative),
1192: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
1193: % fixed dummy (treated) or quantitative (not done because time-consuming);
1194: % varying dummy (not done) or quantitative (not done);
1195: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
1196: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
1197: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
1.325 brouard 1198: o There are 2**cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
1.226 brouard 1199: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 1200:
1.226 brouard 1201:
1202:
1.324 brouard 1203: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
1204: Institut national d'études démographiques, Paris.
1.126 brouard 1205: This software have been partly granted by Euro-REVES, a concerted action
1206: from the European Union.
1207: It is copyrighted identically to a GNU software product, ie programme and
1208: software can be distributed freely for non commercial use. Latest version
1209: can be accessed at http://euroreves.ined.fr/imach .
1210:
1211: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
1212: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
1213:
1214: **********************************************************************/
1215: /*
1216: main
1217: read parameterfile
1218: read datafile
1219: concatwav
1220: freqsummary
1221: if (mle >= 1)
1222: mlikeli
1223: print results files
1224: if mle==1
1225: computes hessian
1226: read end of parameter file: agemin, agemax, bage, fage, estepm
1227: begin-prev-date,...
1228: open gnuplot file
1229: open html file
1.145 brouard 1230: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
1231: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
1232: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
1233: freexexit2 possible for memory heap.
1234:
1235: h Pij x | pij_nom ficrestpij
1236: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
1237: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
1238: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
1239:
1240: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
1241: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
1242: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
1243: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
1244: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
1245:
1.126 brouard 1246: forecasting if prevfcast==1 prevforecast call prevalence()
1247: health expectancies
1248: Variance-covariance of DFLE
1249: prevalence()
1250: movingaverage()
1251: varevsij()
1252: if popbased==1 varevsij(,popbased)
1253: total life expectancies
1254: Variance of period (stable) prevalence
1255: end
1256: */
1257:
1.187 brouard 1258: /* #define DEBUG */
1259: /* #define DEBUGBRENT */
1.203 brouard 1260: /* #define DEBUGLINMIN */
1261: /* #define DEBUGHESS */
1262: #define DEBUGHESSIJ
1.224 brouard 1263: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 1264: #define POWELL /* Instead of NLOPT */
1.224 brouard 1265: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 1266: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
1267: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.319 brouard 1268: /* #define FLATSUP *//* Suppresses directions where likelihood is flat */
1.126 brouard 1269:
1270: #include <math.h>
1271: #include <stdio.h>
1272: #include <stdlib.h>
1273: #include <string.h>
1.226 brouard 1274: #include <ctype.h>
1.159 brouard 1275:
1276: #ifdef _WIN32
1277: #include <io.h>
1.172 brouard 1278: #include <windows.h>
1279: #include <tchar.h>
1.159 brouard 1280: #else
1.126 brouard 1281: #include <unistd.h>
1.159 brouard 1282: #endif
1.126 brouard 1283:
1284: #include <limits.h>
1285: #include <sys/types.h>
1.171 brouard 1286:
1287: #if defined(__GNUC__)
1288: #include <sys/utsname.h> /* Doesn't work on Windows */
1289: #endif
1290:
1.126 brouard 1291: #include <sys/stat.h>
1292: #include <errno.h>
1.159 brouard 1293: /* extern int errno; */
1.126 brouard 1294:
1.157 brouard 1295: /* #ifdef LINUX */
1296: /* #include <time.h> */
1297: /* #include "timeval.h" */
1298: /* #else */
1299: /* #include <sys/time.h> */
1300: /* #endif */
1301:
1.126 brouard 1302: #include <time.h>
1303:
1.136 brouard 1304: #ifdef GSL
1305: #include <gsl/gsl_errno.h>
1306: #include <gsl/gsl_multimin.h>
1307: #endif
1308:
1.167 brouard 1309:
1.162 brouard 1310: #ifdef NLOPT
1311: #include <nlopt.h>
1312: typedef struct {
1313: double (* function)(double [] );
1314: } myfunc_data ;
1315: #endif
1316:
1.126 brouard 1317: /* #include <libintl.h> */
1318: /* #define _(String) gettext (String) */
1319:
1.349 brouard 1320: #define MAXLINE 16384 /* Was 256 and 1024 and 2048. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1321:
1322: #define GNUPLOTPROGRAM "gnuplot"
1.343 brouard 1323: #define GNUPLOTVERSION 5.1
1324: double gnuplotversion=GNUPLOTVERSION;
1.126 brouard 1325: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1.329 brouard 1326: #define FILENAMELENGTH 256
1.126 brouard 1327:
1328: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1329: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1330:
1.349 brouard 1331: #define MAXPARM 216 /**< Maximum number of parameters for the optimization was 128 */
1.144 brouard 1332: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1333:
1334: #define NINTERVMAX 8
1.144 brouard 1335: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1336: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.325 brouard 1337: #define NCOVMAX 30 /**< Maximum number of covariates used in the model, including generated covariates V1*V2 or V1*age */
1.197 brouard 1338: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1339: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1340: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1341: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1342: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1343: /* #define AGESUP 130 */
1.288 brouard 1344: /* #define AGESUP 150 */
1345: #define AGESUP 200
1.268 brouard 1346: #define AGEINF 0
1.218 brouard 1347: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1348: #define AGEBASE 40
1.194 brouard 1349: #define AGEOVERFLOW 1.e20
1.164 brouard 1350: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1351: #ifdef _WIN32
1352: #define DIRSEPARATOR '\\'
1353: #define CHARSEPARATOR "\\"
1354: #define ODIRSEPARATOR '/'
1355: #else
1.126 brouard 1356: #define DIRSEPARATOR '/'
1357: #define CHARSEPARATOR "/"
1358: #define ODIRSEPARATOR '\\'
1359: #endif
1360:
1.350 ! brouard 1361: /* $Id: imach.c,v 1.349 2023/01/31 09:19:37 brouard Exp $ */
1.126 brouard 1362: /* $State: Exp $ */
1.196 brouard 1363: #include "version.h"
1364: char version[]=__IMACH_VERSION__;
1.349 brouard 1365: 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";
1.350 ! brouard 1366: char fullversion[]="$Revision: 1.349 $ $Date: 2023/01/31 09:19:37 $";
1.126 brouard 1367: char strstart[80];
1368: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1369: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.342 brouard 1370: int debugILK=0; /* debugILK is set by a #d in a comment line */
1.187 brouard 1371: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.330 brouard 1372: /* Number of covariates model (1)=V2+V1+ V3*age+V2*V4 */
1373: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
1.335 brouard 1374: 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 1375: 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 1376: int cptcovs=0; /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
1377: int cptcovsnq=0; /**< cptcovsnq number of SIMPLE covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1378: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1.349 brouard 1379: int cptcovprodage=0; /**< Number of fixed covariates with age: V3*age or V2*V3*age 1 */
1380: int cptcovprodvage=0; /**< Number of varying covariates with age: V7*age or V7*V6*age */
1381: int cptcovdageprod=0; /**< Number of doubleproducts with age, since 0.99r44 only: age*Vn*Vm for gnuplot printing*/
1.145 brouard 1382: int cptcovprodnoage=0; /**< Number of covariate products without age */
1.335 brouard 1383: 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 1384: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1385: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.339 brouard 1386: int ncovvt=0; /* Total number of effective (wave) varying covariates (dummy or quantitative or products [without age]) in the model */
1.349 brouard 1387: 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 */
1388: 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 */
1389: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (single or product, dummy or quantitative) in the model */
1390: 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 1391: int nsd=0; /**< Total number of single dummy variables (output) */
1392: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1393: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1394: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1395: int ntveff=0; /**< ntveff number of effective time varying variables */
1396: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1397: int cptcov=0; /* Working variable */
1.334 brouard 1398: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs+1 declared globally ;*/
1.290 brouard 1399: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1400: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.302 brouard 1401: int npar=NPARMAX; /* Number of parameters (nlstate+ndeath-1)*nlstate*ncovmodel; */
1.126 brouard 1402: int nlstate=2; /* Number of live states */
1403: int ndeath=1; /* Number of dead states */
1.130 brouard 1404: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.339 brouard 1405: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable*/
1406: int ncovcolt=0; /* ncovcolt=ncovcol+nqv+ntv+nqtv; total of covariates in the data, not in the model equation*/
1.126 brouard 1407: int popbased=0;
1408:
1409: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1410: int maxwav=0; /* Maxim number of waves */
1411: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1412: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1413: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1414: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1415: int mle=1, weightopt=0;
1.126 brouard 1416: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1417: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1418: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1419: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1420: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1421: int selected(int kvar); /* Is covariate kvar selected for printing results */
1422:
1.130 brouard 1423: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1424: double **matprod2(); /* test */
1.126 brouard 1425: double **oldm, **newm, **savm; /* Working pointers to matrices */
1426: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1427: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1428:
1.136 brouard 1429: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1430: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1431: FILE *ficlog, *ficrespow;
1.130 brouard 1432: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1433: double fretone; /* Only one call to likelihood */
1.130 brouard 1434: long ipmx=0; /* Number of contributions */
1.126 brouard 1435: double sw; /* Sum of weights */
1436: char filerespow[FILENAMELENGTH];
1437: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1438: FILE *ficresilk;
1439: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1440: FILE *ficresprobmorprev;
1441: FILE *fichtm, *fichtmcov; /* Html File */
1442: FILE *ficreseij;
1443: char filerese[FILENAMELENGTH];
1444: FILE *ficresstdeij;
1445: char fileresstde[FILENAMELENGTH];
1446: FILE *ficrescveij;
1447: char filerescve[FILENAMELENGTH];
1448: FILE *ficresvij;
1449: char fileresv[FILENAMELENGTH];
1.269 brouard 1450:
1.126 brouard 1451: char title[MAXLINE];
1.234 brouard 1452: char model[MAXLINE]; /**< The model line */
1.217 brouard 1453: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1454: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1455: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1456: char command[FILENAMELENGTH];
1457: int outcmd=0;
1458:
1.217 brouard 1459: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1460: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1461: char filelog[FILENAMELENGTH]; /* Log file */
1462: char filerest[FILENAMELENGTH];
1463: char fileregp[FILENAMELENGTH];
1464: char popfile[FILENAMELENGTH];
1465:
1466: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1467:
1.157 brouard 1468: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1469: /* struct timezone tzp; */
1470: /* extern int gettimeofday(); */
1471: struct tm tml, *gmtime(), *localtime();
1472:
1473: extern time_t time();
1474:
1475: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1476: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1.349 brouard 1477: time_t rlast_btime; /* raw time */
1.157 brouard 1478: struct tm tm;
1479:
1.126 brouard 1480: char strcurr[80], strfor[80];
1481:
1482: char *endptr;
1483: long lval;
1484: double dval;
1485:
1486: #define NR_END 1
1487: #define FREE_ARG char*
1488: #define FTOL 1.0e-10
1489:
1490: #define NRANSI
1.240 brouard 1491: #define ITMAX 200
1492: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1493:
1494: #define TOL 2.0e-4
1495:
1496: #define CGOLD 0.3819660
1497: #define ZEPS 1.0e-10
1498: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1499:
1500: #define GOLD 1.618034
1501: #define GLIMIT 100.0
1502: #define TINY 1.0e-20
1503:
1504: static double maxarg1,maxarg2;
1505: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1506: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1507:
1508: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1509: #define rint(a) floor(a+0.5)
1.166 brouard 1510: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1511: #define mytinydouble 1.0e-16
1.166 brouard 1512: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1513: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1514: /* static double dsqrarg; */
1515: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1516: static double sqrarg;
1517: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1518: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1519: int agegomp= AGEGOMP;
1520:
1521: int imx;
1522: int stepm=1;
1523: /* Stepm, step in month: minimum step interpolation*/
1524:
1525: int estepm;
1526: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1527:
1528: int m,nb;
1529: long *num;
1.197 brouard 1530: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1531: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1532: covariate for which somebody answered excluding
1533: undefined. Usually 2: 0 and 1. */
1534: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1535: covariate for which somebody answered including
1536: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1537: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1538: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1539: double ***mobaverage, ***mobaverages; /* New global variable */
1.332 brouard 1540: 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 1541: double *ageexmed,*agecens;
1542: double dateintmean=0;
1.296 brouard 1543: double anprojd, mprojd, jprojd; /* For eventual projections */
1544: double anprojf, mprojf, jprojf;
1.126 brouard 1545:
1.296 brouard 1546: double anbackd, mbackd, jbackd; /* For eventual backprojections */
1547: double anbackf, mbackf, jbackf;
1548: double jintmean,mintmean,aintmean;
1.126 brouard 1549: double *weight;
1550: int **s; /* Status */
1.141 brouard 1551: double *agedc;
1.145 brouard 1552: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1553: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1554: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1555: double **coqvar; /* Fixed quantitative covariate nqv */
1.341 brouard 1556: double ***cotvar; /* Time varying covariate start at ncovcol + nqv + (1 to ntv) */
1.225 brouard 1557: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1558: double idx;
1559: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.319 brouard 1560: /* Some documentation */
1561: /* Design original data
1562: * V1 V2 V3 V4 V5 V6 V7 V8 Weight ddb ddth d1st s1 V9 V10 V11 V12 s2 V9 V10 V11 V12
1563: * < ncovcol=6 > nqv=2 (V7 V8) dv dv dv qtv dv dv dvv qtv
1564: * ntv=3 nqtv=1
1.330 brouard 1565: * cptcovn number of covariates (not including constant and age or age*age) = number of plus sign + 1 = 10+1=11
1.319 brouard 1566: * For time varying covariate, quanti or dummies
1567: * cotqvar[wav][iv(1 to nqtv)][i]= [1][12][i]=(V12) quanti
1.341 brouard 1568: * cotvar[wav][ncovcol+nqv+ iv(1 to nqtv)][i]= [(1 to nqtv)][i]=(V12) quanti
1.319 brouard 1569: * cotvar[wav][iv(1 to ntv)][i]= [1][1][i]=(V9) dummies at wav 1
1570: * cotvar[wav][iv(1 to ntv)][i]= [1][2][i]=(V10) dummies at wav 1
1.332 brouard 1571: * covar[Vk,i], value of the Vkth fixed covariate dummy or quanti for individual i:
1.319 brouard 1572: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
1573: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 + V9 + V9*age + V10
1574: * k= 1 2 3 4 5 6 7 8 9 10 11
1575: */
1576: /* According to the model, more columns can be added to covar by the product of covariates */
1.318 brouard 1577: /* 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
1578: # States 1=Coresidence, 2 Living alone, 3 Institution
1579: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1580: */
1.349 brouard 1581: /* V5+V4+ V3+V4*V3 +V5*age+V2 +V1*V2+V1*age+V1+V4*V3*age */
1582: /* kmodel 1 2 3 4 5 6 7 8 9 10 */
1583: /*Typevar[k]= 0 0 0 2 1 0 2 1 0 3 *//*0 for simple covariate (dummy, quantitative,*/
1584: /* fixed or varying), 1 for age product, 2 for*/
1585: /* product without age, 3 for age and double product */
1586: /*Dummy[k]= 1 0 0 1 3 1 1 2 0 3 *//*Dummy[k] 0=dummy (0 1), 1 quantitative */
1587: /*(single or product without age), 2 dummy*/
1588: /* with age product, 3 quant with age product*/
1589: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 6 */
1590: /* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */
1591: /*TnsdVar[Tvar] 1 2 3 */
1592: /*Tvaraff[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1593: /*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1594: /*TvarsDind[nsd] 2 3 9 */ /* position K of single dummy cova */
1595: /* nsq 1 2 */ /* Counting single quantit tv */
1596: /* TvarsQ[k] 5 2 */ /* Number of single quantitative cova */
1597: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1598: /* Tprod[i]=k 1 2 */ /* Position in model of the ith prod without age */
1599: /* cptcovage 1 2 3 */ /* Counting cov*age in the model equation */
1600: /* Tage[cptcovage]=k 5 8 10 */ /* Position in the model of ith cov*age */
1.350 ! brouard 1601: /* 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"*/
! 1602: /* 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}*/
! 1603: /* p Tvard[2][1]@21 = {7, 2, 6, 3, 7, 3, 6, 4, 7, 4, 0 <repeats 11 times>}
! 1604: /* 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}*/
! 1605: /* 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 1606: /* Tvard[1][1]@4={4,3,1,2} V4*V3 V1*V2 */ /* Position in model of the ith prod without age */
1.330 brouard 1607: /* 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 1608: /* 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 1609: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.234 brouard 1610: /* Type */
1611: /* V 1 2 3 4 5 */
1612: /* F F V V V */
1613: /* D Q D D Q */
1614: /* */
1615: int *TvarsD;
1.330 brouard 1616: int *TnsdVar;
1.234 brouard 1617: int *TvarsDind;
1618: int *TvarsQ;
1619: int *TvarsQind;
1620:
1.318 brouard 1621: #define MAXRESULTLINESPONE 10+1
1.235 brouard 1622: int nresult=0;
1.258 brouard 1623: int parameterline=0; /* # of the parameter (type) line */
1.334 brouard 1624: int TKresult[MAXRESULTLINESPONE]; /* TKresult[nres]=k for each resultline nres give the corresponding combination of dummies */
1625: int resultmodel[MAXRESULTLINESPONE][NCOVMAX];/* resultmodel[k1]=k3: k1th position in the model corresponds to the k3 position in the resultline */
1626: int modelresult[MAXRESULTLINESPONE][NCOVMAX];/* modelresult[k3]=k1: k1th position in the model corresponds to the k3 position in the resultline */
1627: int Tresult[MAXRESULTLINESPONE][NCOVMAX];/* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1628: int Tinvresult[MAXRESULTLINESPONE][NCOVMAX];/* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1629: double TinvDoQresult[MAXRESULTLINESPONE][NCOVMAX];/* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.334 brouard 1630: int Tvresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1631: double Tqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.318 brouard 1632: double Tqinvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
1.332 brouard 1633: int Tvqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.318 brouard 1634:
1635: /* 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
1636: # States 1=Coresidence, 2 Living alone, 3 Institution
1637: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1638: */
1.234 brouard 1639: /* 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 1640: 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 */
1641: 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 */
1642: 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 */
1643: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1644: 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 */
1645: 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 1646: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1647: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1648: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1649: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1650: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1651: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1652: 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 */
1653: 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 1654: int *TvarVV; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1655: int *TvarVVind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1.349 brouard 1656: int *TvarVVA; /* We count ncovvt time varying covariates (single or products with age) and put their name into TvarVVA */
1657: int *TvarVVAind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1658: int *TvarAVVA; /* We count ALL ncovta time varying covariates (single or products with age) and put their name into TvarVVA */
1659: int *TvarAVVAind; /* We count ALL ncovta time varying covariates (single or products without age) and put their name into TvarVV */
1.339 brouard 1660: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
1.349 brouard 1661: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age */
1662: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
1663: /* TvarVV={3,1,3,1,3}, for V3 and then the product V1*V3 is decomposed into V1 and V3 */
1664: /* 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 1665: int *Tvarsel; /**< Selected covariates for output */
1666: double *Tvalsel; /**< Selected modality value of covariate for output */
1.349 brouard 1667: 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 1668: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1669: 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 1670: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1671: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1672: int *Tage;
1.227 brouard 1673: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1674: 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 1675: 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*/
1676: 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 1677: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1678: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1679: int **Tvard;
1.330 brouard 1680: int **Tvardk;
1.227 brouard 1681: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1682: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1683: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1684: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1685: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1686: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1687: double *lsurv, *lpop, *tpop;
1688:
1.231 brouard 1689: #define FD 1; /* Fixed dummy covariate */
1690: #define FQ 2; /* Fixed quantitative covariate */
1691: #define FP 3; /* Fixed product covariate */
1692: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1693: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1694: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1695: #define VD 10; /* Varying dummy covariate */
1696: #define VQ 11; /* Varying quantitative covariate */
1697: #define VP 12; /* Varying product covariate */
1698: #define VPDD 13; /* Varying product dummy*dummy covariate */
1699: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1700: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1701: #define APFD 16; /* Age product * fixed dummy covariate */
1702: #define APFQ 17; /* Age product * fixed quantitative covariate */
1703: #define APVD 18; /* Age product * varying dummy covariate */
1704: #define APVQ 19; /* Age product * varying quantitative covariate */
1705:
1706: #define FTYPE 1; /* Fixed covariate */
1707: #define VTYPE 2; /* Varying covariate (loop in wave) */
1708: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1709:
1710: struct kmodel{
1711: int maintype; /* main type */
1712: int subtype; /* subtype */
1713: };
1714: struct kmodel modell[NCOVMAX];
1715:
1.143 brouard 1716: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1717: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1718:
1719: /**************** split *************************/
1720: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1721: {
1722: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1723: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1724: */
1725: char *ss; /* pointer */
1.186 brouard 1726: int l1=0, l2=0; /* length counters */
1.126 brouard 1727:
1728: l1 = strlen(path ); /* length of path */
1729: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1730: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1731: if ( ss == NULL ) { /* no directory, so determine current directory */
1732: strcpy( name, path ); /* we got the fullname name because no directory */
1733: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1734: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1735: /* get current working directory */
1736: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1737: #ifdef WIN32
1738: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1739: #else
1740: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1741: #endif
1.126 brouard 1742: return( GLOCK_ERROR_GETCWD );
1743: }
1744: /* got dirc from getcwd*/
1745: printf(" DIRC = %s \n",dirc);
1.205 brouard 1746: } else { /* strip directory from path */
1.126 brouard 1747: ss++; /* after this, the filename */
1748: l2 = strlen( ss ); /* length of filename */
1749: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1750: strcpy( name, ss ); /* save file name */
1751: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1752: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1753: printf(" DIRC2 = %s \n",dirc);
1754: }
1755: /* We add a separator at the end of dirc if not exists */
1756: l1 = strlen( dirc ); /* length of directory */
1757: if( dirc[l1-1] != DIRSEPARATOR ){
1758: dirc[l1] = DIRSEPARATOR;
1759: dirc[l1+1] = 0;
1760: printf(" DIRC3 = %s \n",dirc);
1761: }
1762: ss = strrchr( name, '.' ); /* find last / */
1763: if (ss >0){
1764: ss++;
1765: strcpy(ext,ss); /* save extension */
1766: l1= strlen( name);
1767: l2= strlen(ss)+1;
1768: strncpy( finame, name, l1-l2);
1769: finame[l1-l2]= 0;
1770: }
1771:
1772: return( 0 ); /* we're done */
1773: }
1774:
1775:
1776: /******************************************/
1777:
1778: void replace_back_to_slash(char *s, char*t)
1779: {
1780: int i;
1781: int lg=0;
1782: i=0;
1783: lg=strlen(t);
1784: for(i=0; i<= lg; i++) {
1785: (s[i] = t[i]);
1786: if (t[i]== '\\') s[i]='/';
1787: }
1788: }
1789:
1.132 brouard 1790: char *trimbb(char *out, char *in)
1.137 brouard 1791: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1792: char *s;
1793: s=out;
1794: while (*in != '\0'){
1.137 brouard 1795: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1796: in++;
1797: }
1798: *out++ = *in++;
1799: }
1800: *out='\0';
1801: return s;
1802: }
1803:
1.187 brouard 1804: /* char *substrchaine(char *out, char *in, char *chain) */
1805: /* { */
1806: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1807: /* char *s, *t; */
1808: /* t=in;s=out; */
1809: /* while ((*in != *chain) && (*in != '\0')){ */
1810: /* *out++ = *in++; */
1811: /* } */
1812:
1813: /* /\* *in matches *chain *\/ */
1814: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1815: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1816: /* } */
1817: /* in--; chain--; */
1818: /* while ( (*in != '\0')){ */
1819: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1820: /* *out++ = *in++; */
1821: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1822: /* } */
1823: /* *out='\0'; */
1824: /* out=s; */
1825: /* return out; */
1826: /* } */
1827: char *substrchaine(char *out, char *in, char *chain)
1828: {
1829: /* Substract chain 'chain' from 'in', return and output 'out' */
1.349 brouard 1830: /* in="V1+V1*age+age*age+V2", chain="+age*age" out="V1+V1*age+V2" */
1.187 brouard 1831:
1832: char *strloc;
1833:
1.349 brouard 1834: strcpy (out, in); /* out="V1+V1*age+age*age+V2" */
1835: strloc = strstr(out, chain); /* strloc points to out at "+age*age+V2" */
1836: 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 1837: if(strloc != NULL){
1.349 brouard 1838: /* will affect out */ /* strloc+strlen(chain)=|+V2 = "V1+V1*age+age*age|+V2" */ /* Will also work in Unicodek */
1839: 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)*/
1840: /* equivalent to strcpy (strloc, strloc +strlen(chain)) if no overlap; Copies from "+V2" to V1+V1*age+ */
1.187 brouard 1841: }
1.349 brouard 1842: 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 1843: return out;
1844: }
1845:
1846:
1.145 brouard 1847: char *cutl(char *blocc, char *alocc, char *in, char occ)
1848: {
1.187 brouard 1849: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.349 brouard 1850: and alocc starts after first occurence of char 'occ' : ex cutl(blocc,alocc,"abcdef2ghi2j",'2')
1.310 brouard 1851: gives alocc="abcdef" and blocc="ghi2j".
1.145 brouard 1852: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1853: */
1.160 brouard 1854: char *s, *t;
1.145 brouard 1855: t=in;s=in;
1856: while ((*in != occ) && (*in != '\0')){
1857: *alocc++ = *in++;
1858: }
1859: if( *in == occ){
1860: *(alocc)='\0';
1861: s=++in;
1862: }
1863:
1864: if (s == t) {/* occ not found */
1865: *(alocc-(in-s))='\0';
1866: in=s;
1867: }
1868: while ( *in != '\0'){
1869: *blocc++ = *in++;
1870: }
1871:
1872: *blocc='\0';
1873: return t;
1874: }
1.137 brouard 1875: char *cutv(char *blocc, char *alocc, char *in, char occ)
1876: {
1.187 brouard 1877: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1878: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1879: gives blocc="abcdef2ghi" and alocc="j".
1880: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1881: */
1882: char *s, *t;
1883: t=in;s=in;
1884: while (*in != '\0'){
1885: while( *in == occ){
1886: *blocc++ = *in++;
1887: s=in;
1888: }
1889: *blocc++ = *in++;
1890: }
1891: if (s == t) /* occ not found */
1892: *(blocc-(in-s))='\0';
1893: else
1894: *(blocc-(in-s)-1)='\0';
1895: in=s;
1896: while ( *in != '\0'){
1897: *alocc++ = *in++;
1898: }
1899:
1900: *alocc='\0';
1901: return s;
1902: }
1903:
1.126 brouard 1904: int nbocc(char *s, char occ)
1905: {
1906: int i,j=0;
1907: int lg=20;
1908: i=0;
1909: lg=strlen(s);
1910: for(i=0; i<= lg; i++) {
1.234 brouard 1911: if (s[i] == occ ) j++;
1.126 brouard 1912: }
1913: return j;
1914: }
1915:
1.349 brouard 1916: int nboccstr(char *textin, char *chain)
1917: {
1918: /* Counts the number of occurence of "chain" in string textin */
1919: /* in="+V7*V4+age*V2+age*V3+age*V4" chain="age" */
1920: char *strloc;
1921:
1922: int i,j=0;
1923:
1924: i=0;
1925:
1926: strloc=textin; /* strloc points to "^+V7*V4+age+..." in textin */
1927: for(;;) {
1928: strloc= strstr(strloc,chain); /* strloc points to first character of chain in textin if found. Example strloc points^ to "+V7*V4+^age" in textin */
1929: if(strloc != NULL){
1930: strloc = strloc+strlen(chain); /* strloc points to "+V7*V4+age^" in textin */
1931: j++;
1932: }else
1933: break;
1934: }
1935: return j;
1936:
1937: }
1.137 brouard 1938: /* void cutv(char *u,char *v, char*t, char occ) */
1939: /* { */
1940: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1941: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1942: /* gives u="abcdef2ghi" and v="j" *\/ */
1943: /* int i,lg,j,p=0; */
1944: /* i=0; */
1945: /* lg=strlen(t); */
1946: /* for(j=0; j<=lg-1; j++) { */
1947: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1948: /* } */
1.126 brouard 1949:
1.137 brouard 1950: /* for(j=0; j<p; j++) { */
1951: /* (u[j] = t[j]); */
1952: /* } */
1953: /* u[p]='\0'; */
1.126 brouard 1954:
1.137 brouard 1955: /* for(j=0; j<= lg; j++) { */
1956: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1957: /* } */
1958: /* } */
1.126 brouard 1959:
1.160 brouard 1960: #ifdef _WIN32
1961: char * strsep(char **pp, const char *delim)
1962: {
1963: char *p, *q;
1964:
1965: if ((p = *pp) == NULL)
1966: return 0;
1967: if ((q = strpbrk (p, delim)) != NULL)
1968: {
1969: *pp = q + 1;
1970: *q = '\0';
1971: }
1972: else
1973: *pp = 0;
1974: return p;
1975: }
1976: #endif
1977:
1.126 brouard 1978: /********************** nrerror ********************/
1979:
1980: void nrerror(char error_text[])
1981: {
1982: fprintf(stderr,"ERREUR ...\n");
1983: fprintf(stderr,"%s\n",error_text);
1984: exit(EXIT_FAILURE);
1985: }
1986: /*********************** vector *******************/
1987: double *vector(int nl, int nh)
1988: {
1989: double *v;
1990: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1991: if (!v) nrerror("allocation failure in vector");
1992: return v-nl+NR_END;
1993: }
1994:
1995: /************************ free vector ******************/
1996: void free_vector(double*v, int nl, int nh)
1997: {
1998: free((FREE_ARG)(v+nl-NR_END));
1999: }
2000:
2001: /************************ivector *******************************/
2002: int *ivector(long nl,long nh)
2003: {
2004: int *v;
2005: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
2006: if (!v) nrerror("allocation failure in ivector");
2007: return v-nl+NR_END;
2008: }
2009:
2010: /******************free ivector **************************/
2011: void free_ivector(int *v, long nl, long nh)
2012: {
2013: free((FREE_ARG)(v+nl-NR_END));
2014: }
2015:
2016: /************************lvector *******************************/
2017: long *lvector(long nl,long nh)
2018: {
2019: long *v;
2020: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
2021: if (!v) nrerror("allocation failure in ivector");
2022: return v-nl+NR_END;
2023: }
2024:
2025: /******************free lvector **************************/
2026: void free_lvector(long *v, long nl, long nh)
2027: {
2028: free((FREE_ARG)(v+nl-NR_END));
2029: }
2030:
2031: /******************* imatrix *******************************/
2032: int **imatrix(long nrl, long nrh, long ncl, long nch)
2033: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
2034: {
2035: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
2036: int **m;
2037:
2038: /* allocate pointers to rows */
2039: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
2040: if (!m) nrerror("allocation failure 1 in matrix()");
2041: m += NR_END;
2042: m -= nrl;
2043:
2044:
2045: /* allocate rows and set pointers to them */
2046: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
2047: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2048: m[nrl] += NR_END;
2049: m[nrl] -= ncl;
2050:
2051: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
2052:
2053: /* return pointer to array of pointers to rows */
2054: return m;
2055: }
2056:
2057: /****************** free_imatrix *************************/
2058: void free_imatrix(m,nrl,nrh,ncl,nch)
2059: int **m;
2060: long nch,ncl,nrh,nrl;
2061: /* free an int matrix allocated by imatrix() */
2062: {
2063: free((FREE_ARG) (m[nrl]+ncl-NR_END));
2064: free((FREE_ARG) (m+nrl-NR_END));
2065: }
2066:
2067: /******************* matrix *******************************/
2068: double **matrix(long nrl, long nrh, long ncl, long nch)
2069: {
2070: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
2071: double **m;
2072:
2073: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
2074: if (!m) nrerror("allocation failure 1 in matrix()");
2075: m += NR_END;
2076: m -= nrl;
2077:
2078: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
2079: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2080: m[nrl] += NR_END;
2081: m[nrl] -= ncl;
2082:
2083: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2084: return m;
1.145 brouard 2085: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
2086: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
2087: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 2088: */
2089: }
2090:
2091: /*************************free matrix ************************/
2092: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
2093: {
2094: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2095: free((FREE_ARG)(m+nrl-NR_END));
2096: }
2097:
2098: /******************* ma3x *******************************/
2099: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
2100: {
2101: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
2102: double ***m;
2103:
2104: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
2105: if (!m) nrerror("allocation failure 1 in matrix()");
2106: m += NR_END;
2107: m -= nrl;
2108:
2109: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
2110: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2111: m[nrl] += NR_END;
2112: m[nrl] -= ncl;
2113:
2114: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2115:
2116: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
2117: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
2118: m[nrl][ncl] += NR_END;
2119: m[nrl][ncl] -= nll;
2120: for (j=ncl+1; j<=nch; j++)
2121: m[nrl][j]=m[nrl][j-1]+nlay;
2122:
2123: for (i=nrl+1; i<=nrh; i++) {
2124: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
2125: for (j=ncl+1; j<=nch; j++)
2126: m[i][j]=m[i][j-1]+nlay;
2127: }
2128: return m;
2129: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
2130: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
2131: */
2132: }
2133:
2134: /*************************free ma3x ************************/
2135: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
2136: {
2137: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
2138: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2139: free((FREE_ARG)(m+nrl-NR_END));
2140: }
2141:
2142: /*************** function subdirf ***********/
2143: char *subdirf(char fileres[])
2144: {
2145: /* Caution optionfilefiname is hidden */
2146: strcpy(tmpout,optionfilefiname);
2147: strcat(tmpout,"/"); /* Add to the right */
2148: strcat(tmpout,fileres);
2149: return tmpout;
2150: }
2151:
2152: /*************** function subdirf2 ***********/
2153: char *subdirf2(char fileres[], char *preop)
2154: {
1.314 brouard 2155: /* Example subdirf2(optionfilefiname,"FB_") with optionfilefiname="texte", result="texte/FB_texte"
2156: Errors in subdirf, 2, 3 while printing tmpout is
1.315 brouard 2157: rewritten within the same printf. Workaround: many printfs */
1.126 brouard 2158: /* Caution optionfilefiname is hidden */
2159: strcpy(tmpout,optionfilefiname);
2160: strcat(tmpout,"/");
2161: strcat(tmpout,preop);
2162: strcat(tmpout,fileres);
2163: return tmpout;
2164: }
2165:
2166: /*************** function subdirf3 ***********/
2167: char *subdirf3(char fileres[], char *preop, char *preop2)
2168: {
2169:
2170: /* Caution optionfilefiname is hidden */
2171: strcpy(tmpout,optionfilefiname);
2172: strcat(tmpout,"/");
2173: strcat(tmpout,preop);
2174: strcat(tmpout,preop2);
2175: strcat(tmpout,fileres);
2176: return tmpout;
2177: }
1.213 brouard 2178:
2179: /*************** function subdirfext ***********/
2180: char *subdirfext(char fileres[], char *preop, char *postop)
2181: {
2182:
2183: strcpy(tmpout,preop);
2184: strcat(tmpout,fileres);
2185: strcat(tmpout,postop);
2186: return tmpout;
2187: }
1.126 brouard 2188:
1.213 brouard 2189: /*************** function subdirfext3 ***********/
2190: char *subdirfext3(char fileres[], char *preop, char *postop)
2191: {
2192:
2193: /* Caution optionfilefiname is hidden */
2194: strcpy(tmpout,optionfilefiname);
2195: strcat(tmpout,"/");
2196: strcat(tmpout,preop);
2197: strcat(tmpout,fileres);
2198: strcat(tmpout,postop);
2199: return tmpout;
2200: }
2201:
1.162 brouard 2202: char *asc_diff_time(long time_sec, char ascdiff[])
2203: {
2204: long sec_left, days, hours, minutes;
2205: days = (time_sec) / (60*60*24);
2206: sec_left = (time_sec) % (60*60*24);
2207: hours = (sec_left) / (60*60) ;
2208: sec_left = (sec_left) %(60*60);
2209: minutes = (sec_left) /60;
2210: sec_left = (sec_left) % (60);
2211: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
2212: return ascdiff;
2213: }
2214:
1.126 brouard 2215: /***************** f1dim *************************/
2216: extern int ncom;
2217: extern double *pcom,*xicom;
2218: extern double (*nrfunc)(double []);
2219:
2220: double f1dim(double x)
2221: {
2222: int j;
2223: double f;
2224: double *xt;
2225:
2226: xt=vector(1,ncom);
2227: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
2228: f=(*nrfunc)(xt);
2229: free_vector(xt,1,ncom);
2230: return f;
2231: }
2232:
2233: /*****************brent *************************/
2234: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 2235: {
2236: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
2237: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
2238: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
2239: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
2240: * returned function value.
2241: */
1.126 brouard 2242: int iter;
2243: double a,b,d,etemp;
1.159 brouard 2244: double fu=0,fv,fw,fx;
1.164 brouard 2245: double ftemp=0.;
1.126 brouard 2246: double p,q,r,tol1,tol2,u,v,w,x,xm;
2247: double e=0.0;
2248:
2249: a=(ax < cx ? ax : cx);
2250: b=(ax > cx ? ax : cx);
2251: x=w=v=bx;
2252: fw=fv=fx=(*f)(x);
2253: for (iter=1;iter<=ITMAX;iter++) {
2254: xm=0.5*(a+b);
2255: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
2256: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
2257: printf(".");fflush(stdout);
2258: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 2259: #ifdef DEBUGBRENT
1.126 brouard 2260: 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);
2261: 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);
2262: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
2263: #endif
2264: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
2265: *xmin=x;
2266: return fx;
2267: }
2268: ftemp=fu;
2269: if (fabs(e) > tol1) {
2270: r=(x-w)*(fx-fv);
2271: q=(x-v)*(fx-fw);
2272: p=(x-v)*q-(x-w)*r;
2273: q=2.0*(q-r);
2274: if (q > 0.0) p = -p;
2275: q=fabs(q);
2276: etemp=e;
2277: e=d;
2278: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 2279: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 2280: else {
1.224 brouard 2281: d=p/q;
2282: u=x+d;
2283: if (u-a < tol2 || b-u < tol2)
2284: d=SIGN(tol1,xm-x);
1.126 brouard 2285: }
2286: } else {
2287: d=CGOLD*(e=(x >= xm ? a-x : b-x));
2288: }
2289: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
2290: fu=(*f)(u);
2291: if (fu <= fx) {
2292: if (u >= x) a=x; else b=x;
2293: SHFT(v,w,x,u)
1.183 brouard 2294: SHFT(fv,fw,fx,fu)
2295: } else {
2296: if (u < x) a=u; else b=u;
2297: if (fu <= fw || w == x) {
1.224 brouard 2298: v=w;
2299: w=u;
2300: fv=fw;
2301: fw=fu;
1.183 brouard 2302: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 2303: v=u;
2304: fv=fu;
1.183 brouard 2305: }
2306: }
1.126 brouard 2307: }
2308: nrerror("Too many iterations in brent");
2309: *xmin=x;
2310: return fx;
2311: }
2312:
2313: /****************** mnbrak ***********************/
2314:
2315: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
2316: double (*func)(double))
1.183 brouard 2317: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
2318: the downhill direction (defined by the function as evaluated at the initial points) and returns
2319: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
2320: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
2321: */
1.126 brouard 2322: double ulim,u,r,q, dum;
2323: double fu;
1.187 brouard 2324:
2325: double scale=10.;
2326: int iterscale=0;
2327:
2328: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
2329: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
2330:
2331:
2332: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
2333: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
2334: /* *bx = *ax - (*ax - *bx)/scale; */
2335: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
2336: /* } */
2337:
1.126 brouard 2338: if (*fb > *fa) {
2339: SHFT(dum,*ax,*bx,dum)
1.183 brouard 2340: SHFT(dum,*fb,*fa,dum)
2341: }
1.126 brouard 2342: *cx=(*bx)+GOLD*(*bx-*ax);
2343: *fc=(*func)(*cx);
1.183 brouard 2344: #ifdef DEBUG
1.224 brouard 2345: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
2346: 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 2347: #endif
1.224 brouard 2348: 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 2349: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 2350: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 2351: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 2352: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
2353: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
2354: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 2355: fu=(*func)(u);
1.163 brouard 2356: #ifdef DEBUG
2357: /* f(x)=A(x-u)**2+f(u) */
2358: double A, fparabu;
2359: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2360: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 2361: 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);
2362: 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 2363: /* And thus,it can be that fu > *fc even if fparabu < *fc */
2364: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
2365: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
2366: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 2367: #endif
1.184 brouard 2368: #ifdef MNBRAKORIGINAL
1.183 brouard 2369: #else
1.191 brouard 2370: /* if (fu > *fc) { */
2371: /* #ifdef DEBUG */
2372: /* printf("mnbrak4 fu > fc \n"); */
2373: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
2374: /* #endif */
2375: /* /\* 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 *\\/ *\/ */
2376: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2377: /* dum=u; /\* Shifting c and u *\/ */
2378: /* u = *cx; */
2379: /* *cx = dum; */
2380: /* dum = fu; */
2381: /* fu = *fc; */
2382: /* *fc =dum; */
2383: /* } else { /\* end *\/ */
2384: /* #ifdef DEBUG */
2385: /* printf("mnbrak3 fu < fc \n"); */
2386: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2387: /* #endif */
2388: /* dum=u; /\* Shifting c and u *\/ */
2389: /* u = *cx; */
2390: /* *cx = dum; */
2391: /* dum = fu; */
2392: /* fu = *fc; */
2393: /* *fc =dum; */
2394: /* } */
1.224 brouard 2395: #ifdef DEBUGMNBRAK
2396: double A, fparabu;
2397: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2398: fparabu= *fa - A*(*ax-u)*(*ax-u);
2399: 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);
2400: 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 2401: #endif
1.191 brouard 2402: dum=u; /* Shifting c and u */
2403: u = *cx;
2404: *cx = dum;
2405: dum = fu;
2406: fu = *fc;
2407: *fc =dum;
1.183 brouard 2408: #endif
1.162 brouard 2409: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2410: #ifdef DEBUG
1.224 brouard 2411: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2412: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2413: #endif
1.126 brouard 2414: fu=(*func)(u);
2415: if (fu < *fc) {
1.183 brouard 2416: #ifdef DEBUG
1.224 brouard 2417: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2418: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2419: #endif
2420: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2421: SHFT(*fb,*fc,fu,(*func)(u))
2422: #ifdef DEBUG
2423: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2424: #endif
2425: }
1.162 brouard 2426: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2427: #ifdef DEBUG
1.224 brouard 2428: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2429: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2430: #endif
1.126 brouard 2431: u=ulim;
2432: fu=(*func)(u);
1.183 brouard 2433: } else { /* u could be left to b (if r > q parabola has a maximum) */
2434: #ifdef DEBUG
1.224 brouard 2435: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2436: 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 2437: #endif
1.126 brouard 2438: u=(*cx)+GOLD*(*cx-*bx);
2439: fu=(*func)(u);
1.224 brouard 2440: #ifdef DEBUG
2441: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2442: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2443: #endif
1.183 brouard 2444: } /* end tests */
1.126 brouard 2445: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2446: SHFT(*fa,*fb,*fc,fu)
2447: #ifdef DEBUG
1.224 brouard 2448: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2449: 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 2450: #endif
2451: } /* 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 2452: }
2453:
2454: /*************** linmin ************************/
1.162 brouard 2455: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2456: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2457: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2458: the value of func at the returned location p . This is actually all accomplished by calling the
2459: routines mnbrak and brent .*/
1.126 brouard 2460: int ncom;
2461: double *pcom,*xicom;
2462: double (*nrfunc)(double []);
2463:
1.224 brouard 2464: #ifdef LINMINORIGINAL
1.126 brouard 2465: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2466: #else
2467: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2468: #endif
1.126 brouard 2469: {
2470: double brent(double ax, double bx, double cx,
2471: double (*f)(double), double tol, double *xmin);
2472: double f1dim(double x);
2473: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2474: double *fc, double (*func)(double));
2475: int j;
2476: double xx,xmin,bx,ax;
2477: double fx,fb,fa;
1.187 brouard 2478:
1.203 brouard 2479: #ifdef LINMINORIGINAL
2480: #else
2481: double scale=10., axs, xxs; /* Scale added for infinity */
2482: #endif
2483:
1.126 brouard 2484: ncom=n;
2485: pcom=vector(1,n);
2486: xicom=vector(1,n);
2487: nrfunc=func;
2488: for (j=1;j<=n;j++) {
2489: pcom[j]=p[j];
1.202 brouard 2490: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2491: }
1.187 brouard 2492:
1.203 brouard 2493: #ifdef LINMINORIGINAL
2494: xx=1.;
2495: #else
2496: axs=0.0;
2497: xxs=1.;
2498: do{
2499: xx= xxs;
2500: #endif
1.187 brouard 2501: ax=0.;
2502: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2503: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2504: /* 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)) */
2505: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2506: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2507: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2508: /* 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 2509: #ifdef LINMINORIGINAL
2510: #else
2511: if (fx != fx){
1.224 brouard 2512: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2513: printf("|");
2514: fprintf(ficlog,"|");
1.203 brouard 2515: #ifdef DEBUGLINMIN
1.224 brouard 2516: 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 2517: #endif
2518: }
1.224 brouard 2519: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2520: #endif
2521:
1.191 brouard 2522: #ifdef DEBUGLINMIN
2523: 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 2524: 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 2525: #endif
1.224 brouard 2526: #ifdef LINMINORIGINAL
2527: #else
1.317 brouard 2528: if(fb == fx){ /* Flat function in the direction */
2529: xmin=xx;
1.224 brouard 2530: *flat=1;
1.317 brouard 2531: }else{
1.224 brouard 2532: *flat=0;
2533: #endif
2534: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2535: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2536: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2537: /* fmin = f(p[j] + xmin * xi[j]) */
2538: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2539: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2540: #ifdef DEBUG
1.224 brouard 2541: 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);
2542: 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);
2543: #endif
2544: #ifdef LINMINORIGINAL
2545: #else
2546: }
1.126 brouard 2547: #endif
1.191 brouard 2548: #ifdef DEBUGLINMIN
2549: printf("linmin end ");
1.202 brouard 2550: fprintf(ficlog,"linmin end ");
1.191 brouard 2551: #endif
1.126 brouard 2552: for (j=1;j<=n;j++) {
1.203 brouard 2553: #ifdef LINMINORIGINAL
2554: xi[j] *= xmin;
2555: #else
2556: #ifdef DEBUGLINMIN
2557: if(xxs <1.0)
2558: printf(" before xi[%d]=%12.8f", j,xi[j]);
2559: #endif
2560: 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) */
2561: #ifdef DEBUGLINMIN
2562: if(xxs <1.0)
2563: 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 );
2564: #endif
2565: #endif
1.187 brouard 2566: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2567: }
1.191 brouard 2568: #ifdef DEBUGLINMIN
1.203 brouard 2569: printf("\n");
1.191 brouard 2570: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2571: 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 2572: for (j=1;j<=n;j++) {
1.202 brouard 2573: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2574: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2575: if(j % ncovmodel == 0){
1.191 brouard 2576: printf("\n");
1.202 brouard 2577: fprintf(ficlog,"\n");
2578: }
1.191 brouard 2579: }
1.203 brouard 2580: #else
1.191 brouard 2581: #endif
1.126 brouard 2582: free_vector(xicom,1,n);
2583: free_vector(pcom,1,n);
2584: }
2585:
2586:
2587: /*************** powell ************************/
1.162 brouard 2588: /*
1.317 brouard 2589: Minimization of a function func of n variables. Input consists in an initial starting point
2590: p[1..n] ; an initial matrix xi[1..n][1..n] whose columns contain the initial set of di-
2591: rections (usually the n unit vectors); and ftol, the fractional tolerance in the function value
2592: such that failure to decrease by more than this amount in one iteration signals doneness. On
1.162 brouard 2593: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2594: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2595: */
1.224 brouard 2596: #ifdef LINMINORIGINAL
2597: #else
2598: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2599: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2600: #endif
1.126 brouard 2601: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2602: double (*func)(double []))
2603: {
1.224 brouard 2604: #ifdef LINMINORIGINAL
2605: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2606: double (*func)(double []));
1.224 brouard 2607: #else
1.241 brouard 2608: void linmin(double p[], double xi[], int n, double *fret,
2609: double (*func)(double []),int *flat);
1.224 brouard 2610: #endif
1.239 brouard 2611: int i,ibig,j,jk,k;
1.126 brouard 2612: double del,t,*pt,*ptt,*xit;
1.181 brouard 2613: double directest;
1.126 brouard 2614: double fp,fptt;
2615: double *xits;
2616: int niterf, itmp;
1.349 brouard 2617: int Bigter=0, nBigterf=1;
2618:
1.126 brouard 2619: pt=vector(1,n);
2620: ptt=vector(1,n);
2621: xit=vector(1,n);
2622: xits=vector(1,n);
2623: *fret=(*func)(p);
2624: for (j=1;j<=n;j++) pt[j]=p[j];
1.338 brouard 2625: rcurr_time = time(NULL);
2626: fp=(*fret); /* Initialisation */
1.126 brouard 2627: for (*iter=1;;++(*iter)) {
2628: ibig=0;
2629: del=0.0;
1.157 brouard 2630: rlast_time=rcurr_time;
1.349 brouard 2631: rlast_btime=rcurr_time;
1.157 brouard 2632: /* (void) gettimeofday(&curr_time,&tzp); */
2633: rcurr_time = time(NULL);
2634: curr_time = *localtime(&rcurr_time);
1.337 brouard 2635: /* 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); */
2636: /* 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 2637: Bigter=(*iter - *iter % ncovmodel)/ncovmodel +1; /* Big iteration, i.e on ncovmodel cycle */
2638: 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);
2639: 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);
2640: fprintf(ficrespow,"%d %d %.12f %d",*iter,Bigter, *fret,curr_time.tm_sec-start_time.tm_sec);
1.324 brouard 2641: fp=(*fret); /* From former iteration or initial value */
1.192 brouard 2642: for (i=1;i<=n;i++) {
1.126 brouard 2643: fprintf(ficrespow," %.12lf", p[i]);
2644: }
1.239 brouard 2645: fprintf(ficrespow,"\n");fflush(ficrespow);
2646: printf("\n#model= 1 + age ");
2647: fprintf(ficlog,"\n#model= 1 + age ");
2648: if(nagesqr==1){
1.241 brouard 2649: printf(" + age*age ");
2650: fprintf(ficlog," + age*age ");
1.239 brouard 2651: }
2652: for(j=1;j <=ncovmodel-2;j++){
2653: if(Typevar[j]==0) {
2654: printf(" + V%d ",Tvar[j]);
2655: fprintf(ficlog," + V%d ",Tvar[j]);
2656: }else if(Typevar[j]==1) {
2657: printf(" + V%d*age ",Tvar[j]);
2658: fprintf(ficlog," + V%d*age ",Tvar[j]);
2659: }else if(Typevar[j]==2) {
2660: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2661: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 2662: }else if(Typevar[j]==3) {
2663: printf(" + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2664: fprintf(ficlog," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.239 brouard 2665: }
2666: }
1.126 brouard 2667: printf("\n");
1.239 brouard 2668: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2669: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2670: fprintf(ficlog,"\n");
1.239 brouard 2671: for(i=1,jk=1; i <=nlstate; i++){
2672: for(k=1; k <=(nlstate+ndeath); k++){
2673: if (k != i) {
2674: printf("%d%d ",i,k);
2675: fprintf(ficlog,"%d%d ",i,k);
2676: for(j=1; j <=ncovmodel; j++){
2677: printf("%12.7f ",p[jk]);
2678: fprintf(ficlog,"%12.7f ",p[jk]);
2679: jk++;
2680: }
2681: printf("\n");
2682: fprintf(ficlog,"\n");
2683: }
2684: }
2685: }
1.241 brouard 2686: if(*iter <=3 && *iter >1){
1.157 brouard 2687: tml = *localtime(&rcurr_time);
2688: strcpy(strcurr,asctime(&tml));
2689: rforecast_time=rcurr_time;
1.126 brouard 2690: itmp = strlen(strcurr);
2691: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2692: strcurr[itmp-1]='\0';
1.162 brouard 2693: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2694: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.349 brouard 2695: for(nBigterf=1;nBigterf<=31;nBigterf+=10){
2696: niterf=nBigterf*ncovmodel;
2697: /* rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time); */
1.241 brouard 2698: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2699: forecast_time = *localtime(&rforecast_time);
2700: strcpy(strfor,asctime(&forecast_time));
2701: itmp = strlen(strfor);
2702: if(strfor[itmp-1]=='\n')
2703: strfor[itmp-1]='\0';
1.349 brouard 2704: 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);
2705: 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 2706: }
2707: }
1.187 brouard 2708: for (i=1;i<=n;i++) { /* For each direction i */
2709: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2710: fptt=(*fret);
2711: #ifdef DEBUG
1.203 brouard 2712: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2713: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2714: #endif
1.203 brouard 2715: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2716: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2717: #ifdef LINMINORIGINAL
1.188 brouard 2718: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2719: #else
2720: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2721: flatdir[i]=flat; /* Function is vanishing in that direction i */
2722: #endif
2723: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2724: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2725: /* because that direction will be replaced unless the gain del is small */
2726: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2727: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2728: /* with the new direction. */
2729: del=fabs(fptt-(*fret));
2730: ibig=i;
1.126 brouard 2731: }
2732: #ifdef DEBUG
2733: printf("%d %.12e",i,(*fret));
2734: fprintf(ficlog,"%d %.12e",i,(*fret));
2735: for (j=1;j<=n;j++) {
1.224 brouard 2736: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2737: printf(" x(%d)=%.12e",j,xit[j]);
2738: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2739: }
2740: for(j=1;j<=n;j++) {
1.225 brouard 2741: printf(" p(%d)=%.12e",j,p[j]);
2742: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2743: }
2744: printf("\n");
2745: fprintf(ficlog,"\n");
2746: #endif
1.187 brouard 2747: } /* end loop on each direction i */
2748: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2749: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2750: /* New value of last point Pn is not computed, P(n-1) */
1.319 brouard 2751: for(j=1;j<=n;j++) {
2752: if(flatdir[j] >0){
2753: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2754: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
1.302 brouard 2755: }
1.319 brouard 2756: /* printf("\n"); */
2757: /* fprintf(ficlog,"\n"); */
2758: }
1.243 brouard 2759: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2760: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2761: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2762: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2763: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2764: /* decreased of more than 3.84 */
2765: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2766: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2767: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2768:
1.188 brouard 2769: /* Starting the program with initial values given by a former maximization will simply change */
2770: /* the scales of the directions and the directions, because the are reset to canonical directions */
2771: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2772: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2773: #ifdef DEBUG
2774: int k[2],l;
2775: k[0]=1;
2776: k[1]=-1;
2777: printf("Max: %.12e",(*func)(p));
2778: fprintf(ficlog,"Max: %.12e",(*func)(p));
2779: for (j=1;j<=n;j++) {
2780: printf(" %.12e",p[j]);
2781: fprintf(ficlog," %.12e",p[j]);
2782: }
2783: printf("\n");
2784: fprintf(ficlog,"\n");
2785: for(l=0;l<=1;l++) {
2786: for (j=1;j<=n;j++) {
2787: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2788: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2789: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2790: }
2791: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2792: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2793: }
2794: #endif
2795:
2796: free_vector(xit,1,n);
2797: free_vector(xits,1,n);
2798: free_vector(ptt,1,n);
2799: free_vector(pt,1,n);
2800: return;
1.192 brouard 2801: } /* enough precision */
1.240 brouard 2802: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2803: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2804: ptt[j]=2.0*p[j]-pt[j];
2805: xit[j]=p[j]-pt[j];
2806: pt[j]=p[j];
2807: }
1.181 brouard 2808: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2809: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2810: if (*iter <=4) {
1.225 brouard 2811: #else
2812: #endif
1.224 brouard 2813: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2814: #else
1.161 brouard 2815: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2816: #endif
1.162 brouard 2817: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2818: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2819: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2820: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2821: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2822: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2823: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2824: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2825: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2826: /* Even if f3 <f1, directest can be negative and t >0 */
2827: /* mu² and del² are equal when f3=f1 */
2828: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2829: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2830: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2831: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2832: #ifdef NRCORIGINAL
2833: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2834: #else
2835: 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 2836: t= t- del*SQR(fp-fptt);
1.183 brouard 2837: #endif
1.202 brouard 2838: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2839: #ifdef DEBUG
1.181 brouard 2840: 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);
2841: 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 2842: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2843: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2844: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2845: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2846: 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);
2847: 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);
2848: #endif
1.183 brouard 2849: #ifdef POWELLORIGINAL
2850: if (t < 0.0) { /* Then we use it for new direction */
2851: #else
1.182 brouard 2852: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2853: 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 2854: 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 2855: 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 2856: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2857: }
1.181 brouard 2858: if (directest < 0.0) { /* Then we use it for new direction */
2859: #endif
1.191 brouard 2860: #ifdef DEBUGLINMIN
1.234 brouard 2861: printf("Before linmin in direction P%d-P0\n",n);
2862: for (j=1;j<=n;j++) {
2863: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2864: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2865: if(j % ncovmodel == 0){
2866: printf("\n");
2867: fprintf(ficlog,"\n");
2868: }
2869: }
1.224 brouard 2870: #endif
2871: #ifdef LINMINORIGINAL
1.234 brouard 2872: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2873: #else
1.234 brouard 2874: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2875: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2876: #endif
1.234 brouard 2877:
1.191 brouard 2878: #ifdef DEBUGLINMIN
1.234 brouard 2879: for (j=1;j<=n;j++) {
2880: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2881: fprintf(ficlog,"After 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
1.234 brouard 2888: for (j=1;j<=n;j++) {
2889: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2890: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2891: }
1.224 brouard 2892: #ifdef LINMINORIGINAL
2893: #else
1.234 brouard 2894: for (j=1, flatd=0;j<=n;j++) {
2895: if(flatdir[j]>0)
2896: flatd++;
2897: }
2898: if(flatd >0){
1.255 brouard 2899: printf("%d flat directions: ",flatd);
2900: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2901: for (j=1;j<=n;j++) {
2902: if(flatdir[j]>0){
2903: printf("%d ",j);
2904: fprintf(ficlog,"%d ",j);
2905: }
2906: }
2907: printf("\n");
2908: fprintf(ficlog,"\n");
1.319 brouard 2909: #ifdef FLATSUP
2910: free_vector(xit,1,n);
2911: free_vector(xits,1,n);
2912: free_vector(ptt,1,n);
2913: free_vector(pt,1,n);
2914: return;
2915: #endif
1.234 brouard 2916: }
1.191 brouard 2917: #endif
1.234 brouard 2918: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2919: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2920:
1.126 brouard 2921: #ifdef DEBUG
1.234 brouard 2922: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2923: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2924: for(j=1;j<=n;j++){
2925: printf(" %lf",xit[j]);
2926: fprintf(ficlog," %lf",xit[j]);
2927: }
2928: printf("\n");
2929: fprintf(ficlog,"\n");
1.126 brouard 2930: #endif
1.192 brouard 2931: } /* end of t or directest negative */
1.224 brouard 2932: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2933: #else
1.234 brouard 2934: } /* end if (fptt < fp) */
1.192 brouard 2935: #endif
1.225 brouard 2936: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2937: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2938: #else
1.224 brouard 2939: #endif
1.234 brouard 2940: } /* loop iteration */
1.126 brouard 2941: }
1.234 brouard 2942:
1.126 brouard 2943: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2944:
1.235 brouard 2945: 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 2946: {
1.338 brouard 2947: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij . Nicely done
1.279 brouard 2948: * (and selected quantitative values in nres)
2949: * by left multiplying the unit
2950: * matrix by transitions matrix until convergence is reached with precision ftolpl
2951: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2952: * Wx is row vector: population in state 1, population in state 2, population dead
2953: * or prevalence in state 1, prevalence in state 2, 0
2954: * newm is the matrix after multiplications, its rows are identical at a factor.
2955: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2956: * Output is prlim.
2957: * Initial matrix pimij
2958: */
1.206 brouard 2959: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2960: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2961: /* 0, 0 , 1} */
2962: /*
2963: * and after some iteration: */
2964: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2965: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2966: /* 0, 0 , 1} */
2967: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2968: /* {0.51571254859325999, 0.4842874514067399, */
2969: /* 0.51326036147820708, 0.48673963852179264} */
2970: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2971:
1.332 brouard 2972: int i, ii,j,k, k1;
1.209 brouard 2973: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2974: /* double **matprod2(); */ /* test */
1.218 brouard 2975: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2976: double **newm;
1.209 brouard 2977: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2978: int ncvloop=0;
1.288 brouard 2979: int first=0;
1.169 brouard 2980:
1.209 brouard 2981: min=vector(1,nlstate);
2982: max=vector(1,nlstate);
2983: meandiff=vector(1,nlstate);
2984:
1.218 brouard 2985: /* Starting with matrix unity */
1.126 brouard 2986: for (ii=1;ii<=nlstate+ndeath;ii++)
2987: for (j=1;j<=nlstate+ndeath;j++){
2988: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2989: }
1.169 brouard 2990:
2991: cov[1]=1.;
2992:
2993: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2994: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2995: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2996: ncvloop++;
1.126 brouard 2997: newm=savm;
2998: /* Covariates have to be included here again */
1.138 brouard 2999: cov[2]=agefin;
1.319 brouard 3000: if(nagesqr==1){
3001: cov[3]= agefin*agefin;
3002: }
1.332 brouard 3003: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
3004: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
3005: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3006: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3007: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
3008: }else{
3009: cov[2+nagesqr+k1]=precov[nres][k1];
3010: }
3011: }/* End of loop on model equation */
3012:
3013: /* Start of old code (replaced by a loop on position in the model equation */
3014: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only of the model *\/ */
3015: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
3016: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; *\/ */
3017: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TnsdVar[TvarsD[k]])]; */
3018: /* /\* model = 1 +age + V1*V3 + age*V1 + V2 + V1 + age*V2 + V3 + V3*age + V1*V2 */
3019: /* * k 1 2 3 4 5 6 7 8 */
3020: /* *cov[] 1 2 3 4 5 6 7 8 9 10 */
3021: /* *TypeVar[k] 2 1 0 0 1 0 1 2 */
3022: /* *Dummy[k] 0 2 0 0 2 0 2 0 */
3023: /* *Tvar[k] 4 1 2 1 2 3 3 5 */
3024: /* *nsd=3 (1) (2) (3) */
3025: /* *TvarsD[nsd] [1]=2 1 3 */
3026: /* *TnsdVar [2]=2 [1]=1 [3]=3 */
3027: /* *TvarsDind[nsd](=k) [1]=3 [2]=4 [3]=6 */
3028: /* *Tage[] [1]=1 [2]=2 [3]=3 */
3029: /* *Tvard[] [1][1]=1 [2][1]=1 */
3030: /* * [1][2]=3 [2][2]=2 */
3031: /* *Tprod[](=k) [1]=1 [2]=8 */
3032: /* *TvarsDp(=Tvar) [1]=1 [2]=2 [3]=3 [4]=5 */
3033: /* *TvarD (=k) [1]=1 [2]=3 [3]=4 [3]=6 [4]=6 */
3034: /* *TvarsDpType */
3035: /* *si model= 1 + age + V3 + V2*age + V2 + V3*age */
3036: /* * nsd=1 (1) (2) */
3037: /* *TvarsD[nsd] 3 2 */
3038: /* *TnsdVar (3)=1 (2)=2 */
3039: /* *TvarsDind[nsd](=k) [1]=1 [2]=3 */
3040: /* *Tage[] [1]=2 [2]= 3 */
3041: /* *\/ */
3042: /* /\* cov[++k1]=nbcode[TvarsD[k]][codtabm(ij,k)]; *\/ */
3043: /* /\* 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)); *\/ */
3044: /* } */
3045: /* for (k=1; k<=nsq;k++) { /\* For single quantitative varying covariates only of the model *\/ */
3046: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3047: /* /\* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline *\/ */
3048: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
3049: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][resultmodel[nres][k1]] */
3050: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
3051: /* /\* 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]); *\/ */
3052: /* } */
3053: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
3054: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
3055: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3056: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
3057: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
3058: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3059: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
3060: /* } */
3061: /* /\* 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]); *\/ */
3062: /* } */
3063: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
3064: /* /\* 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]); *\/ */
3065: /* if(Dummy[Tvard[k][1]]==0){ */
3066: /* if(Dummy[Tvard[k][2]]==0){ */
3067: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3068: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3069: /* }else{ */
3070: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3071: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
3072: /* } */
3073: /* }else{ */
3074: /* if(Dummy[Tvard[k][2]]==0){ */
3075: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3076: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
3077: /* }else{ */
3078: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3079: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
3080: /* } */
3081: /* } */
3082: /* } /\* End product without age *\/ */
3083: /* ENd of old code */
1.138 brouard 3084: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
3085: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
3086: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 3087: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3088: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.319 brouard 3089: /* age and covariate values of ij are in 'cov' */
1.142 brouard 3090: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 3091:
1.126 brouard 3092: savm=oldm;
3093: oldm=newm;
1.209 brouard 3094:
3095: for(j=1; j<=nlstate; j++){
3096: max[j]=0.;
3097: min[j]=1.;
3098: }
3099: for(i=1;i<=nlstate;i++){
3100: sumnew=0;
3101: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
3102: for(j=1; j<=nlstate; j++){
3103: prlim[i][j]= newm[i][j]/(1-sumnew);
3104: max[j]=FMAX(max[j],prlim[i][j]);
3105: min[j]=FMIN(min[j],prlim[i][j]);
3106: }
3107: }
3108:
1.126 brouard 3109: maxmax=0.;
1.209 brouard 3110: for(j=1; j<=nlstate; j++){
3111: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
3112: maxmax=FMAX(maxmax,meandiff[j]);
3113: /* 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 3114: } /* j loop */
1.203 brouard 3115: *ncvyear= (int)age- (int)agefin;
1.208 brouard 3116: /* 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 3117: if(maxmax < ftolpl){
1.209 brouard 3118: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
3119: free_vector(min,1,nlstate);
3120: free_vector(max,1,nlstate);
3121: free_vector(meandiff,1,nlstate);
1.126 brouard 3122: return prlim;
3123: }
1.288 brouard 3124: } /* agefin loop */
1.208 brouard 3125: /* After some age loop it doesn't converge */
1.288 brouard 3126: if(!first){
3127: first=1;
3128: 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 3129: 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);
3130: }else if (first >=1 && first <10){
3131: 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);
3132: first++;
3133: }else if (first ==10){
3134: 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);
3135: 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");
3136: fprintf(ficlog,"Warning: the stable prevalence no convergence; too many cases, giving up noticing, even in log file\n");
3137: first++;
1.288 brouard 3138: }
3139:
1.209 brouard 3140: /* 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); */
3141: free_vector(min,1,nlstate);
3142: free_vector(max,1,nlstate);
3143: free_vector(meandiff,1,nlstate);
1.208 brouard 3144:
1.169 brouard 3145: return prlim; /* should not reach here */
1.126 brouard 3146: }
3147:
1.217 brouard 3148:
3149: /**** Back Prevalence limit (stable or period prevalence) ****************/
3150:
1.218 brouard 3151: /* 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) */
3152: /* 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 3153: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 3154: {
1.264 brouard 3155: /* 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 3156: matrix by transitions matrix until convergence is reached with precision ftolpl */
3157: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
3158: /* Wx is row vector: population in state 1, population in state 2, population dead */
3159: /* or prevalence in state 1, prevalence in state 2, 0 */
3160: /* newm is the matrix after multiplications, its rows are identical at a factor */
3161: /* Initial matrix pimij */
3162: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
3163: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
3164: /* 0, 0 , 1} */
3165: /*
3166: * and after some iteration: */
3167: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
3168: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
3169: /* 0, 0 , 1} */
3170: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
3171: /* {0.51571254859325999, 0.4842874514067399, */
3172: /* 0.51326036147820708, 0.48673963852179264} */
3173: /* If we start from prlim again, prlim tends to a constant matrix */
3174:
1.332 brouard 3175: int i, ii,j,k, k1;
1.247 brouard 3176: int first=0;
1.217 brouard 3177: double *min, *max, *meandiff, maxmax,sumnew=0.;
3178: /* double **matprod2(); */ /* test */
3179: double **out, cov[NCOVMAX+1], **bmij();
3180: double **newm;
1.218 brouard 3181: double **dnewm, **doldm, **dsavm; /* for use */
3182: double **oldm, **savm; /* for use */
3183:
1.217 brouard 3184: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
3185: int ncvloop=0;
3186:
3187: min=vector(1,nlstate);
3188: max=vector(1,nlstate);
3189: meandiff=vector(1,nlstate);
3190:
1.266 brouard 3191: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
3192: oldm=oldms; savm=savms;
3193:
3194: /* Starting with matrix unity */
3195: for (ii=1;ii<=nlstate+ndeath;ii++)
3196: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 3197: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3198: }
3199:
3200: cov[1]=1.;
3201:
3202: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3203: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 3204: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 3205: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
3206: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 3207: ncvloop++;
1.218 brouard 3208: newm=savm; /* oldm should be kept from previous iteration or unity at start */
3209: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 3210: /* Covariates have to be included here again */
3211: cov[2]=agefin;
1.319 brouard 3212: if(nagesqr==1){
1.217 brouard 3213: cov[3]= agefin*agefin;;
1.319 brouard 3214: }
1.332 brouard 3215: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3216: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3217: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.242 brouard 3218: }else{
1.332 brouard 3219: cov[2+nagesqr+k1]=precov[nres][k1];
1.242 brouard 3220: }
1.332 brouard 3221: }/* End of loop on model equation */
3222:
3223: /* Old code */
3224:
3225: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
3226: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
3227: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; */
3228: /* /\* 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)); *\/ */
3229: /* } */
3230: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
3231: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
3232: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
3233: /* /\* /\\* 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])]); *\\/ *\/ */
3234: /* /\* } *\/ */
3235: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
3236: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3237: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
3238: /* /\* 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]); *\/ */
3239: /* } */
3240: /* /\* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; *\/ */
3241: /* /\* for (k=1; k<=cptcovprod;k++) /\\* Useless *\\/ *\/ */
3242: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\\/ *\/ */
3243: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3244: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
3245: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age *\\/ ERROR ???*\/ */
3246: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
3247: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3248: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
3249: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3250: /* } */
3251: /* /\* 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]); *\/ */
3252: /* } */
3253: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
3254: /* /\* 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]); *\/ */
3255: /* if(Dummy[Tvard[k][1]]==0){ */
3256: /* if(Dummy[Tvard[k][2]]==0){ */
3257: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3258: /* }else{ */
3259: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3260: /* } */
3261: /* }else{ */
3262: /* if(Dummy[Tvard[k][2]]==0){ */
3263: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3264: /* }else{ */
3265: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3266: /* } */
3267: /* } */
3268: /* } */
1.217 brouard 3269:
3270: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
3271: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
3272: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
3273: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3274: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 3275: /* ij should be linked to the correct index of cov */
3276: /* age and covariate values ij are in 'cov', but we need to pass
3277: * ij for the observed prevalence at age and status and covariate
3278: * number: prevacurrent[(int)agefin][ii][ij]
3279: */
3280: /* 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 *\/ */
3281: /* 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 *\/ */
3282: 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 3283: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 3284: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
3285: /* for(i=1; i<=nlstate+ndeath; i++) { */
3286: /* printf("%d newm= ",i); */
3287: /* for(j=1;j<=nlstate+ndeath;j++) { */
3288: /* printf("%f ",newm[i][j]); */
3289: /* } */
3290: /* printf("oldm * "); */
3291: /* for(j=1;j<=nlstate+ndeath;j++) { */
3292: /* printf("%f ",oldm[i][j]); */
3293: /* } */
1.268 brouard 3294: /* printf(" bmmij "); */
1.266 brouard 3295: /* for(j=1;j<=nlstate+ndeath;j++) { */
3296: /* printf("%f ",pmmij[i][j]); */
3297: /* } */
3298: /* printf("\n"); */
3299: /* } */
3300: /* } */
1.217 brouard 3301: savm=oldm;
3302: oldm=newm;
1.266 brouard 3303:
1.217 brouard 3304: for(j=1; j<=nlstate; j++){
3305: max[j]=0.;
3306: min[j]=1.;
3307: }
3308: for(j=1; j<=nlstate; j++){
3309: for(i=1;i<=nlstate;i++){
1.234 brouard 3310: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
3311: bprlim[i][j]= newm[i][j];
3312: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
3313: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 3314: }
3315: }
1.218 brouard 3316:
1.217 brouard 3317: maxmax=0.;
3318: for(i=1; i<=nlstate; i++){
1.318 brouard 3319: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column, could be nan! */
1.217 brouard 3320: maxmax=FMAX(maxmax,meandiff[i]);
3321: /* 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 3322: } /* i loop */
1.217 brouard 3323: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 3324: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3325: if(maxmax < ftolpl){
1.220 brouard 3326: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3327: free_vector(min,1,nlstate);
3328: free_vector(max,1,nlstate);
3329: free_vector(meandiff,1,nlstate);
3330: return bprlim;
3331: }
1.288 brouard 3332: } /* agefin loop */
1.217 brouard 3333: /* After some age loop it doesn't converge */
1.288 brouard 3334: if(!first){
1.247 brouard 3335: first=1;
3336: 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\
3337: 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);
3338: }
3339: 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 3340: 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);
3341: /* 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); */
3342: free_vector(min,1,nlstate);
3343: free_vector(max,1,nlstate);
3344: free_vector(meandiff,1,nlstate);
3345:
3346: return bprlim; /* should not reach here */
3347: }
3348:
1.126 brouard 3349: /*************** transition probabilities ***************/
3350:
3351: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
3352: {
1.138 brouard 3353: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 3354: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 3355: model to the ncovmodel covariates (including constant and age).
3356: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3357: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3358: ncth covariate in the global vector x is given by the formula:
3359: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3360: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3361: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3362: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 3363: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 3364: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 3365: Sum on j ps[i][j] should equal to 1.
1.138 brouard 3366: */
3367: double s1, lnpijopii;
1.126 brouard 3368: /*double t34;*/
1.164 brouard 3369: int i,j, nc, ii, jj;
1.126 brouard 3370:
1.223 brouard 3371: for(i=1; i<= nlstate; i++){
3372: for(j=1; j<i;j++){
3373: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3374: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3375: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3376: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3377: }
3378: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3379: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3380: }
3381: for(j=i+1; j<=nlstate+ndeath;j++){
3382: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3383: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3384: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3385: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3386: }
3387: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3388: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3389: }
3390: }
1.218 brouard 3391:
1.223 brouard 3392: for(i=1; i<= nlstate; i++){
3393: s1=0;
3394: for(j=1; j<i; j++){
1.339 brouard 3395: /* printf("debug1 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 3396: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3397: }
3398: for(j=i+1; j<=nlstate+ndeath; j++){
1.339 brouard 3399: /* printf("debug2 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 3400: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3401: }
3402: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3403: ps[i][i]=1./(s1+1.);
3404: /* Computing other pijs */
3405: for(j=1; j<i; j++)
1.325 brouard 3406: ps[i][j]= exp(ps[i][j])*ps[i][i];/* Bug valgrind */
1.223 brouard 3407: for(j=i+1; j<=nlstate+ndeath; j++)
3408: ps[i][j]= exp(ps[i][j])*ps[i][i];
3409: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3410: } /* end i */
1.218 brouard 3411:
1.223 brouard 3412: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3413: for(jj=1; jj<= nlstate+ndeath; jj++){
3414: ps[ii][jj]=0;
3415: ps[ii][ii]=1;
3416: }
3417: }
1.294 brouard 3418:
3419:
1.223 brouard 3420: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3421: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3422: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3423: /* } */
3424: /* printf("\n "); */
3425: /* } */
3426: /* printf("\n ");printf("%lf ",cov[2]);*/
3427: /*
3428: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 3429: goto end;*/
1.266 brouard 3430: return ps; /* Pointer is unchanged since its call */
1.126 brouard 3431: }
3432:
1.218 brouard 3433: /*************** backward transition probabilities ***************/
3434:
3435: /* 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 ) */
3436: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
3437: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
3438: {
1.302 brouard 3439: /* 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 3440: * 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 3441: */
1.218 brouard 3442: int i, ii, j,k;
1.222 brouard 3443:
3444: double **out, **pmij();
3445: double sumnew=0.;
1.218 brouard 3446: double agefin;
1.292 brouard 3447: 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 3448: double **dnewm, **dsavm, **doldm;
3449: double **bbmij;
3450:
1.218 brouard 3451: doldm=ddoldms; /* global pointers */
1.222 brouard 3452: dnewm=ddnewms;
3453: dsavm=ddsavms;
1.318 brouard 3454:
3455: /* Debug */
3456: /* printf("Bmij ij=%d, cov[2}=%f\n", ij, cov[2]); */
1.222 brouard 3457: agefin=cov[2];
1.268 brouard 3458: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 3459: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 3460: the observed prevalence (with this covariate ij) at beginning of transition */
3461: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 3462:
3463: /* P_x */
1.325 brouard 3464: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm *//* Bug valgrind */
1.268 brouard 3465: /* outputs pmmij which is a stochastic matrix in row */
3466:
3467: /* Diag(w_x) */
1.292 brouard 3468: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 3469: sumnew=0.;
1.269 brouard 3470: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 3471: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.297 brouard 3472: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 3473: sumnew+=prevacurrent[(int)agefin][ii][ij];
3474: }
3475: if(sumnew >0.01){ /* At least some value in the prevalence */
3476: for (ii=1;ii<=nlstate+ndeath;ii++){
3477: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 3478: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 3479: }
3480: }else{
3481: for (ii=1;ii<=nlstate+ndeath;ii++){
3482: for (j=1;j<=nlstate+ndeath;j++)
3483: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
3484: }
3485: /* if(sumnew <0.9){ */
3486: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3487: /* } */
3488: }
3489: k3=0.0; /* We put the last diagonal to 0 */
3490: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3491: doldm[ii][ii]= k3;
3492: }
3493: /* End doldm, At the end doldm is diag[(w_i)] */
3494:
1.292 brouard 3495: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
3496: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 3497:
1.292 brouard 3498: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 3499: /* 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 3500: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3501: sumnew=0.;
1.222 brouard 3502: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3503: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3504: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3505: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3506: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3507: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3508: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3509: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3510: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3511: /* }else */
1.268 brouard 3512: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3513: } /*End ii */
3514: } /* 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 */
3515:
1.292 brouard 3516: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 3517: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3518: /* end bmij */
1.266 brouard 3519: return ps; /*pointer is unchanged */
1.218 brouard 3520: }
1.217 brouard 3521: /*************** transition probabilities ***************/
3522:
1.218 brouard 3523: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3524: {
3525: /* According to parameters values stored in x and the covariate's values stored in cov,
3526: computes the probability to be observed in state j being in state i by appying the
3527: model to the ncovmodel covariates (including constant and age).
3528: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3529: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3530: ncth covariate in the global vector x is given by the formula:
3531: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3532: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3533: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3534: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3535: Outputs ps[i][j] the probability to be observed in j being in j according to
3536: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3537: */
3538: double s1, lnpijopii;
3539: /*double t34;*/
3540: int i,j, nc, ii, jj;
3541:
1.234 brouard 3542: for(i=1; i<= nlstate; i++){
3543: for(j=1; j<i;j++){
3544: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3545: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3546: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3547: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3548: }
3549: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3550: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3551: }
3552: for(j=i+1; j<=nlstate+ndeath;j++){
3553: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3554: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3555: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3556: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3557: }
3558: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3559: }
3560: }
3561:
3562: for(i=1; i<= nlstate; i++){
3563: s1=0;
3564: for(j=1; j<i; j++){
3565: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3566: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3567: }
3568: for(j=i+1; j<=nlstate+ndeath; j++){
3569: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3570: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3571: }
3572: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3573: ps[i][i]=1./(s1+1.);
3574: /* Computing other pijs */
3575: for(j=1; j<i; j++)
3576: ps[i][j]= exp(ps[i][j])*ps[i][i];
3577: for(j=i+1; j<=nlstate+ndeath; j++)
3578: ps[i][j]= exp(ps[i][j])*ps[i][i];
3579: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3580: } /* end i */
3581:
3582: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3583: for(jj=1; jj<= nlstate+ndeath; jj++){
3584: ps[ii][jj]=0;
3585: ps[ii][ii]=1;
3586: }
3587: }
1.296 brouard 3588: /* Added for prevbcast */ /* Transposed matrix too */
1.234 brouard 3589: for(jj=1; jj<= nlstate+ndeath; jj++){
3590: s1=0.;
3591: for(ii=1; ii<= nlstate+ndeath; ii++){
3592: s1+=ps[ii][jj];
3593: }
3594: for(ii=1; ii<= nlstate; ii++){
3595: ps[ii][jj]=ps[ii][jj]/s1;
3596: }
3597: }
3598: /* Transposition */
3599: for(jj=1; jj<= nlstate+ndeath; jj++){
3600: for(ii=jj; ii<= nlstate+ndeath; ii++){
3601: s1=ps[ii][jj];
3602: ps[ii][jj]=ps[jj][ii];
3603: ps[jj][ii]=s1;
3604: }
3605: }
3606: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3607: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3608: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3609: /* } */
3610: /* printf("\n "); */
3611: /* } */
3612: /* printf("\n ");printf("%lf ",cov[2]);*/
3613: /*
3614: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3615: goto end;*/
3616: return ps;
1.217 brouard 3617: }
3618:
3619:
1.126 brouard 3620: /**************** Product of 2 matrices ******************/
3621:
1.145 brouard 3622: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3623: {
3624: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3625: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3626: /* in, b, out are matrice of pointers which should have been initialized
3627: before: only the contents of out is modified. The function returns
3628: a pointer to pointers identical to out */
1.145 brouard 3629: int i, j, k;
1.126 brouard 3630: for(i=nrl; i<= nrh; i++)
1.145 brouard 3631: for(k=ncolol; k<=ncoloh; k++){
3632: out[i][k]=0.;
3633: for(j=ncl; j<=nch; j++)
3634: out[i][k] +=in[i][j]*b[j][k];
3635: }
1.126 brouard 3636: return out;
3637: }
3638:
3639:
3640: /************* Higher Matrix Product ***************/
3641:
1.235 brouard 3642: 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 3643: {
1.336 brouard 3644: /* Already optimized with precov.
3645: 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 3646: 'nhstepm*hstepm*stepm' months (i.e. until
3647: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3648: nhstepm*hstepm matrices.
3649: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3650: (typically every 2 years instead of every month which is too big
3651: for the memory).
3652: Model is determined by parameters x and covariates have to be
3653: included manually here.
3654:
3655: */
3656:
1.330 brouard 3657: int i, j, d, h, k, k1;
1.131 brouard 3658: double **out, cov[NCOVMAX+1];
1.126 brouard 3659: double **newm;
1.187 brouard 3660: double agexact;
1.214 brouard 3661: double agebegin, ageend;
1.126 brouard 3662:
3663: /* Hstepm could be zero and should return the unit matrix */
3664: for (i=1;i<=nlstate+ndeath;i++)
3665: for (j=1;j<=nlstate+ndeath;j++){
3666: oldm[i][j]=(i==j ? 1.0 : 0.0);
3667: po[i][j][0]=(i==j ? 1.0 : 0.0);
3668: }
3669: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3670: for(h=1; h <=nhstepm; h++){
3671: for(d=1; d <=hstepm; d++){
3672: newm=savm;
3673: /* Covariates have to be included here again */
3674: cov[1]=1.;
1.214 brouard 3675: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3676: cov[2]=agexact;
1.319 brouard 3677: if(nagesqr==1){
1.227 brouard 3678: cov[3]= agexact*agexact;
1.319 brouard 3679: }
1.330 brouard 3680: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
3681: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
3682: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3683: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3684: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
3685: }else{
3686: cov[2+nagesqr+k1]=precov[nres][k1];
3687: }
3688: }/* End of loop on model equation */
3689: /* Old code */
3690: /* if( Dummy[k1]==0 && Typevar[k1]==0 ){ /\* Single dummy *\/ */
3691: /* /\* V(Tvarsel)=Tvalsel=Tresult[nres][pos](value); V(Tvresult[nres][pos] (variable): V(variable)=value) *\/ */
3692: /* /\* for (k=1; k<=nsd;k++) { /\\* For single dummy covariates only *\\/ *\/ */
3693: /* /\* /\\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\\/ *\/ */
3694: /* /\* codtabm(ij,k) (1 & (ij-1) >> (k-1))+1 *\/ */
3695: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3696: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3697: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
3698: /* /\* nsd 1 2 3 *\/ /\* Counting single dummies covar fixed or tv *\/ */
3699: /* /\*TvarsD[nsd] 4 3 1 *\/ /\* ID of single dummy cova fixed or timevary*\/ */
3700: /* /\*TvarsDind[k] 2 3 9 *\/ /\* position K of single dummy cova *\/ */
3701: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];or [codtabm(ij,TnsdVar[TvarsD[k]] *\/ */
3702: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
3703: /* /\* 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]])); *\/ */
3704: /* 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); */
3705: /* printf("hpxij new Dummy precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3706: /* }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /\* Single quantitative variables *\/ */
3707: /* /\* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline *\/ */
3708: /* cov[2+nagesqr+k1]=Tqresult[nres][resultmodel[nres][k1]]; */
3709: /* /\* for (k=1; k<=nsq;k++) { /\\* For single varying covariates only *\\/ *\/ */
3710: /* /\* /\\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\\/ *\/ */
3711: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
3712: /* 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]]); */
3713: /* printf("hpxij new Quanti precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3714: /* }else if( Dummy[k1]==2 ){ /\* For dummy with age product *\/ */
3715: /* /\* Tvar[k1] Variable in the age product age*V1 is 1 *\/ */
3716: /* /\* [Tinvresult[nres][V1] is its value in the resultline nres *\/ */
3717: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvar[k1]]*cov[2]; */
3718: /* 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]); */
3719: /* printf("hpxij new Dummy with age product precov[nres=%d][k1=%d]=%.4f * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
3720:
3721: /* /\* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; *\/ */
3722: /* /\* for (k=1; k<=cptcovage;k++){ /\\* For product with age V1+V1*age +V4 +age*V3 *\\/ *\/ */
3723: /* /\* 1+2 Tage[1]=2 TVar[2]=1 Dummy[2]=2, Tage[2]=4 TVar[4]=3 Dummy[4]=3 quant*\/ */
3724: /* /\* *\/ */
1.330 brouard 3725: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3726: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3727: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
1.332 brouard 3728: /* /\*cptcovage=2 1 2 *\/ */
3729: /* /\*Tage[k]= 5 8 *\/ */
3730: /* }else if( Dummy[k1]==3 ){ /\* For quant with age product *\/ */
3731: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
3732: /* 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]]); */
3733: /* printf("hpxij new Quanti with age product precov[nres=%d][k1=%d] * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
3734: /* /\* if(Dummy[Tage[k]]== 2){ /\\* dummy with age *\\/ *\/ */
3735: /* /\* /\\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\\* dummy with age *\\\/ *\\/ *\/ */
3736: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\\/ *\/ */
3737: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\\/ *\/ */
3738: /* /\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\/ */
3739: /* /\* 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); *\/ */
3740: /* /\* } else if(Dummy[Tage[k]]== 3){ /\\* quantitative with age *\\/ *\/ */
3741: /* /\* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; *\/ */
3742: /* /\* } *\/ */
3743: /* /\* 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]); *\/ */
3744: /* }else if(Typevar[k1]==2 ){ /\* For product (not with age) *\/ */
3745: /* /\* for (k=1; k<=cptcovprod;k++){ /\\* For product without age *\\/ *\/ */
3746: /* /\* /\\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\\/ *\/ */
3747: /* /\* /\\* k 1 2 3 4 5 6 7 8 9 *\\/ *\/ */
3748: /* /\* /\\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\\/ *\/ */
3749: /* /\* /\\*cptcovprod=1 1 2 *\\/ *\/ */
3750: /* /\* /\\*Tprod[]= 4 7 *\\/ *\/ */
3751: /* /\* /\\*Tvard[][1] 4 1 *\\/ *\/ */
3752: /* /\* /\\*Tvard[][2] 3 2 *\\/ *\/ */
1.330 brouard 3753:
1.332 brouard 3754: /* /\* 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])]); *\/ */
3755: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3756: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]]; */
3757: /* 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]]); */
3758: /* printf("hpxij new Product no age product precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3759:
3760: /* /\* if(Dummy[Tvardk[k1][1]]==0){ *\/ */
3761: /* /\* if(Dummy[Tvardk[k1][2]]==0){ /\\* Product of dummies *\\/ *\/ */
3762: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3763: /* /\* cov[2+nagesqr+k1]=Tinvresult[nres][Tvardk[k1][1]] * Tinvresult[nres][Tvardk[k1][2]]; *\/ */
3764: /* /\* 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]])]; *\/ */
3765: /* /\* }else{ /\\* Product of dummy by quantitative *\\/ *\/ */
3766: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,TnsdVar[Tvard[k][1]])] * Tqresult[nres][k]; *\/ */
3767: /* /\* cov[2+nagesqr+k1]=Tresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]]; *\/ */
3768: /* /\* } *\/ */
3769: /* /\* }else{ /\\* Product of quantitative by...*\\/ *\/ */
3770: /* /\* if(Dummy[Tvard[k][2]]==0){ /\\* quant by dummy *\\/ *\/ */
3771: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][Tvard[k][1]]; *\\/ *\/ */
3772: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
3773: /* /\* }else{ /\\* Product of two quant *\\/ *\/ */
3774: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\\/ *\/ */
3775: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
3776: /* /\* } *\/ */
3777: /* /\* }/\\*end of products quantitative *\\/ *\/ */
3778: /* }/\*end of products *\/ */
3779: /* } /\* End of loop on model equation *\/ */
1.235 brouard 3780: /* for (k=1; k<=cptcovn;k++) */
3781: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3782: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3783: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3784: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3785: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3786:
3787:
1.126 brouard 3788: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3789: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.319 brouard 3790: /* right multiplication of oldm by the current matrix */
1.126 brouard 3791: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3792: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3793: /* if((int)age == 70){ */
3794: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3795: /* for(i=1; i<=nlstate+ndeath; i++) { */
3796: /* printf("%d pmmij ",i); */
3797: /* for(j=1;j<=nlstate+ndeath;j++) { */
3798: /* printf("%f ",pmmij[i][j]); */
3799: /* } */
3800: /* printf(" oldm "); */
3801: /* for(j=1;j<=nlstate+ndeath;j++) { */
3802: /* printf("%f ",oldm[i][j]); */
3803: /* } */
3804: /* printf("\n"); */
3805: /* } */
3806: /* } */
1.126 brouard 3807: savm=oldm;
3808: oldm=newm;
3809: }
3810: for(i=1; i<=nlstate+ndeath; i++)
3811: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3812: po[i][j][h]=newm[i][j];
3813: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3814: }
1.128 brouard 3815: /*printf("h=%d ",h);*/
1.126 brouard 3816: } /* end h */
1.267 brouard 3817: /* printf("\n H=%d \n",h); */
1.126 brouard 3818: return po;
3819: }
3820:
1.217 brouard 3821: /************* Higher Back Matrix Product ***************/
1.218 brouard 3822: /* 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 3823: 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 3824: {
1.332 brouard 3825: /* For dummy covariates given in each resultline (for historical, computes the corresponding combination ij),
3826: computes the transition matrix starting at age 'age' over
1.217 brouard 3827: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3828: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3829: nhstepm*hstepm matrices.
3830: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3831: (typically every 2 years instead of every month which is too big
1.217 brouard 3832: for the memory).
1.218 brouard 3833: Model is determined by parameters x and covariates have to be
1.266 brouard 3834: included manually here. Then we use a call to bmij(x and cov)
3835: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3836: */
1.217 brouard 3837:
1.332 brouard 3838: int i, j, d, h, k, k1;
1.266 brouard 3839: double **out, cov[NCOVMAX+1], **bmij();
3840: double **newm, ***newmm;
1.217 brouard 3841: double agexact;
3842: double agebegin, ageend;
1.222 brouard 3843: double **oldm, **savm;
1.217 brouard 3844:
1.266 brouard 3845: newmm=po; /* To be saved */
3846: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3847: /* Hstepm could be zero and should return the unit matrix */
3848: for (i=1;i<=nlstate+ndeath;i++)
3849: for (j=1;j<=nlstate+ndeath;j++){
3850: oldm[i][j]=(i==j ? 1.0 : 0.0);
3851: po[i][j][0]=(i==j ? 1.0 : 0.0);
3852: }
3853: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3854: for(h=1; h <=nhstepm; h++){
3855: for(d=1; d <=hstepm; d++){
3856: newm=savm;
3857: /* Covariates have to be included here again */
3858: cov[1]=1.;
1.271 brouard 3859: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3860: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
1.318 brouard 3861: /* Debug */
3862: /* printf("hBxij age=%lf, agexact=%lf\n", age, agexact); */
1.217 brouard 3863: cov[2]=agexact;
1.332 brouard 3864: if(nagesqr==1){
1.222 brouard 3865: cov[3]= agexact*agexact;
1.332 brouard 3866: }
3867: /** New code */
3868: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3869: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3870: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.325 brouard 3871: }else{
1.332 brouard 3872: cov[2+nagesqr+k1]=precov[nres][k1];
1.325 brouard 3873: }
1.332 brouard 3874: }/* End of loop on model equation */
3875: /** End of new code */
3876: /** This was old code */
3877: /* for (k=1; k<=nsd;k++){ /\* For single dummy covariates only *\//\* cptcovn error *\/ */
3878: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
3879: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
3880: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])];/\* Bug valgrind *\/ */
3881: /* /\* 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)); *\/ */
3882: /* } */
3883: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
3884: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3885: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
3886: /* /\* 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]); *\/ */
3887: /* } */
3888: /* for (k=1; k<=cptcovage;k++){ /\* Should start at cptcovn+1 *\//\* For product with age *\/ */
3889: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age error!!!*\\/ *\/ */
3890: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
3891: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3892: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
3893: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3894: /* } */
3895: /* /\* 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]); *\/ */
3896: /* } */
3897: /* for (k=1; k<=cptcovprod;k++){ /\* Useless because included in cptcovn *\/ */
3898: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])]*nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3899: /* if(Dummy[Tvard[k][1]]==0){ */
3900: /* if(Dummy[Tvard[k][2]]==0){ */
3901: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][1])]; */
3902: /* }else{ */
3903: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3904: /* } */
3905: /* }else{ */
3906: /* if(Dummy[Tvard[k][2]]==0){ */
3907: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3908: /* }else{ */
3909: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3910: /* } */
3911: /* } */
3912: /* } */
3913: /* /\*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*\/ */
3914: /* /\*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*\/ */
3915: /** End of old code */
3916:
1.218 brouard 3917: /* Careful transposed matrix */
1.266 brouard 3918: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3919: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3920: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3921: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.325 brouard 3922: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);/* Bug valgrind */
1.217 brouard 3923: /* if((int)age == 70){ */
3924: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3925: /* for(i=1; i<=nlstate+ndeath; i++) { */
3926: /* printf("%d pmmij ",i); */
3927: /* for(j=1;j<=nlstate+ndeath;j++) { */
3928: /* printf("%f ",pmmij[i][j]); */
3929: /* } */
3930: /* printf(" oldm "); */
3931: /* for(j=1;j<=nlstate+ndeath;j++) { */
3932: /* printf("%f ",oldm[i][j]); */
3933: /* } */
3934: /* printf("\n"); */
3935: /* } */
3936: /* } */
3937: savm=oldm;
3938: oldm=newm;
3939: }
3940: for(i=1; i<=nlstate+ndeath; i++)
3941: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3942: po[i][j][h]=newm[i][j];
1.268 brouard 3943: /* if(h==nhstepm) */
3944: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3945: }
1.268 brouard 3946: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3947: } /* end h */
1.268 brouard 3948: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3949: return po;
3950: }
3951:
3952:
1.162 brouard 3953: #ifdef NLOPT
3954: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3955: double fret;
3956: double *xt;
3957: int j;
3958: myfunc_data *d2 = (myfunc_data *) pd;
3959: /* xt = (p1-1); */
3960: xt=vector(1,n);
3961: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3962:
3963: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3964: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3965: printf("Function = %.12lf ",fret);
3966: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3967: printf("\n");
3968: free_vector(xt,1,n);
3969: return fret;
3970: }
3971: #endif
1.126 brouard 3972:
3973: /*************** log-likelihood *************/
3974: double func( double *x)
3975: {
1.336 brouard 3976: int i, ii, j, k, mi, d, kk, kf=0;
1.226 brouard 3977: int ioffset=0;
1.339 brouard 3978: int ipos=0,iposold=0,ncovv=0;
3979:
1.340 brouard 3980: double cotvarv, cotvarvold;
1.226 brouard 3981: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3982: double **out;
3983: double lli; /* Individual log likelihood */
3984: int s1, s2;
1.228 brouard 3985: 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 3986:
1.226 brouard 3987: double bbh, survp;
3988: double agexact;
1.336 brouard 3989: double agebegin, ageend;
1.226 brouard 3990: /*extern weight */
3991: /* We are differentiating ll according to initial status */
3992: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3993: /*for(i=1;i<imx;i++)
3994: printf(" %d\n",s[4][i]);
3995: */
1.162 brouard 3996:
1.226 brouard 3997: ++countcallfunc;
1.162 brouard 3998:
1.226 brouard 3999: cov[1]=1.;
1.126 brouard 4000:
1.226 brouard 4001: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 4002: ioffset=0;
1.226 brouard 4003: if(mle==1){
4004: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4005: /* Computes the values of the ncovmodel covariates of the model
4006: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
4007: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
4008: to be observed in j being in i according to the model.
4009: */
1.243 brouard 4010: ioffset=2+nagesqr ;
1.233 brouard 4011: /* Fixed */
1.345 brouard 4012: for (kf=1; kf<=ncovf;kf++){ /* For each fixed covariate dummy or quant or prod */
1.319 brouard 4013: /* # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi */
4014: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
4015: /* 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 4016: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.336 brouard 4017: 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 4018: /* V1*V2 (7) TvarFind[2]=7, TvarFind[3]=9 */
1.234 brouard 4019: }
1.226 brouard 4020: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
1.319 brouard 4021: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
1.226 brouard 4022: has been calculated etc */
4023: /* For an individual i, wav[i] gives the number of effective waves */
4024: /* We compute the contribution to Likelihood of each effective transition
4025: mw[mi][i] is real wave of the mi th effectve wave */
4026: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
4027: s2=s[mw[mi+1][i]][i];
1.341 brouard 4028: 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 4029: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
4030: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
4031: */
1.336 brouard 4032: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
4033: /* Wave varying (but not age varying) */
1.339 brouard 4034: /* 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*\/ */
4035: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; but where is the crossproduct? *\/ */
4036: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
4037: /* } */
1.340 brouard 4038: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age )*/
4039: itv=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
4040: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
1.345 brouard 4041: if(FixedV[itv]!=0){ /* Not a fixed covariate */
1.341 brouard 4042: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]][i]; /* cotvar[wav][ncovcol+nqv+iv][i] */
1.340 brouard 4043: }else{ /* fixed covariate */
1.345 brouard 4044: 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 4045: }
1.339 brouard 4046: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 brouard 4047: cotvarvold=cotvarv;
4048: }else{ /* A second product */
4049: cotvarv=cotvarv*cotvarvold;
1.339 brouard 4050: }
4051: iposold=ipos;
1.340 brouard 4052: cov[ioffset+ipos]=cotvarv;
1.234 brouard 4053: }
1.339 brouard 4054: /* for products of time varying to be done */
1.234 brouard 4055: for (ii=1;ii<=nlstate+ndeath;ii++)
4056: for (j=1;j<=nlstate+ndeath;j++){
4057: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4058: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4059: }
1.336 brouard 4060:
4061: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4062: 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 4063: for(d=0; d<dh[mi][i]; d++){
4064: newm=savm;
4065: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4066: cov[2]=agexact;
4067: if(nagesqr==1)
4068: cov[3]= agexact*agexact; /* Should be changed here */
1.349 brouard 4069: /* for (kk=1; kk<=cptcovage;kk++) { */
4070: /* if(!FixedV[Tvar[Tage[kk]]]) */
4071: /* cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /\* Tage[kk] gives the data-covariate associated with age *\/ */
4072: /* else */
4073: /* 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) *\/ */
4074: /* } */
4075: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
4076: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
4077: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4078: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
4079: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
4080: }else{ /* fixed covariate */
4081: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
4082: }
4083: if(ipos!=iposold){ /* Not a product or first of a product */
4084: cotvarvold=cotvarv;
4085: }else{ /* A second product */
4086: cotvarv=cotvarv*cotvarvold;
4087: }
4088: iposold=ipos;
4089: cov[ioffset+ipos]=cotvarv*agexact;
4090: /* For products */
1.234 brouard 4091: }
1.349 brouard 4092:
1.234 brouard 4093: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4094: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4095: savm=oldm;
4096: oldm=newm;
4097: } /* end mult */
4098:
4099: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
4100: /* But now since version 0.9 we anticipate for bias at large stepm.
4101: * If stepm is larger than one month (smallest stepm) and if the exact delay
4102: * (in months) between two waves is not a multiple of stepm, we rounded to
4103: * the nearest (and in case of equal distance, to the lowest) interval but now
4104: * we keep into memory the bias bh[mi][i] and also the previous matrix product
4105: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
4106: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 4107: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
4108: * -stepm/2 to stepm/2 .
4109: * For stepm=1 the results are the same as for previous versions of Imach.
4110: * For stepm > 1 the results are less biased than in previous versions.
4111: */
1.234 brouard 4112: s1=s[mw[mi][i]][i];
4113: s2=s[mw[mi+1][i]][i];
4114: bbh=(double)bh[mi][i]/(double)stepm;
4115: /* bias bh is positive if real duration
4116: * is higher than the multiple of stepm and negative otherwise.
4117: */
4118: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
4119: if( s2 > nlstate){
4120: /* i.e. if s2 is a death state and if the date of death is known
4121: then the contribution to the likelihood is the probability to
4122: die between last step unit time and current step unit time,
4123: which is also equal to probability to die before dh
4124: minus probability to die before dh-stepm .
4125: In version up to 0.92 likelihood was computed
4126: as if date of death was unknown. Death was treated as any other
4127: health state: the date of the interview describes the actual state
4128: and not the date of a change in health state. The former idea was
4129: to consider that at each interview the state was recorded
4130: (healthy, disable or death) and IMaCh was corrected; but when we
4131: introduced the exact date of death then we should have modified
4132: the contribution of an exact death to the likelihood. This new
4133: contribution is smaller and very dependent of the step unit
4134: stepm. It is no more the probability to die between last interview
4135: and month of death but the probability to survive from last
4136: interview up to one month before death multiplied by the
4137: probability to die within a month. Thanks to Chris
4138: Jackson for correcting this bug. Former versions increased
4139: mortality artificially. The bad side is that we add another loop
4140: which slows down the processing. The difference can be up to 10%
4141: lower mortality.
4142: */
4143: /* If, at the beginning of the maximization mostly, the
4144: cumulative probability or probability to be dead is
4145: constant (ie = 1) over time d, the difference is equal to
4146: 0. out[s1][3] = savm[s1][3]: probability, being at state
4147: s1 at precedent wave, to be dead a month before current
4148: wave is equal to probability, being at state s1 at
4149: precedent wave, to be dead at mont of the current
4150: wave. Then the observed probability (that this person died)
4151: is null according to current estimated parameter. In fact,
4152: it should be very low but not zero otherwise the log go to
4153: infinity.
4154: */
1.183 brouard 4155: /* #ifdef INFINITYORIGINAL */
4156: /* lli=log(out[s1][s2] - savm[s1][s2]); */
4157: /* #else */
4158: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
4159: /* lli=log(mytinydouble); */
4160: /* else */
4161: /* lli=log(out[s1][s2] - savm[s1][s2]); */
4162: /* #endif */
1.226 brouard 4163: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4164:
1.226 brouard 4165: } else if ( s2==-1 ) { /* alive */
4166: for (j=1,survp=0. ; j<=nlstate; j++)
4167: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4168: /*survp += out[s1][j]; */
4169: lli= log(survp);
4170: }
1.336 brouard 4171: /* else if (s2==-4) { */
4172: /* for (j=3,survp=0. ; j<=nlstate; j++) */
4173: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
4174: /* lli= log(survp); */
4175: /* } */
4176: /* else if (s2==-5) { */
4177: /* for (j=1,survp=0. ; j<=2; j++) */
4178: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
4179: /* lli= log(survp); */
4180: /* } */
1.226 brouard 4181: else{
4182: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4183: /* 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 */
4184: }
4185: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
4186: /*if(lli ==000.0)*/
1.340 brouard 4187: /* 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 4188: ipmx +=1;
4189: sw += weight[i];
4190: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4191: /* if (lli < log(mytinydouble)){ */
4192: /* 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); */
4193: /* 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]); */
4194: /* } */
4195: } /* end of wave */
4196: } /* end of individual */
4197: } else if(mle==2){
4198: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.319 brouard 4199: ioffset=2+nagesqr ;
4200: for (k=1; k<=ncovf;k++)
4201: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];
1.226 brouard 4202: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 4203: for(k=1; k <= ncovv ; k++){
1.341 brouard 4204: 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 4205: }
1.226 brouard 4206: for (ii=1;ii<=nlstate+ndeath;ii++)
4207: for (j=1;j<=nlstate+ndeath;j++){
4208: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4209: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4210: }
4211: for(d=0; d<=dh[mi][i]; d++){
4212: newm=savm;
4213: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4214: cov[2]=agexact;
4215: if(nagesqr==1)
4216: cov[3]= agexact*agexact;
4217: for (kk=1; kk<=cptcovage;kk++) {
4218: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4219: }
4220: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4221: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4222: savm=oldm;
4223: oldm=newm;
4224: } /* end mult */
4225:
4226: s1=s[mw[mi][i]][i];
4227: s2=s[mw[mi+1][i]][i];
4228: bbh=(double)bh[mi][i]/(double)stepm;
4229: 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 */
4230: ipmx +=1;
4231: sw += weight[i];
4232: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4233: } /* end of wave */
4234: } /* end of individual */
4235: } else if(mle==3){ /* exponential inter-extrapolation */
4236: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4237: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4238: for(mi=1; mi<= wav[i]-1; mi++){
4239: for (ii=1;ii<=nlstate+ndeath;ii++)
4240: for (j=1;j<=nlstate+ndeath;j++){
4241: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4242: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4243: }
4244: for(d=0; d<dh[mi][i]; d++){
4245: newm=savm;
4246: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4247: cov[2]=agexact;
4248: if(nagesqr==1)
4249: cov[3]= agexact*agexact;
4250: for (kk=1; kk<=cptcovage;kk++) {
1.340 brouard 4251: if(!FixedV[Tvar[Tage[kk]]])
4252: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
4253: else
1.341 brouard 4254: 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 4255: }
4256: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4257: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4258: savm=oldm;
4259: oldm=newm;
4260: } /* end mult */
4261:
4262: s1=s[mw[mi][i]][i];
4263: s2=s[mw[mi+1][i]][i];
4264: bbh=(double)bh[mi][i]/(double)stepm;
4265: 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 */
4266: ipmx +=1;
4267: sw += weight[i];
4268: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4269: } /* end of wave */
4270: } /* end of individual */
4271: }else if (mle==4){ /* ml=4 no inter-extrapolation */
4272: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4273: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4274: for(mi=1; mi<= wav[i]-1; mi++){
4275: for (ii=1;ii<=nlstate+ndeath;ii++)
4276: for (j=1;j<=nlstate+ndeath;j++){
4277: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4278: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4279: }
4280: for(d=0; d<dh[mi][i]; d++){
4281: newm=savm;
4282: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4283: cov[2]=agexact;
4284: if(nagesqr==1)
4285: cov[3]= agexact*agexact;
4286: for (kk=1; kk<=cptcovage;kk++) {
4287: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4288: }
1.126 brouard 4289:
1.226 brouard 4290: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4291: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4292: savm=oldm;
4293: oldm=newm;
4294: } /* end mult */
4295:
4296: s1=s[mw[mi][i]][i];
4297: s2=s[mw[mi+1][i]][i];
4298: if( s2 > nlstate){
4299: lli=log(out[s1][s2] - savm[s1][s2]);
4300: } else if ( s2==-1 ) { /* alive */
4301: for (j=1,survp=0. ; j<=nlstate; j++)
4302: survp += out[s1][j];
4303: lli= log(survp);
4304: }else{
4305: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4306: }
4307: ipmx +=1;
4308: sw += weight[i];
4309: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.343 brouard 4310: /* 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 4311: } /* end of wave */
4312: } /* end of individual */
4313: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
4314: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4315: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4316: for(mi=1; mi<= wav[i]-1; mi++){
4317: for (ii=1;ii<=nlstate+ndeath;ii++)
4318: for (j=1;j<=nlstate+ndeath;j++){
4319: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4320: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4321: }
4322: for(d=0; d<dh[mi][i]; d++){
4323: newm=savm;
4324: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4325: cov[2]=agexact;
4326: if(nagesqr==1)
4327: cov[3]= agexact*agexact;
4328: for (kk=1; kk<=cptcovage;kk++) {
1.340 brouard 4329: if(!FixedV[Tvar[Tage[kk]]])
4330: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
4331: else
1.341 brouard 4332: 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 4333: }
1.126 brouard 4334:
1.226 brouard 4335: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4336: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4337: savm=oldm;
4338: oldm=newm;
4339: } /* end mult */
4340:
4341: s1=s[mw[mi][i]][i];
4342: s2=s[mw[mi+1][i]][i];
4343: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4344: ipmx +=1;
4345: sw += weight[i];
4346: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4347: /*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]);*/
4348: } /* end of wave */
4349: } /* end of individual */
4350: } /* End of if */
4351: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
4352: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
4353: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4354: return -l;
1.126 brouard 4355: }
4356:
4357: /*************** log-likelihood *************/
4358: double funcone( double *x)
4359: {
1.228 brouard 4360: /* Same as func but slower because of a lot of printf and if */
1.349 brouard 4361: int i, ii, j, k, mi, d, kk, kv=0, kf=0;
1.228 brouard 4362: int ioffset=0;
1.339 brouard 4363: int ipos=0,iposold=0,ncovv=0;
4364:
1.340 brouard 4365: double cotvarv, cotvarvold;
1.131 brouard 4366: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 4367: double **out;
4368: double lli; /* Individual log likelihood */
4369: double llt;
4370: int s1, s2;
1.228 brouard 4371: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
4372:
1.126 brouard 4373: double bbh, survp;
1.187 brouard 4374: double agexact;
1.214 brouard 4375: double agebegin, ageend;
1.126 brouard 4376: /*extern weight */
4377: /* We are differentiating ll according to initial status */
4378: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
4379: /*for(i=1;i<imx;i++)
4380: printf(" %d\n",s[4][i]);
4381: */
4382: cov[1]=1.;
4383:
4384: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 4385: ioffset=0;
4386: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.336 brouard 4387: /* Computes the values of the ncovmodel covariates of the model
4388: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
4389: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
4390: to be observed in j being in i according to the model.
4391: */
1.243 brouard 4392: /* ioffset=2+nagesqr+cptcovage; */
4393: ioffset=2+nagesqr;
1.232 brouard 4394: /* Fixed */
1.224 brouard 4395: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 4396: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
1.349 brouard 4397: 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 4398: /* printf("Debug3 TvarFind[%d]=%d",kf, TvarFind[kf]); */
4399: /* printf(" Tvar[TvarFind[kf]]=%d", Tvar[TvarFind[kf]]); */
4400: /* printf(" i=%d covar[Tvar[TvarFind[kf]]][i]=%f\n",i,covar[Tvar[TvarFind[kf]]][i]); */
1.335 brouard 4401: 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 4402: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
4403: /* cov[2+6]=covar[Tvar[6]][i]; */
4404: /* cov[2+6]=covar[2][i]; V2 */
4405: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
4406: /* cov[2+7]=covar[Tvar[7]][i]; */
4407: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
4408: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
4409: /* cov[2+9]=covar[Tvar[9]][i]; */
4410: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 4411: }
1.336 brouard 4412: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
4413: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
4414: has been calculated etc */
4415: /* For an individual i, wav[i] gives the number of effective waves */
4416: /* We compute the contribution to Likelihood of each effective transition
4417: mw[mi][i] is real wave of the mi th effectve wave */
4418: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
4419: s2=s[mw[mi+1][i]][i];
1.341 brouard 4420: And the iv th varying covariate in the DATA is the cotvar[mw[mi+1][i]][ncovcol+nqv+iv][i]
1.336 brouard 4421: */
4422: /* This part may be useless now because everythin should be in covar */
1.232 brouard 4423: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
4424: /* 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?)*\/ */
4425: /* } */
1.231 brouard 4426: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
4427: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
4428: /* } */
1.225 brouard 4429:
1.233 brouard 4430:
4431: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.339 brouard 4432: /* 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 */
4433: /* for(k=1; k <= ncovv ; k++){ /\* Varying covariates (single and product but no age )*\/ */
4434: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; *\/ */
4435: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
4436: /* } */
4437:
4438: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
4439: /* model V1+V3+age*V1+age*V3+V1*V3 */
4440: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
4441: /* TvarVV[1]=V3 (first time varying in the model equation, TvarVV[2]=V1 (in V1*V3) TvarVV[3]=3(V3) */
4442: /* We need the position of the time varying or product in the model */
4443: /* 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 */
4444: /* TvarVV gives the variable name */
1.340 brouard 4445: /* Other example V1 + V3 + V5 + age*V1 + age*V3 + age*V5 + V1*V3 + V3*V5 + V1*V5
4446: * k= 1 2 3 4 5 6 7 8 9
4447: * varying 1 2 3 4 5
4448: * ncovv 1 2 3 4 5 6 7 8
1.343 brouard 4449: * TvarVV[ncovv] V3 5 1 3 3 5 1 5
1.340 brouard 4450: * TvarVVind 2 3 7 7 8 8 9 9
4451: * TvarFind[k] 1 0 0 0 0 0 0 0 0
4452: */
1.345 brouard 4453: /* Other model ncovcol=5 nqv=0 ntv=3 nqtv=0 nlstate=3
1.349 brouard 4454: * 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 4455: * FixedV[ncovcol+qv+ntv+nqtv] V5
1.349 brouard 4456: * 3 V1 V2 V3 V4 V5 V6 V7 V8 V3*V2 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
4457: * 0 0 0 0 0 1 1 1 0, 0, 1,1, 1, 0, 1, 0, 1, 0, 1, 0}
4458: * 3 0 0 0 0 0 1 1 1 0, 1 1 1 1 1}
4459: * model= V2 + V3 + V4 + V6 + V7 + V6*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
4460: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
4461: * +age*V6*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4462: * model2= V2 + V3 + V4 + V6 + V7 + V3*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
4463: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
4464: * +age*V3*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4465: * model3= V2 + V3 + V4 + V6 + V7 + age*V3*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
4466: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
4467: * +V3*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4468: * kmodel 1 2 3 4 5 6 7 8 9 10 11
4469: * 12 13 14 15 16
4470: * 17 18 19 20 21
4471: * Tvar[kmodel] 2 3 4 6 7 9 10 11 12 13 14
4472: * 2 3 4 6 7
4473: * 9 11 12 13 14
4474: * cptcovage=5+5 total of covariates with age
4475: * Tage[cptcovage] age*V2=12 13 14 15 16
4476: *1 17 18 19 20 21 gives the position in model of covariates associated with age
4477: *3 Tage[cptcovage] age*V3*V2=6
4478: *3 age*V2=12 13 14 15 16
4479: *3 age*V6*V3=18 19 20 21
4480: * Tvar[Tage[cptcovage]] Tvar[12]=2 3 4 6 Tvar[16]=7(age*V7)
4481: * 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
4482: * 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
4483: * 3 Tvar[Tage[cptcovage]] Tvar[6]=9 Tvar[12]=2 3 4 6 Tvar[16]=7(age*V7)
4484: * 3 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14
4485: * 3 Tage[cptcovage] age*V3*V2=6 age*V2=12 age*V3 13 14 15 16
4486: * age*V6*V3=18 19 20 21 gives the position in model of covariates associated with age
4487: * 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
4488: * Tvar= {2, 3, 4, 6, 7,
4489: * 9, 10, 11, 12, 13, 14,
4490: * Tvar[12]=2, 3, 4, 6, 7,
4491: * Tvar[17]=9, 11, 12, 13, 14}
4492: * Typevar[1]@21 = {0, 0, 0, 0, 0,
4493: * 2, 2, 2, 2, 2, 2,
4494: * 3 3, 2, 2, 2, 2, 2,
4495: * 1, 1, 1, 1, 1,
4496: * 3, 3, 3, 3, 3}
4497: * 3 2, 3, 3, 3, 3}
4498: * 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
4499: * p Tprod[1]@21 {6, 7, 8, 9, 10, 11, 0 <repeats 15 times>}
4500: * 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}
4501: * 3 Tprod[1]@21 {17, 7, 8, 9, 10, 11, 0 <repeats 15 times>}
4502: * cptcovprod=11 (6+5)
4503: * FixedV[Tvar[Tage[cptcovage]]]] FixedV[2]=0 FixedV[3]=0 0 1 (age*V7)Tvar[16]=1 FixedV[absolute] not [kmodel]
4504: * FixedV[Tvar[17]=FixedV[age*V6*V2]=FixedV[9]=1 1 1 1 1
4505: * 3 FixedV[Tvar[17]=FixedV[age*V3*V2]=FixedV[9]=0 [11]=1 1 1 1
4506: * FixedV[] V1=0 V2=0 V3=0 v4=0 V5=0 V6=1 V7=1 v8=1 OK then model dependent
4507: * 9=1 [V7*V2]=[10]=1 11=1 12=1 13=1 14=1
4508: * 3 9=0 [V7*V2]=[10]=1 11=1 12=1 13=1 14=1
4509: * cptcovdageprod=5 for gnuplot printing
4510: * cptcovprodvage=6
4511: * ncova=15 1 2 3 4 5
4512: * 6 7 8 9 10 11 12 13 14 15
4513: * TvarA 2 3 4 6 7
4514: * 6 2 6 7 7 3 6 4 7 4
4515: * TvaAind 12 12 13 13 14 14 15 15 16 16
1.345 brouard 4516: * ncovf 1 2 3
1.349 brouard 4517: * V6 V7 V6*V2 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
4518: * ncovvt=14 1 2 3 4 5 6 7 8 9 10 11 12 13 14
4519: * TvarVV[1]@14 = itv {V6=6, 7, V6*V2=6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
4520: * TvarVVind[1]@14= {4, 5, 6, 6, 7, 7, 8, 8, 9, 9, 10, 10, 11, 11}
4521: * 3 ncovvt=12 V6 V7 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
4522: * 3 TvarVV[1]@12 = itv {6, 7, V7*V2=7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
4523: * 3 1 2 3 4 5 6 7 8 9 10 11 12
4524: * TvarVVind[1]@12= {V6 is in k=4, 5, 7,(4isV2)=7, 8, 8, 9, 9, 10,10, 11,11}TvarVVind[12]=k=11
4525: * TvarV 6, 7, 9, 10, 11, 12, 13, 14
4526: * 3 cptcovprodvage=6
4527: * 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
4528: * 3 TvarAVVA[1]@15= itva 3 2 2 3 4 6 7 6 3 7 3 6 4 7 4
4529: * 3 ncovta 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
4530: * TvarAVVAind[1]@15= V3 is in k=2 1 1 2 3 4 5 4,2 5,2, 4,3 5 3}TvarVVAind[]
4531: * TvarAVVAind[1]@15= V3 is in k=6 6 12 13 14 15 16 18 18 19,19, 20,20 21,21}TvarVVAind[]
4532: * 3 ncovvta=10 +age*V6 + age*V7 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4533: * 3 we want to compute =cotvar[mw[mi][i]][TvarVVA[ncovva]][i] at position TvarVVAind[ncovva]
4534: * 3 TvarVVA[1]@10= itva 6 7 6 3 7 3 6 4 7 4
4535: * 3 ncovva 1 2 3 4 5 6 7 8 9 10
4536: * TvarVVAind[1]@10= V6 is in k=4 5 8,8 9, 9, 10,10 11 11}TvarVVAind[]
4537: * TvarVVAind[1]@10= 15 16 18,18 19,19, 20,20 21 21}TvarVVAind[]
4538: * TvarVA V3*V2=6 6 , 1, 2, 11, 12, 13, 14
1.345 brouard 4539: * TvarFind[1]@14= {1, 2, 3, 0 <repeats 12 times>}
1.349 brouard 4540: * Tvar[1]@21= {2, 3, 4, 6, 7, 9, 10, 11, 12, 13, 14,
4541: * 2, 3, 4, 6, 7,
4542: * 6, 8, 9, 10, 11}
1.345 brouard 4543: * TvarFind[itv] 0 0 0
4544: * FixedV[itv] 1 1 1 0 1 0 1 0 1 0 0
4545: * Tvar[TvarFind[ncovf]]=[1]=2 [2]=3 [4]=4
4546: * Tvar[TvarFind[itv]] [0]=? ?ncovv 1 à ncovvt]
4547: * Not a fixed cotvar[mw][itv][i] 6 7 6 2 7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
1.349 brouard 4548: * fixed covar[itv] [6] [7] [6][2]
1.345 brouard 4549: */
4550:
1.349 brouard 4551: 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 */
4552: 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 4553: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
1.345 brouard 4554: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
4555: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
4556: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
1.340 brouard 4557: }else{ /* fixed covariate */
1.345 brouard 4558: /* 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 4559: cotvarv=covar[itv][i]; /* Good: In V6*V3, 3 is fixed at position of the data */
1.340 brouard 4560: }
1.339 brouard 4561: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 brouard 4562: cotvarvold=cotvarv;
4563: }else{ /* A second product */
4564: cotvarv=cotvarv*cotvarvold;
1.339 brouard 4565: }
4566: iposold=ipos;
1.340 brouard 4567: cov[ioffset+ipos]=cotvarv;
1.339 brouard 4568: /* For products */
4569: }
4570: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates single *\/ */
4571: /* iv=TvarVDind[itv]; /\* iv, position in the model equation of time varying covariate itv *\/ */
4572: /* /\* "V1+V3+age*V1+age*V3+V1*V3" with V3 time varying *\/ */
4573: /* /\* 1 2 3 4 5 *\/ */
4574: /* /\*itv 1 *\/ */
4575: /* /\* TvarVInd[1]= 2 *\/ */
4576: /* /\* iv= Tvar[Tmodelind[itv]]-ncovcol-nqv; /\\* Counting the # varying covariate from 1 to ntveff *\\/ *\/ */
4577: /* /\* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; *\/ */
4578: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; *\/ */
4579: /* /\* k=ioffset-2-nagesqr-cptcovage+itv; /\\* position in simple model *\\/ *\/ */
4580: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; *\/ */
4581: /* cov[ioffset+iv]=cotvar[mw[mi][i]][itv][i]; */
4582: /* /\* 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]); *\/ */
4583: /* } */
1.232 brouard 4584: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 4585: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4586: /* /\* 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]); *\/ */
4587: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 4588: /* } */
1.126 brouard 4589: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 4590: for (j=1;j<=nlstate+ndeath;j++){
4591: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4592: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4593: }
1.214 brouard 4594:
4595: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4596: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
4597: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 4598: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 4599: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
4600: and mw[mi+1][i]. dh depends on stepm.*/
4601: newm=savm;
1.247 brouard 4602: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 4603: cov[2]=agexact;
4604: if(nagesqr==1)
4605: cov[3]= agexact*agexact;
1.349 brouard 4606: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
4607: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
4608: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4609: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
4610: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
4611: /* printf("DEBUG ncovva=%d, Varying TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4612: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
4613: }else{ /* fixed covariate */
4614: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
4615: /* printf("DEBUG ncovva=%d, Fixed TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4616: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
4617: }
4618: if(ipos!=iposold){ /* Not a product or first of a product */
4619: cotvarvold=cotvarv;
4620: }else{ /* A second product */
4621: /* printf("DEBUG * \n"); */
4622: cotvarv=cotvarv*cotvarvold;
4623: }
4624: iposold=ipos;
4625: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
4626: cov[ioffset+ipos]=cotvarv*agexact;
4627: /* For products */
1.242 brouard 4628: }
1.349 brouard 4629:
1.242 brouard 4630: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
4631: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
4632: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4633: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4634: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
4635: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
4636: savm=oldm;
4637: oldm=newm;
1.126 brouard 4638: } /* end mult */
1.336 brouard 4639: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
4640: /* But now since version 0.9 we anticipate for bias at large stepm.
4641: * If stepm is larger than one month (smallest stepm) and if the exact delay
4642: * (in months) between two waves is not a multiple of stepm, we rounded to
4643: * the nearest (and in case of equal distance, to the lowest) interval but now
4644: * we keep into memory the bias bh[mi][i] and also the previous matrix product
4645: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
4646: * probability in order to take into account the bias as a fraction of the way
4647: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
4648: * -stepm/2 to stepm/2 .
4649: * For stepm=1 the results are the same as for previous versions of Imach.
4650: * For stepm > 1 the results are less biased than in previous versions.
4651: */
1.126 brouard 4652: s1=s[mw[mi][i]][i];
4653: s2=s[mw[mi+1][i]][i];
1.217 brouard 4654: /* if(s2==-1){ */
1.268 brouard 4655: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 4656: /* /\* exit(1); *\/ */
4657: /* } */
1.126 brouard 4658: bbh=(double)bh[mi][i]/(double)stepm;
4659: /* bias is positive if real duration
4660: * is higher than the multiple of stepm and negative otherwise.
4661: */
4662: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 4663: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4664: } else if ( s2==-1 ) { /* alive */
1.242 brouard 4665: for (j=1,survp=0. ; j<=nlstate; j++)
4666: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4667: lli= log(survp);
1.126 brouard 4668: }else if (mle==1){
1.242 brouard 4669: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 4670: } else if(mle==2){
1.242 brouard 4671: 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 4672: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 4673: 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 4674: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 4675: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 4676: } else{ /* mle=0 back to 1 */
1.242 brouard 4677: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4678: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 4679: } /* End of if */
4680: ipmx +=1;
4681: sw += weight[i];
4682: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.342 brouard 4683: /* Printing covariates values for each contribution for checking */
1.343 brouard 4684: /* 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 4685: if(globpr){
1.246 brouard 4686: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 4687: %11.6f %11.6f %11.6f ", \
1.242 brouard 4688: 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 4689: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.343 brouard 4690: /* printf("%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\ */
4691: /* %11.6f %11.6f %11.6f ", \ */
4692: /* num[i], agebegin, ageend, i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],weight[i]*gipmx/gsw, */
4693: /* 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2])); */
1.242 brouard 4694: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
4695: llt +=ll[k]*gipmx/gsw;
4696: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
1.335 brouard 4697: /* printf(" %10.6f",-ll[k]*gipmx/gsw); */
1.242 brouard 4698: }
1.343 brouard 4699: fprintf(ficresilk," %10.6f ", -llt);
1.335 brouard 4700: /* printf(" %10.6f\n", -llt); */
1.342 brouard 4701: /* if(debugILK){ /\* debugILK is set by a #d in a comment line *\/ */
1.343 brouard 4702: /* fprintf(ficresilk,"%09ld ", num[i]); */ /* not necessary */
4703: for (kf=1; kf<=ncovf;kf++){ /* Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */
4704: fprintf(ficresilk," %g",covar[Tvar[TvarFind[kf]]][i]);
4705: }
4706: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age) including individual from products */
4707: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4708: if(ipos!=iposold){ /* Not a product or first of a product */
4709: fprintf(ficresilk," %g",cov[ioffset+ipos]);
4710: /* printf(" %g",cov[ioffset+ipos]); */
4711: }else{
4712: fprintf(ficresilk,"*");
4713: /* printf("*"); */
1.342 brouard 4714: }
1.343 brouard 4715: iposold=ipos;
4716: }
1.349 brouard 4717: /* for (kk=1; kk<=cptcovage;kk++) { */
4718: /* if(!FixedV[Tvar[Tage[kk]]]){ */
4719: /* fprintf(ficresilk," %g*age",covar[Tvar[Tage[kk]]][i]); */
4720: /* /\* printf(" %g*age",covar[Tvar[Tage[kk]]][i]); *\/ */
4721: /* }else{ */
4722: /* fprintf(ficresilk," %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */
4723: /* /\* printf(" %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/\\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\\/ *\/ */
4724: /* } */
4725: /* } */
4726: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
4727: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
4728: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4729: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
4730: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
4731: /* printf("DEBUG ncovva=%d, Varying TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4732: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
4733: }else{ /* fixed covariate */
4734: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
4735: /* printf("DEBUG ncovva=%d, Fixed TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4736: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
4737: }
4738: if(ipos!=iposold){ /* Not a product or first of a product */
4739: cotvarvold=cotvarv;
4740: }else{ /* A second product */
4741: /* printf("DEBUG * \n"); */
4742: cotvarv=cotvarv*cotvarvold;
1.342 brouard 4743: }
1.349 brouard 4744: cotvarv=cotvarv*agexact;
4745: fprintf(ficresilk," %g*age",cotvarv);
4746: iposold=ipos;
4747: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
4748: cov[ioffset+ipos]=cotvarv;
4749: /* For products */
1.343 brouard 4750: }
4751: /* printf("\n"); */
1.342 brouard 4752: /* } /\* End debugILK *\/ */
4753: fprintf(ficresilk,"\n");
4754: } /* End if globpr */
1.335 brouard 4755: } /* end of wave */
4756: } /* end of individual */
4757: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
1.232 brouard 4758: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
1.335 brouard 4759: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4760: if(globpr==0){ /* First time we count the contributions and weights */
4761: gipmx=ipmx;
4762: gsw=sw;
4763: }
1.343 brouard 4764: return -l;
1.126 brouard 4765: }
4766:
4767:
4768: /*************** function likelione ***********/
1.292 brouard 4769: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 4770: {
4771: /* This routine should help understanding what is done with
4772: the selection of individuals/waves and
4773: to check the exact contribution to the likelihood.
4774: Plotting could be done.
1.342 brouard 4775: */
4776: void pstamp(FILE *ficres);
1.343 brouard 4777: int k, kf, kk, kvar, ncovv, iposold, ipos;
1.126 brouard 4778:
4779: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 4780: strcpy(fileresilk,"ILK_");
1.202 brouard 4781: strcat(fileresilk,fileresu);
1.126 brouard 4782: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
4783: printf("Problem with resultfile: %s\n", fileresilk);
4784: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
4785: }
1.342 brouard 4786: pstamp(ficresilk);fprintf(ficresilk,"# model=1+age+%s\n",model);
1.214 brouard 4787: 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");
4788: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 4789: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
4790: for(k=1; k<=nlstate; k++)
4791: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
1.342 brouard 4792: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total) ");
4793:
4794: /* if(debugILK){ /\* debugILK is set by a #d in a comment line *\/ */
4795: for(kf=1;kf <= ncovf; kf++){
4796: fprintf(ficresilk,"V%d",Tvar[TvarFind[kf]]);
4797: /* printf("V%d",Tvar[TvarFind[kf]]); */
4798: }
4799: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){
1.343 brouard 4800: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
1.342 brouard 4801: if(ipos!=iposold){ /* Not a product or first of a product */
4802: /* printf(" %d",ipos); */
4803: fprintf(ficresilk," V%d",TvarVV[ncovv]);
4804: }else{
4805: /* printf("*"); */
4806: fprintf(ficresilk,"*");
1.343 brouard 4807: }
1.342 brouard 4808: iposold=ipos;
4809: }
4810: for (kk=1; kk<=cptcovage;kk++) {
4811: if(!FixedV[Tvar[Tage[kk]]]){
4812: /* printf(" %d*age(Fixed)",Tvar[Tage[kk]]); */
4813: fprintf(ficresilk," %d*age(Fixed)",Tvar[Tage[kk]]);
4814: }else{
4815: fprintf(ficresilk," %d*age(Varying)",Tvar[Tage[kk]]);/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
4816: /* printf(" %d*age(Varying)",Tvar[Tage[kk]]);/\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */
4817: }
4818: }
4819: /* } /\* End if debugILK *\/ */
4820: /* printf("\n"); */
4821: fprintf(ficresilk,"\n");
4822: } /* End glogpri */
1.126 brouard 4823:
1.292 brouard 4824: *fretone=(*func)(p);
1.126 brouard 4825: if(*globpri !=0){
4826: fclose(ficresilk);
1.205 brouard 4827: if (mle ==0)
4828: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
4829: else if(mle >=1)
4830: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
4831: 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 4832: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 4833:
1.207 brouard 4834: 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 4835: <img src=\"%s-ori.png\">\n",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4836: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.343 brouard 4837: <img src=\"%s-dest.png\">\n",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
4838:
4839: for (k=1; k<= nlstate ; k++) {
4840: 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 \
4841: <img src=\"%s-p%dj.png\">\n",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
4842: for(kf=1; kf <= ncovf; kf++){ /* For each simple dummy covariate of the model */
1.350 ! brouard 4843: kvar=Tvar[TvarFind[kf]]; /* variable */
! 4844: 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]]);
! 4845: 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);
! 4846: fprintf(fichtm,"<img src=\"%s-p%dj-%d.png\">",subdirf2(optionfilefiname,"ILK_"),k,Tvar[TvarFind[kf]]);
1.343 brouard 4847: }
4848: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Loop on the time varying extended covariates (with extension of Vn*Vm */
4849: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
4850: kvar=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
4851: /* 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]); */
4852: if(ipos!=iposold){ /* Not a product or first of a product */
4853: /* fprintf(ficresilk," V%d",TvarVV[ncovv]); */
4854: /* printf(" DebugILK fichtm ipos=%d != iposold=%d\n", ipos, iposold); */
4855: 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) */
4856: 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> \
4857: <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);
4858: } /* End only for dummies time varying (single?) */
4859: }else{ /* Useless product */
4860: /* printf("*"); */
4861: /* fprintf(ficresilk,"*"); */
4862: }
4863: iposold=ipos;
4864: } /* For each time varying covariate */
4865: } /* End loop on states */
4866:
4867: /* if(debugILK){ */
4868: /* for(kf=1; kf <= ncovf; kf++){ /\* For each simple dummy covariate of the model *\/ */
4869: /* /\* kvar=Tvar[TvarFind[kf]]; *\/ /\* variable *\/ */
4870: /* for (k=1; k<= nlstate ; k++) { */
4871: /* 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> \ */
4872: /* <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]]); */
4873: /* } */
4874: /* } */
4875: /* for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /\* Loop on the time varying extended covariates (with extension of Vn*Vm *\/ */
4876: /* ipos=TvarVVind[ncovv]; /\* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate *\/ */
4877: /* kvar=TvarVV[ncovv]; /\* TvarVV={3, 1, 3} gives the name of each varying covariate *\/ */
4878: /* /\* 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]); *\/ */
4879: /* if(ipos!=iposold){ /\* Not a product or first of a product *\/ */
4880: /* /\* fprintf(ficresilk," V%d",TvarVV[ncovv]); *\/ */
4881: /* /\* printf(" DebugILK fichtm ipos=%d != iposold=%d\n", ipos, iposold); *\/ */
4882: /* 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) *\/ */
4883: /* for (k=1; k<= nlstate ; k++) { */
4884: /* 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> \ */
4885: /* <img src=\"%s-p%dj-%d.png\">",k,k,kvar,kvar,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,kvar); */
4886: /* } /\* End state *\/ */
4887: /* } /\* End only for dummies time varying (single?) *\/ */
4888: /* }else{ /\* Useless product *\/ */
4889: /* /\* printf("*"); *\/ */
4890: /* /\* fprintf(ficresilk,"*"); *\/ */
4891: /* } */
4892: /* iposold=ipos; */
4893: /* } /\* For each time varying covariate *\/ */
4894: /* }/\* End debugILK *\/ */
1.207 brouard 4895: fflush(fichtm);
1.343 brouard 4896: }/* End globpri */
1.126 brouard 4897: return;
4898: }
4899:
4900:
4901: /*********** Maximum Likelihood Estimation ***************/
4902:
4903: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
4904: {
1.319 brouard 4905: int i,j,k, jk, jkk=0, iter=0;
1.126 brouard 4906: double **xi;
4907: double fret;
4908: double fretone; /* Only one call to likelihood */
4909: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 4910:
4911: #ifdef NLOPT
4912: int creturn;
4913: nlopt_opt opt;
4914: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
4915: double *lb;
4916: double minf; /* the minimum objective value, upon return */
4917: double * p1; /* Shifted parameters from 0 instead of 1 */
4918: myfunc_data dinst, *d = &dinst;
4919: #endif
4920:
4921:
1.126 brouard 4922: xi=matrix(1,npar,1,npar);
4923: for (i=1;i<=npar;i++)
4924: for (j=1;j<=npar;j++)
4925: xi[i][j]=(i==j ? 1.0 : 0.0);
4926: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 4927: strcpy(filerespow,"POW_");
1.126 brouard 4928: strcat(filerespow,fileres);
4929: if((ficrespow=fopen(filerespow,"w"))==NULL) {
4930: printf("Problem with resultfile: %s\n", filerespow);
4931: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
4932: }
4933: fprintf(ficrespow,"# Powell\n# iter -2*LL");
4934: for (i=1;i<=nlstate;i++)
4935: for(j=1;j<=nlstate+ndeath;j++)
4936: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
4937: fprintf(ficrespow,"\n");
1.162 brouard 4938: #ifdef POWELL
1.319 brouard 4939: #ifdef LINMINORIGINAL
4940: #else /* LINMINORIGINAL */
4941:
4942: flatdir=ivector(1,npar);
4943: for (j=1;j<=npar;j++) flatdir[j]=0;
4944: #endif /*LINMINORIGINAL */
4945:
4946: #ifdef FLATSUP
4947: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4948: /* reorganizing p by suppressing flat directions */
4949: for(i=1, jk=1; i <=nlstate; i++){
4950: for(k=1; k <=(nlstate+ndeath); k++){
4951: if (k != i) {
4952: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4953: if(flatdir[jk]==1){
4954: printf(" To be skipped %d%d flatdir[%d]=%d ",i,k,jk, flatdir[jk]);
4955: }
4956: for(j=1; j <=ncovmodel; j++){
4957: printf("%12.7f ",p[jk]);
4958: jk++;
4959: }
4960: printf("\n");
4961: }
4962: }
4963: }
4964: /* skipping */
4965: /* for(i=1, jk=1, jkk=1;(flatdir[jk]==0)&& (i <=nlstate); i++){ */
4966: for(i=1, jk=1, jkk=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 jk=%d p[%d] ",i,k,jk, flatdir[jk],jk, jk);
4972: for(j=1; j <=ncovmodel; jk++,j++){
4973: printf(" p[%d]=%12.7f",jk, p[jk]);
4974: /*q[jjk]=p[jk];*/
4975: }
4976: }else{
4977: printf(" To be kept %d%d flatdir[%d]=%d jk=%d q[%d]=p[%d] ",i,k,jk, flatdir[jk],jk, jkk, jk);
4978: for(j=1; j <=ncovmodel; jk++,jkk++,j++){
4979: printf(" p[%d]=%12.7f=q[%d]",jk, p[jk],jkk);
4980: /*q[jjk]=p[jk];*/
4981: }
4982: }
4983: printf("\n");
4984: }
4985: fflush(stdout);
4986: }
4987: }
4988: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4989: #else /* FLATSUP */
1.126 brouard 4990: powell(p,xi,npar,ftol,&iter,&fret,func);
1.319 brouard 4991: #endif /* FLATSUP */
4992:
4993: #ifdef LINMINORIGINAL
4994: #else
4995: free_ivector(flatdir,1,npar);
4996: #endif /* LINMINORIGINAL*/
4997: #endif /* POWELL */
1.126 brouard 4998:
1.162 brouard 4999: #ifdef NLOPT
5000: #ifdef NEWUOA
5001: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
5002: #else
5003: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
5004: #endif
5005: lb=vector(0,npar-1);
5006: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
5007: nlopt_set_lower_bounds(opt, lb);
5008: nlopt_set_initial_step1(opt, 0.1);
5009:
5010: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
5011: d->function = func;
5012: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
5013: nlopt_set_min_objective(opt, myfunc, d);
5014: nlopt_set_xtol_rel(opt, ftol);
5015: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
5016: printf("nlopt failed! %d\n",creturn);
5017: }
5018: else {
5019: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
5020: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
5021: iter=1; /* not equal */
5022: }
5023: nlopt_destroy(opt);
5024: #endif
1.319 brouard 5025: #ifdef FLATSUP
5026: /* npared = npar -flatd/ncovmodel; */
5027: /* xired= matrix(1,npared,1,npared); */
5028: /* paramred= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); */
5029: /* powell(pred,xired,npared,ftol,&iter,&fret,flatdir,func); */
5030: /* free_matrix(xire,1,npared,1,npared); */
5031: #else /* FLATSUP */
5032: #endif /* FLATSUP */
1.126 brouard 5033: free_matrix(xi,1,npar,1,npar);
5034: fclose(ficrespow);
1.203 brouard 5035: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
5036: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 5037: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 5038:
5039: }
5040:
5041: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 5042: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 5043: {
5044: double **a,**y,*x,pd;
1.203 brouard 5045: /* double **hess; */
1.164 brouard 5046: int i, j;
1.126 brouard 5047: int *indx;
5048:
5049: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 5050: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 5051: void lubksb(double **a, int npar, int *indx, double b[]) ;
5052: void ludcmp(double **a, int npar, int *indx, double *d) ;
5053: double gompertz(double p[]);
1.203 brouard 5054: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 5055:
5056: printf("\nCalculation of the hessian matrix. Wait...\n");
5057: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
5058: for (i=1;i<=npar;i++){
1.203 brouard 5059: printf("%d-",i);fflush(stdout);
5060: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 5061:
5062: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
5063:
5064: /* printf(" %f ",p[i]);
5065: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
5066: }
5067:
5068: for (i=1;i<=npar;i++) {
5069: for (j=1;j<=npar;j++) {
5070: if (j>i) {
1.203 brouard 5071: printf(".%d-%d",i,j);fflush(stdout);
5072: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
5073: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 5074:
5075: hess[j][i]=hess[i][j];
5076: /*printf(" %lf ",hess[i][j]);*/
5077: }
5078: }
5079: }
5080: printf("\n");
5081: fprintf(ficlog,"\n");
5082:
5083: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
5084: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
5085:
5086: a=matrix(1,npar,1,npar);
5087: y=matrix(1,npar,1,npar);
5088: x=vector(1,npar);
5089: indx=ivector(1,npar);
5090: for (i=1;i<=npar;i++)
5091: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
5092: ludcmp(a,npar,indx,&pd);
5093:
5094: for (j=1;j<=npar;j++) {
5095: for (i=1;i<=npar;i++) x[i]=0;
5096: x[j]=1;
5097: lubksb(a,npar,indx,x);
5098: for (i=1;i<=npar;i++){
5099: matcov[i][j]=x[i];
5100: }
5101: }
5102:
5103: printf("\n#Hessian matrix#\n");
5104: fprintf(ficlog,"\n#Hessian matrix#\n");
5105: for (i=1;i<=npar;i++) {
5106: for (j=1;j<=npar;j++) {
1.203 brouard 5107: printf("%.6e ",hess[i][j]);
5108: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 5109: }
5110: printf("\n");
5111: fprintf(ficlog,"\n");
5112: }
5113:
1.203 brouard 5114: /* printf("\n#Covariance matrix#\n"); */
5115: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
5116: /* for (i=1;i<=npar;i++) { */
5117: /* for (j=1;j<=npar;j++) { */
5118: /* printf("%.6e ",matcov[i][j]); */
5119: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
5120: /* } */
5121: /* printf("\n"); */
5122: /* fprintf(ficlog,"\n"); */
5123: /* } */
5124:
1.126 brouard 5125: /* Recompute Inverse */
1.203 brouard 5126: /* for (i=1;i<=npar;i++) */
5127: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
5128: /* ludcmp(a,npar,indx,&pd); */
5129:
5130: /* printf("\n#Hessian matrix recomputed#\n"); */
5131:
5132: /* for (j=1;j<=npar;j++) { */
5133: /* for (i=1;i<=npar;i++) x[i]=0; */
5134: /* x[j]=1; */
5135: /* lubksb(a,npar,indx,x); */
5136: /* for (i=1;i<=npar;i++){ */
5137: /* y[i][j]=x[i]; */
5138: /* printf("%.3e ",y[i][j]); */
5139: /* fprintf(ficlog,"%.3e ",y[i][j]); */
5140: /* } */
5141: /* printf("\n"); */
5142: /* fprintf(ficlog,"\n"); */
5143: /* } */
5144:
5145: /* Verifying the inverse matrix */
5146: #ifdef DEBUGHESS
5147: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 5148:
1.203 brouard 5149: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
5150: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 5151:
5152: for (j=1;j<=npar;j++) {
5153: for (i=1;i<=npar;i++){
1.203 brouard 5154: printf("%.2f ",y[i][j]);
5155: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 5156: }
5157: printf("\n");
5158: fprintf(ficlog,"\n");
5159: }
1.203 brouard 5160: #endif
1.126 brouard 5161:
5162: free_matrix(a,1,npar,1,npar);
5163: free_matrix(y,1,npar,1,npar);
5164: free_vector(x,1,npar);
5165: free_ivector(indx,1,npar);
1.203 brouard 5166: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 5167:
5168:
5169: }
5170:
5171: /*************** hessian matrix ****************/
5172: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 5173: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 5174: int i;
5175: int l=1, lmax=20;
1.203 brouard 5176: double k1,k2, res, fx;
1.132 brouard 5177: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 5178: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
5179: int k=0,kmax=10;
5180: double l1;
5181:
5182: fx=func(x);
5183: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 5184: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 5185: l1=pow(10,l);
5186: delts=delt;
5187: for(k=1 ; k <kmax; k=k+1){
5188: delt = delta*(l1*k);
5189: p2[theta]=x[theta] +delt;
1.145 brouard 5190: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 5191: p2[theta]=x[theta]-delt;
5192: k2=func(p2)-fx;
5193: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 5194: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 5195:
1.203 brouard 5196: #ifdef DEBUGHESSII
1.126 brouard 5197: 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);
5198: 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);
5199: #endif
5200: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
5201: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
5202: k=kmax;
5203: }
5204: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 5205: k=kmax; l=lmax*10;
1.126 brouard 5206: }
5207: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
5208: delts=delt;
5209: }
1.203 brouard 5210: } /* End loop k */
1.126 brouard 5211: }
5212: delti[theta]=delts;
5213: return res;
5214:
5215: }
5216:
1.203 brouard 5217: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 5218: {
5219: int i;
1.164 brouard 5220: int l=1, lmax=20;
1.126 brouard 5221: double k1,k2,k3,k4,res,fx;
1.132 brouard 5222: double p2[MAXPARM+1];
1.203 brouard 5223: int k, kmax=1;
5224: double v1, v2, cv12, lc1, lc2;
1.208 brouard 5225:
5226: int firstime=0;
1.203 brouard 5227:
1.126 brouard 5228: fx=func(x);
1.203 brouard 5229: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 5230: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 5231: p2[thetai]=x[thetai]+delti[thetai]*k;
5232: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 5233: k1=func(p2)-fx;
5234:
1.203 brouard 5235: p2[thetai]=x[thetai]+delti[thetai]*k;
5236: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 5237: k2=func(p2)-fx;
5238:
1.203 brouard 5239: p2[thetai]=x[thetai]-delti[thetai]*k;
5240: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 5241: k3=func(p2)-fx;
5242:
1.203 brouard 5243: p2[thetai]=x[thetai]-delti[thetai]*k;
5244: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 5245: k4=func(p2)-fx;
1.203 brouard 5246: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
5247: if(k1*k2*k3*k4 <0.){
1.208 brouard 5248: firstime=1;
1.203 brouard 5249: kmax=kmax+10;
1.208 brouard 5250: }
5251: if(kmax >=10 || firstime ==1){
1.246 brouard 5252: 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);
5253: 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 5254: 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);
5255: 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);
5256: }
5257: #ifdef DEBUGHESSIJ
5258: v1=hess[thetai][thetai];
5259: v2=hess[thetaj][thetaj];
5260: cv12=res;
5261: /* Computing eigen value of Hessian matrix */
5262: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
5263: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
5264: if ((lc2 <0) || (lc1 <0) ){
5265: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
5266: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
5267: 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);
5268: 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);
5269: }
1.126 brouard 5270: #endif
5271: }
5272: return res;
5273: }
5274:
1.203 brouard 5275: /* Not done yet: Was supposed to fix if not exactly at the maximum */
5276: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
5277: /* { */
5278: /* int i; */
5279: /* int l=1, lmax=20; */
5280: /* double k1,k2,k3,k4,res,fx; */
5281: /* double p2[MAXPARM+1]; */
5282: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
5283: /* int k=0,kmax=10; */
5284: /* double l1; */
5285:
5286: /* fx=func(x); */
5287: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
5288: /* l1=pow(10,l); */
5289: /* delts=delt; */
5290: /* for(k=1 ; k <kmax; k=k+1){ */
5291: /* delt = delti*(l1*k); */
5292: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
5293: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
5294: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
5295: /* k1=func(p2)-fx; */
5296:
5297: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
5298: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
5299: /* k2=func(p2)-fx; */
5300:
5301: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
5302: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
5303: /* k3=func(p2)-fx; */
5304:
5305: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
5306: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
5307: /* k4=func(p2)-fx; */
5308: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
5309: /* #ifdef DEBUGHESSIJ */
5310: /* 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); */
5311: /* 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); */
5312: /* #endif */
5313: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
5314: /* k=kmax; */
5315: /* } */
5316: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
5317: /* k=kmax; l=lmax*10; */
5318: /* } */
5319: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
5320: /* delts=delt; */
5321: /* } */
5322: /* } /\* End loop k *\/ */
5323: /* } */
5324: /* delti[theta]=delts; */
5325: /* return res; */
5326: /* } */
5327:
5328:
1.126 brouard 5329: /************** Inverse of matrix **************/
5330: void ludcmp(double **a, int n, int *indx, double *d)
5331: {
5332: int i,imax,j,k;
5333: double big,dum,sum,temp;
5334: double *vv;
5335:
5336: vv=vector(1,n);
5337: *d=1.0;
5338: for (i=1;i<=n;i++) {
5339: big=0.0;
5340: for (j=1;j<=n;j++)
5341: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 5342: if (big == 0.0){
5343: printf(" Singular Hessian matrix at row %d:\n",i);
5344: for (j=1;j<=n;j++) {
5345: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
5346: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
5347: }
5348: fflush(ficlog);
5349: fclose(ficlog);
5350: nrerror("Singular matrix in routine ludcmp");
5351: }
1.126 brouard 5352: vv[i]=1.0/big;
5353: }
5354: for (j=1;j<=n;j++) {
5355: for (i=1;i<j;i++) {
5356: sum=a[i][j];
5357: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
5358: a[i][j]=sum;
5359: }
5360: big=0.0;
5361: for (i=j;i<=n;i++) {
5362: sum=a[i][j];
5363: for (k=1;k<j;k++)
5364: sum -= a[i][k]*a[k][j];
5365: a[i][j]=sum;
5366: if ( (dum=vv[i]*fabs(sum)) >= big) {
5367: big=dum;
5368: imax=i;
5369: }
5370: }
5371: if (j != imax) {
5372: for (k=1;k<=n;k++) {
5373: dum=a[imax][k];
5374: a[imax][k]=a[j][k];
5375: a[j][k]=dum;
5376: }
5377: *d = -(*d);
5378: vv[imax]=vv[j];
5379: }
5380: indx[j]=imax;
5381: if (a[j][j] == 0.0) a[j][j]=TINY;
5382: if (j != n) {
5383: dum=1.0/(a[j][j]);
5384: for (i=j+1;i<=n;i++) a[i][j] *= dum;
5385: }
5386: }
5387: free_vector(vv,1,n); /* Doesn't work */
5388: ;
5389: }
5390:
5391: void lubksb(double **a, int n, int *indx, double b[])
5392: {
5393: int i,ii=0,ip,j;
5394: double sum;
5395:
5396: for (i=1;i<=n;i++) {
5397: ip=indx[i];
5398: sum=b[ip];
5399: b[ip]=b[i];
5400: if (ii)
5401: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
5402: else if (sum) ii=i;
5403: b[i]=sum;
5404: }
5405: for (i=n;i>=1;i--) {
5406: sum=b[i];
5407: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
5408: b[i]=sum/a[i][i];
5409: }
5410: }
5411:
5412: void pstamp(FILE *fichier)
5413: {
1.196 brouard 5414: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 5415: }
5416:
1.297 brouard 5417: void date2dmy(double date,double *day, double *month, double *year){
5418: double yp=0., yp1=0., yp2=0.;
5419:
5420: yp1=modf(date,&yp);/* extracts integral of date in yp and
5421: fractional in yp1 */
5422: *year=yp;
5423: yp2=modf((yp1*12),&yp);
5424: *month=yp;
5425: yp1=modf((yp2*30.5),&yp);
5426: *day=yp;
5427: if(*day==0) *day=1;
5428: if(*month==0) *month=1;
5429: }
5430:
1.253 brouard 5431:
5432:
1.126 brouard 5433: /************ Frequencies ********************/
1.251 brouard 5434: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 5435: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
5436: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 5437: { /* Some frequencies as well as proposing some starting values */
1.332 brouard 5438: /* Frequencies of any combination of dummy covariate used in the model equation */
1.265 brouard 5439: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 5440: int iind=0, iage=0;
5441: int mi; /* Effective wave */
5442: int first;
5443: double ***freq; /* Frequencies */
1.268 brouard 5444: 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 */
5445: 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 5446: double *meanq, *stdq, *idq;
1.226 brouard 5447: double **meanqt;
5448: double *pp, **prop, *posprop, *pospropt;
5449: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
5450: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
5451: double agebegin, ageend;
5452:
5453: pp=vector(1,nlstate);
1.251 brouard 5454: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 5455: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
5456: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
5457: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
5458: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 5459: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 5460: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 5461: meanqt=matrix(1,lastpass,1,nqtveff);
5462: strcpy(fileresp,"P_");
5463: strcat(fileresp,fileresu);
5464: /*strcat(fileresphtm,fileresu);*/
5465: if((ficresp=fopen(fileresp,"w"))==NULL) {
5466: printf("Problem with prevalence resultfile: %s\n", fileresp);
5467: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
5468: exit(0);
5469: }
1.240 brouard 5470:
1.226 brouard 5471: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
5472: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
5473: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
5474: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
5475: fflush(ficlog);
5476: exit(70);
5477: }
5478: else{
5479: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 5480: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 5481: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 5482: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
5483: }
1.319 brouard 5484: 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 5485:
1.226 brouard 5486: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
5487: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
5488: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
5489: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
5490: fflush(ficlog);
5491: exit(70);
1.240 brouard 5492: } else{
1.226 brouard 5493: 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 5494: ,<hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 5495: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 5496: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
5497: }
1.319 brouard 5498: 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 5499:
1.253 brouard 5500: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
5501: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 5502: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 5503: j1=0;
1.126 brouard 5504:
1.227 brouard 5505: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
1.335 brouard 5506: j=cptcoveff; /* Only simple dummy covariates used in the model */
1.330 brouard 5507: /* j=cptcovn; /\* Only dummy covariates of the model *\/ */
1.226 brouard 5508: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 5509:
5510:
1.226 brouard 5511: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
5512: reference=low_education V1=0,V2=0
5513: med_educ V1=1 V2=0,
5514: high_educ V1=0 V2=1
1.330 brouard 5515: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcovn
1.226 brouard 5516: */
1.249 brouard 5517: dateintsum=0;
5518: k2cpt=0;
5519:
1.253 brouard 5520: if(cptcoveff == 0 )
1.265 brouard 5521: nl=1; /* Constant and age model only */
1.253 brouard 5522: else
5523: nl=2;
1.265 brouard 5524:
5525: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
5526: /* Loop on nj=1 or 2 if dummy covariates j!=0
1.335 brouard 5527: * Loop on j1(1 to 2**cptcoveff) covariate combination
1.265 brouard 5528: * freq[s1][s2][iage] =0.
5529: * Loop on iind
5530: * ++freq[s1][s2][iage] weighted
5531: * end iind
5532: * if covariate and j!0
5533: * headers Variable on one line
5534: * endif cov j!=0
5535: * header of frequency table by age
5536: * Loop on age
5537: * pp[s1]+=freq[s1][s2][iage] weighted
5538: * pos+=freq[s1][s2][iage] weighted
5539: * Loop on s1 initial state
5540: * fprintf(ficresp
5541: * end s1
5542: * end age
5543: * if j!=0 computes starting values
5544: * end compute starting values
5545: * end j1
5546: * end nl
5547: */
1.253 brouard 5548: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
5549: if(nj==1)
5550: j=0; /* First pass for the constant */
1.265 brouard 5551: else{
1.335 brouard 5552: 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 5553: }
1.251 brouard 5554: first=1;
1.332 brouard 5555: 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 5556: posproptt=0.;
1.330 brouard 5557: /*printf("cptcovn=%d Tvaraff=%d", cptcovn,Tvaraff[1]);
1.251 brouard 5558: scanf("%d", i);*/
5559: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 5560: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 5561: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 5562: freq[i][s2][m]=0;
1.251 brouard 5563:
5564: for (i=1; i<=nlstate; i++) {
1.240 brouard 5565: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 5566: prop[i][m]=0;
5567: posprop[i]=0;
5568: pospropt[i]=0;
5569: }
1.283 brouard 5570: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 5571: idq[z1]=0.;
5572: meanq[z1]=0.;
5573: stdq[z1]=0.;
1.283 brouard 5574: }
5575: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 5576: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 5577: /* meanqt[m][z1]=0.; */
5578: /* } */
5579: /* } */
1.251 brouard 5580: /* dateintsum=0; */
5581: /* k2cpt=0; */
5582:
1.265 brouard 5583: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 5584: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
5585: bool=1;
5586: if(j !=0){
5587: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
1.335 brouard 5588: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
5589: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
1.251 brouard 5590: /* if(Tvaraff[z1] ==-20){ */
5591: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
5592: /* }else if(Tvaraff[z1] ==-10){ */
5593: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
1.330 brouard 5594: /* }else */ /* TODO TODO codtabm(j1,z1) or codtabm(j1,Tvaraff[z1]]z1)*/
1.335 brouard 5595: /* 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); */
5596: if(Tvaraff[z1]<1 || Tvaraff[z1]>=NCOVMAX)
1.338 brouard 5597: printf("Error Tvaraff[z1]=%d<1 or >=%d, cptcoveff=%d model=1+age+%s\n",Tvaraff[z1],NCOVMAX, cptcoveff, model);
1.332 brouard 5598: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]){ /* for combination j1 of covariates */
1.265 brouard 5599: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 5600: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
1.332 brouard 5601: /* 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", */
5602: /* bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),*/
5603: /* j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
1.251 brouard 5604: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
5605: } /* Onlyf fixed */
5606: } /* end z1 */
1.335 brouard 5607: } /* cptcoveff > 0 */
1.251 brouard 5608: } /* end any */
5609: }/* end j==0 */
1.265 brouard 5610: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 5611: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 5612: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 5613: m=mw[mi][iind];
5614: if(j!=0){
5615: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
1.335 brouard 5616: for (z1=1; z1<=cptcoveff; z1++) {
1.251 brouard 5617: if( Fixed[Tmodelind[z1]]==1){
1.341 brouard 5618: /* iv= Tvar[Tmodelind[z1]]-ncovcol-nqv; /\* Good *\/ */
5619: iv= Tvar[Tmodelind[z1]]; /* Good *//* because cotvar starts now at first at ncovcol+nqv+ntv */
1.332 brouard 5620: 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 5621: value is -1, we don't select. It differs from the
5622: constant and age model which counts them. */
5623: bool=0; /* not selected */
5624: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
1.334 brouard 5625: /* i1=Tvaraff[z1]; */
5626: /* i2=TnsdVar[i1]; */
5627: /* i3=nbcode[i1][i2]; */
5628: /* i4=covar[i1][iind]; */
5629: /* if(i4 != i3){ */
5630: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) { /* Bug valgrind */
1.251 brouard 5631: bool=0;
5632: }
5633: }
5634: }
5635: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
5636: } /* end j==0 */
5637: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 5638: if(bool==1){ /*Selected */
1.251 brouard 5639: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
5640: and mw[mi+1][iind]. dh depends on stepm. */
5641: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
5642: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
5643: if(m >=firstpass && m <=lastpass){
5644: k2=anint[m][iind]+(mint[m][iind]/12.);
5645: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
5646: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
5647: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
5648: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
5649: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
5650: if (m<lastpass) {
5651: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
5652: /* 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]); */
5653: if(s[m][iind]==-1)
5654: 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.));
5655: 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 5656: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean on known values only */
5657: if(!isnan(covar[ncovcol+z1][iind])){
1.332 brouard 5658: idq[z1]=idq[z1]+weight[iind];
5659: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
5660: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; *//*error*/
5661: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
1.311 brouard 5662: }
1.284 brouard 5663: }
1.251 brouard 5664: /* if((int)agev[m][iind] == 55) */
5665: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
5666: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
5667: 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 5668: }
1.251 brouard 5669: } /* end if between passes */
5670: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
5671: dateintsum=dateintsum+k2; /* on all covariates ?*/
5672: k2cpt++;
5673: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 5674: }
1.251 brouard 5675: }else{
5676: bool=1;
5677: }/* end bool 2 */
5678: } /* end m */
1.284 brouard 5679: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
5680: /* idq[z1]=idq[z1]+weight[iind]; */
5681: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
5682: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
5683: /* } */
1.251 brouard 5684: } /* end bool */
5685: } /* end iind = 1 to imx */
1.319 brouard 5686: /* prop[s][age] is fed for any initial and valid live state as well as
1.251 brouard 5687: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
5688:
5689:
5690: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.335 brouard 5691: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
1.265 brouard 5692: pstamp(ficresp);
1.335 brouard 5693: if (cptcoveff>0 && j!=0){
1.265 brouard 5694: pstamp(ficresp);
1.251 brouard 5695: printf( "\n#********** Variable ");
5696: fprintf(ficresp, "\n#********** Variable ");
5697: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
5698: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
5699: fprintf(ficlog, "\n#********** Variable ");
1.340 brouard 5700: for (z1=1; z1<=cptcoveff; z1++){
1.251 brouard 5701: if(!FixedV[Tvaraff[z1]]){
1.330 brouard 5702: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5703: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5704: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5705: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5706: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.250 brouard 5707: }else{
1.330 brouard 5708: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5709: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5710: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5711: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5712: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.251 brouard 5713: }
5714: }
5715: printf( "**********\n#");
5716: fprintf(ficresp, "**********\n#");
5717: fprintf(ficresphtm, "**********</h3>\n");
5718: fprintf(ficresphtmfr, "**********</h3>\n");
5719: fprintf(ficlog, "**********\n");
5720: }
1.284 brouard 5721: /*
5722: Printing means of quantitative variables if any
5723: */
5724: for (z1=1; z1<= nqfveff; z1++) {
1.311 brouard 5725: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.3g (weighted) individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.312 brouard 5726: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
1.284 brouard 5727: if(weightopt==1){
5728: printf(" Weighted mean and standard deviation of");
5729: fprintf(ficlog," Weighted mean and standard deviation of");
5730: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
5731: }
1.311 brouard 5732: /* mu = \frac{w x}{\sum w}
5733: var = \frac{\sum w (x-mu)^2}{\sum w} = \frac{w x^2}{\sum w} - mu^2
5734: */
5735: 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]));
5736: 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]));
5737: 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 5738: }
5739: /* for (z1=1; z1<= nqtveff; z1++) { */
5740: /* for(m=1;m<=lastpass;m++){ */
5741: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
5742: /* } */
5743: /* } */
1.283 brouard 5744:
1.251 brouard 5745: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.335 brouard 5746: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
1.265 brouard 5747: fprintf(ficresp, " Age");
1.335 brouard 5748: if(nj==2) for (z1=1; z1<=cptcoveff; z1++) {
5749: 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]]);
5750: fprintf(ficresp, " V%d=%d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5751: }
1.251 brouard 5752: for(i=1; i<=nlstate;i++) {
1.335 brouard 5753: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 5754: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
5755: }
1.335 brouard 5756: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 5757: fprintf(ficresphtm, "\n");
5758:
5759: /* Header of frequency table by age */
5760: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
5761: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 5762: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 5763: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5764: if(s2!=0 && m!=0)
5765: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 5766: }
1.226 brouard 5767: }
1.251 brouard 5768: fprintf(ficresphtmfr, "\n");
5769:
5770: /* For each age */
5771: for(iage=iagemin; iage <= iagemax+3; iage++){
5772: fprintf(ficresphtm,"<tr>");
5773: if(iage==iagemax+1){
5774: fprintf(ficlog,"1");
5775: fprintf(ficresphtmfr,"<tr><th>0</th> ");
5776: }else if(iage==iagemax+2){
5777: fprintf(ficlog,"0");
5778: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
5779: }else if(iage==iagemax+3){
5780: fprintf(ficlog,"Total");
5781: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
5782: }else{
1.240 brouard 5783: if(first==1){
1.251 brouard 5784: first=0;
5785: printf("See log file for details...\n");
5786: }
5787: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
5788: fprintf(ficlog,"Age %d", iage);
5789: }
1.265 brouard 5790: for(s1=1; s1 <=nlstate ; s1++){
5791: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
5792: pp[s1] += freq[s1][m][iage];
1.251 brouard 5793: }
1.265 brouard 5794: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5795: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 5796: pos += freq[s1][m][iage];
5797: if(pp[s1]>=1.e-10){
1.251 brouard 5798: if(first==1){
1.265 brouard 5799: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5800: }
1.265 brouard 5801: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5802: }else{
5803: if(first==1)
1.265 brouard 5804: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
5805: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 5806: }
5807: }
5808:
1.265 brouard 5809: for(s1=1; s1 <=nlstate ; s1++){
5810: /* posprop[s1]=0; */
5811: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
5812: pp[s1] += freq[s1][m][iage];
5813: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
5814:
5815: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
5816: pos += pp[s1]; /* pos is the total number of transitions until this age */
5817: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
5818: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5819: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
5820: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5821: }
5822:
5823: /* Writing ficresp */
1.335 brouard 5824: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5825: if( iage <= iagemax){
5826: fprintf(ficresp," %d",iage);
5827: }
5828: }else if( nj==2){
5829: if( iage <= iagemax){
5830: fprintf(ficresp," %d",iage);
1.335 brouard 5831: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.265 brouard 5832: }
1.240 brouard 5833: }
1.265 brouard 5834: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 5835: if(pos>=1.e-5){
1.251 brouard 5836: if(first==1)
1.265 brouard 5837: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
5838: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 5839: }else{
5840: if(first==1)
1.265 brouard 5841: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
5842: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 5843: }
5844: if( iage <= iagemax){
5845: if(pos>=1.e-5){
1.335 brouard 5846: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5847: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5848: }else if( nj==2){
5849: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5850: }
5851: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5852: /*probs[iage][s1][j1]= pp[s1]/pos;*/
5853: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
5854: } else{
1.335 brouard 5855: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
1.265 brouard 5856: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 5857: }
1.240 brouard 5858: }
1.265 brouard 5859: pospropt[s1] +=posprop[s1];
5860: } /* end loop s1 */
1.251 brouard 5861: /* pospropt=0.; */
1.265 brouard 5862: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 5863: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5864: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 5865: if(first==1){
1.265 brouard 5866: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5867: }
1.265 brouard 5868: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
5869: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5870: }
1.265 brouard 5871: if(s1!=0 && m!=0)
5872: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 5873: }
1.265 brouard 5874: } /* end loop s1 */
1.251 brouard 5875: posproptt=0.;
1.265 brouard 5876: for(s1=1; s1 <=nlstate; s1++){
5877: posproptt += pospropt[s1];
1.251 brouard 5878: }
5879: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 5880: fprintf(ficresphtm,"</tr>\n");
1.335 brouard 5881: if((cptcoveff==0 && nj==1)|| nj==2 ) {
1.265 brouard 5882: if(iage <= iagemax)
5883: fprintf(ficresp,"\n");
1.240 brouard 5884: }
1.251 brouard 5885: if(first==1)
5886: printf("Others in log...\n");
5887: fprintf(ficlog,"\n");
5888: } /* end loop age iage */
1.265 brouard 5889:
1.251 brouard 5890: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 5891: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5892: if(posproptt < 1.e-5){
1.265 brouard 5893: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 5894: }else{
1.265 brouard 5895: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 5896: }
1.226 brouard 5897: }
1.251 brouard 5898: fprintf(ficresphtm,"</tr>\n");
5899: fprintf(ficresphtm,"</table>\n");
5900: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 5901: if(posproptt < 1.e-5){
1.251 brouard 5902: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
5903: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 5904: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
5905: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 5906: invalidvarcomb[j1]=1;
1.226 brouard 5907: }else{
1.338 brouard 5908: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced (or no resultline).</p>",j1);
1.251 brouard 5909: invalidvarcomb[j1]=0;
1.226 brouard 5910: }
1.251 brouard 5911: fprintf(ficresphtmfr,"</table>\n");
5912: fprintf(ficlog,"\n");
5913: if(j!=0){
5914: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 5915: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5916: for(k=1; k <=(nlstate+ndeath); k++){
5917: if (k != i) {
1.265 brouard 5918: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 5919: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 5920: if(j1==1){ /* All dummy covariates to zero */
5921: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
5922: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 5923: printf("%d%d ",i,k);
5924: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5925: 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]));
5926: 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]));
5927: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 5928: }
1.253 brouard 5929: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
5930: for(iage=iagemin; iage <= iagemax+3; iage++){
5931: x[iage]= (double)iage;
5932: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 5933: /* 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 5934: }
1.268 brouard 5935: /* Some are not finite, but linreg will ignore these ages */
5936: no=0;
1.253 brouard 5937: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 5938: pstart[s1]=b;
5939: pstart[s1-1]=a;
1.252 brouard 5940: }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 */
5941: 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]);
5942: 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 5943: 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 5944: printf("%d%d ",i,k);
5945: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5946: 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 5947: }else{ /* Other cases, like quantitative fixed or varying covariates */
5948: ;
5949: }
5950: /* printf("%12.7f )", param[i][jj][k]); */
5951: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5952: s1++;
1.251 brouard 5953: } /* end jj */
5954: } /* end k!= i */
5955: } /* end k */
1.265 brouard 5956: } /* end i, s1 */
1.251 brouard 5957: } /* end j !=0 */
5958: } /* end selected combination of covariate j1 */
5959: if(j==0){ /* We can estimate starting values from the occurences in each case */
5960: printf("#Freqsummary: Starting values for the constants:\n");
5961: fprintf(ficlog,"\n");
1.265 brouard 5962: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5963: for(k=1; k <=(nlstate+ndeath); k++){
5964: if (k != i) {
5965: printf("%d%d ",i,k);
5966: fprintf(ficlog,"%d%d ",i,k);
5967: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 5968: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 5969: if(jj==1){ /* Age has to be done */
1.265 brouard 5970: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
5971: 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]));
5972: 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 5973: }
5974: /* printf("%12.7f )", param[i][jj][k]); */
5975: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5976: s1++;
1.250 brouard 5977: }
1.251 brouard 5978: printf("\n");
5979: fprintf(ficlog,"\n");
1.250 brouard 5980: }
5981: }
1.284 brouard 5982: } /* end of state i */
1.251 brouard 5983: printf("#Freqsummary\n");
5984: fprintf(ficlog,"\n");
1.265 brouard 5985: for(s1=-1; s1 <=nlstate+ndeath; s1++){
5986: for(s2=-1; s2 <=nlstate+ndeath; s2++){
5987: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
5988: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5989: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5990: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
5991: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
5992: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 5993: /* } */
5994: }
1.265 brouard 5995: } /* end loop s1 */
1.251 brouard 5996:
5997: printf("\n");
5998: fprintf(ficlog,"\n");
5999: } /* end j=0 */
1.249 brouard 6000: } /* end j */
1.252 brouard 6001:
1.253 brouard 6002: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 6003: for(i=1, jk=1; i <=nlstate; i++){
6004: for(j=1; j <=nlstate+ndeath; j++){
6005: if(j!=i){
6006: /*ca[0]= k+'a'-1;ca[1]='\0';*/
6007: printf("%1d%1d",i,j);
6008: fprintf(ficparo,"%1d%1d",i,j);
6009: for(k=1; k<=ncovmodel;k++){
6010: /* printf(" %lf",param[i][j][k]); */
6011: /* fprintf(ficparo," %lf",param[i][j][k]); */
6012: p[jk]=pstart[jk];
6013: printf(" %f ",pstart[jk]);
6014: fprintf(ficparo," %f ",pstart[jk]);
6015: jk++;
6016: }
6017: printf("\n");
6018: fprintf(ficparo,"\n");
6019: }
6020: }
6021: }
6022: } /* end mle=-2 */
1.226 brouard 6023: dateintmean=dateintsum/k2cpt;
1.296 brouard 6024: date2dmy(dateintmean,&jintmean,&mintmean,&aintmean);
1.240 brouard 6025:
1.226 brouard 6026: fclose(ficresp);
6027: fclose(ficresphtm);
6028: fclose(ficresphtmfr);
1.283 brouard 6029: free_vector(idq,1,nqfveff);
1.226 brouard 6030: free_vector(meanq,1,nqfveff);
1.284 brouard 6031: free_vector(stdq,1,nqfveff);
1.226 brouard 6032: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 6033: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
6034: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 6035: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 6036: free_vector(pospropt,1,nlstate);
6037: free_vector(posprop,1,nlstate);
1.251 brouard 6038: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 6039: free_vector(pp,1,nlstate);
6040: /* End of freqsummary */
6041: }
1.126 brouard 6042:
1.268 brouard 6043: /* Simple linear regression */
6044: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
6045:
6046: /* y=a+bx regression */
6047: double sumx = 0.0; /* sum of x */
6048: double sumx2 = 0.0; /* sum of x**2 */
6049: double sumxy = 0.0; /* sum of x * y */
6050: double sumy = 0.0; /* sum of y */
6051: double sumy2 = 0.0; /* sum of y**2 */
6052: double sume2 = 0.0; /* sum of square or residuals */
6053: double yhat;
6054:
6055: double denom=0;
6056: int i;
6057: int ne=*no;
6058:
6059: for ( i=ifi, ne=0;i<=ila;i++) {
6060: if(!isfinite(x[i]) || !isfinite(y[i])){
6061: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
6062: continue;
6063: }
6064: ne=ne+1;
6065: sumx += x[i];
6066: sumx2 += x[i]*x[i];
6067: sumxy += x[i] * y[i];
6068: sumy += y[i];
6069: sumy2 += y[i]*y[i];
6070: denom = (ne * sumx2 - sumx*sumx);
6071: /* 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); */
6072: }
6073:
6074: denom = (ne * sumx2 - sumx*sumx);
6075: if (denom == 0) {
6076: // vertical, slope m is infinity
6077: *b = INFINITY;
6078: *a = 0;
6079: if (r) *r = 0;
6080: return 1;
6081: }
6082:
6083: *b = (ne * sumxy - sumx * sumy) / denom;
6084: *a = (sumy * sumx2 - sumx * sumxy) / denom;
6085: if (r!=NULL) {
6086: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
6087: sqrt((sumx2 - sumx*sumx/ne) *
6088: (sumy2 - sumy*sumy/ne));
6089: }
6090: *no=ne;
6091: for ( i=ifi, ne=0;i<=ila;i++) {
6092: if(!isfinite(x[i]) || !isfinite(y[i])){
6093: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
6094: continue;
6095: }
6096: ne=ne+1;
6097: yhat = y[i] - *a -*b* x[i];
6098: sume2 += yhat * yhat ;
6099:
6100: denom = (ne * sumx2 - sumx*sumx);
6101: /* 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); */
6102: }
6103: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
6104: *sa= *sb * sqrt(sumx2/ne);
6105:
6106: return 0;
6107: }
6108:
1.126 brouard 6109: /************ Prevalence ********************/
1.227 brouard 6110: 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)
6111: {
6112: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
6113: in each health status at the date of interview (if between dateprev1 and dateprev2).
6114: We still use firstpass and lastpass as another selection.
6115: */
1.126 brouard 6116:
1.227 brouard 6117: int i, m, jk, j1, bool, z1,j, iv;
6118: int mi; /* Effective wave */
6119: int iage;
6120: double agebegin, ageend;
6121:
6122: double **prop;
6123: double posprop;
6124: double y2; /* in fractional years */
6125: int iagemin, iagemax;
6126: int first; /** to stop verbosity which is redirected to log file */
6127:
6128: iagemin= (int) agemin;
6129: iagemax= (int) agemax;
6130: /*pp=vector(1,nlstate);*/
1.251 brouard 6131: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 6132: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
6133: j1=0;
1.222 brouard 6134:
1.227 brouard 6135: /*j=cptcoveff;*/
6136: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 6137:
1.288 brouard 6138: first=0;
1.335 brouard 6139: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of simple dummy covariates */
1.227 brouard 6140: for (i=1; i<=nlstate; i++)
1.251 brouard 6141: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 6142: prop[i][iage]=0.0;
6143: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
6144: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
6145: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
6146:
6147: for (i=1; i<=imx; i++) { /* Each individual */
6148: bool=1;
6149: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
6150: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
6151: m=mw[mi][i];
6152: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
6153: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
6154: for (z1=1; z1<=cptcoveff; z1++){
6155: if( Fixed[Tmodelind[z1]]==1){
1.341 brouard 6156: iv= Tvar[Tmodelind[z1]];/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
1.332 brouard 6157: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) /* iv=1 to ntv, right modality */
1.227 brouard 6158: bool=0;
6159: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
1.332 brouard 6160: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) {
1.227 brouard 6161: bool=0;
6162: }
6163: }
6164: if(bool==1){ /* Otherwise we skip that wave/person */
6165: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
6166: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
6167: if(m >=firstpass && m <=lastpass){
6168: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
6169: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
6170: if(agev[m][i]==0) agev[m][i]=iagemax+1;
6171: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 6172: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 6173: 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);
6174: exit(1);
6175: }
6176: if (s[m][i]>0 && s[m][i]<=nlstate) {
6177: /*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]]);*/
6178: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
6179: prop[s[m][i]][iagemax+3] += weight[i];
6180: } /* end valid statuses */
6181: } /* end selection of dates */
6182: } /* end selection of waves */
6183: } /* end bool */
6184: } /* end wave */
6185: } /* end individual */
6186: for(i=iagemin; i <= iagemax+3; i++){
6187: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
6188: posprop += prop[jk][i];
6189: }
6190:
6191: for(jk=1; jk <=nlstate ; jk++){
6192: if( i <= iagemax){
6193: if(posprop>=1.e-5){
6194: probs[i][jk][j1]= prop[jk][i]/posprop;
6195: } else{
1.288 brouard 6196: if(!first){
6197: first=1;
1.266 brouard 6198: 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]);
6199: }else{
1.288 brouard 6200: 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 6201: }
6202: }
6203: }
6204: }/* end jk */
6205: }/* end i */
1.222 brouard 6206: /*} *//* end i1 */
1.227 brouard 6207: } /* end j1 */
1.222 brouard 6208:
1.227 brouard 6209: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
6210: /*free_vector(pp,1,nlstate);*/
1.251 brouard 6211: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 6212: } /* End of prevalence */
1.126 brouard 6213:
6214: /************* Waves Concatenation ***************/
6215:
6216: 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)
6217: {
1.298 brouard 6218: /* 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 6219: Death is a valid wave (if date is known).
6220: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
6221: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
1.298 brouard 6222: and mw[mi+1][i]. dh depends on stepm. s[m][i] exists for any wave from firstpass to lastpass
1.227 brouard 6223: */
1.126 brouard 6224:
1.224 brouard 6225: int i=0, mi=0, m=0, mli=0;
1.126 brouard 6226: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
6227: double sum=0., jmean=0.;*/
1.224 brouard 6228: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 6229: int j, k=0,jk, ju, jl;
6230: double sum=0.;
6231: first=0;
1.214 brouard 6232: firstwo=0;
1.217 brouard 6233: firsthree=0;
1.218 brouard 6234: firstfour=0;
1.164 brouard 6235: jmin=100000;
1.126 brouard 6236: jmax=-1;
6237: jmean=0.;
1.224 brouard 6238:
6239: /* Treating live states */
1.214 brouard 6240: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 6241: mi=0; /* First valid wave */
1.227 brouard 6242: mli=0; /* Last valid wave */
1.309 brouard 6243: m=firstpass; /* Loop on waves */
6244: while(s[m][i] <= nlstate){ /* a live state or unknown state */
1.227 brouard 6245: 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 */
6246: mli=m-1;/* mw[++mi][i]=m-1; */
6247: }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 6248: 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 6249: mli=m;
1.224 brouard 6250: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
6251: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 6252: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 6253: }
1.309 brouard 6254: else{ /* m = lastpass, eventual special issue with warning */
1.224 brouard 6255: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 6256: break;
1.224 brouard 6257: #else
1.317 brouard 6258: 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 6259: if(firsthree == 0){
1.302 brouard 6260: 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 6261: firsthree=1;
1.317 brouard 6262: }else if(firsthree >=1 && firsthree < 10){
6263: 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);
6264: firsthree++;
6265: }else if(firsthree == 10){
6266: printf("Information, too many Information flags: no more reported to log either\n");
6267: fprintf(ficlog,"Information, too many Information flags: no more reported to log either\n");
6268: firsthree++;
6269: }else{
6270: firsthree++;
1.227 brouard 6271: }
1.309 brouard 6272: mw[++mi][i]=m; /* Valid transition with unknown status */
1.227 brouard 6273: mli=m;
6274: }
6275: if(s[m][i]==-2){ /* Vital status is really unknown */
6276: nbwarn++;
1.309 brouard 6277: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified?not a transition */
1.227 brouard 6278: 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);
6279: 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);
6280: }
6281: break;
6282: }
6283: break;
1.224 brouard 6284: #endif
1.227 brouard 6285: }/* End m >= lastpass */
1.126 brouard 6286: }/* end while */
1.224 brouard 6287:
1.227 brouard 6288: /* 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 6289: /* After last pass */
1.224 brouard 6290: /* Treating death states */
1.214 brouard 6291: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 6292: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
6293: /* } */
1.126 brouard 6294: mi++; /* Death is another wave */
6295: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 6296: /* Only death is a correct wave */
1.126 brouard 6297: mw[mi][i]=m;
1.257 brouard 6298: } /* else not in a death state */
1.224 brouard 6299: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 6300: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 6301: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.309 brouard 6302: 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 6303: nbwarn++;
6304: if(firstfiv==0){
1.309 brouard 6305: 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 6306: firstfiv=1;
6307: }else{
1.309 brouard 6308: 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 6309: }
1.309 brouard 6310: s[m][i]=nlstate+1; /* Fixing the status as death. Be careful if multiple death states */
6311: }else{ /* Month of Death occured afer last wave month, potential bias */
1.227 brouard 6312: nberr++;
6313: if(firstwo==0){
1.309 brouard 6314: 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 6315: firstwo=1;
6316: }
1.309 brouard 6317: 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 6318: }
1.257 brouard 6319: }else{ /* if date of interview is unknown */
1.227 brouard 6320: /* death is known but not confirmed by death status at any wave */
6321: if(firstfour==0){
1.309 brouard 6322: 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 6323: firstfour=1;
6324: }
1.309 brouard 6325: 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 6326: }
1.224 brouard 6327: } /* end if date of death is known */
6328: #endif
1.309 brouard 6329: wav[i]=mi; /* mi should be the last effective wave (or mli), */
6330: /* wav[i]=mw[mi][i]; */
1.126 brouard 6331: if(mi==0){
6332: nbwarn++;
6333: if(first==0){
1.227 brouard 6334: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
6335: first=1;
1.126 brouard 6336: }
6337: if(first==1){
1.227 brouard 6338: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 6339: }
6340: } /* end mi==0 */
6341: } /* End individuals */
1.214 brouard 6342: /* wav and mw are no more changed */
1.223 brouard 6343:
1.317 brouard 6344: printf("Information, you have to check %d informations which haven't been logged!\n",firsthree);
6345: fprintf(ficlog,"Information, you have to check %d informations which haven't been logged!\n",firsthree);
6346:
6347:
1.126 brouard 6348: for(i=1; i<=imx; i++){
6349: for(mi=1; mi<wav[i];mi++){
6350: if (stepm <=0)
1.227 brouard 6351: dh[mi][i]=1;
1.126 brouard 6352: else{
1.260 brouard 6353: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 6354: if (agedc[i] < 2*AGESUP) {
6355: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
6356: if(j==0) j=1; /* Survives at least one month after exam */
6357: else if(j<0){
6358: nberr++;
6359: 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]);
6360: j=1; /* Temporary Dangerous patch */
6361: 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);
6362: 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]);
6363: 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);
6364: }
6365: k=k+1;
6366: if (j >= jmax){
6367: jmax=j;
6368: ijmax=i;
6369: }
6370: if (j <= jmin){
6371: jmin=j;
6372: ijmin=i;
6373: }
6374: sum=sum+j;
6375: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
6376: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
6377: }
6378: }
6379: else{
6380: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 6381: /* 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 6382:
1.227 brouard 6383: k=k+1;
6384: if (j >= jmax) {
6385: jmax=j;
6386: ijmax=i;
6387: }
6388: else if (j <= jmin){
6389: jmin=j;
6390: ijmin=i;
6391: }
6392: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
6393: /*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]);*/
6394: if(j<0){
6395: nberr++;
6396: 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]);
6397: 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]);
6398: }
6399: sum=sum+j;
6400: }
6401: jk= j/stepm;
6402: jl= j -jk*stepm;
6403: ju= j -(jk+1)*stepm;
6404: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
6405: if(jl==0){
6406: dh[mi][i]=jk;
6407: bh[mi][i]=0;
6408: }else{ /* We want a negative bias in order to only have interpolation ie
6409: * to avoid the price of an extra matrix product in likelihood */
6410: dh[mi][i]=jk+1;
6411: bh[mi][i]=ju;
6412: }
6413: }else{
6414: if(jl <= -ju){
6415: dh[mi][i]=jk;
6416: bh[mi][i]=jl; /* bias is positive if real duration
6417: * is higher than the multiple of stepm and negative otherwise.
6418: */
6419: }
6420: else{
6421: dh[mi][i]=jk+1;
6422: bh[mi][i]=ju;
6423: }
6424: if(dh[mi][i]==0){
6425: dh[mi][i]=1; /* At least one step */
6426: bh[mi][i]=ju; /* At least one step */
6427: /* 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);*/
6428: }
6429: } /* end if mle */
1.126 brouard 6430: }
6431: } /* end wave */
6432: }
6433: jmean=sum/k;
6434: 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 6435: 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 6436: }
1.126 brouard 6437:
6438: /*********** Tricode ****************************/
1.220 brouard 6439: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 6440: {
6441: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
6442: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
6443: * Boring subroutine which should only output nbcode[Tvar[j]][k]
6444: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
6445: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
6446: */
1.130 brouard 6447:
1.242 brouard 6448: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
6449: int modmaxcovj=0; /* Modality max of covariates j */
6450: int cptcode=0; /* Modality max of covariates j */
6451: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 6452:
6453:
1.242 brouard 6454: /* cptcoveff=0; */
6455: /* *cptcov=0; */
1.126 brouard 6456:
1.242 brouard 6457: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 6458: for (k=1; k <= maxncov; k++)
6459: for(j=1; j<=2; j++)
6460: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 6461:
1.242 brouard 6462: /* Loop on covariates without age and products and no quantitative variable */
1.335 brouard 6463: 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 6464: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
1.343 brouard 6465: /* printf("Testing k=%d, cptcovt=%d\n",k, cptcovt); */
1.349 brouard 6466: 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 6467: switch(Fixed[k]) {
6468: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
1.311 brouard 6469: modmaxcovj=0;
6470: modmincovj=0;
1.242 brouard 6471: 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 6472: /* 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 6473: ij=(int)(covar[Tvar[k]][i]);
6474: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
6475: * If product of Vn*Vm, still boolean *:
6476: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
6477: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
6478: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
6479: modality of the nth covariate of individual i. */
6480: if (ij > modmaxcovj)
6481: modmaxcovj=ij;
6482: else if (ij < modmincovj)
6483: modmincovj=ij;
1.287 brouard 6484: if (ij <0 || ij >1 ){
1.311 brouard 6485: printf("ERROR, IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
6486: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
6487: fflush(ficlog);
6488: exit(1);
1.287 brouard 6489: }
6490: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 6491: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
6492: exit(1);
6493: }else
6494: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
6495: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
6496: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
6497: /* getting the maximum value of the modality of the covariate
6498: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
6499: female ies 1, then modmaxcovj=1.
6500: */
6501: } /* end for loop on individuals i */
6502: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
6503: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
6504: cptcode=modmaxcovj;
6505: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
6506: /*for (i=0; i<=cptcode; i++) {*/
6507: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
6508: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
6509: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
6510: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
6511: if( j != -1){
6512: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
6513: covariate for which somebody answered excluding
6514: undefined. Usually 2: 0 and 1. */
6515: }
6516: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
6517: covariate for which somebody answered including
6518: undefined. Usually 3: -1, 0 and 1. */
6519: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
6520: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
6521: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 6522:
1.242 brouard 6523: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
6524: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
6525: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
6526: /* modmincovj=3; modmaxcovj = 7; */
6527: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
6528: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
6529: /* defining two dummy variables: variables V1_1 and V1_2.*/
6530: /* nbcode[Tvar[j]][ij]=k; */
6531: /* nbcode[Tvar[j]][1]=0; */
6532: /* nbcode[Tvar[j]][2]=1; */
6533: /* nbcode[Tvar[j]][3]=2; */
6534: /* To be continued (not working yet). */
6535: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 6536:
6537: /* 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*/
6538: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
6539: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
6540: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
6541: /*, could be restored in the future */
6542: 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 6543: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
6544: break;
6545: }
6546: ij++;
1.287 brouard 6547: 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 6548: cptcode = ij; /* New max modality for covar j */
6549: } /* end of loop on modality i=-1 to 1 or more */
6550: break;
6551: case 1: /* Testing on varying covariate, could be simple and
6552: * should look at waves or product of fixed *
6553: * varying. No time to test -1, assuming 0 and 1 only */
6554: ij=0;
6555: for(i=0; i<=1;i++){
6556: nbcode[Tvar[k]][++ij]=i;
6557: }
6558: break;
6559: default:
6560: break;
6561: } /* end switch */
6562: } /* end dummy test */
1.349 brouard 6563: if(Dummy[k]==1 && Typevar[k] !=1 && Typevar[k] !=3 && Fixed ==0){ /* Fixed Quantitative covariate and not age product */
1.311 brouard 6564: 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 6565: if(Tvar[k]<=0 || Tvar[k]>=NCOVMAX){
6566: printf("Error k=%d \n",k);
6567: exit(1);
6568: }
1.311 brouard 6569: if(isnan(covar[Tvar[k]][i])){
6570: printf("ERROR, IMaCh doesn't treat fixed quantitative covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
6571: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
6572: fflush(ficlog);
6573: exit(1);
6574: }
6575: }
1.335 brouard 6576: } /* end Quanti */
1.287 brouard 6577: } /* 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 6578:
6579: for (k=-1; k< maxncov; k++) Ndum[k]=0;
6580: /* Look at fixed dummy (single or product) covariates to check empty modalities */
6581: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
6582: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
6583: 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 */
6584: 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 */
6585: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
6586: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
6587:
6588: ij=0;
6589: /* 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 6590: 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 */
6591: /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
1.242 brouard 6592: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
6593: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
1.335 brouard 6594: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy simple and non empty in the model */
6595: /* Typevar[k] =0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
6596: /* 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 6597: /* If product not in single variable we don't print results */
6598: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
1.335 brouard 6599: ++ij;/* V5 + V4 + V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V1, *//* V5 quanti, V2 quanti, V4, V3, V1 dummies */
6600: /* k= 1 2 3 4 5 6 7 8 9 */
6601: /* Tvar[k]= 5 4 3 6 5 2 7 1 1 */
6602: /* ij 1 2 3 */
6603: /* Tvaraff[ij]= 4 3 1 */
6604: /* Tmodelind[ij]=2 3 9 */
6605: /* TmodelInvind[ij]=2 1 1 */
1.242 brouard 6606: 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*/
6607: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
6608: 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 */
6609: if(Fixed[k]!=0)
6610: anyvaryingduminmodel=1;
6611: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
6612: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
6613: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
6614: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
6615: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
6616: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
6617: }
6618: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
6619: /* ij--; */
6620: /* cptcoveff=ij; /\*Number of total covariates*\/ */
1.335 brouard 6621: *cptcov=ij; /* cptcov= Number of total real effective simple dummies (fixed or time arying) effective (used as cptcoveff in other functions)
1.242 brouard 6622: * because they can be excluded from the model and real
6623: * if in the model but excluded because missing values, but how to get k from ij?*/
6624: for(j=ij+1; j<= cptcovt; j++){
6625: Tvaraff[j]=0;
6626: Tmodelind[j]=0;
6627: }
6628: for(j=ntveff+1; j<= cptcovt; j++){
6629: TmodelInvind[j]=0;
6630: }
6631: /* To be sorted */
6632: ;
6633: }
1.126 brouard 6634:
1.145 brouard 6635:
1.126 brouard 6636: /*********** Health Expectancies ****************/
6637:
1.235 brouard 6638: 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 6639:
6640: {
6641: /* Health expectancies, no variances */
1.329 brouard 6642: /* cij is the combination in the list of combination of dummy covariates */
6643: /* strstart is a string of time at start of computing */
1.164 brouard 6644: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 6645: int nhstepma, nstepma; /* Decreasing with age */
6646: double age, agelim, hf;
6647: double ***p3mat;
6648: double eip;
6649:
1.238 brouard 6650: /* pstamp(ficreseij); */
1.126 brouard 6651: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
6652: fprintf(ficreseij,"# Age");
6653: for(i=1; i<=nlstate;i++){
6654: for(j=1; j<=nlstate;j++){
6655: fprintf(ficreseij," e%1d%1d ",i,j);
6656: }
6657: fprintf(ficreseij," e%1d. ",i);
6658: }
6659: fprintf(ficreseij,"\n");
6660:
6661:
6662: if(estepm < stepm){
6663: printf ("Problem %d lower than %d\n",estepm, stepm);
6664: }
6665: else hstepm=estepm;
6666: /* We compute the life expectancy from trapezoids spaced every estepm months
6667: * This is mainly to measure the difference between two models: for example
6668: * if stepm=24 months pijx are given only every 2 years and by summing them
6669: * we are calculating an estimate of the Life Expectancy assuming a linear
6670: * progression in between and thus overestimating or underestimating according
6671: * to the curvature of the survival function. If, for the same date, we
6672: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6673: * to compare the new estimate of Life expectancy with the same linear
6674: * hypothesis. A more precise result, taking into account a more precise
6675: * curvature will be obtained if estepm is as small as stepm. */
6676:
6677: /* For example we decided to compute the life expectancy with the smallest unit */
6678: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6679: nhstepm is the number of hstepm from age to agelim
6680: nstepm is the number of stepm from age to agelin.
1.270 brouard 6681: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 6682: and note for a fixed period like estepm months */
6683: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6684: survival function given by stepm (the optimization length). Unfortunately it
6685: means that if the survival funtion is printed only each two years of age and if
6686: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6687: results. So we changed our mind and took the option of the best precision.
6688: */
6689: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6690:
6691: agelim=AGESUP;
6692: /* If stepm=6 months */
6693: /* Computed by stepm unit matrices, product of hstepm matrices, stored
6694: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
6695:
6696: /* nhstepm age range expressed in number of stepm */
6697: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6698: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6699: /* if (stepm >= YEARM) hstepm=1;*/
6700: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6701: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6702:
6703: for (age=bage; age<=fage; age ++){
6704: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6705: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6706: /* if (stepm >= YEARM) hstepm=1;*/
6707: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
6708:
6709: /* If stepm=6 months */
6710: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6711: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
1.330 brouard 6712: /* 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 6713: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 6714:
6715: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6716:
6717: printf("%d|",(int)age);fflush(stdout);
6718: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6719:
6720: /* Computing expectancies */
6721: for(i=1; i<=nlstate;i++)
6722: for(j=1; j<=nlstate;j++)
6723: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6724: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
6725:
6726: /* 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]);*/
6727:
6728: }
6729:
6730: fprintf(ficreseij,"%3.0f",age );
6731: for(i=1; i<=nlstate;i++){
6732: eip=0;
6733: for(j=1; j<=nlstate;j++){
6734: eip +=eij[i][j][(int)age];
6735: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
6736: }
6737: fprintf(ficreseij,"%9.4f", eip );
6738: }
6739: fprintf(ficreseij,"\n");
6740:
6741: }
6742: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6743: printf("\n");
6744: fprintf(ficlog,"\n");
6745:
6746: }
6747:
1.235 brouard 6748: 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 6749:
6750: {
6751: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 6752: to initial status i, ei. .
1.126 brouard 6753: */
1.336 brouard 6754: /* Very time consuming function, but already optimized with precov */
1.126 brouard 6755: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
6756: int nhstepma, nstepma; /* Decreasing with age */
6757: double age, agelim, hf;
6758: double ***p3matp, ***p3matm, ***varhe;
6759: double **dnewm,**doldm;
6760: double *xp, *xm;
6761: double **gp, **gm;
6762: double ***gradg, ***trgradg;
6763: int theta;
6764:
6765: double eip, vip;
6766:
6767: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
6768: xp=vector(1,npar);
6769: xm=vector(1,npar);
6770: dnewm=matrix(1,nlstate*nlstate,1,npar);
6771: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
6772:
6773: pstamp(ficresstdeij);
6774: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
6775: fprintf(ficresstdeij,"# Age");
6776: for(i=1; i<=nlstate;i++){
6777: for(j=1; j<=nlstate;j++)
6778: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
6779: fprintf(ficresstdeij," e%1d. ",i);
6780: }
6781: fprintf(ficresstdeij,"\n");
6782:
6783: pstamp(ficrescveij);
6784: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
6785: fprintf(ficrescveij,"# Age");
6786: for(i=1; i<=nlstate;i++)
6787: for(j=1; j<=nlstate;j++){
6788: cptj= (j-1)*nlstate+i;
6789: for(i2=1; i2<=nlstate;i2++)
6790: for(j2=1; j2<=nlstate;j2++){
6791: cptj2= (j2-1)*nlstate+i2;
6792: if(cptj2 <= cptj)
6793: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
6794: }
6795: }
6796: fprintf(ficrescveij,"\n");
6797:
6798: if(estepm < stepm){
6799: printf ("Problem %d lower than %d\n",estepm, stepm);
6800: }
6801: else hstepm=estepm;
6802: /* We compute the life expectancy from trapezoids spaced every estepm months
6803: * This is mainly to measure the difference between two models: for example
6804: * if stepm=24 months pijx are given only every 2 years and by summing them
6805: * we are calculating an estimate of the Life Expectancy assuming a linear
6806: * progression in between and thus overestimating or underestimating according
6807: * to the curvature of the survival function. If, for the same date, we
6808: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6809: * to compare the new estimate of Life expectancy with the same linear
6810: * hypothesis. A more precise result, taking into account a more precise
6811: * curvature will be obtained if estepm is as small as stepm. */
6812:
6813: /* For example we decided to compute the life expectancy with the smallest unit */
6814: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6815: nhstepm is the number of hstepm from age to agelim
6816: nstepm is the number of stepm from age to agelin.
6817: Look at hpijx to understand the reason of that which relies in memory size
6818: and note for a fixed period like estepm months */
6819: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6820: survival function given by stepm (the optimization length). Unfortunately it
6821: means that if the survival funtion is printed only each two years of age and if
6822: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6823: results. So we changed our mind and took the option of the best precision.
6824: */
6825: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6826:
6827: /* If stepm=6 months */
6828: /* nhstepm age range expressed in number of stepm */
6829: agelim=AGESUP;
6830: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
6831: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6832: /* if (stepm >= YEARM) hstepm=1;*/
6833: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6834:
6835: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6836: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6837: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
6838: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
6839: gp=matrix(0,nhstepm,1,nlstate*nlstate);
6840: gm=matrix(0,nhstepm,1,nlstate*nlstate);
6841:
6842: for (age=bage; age<=fage; age ++){
6843: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6844: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6845: /* if (stepm >= YEARM) hstepm=1;*/
6846: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 6847:
1.126 brouard 6848: /* If stepm=6 months */
6849: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6850: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
6851:
6852: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 6853:
1.126 brouard 6854: /* Computing Variances of health expectancies */
6855: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
6856: decrease memory allocation */
6857: for(theta=1; theta <=npar; theta++){
6858: for(i=1; i<=npar; i++){
1.222 brouard 6859: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6860: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 6861: }
1.235 brouard 6862: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
6863: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 6864:
1.126 brouard 6865: for(j=1; j<= nlstate; j++){
1.222 brouard 6866: for(i=1; i<=nlstate; i++){
6867: for(h=0; h<=nhstepm-1; h++){
6868: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
6869: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
6870: }
6871: }
1.126 brouard 6872: }
1.218 brouard 6873:
1.126 brouard 6874: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 6875: for(h=0; h<=nhstepm-1; h++){
6876: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
6877: }
1.126 brouard 6878: }/* End theta */
6879:
6880:
6881: for(h=0; h<=nhstepm-1; h++)
6882: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 6883: for(theta=1; theta <=npar; theta++)
6884: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 6885:
1.218 brouard 6886:
1.222 brouard 6887: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 6888: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 6889: varhe[ij][ji][(int)age] =0.;
1.218 brouard 6890:
1.222 brouard 6891: printf("%d|",(int)age);fflush(stdout);
6892: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6893: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 6894: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 6895: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
6896: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
6897: for(ij=1;ij<=nlstate*nlstate;ij++)
6898: for(ji=1;ji<=nlstate*nlstate;ji++)
6899: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 6900: }
6901: }
1.320 brouard 6902: /* if((int)age ==50){ */
6903: /* printf(" age=%d cij=%d nres=%d varhe[%d][%d]=%f ",(int)age, cij, nres, 1,2,varhe[1][2]); */
6904: /* } */
1.126 brouard 6905: /* Computing expectancies */
1.235 brouard 6906: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 6907: for(i=1; i<=nlstate;i++)
6908: for(j=1; j<=nlstate;j++)
1.222 brouard 6909: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6910: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 6911:
1.222 brouard 6912: /* 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 6913:
1.222 brouard 6914: }
1.269 brouard 6915:
6916: /* Standard deviation of expectancies ij */
1.126 brouard 6917: fprintf(ficresstdeij,"%3.0f",age );
6918: for(i=1; i<=nlstate;i++){
6919: eip=0.;
6920: vip=0.;
6921: for(j=1; j<=nlstate;j++){
1.222 brouard 6922: eip += eij[i][j][(int)age];
6923: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
6924: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
6925: 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 6926: }
6927: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
6928: }
6929: fprintf(ficresstdeij,"\n");
1.218 brouard 6930:
1.269 brouard 6931: /* Variance of expectancies ij */
1.126 brouard 6932: fprintf(ficrescveij,"%3.0f",age );
6933: for(i=1; i<=nlstate;i++)
6934: for(j=1; j<=nlstate;j++){
1.222 brouard 6935: cptj= (j-1)*nlstate+i;
6936: for(i2=1; i2<=nlstate;i2++)
6937: for(j2=1; j2<=nlstate;j2++){
6938: cptj2= (j2-1)*nlstate+i2;
6939: if(cptj2 <= cptj)
6940: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
6941: }
1.126 brouard 6942: }
6943: fprintf(ficrescveij,"\n");
1.218 brouard 6944:
1.126 brouard 6945: }
6946: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
6947: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
6948: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
6949: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
6950: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6951: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6952: printf("\n");
6953: fprintf(ficlog,"\n");
1.218 brouard 6954:
1.126 brouard 6955: free_vector(xm,1,npar);
6956: free_vector(xp,1,npar);
6957: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
6958: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
6959: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
6960: }
1.218 brouard 6961:
1.126 brouard 6962: /************ Variance ******************/
1.235 brouard 6963: 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 6964: {
1.279 brouard 6965: /** Variance of health expectancies
6966: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
6967: * double **newm;
6968: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
6969: */
1.218 brouard 6970:
6971: /* int movingaverage(); */
6972: double **dnewm,**doldm;
6973: double **dnewmp,**doldmp;
6974: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 6975: int first=0;
1.218 brouard 6976: int k;
6977: double *xp;
1.279 brouard 6978: double **gp, **gm; /**< for var eij */
6979: double ***gradg, ***trgradg; /**< for var eij */
6980: double **gradgp, **trgradgp; /**< for var p point j */
6981: double *gpp, *gmp; /**< for var p point j */
6982: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 6983: double ***p3mat;
6984: double age,agelim, hf;
6985: /* double ***mobaverage; */
6986: int theta;
6987: char digit[4];
6988: char digitp[25];
6989:
6990: char fileresprobmorprev[FILENAMELENGTH];
6991:
6992: if(popbased==1){
6993: if(mobilav!=0)
6994: strcpy(digitp,"-POPULBASED-MOBILAV_");
6995: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
6996: }
6997: else
6998: strcpy(digitp,"-STABLBASED_");
1.126 brouard 6999:
1.218 brouard 7000: /* if (mobilav!=0) { */
7001: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
7002: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
7003: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
7004: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
7005: /* } */
7006: /* } */
7007:
7008: strcpy(fileresprobmorprev,"PRMORPREV-");
7009: sprintf(digit,"%-d",ij);
7010: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
7011: strcat(fileresprobmorprev,digit); /* Tvar to be done */
7012: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
7013: strcat(fileresprobmorprev,fileresu);
7014: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
7015: printf("Problem with resultfile: %s\n", fileresprobmorprev);
7016: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
7017: }
7018: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
7019: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
7020: pstamp(ficresprobmorprev);
7021: 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 7022: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
1.337 brouard 7023:
7024: /* We use TinvDoQresult[nres][resultmodel[nres][j] we sort according to the equation model and the resultline: it is a choice */
7025: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ /\* To be done*\/ */
7026: /* fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
7027: /* } */
7028: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */ /* To be done*/
1.344 brouard 7029: /* fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); */
1.337 brouard 7030: fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 7031: }
1.337 brouard 7032: /* for(j=1;j<=cptcoveff;j++) */
7033: /* fprintf(ficresprobmorprev," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,TnsdVar[Tvaraff[j]])]); */
1.238 brouard 7034: fprintf(ficresprobmorprev,"\n");
7035:
1.218 brouard 7036: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
7037: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
7038: fprintf(ficresprobmorprev," p.%-d SE",j);
7039: for(i=1; i<=nlstate;i++)
7040: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
7041: }
7042: fprintf(ficresprobmorprev,"\n");
7043:
7044: fprintf(ficgp,"\n# Routine varevsij");
7045: fprintf(ficgp,"\nunset title \n");
7046: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
7047: 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");
7048: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 7049:
1.218 brouard 7050: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7051: pstamp(ficresvij);
7052: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
7053: if(popbased==1)
7054: 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);
7055: else
7056: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
7057: fprintf(ficresvij,"# Age");
7058: for(i=1; i<=nlstate;i++)
7059: for(j=1; j<=nlstate;j++)
7060: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
7061: fprintf(ficresvij,"\n");
7062:
7063: xp=vector(1,npar);
7064: dnewm=matrix(1,nlstate,1,npar);
7065: doldm=matrix(1,nlstate,1,nlstate);
7066: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
7067: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7068:
7069: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
7070: gpp=vector(nlstate+1,nlstate+ndeath);
7071: gmp=vector(nlstate+1,nlstate+ndeath);
7072: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 7073:
1.218 brouard 7074: if(estepm < stepm){
7075: printf ("Problem %d lower than %d\n",estepm, stepm);
7076: }
7077: else hstepm=estepm;
7078: /* For example we decided to compute the life expectancy with the smallest unit */
7079: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
7080: nhstepm is the number of hstepm from age to agelim
7081: nstepm is the number of stepm from age to agelim.
7082: Look at function hpijx to understand why because of memory size limitations,
7083: we decided (b) to get a life expectancy respecting the most precise curvature of the
7084: survival function given by stepm (the optimization length). Unfortunately it
7085: means that if the survival funtion is printed every two years of age and if
7086: you sum them up and add 1 year (area under the trapezoids) you won't get the same
7087: results. So we changed our mind and took the option of the best precision.
7088: */
7089: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
7090: agelim = AGESUP;
7091: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
7092: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7093: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
7094: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
7095: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
7096: gp=matrix(0,nhstepm,1,nlstate);
7097: gm=matrix(0,nhstepm,1,nlstate);
7098:
7099:
7100: for(theta=1; theta <=npar; theta++){
7101: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
7102: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7103: }
1.279 brouard 7104: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
7105: * returns into prlim .
1.288 brouard 7106: */
1.242 brouard 7107: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 7108:
7109: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 7110: if (popbased==1) {
7111: if(mobilav ==0){
7112: for(i=1; i<=nlstate;i++)
7113: prlim[i][i]=probs[(int)age][i][ij];
7114: }else{ /* mobilav */
7115: for(i=1; i<=nlstate;i++)
7116: prlim[i][i]=mobaverage[(int)age][i][ij];
7117: }
7118: }
1.295 brouard 7119: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h.
1.279 brouard 7120: */
7121: 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 7122: /**< 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 7123: * at horizon h in state j including mortality.
7124: */
1.218 brouard 7125: for(j=1; j<= nlstate; j++){
7126: for(h=0; h<=nhstepm; h++){
7127: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
7128: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
7129: }
7130: }
1.279 brouard 7131: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 7132: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 7133: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 7134: */
7135: for(j=nlstate+1;j<=nlstate+ndeath;j++){
7136: for(i=1,gpp[j]=0.; i<= nlstate; i++)
7137: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 7138: }
7139:
7140: /* Again with minus shift */
1.218 brouard 7141:
7142: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
7143: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 7144:
1.242 brouard 7145: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 7146:
7147: if (popbased==1) {
7148: if(mobilav ==0){
7149: for(i=1; i<=nlstate;i++)
7150: prlim[i][i]=probs[(int)age][i][ij];
7151: }else{ /* mobilav */
7152: for(i=1; i<=nlstate;i++)
7153: prlim[i][i]=mobaverage[(int)age][i][ij];
7154: }
7155: }
7156:
1.235 brouard 7157: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 7158:
7159: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
7160: for(h=0; h<=nhstepm; h++){
7161: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
7162: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
7163: }
7164: }
7165: /* This for computing probability of death (h=1 means
7166: computed over hstepm matrices product = hstepm*stepm months)
7167: as a weighted average of prlim.
7168: */
7169: for(j=nlstate+1;j<=nlstate+ndeath;j++){
7170: for(i=1,gmp[j]=0.; i<= nlstate; i++)
7171: gmp[j] += prlim[i][i]*p3mat[i][j][1];
7172: }
1.279 brouard 7173: /* end shifting computations */
7174:
7175: /**< Computing gradient matrix at horizon h
7176: */
1.218 brouard 7177: for(j=1; j<= nlstate; j++) /* vareij */
7178: for(h=0; h<=nhstepm; h++){
7179: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
7180: }
1.279 brouard 7181: /**< Gradient of overall mortality p.3 (or p.j)
7182: */
7183: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 7184: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
7185: }
7186:
7187: } /* End theta */
1.279 brouard 7188:
7189: /* We got the gradient matrix for each theta and state j */
1.218 brouard 7190: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
7191:
7192: for(h=0; h<=nhstepm; h++) /* veij */
7193: for(j=1; j<=nlstate;j++)
7194: for(theta=1; theta <=npar; theta++)
7195: trgradg[h][j][theta]=gradg[h][theta][j];
7196:
7197: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
7198: for(theta=1; theta <=npar; theta++)
7199: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 7200: /**< as well as its transposed matrix
7201: */
1.218 brouard 7202:
7203: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
7204: for(i=1;i<=nlstate;i++)
7205: for(j=1;j<=nlstate;j++)
7206: vareij[i][j][(int)age] =0.;
1.279 brouard 7207:
7208: /* Computing trgradg by matcov by gradg at age and summing over h
7209: * and k (nhstepm) formula 15 of article
7210: * Lievre-Brouard-Heathcote
7211: */
7212:
1.218 brouard 7213: for(h=0;h<=nhstepm;h++){
7214: for(k=0;k<=nhstepm;k++){
7215: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
7216: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
7217: for(i=1;i<=nlstate;i++)
7218: for(j=1;j<=nlstate;j++)
7219: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
7220: }
7221: }
7222:
1.279 brouard 7223: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
7224: * p.j overall mortality formula 49 but computed directly because
7225: * we compute the grad (wix pijx) instead of grad (pijx),even if
7226: * wix is independent of theta.
7227: */
1.218 brouard 7228: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
7229: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
7230: for(j=nlstate+1;j<=nlstate+ndeath;j++)
7231: for(i=nlstate+1;i<=nlstate+ndeath;i++)
7232: varppt[j][i]=doldmp[j][i];
7233: /* end ppptj */
7234: /* x centered again */
7235:
1.242 brouard 7236: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 7237:
7238: if (popbased==1) {
7239: if(mobilav ==0){
7240: for(i=1; i<=nlstate;i++)
7241: prlim[i][i]=probs[(int)age][i][ij];
7242: }else{ /* mobilav */
7243: for(i=1; i<=nlstate;i++)
7244: prlim[i][i]=mobaverage[(int)age][i][ij];
7245: }
7246: }
7247:
7248: /* This for computing probability of death (h=1 means
7249: computed over hstepm (estepm) matrices product = hstepm*stepm months)
7250: as a weighted average of prlim.
7251: */
1.235 brouard 7252: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 7253: for(j=nlstate+1;j<=nlstate+ndeath;j++){
7254: for(i=1,gmp[j]=0.;i<= nlstate; i++)
7255: gmp[j] += prlim[i][i]*p3mat[i][j][1];
7256: }
7257: /* end probability of death */
7258:
7259: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
7260: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
7261: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
7262: for(i=1; i<=nlstate;i++){
7263: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
7264: }
7265: }
7266: fprintf(ficresprobmorprev,"\n");
7267:
7268: fprintf(ficresvij,"%.0f ",age );
7269: for(i=1; i<=nlstate;i++)
7270: for(j=1; j<=nlstate;j++){
7271: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
7272: }
7273: fprintf(ficresvij,"\n");
7274: free_matrix(gp,0,nhstepm,1,nlstate);
7275: free_matrix(gm,0,nhstepm,1,nlstate);
7276: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
7277: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
7278: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
7279: } /* End age */
7280: free_vector(gpp,nlstate+1,nlstate+ndeath);
7281: free_vector(gmp,nlstate+1,nlstate+ndeath);
7282: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
7283: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
7284: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
7285: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
7286: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
7287: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
7288: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
7289: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
7290: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
7291: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
7292: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
7293: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
7294: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
7295: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
7296: 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);
7297: /* 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 7298: */
1.218 brouard 7299: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
7300: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 7301:
1.218 brouard 7302: free_vector(xp,1,npar);
7303: free_matrix(doldm,1,nlstate,1,nlstate);
7304: free_matrix(dnewm,1,nlstate,1,npar);
7305: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7306: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
7307: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7308: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
7309: fclose(ficresprobmorprev);
7310: fflush(ficgp);
7311: fflush(fichtm);
7312: } /* end varevsij */
1.126 brouard 7313:
7314: /************ Variance of prevlim ******************/
1.269 brouard 7315: 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 7316: {
1.205 brouard 7317: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 7318: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 7319:
1.268 brouard 7320: double **dnewmpar,**doldm;
1.126 brouard 7321: int i, j, nhstepm, hstepm;
7322: double *xp;
7323: double *gp, *gm;
7324: double **gradg, **trgradg;
1.208 brouard 7325: double **mgm, **mgp;
1.126 brouard 7326: double age,agelim;
7327: int theta;
7328:
7329: pstamp(ficresvpl);
1.288 brouard 7330: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 7331: fprintf(ficresvpl,"# Age ");
7332: if(nresult >=1)
7333: fprintf(ficresvpl," Result# ");
1.126 brouard 7334: for(i=1; i<=nlstate;i++)
7335: fprintf(ficresvpl," %1d-%1d",i,i);
7336: fprintf(ficresvpl,"\n");
7337:
7338: xp=vector(1,npar);
1.268 brouard 7339: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 7340: doldm=matrix(1,nlstate,1,nlstate);
7341:
7342: hstepm=1*YEARM; /* Every year of age */
7343: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
7344: agelim = AGESUP;
7345: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
7346: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7347: if (stepm >= YEARM) hstepm=1;
7348: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
7349: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 7350: mgp=matrix(1,npar,1,nlstate);
7351: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 7352: gp=vector(1,nlstate);
7353: gm=vector(1,nlstate);
7354:
7355: for(theta=1; theta <=npar; theta++){
7356: for(i=1; i<=npar; i++){ /* Computes gradient */
7357: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7358: }
1.288 brouard 7359: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
7360: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
7361: /* else */
7362: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 7363: for(i=1;i<=nlstate;i++){
1.126 brouard 7364: gp[i] = prlim[i][i];
1.208 brouard 7365: mgp[theta][i] = prlim[i][i];
7366: }
1.126 brouard 7367: for(i=1; i<=npar; i++) /* Computes gradient */
7368: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 7369: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
7370: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
7371: /* else */
7372: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 7373: for(i=1;i<=nlstate;i++){
1.126 brouard 7374: gm[i] = prlim[i][i];
1.208 brouard 7375: mgm[theta][i] = prlim[i][i];
7376: }
1.126 brouard 7377: for(i=1;i<=nlstate;i++)
7378: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 7379: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 7380: } /* End theta */
7381:
7382: trgradg =matrix(1,nlstate,1,npar);
7383:
7384: for(j=1; j<=nlstate;j++)
7385: for(theta=1; theta <=npar; theta++)
7386: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 7387: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7388: /* printf("\nmgm mgp %d ",(int)age); */
7389: /* for(j=1; j<=nlstate;j++){ */
7390: /* printf(" %d ",j); */
7391: /* for(theta=1; theta <=npar; theta++) */
7392: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
7393: /* printf("\n "); */
7394: /* } */
7395: /* } */
7396: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7397: /* printf("\n gradg %d ",(int)age); */
7398: /* for(j=1; j<=nlstate;j++){ */
7399: /* printf("%d ",j); */
7400: /* for(theta=1; theta <=npar; theta++) */
7401: /* printf("%d %lf ",theta,gradg[theta][j]); */
7402: /* printf("\n "); */
7403: /* } */
7404: /* } */
1.126 brouard 7405:
7406: for(i=1;i<=nlstate;i++)
7407: varpl[i][(int)age] =0.;
1.209 brouard 7408: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 7409: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7410: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 7411: }else{
1.268 brouard 7412: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7413: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 7414: }
1.126 brouard 7415: for(i=1;i<=nlstate;i++)
7416: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
7417:
7418: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 7419: if(nresult >=1)
7420: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 7421: for(i=1; i<=nlstate;i++){
1.126 brouard 7422: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 7423: /* for(j=1;j<=nlstate;j++) */
7424: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
7425: }
1.126 brouard 7426: fprintf(ficresvpl,"\n");
7427: free_vector(gp,1,nlstate);
7428: free_vector(gm,1,nlstate);
1.208 brouard 7429: free_matrix(mgm,1,npar,1,nlstate);
7430: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 7431: free_matrix(gradg,1,npar,1,nlstate);
7432: free_matrix(trgradg,1,nlstate,1,npar);
7433: } /* End age */
7434:
7435: free_vector(xp,1,npar);
7436: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 7437: free_matrix(dnewmpar,1,nlstate,1,nlstate);
7438:
7439: }
7440:
7441:
7442: /************ Variance of backprevalence limit ******************/
1.269 brouard 7443: 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 7444: {
7445: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
7446: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
7447:
7448: double **dnewmpar,**doldm;
7449: int i, j, nhstepm, hstepm;
7450: double *xp;
7451: double *gp, *gm;
7452: double **gradg, **trgradg;
7453: double **mgm, **mgp;
7454: double age,agelim;
7455: int theta;
7456:
7457: pstamp(ficresvbl);
7458: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
7459: fprintf(ficresvbl,"# Age ");
7460: if(nresult >=1)
7461: fprintf(ficresvbl," Result# ");
7462: for(i=1; i<=nlstate;i++)
7463: fprintf(ficresvbl," %1d-%1d",i,i);
7464: fprintf(ficresvbl,"\n");
7465:
7466: xp=vector(1,npar);
7467: dnewmpar=matrix(1,nlstate,1,npar);
7468: doldm=matrix(1,nlstate,1,nlstate);
7469:
7470: hstepm=1*YEARM; /* Every year of age */
7471: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
7472: agelim = AGEINF;
7473: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
7474: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7475: if (stepm >= YEARM) hstepm=1;
7476: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
7477: gradg=matrix(1,npar,1,nlstate);
7478: mgp=matrix(1,npar,1,nlstate);
7479: mgm=matrix(1,npar,1,nlstate);
7480: gp=vector(1,nlstate);
7481: gm=vector(1,nlstate);
7482:
7483: for(theta=1; theta <=npar; theta++){
7484: for(i=1; i<=npar; i++){ /* Computes gradient */
7485: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7486: }
7487: if(mobilavproj > 0 )
7488: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7489: else
7490: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7491: for(i=1;i<=nlstate;i++){
7492: gp[i] = bprlim[i][i];
7493: mgp[theta][i] = bprlim[i][i];
7494: }
7495: for(i=1; i<=npar; i++) /* Computes gradient */
7496: xp[i] = x[i] - (i==theta ?delti[theta]:0);
7497: if(mobilavproj > 0 )
7498: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7499: else
7500: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7501: for(i=1;i<=nlstate;i++){
7502: gm[i] = bprlim[i][i];
7503: mgm[theta][i] = bprlim[i][i];
7504: }
7505: for(i=1;i<=nlstate;i++)
7506: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
7507: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
7508: } /* End theta */
7509:
7510: trgradg =matrix(1,nlstate,1,npar);
7511:
7512: for(j=1; j<=nlstate;j++)
7513: for(theta=1; theta <=npar; theta++)
7514: trgradg[j][theta]=gradg[theta][j];
7515: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7516: /* printf("\nmgm mgp %d ",(int)age); */
7517: /* for(j=1; j<=nlstate;j++){ */
7518: /* printf(" %d ",j); */
7519: /* for(theta=1; theta <=npar; theta++) */
7520: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
7521: /* printf("\n "); */
7522: /* } */
7523: /* } */
7524: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7525: /* printf("\n gradg %d ",(int)age); */
7526: /* for(j=1; j<=nlstate;j++){ */
7527: /* printf("%d ",j); */
7528: /* for(theta=1; theta <=npar; theta++) */
7529: /* printf("%d %lf ",theta,gradg[theta][j]); */
7530: /* printf("\n "); */
7531: /* } */
7532: /* } */
7533:
7534: for(i=1;i<=nlstate;i++)
7535: varbpl[i][(int)age] =0.;
7536: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
7537: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7538: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
7539: }else{
7540: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7541: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
7542: }
7543: for(i=1;i<=nlstate;i++)
7544: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
7545:
7546: fprintf(ficresvbl,"%.0f ",age );
7547: if(nresult >=1)
7548: fprintf(ficresvbl,"%d ",nres );
7549: for(i=1; i<=nlstate;i++)
7550: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
7551: fprintf(ficresvbl,"\n");
7552: free_vector(gp,1,nlstate);
7553: free_vector(gm,1,nlstate);
7554: free_matrix(mgm,1,npar,1,nlstate);
7555: free_matrix(mgp,1,npar,1,nlstate);
7556: free_matrix(gradg,1,npar,1,nlstate);
7557: free_matrix(trgradg,1,nlstate,1,npar);
7558: } /* End age */
7559:
7560: free_vector(xp,1,npar);
7561: free_matrix(doldm,1,nlstate,1,npar);
7562: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 7563:
7564: }
7565:
7566: /************ Variance of one-step probabilities ******************/
7567: 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 7568: {
7569: int i, j=0, k1, l1, tj;
7570: int k2, l2, j1, z1;
7571: int k=0, l;
7572: int first=1, first1, first2;
1.326 brouard 7573: int nres=0; /* New */
1.222 brouard 7574: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
7575: double **dnewm,**doldm;
7576: double *xp;
7577: double *gp, *gm;
7578: double **gradg, **trgradg;
7579: double **mu;
7580: double age, cov[NCOVMAX+1];
7581: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
7582: int theta;
7583: char fileresprob[FILENAMELENGTH];
7584: char fileresprobcov[FILENAMELENGTH];
7585: char fileresprobcor[FILENAMELENGTH];
7586: double ***varpij;
7587:
7588: strcpy(fileresprob,"PROB_");
7589: strcat(fileresprob,fileres);
7590: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
7591: printf("Problem with resultfile: %s\n", fileresprob);
7592: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
7593: }
7594: strcpy(fileresprobcov,"PROBCOV_");
7595: strcat(fileresprobcov,fileresu);
7596: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
7597: printf("Problem with resultfile: %s\n", fileresprobcov);
7598: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
7599: }
7600: strcpy(fileresprobcor,"PROBCOR_");
7601: strcat(fileresprobcor,fileresu);
7602: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
7603: printf("Problem with resultfile: %s\n", fileresprobcor);
7604: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
7605: }
7606: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7607: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7608: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7609: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7610: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7611: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7612: pstamp(ficresprob);
7613: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
7614: fprintf(ficresprob,"# Age");
7615: pstamp(ficresprobcov);
7616: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
7617: fprintf(ficresprobcov,"# Age");
7618: pstamp(ficresprobcor);
7619: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
7620: fprintf(ficresprobcor,"# Age");
1.126 brouard 7621:
7622:
1.222 brouard 7623: for(i=1; i<=nlstate;i++)
7624: for(j=1; j<=(nlstate+ndeath);j++){
7625: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
7626: fprintf(ficresprobcov," p%1d-%1d ",i,j);
7627: fprintf(ficresprobcor," p%1d-%1d ",i,j);
7628: }
7629: /* fprintf(ficresprob,"\n");
7630: fprintf(ficresprobcov,"\n");
7631: fprintf(ficresprobcor,"\n");
7632: */
7633: xp=vector(1,npar);
7634: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7635: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
7636: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
7637: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
7638: first=1;
7639: fprintf(ficgp,"\n# Routine varprob");
7640: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
7641: fprintf(fichtm,"\n");
7642:
1.288 brouard 7643: 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 7644: 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);
7645: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 7646: and drawn. It helps understanding how is the covariance between two incidences.\
7647: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 7648: 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 7649: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
7650: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
7651: standard deviations wide on each axis. <br>\
7652: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
7653: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
7654: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
7655:
1.222 brouard 7656: cov[1]=1;
7657: /* tj=cptcoveff; */
1.225 brouard 7658: tj = (int) pow(2,cptcoveff);
1.222 brouard 7659: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
7660: j1=0;
1.332 brouard 7661:
7662: for(nres=1;nres <=nresult; nres++){ /* For each resultline */
7663: for(j1=1; j1<=tj;j1++){ /* For any combination of dummy covariates, fixed and varying */
1.342 brouard 7664: /* 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 7665: if(tj != 1 && TKresult[nres]!= j1)
7666: continue;
7667:
7668: /* for(j1=1; j1<=tj;j1++){ /\* For each valid combination of covariates or only once*\/ */
7669: /* for(nres=1;nres <=1; nres++){ /\* For each resultline *\/ */
7670: /* /\* for(nres=1;nres <=nresult; nres++){ /\\* For each resultline *\\/ *\/ */
1.222 brouard 7671: if (cptcovn>0) {
1.334 brouard 7672: fprintf(ficresprob, "\n#********** Variable ");
7673: fprintf(ficresprobcov, "\n#********** Variable ");
7674: fprintf(ficgp, "\n#********** Variable ");
7675: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
7676: fprintf(ficresprobcor, "\n#********** Variable ");
7677:
7678: /* Including quantitative variables of the resultline to be done */
7679: for (z1=1; z1<=cptcovs; z1++){ /* Loop on each variable of this resultline */
1.343 brouard 7680: /* printf("Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model); */
1.338 brouard 7681: fprintf(ficlog,"Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model);
7682: /* 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 7683: if(Dummy[modelresult[nres][z1]]==0){/* Dummy variable of the variable in position modelresult in the model corresponding to z1 in resultline */
7684: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed referenced to model equation */
7685: 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 */
7686: 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 */
7687: 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 */
7688: 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 */
7689: 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 */
7690: fprintf(ficresprob,"fixed ");
7691: fprintf(ficresprobcov,"fixed ");
7692: fprintf(ficgp,"fixed ");
7693: fprintf(fichtmcov,"fixed ");
7694: fprintf(ficresprobcor,"fixed ");
7695: }else{
7696: fprintf(ficresprob,"varyi ");
7697: fprintf(ficresprobcov,"varyi ");
7698: fprintf(ficgp,"varyi ");
7699: fprintf(fichtmcov,"varyi ");
7700: fprintf(ficresprobcor,"varyi ");
7701: }
7702: }else if(Dummy[modelresult[nres][z1]]==1){ /* Quanti variable */
7703: /* For each selected (single) quantitative value */
1.337 brouard 7704: fprintf(ficresprob," V%d=%lg ",Tvqresult[nres][z1],Tqresult[nres][z1]);
1.334 brouard 7705: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed */
7706: fprintf(ficresprob,"fixed ");
7707: fprintf(ficresprobcov,"fixed ");
7708: fprintf(ficgp,"fixed ");
7709: fprintf(fichtmcov,"fixed ");
7710: fprintf(ficresprobcor,"fixed ");
7711: }else{
7712: fprintf(ficresprob,"varyi ");
7713: fprintf(ficresprobcov,"varyi ");
7714: fprintf(ficgp,"varyi ");
7715: fprintf(fichtmcov,"varyi ");
7716: fprintf(ficresprobcor,"varyi ");
7717: }
7718: }else{
7719: 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 */
7720: 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 */
7721: exit(1);
7722: }
7723: } /* End loop on variable of this resultline */
7724: /* for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]); */
1.222 brouard 7725: fprintf(ficresprob, "**********\n#\n");
7726: fprintf(ficresprobcov, "**********\n#\n");
7727: fprintf(ficgp, "**********\n#\n");
7728: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
7729: fprintf(ficresprobcor, "**********\n#");
7730: if(invalidvarcomb[j1]){
7731: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
7732: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
7733: continue;
7734: }
7735: }
7736: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
7737: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7738: gp=vector(1,(nlstate)*(nlstate+ndeath));
7739: gm=vector(1,(nlstate)*(nlstate+ndeath));
1.334 brouard 7740: for (age=bage; age<=fage; age ++){ /* Fo each age we feed the model equation with covariates, using precov as in hpxij() ? */
1.222 brouard 7741: cov[2]=age;
7742: if(nagesqr==1)
7743: cov[3]= age*age;
1.334 brouard 7744: /* New code end of combination but for each resultline */
7745: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 7746: if(Typevar[k1]==1 || Typevar[k1] ==3){ /* A product with age */
1.334 brouard 7747: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.326 brouard 7748: }else{
1.334 brouard 7749: cov[2+nagesqr+k1]=precov[nres][k1];
1.326 brouard 7750: }
1.334 brouard 7751: }/* End of loop on model equation */
7752: /* Old code */
7753: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
7754: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)]; *\/ */
7755: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
7756: /* /\* Here comes the value of the covariate 'j1' after renumbering k with single dummy covariates *\/ */
7757: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(j1,TnsdVar[TvarsD[k]])]; */
7758: /* /\*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*\//\* j1 1 2 3 4 */
7759: /* * 1 1 1 1 1 */
7760: /* * 2 2 1 1 1 */
7761: /* * 3 1 2 1 1 */
7762: /* *\/ */
7763: /* /\* nbcode[1][1]=0 nbcode[1][2]=1;*\/ */
7764: /* } */
7765: /* /\* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
7766: /* /\* ) p nbcode[Tvar[Tage[k]]][(1 & (ij-1) >> (k-1))+1] *\/ */
7767: /* /\*for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; *\/ */
7768: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
7769: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
7770: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(j1,TnsdVar[Tvar[Tage[k]]])]*cov[2]; */
7771: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
7772: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
7773: /* 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]); */
7774: /* /\* cov[2+nagesqr+Tage[k]]=meanq[k]/idq[k]*cov[2];/\\* Using the mean of quantitative variable Tvar[Tage[k]] /\\* Tqresult[nres][k]; *\\/ *\/ */
7775: /* /\* exit(1); *\/ */
7776: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
7777: /* } */
7778: /* /\* cov[2+Tage[k]+nagesqr]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
7779: /* } */
7780: /* for (k=1; k<=cptcovprod;k++){/\* For product without age *\/ */
7781: /* if(Dummy[Tvard[k][1]]==0){ */
7782: /* if(Dummy[Tvard[k][2]]==0){ */
7783: /* 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]])]; */
7784: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
7785: /* }else{ /\* Should we use the mean of the quantitative variables? *\/ */
7786: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(j1,TnsdVar[Tvard[k][1]])] * Tqresult[nres][resultmodel[nres][k]]; */
7787: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
7788: /* } */
7789: /* }else{ */
7790: /* if(Dummy[Tvard[k][2]]==0){ */
7791: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(j1,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][TnsdVar[Tvard[k][1]]]; */
7792: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
7793: /* }else{ */
7794: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][TnsdVar[Tvard[k][1]]]* Tqinvresult[nres][TnsdVar[Tvard[k][2]]]; */
7795: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
7796: /* } */
7797: /* } */
7798: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
7799: /* } */
1.326 brouard 7800: /* For each age and combination of dummy covariates we slightly move the parameters of delti in order to get the gradient*/
1.222 brouard 7801: for(theta=1; theta <=npar; theta++){
7802: for(i=1; i<=npar; i++)
7803: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 7804:
1.222 brouard 7805: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 7806:
1.222 brouard 7807: k=0;
7808: for(i=1; i<= (nlstate); i++){
7809: for(j=1; j<=(nlstate+ndeath);j++){
7810: k=k+1;
7811: gp[k]=pmmij[i][j];
7812: }
7813: }
1.220 brouard 7814:
1.222 brouard 7815: for(i=1; i<=npar; i++)
7816: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 7817:
1.222 brouard 7818: pmij(pmmij,cov,ncovmodel,xp,nlstate);
7819: k=0;
7820: for(i=1; i<=(nlstate); i++){
7821: for(j=1; j<=(nlstate+ndeath);j++){
7822: k=k+1;
7823: gm[k]=pmmij[i][j];
7824: }
7825: }
1.220 brouard 7826:
1.222 brouard 7827: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
7828: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
7829: }
1.126 brouard 7830:
1.222 brouard 7831: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
7832: for(theta=1; theta <=npar; theta++)
7833: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 7834:
1.222 brouard 7835: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
7836: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 7837:
1.222 brouard 7838: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 7839:
1.222 brouard 7840: k=0;
7841: for(i=1; i<=(nlstate); i++){
7842: for(j=1; j<=(nlstate+ndeath);j++){
7843: k=k+1;
7844: mu[k][(int) age]=pmmij[i][j];
7845: }
7846: }
7847: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
7848: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
7849: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 7850:
1.222 brouard 7851: /*printf("\n%d ",(int)age);
7852: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7853: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7854: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7855: }*/
1.220 brouard 7856:
1.222 brouard 7857: fprintf(ficresprob,"\n%d ",(int)age);
7858: fprintf(ficresprobcov,"\n%d ",(int)age);
7859: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 7860:
1.222 brouard 7861: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
7862: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
7863: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7864: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
7865: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
7866: }
7867: i=0;
7868: for (k=1; k<=(nlstate);k++){
7869: for (l=1; l<=(nlstate+ndeath);l++){
7870: i++;
7871: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
7872: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
7873: for (j=1; j<=i;j++){
7874: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
7875: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
7876: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
7877: }
7878: }
7879: }/* end of loop for state */
7880: } /* end of loop for age */
7881: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
7882: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
7883: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7884: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7885:
7886: /* Confidence intervalle of pij */
7887: /*
7888: fprintf(ficgp,"\nunset parametric;unset label");
7889: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
7890: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
7891: 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);
7892: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
7893: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
7894: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
7895: */
7896:
7897: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
7898: first1=1;first2=2;
7899: for (k2=1; k2<=(nlstate);k2++){
7900: for (l2=1; l2<=(nlstate+ndeath);l2++){
7901: if(l2==k2) continue;
7902: j=(k2-1)*(nlstate+ndeath)+l2;
7903: for (k1=1; k1<=(nlstate);k1++){
7904: for (l1=1; l1<=(nlstate+ndeath);l1++){
7905: if(l1==k1) continue;
7906: i=(k1-1)*(nlstate+ndeath)+l1;
7907: if(i<=j) continue;
7908: for (age=bage; age<=fage; age ++){
7909: if ((int)age %5==0){
7910: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
7911: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
7912: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
7913: mu1=mu[i][(int) age]/stepm*YEARM ;
7914: mu2=mu[j][(int) age]/stepm*YEARM;
7915: c12=cv12/sqrt(v1*v2);
7916: /* Computing eigen value of matrix of covariance */
7917: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7918: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7919: if ((lc2 <0) || (lc1 <0) ){
7920: if(first2==1){
7921: first1=0;
7922: 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);
7923: }
7924: 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);
7925: /* lc1=fabs(lc1); */ /* If we want to have them positive */
7926: /* lc2=fabs(lc2); */
7927: }
1.220 brouard 7928:
1.222 brouard 7929: /* Eigen vectors */
1.280 brouard 7930: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
7931: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7932: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7933: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
7934: }else
7935: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 7936: /*v21=sqrt(1.-v11*v11); *//* error */
7937: v21=(lc1-v1)/cv12*v11;
7938: v12=-v21;
7939: v22=v11;
7940: tnalp=v21/v11;
7941: if(first1==1){
7942: first1=0;
7943: 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);
7944: }
7945: 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);
7946: /*printf(fignu*/
7947: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
7948: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
7949: if(first==1){
7950: first=0;
7951: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
7952: fprintf(ficgp,"\nset parametric;unset label");
7953: 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);
7954: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 7955: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 7956: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 7957: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 7958: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
7959: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7960: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7961: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
7962: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7963: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7964: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7965: 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 7966: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
7967: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 7968: }else{
7969: first=0;
7970: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
7971: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7972: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7973: 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 7974: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
7975: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 7976: }/* if first */
7977: } /* age mod 5 */
7978: } /* end loop age */
7979: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7980: first=1;
7981: } /*l12 */
7982: } /* k12 */
7983: } /*l1 */
7984: }/* k1 */
1.332 brouard 7985: } /* loop on combination of covariates j1 */
1.326 brouard 7986: } /* loop on nres */
1.222 brouard 7987: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
7988: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
7989: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
7990: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
7991: free_vector(xp,1,npar);
7992: fclose(ficresprob);
7993: fclose(ficresprobcov);
7994: fclose(ficresprobcor);
7995: fflush(ficgp);
7996: fflush(fichtmcov);
7997: }
1.126 brouard 7998:
7999:
8000: /******************* Printing html file ***********/
1.201 brouard 8001: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 8002: int lastpass, int stepm, int weightopt, char model[],\
8003: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.296 brouard 8004: int popforecast, int mobilav, int prevfcast, int mobilavproj, int prevbcast, int estepm , \
8005: double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \
8006: double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){
1.237 brouard 8007: int jj1, k1, i1, cpt, k4, nres;
1.319 brouard 8008: /* In fact some results are already printed in fichtm which is open */
1.126 brouard 8009: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
8010: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
8011: </ul>");
1.319 brouard 8012: /* fprintf(fichtm,"<ul><li> model=1+age+%s\n \ */
8013: /* </ul>", model); */
1.214 brouard 8014: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
8015: 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",
8016: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
1.332 brouard 8017: 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 8018: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
8019: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 8020: fprintf(fichtm,"\
8021: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 8022: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 8023: fprintf(fichtm,"\
1.217 brouard 8024: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
8025: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
8026: fprintf(fichtm,"\
1.288 brouard 8027: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 8028: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 8029: fprintf(fichtm,"\
1.288 brouard 8030: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 8031: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
8032: fprintf(fichtm,"\
1.211 brouard 8033: - (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 8034: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 8035: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 8036: if(prevfcast==1){
8037: fprintf(fichtm,"\
8038: - Prevalence projections by age and states: \
1.201 brouard 8039: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 8040: }
1.126 brouard 8041:
8042:
1.225 brouard 8043: m=pow(2,cptcoveff);
1.222 brouard 8044: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 8045:
1.317 brouard 8046: fprintf(fichtm," \n<ul><li><b>Graphs (first order)</b></li><p>");
1.264 brouard 8047:
8048: jj1=0;
8049:
8050: fprintf(fichtm," \n<ul>");
1.337 brouard 8051: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8052: /* k1=nres; */
1.338 brouard 8053: k1=TKresult[nres];
8054: if(TKresult[nres]==0)k1=1; /* To be checked for no result */
1.337 brouard 8055: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
8056: /* if(m != 1 && TKresult[nres]!= k1) */
8057: /* continue; */
1.264 brouard 8058: jj1++;
8059: if (cptcovn > 0) {
8060: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
1.337 brouard 8061: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
8062: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 8063: }
1.337 brouard 8064: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
8065: /* fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
8066: /* } */
8067: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8068: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8069: /* } */
1.264 brouard 8070: fprintf(fichtm,"\">");
8071:
8072: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
8073: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 8074: for (cpt=1; cpt<=cptcovs;cpt++){
8075: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 8076: }
1.337 brouard 8077: /* fprintf(fichtm,"************ Results for covariates"); */
8078: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
8079: /* fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
8080: /* } */
8081: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8082: /* fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8083: /* } */
1.264 brouard 8084: if(invalidvarcomb[k1]){
8085: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
8086: continue;
8087: }
8088: fprintf(fichtm,"</a></li>");
8089: } /* cptcovn >0 */
8090: }
1.317 brouard 8091: fprintf(fichtm," \n</ul>");
1.264 brouard 8092:
1.222 brouard 8093: jj1=0;
1.237 brouard 8094:
1.337 brouard 8095: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8096: /* k1=nres; */
1.338 brouard 8097: k1=TKresult[nres];
8098: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8099: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
8100: /* if(m != 1 && TKresult[nres]!= k1) */
8101: /* continue; */
1.220 brouard 8102:
1.222 brouard 8103: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
8104: jj1++;
8105: if (cptcovn > 0) {
1.264 brouard 8106: fprintf(fichtm,"\n<p><a name=\"rescov");
1.337 brouard 8107: for (cpt=1; cpt<=cptcovs;cpt++){
8108: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 8109: }
1.337 brouard 8110: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8111: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8112: /* } */
1.264 brouard 8113: fprintf(fichtm,"\"</a>");
8114:
1.222 brouard 8115: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 8116: for (cpt=1; cpt<=cptcovs;cpt++){
8117: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
8118: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 8119: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
8120: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 8121: }
1.230 brouard 8122: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.338 brouard 8123: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.222 brouard 8124: if(invalidvarcomb[k1]){
8125: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
8126: printf("\nCombination (%d) ignored because no cases \n",k1);
8127: continue;
8128: }
8129: }
8130: /* aij, bij */
1.259 brouard 8131: 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 8132: <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 8133: /* Pij */
1.241 brouard 8134: 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> \
8135: <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 8136: /* Quasi-incidences */
8137: 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 8138: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 8139: 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 8140: 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> \
8141: <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 8142: /* Survival functions (period) in state j */
8143: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 8144: 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);
8145: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
8146: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.222 brouard 8147: }
8148: /* State specific survival functions (period) */
8149: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 8150: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
8151: And probability to be observed in various states (up to %d) being in state %d at different ages. \
1.329 brouard 8152: <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);
8153: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
8154: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.222 brouard 8155: }
1.288 brouard 8156: /* Period (forward stable) prevalence in each health state */
1.222 brouard 8157: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 8158: 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 8159: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
1.329 brouard 8160: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.222 brouard 8161: }
1.296 brouard 8162: if(prevbcast==1){
1.288 brouard 8163: /* Backward prevalence in each health state */
1.222 brouard 8164: for(cpt=1; cpt<=nlstate;cpt++){
1.338 brouard 8165: 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);
8166: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJB_"),subdirf2(optionfilefiname,"PIJB_"));
8167: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.222 brouard 8168: }
1.217 brouard 8169: }
1.222 brouard 8170: if(prevfcast==1){
1.288 brouard 8171: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 8172: for(cpt=1; cpt<=nlstate;cpt++){
1.314 brouard 8173: 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);
8174: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"F_"),subdirf2(optionfilefiname,"F_"));
8175: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",
8176: subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 8177: }
8178: }
1.296 brouard 8179: if(prevbcast==1){
1.268 brouard 8180: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
8181: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 8182: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
8183: 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 \
8184: 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 8185: 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);
8186: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"FB_"),subdirf2(optionfilefiname,"FB_"));
8187: fprintf(fichtm," <img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
1.268 brouard 8188: }
8189: }
1.220 brouard 8190:
1.222 brouard 8191: for(cpt=1; cpt<=nlstate;cpt++) {
1.314 brouard 8192: 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);
8193: fprintf(fichtm," (data from text file <a href=\"%s.txt\"> %s.txt</a>)\n<br>",subdirf2(optionfilefiname,"E_"),subdirf2(optionfilefiname,"E_"));
8194: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres );
1.222 brouard 8195: }
8196: /* } /\* end i1 *\/ */
1.337 brouard 8197: }/* End k1=nres */
1.222 brouard 8198: fprintf(fichtm,"</ul>");
1.126 brouard 8199:
1.222 brouard 8200: fprintf(fichtm,"\
1.126 brouard 8201: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 8202: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 8203: - 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 8204: But because parameters are usually highly correlated (a higher incidence of disability \
8205: and a higher incidence of recovery can give very close observed transition) it might \
8206: be very useful to look not only at linear confidence intervals estimated from the \
8207: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
8208: (parameters) of the logistic regression, it might be more meaningful to visualize the \
8209: covariance matrix of the one-step probabilities. \
8210: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 8211:
1.222 brouard 8212: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
8213: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
8214: fprintf(fichtm,"\
1.126 brouard 8215: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 8216: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 8217:
1.222 brouard 8218: fprintf(fichtm,"\
1.126 brouard 8219: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 8220: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
8221: fprintf(fichtm,"\
1.126 brouard 8222: - 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): \
8223: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 8224: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 8225: fprintf(fichtm,"\
1.126 brouard 8226: - (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): \
8227: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 8228: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 8229: fprintf(fichtm,"\
1.288 brouard 8230: - 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 8231: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
8232: fprintf(fichtm,"\
1.128 brouard 8233: - 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 8234: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
8235: fprintf(fichtm,"\
1.288 brouard 8236: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 8237: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 8238:
8239: /* if(popforecast==1) fprintf(fichtm,"\n */
8240: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
8241: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
8242: /* <br>",fileres,fileres,fileres,fileres); */
8243: /* else */
1.338 brouard 8244: /* 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 8245: fflush(fichtm);
1.126 brouard 8246:
1.225 brouard 8247: m=pow(2,cptcoveff);
1.222 brouard 8248: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 8249:
1.317 brouard 8250: fprintf(fichtm," <ul><li><b>Graphs (second order)</b></li><p>");
8251:
8252: jj1=0;
8253:
8254: fprintf(fichtm," \n<ul>");
1.337 brouard 8255: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8256: /* k1=nres; */
1.338 brouard 8257: k1=TKresult[nres];
1.337 brouard 8258: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
8259: /* if(m != 1 && TKresult[nres]!= k1) */
8260: /* continue; */
1.317 brouard 8261: jj1++;
8262: if (cptcovn > 0) {
8263: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescovsecond");
1.337 brouard 8264: for (cpt=1; cpt<=cptcovs;cpt++){
8265: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8266: }
8267: fprintf(fichtm,"\">");
8268:
8269: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
8270: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 8271: for (cpt=1; cpt<=cptcovs;cpt++){
8272: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8273: }
8274: if(invalidvarcomb[k1]){
8275: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
8276: continue;
8277: }
8278: fprintf(fichtm,"</a></li>");
8279: } /* cptcovn >0 */
1.337 brouard 8280: } /* End nres */
1.317 brouard 8281: fprintf(fichtm," \n</ul>");
8282:
1.222 brouard 8283: jj1=0;
1.237 brouard 8284:
1.241 brouard 8285: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8286: /* k1=nres; */
1.338 brouard 8287: k1=TKresult[nres];
8288: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8289: /* for(k1=1; k1<=m;k1++){ */
8290: /* if(m != 1 && TKresult[nres]!= k1) */
8291: /* continue; */
1.222 brouard 8292: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
8293: jj1++;
1.126 brouard 8294: if (cptcovn > 0) {
1.317 brouard 8295: fprintf(fichtm,"\n<p><a name=\"rescovsecond");
1.337 brouard 8296: for (cpt=1; cpt<=cptcovs;cpt++){
8297: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8298: }
8299: fprintf(fichtm,"\"</a>");
8300:
1.126 brouard 8301: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 8302: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcoveff number of variables */
8303: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
8304: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 8305: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
1.317 brouard 8306: }
1.237 brouard 8307:
1.338 brouard 8308: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.220 brouard 8309:
1.222 brouard 8310: if(invalidvarcomb[k1]){
8311: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
8312: continue;
8313: }
1.337 brouard 8314: } /* If cptcovn >0 */
1.126 brouard 8315: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 8316: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.314 brouard 8317: 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);
8318: fprintf(fichtm," (data from text file <a href=\"%s\">%s</a>)\n <br>",subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
8319: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"V_"), cpt,k1,nres);
1.126 brouard 8320: }
8321: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.314 brouard 8322: health expectancies in each live states (1 to %d). If popbased=1 the smooth (due to the model) \
1.128 brouard 8323: true period expectancies (those weighted with period prevalences are also\
8324: drawn in addition to the population based expectancies computed using\
1.314 brouard 8325: 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);
8326: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>) \n<br>",subdirf2(optionfilefiname,"T_"),subdirf2(optionfilefiname,"T_"));
8327: fprintf(fichtm,"<img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 8328: /* } /\* end i1 *\/ */
1.241 brouard 8329: }/* End nres */
1.222 brouard 8330: fprintf(fichtm,"</ul>");
8331: fflush(fichtm);
1.126 brouard 8332: }
8333:
8334: /******************* Gnuplot file **************/
1.296 brouard 8335: 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 8336:
8337: char dirfileres[132],optfileres[132];
1.264 brouard 8338: char gplotcondition[132], gplotlabel[132];
1.343 brouard 8339: 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 8340: int lv=0, vlv=0, kl=0;
1.130 brouard 8341: int ng=0;
1.201 brouard 8342: int vpopbased;
1.223 brouard 8343: int ioffset; /* variable offset for columns */
1.270 brouard 8344: int iyearc=1; /* variable column for year of projection */
8345: int iagec=1; /* variable column for age of projection */
1.235 brouard 8346: int nres=0; /* Index of resultline */
1.266 brouard 8347: int istart=1; /* For starting graphs in projections */
1.219 brouard 8348:
1.126 brouard 8349: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
8350: /* printf("Problem with file %s",optionfilegnuplot); */
8351: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
8352: /* } */
8353:
8354: /*#ifdef windows */
8355: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 8356: /*#endif */
1.225 brouard 8357: m=pow(2,cptcoveff);
1.126 brouard 8358:
1.274 brouard 8359: /* diagram of the model */
8360: fprintf(ficgp,"\n#Diagram of the model \n");
8361: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
8362: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
8363: 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);
8364:
1.343 brouard 8365: 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 8366: fprintf(ficgp,"\n#show arrow\nunset label\n");
8367: 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);
8368: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
8369: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
8370: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
8371: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
8372:
1.202 brouard 8373: /* Contribution to likelihood */
8374: /* Plot the probability implied in the likelihood */
1.223 brouard 8375: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
8376: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
8377: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
8378: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 8379: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 8380: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
8381: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 8382: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
8383: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
8384: 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));
8385: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
8386: 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));
8387: for (i=1; i<= nlstate ; i ++) {
8388: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
8389: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
8390: 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);
8391: for (j=2; j<= nlstate+ndeath ; j ++) {
8392: 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);
8393: }
8394: fprintf(ficgp,";\nset out; unset ylabel;\n");
8395: }
8396: /* 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 */
8397: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
8398: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
8399: fprintf(ficgp,"\nset out;unset log\n");
8400: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 8401:
1.343 brouard 8402: /* Plot the probability implied in the likelihood by covariate value */
8403: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
8404: /* if(debugILK==1){ */
8405: for(kf=1; kf <= ncovf; kf++){ /* For each simple dummy covariate of the model */
1.347 brouard 8406: kvar=Tvar[TvarFind[kf]]; /* variable name */
8407: /* k=18+Tvar[TvarFind[kf]];/\*offset because there are 18 columns in the ILK_ file but could be placed else where *\/ */
1.350 ! brouard 8408: /* k=18+kf;/\*offset because there are 18 columns in the ILK_ file *\/ */
! 8409: k=19+kf;/*offset because there are 19 columns in the ILK_ file */
1.343 brouard 8410: for (i=1; i<= nlstate ; i ++) {
8411: fprintf(ficgp,"\nset out \"%s-p%dj-%d.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i,kvar);
8412: fprintf(ficgp,"unset log;\n# For each simple dummy covariate of the model \n plot \"%s\"",subdirf(fileresilk));
1.348 brouard 8413: if(gnuplotversion >=5.2){ /* Former gnuplot versions do not have variable pointsize!! */
8414: 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);
8415: for (j=2; j<= nlstate+ndeath ; j ++) {
8416: 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);
8417: }
8418: }else{
8419: 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);
8420: for (j=2; j<= nlstate+ndeath ; j ++) {
8421: 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);
8422: }
1.343 brouard 8423: }
8424: fprintf(ficgp,";\nset out; unset ylabel;\n");
8425: }
8426: } /* End of each covariate dummy */
8427: for(ncovv=1, iposold=0, kk=0; ncovv <= ncovvt ; ncovv++){
8428: /* Other example V1 + V3 + V5 + age*V1 + age*V3 + age*V5 + V1*V3 + V3*V5 + V1*V5
8429: * kmodel = 1 2 3 4 5 6 7 8 9
8430: * varying 1 2 3 4 5
8431: * ncovv 1 2 3 4 5 6 7 8
8432: * TvarVV[ncovv] V3 5 1 3 3 5 1 5
8433: * TvarVVind[ncovv]=kmodel 2 3 7 7 8 8 9 9
8434: * TvarFind[kmodel] 1 0 0 0 0 0 0 0 0
8435: * kdata ncovcol=[V1 V2] nqv=0 ntv=[V3 V4] nqtv=V5
8436: * Dummy[kmodel] 0 0 1 2 2 3 1 1 1
8437: */
8438: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
8439: kvar=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
8440: /* 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]); */
8441: if(ipos!=iposold){ /* Not a product or first of a product */
8442: /* printf(" %d",ipos); */
8443: /* fprintf(ficresilk," V%d",TvarVV[ncovv]); */
8444: /* printf(" DebugILK ficgp suite ipos=%d != iposold=%d\n", ipos, iposold); */
8445: kk++; /* Position of the ncovv column in ILK_ */
8446: k=18+ncovf+kk; /*offset because there are 18 columns in the ILK_ file plus ncovf fixed covariate */
8447: 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) */
8448: for (i=1; i<= nlstate ; i ++) {
8449: fprintf(ficgp,"\nset out \"%s-p%dj-%d.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i,kvar);
8450: fprintf(ficgp,"unset log;\n# For each simple dummy covariate of the model \n plot \"%s\"",subdirf(fileresilk));
8451:
1.348 brouard 8452: /* printf("Before DebugILK gnuplotversion=%g >=5.2\n",gnuplotversion); */
1.343 brouard 8453: if(gnuplotversion >=5.2){ /* Former gnuplot versions do not have variable pointsize!! */
8454: /* printf("DebugILK gnuplotversion=%g >=5.2\n",gnuplotversion); */
8455: 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);
8456: for (j=2; j<= nlstate+ndeath ; j ++) {
8457: 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);
8458: }
8459: }else{
8460: /* printf("DebugILK gnuplotversion=%g <5.2\n",gnuplotversion); */
8461: 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);
8462: for (j=2; j<= nlstate+ndeath ; j ++) {
8463: 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);
8464: }
8465: }
8466: fprintf(ficgp,";\nset out; unset ylabel;\n");
8467: }
8468: }/* End if dummy varying */
8469: }else{ /*Product */
8470: /* printf("*"); */
8471: /* fprintf(ficresilk,"*"); */
8472: }
8473: iposold=ipos;
8474: } /* For each time varying covariate */
8475: /* } /\* debugILK==1 *\/ */
8476: /* 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 */
8477: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
8478: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
8479: fprintf(ficgp,"\nset out;unset log\n");
8480: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
8481:
8482:
8483:
1.126 brouard 8484: strcpy(dirfileres,optionfilefiname);
8485: strcpy(optfileres,"vpl");
1.223 brouard 8486: /* 1eme*/
1.238 brouard 8487: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
1.337 brouard 8488: /* for (k1=1; k1<= m ; k1 ++){ /\* For each valid combination of covariate *\/ */
1.236 brouard 8489: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8490: k1=TKresult[nres];
1.338 brouard 8491: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.238 brouard 8492: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.337 brouard 8493: /* if(m != 1 && TKresult[nres]!= k1) */
8494: /* continue; */
1.238 brouard 8495: /* We are interested in selected combination by the resultline */
1.246 brouard 8496: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 8497: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 8498: strcpy(gplotlabel,"(");
1.337 brouard 8499: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8500: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8501: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8502:
8503: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate k get corresponding value lv for combination k1 *\/ */
8504: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the value of the covariate corresponding to k1 combination *\\/ *\/ */
8505: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8506: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8507: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8508: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8509: /* vlv= nbcode[Tvaraff[k]][lv]; /\* vlv is the value of the covariate lv, 0 or 1 *\/ */
8510: /* /\* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv *\/ */
8511: /* /\* printf(" V%d=%d ",Tvaraff[k],vlv); *\/ */
8512: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8513: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8514: /* } */
8515: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8516: /* /\* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); *\/ */
8517: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8518: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.264 brouard 8519: }
8520: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 8521: /* printf("\n#\n"); */
1.238 brouard 8522: fprintf(ficgp,"\n#\n");
8523: if(invalidvarcomb[k1]){
1.260 brouard 8524: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 8525: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8526: continue;
8527: }
1.235 brouard 8528:
1.241 brouard 8529: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
8530: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 8531: /* 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 8532: fprintf(ficgp,"set title \"Alive state %d %s model=1+age+%s\" font \"Helvetica,12\"\n",cpt,gplotlabel,model);
1.260 brouard 8533: 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);
8534: /* 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); */
8535: /* k1-1 error should be nres-1*/
1.238 brouard 8536: for (i=1; i<= nlstate ; i ++) {
8537: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8538: else fprintf(ficgp," %%*lf (%%*lf)");
8539: }
1.288 brouard 8540: 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 8541: for (i=1; i<= nlstate ; i ++) {
8542: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8543: else fprintf(ficgp," %%*lf (%%*lf)");
8544: }
1.260 brouard 8545: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 8546: for (i=1; i<= nlstate ; i ++) {
8547: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8548: else fprintf(ficgp," %%*lf (%%*lf)");
8549: }
1.265 brouard 8550: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
8551:
8552: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
8553: if(cptcoveff ==0){
1.271 brouard 8554: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 8555: }else{
8556: kl=0;
8557: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 8558: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
8559: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.265 brouard 8560: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8561: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8562: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8563: vlv= nbcode[Tvaraff[k]][lv];
8564: kl++;
8565: /* 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 *\/ */
8566: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8567: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8568: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
8569: if(k==cptcoveff){
8570: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
8571: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
8572: }else{
8573: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
8574: kl++;
8575: }
8576: } /* end covariate */
8577: } /* end if no covariate */
8578:
1.296 brouard 8579: if(prevbcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
1.238 brouard 8580: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 8581: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 8582: if(cptcoveff ==0){
1.245 brouard 8583: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 8584: }else{
8585: kl=0;
8586: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 8587: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
8588: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.238 brouard 8589: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8590: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8591: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 8592: /* vlv= nbcode[Tvaraff[k]][lv]; */
8593: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.223 brouard 8594: kl++;
1.238 brouard 8595: /* 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 *\/ */
8596: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8597: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8598: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
8599: if(k==cptcoveff){
1.245 brouard 8600: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 8601: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 8602: }else{
1.332 brouard 8603: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]);
1.238 brouard 8604: kl++;
8605: }
8606: } /* end covariate */
8607: } /* end if no covariate */
1.296 brouard 8608: if(prevbcast == 1){
1.268 brouard 8609: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
8610: /* k1-1 error should be nres-1*/
8611: for (i=1; i<= nlstate ; i ++) {
8612: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8613: else fprintf(ficgp," %%*lf (%%*lf)");
8614: }
1.271 brouard 8615: 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 8616: for (i=1; i<= nlstate ; i ++) {
8617: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8618: else fprintf(ficgp," %%*lf (%%*lf)");
8619: }
1.276 brouard 8620: 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 8621: for (i=1; i<= nlstate ; i ++) {
8622: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8623: else fprintf(ficgp," %%*lf (%%*lf)");
8624: }
1.274 brouard 8625: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 8626: } /* end if backprojcast */
1.296 brouard 8627: } /* end if prevbcast */
1.276 brouard 8628: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
8629: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 8630: } /* nres */
1.337 brouard 8631: /* } /\* k1 *\/ */
1.201 brouard 8632: } /* cpt */
1.235 brouard 8633:
8634:
1.126 brouard 8635: /*2 eme*/
1.337 brouard 8636: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 8637: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8638: k1=TKresult[nres];
1.338 brouard 8639: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8640: /* if(m != 1 && TKresult[nres]!= k1) */
8641: /* continue; */
1.238 brouard 8642: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 8643: strcpy(gplotlabel,"(");
1.337 brouard 8644: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8645: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8646: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8647: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8648: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8649: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8650: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8651: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8652: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8653: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8654: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8655: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8656: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8657: /* } */
8658: /* /\* for(k=1; k <= ncovds; k++){ *\/ */
8659: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8660: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8661: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8662: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 8663: }
1.264 brouard 8664: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8665: fprintf(ficgp,"\n#\n");
1.223 brouard 8666: if(invalidvarcomb[k1]){
8667: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8668: continue;
8669: }
1.219 brouard 8670:
1.241 brouard 8671: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 8672: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 8673: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
8674: if(vpopbased==0){
1.238 brouard 8675: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 8676: }else
1.238 brouard 8677: fprintf(ficgp,"\nreplot ");
8678: for (i=1; i<= nlstate+1 ; i ++) {
8679: k=2*i;
1.261 brouard 8680: 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 8681: for (j=1; j<= nlstate+1 ; j ++) {
8682: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8683: else fprintf(ficgp," %%*lf (%%*lf)");
8684: }
8685: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
8686: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 8687: 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 8688: for (j=1; j<= nlstate+1 ; j ++) {
8689: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8690: else fprintf(ficgp," %%*lf (%%*lf)");
8691: }
8692: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 8693: 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 8694: for (j=1; j<= nlstate+1 ; j ++) {
8695: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8696: else fprintf(ficgp," %%*lf (%%*lf)");
8697: }
8698: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
8699: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
8700: } /* state */
8701: } /* vpopbased */
1.264 brouard 8702: 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 8703: } /* end nres */
1.337 brouard 8704: /* } /\* k1 end 2 eme*\/ */
1.238 brouard 8705:
8706:
8707: /*3eme*/
1.337 brouard 8708: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 8709: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8710: k1=TKresult[nres];
1.338 brouard 8711: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8712: /* if(m != 1 && TKresult[nres]!= k1) */
8713: /* continue; */
1.238 brouard 8714:
1.332 brouard 8715: for (cpt=1; cpt<= nlstate ; cpt ++) { /* Fragile no verification of covariate values */
1.261 brouard 8716: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 8717: strcpy(gplotlabel,"(");
1.337 brouard 8718: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8719: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8720: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8721: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8722: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8723: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8724: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8725: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8726: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8727: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8728: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8729: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8730: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8731: /* } */
8732: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8733: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
8734: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
8735: }
1.264 brouard 8736: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8737: fprintf(ficgp,"\n#\n");
8738: if(invalidvarcomb[k1]){
8739: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8740: continue;
8741: }
8742:
8743: /* k=2+nlstate*(2*cpt-2); */
8744: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 8745: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 8746: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 8747: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 8748: 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 8749: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8750: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8751: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
8752: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8753: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8754: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 8755:
1.238 brouard 8756: */
8757: for (i=1; i< nlstate ; i ++) {
1.261 brouard 8758: 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 8759: /* 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 8760:
1.238 brouard 8761: }
1.261 brouard 8762: 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 8763: }
1.264 brouard 8764: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 8765: } /* end nres */
1.337 brouard 8766: /* } /\* end kl 3eme *\/ */
1.126 brouard 8767:
1.223 brouard 8768: /* 4eme */
1.201 brouard 8769: /* Survival functions (period) from state i in state j by initial state i */
1.337 brouard 8770: /* for (k1=1; k1<=m; k1++){ /\* For each covariate and each value *\/ */
1.238 brouard 8771: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8772: k1=TKresult[nres];
1.338 brouard 8773: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8774: /* if(m != 1 && TKresult[nres]!= k1) */
8775: /* continue; */
1.238 brouard 8776: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 8777: strcpy(gplotlabel,"(");
1.337 brouard 8778: fprintf(ficgp,"\n#\n#\n# Survival functions in state %d : 'LIJ_' files, cov=%d state=%d", cpt, k1, cpt);
8779: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8780: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8781: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8782: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8783: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8784: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8785: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8786: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8787: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8788: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8789: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8790: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8791: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8792: /* } */
8793: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8794: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8795: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 8796: }
1.264 brouard 8797: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8798: fprintf(ficgp,"\n#\n");
8799: if(invalidvarcomb[k1]){
8800: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8801: continue;
1.223 brouard 8802: }
1.238 brouard 8803:
1.241 brouard 8804: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 8805: 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 8806: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8807: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8808: k=3;
8809: for (i=1; i<= nlstate ; i ++){
8810: if(i==1){
8811: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8812: }else{
8813: fprintf(ficgp,", '' ");
8814: }
8815: l=(nlstate+ndeath)*(i-1)+1;
8816: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8817: for (j=2; j<= nlstate+ndeath ; j ++)
8818: fprintf(ficgp,"+$%d",k+l+j-1);
8819: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
8820: } /* nlstate */
1.264 brouard 8821: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8822: } /* end cpt state*/
8823: } /* end nres */
1.337 brouard 8824: /* } /\* end covariate k1 *\/ */
1.238 brouard 8825:
1.220 brouard 8826: /* 5eme */
1.201 brouard 8827: /* Survival functions (period) from state i in state j by final state j */
1.337 brouard 8828: /* for (k1=1; k1<= m ; k1++){ /\* For each covariate combination if any *\/ */
1.238 brouard 8829: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8830: k1=TKresult[nres];
1.338 brouard 8831: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8832: /* if(m != 1 && TKresult[nres]!= k1) */
8833: /* continue; */
1.238 brouard 8834: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 8835: strcpy(gplotlabel,"(");
1.238 brouard 8836: 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 8837: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8838: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8839: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8840: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8841: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8842: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8843: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8844: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8845: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8846: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8847: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8848: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8849: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8850: /* } */
8851: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8852: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8853: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 8854: }
1.264 brouard 8855: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8856: fprintf(ficgp,"\n#\n");
8857: if(invalidvarcomb[k1]){
8858: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8859: continue;
8860: }
1.227 brouard 8861:
1.241 brouard 8862: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 8863: fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
1.238 brouard 8864: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8865: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8866: k=3;
8867: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8868: if(j==1)
8869: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8870: else
8871: fprintf(ficgp,", '' ");
8872: l=(nlstate+ndeath)*(cpt-1) +j;
8873: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
8874: /* for (i=2; i<= nlstate+ndeath ; i ++) */
8875: /* fprintf(ficgp,"+$%d",k+l+i-1); */
8876: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
8877: } /* nlstate */
8878: fprintf(ficgp,", '' ");
8879: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
8880: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8881: l=(nlstate+ndeath)*(cpt-1) +j;
8882: if(j < nlstate)
8883: fprintf(ficgp,"$%d +",k+l);
8884: else
8885: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
8886: }
1.264 brouard 8887: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8888: } /* end cpt state*/
1.337 brouard 8889: /* } /\* end covariate *\/ */
1.238 brouard 8890: } /* end nres */
1.227 brouard 8891:
1.220 brouard 8892: /* 6eme */
1.202 brouard 8893: /* CV preval stable (period) for each covariate */
1.337 brouard 8894: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8895: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8896: k1=TKresult[nres];
1.338 brouard 8897: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8898: /* if(m != 1 && TKresult[nres]!= k1) */
8899: /* continue; */
1.255 brouard 8900: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 8901: strcpy(gplotlabel,"(");
1.288 brouard 8902: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 8903: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8904: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8905: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8906: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8907: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8908: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8909: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8910: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8911: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8912: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8913: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8914: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8915: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8916: /* } */
8917: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8918: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8919: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 8920: }
1.264 brouard 8921: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8922: fprintf(ficgp,"\n#\n");
1.223 brouard 8923: if(invalidvarcomb[k1]){
1.227 brouard 8924: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8925: continue;
1.223 brouard 8926: }
1.227 brouard 8927:
1.241 brouard 8928: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 8929: 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 8930: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 8931: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 8932: k=3; /* Offset */
1.255 brouard 8933: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 8934: if(i==1)
8935: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8936: else
8937: fprintf(ficgp,", '' ");
1.255 brouard 8938: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 8939: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8940: for (j=2; j<= nlstate ; j ++)
8941: fprintf(ficgp,"+$%d",k+l+j-1);
8942: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 8943: } /* nlstate */
1.264 brouard 8944: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 8945: } /* end cpt state*/
8946: } /* end covariate */
1.227 brouard 8947:
8948:
1.220 brouard 8949: /* 7eme */
1.296 brouard 8950: if(prevbcast == 1){
1.288 brouard 8951: /* CV backward prevalence for each covariate */
1.337 brouard 8952: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8953: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8954: k1=TKresult[nres];
1.338 brouard 8955: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8956: /* if(m != 1 && TKresult[nres]!= k1) */
8957: /* continue; */
1.268 brouard 8958: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 8959: strcpy(gplotlabel,"(");
1.288 brouard 8960: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 8961: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8962: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8963: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8964: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8965: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8966: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8967: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8968: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8969: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8970: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8971: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8972: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8973: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8974: /* } */
8975: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8976: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8977: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 8978: }
1.264 brouard 8979: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 8980: fprintf(ficgp,"\n#\n");
8981: if(invalidvarcomb[k1]){
8982: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8983: continue;
8984: }
8985:
1.241 brouard 8986: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 8987: 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 8988: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 8989: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 8990: k=3; /* Offset */
1.268 brouard 8991: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 8992: if(i==1)
8993: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
8994: else
8995: fprintf(ficgp,", '' ");
8996: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 8997: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.324 brouard 8998: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
8999: /* 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 9000: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 9001: /* for (j=2; j<= nlstate ; j ++) */
9002: /* fprintf(ficgp,"+$%d",k+l+j-1); */
9003: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 9004: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 9005: } /* nlstate */
1.264 brouard 9006: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 9007: } /* end cpt state*/
9008: } /* end covariate */
1.296 brouard 9009: } /* End if prevbcast */
1.218 brouard 9010:
1.223 brouard 9011: /* 8eme */
1.218 brouard 9012: if(prevfcast==1){
1.288 brouard 9013: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 9014:
1.337 brouard 9015: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 9016: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9017: k1=TKresult[nres];
1.338 brouard 9018: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9019: /* if(m != 1 && TKresult[nres]!= k1) */
9020: /* continue; */
1.211 brouard 9021: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 9022: strcpy(gplotlabel,"(");
1.288 brouard 9023: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 9024: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
9025: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9026: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9027: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
9028: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
9029: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
9030: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9031: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9032: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9033: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9034: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9035: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9036: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9037: /* } */
9038: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9039: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9040: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 9041: }
1.264 brouard 9042: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 9043: fprintf(ficgp,"\n#\n");
9044: if(invalidvarcomb[k1]){
9045: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
9046: continue;
9047: }
9048:
9049: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 9050: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 9051: 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 9052: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 9053: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 9054:
9055: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
9056: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
9057: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
9058: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 9059: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9060: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9061: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9062: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 9063: if(i==istart){
1.227 brouard 9064: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
9065: }else{
9066: fprintf(ficgp,",\\\n '' ");
9067: }
9068: if(cptcoveff ==0){ /* No covariate */
9069: ioffset=2; /* Age is in 2 */
9070: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9071: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9072: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9073: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9074: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 9075: if(i==nlstate+1){
1.270 brouard 9076: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 9077: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
9078: fprintf(ficgp,",\\\n '' ");
9079: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 9080: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 9081: offyear, \
1.268 brouard 9082: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 9083: }else
1.227 brouard 9084: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
9085: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
9086: }else{ /* more than 2 covariates */
1.270 brouard 9087: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
9088: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9089: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9090: iyearc=ioffset-1;
9091: iagec=ioffset;
1.227 brouard 9092: fprintf(ficgp," u %d:(",ioffset);
9093: kl=0;
9094: strcpy(gplotcondition,"(");
9095: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
1.332 brouard 9096: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9097: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.227 brouard 9098: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
9099: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
9100: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 9101: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
9102: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.227 brouard 9103: kl++;
9104: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
9105: kl++;
9106: if(k <cptcoveff && cptcoveff>1)
9107: sprintf(gplotcondition+strlen(gplotcondition)," && ");
9108: }
9109: strcpy(gplotcondition+strlen(gplotcondition),")");
9110: /* 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 *\/ */
9111: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
9112: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
9113: /* '' 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*/
9114: if(i==nlstate+1){
1.270 brouard 9115: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
9116: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 9117: fprintf(ficgp,",\\\n '' ");
1.270 brouard 9118: fprintf(ficgp," u %d:(",iagec);
9119: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
9120: iyearc, iagec, offyear, \
9121: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 9122: /* '' 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 9123: }else{
9124: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
9125: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
9126: }
9127: } /* end if covariate */
9128: } /* nlstate */
1.264 brouard 9129: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 9130: } /* end cpt state*/
9131: } /* end covariate */
9132: } /* End if prevfcast */
1.227 brouard 9133:
1.296 brouard 9134: if(prevbcast==1){
1.268 brouard 9135: /* Back projection from cross-sectional to stable (mixed) for each covariate */
9136:
1.337 brouard 9137: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.268 brouard 9138: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9139: k1=TKresult[nres];
1.338 brouard 9140: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9141: /* if(m != 1 && TKresult[nres]!= k1) */
9142: /* continue; */
1.268 brouard 9143: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
9144: strcpy(gplotlabel,"(");
9145: 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 9146: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
9147: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9148: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9149: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
9150: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
9151: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9152: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9153: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9154: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9155: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9156: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9157: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9158: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9159: /* } */
9160: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9161: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9162: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.268 brouard 9163: }
9164: strcpy(gplotlabel+strlen(gplotlabel),")");
9165: fprintf(ficgp,"\n#\n");
9166: if(invalidvarcomb[k1]){
9167: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
9168: continue;
9169: }
9170:
9171: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
9172: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
9173: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
9174: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
9175: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
9176:
9177: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
9178: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
9179: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
9180: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
9181: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9182: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9183: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9184: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9185: if(i==istart){
9186: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
9187: }else{
9188: fprintf(ficgp,",\\\n '' ");
9189: }
9190: if(cptcoveff ==0){ /* No covariate */
9191: ioffset=2; /* Age is in 2 */
9192: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9193: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9194: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9195: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9196: fprintf(ficgp," u %d:(", ioffset);
9197: if(i==nlstate+1){
1.270 brouard 9198: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 9199: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
9200: fprintf(ficgp,",\\\n '' ");
9201: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 9202: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 9203: offbyear, \
9204: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
9205: }else
9206: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
9207: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
9208: }else{ /* more than 2 covariates */
1.270 brouard 9209: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
9210: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9211: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9212: iyearc=ioffset-1;
9213: iagec=ioffset;
1.268 brouard 9214: fprintf(ficgp," u %d:(",ioffset);
9215: kl=0;
9216: strcpy(gplotcondition,"(");
1.337 brouard 9217: for (k=1; k<=cptcovs; k++){ /* For each covariate k of the resultline, get corresponding value lv for combination k1 */
1.338 brouard 9218: if(Dummy[modelresult[nres][k]]==0){ /* To be verified */
1.337 brouard 9219: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate writing the chain of conditions *\/ */
9220: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9221: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9222: lv=Tvresult[nres][k];
9223: vlv=TinvDoQresult[nres][Tvresult[nres][k]];
9224: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
9225: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
9226: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
9227: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
9228: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9229: kl++;
9230: /* sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); */
9231: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%lg " ,kl,Tvresult[nres][k], kl+1,TinvDoQresult[nres][Tvresult[nres][k]]);
9232: kl++;
1.338 brouard 9233: if(k <cptcovs && cptcovs>1)
1.337 brouard 9234: sprintf(gplotcondition+strlen(gplotcondition)," && ");
9235: }
1.268 brouard 9236: }
9237: strcpy(gplotcondition+strlen(gplotcondition),")");
9238: /* 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 *\/ */
9239: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
9240: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
9241: /* '' 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*/
9242: if(i==nlstate+1){
1.270 brouard 9243: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
9244: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 9245: fprintf(ficgp,",\\\n '' ");
1.270 brouard 9246: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 9247: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 9248: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
9249: iyearc,iagec,offbyear, \
9250: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 9251: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
9252: }else{
9253: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
9254: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
9255: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
9256: }
9257: } /* end if covariate */
9258: } /* nlstate */
9259: fprintf(ficgp,"\nset out; unset label;\n");
9260: } /* end cpt state*/
9261: } /* end covariate */
1.296 brouard 9262: } /* End if prevbcast */
1.268 brouard 9263:
1.227 brouard 9264:
1.238 brouard 9265: /* 9eme writing MLE parameters */
9266: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 9267: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 9268: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 9269: for(k=1; k <=(nlstate+ndeath); k++){
9270: if (k != i) {
1.227 brouard 9271: fprintf(ficgp,"# current state %d\n",k);
9272: for(j=1; j <=ncovmodel; j++){
9273: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
9274: jk++;
9275: }
9276: fprintf(ficgp,"\n");
1.126 brouard 9277: }
9278: }
1.223 brouard 9279: }
1.187 brouard 9280: fprintf(ficgp,"##############\n#\n");
1.227 brouard 9281:
1.145 brouard 9282: /*goto avoid;*/
1.238 brouard 9283: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
9284: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 9285: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
9286: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
9287: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
9288: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
9289: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
9290: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
9291: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
9292: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
9293: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
9294: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
9295: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
9296: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
9297: fprintf(ficgp,"#\n");
1.223 brouard 9298: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 9299: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.338 brouard 9300: fprintf(ficgp,"#model=1+age+%s \n",model);
1.238 brouard 9301: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 brouard 9302: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
1.337 brouard 9303: /* for(k1=1; k1 <=m; k1++) /\* For each combination of covariate *\/ */
1.237 brouard 9304: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9305: /* k1=nres; */
1.338 brouard 9306: k1=TKresult[nres];
9307: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9308: fprintf(ficgp,"\n\n# Resultline k1=%d ",k1);
1.264 brouard 9309: strcpy(gplotlabel,"(");
1.276 brouard 9310: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.337 brouard 9311: for (k=1; k<=cptcovs; k++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
9312: /* for each resultline nres, and position k, Tvresult[nres][k] gives the name of the variable and
9313: TinvDoQresult[nres][Tvresult[nres][k]] gives its value double or integer) */
9314: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9315: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9316: }
9317: /* if(m != 1 && TKresult[nres]!= k1) */
9318: /* continue; */
9319: /* fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1); */
9320: /* strcpy(gplotlabel,"("); */
9321: /* /\*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*\/ */
9322: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
9323: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
9324: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9325: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9326: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9327: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9328: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9329: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9330: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9331: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9332: /* } */
9333: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9334: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9335: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9336: /* } */
1.264 brouard 9337: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 9338: fprintf(ficgp,"\n#\n");
1.264 brouard 9339: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 9340: fprintf(ficgp,"\nset key outside ");
9341: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
9342: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 9343: fprintf(ficgp,"\nset ter svg size 640, 480 ");
9344: if (ng==1){
9345: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
9346: fprintf(ficgp,"\nunset log y");
9347: }else if (ng==2){
9348: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
9349: fprintf(ficgp,"\nset log y");
9350: }else if (ng==3){
9351: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
9352: fprintf(ficgp,"\nset log y");
9353: }else
9354: fprintf(ficgp,"\nunset title ");
9355: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
9356: i=1;
9357: for(k2=1; k2<=nlstate; k2++) {
9358: k3=i;
9359: for(k=1; k<=(nlstate+ndeath); k++) {
9360: if (k != k2){
9361: switch( ng) {
9362: case 1:
9363: if(nagesqr==0)
9364: fprintf(ficgp," p%d+p%d*x",i,i+1);
9365: else /* nagesqr =1 */
9366: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
9367: break;
9368: case 2: /* ng=2 */
9369: if(nagesqr==0)
9370: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
9371: else /* nagesqr =1 */
9372: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
9373: break;
9374: case 3:
9375: if(nagesqr==0)
9376: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
9377: else /* nagesqr =1 */
9378: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
9379: break;
9380: }
9381: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 9382: ijp=1; /* product no age */
9383: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
9384: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 9385: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.329 brouard 9386: switch(Typevar[j]){
9387: case 1:
9388: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
9389: if(j==Tage[ij]) { /* Product by age To be looked at!!*//* Bug valgrind */
9390: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
9391: if(DummyV[j]==0){/* Bug valgrind */
9392: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
9393: }else{ /* quantitative */
9394: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
9395: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9396: }
9397: ij++;
1.268 brouard 9398: }
1.237 brouard 9399: }
1.329 brouard 9400: }
9401: break;
9402: case 2:
9403: if(cptcovprod >0){
9404: if(j==Tprod[ijp]) { /* */
9405: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9406: if(ijp <=cptcovprod) { /* Product */
9407: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
9408: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
9409: /* 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)]); */
9410: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9411: }else{ /* Vn is dummy and Vm is quanti */
9412: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
9413: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9414: }
9415: }else{ /* Vn*Vm Vn is quanti */
9416: if(DummyV[Tvard[ijp][2]]==0){
9417: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
9418: }else{ /* Both quanti */
9419: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9420: }
1.268 brouard 9421: }
1.329 brouard 9422: ijp++;
1.237 brouard 9423: }
1.329 brouard 9424: } /* end Tprod */
9425: }
9426: break;
1.349 brouard 9427: case 3:
9428: if(cptcovdageprod >0){
9429: /* if(j==Tprod[ijp]) { */ /* not necessary */
9430: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
1.350 ! brouard 9431: if(ijp <=cptcovprod) { /* Product Vn*Vm and age*VN*Vm*/
! 9432: if(DummyV[Tvardk[ijp][1]]==0){/* Vn is dummy */
! 9433: if(DummyV[Tvardk[ijp][2]]==0){/* Vn and Vm are dummy */
1.349 brouard 9434: /* 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)]); */
9435: fprintf(ficgp,"+p%d*%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9436: }else{ /* Vn is dummy and Vm is quanti */
9437: /* 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 9438: 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 9439: }
1.350 ! brouard 9440: }else{ /* age* Vn*Vm Vn is quanti HERE */
1.349 brouard 9441: if(DummyV[Tvard[ijp][2]]==0){
1.350 ! brouard 9442: 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 9443: }else{ /* Both quanti */
1.350 ! brouard 9444: 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 9445: }
9446: }
9447: ijp++;
9448: }
9449: /* } */ /* end Tprod */
9450: }
9451: break;
1.329 brouard 9452: case 0:
9453: /* simple covariate */
1.264 brouard 9454: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 9455: if(Dummy[j]==0){
9456: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
9457: }else{ /* quantitative */
9458: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 9459: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 9460: }
1.329 brouard 9461: /* end simple */
9462: break;
9463: default:
9464: break;
9465: } /* end switch */
1.237 brouard 9466: } /* end j */
1.329 brouard 9467: }else{ /* k=k2 */
9468: if(ng !=1 ){ /* For logit formula of log p11 is more difficult to get */
9469: fprintf(ficgp," (1.");i=i-ncovmodel;
9470: }else
9471: i=i-ncovmodel;
1.223 brouard 9472: }
1.227 brouard 9473:
1.223 brouard 9474: if(ng != 1){
9475: fprintf(ficgp,")/(1");
1.227 brouard 9476:
1.264 brouard 9477: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 9478: if(nagesqr==0)
1.264 brouard 9479: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 9480: else /* nagesqr =1 */
1.264 brouard 9481: 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 9482:
1.223 brouard 9483: ij=1;
1.329 brouard 9484: ijp=1;
9485: /* for(j=3; j <=ncovmodel-nagesqr; j++){ */
9486: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
9487: switch(Typevar[j]){
9488: case 1:
9489: if(cptcovage >0){
9490: if(j==Tage[ij]) { /* Bug valgrind */
9491: if(ij <=cptcovage) { /* Bug valgrind */
9492: if(DummyV[j]==0){/* Bug valgrind */
9493: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]); */
9494: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,nbcode[Tvar[j]][codtabm(k1,j)]); */
9495: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]);
9496: /* fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);; */
9497: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9498: }else{ /* quantitative */
9499: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
9500: fprintf(ficgp,"+p%d*%f*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
9501: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
9502: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9503: }
9504: ij++;
9505: }
9506: }
9507: }
9508: break;
9509: case 2:
9510: if(cptcovprod >0){
9511: if(j==Tprod[ijp]) { /* */
9512: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9513: if(ijp <=cptcovprod) { /* Product */
9514: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
9515: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
9516: /* 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)]); */
9517: fprintf(ficgp,"+p%d*%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9518: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
9519: }else{ /* Vn is dummy and Vm is quanti */
9520: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
9521: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9522: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9523: }
9524: }else{ /* Vn*Vm Vn is quanti */
9525: if(DummyV[Tvard[ijp][2]]==0){
9526: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
9527: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
9528: }else{ /* Both quanti */
9529: fprintf(ficgp,"+p%d*%f*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9530: /* fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9531: }
9532: }
9533: ijp++;
9534: }
9535: } /* end Tprod */
9536: } /* end if */
9537: break;
1.349 brouard 9538: case 3:
9539: if(cptcovdageprod >0){
9540: /* if(j==Tprod[ijp]) { /\* *\/ */
9541: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9542: if(ijp <=cptcovprod) { /* Product */
1.350 ! brouard 9543: if(DummyV[Tvardk[ijp][1]]==0){/* Vn is dummy */
! 9544: if(DummyV[Tvardk[ijp][2]]==0){/* Vn and Vm are dummy */
1.349 brouard 9545: /* 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 9546: 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 9547: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
9548: }else{ /* Vn is dummy and Vm is quanti */
9549: /* 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 9550: 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 9551: /* fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9552: }
9553: }else{ /* Vn*Vm Vn is quanti */
1.350 ! brouard 9554: if(DummyV[Tvardk[ijp][2]]==0){
! 9555: 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 9556: /* fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
9557: }else{ /* Both quanti */
1.350 ! brouard 9558: 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 9559: /* fprintf(ficgp,"+p%d*%f*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9560: }
9561: }
9562: ijp++;
9563: }
9564: /* } /\* end Tprod *\/ */
9565: } /* end if */
9566: break;
1.329 brouard 9567: case 0:
9568: /* simple covariate */
9569: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
9570: if(Dummy[j]==0){
9571: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
9572: fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]); /* */
9573: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
9574: }else{ /* quantitative */
9575: fprintf(ficgp,"+p%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* */
9576: /* fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* *\/ */
9577: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9578: }
9579: /* end simple */
9580: /* fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);/\* Valgrind bug nbcode *\/ */
9581: break;
9582: default:
9583: break;
9584: } /* end switch */
1.223 brouard 9585: }
9586: fprintf(ficgp,")");
9587: }
9588: fprintf(ficgp,")");
9589: if(ng ==2)
1.276 brouard 9590: 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 9591: else /* ng= 3 */
1.276 brouard 9592: 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 9593: }else{ /* end ng <> 1 */
1.223 brouard 9594: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 9595: 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 9596: }
9597: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
9598: fprintf(ficgp,",");
9599: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
9600: fprintf(ficgp,",");
9601: i=i+ncovmodel;
9602: } /* end k */
9603: } /* end k2 */
1.276 brouard 9604: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
9605: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.337 brouard 9606: } /* end resultline */
1.223 brouard 9607: } /* end ng */
9608: /* avoid: */
9609: fflush(ficgp);
1.126 brouard 9610: } /* end gnuplot */
9611:
9612:
9613: /*************** Moving average **************/
1.219 brouard 9614: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 9615: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 9616:
1.222 brouard 9617: int i, cpt, cptcod;
9618: int modcovmax =1;
9619: int mobilavrange, mob;
9620: int iage=0;
1.288 brouard 9621: int firstA1=0, firstA2=0;
1.222 brouard 9622:
1.266 brouard 9623: double sum=0., sumr=0.;
1.222 brouard 9624: double age;
1.266 brouard 9625: double *sumnewp, *sumnewm, *sumnewmr;
9626: double *agemingood, *agemaxgood;
9627: double *agemingoodr, *agemaxgoodr;
1.222 brouard 9628:
9629:
1.278 brouard 9630: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
9631: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 9632:
9633: sumnewp = vector(1,ncovcombmax);
9634: sumnewm = vector(1,ncovcombmax);
1.266 brouard 9635: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 9636: agemingood = vector(1,ncovcombmax);
1.266 brouard 9637: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 9638: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 9639: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 9640:
9641: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 9642: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 9643: sumnewp[cptcod]=0.;
1.266 brouard 9644: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
9645: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 9646: }
9647: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
9648:
1.266 brouard 9649: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
9650: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 9651: else mobilavrange=mobilav;
9652: for (age=bage; age<=fage; age++)
9653: for (i=1; i<=nlstate;i++)
9654: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
9655: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9656: /* We keep the original values on the extreme ages bage, fage and for
9657: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
9658: we use a 5 terms etc. until the borders are no more concerned.
9659: */
9660: for (mob=3;mob <=mobilavrange;mob=mob+2){
9661: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 9662: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
9663: sumnewm[cptcod]=0.;
9664: for (i=1; i<=nlstate;i++){
1.222 brouard 9665: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
9666: for (cpt=1;cpt<=(mob-1)/2;cpt++){
9667: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
9668: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
9669: }
9670: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 9671: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9672: } /* end i */
9673: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
9674: } /* end cptcod */
1.222 brouard 9675: }/* end age */
9676: }/* end mob */
1.266 brouard 9677: }else{
9678: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 9679: return -1;
1.266 brouard 9680: }
9681:
9682: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 9683: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
9684: if(invalidvarcomb[cptcod]){
9685: printf("\nCombination (%d) ignored because no cases \n",cptcod);
9686: continue;
9687: }
1.219 brouard 9688:
1.266 brouard 9689: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
9690: sumnewm[cptcod]=0.;
9691: sumnewmr[cptcod]=0.;
9692: for (i=1; i<=nlstate;i++){
9693: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9694: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9695: }
9696: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9697: agemingoodr[cptcod]=age;
9698: }
9699: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9700: agemingood[cptcod]=age;
9701: }
9702: } /* age */
9703: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 9704: sumnewm[cptcod]=0.;
1.266 brouard 9705: sumnewmr[cptcod]=0.;
1.222 brouard 9706: for (i=1; i<=nlstate;i++){
9707: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 9708: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9709: }
9710: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9711: agemaxgoodr[cptcod]=age;
1.222 brouard 9712: }
9713: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 9714: agemaxgood[cptcod]=age;
9715: }
9716: } /* age */
9717: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
9718: /* but they will change */
1.288 brouard 9719: firstA1=0;firstA2=0;
1.266 brouard 9720: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
9721: sumnewm[cptcod]=0.;
9722: sumnewmr[cptcod]=0.;
9723: for (i=1; i<=nlstate;i++){
9724: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9725: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9726: }
9727: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
9728: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9729: agemaxgoodr[cptcod]=age; /* age min */
9730: for (i=1; i<=nlstate;i++)
9731: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9732: }else{ /* bad we change the value with the values of good ages */
9733: for (i=1; i<=nlstate;i++){
9734: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
9735: } /* i */
9736: } /* end bad */
9737: }else{
9738: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9739: agemaxgood[cptcod]=age;
9740: }else{ /* bad we change the value with the values of good ages */
9741: for (i=1; i<=nlstate;i++){
9742: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
9743: } /* i */
9744: } /* end bad */
9745: }/* end else */
9746: sum=0.;sumr=0.;
9747: for (i=1; i<=nlstate;i++){
9748: sum+=mobaverage[(int)age][i][cptcod];
9749: sumr+=probs[(int)age][i][cptcod];
9750: }
9751: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 9752: if(!firstA1){
9753: firstA1=1;
9754: 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);
9755: }
9756: 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 9757: } /* end bad */
9758: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
9759: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 9760: if(!firstA2){
9761: firstA2=1;
9762: 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);
9763: }
9764: 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 9765: } /* end bad */
9766: }/* age */
1.266 brouard 9767:
9768: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 9769: sumnewm[cptcod]=0.;
1.266 brouard 9770: sumnewmr[cptcod]=0.;
1.222 brouard 9771: for (i=1; i<=nlstate;i++){
9772: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 9773: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9774: }
9775: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
9776: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
9777: agemingoodr[cptcod]=age;
9778: for (i=1; i<=nlstate;i++)
9779: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9780: }else{ /* bad we change the value with the values of good ages */
9781: for (i=1; i<=nlstate;i++){
9782: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
9783: } /* i */
9784: } /* end bad */
9785: }else{
9786: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9787: agemingood[cptcod]=age;
9788: }else{ /* bad */
9789: for (i=1; i<=nlstate;i++){
9790: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
9791: } /* i */
9792: } /* end bad */
9793: }/* end else */
9794: sum=0.;sumr=0.;
9795: for (i=1; i<=nlstate;i++){
9796: sum+=mobaverage[(int)age][i][cptcod];
9797: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 9798: }
1.266 brouard 9799: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 9800: 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 9801: } /* end bad */
9802: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
9803: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 9804: 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 9805: } /* end bad */
9806: }/* age */
1.266 brouard 9807:
1.222 brouard 9808:
9809: for (age=bage; age<=fage; age++){
1.235 brouard 9810: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 9811: sumnewp[cptcod]=0.;
9812: sumnewm[cptcod]=0.;
9813: for (i=1; i<=nlstate;i++){
9814: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
9815: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9816: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
9817: }
9818: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
9819: }
9820: /* printf("\n"); */
9821: /* } */
1.266 brouard 9822:
1.222 brouard 9823: /* brutal averaging */
1.266 brouard 9824: /* for (i=1; i<=nlstate;i++){ */
9825: /* for (age=1; age<=bage; age++){ */
9826: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
9827: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
9828: /* } */
9829: /* for (age=fage; age<=AGESUP; age++){ */
9830: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
9831: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
9832: /* } */
9833: /* } /\* end i status *\/ */
9834: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
9835: /* for (age=1; age<=AGESUP; age++){ */
9836: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
9837: /* mobaverage[(int)age][i][cptcod]=0.; */
9838: /* } */
9839: /* } */
1.222 brouard 9840: }/* end cptcod */
1.266 brouard 9841: free_vector(agemaxgoodr,1, ncovcombmax);
9842: free_vector(agemaxgood,1, ncovcombmax);
9843: free_vector(agemingood,1, ncovcombmax);
9844: free_vector(agemingoodr,1, ncovcombmax);
9845: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 9846: free_vector(sumnewm,1, ncovcombmax);
9847: free_vector(sumnewp,1, ncovcombmax);
9848: return 0;
9849: }/* End movingaverage */
1.218 brouard 9850:
1.126 brouard 9851:
1.296 brouard 9852:
1.126 brouard 9853: /************** Forecasting ******************/
1.296 brouard 9854: /* 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)*/
9855: 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){
9856: /* dateintemean, mean date of interviews
9857: dateprojd, year, month, day of starting projection
9858: dateprojf date of end of projection;year of end of projection (same day and month as proj1).
1.126 brouard 9859: agemin, agemax range of age
9860: dateprev1 dateprev2 range of dates during which prevalence is computed
9861: */
1.296 brouard 9862: /* double anprojd, mprojd, jprojd; */
9863: /* double anprojf, mprojf, jprojf; */
1.267 brouard 9864: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 9865: double agec; /* generic age */
1.296 brouard 9866: double agelim, ppij, yp,yp1,yp2;
1.126 brouard 9867: double *popeffectif,*popcount;
9868: double ***p3mat;
1.218 brouard 9869: /* double ***mobaverage; */
1.126 brouard 9870: char fileresf[FILENAMELENGTH];
9871:
9872: agelim=AGESUP;
1.211 brouard 9873: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
9874: in each health status at the date of interview (if between dateprev1 and dateprev2).
9875: We still use firstpass and lastpass as another selection.
9876: */
1.214 brouard 9877: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
9878: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 9879:
1.201 brouard 9880: strcpy(fileresf,"F_");
9881: strcat(fileresf,fileresu);
1.126 brouard 9882: if((ficresf=fopen(fileresf,"w"))==NULL) {
9883: printf("Problem with forecast resultfile: %s\n", fileresf);
9884: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
9885: }
1.235 brouard 9886: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
9887: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 9888:
1.225 brouard 9889: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 9890:
9891:
9892: stepsize=(int) (stepm+YEARM-1)/YEARM;
9893: if (stepm<=12) stepsize=1;
9894: if(estepm < stepm){
9895: printf ("Problem %d lower than %d\n",estepm, stepm);
9896: }
1.270 brouard 9897: else{
9898: hstepm=estepm;
9899: }
9900: if(estepm > stepm){ /* Yes every two year */
9901: stepsize=2;
9902: }
1.296 brouard 9903: hstepm=hstepm/stepm;
1.126 brouard 9904:
1.296 brouard 9905:
9906: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
9907: /* fractional in yp1 *\/ */
9908: /* aintmean=yp; */
9909: /* yp2=modf((yp1*12),&yp); */
9910: /* mintmean=yp; */
9911: /* yp1=modf((yp2*30.5),&yp); */
9912: /* jintmean=yp; */
9913: /* if(jintmean==0) jintmean=1; */
9914: /* if(mintmean==0) mintmean=1; */
1.126 brouard 9915:
1.296 brouard 9916:
9917: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */
9918: /* date2dmy(dateprojd,&jprojd, &mprojd, &anprojd); */
9919: /* date2dmy(dateprojf,&jprojf, &mprojf, &anprojf); */
1.227 brouard 9920: i1=pow(2,cptcoveff);
1.126 brouard 9921: if (cptcovn < 1){i1=1;}
9922:
1.296 brouard 9923: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.126 brouard 9924:
9925: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 9926:
1.126 brouard 9927: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 9928: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.332 brouard 9929: for(k=1; k<=i1;k++){ /* We want to find the combination k corresponding to the values of the dummies given in this resut line (to be cleaned one day) */
1.253 brouard 9930: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 9931: continue;
1.227 brouard 9932: if(invalidvarcomb[k]){
9933: printf("\nCombination (%d) projection ignored because no cases \n",k);
9934: continue;
9935: }
9936: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
9937: for(j=1;j<=cptcoveff;j++) {
1.332 brouard 9938: /* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); */
9939: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.227 brouard 9940: }
1.235 brouard 9941: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 9942: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 9943: }
1.227 brouard 9944: fprintf(ficresf," yearproj age");
9945: for(j=1; j<=nlstate+ndeath;j++){
9946: for(i=1; i<=nlstate;i++)
9947: fprintf(ficresf," p%d%d",i,j);
9948: fprintf(ficresf," wp.%d",j);
9949: }
1.296 brouard 9950: for (yearp=0; yearp<=(anprojf-anprojd);yearp +=stepsize) {
1.227 brouard 9951: fprintf(ficresf,"\n");
1.296 brouard 9952: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jprojd,mprojd,anprojd+yearp);
1.270 brouard 9953: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
9954: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 9955: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
9956: nhstepm = nhstepm/hstepm;
9957: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9958: oldm=oldms;savm=savms;
1.268 brouard 9959: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 9960: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 9961: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 9962: for (h=0; h<=nhstepm; h++){
9963: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 9964: break;
9965: }
9966: }
9967: fprintf(ficresf,"\n");
9968: for(j=1;j<=cptcoveff;j++)
1.332 brouard 9969: /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Tvaraff not correct *\/ */
9970: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /* TnsdVar[Tvaraff] correct */
1.296 brouard 9971: fprintf(ficresf,"%.f %.f ",anprojd+yearp,agec+h*hstepm/YEARM*stepm);
1.268 brouard 9972:
9973: for(j=1; j<=nlstate+ndeath;j++) {
9974: ppij=0.;
9975: for(i=1; i<=nlstate;i++) {
1.278 brouard 9976: if (mobilav>=1)
9977: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
9978: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
9979: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
9980: }
1.268 brouard 9981: fprintf(ficresf," %.3f", p3mat[i][j][h]);
9982: } /* end i */
9983: fprintf(ficresf," %.3f", ppij);
9984: }/* end j */
1.227 brouard 9985: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9986: } /* end agec */
1.266 brouard 9987: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
9988: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 9989: } /* end yearp */
9990: } /* end k */
1.219 brouard 9991:
1.126 brouard 9992: fclose(ficresf);
1.215 brouard 9993: printf("End of Computing forecasting \n");
9994: fprintf(ficlog,"End of Computing forecasting\n");
9995:
1.126 brouard 9996: }
9997:
1.269 brouard 9998: /************** Back Forecasting ******************/
1.296 brouard 9999: /* 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){ */
10000: 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){
10001: /* back1, year, month, day of starting backprojection
1.267 brouard 10002: agemin, agemax range of age
10003: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 10004: anback2 year of end of backprojection (same day and month as back1).
10005: prevacurrent and prev are prevalences.
1.267 brouard 10006: */
10007: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
10008: double agec; /* generic age */
1.302 brouard 10009: double agelim, ppij, ppi, yp,yp1,yp2; /* ,jintmean,mintmean,aintmean;*/
1.267 brouard 10010: double *popeffectif,*popcount;
10011: double ***p3mat;
10012: /* double ***mobaverage; */
10013: char fileresfb[FILENAMELENGTH];
10014:
1.268 brouard 10015: agelim=AGEINF;
1.267 brouard 10016: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
10017: in each health status at the date of interview (if between dateprev1 and dateprev2).
10018: We still use firstpass and lastpass as another selection.
10019: */
10020: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
10021: /* firstpass, lastpass, stepm, weightopt, model); */
10022:
10023: /*Do we need to compute prevalence again?*/
10024:
10025: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
10026:
10027: strcpy(fileresfb,"FB_");
10028: strcat(fileresfb,fileresu);
10029: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
10030: printf("Problem with back forecast resultfile: %s\n", fileresfb);
10031: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
10032: }
10033: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
10034: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
10035:
10036: if (cptcoveff==0) ncodemax[cptcoveff]=1;
10037:
10038:
10039: stepsize=(int) (stepm+YEARM-1)/YEARM;
10040: if (stepm<=12) stepsize=1;
10041: if(estepm < stepm){
10042: printf ("Problem %d lower than %d\n",estepm, stepm);
10043: }
1.270 brouard 10044: else{
10045: hstepm=estepm;
10046: }
10047: if(estepm >= stepm){ /* Yes every two year */
10048: stepsize=2;
10049: }
1.267 brouard 10050:
10051: hstepm=hstepm/stepm;
1.296 brouard 10052: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
10053: /* fractional in yp1 *\/ */
10054: /* aintmean=yp; */
10055: /* yp2=modf((yp1*12),&yp); */
10056: /* mintmean=yp; */
10057: /* yp1=modf((yp2*30.5),&yp); */
10058: /* jintmean=yp; */
10059: /* if(jintmean==0) jintmean=1; */
10060: /* if(mintmean==0) jintmean=1; */
1.267 brouard 10061:
10062: i1=pow(2,cptcoveff);
10063: if (cptcovn < 1){i1=1;}
10064:
1.296 brouard 10065: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
10066: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 10067:
10068: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
10069:
10070: for(nres=1; nres <= nresult; nres++) /* For each resultline */
10071: for(k=1; k<=i1;k++){
10072: if(i1 != 1 && TKresult[nres]!= k)
10073: continue;
10074: if(invalidvarcomb[k]){
10075: printf("\nCombination (%d) projection ignored because no cases \n",k);
10076: continue;
10077: }
1.268 brouard 10078: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.267 brouard 10079: for(j=1;j<=cptcoveff;j++) {
1.332 brouard 10080: fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.267 brouard 10081: }
10082: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10083: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10084: }
10085: fprintf(ficresfb," yearbproj age");
10086: for(j=1; j<=nlstate+ndeath;j++){
10087: for(i=1; i<=nlstate;i++)
1.268 brouard 10088: fprintf(ficresfb," b%d%d",i,j);
10089: fprintf(ficresfb," b.%d",j);
1.267 brouard 10090: }
1.296 brouard 10091: for (yearp=0; yearp>=(anbackf-anbackd);yearp -=stepsize) {
1.267 brouard 10092: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
10093: fprintf(ficresfb,"\n");
1.296 brouard 10094: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jbackd,mbackd,anbackd+yearp);
1.273 brouard 10095: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 10096: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
10097: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 10098: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 10099: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 10100: nhstepm = nhstepm/hstepm;
10101: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10102: oldm=oldms;savm=savms;
1.268 brouard 10103: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 10104: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 10105: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 10106: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
10107: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
10108: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 10109: for (h=0; h<=nhstepm; h++){
1.268 brouard 10110: if (h*hstepm/YEARM*stepm ==-yearp) {
10111: break;
10112: }
10113: }
10114: fprintf(ficresfb,"\n");
10115: for(j=1;j<=cptcoveff;j++)
1.332 brouard 10116: fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.296 brouard 10117: fprintf(ficresfb,"%.f %.f ",anbackd+yearp,agec-h*hstepm/YEARM*stepm);
1.268 brouard 10118: for(i=1; i<=nlstate+ndeath;i++) {
10119: ppij=0.;ppi=0.;
10120: for(j=1; j<=nlstate;j++) {
10121: /* if (mobilav==1) */
1.269 brouard 10122: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
10123: ppi=ppi+prevacurrent[(int)agec][j][k];
10124: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
10125: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 10126: /* else { */
10127: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
10128: /* } */
1.268 brouard 10129: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
10130: } /* end j */
10131: if(ppi <0.99){
10132: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
10133: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
10134: }
10135: fprintf(ficresfb," %.3f", ppij);
10136: }/* end j */
1.267 brouard 10137: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10138: } /* end agec */
10139: } /* end yearp */
10140: } /* end k */
1.217 brouard 10141:
1.267 brouard 10142: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 10143:
1.267 brouard 10144: fclose(ficresfb);
10145: printf("End of Computing Back forecasting \n");
10146: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 10147:
1.267 brouard 10148: }
1.217 brouard 10149:
1.269 brouard 10150: /* Variance of prevalence limit: varprlim */
10151: 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 10152: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 10153:
10154: char fileresvpl[FILENAMELENGTH];
10155: FILE *ficresvpl;
10156: double **oldm, **savm;
10157: double **varpl; /* Variances of prevalence limits by age */
10158: int i1, k, nres, j ;
10159:
10160: strcpy(fileresvpl,"VPL_");
10161: strcat(fileresvpl,fileresu);
10162: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 10163: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 10164: exit(0);
10165: }
1.288 brouard 10166: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
10167: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 10168:
10169: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
10170: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
10171:
10172: i1=pow(2,cptcoveff);
10173: if (cptcovn < 1){i1=1;}
10174:
1.337 brouard 10175: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10176: k=TKresult[nres];
1.338 brouard 10177: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 10178: /* for(k=1; k<=i1;k++){ /\* We find the combination equivalent to result line values of dummies *\/ */
1.269 brouard 10179: if(i1 != 1 && TKresult[nres]!= k)
10180: continue;
10181: fprintf(ficresvpl,"\n#****** ");
10182: printf("\n#****** ");
10183: fprintf(ficlog,"\n#****** ");
1.337 brouard 10184: for(j=1;j<=cptcovs;j++) {
10185: fprintf(ficresvpl,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10186: fprintf(ficlog,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10187: printf("V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10188: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10189: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.269 brouard 10190: }
1.337 brouard 10191: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
10192: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10193: /* fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10194: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10195: /* } */
1.269 brouard 10196: fprintf(ficresvpl,"******\n");
10197: printf("******\n");
10198: fprintf(ficlog,"******\n");
10199:
10200: varpl=matrix(1,nlstate,(int) bage, (int) fage);
10201: oldm=oldms;savm=savms;
10202: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
10203: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
10204: /*}*/
10205: }
10206:
10207: fclose(ficresvpl);
1.288 brouard 10208: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
10209: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 10210:
10211: }
10212: /* Variance of back prevalence: varbprlim */
10213: 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){
10214: /*------- Variance of back (stable) prevalence------*/
10215:
10216: char fileresvbl[FILENAMELENGTH];
10217: FILE *ficresvbl;
10218:
10219: double **oldm, **savm;
10220: double **varbpl; /* Variances of back prevalence limits by age */
10221: int i1, k, nres, j ;
10222:
10223: strcpy(fileresvbl,"VBL_");
10224: strcat(fileresvbl,fileresu);
10225: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
10226: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
10227: exit(0);
10228: }
10229: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
10230: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
10231:
10232:
10233: i1=pow(2,cptcoveff);
10234: if (cptcovn < 1){i1=1;}
10235:
1.337 brouard 10236: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10237: k=TKresult[nres];
1.338 brouard 10238: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 10239: /* for(k=1; k<=i1;k++){ */
10240: /* if(i1 != 1 && TKresult[nres]!= k) */
10241: /* continue; */
1.269 brouard 10242: fprintf(ficresvbl,"\n#****** ");
10243: printf("\n#****** ");
10244: fprintf(ficlog,"\n#****** ");
1.337 brouard 10245: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */
1.338 brouard 10246: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
10247: fprintf(ficresvbl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
10248: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
1.337 brouard 10249: /* for(j=1;j<=cptcoveff;j++) { */
10250: /* fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10251: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10252: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10253: /* } */
10254: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
10255: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10256: /* fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10257: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
1.269 brouard 10258: }
10259: fprintf(ficresvbl,"******\n");
10260: printf("******\n");
10261: fprintf(ficlog,"******\n");
10262:
10263: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
10264: oldm=oldms;savm=savms;
10265:
10266: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
10267: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
10268: /*}*/
10269: }
10270:
10271: fclose(ficresvbl);
10272: printf("done variance-covariance of back prevalence\n");fflush(stdout);
10273: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
10274:
10275: } /* End of varbprlim */
10276:
1.126 brouard 10277: /************** Forecasting *****not tested NB*************/
1.227 brouard 10278: /* 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 10279:
1.227 brouard 10280: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
10281: /* int *popage; */
10282: /* double calagedatem, agelim, kk1, kk2; */
10283: /* double *popeffectif,*popcount; */
10284: /* double ***p3mat,***tabpop,***tabpopprev; */
10285: /* /\* double ***mobaverage; *\/ */
10286: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 10287:
1.227 brouard 10288: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10289: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10290: /* agelim=AGESUP; */
10291: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 10292:
1.227 brouard 10293: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 10294:
10295:
1.227 brouard 10296: /* strcpy(filerespop,"POP_"); */
10297: /* strcat(filerespop,fileresu); */
10298: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
10299: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
10300: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
10301: /* } */
10302: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
10303: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 10304:
1.227 brouard 10305: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 10306:
1.227 brouard 10307: /* /\* if (mobilav!=0) { *\/ */
10308: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
10309: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
10310: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
10311: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
10312: /* /\* } *\/ */
10313: /* /\* } *\/ */
1.126 brouard 10314:
1.227 brouard 10315: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
10316: /* if (stepm<=12) stepsize=1; */
1.126 brouard 10317:
1.227 brouard 10318: /* agelim=AGESUP; */
1.126 brouard 10319:
1.227 brouard 10320: /* hstepm=1; */
10321: /* hstepm=hstepm/stepm; */
1.218 brouard 10322:
1.227 brouard 10323: /* if (popforecast==1) { */
10324: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
10325: /* printf("Problem with population file : %s\n",popfile);exit(0); */
10326: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
10327: /* } */
10328: /* popage=ivector(0,AGESUP); */
10329: /* popeffectif=vector(0,AGESUP); */
10330: /* popcount=vector(0,AGESUP); */
1.126 brouard 10331:
1.227 brouard 10332: /* i=1; */
10333: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 10334:
1.227 brouard 10335: /* imx=i; */
10336: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
10337: /* } */
1.218 brouard 10338:
1.227 brouard 10339: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
10340: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
10341: /* k=k+1; */
10342: /* fprintf(ficrespop,"\n#******"); */
10343: /* for(j=1;j<=cptcoveff;j++) { */
10344: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
10345: /* } */
10346: /* fprintf(ficrespop,"******\n"); */
10347: /* fprintf(ficrespop,"# Age"); */
10348: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
10349: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 10350:
1.227 brouard 10351: /* for (cpt=0; cpt<=0;cpt++) { */
10352: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 10353:
1.227 brouard 10354: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
10355: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
10356: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 10357:
1.227 brouard 10358: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10359: /* oldm=oldms;savm=savms; */
10360: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 10361:
1.227 brouard 10362: /* for (h=0; h<=nhstepm; h++){ */
10363: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
10364: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
10365: /* } */
10366: /* for(j=1; j<=nlstate+ndeath;j++) { */
10367: /* kk1=0.;kk2=0; */
10368: /* for(i=1; i<=nlstate;i++) { */
10369: /* if (mobilav==1) */
10370: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
10371: /* else { */
10372: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
10373: /* } */
10374: /* } */
10375: /* if (h==(int)(calagedatem+12*cpt)){ */
10376: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
10377: /* /\*fprintf(ficrespop," %.3f", kk1); */
10378: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
10379: /* } */
10380: /* } */
10381: /* for(i=1; i<=nlstate;i++){ */
10382: /* kk1=0.; */
10383: /* for(j=1; j<=nlstate;j++){ */
10384: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
10385: /* } */
10386: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
10387: /* } */
1.218 brouard 10388:
1.227 brouard 10389: /* if (h==(int)(calagedatem+12*cpt)) */
10390: /* for(j=1; j<=nlstate;j++) */
10391: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
10392: /* } */
10393: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10394: /* } */
10395: /* } */
1.218 brouard 10396:
1.227 brouard 10397: /* /\******\/ */
1.218 brouard 10398:
1.227 brouard 10399: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
10400: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
10401: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
10402: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
10403: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 10404:
1.227 brouard 10405: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10406: /* oldm=oldms;savm=savms; */
10407: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
10408: /* for (h=0; h<=nhstepm; h++){ */
10409: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
10410: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
10411: /* } */
10412: /* for(j=1; j<=nlstate+ndeath;j++) { */
10413: /* kk1=0.;kk2=0; */
10414: /* for(i=1; i<=nlstate;i++) { */
10415: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
10416: /* } */
10417: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
10418: /* } */
10419: /* } */
10420: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10421: /* } */
10422: /* } */
10423: /* } */
10424: /* } */
1.218 brouard 10425:
1.227 brouard 10426: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 10427:
1.227 brouard 10428: /* if (popforecast==1) { */
10429: /* free_ivector(popage,0,AGESUP); */
10430: /* free_vector(popeffectif,0,AGESUP); */
10431: /* free_vector(popcount,0,AGESUP); */
10432: /* } */
10433: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10434: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10435: /* fclose(ficrespop); */
10436: /* } /\* End of popforecast *\/ */
1.218 brouard 10437:
1.126 brouard 10438: int fileappend(FILE *fichier, char *optionfich)
10439: {
10440: if((fichier=fopen(optionfich,"a"))==NULL) {
10441: printf("Problem with file: %s\n", optionfich);
10442: fprintf(ficlog,"Problem with file: %s\n", optionfich);
10443: return (0);
10444: }
10445: fflush(fichier);
10446: return (1);
10447: }
10448:
10449:
10450: /**************** function prwizard **********************/
10451: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
10452: {
10453:
10454: /* Wizard to print covariance matrix template */
10455:
1.164 brouard 10456: char ca[32], cb[32];
10457: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 10458: int numlinepar;
10459:
10460: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
10461: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
10462: for(i=1; i <=nlstate; i++){
10463: jj=0;
10464: for(j=1; j <=nlstate+ndeath; j++){
10465: if(j==i) continue;
10466: jj++;
10467: /*ca[0]= k+'a'-1;ca[1]='\0';*/
10468: printf("%1d%1d",i,j);
10469: fprintf(ficparo,"%1d%1d",i,j);
10470: for(k=1; k<=ncovmodel;k++){
10471: /* printf(" %lf",param[i][j][k]); */
10472: /* fprintf(ficparo," %lf",param[i][j][k]); */
10473: printf(" 0.");
10474: fprintf(ficparo," 0.");
10475: }
10476: printf("\n");
10477: fprintf(ficparo,"\n");
10478: }
10479: }
10480: printf("# Scales (for hessian or gradient estimation)\n");
10481: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
10482: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
10483: for(i=1; i <=nlstate; i++){
10484: jj=0;
10485: for(j=1; j <=nlstate+ndeath; j++){
10486: if(j==i) continue;
10487: jj++;
10488: fprintf(ficparo,"%1d%1d",i,j);
10489: printf("%1d%1d",i,j);
10490: fflush(stdout);
10491: for(k=1; k<=ncovmodel;k++){
10492: /* printf(" %le",delti3[i][j][k]); */
10493: /* fprintf(ficparo," %le",delti3[i][j][k]); */
10494: printf(" 0.");
10495: fprintf(ficparo," 0.");
10496: }
10497: numlinepar++;
10498: printf("\n");
10499: fprintf(ficparo,"\n");
10500: }
10501: }
10502: printf("# Covariance matrix\n");
10503: /* # 121 Var(a12)\n\ */
10504: /* # 122 Cov(b12,a12) Var(b12)\n\ */
10505: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
10506: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
10507: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
10508: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
10509: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
10510: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
10511: fflush(stdout);
10512: fprintf(ficparo,"# Covariance matrix\n");
10513: /* # 121 Var(a12)\n\ */
10514: /* # 122 Cov(b12,a12) Var(b12)\n\ */
10515: /* # ...\n\ */
10516: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
10517:
10518: for(itimes=1;itimes<=2;itimes++){
10519: jj=0;
10520: for(i=1; i <=nlstate; i++){
10521: for(j=1; j <=nlstate+ndeath; j++){
10522: if(j==i) continue;
10523: for(k=1; k<=ncovmodel;k++){
10524: jj++;
10525: ca[0]= k+'a'-1;ca[1]='\0';
10526: if(itimes==1){
10527: printf("#%1d%1d%d",i,j,k);
10528: fprintf(ficparo,"#%1d%1d%d",i,j,k);
10529: }else{
10530: printf("%1d%1d%d",i,j,k);
10531: fprintf(ficparo,"%1d%1d%d",i,j,k);
10532: /* printf(" %.5le",matcov[i][j]); */
10533: }
10534: ll=0;
10535: for(li=1;li <=nlstate; li++){
10536: for(lj=1;lj <=nlstate+ndeath; lj++){
10537: if(lj==li) continue;
10538: for(lk=1;lk<=ncovmodel;lk++){
10539: ll++;
10540: if(ll<=jj){
10541: cb[0]= lk +'a'-1;cb[1]='\0';
10542: if(ll<jj){
10543: if(itimes==1){
10544: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10545: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10546: }else{
10547: printf(" 0.");
10548: fprintf(ficparo," 0.");
10549: }
10550: }else{
10551: if(itimes==1){
10552: printf(" Var(%s%1d%1d)",ca,i,j);
10553: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
10554: }else{
10555: printf(" 0.");
10556: fprintf(ficparo," 0.");
10557: }
10558: }
10559: }
10560: } /* end lk */
10561: } /* end lj */
10562: } /* end li */
10563: printf("\n");
10564: fprintf(ficparo,"\n");
10565: numlinepar++;
10566: } /* end k*/
10567: } /*end j */
10568: } /* end i */
10569: } /* end itimes */
10570:
10571: } /* end of prwizard */
10572: /******************* Gompertz Likelihood ******************************/
10573: double gompertz(double x[])
10574: {
1.302 brouard 10575: double A=0.0,B=0.,L=0.0,sump=0.,num=0.;
1.126 brouard 10576: int i,n=0; /* n is the size of the sample */
10577:
1.220 brouard 10578: for (i=1;i<=imx ; i++) {
1.126 brouard 10579: sump=sump+weight[i];
10580: /* sump=sump+1;*/
10581: num=num+1;
10582: }
1.302 brouard 10583: L=0.0;
10584: /* agegomp=AGEGOMP; */
1.126 brouard 10585: /* for (i=0; i<=imx; i++)
10586: 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]);*/
10587:
1.302 brouard 10588: for (i=1;i<=imx ; i++) {
10589: /* mu(a)=mu(agecomp)*exp(teta*(age-agegomp))
10590: mu(a)=x[1]*exp(x[2]*(age-agegomp)); x[1] and x[2] are per year.
10591: * L= Product mu(agedeces)exp(-\int_ageexam^agedc mu(u) du ) for a death between agedc (in month)
10592: * and agedc +1 month, cens[i]=0: log(x[1]/YEARM)
10593: * +
10594: * exp(-\int_ageexam^agecens mu(u) du ) when censored, cens[i]=1
10595: */
10596: if (wav[i] > 1 || agedc[i] < AGESUP) {
10597: if (cens[i] == 1){
10598: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
10599: } else if (cens[i] == 0){
1.126 brouard 10600: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
1.302 brouard 10601: +log(x[1]/YEARM) +x[2]*(agedc[i]-agegomp)+log(YEARM);
10602: } else
10603: printf("Gompertz cens[%d] neither 1 nor 0\n",i);
1.126 brouard 10604: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
1.302 brouard 10605: L=L+A*weight[i];
1.126 brouard 10606: /* 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 10607: }
10608: }
1.126 brouard 10609:
1.302 brouard 10610: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
1.126 brouard 10611:
10612: return -2*L*num/sump;
10613: }
10614:
1.136 brouard 10615: #ifdef GSL
10616: /******************* Gompertz_f Likelihood ******************************/
10617: double gompertz_f(const gsl_vector *v, void *params)
10618: {
1.302 brouard 10619: double A=0.,B=0.,LL=0.0,sump=0.,num=0.;
1.136 brouard 10620: double *x= (double *) v->data;
10621: int i,n=0; /* n is the size of the sample */
10622:
10623: for (i=0;i<=imx-1 ; i++) {
10624: sump=sump+weight[i];
10625: /* sump=sump+1;*/
10626: num=num+1;
10627: }
10628:
10629:
10630: /* for (i=0; i<=imx; i++)
10631: 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]);*/
10632: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
10633: for (i=1;i<=imx ; i++)
10634: {
10635: if (cens[i] == 1 && wav[i]>1)
10636: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
10637:
10638: if (cens[i] == 0 && wav[i]>1)
10639: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
10640: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
10641:
10642: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
10643: if (wav[i] > 1 ) { /* ??? */
10644: LL=LL+A*weight[i];
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]);*/
10646: }
10647: }
10648:
10649: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
10650: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
10651:
10652: return -2*LL*num/sump;
10653: }
10654: #endif
10655:
1.126 brouard 10656: /******************* Printing html file ***********/
1.201 brouard 10657: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 10658: int lastpass, int stepm, int weightopt, char model[],\
10659: int imx, double p[],double **matcov,double agemortsup){
10660: int i,k;
10661:
10662: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
10663: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
10664: for (i=1;i<=2;i++)
10665: 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 10666: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 10667: fprintf(fichtm,"</ul>");
10668:
10669: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
10670:
10671: 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>");
10672:
10673: for (k=agegomp;k<(agemortsup-2);k++)
10674: 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]);
10675:
10676:
10677: fflush(fichtm);
10678: }
10679:
10680: /******************* Gnuplot file **************/
1.201 brouard 10681: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 10682:
10683: char dirfileres[132],optfileres[132];
1.164 brouard 10684:
1.126 brouard 10685: int ng;
10686:
10687:
10688: /*#ifdef windows */
10689: fprintf(ficgp,"cd \"%s\" \n",pathc);
10690: /*#endif */
10691:
10692:
10693: strcpy(dirfileres,optionfilefiname);
10694: strcpy(optfileres,"vpl");
1.199 brouard 10695: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 10696: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 10697: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 10698: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 10699: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
10700:
10701: }
10702:
1.136 brouard 10703: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
10704: {
1.126 brouard 10705:
1.136 brouard 10706: /*-------- data file ----------*/
10707: FILE *fic;
10708: char dummy[]=" ";
1.240 brouard 10709: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 10710: int lstra;
1.136 brouard 10711: int linei, month, year,iout;
1.302 brouard 10712: int noffset=0; /* This is the offset if BOM data file */
1.136 brouard 10713: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 10714: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 10715: char *stratrunc;
1.223 brouard 10716:
1.349 brouard 10717: /* DummyV=ivector(-1,NCOVMAX); /\* 1 to 3 *\/ */
10718: /* FixedV=ivector(-1,NCOVMAX); /\* 1 to 3 *\/ */
1.339 brouard 10719:
10720: ncovcolt=ncovcol+nqv+ntv+nqtv; /* total of covariates in the data, not in the model equation */
10721:
1.136 brouard 10722: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 10723: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
10724: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 10725: }
1.126 brouard 10726:
1.302 brouard 10727: /* Is it a BOM UTF-8 Windows file? */
10728: /* First data line */
10729: linei=0;
10730: while(fgets(line, MAXLINE, fic)) {
10731: noffset=0;
10732: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
10733: {
10734: noffset=noffset+3;
10735: printf("# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);fflush(stdout);
10736: fprintf(ficlog,"# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);
10737: fflush(ficlog); return 1;
10738: }
10739: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
10740: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
10741: {
10742: noffset=noffset+2;
1.304 brouard 10743: 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);
10744: 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 10745: fflush(ficlog); return 1;
10746: }
10747: else if( line[0] == 0 && line[1] == 0)
10748: {
10749: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
10750: noffset=noffset+4;
1.304 brouard 10751: 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);
10752: 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 10753: fflush(ficlog); return 1;
10754: }
10755: } else{
10756: ;/*printf(" Not a BOM file\n");*/
10757: }
10758: /* If line starts with a # it is a comment */
10759: if (line[noffset] == '#') {
10760: linei=linei+1;
10761: break;
10762: }else{
10763: break;
10764: }
10765: }
10766: fclose(fic);
10767: if((fic=fopen(datafile,"r"))==NULL) {
10768: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
10769: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
10770: }
10771: /* Not a Bom file */
10772:
1.136 brouard 10773: i=1;
10774: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
10775: linei=linei+1;
10776: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
10777: if(line[j] == '\t')
10778: line[j] = ' ';
10779: }
10780: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
10781: ;
10782: };
10783: line[j+1]=0; /* Trims blanks at end of line */
10784: if(line[0]=='#'){
10785: fprintf(ficlog,"Comment line\n%s\n",line);
10786: printf("Comment line\n%s\n",line);
10787: continue;
10788: }
10789: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 10790: strcpy(line, linetmp);
1.223 brouard 10791:
10792: /* Loops on waves */
10793: for (j=maxwav;j>=1;j--){
10794: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 10795: cutv(stra, strb, line, ' ');
10796: if(strb[0]=='.') { /* Missing value */
10797: lval=-1;
10798: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
1.341 brouard 10799: cotvar[j][ncovcol+nqv+ntv+iv][i]=-1; /* For performance reasons */
1.238 brouard 10800: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
10801: 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);
10802: 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);
10803: return 1;
10804: }
10805: }else{
10806: errno=0;
10807: /* what_kind_of_number(strb); */
10808: dval=strtod(strb,&endptr);
10809: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
10810: /* if(strb != endptr && *endptr == '\0') */
10811: /* dval=dlval; */
10812: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
10813: if( strb[0]=='\0' || (*endptr != '\0')){
10814: 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);
10815: 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);
10816: return 1;
10817: }
10818: cotqvar[j][iv][i]=dval;
1.341 brouard 10819: cotvar[j][ncovcol+nqv+ntv+iv][i]=dval; /* because cotvar starts now at first ntv */
1.238 brouard 10820: }
10821: strcpy(line,stra);
1.223 brouard 10822: }/* end loop ntqv */
1.225 brouard 10823:
1.223 brouard 10824: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 10825: cutv(stra, strb, line, ' ');
10826: if(strb[0]=='.') { /* Missing value */
10827: lval=-1;
10828: }else{
10829: errno=0;
10830: lval=strtol(strb,&endptr,10);
10831: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
10832: if( strb[0]=='\0' || (*endptr != '\0')){
10833: 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);
10834: 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);
10835: return 1;
10836: }
10837: }
10838: if(lval <-1 || lval >1){
10839: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10840: 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 10841: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10842: For example, for multinomial values like 1, 2 and 3,\n \
10843: build V1=0 V2=0 for the reference value (1),\n \
10844: V1=1 V2=0 for (2) \n \
1.223 brouard 10845: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10846: output of IMaCh is often meaningless.\n \
1.319 brouard 10847: Exiting.\n",lval,linei, i,line,iv,j);
1.238 brouard 10848: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10849: 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 10850: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10851: For example, for multinomial values like 1, 2 and 3,\n \
10852: build V1=0 V2=0 for the reference value (1),\n \
10853: V1=1 V2=0 for (2) \n \
1.223 brouard 10854: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10855: output of IMaCh is often meaningless.\n \
1.319 brouard 10856: Exiting.\n",lval,linei, i,line,iv,j);fflush(ficlog);
1.238 brouard 10857: return 1;
10858: }
1.341 brouard 10859: cotvar[j][ncovcol+nqv+iv][i]=(double)(lval);
1.238 brouard 10860: strcpy(line,stra);
1.223 brouard 10861: }/* end loop ntv */
1.225 brouard 10862:
1.223 brouard 10863: /* Statuses at wave */
1.137 brouard 10864: cutv(stra, strb, line, ' ');
1.223 brouard 10865: if(strb[0]=='.') { /* Missing value */
1.238 brouard 10866: lval=-1;
1.136 brouard 10867: }else{
1.238 brouard 10868: errno=0;
10869: lval=strtol(strb,&endptr,10);
10870: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
1.347 brouard 10871: if( strb[0]=='\0' || (*endptr != '\0' )){
10872: 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);
10873: 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);
10874: return 1;
10875: }else if( lval==0 || lval > nlstate+ndeath){
1.348 brouard 10876: 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);
10877: 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 10878: return 1;
10879: }
1.136 brouard 10880: }
1.225 brouard 10881:
1.136 brouard 10882: s[j][i]=lval;
1.225 brouard 10883:
1.223 brouard 10884: /* Date of Interview */
1.136 brouard 10885: strcpy(line,stra);
10886: cutv(stra, strb,line,' ');
1.169 brouard 10887: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10888: }
1.169 brouard 10889: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 10890: month=99;
10891: year=9999;
1.136 brouard 10892: }else{
1.225 brouard 10893: 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);
10894: 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);
10895: return 1;
1.136 brouard 10896: }
10897: anint[j][i]= (double) year;
1.302 brouard 10898: mint[j][i]= (double)month;
10899: /* if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){ */
10900: /* 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]); */
10901: /* 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]); */
10902: /* } */
1.136 brouard 10903: strcpy(line,stra);
1.223 brouard 10904: } /* End loop on waves */
1.225 brouard 10905:
1.223 brouard 10906: /* Date of death */
1.136 brouard 10907: cutv(stra, strb,line,' ');
1.169 brouard 10908: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10909: }
1.169 brouard 10910: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 10911: month=99;
10912: year=9999;
10913: }else{
1.141 brouard 10914: 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 10915: 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);
10916: return 1;
1.136 brouard 10917: }
10918: andc[i]=(double) year;
10919: moisdc[i]=(double) month;
10920: strcpy(line,stra);
10921:
1.223 brouard 10922: /* Date of birth */
1.136 brouard 10923: cutv(stra, strb,line,' ');
1.169 brouard 10924: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10925: }
1.169 brouard 10926: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 10927: month=99;
10928: year=9999;
10929: }else{
1.141 brouard 10930: 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);
10931: 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 10932: return 1;
1.136 brouard 10933: }
10934: if (year==9999) {
1.141 brouard 10935: 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);
10936: 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 10937: return 1;
10938:
1.136 brouard 10939: }
10940: annais[i]=(double)(year);
1.302 brouard 10941: moisnais[i]=(double)(month);
10942: for (j=1;j<=maxwav;j++){
10943: if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){
10944: 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]);
10945: 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]);
10946: }
10947: }
10948:
1.136 brouard 10949: strcpy(line,stra);
1.225 brouard 10950:
1.223 brouard 10951: /* Sample weight */
1.136 brouard 10952: cutv(stra, strb,line,' ');
10953: errno=0;
10954: dval=strtod(strb,&endptr);
10955: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 10956: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
10957: 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 10958: fflush(ficlog);
10959: return 1;
10960: }
10961: weight[i]=dval;
10962: strcpy(line,stra);
1.225 brouard 10963:
1.223 brouard 10964: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
10965: cutv(stra, strb, line, ' ');
10966: if(strb[0]=='.') { /* Missing value */
1.225 brouard 10967: lval=-1;
1.311 brouard 10968: coqvar[iv][i]=NAN;
10969: covar[ncovcol+iv][i]=NAN; /* including qvar in standard covar for performance reasons */
1.223 brouard 10970: }else{
1.225 brouard 10971: errno=0;
10972: /* what_kind_of_number(strb); */
10973: dval=strtod(strb,&endptr);
10974: /* if(strb != endptr && *endptr == '\0') */
10975: /* dval=dlval; */
10976: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
10977: if( strb[0]=='\0' || (*endptr != '\0')){
10978: 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);
10979: 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);
10980: return 1;
10981: }
10982: coqvar[iv][i]=dval;
1.226 brouard 10983: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 10984: }
10985: strcpy(line,stra);
10986: }/* end loop nqv */
1.136 brouard 10987:
1.223 brouard 10988: /* Covariate values */
1.136 brouard 10989: for (j=ncovcol;j>=1;j--){
10990: cutv(stra, strb,line,' ');
1.223 brouard 10991: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 10992: lval=-1;
1.136 brouard 10993: }else{
1.225 brouard 10994: errno=0;
10995: lval=strtol(strb,&endptr,10);
10996: if( strb[0]=='\0' || (*endptr != '\0')){
10997: 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);
10998: 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);
10999: return 1;
11000: }
1.136 brouard 11001: }
11002: if(lval <-1 || lval >1){
1.225 brouard 11003: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 11004: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
11005: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 11006: For example, for multinomial values like 1, 2 and 3,\n \
11007: build V1=0 V2=0 for the reference value (1),\n \
11008: V1=1 V2=0 for (2) \n \
1.136 brouard 11009: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 11010: output of IMaCh is often meaningless.\n \
1.136 brouard 11011: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 11012: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 11013: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
11014: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 11015: For example, for multinomial values like 1, 2 and 3,\n \
11016: build V1=0 V2=0 for the reference value (1),\n \
11017: V1=1 V2=0 for (2) \n \
1.136 brouard 11018: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 11019: output of IMaCh is often meaningless.\n \
1.136 brouard 11020: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 11021: return 1;
1.136 brouard 11022: }
11023: covar[j][i]=(double)(lval);
11024: strcpy(line,stra);
11025: }
11026: lstra=strlen(stra);
1.225 brouard 11027:
1.136 brouard 11028: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
11029: stratrunc = &(stra[lstra-9]);
11030: num[i]=atol(stratrunc);
11031: }
11032: else
11033: num[i]=atol(stra);
11034: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
11035: 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;}*/
11036:
11037: i=i+1;
11038: } /* End loop reading data */
1.225 brouard 11039:
1.136 brouard 11040: *imax=i-1; /* Number of individuals */
11041: fclose(fic);
1.225 brouard 11042:
1.136 brouard 11043: return (0);
1.164 brouard 11044: /* endread: */
1.225 brouard 11045: printf("Exiting readdata: ");
11046: fclose(fic);
11047: return (1);
1.223 brouard 11048: }
1.126 brouard 11049:
1.234 brouard 11050: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 11051: char *p1 = *stri, *p2 = *stri;
1.235 brouard 11052: while (*p2 == ' ')
1.234 brouard 11053: p2++;
11054: /* while ((*p1++ = *p2++) !=0) */
11055: /* ; */
11056: /* do */
11057: /* while (*p2 == ' ') */
11058: /* p2++; */
11059: /* while (*p1++ == *p2++); */
11060: *stri=p2;
1.145 brouard 11061: }
11062:
1.330 brouard 11063: int decoderesult( char resultline[], int nres)
1.230 brouard 11064: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
11065: {
1.235 brouard 11066: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 11067: char resultsav[MAXLINE];
1.330 brouard 11068: /* int resultmodel[MAXLINE]; */
1.334 brouard 11069: /* int modelresult[MAXLINE]; */
1.230 brouard 11070: char stra[80], strb[80], strc[80], strd[80],stre[80];
11071:
1.234 brouard 11072: removefirstspace(&resultline);
1.332 brouard 11073: printf("decoderesult:%s\n",resultline);
1.230 brouard 11074:
1.332 brouard 11075: strcpy(resultsav,resultline);
1.342 brouard 11076: /* printf("Decoderesult resultsav=\"%s\" resultline=\"%s\"\n", resultsav, resultline); */
1.230 brouard 11077: if (strlen(resultsav) >1){
1.334 brouard 11078: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' in this resultline */
1.230 brouard 11079: }
1.253 brouard 11080: if(j == 0){ /* Resultline but no = */
11081: TKresult[nres]=0; /* Combination for the nresult and the model */
11082: return (0);
11083: }
1.234 brouard 11084: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
1.334 brouard 11085: 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);
11086: 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 11087: /* return 1;*/
1.234 brouard 11088: }
1.334 brouard 11089: for(k=1; k<=j;k++){ /* Loop on any covariate of the RESULT LINE */
1.234 brouard 11090: if(nbocc(resultsav,'=') >1){
1.318 brouard 11091: 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 11092: /* 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 11093: cutl(strc,strd,strb,'='); /* strb:"V4=1" strc="1" strd="V4" */
1.332 brouard 11094: /* If a blank, then strc="V4=" and strd='\0' */
11095: if(strc[0]=='\0'){
11096: printf("Error in resultline, probably a blank after the \"%s\", \"result:%s\", stra=\"%s\" resultsav=\"%s\"\n",strb,resultline, stra, resultsav);
11097: fprintf(ficlog,"Error in resultline, probably a blank after the \"V%s=\", resultline=%s\n",strb,resultline);
11098: return 1;
11099: }
1.234 brouard 11100: }else
11101: cutl(strc,strd,resultsav,'=');
1.318 brouard 11102: Tvalsel[k]=atof(strc); /* 1 */ /* Tvalsel of k is the float value of the kth covariate appearing in this result line */
1.234 brouard 11103:
1.230 brouard 11104: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
1.318 brouard 11105: 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 11106: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
11107: /* cptcovsel++; */
11108: if (nbocc(stra,'=') >0)
11109: strcpy(resultsav,stra); /* and analyzes it */
11110: }
1.235 brouard 11111: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 11112: /* 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 11113: 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 11114: if(Typevar[k1]==0){ /* Single covariate in model */
11115: /* 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.234 brouard 11116: match=0;
1.318 brouard 11117: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
11118: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 11119: modelresult[nres][k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.318 brouard 11120: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
1.234 brouard 11121: break;
11122: }
11123: }
11124: if(match == 0){
1.338 brouard 11125: 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]);
11126: 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 11127: return 1;
1.234 brouard 11128: }
1.332 brouard 11129: }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*/
11130: /* We feed resultmodel[k1]=k2; */
11131: match=0;
11132: 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 */
11133: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 11134: 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 11135: resultmodel[nres][k1]=k2; /* Added here */
1.342 brouard 11136: /* printf("Decoderesult first modelresult[k2=%d]=%d (k1) V%d*AGE\n",k2,k1,Tvar[k1]); */
1.332 brouard 11137: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
11138: break;
11139: }
11140: }
11141: if(match == 0){
1.338 brouard 11142: 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]);
11143: 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 11144: return 1;
11145: }
1.349 brouard 11146: }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 11147: /* resultmodel[nres][of such a Vn * Vm product k1] is not unique, so can't exist, we feed Tvard[k1][1] and [2] */
11148: match=0;
1.342 brouard 11149: /* 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 11150: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
11151: if(Tvardk[k1][1]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
11152: /* modelresult[k2]=k1; */
1.342 brouard 11153: /* printf("Decoderesult first Product modelresult[k2=%d]=%d (k1) V%d * \n",k2,k1,Tvarsel[k2]); */
1.332 brouard 11154: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
11155: }
11156: }
11157: if(match == 0){
1.349 brouard 11158: 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);
11159: 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 11160: return 1;
11161: }
11162: match=0;
11163: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
11164: if(Tvardk[k1][2]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
11165: /* modelresult[k2]=k1;*/
1.342 brouard 11166: /* printf("Decoderesult second Product modelresult[k2=%d]=%d (k1) * V%d \n ",k2,k1,Tvarsel[k2]); */
1.332 brouard 11167: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
11168: break;
11169: }
11170: }
11171: if(match == 0){
1.349 brouard 11172: 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);
11173: 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 11174: return 1;
11175: }
11176: }/* End of testing */
1.333 brouard 11177: }/* End loop cptcovt */
1.235 brouard 11178: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 11179: /* Feeds resultmodel[nres][k1]=k2 for single covariate (k1) in the model equation */
1.334 brouard 11180: 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)
11181: * Loop on resultline variables: result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 11182: match=0;
1.318 brouard 11183: 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 11184: if(Typevar[k1]==0){ /* Single only */
1.349 brouard 11185: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 What if a product? */
1.330 brouard 11186: 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 11187: 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 11188: ++match;
11189: }
11190: }
11191: }
11192: if(match == 0){
1.338 brouard 11193: printf("Error in result line: variable V%d is missing in model; result: %s, model=1+age+%s\n",Tvarsel[k2], resultline, model);
11194: 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 11195: return 1;
1.234 brouard 11196: }else if(match > 1){
1.338 brouard 11197: printf("Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
11198: fprintf(ficlog,"Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
1.310 brouard 11199: return 1;
1.234 brouard 11200: }
11201: }
1.334 brouard 11202: /* cptcovres=j /\* Number of variables in the resultline is equal to cptcovs and thus useless *\/ */
1.234 brouard 11203: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 11204: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.330 brouard 11205: /* nres=1st result line: V4=1 V5=25.1 V3=0 V2=8 V1=1 */
11206: /* 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*/
11207: /* nres=2nd result line: V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.235 brouard 11208: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
11209: /* 1 0 0 0 */
11210: /* 2 1 0 0 */
11211: /* 3 0 1 0 */
1.330 brouard 11212: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 (nres=2)*/
1.235 brouard 11213: /* 5 0 0 1 */
1.330 brouard 11214: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 (nres=1)*/
1.235 brouard 11215: /* 7 0 1 1 */
11216: /* 8 1 1 1 */
1.237 brouard 11217: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
11218: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
11219: /* V5*age V5 known which value for nres? */
11220: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.334 brouard 11221: 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.
11222: * loop on position k1 in the MODEL LINE */
1.331 brouard 11223: /* k counting number of combination of single dummies in the equation model */
11224: /* k4 counting single dummies in the equation model */
11225: /* k4q counting single quantitatives in the equation model */
1.344 brouard 11226: 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 11227: /* 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 11228: /* 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 11229: /* Value in the (current nres) resultline of the variable at the k1th position in the model equation resultmodel[nres][k1]= k3 */
1.332 brouard 11230: /* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline */
11231: /* k3 is the position in the nres result line of the k1th variable of the model equation */
11232: /* Tvarsel[k3]: Name of the variable at the k3th position in the result line. */
11233: /* Tvalsel[k3]: Value of the variable at the k3th position in the result line. */
11234: /* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.334 brouard 11235: /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 11236: /* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1.330 brouard 11237: /* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.332 brouard 11238: k3= resultmodel[nres][k1]; /* From position k1 in model get position k3 in result line */
11239: /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
11240: 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 11241: 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 11242: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][Name]=Value; stores the value into the name of the variable. */
1.332 brouard 11243: /* Tinvresult[nres][4]=1 */
1.334 brouard 11244: /* Tresult[nres][k4+1]=Tvalsel[k3];/\* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) *\/ */
11245: Tresult[nres][k3]=Tvalsel[k3];/* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) */
11246: /* Tvresult[nres][k4+1]=(int)Tvarsel[k3];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
11247: Tvresult[nres][k3]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
1.237 brouard 11248: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.334 brouard 11249: precov[nres][k1]=Tvalsel[k3]; /* Value from resultline of the variable at the k1 position in the model */
1.342 brouard 11250: /* 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 11251: k4++;;
1.331 brouard 11252: }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Quantitative and single */
1.330 brouard 11253: /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.332 brouard 11254: /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.330 brouard 11255: /* Tqinvresult[nres][Name of a quantitative variable]= value of the variable in the result line */
1.332 brouard 11256: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 5 =k3q */
11257: k2q=(int)Tvarsel[k3q]; /* Name of variable at k3q th position in the resultline */
11258: /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.334 brouard 11259: /* Tqresult[nres][k4q+1]=Tvalsel[k3q]; /\* Tqresult[nres][1]=25.1 *\/ */
11260: /* Tvresult[nres][k4q+1]=(int)Tvarsel[k3q];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
11261: /* Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /\* Tvqresult[nres][1]=5 *\/ */
11262: Tqresult[nres][k3q]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
11263: Tvresult[nres][k3q]=(int)Tvarsel[k3q];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
11264: Tvqresult[nres][k3q]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
1.237 brouard 11265: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.330 brouard 11266: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.332 brouard 11267: precov[nres][k1]=Tvalsel[k3q];
1.342 brouard 11268: /* 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 11269: k4q++;;
1.350 ! brouard 11270: }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"*/
! 11271: /* Tvar[k1]; */ /* Age variable */ /* 17 age*V6*V2 ?*/
1.332 brouard 11272: /* Wrong we want the value of variable name Tvar[k1] */
1.350 ! brouard 11273: if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
! 11274: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
! 11275: /* 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]]); */
! 11276: }else{
! 11277: k3= resultmodel[nres][k1]; /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
! 11278: 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)*/
! 11279: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][4]=1 */
! 11280: precov[nres][k1]=Tvalsel[k3];
! 11281: }
1.342 brouard 11282: /* 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 11283: }else if( Dummy[k1]==3 ){ /* For quant with age product */
1.350 ! brouard 11284: if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
! 11285: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
! 11286: /* 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]]); */
! 11287: }else{
! 11288: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 25.1=k3q */
! 11289: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
! 11290: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* TinvDoQresult[nres][5]=25.1 */
! 11291: precov[nres][k1]=Tvalsel[k3q];
! 11292: }
1.342 brouard 11293: /* 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 11294: }else if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
1.332 brouard 11295: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
1.342 brouard 11296: /* 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 11297: }else{
1.332 brouard 11298: printf("Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
11299: fprintf(ficlog,"Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
1.235 brouard 11300: }
11301: }
1.234 brouard 11302:
1.334 brouard 11303: TKresult[nres]=++k; /* Number of combinations of dummies for the nresult and the model =Tvalsel[k3]*pow(2,k4) + 1*/
1.230 brouard 11304: return (0);
11305: }
1.235 brouard 11306:
1.230 brouard 11307: int decodemodel( char model[], int lastobs)
11308: /**< This routine decodes the model and returns:
1.224 brouard 11309: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
11310: * - nagesqr = 1 if age*age in the model, otherwise 0.
11311: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
11312: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
11313: * - cptcovage number of covariates with age*products =2
11314: * - cptcovs number of simple covariates
1.339 brouard 11315: * ncovcolt=ncovcol+nqv+ntv+nqtv total of covariates in the data, not in the model equation
1.224 brouard 11316: * - 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 11317: * which is a new column after the 9 (ncovcol+nqv+ntv+nqtv) variables.
1.319 brouard 11318: * - if k is a product Vn*Vm, covar[k][i] is filled with correct values for each individual
1.224 brouard 11319: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
11320: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
11321: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
11322: */
1.319 brouard 11323: /* 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 11324: {
1.238 brouard 11325: int i, j, k, ks, v;
1.349 brouard 11326: int n,m;
11327: int j1, k1, k11, k12, k2, k3, k4;
11328: char modelsav[300];
11329: char stra[300], strb[300], strc[300], strd[300],stre[300],strf[300];
1.187 brouard 11330: char *strpt;
1.349 brouard 11331: int **existcomb;
11332:
11333: existcomb=imatrix(1,NCOVMAX,1,NCOVMAX);
11334: for(i=1;i<=NCOVMAX;i++)
11335: for(j=1;j<=NCOVMAX;j++)
11336: existcomb[i][j]=0;
11337:
1.145 brouard 11338: /*removespace(model);*/
1.136 brouard 11339: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.349 brouard 11340: j=0, j1=0, k1=0, k12=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 11341: if (strstr(model,"AGE") !=0){
1.192 brouard 11342: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
11343: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 11344: return 1;
11345: }
1.141 brouard 11346: if (strstr(model,"v") !=0){
1.338 brouard 11347: printf("Error. 'v' must be in upper case 'V' model=1+age+%s ",model);
11348: fprintf(ficlog,"Error. 'v' must be in upper case model=1+age+%s ",model);fflush(ficlog);
1.141 brouard 11349: return 1;
11350: }
1.187 brouard 11351: strcpy(modelsav,model);
11352: if ((strpt=strstr(model,"age*age")) !=0){
1.338 brouard 11353: printf(" strpt=%s, model=1+age+%s\n",strpt, model);
1.187 brouard 11354: if(strpt != model){
1.338 brouard 11355: printf("Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 11356: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 11357: corresponding column of parameters.\n",model);
1.338 brouard 11358: fprintf(ficlog,"Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 11359: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 11360: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 11361: return 1;
1.225 brouard 11362: }
1.187 brouard 11363: nagesqr=1;
11364: if (strstr(model,"+age*age") !=0)
1.234 brouard 11365: substrchaine(modelsav, model, "+age*age");
1.187 brouard 11366: else if (strstr(model,"age*age+") !=0)
1.234 brouard 11367: substrchaine(modelsav, model, "age*age+");
1.187 brouard 11368: else
1.234 brouard 11369: substrchaine(modelsav, model, "age*age");
1.187 brouard 11370: }else
11371: nagesqr=0;
1.349 brouard 11372: 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 11373: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
11374: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.349 brouard 11375: cptcovs=j+1-j1; /**< Number of simple covariates V1 +V1*age +V3 +V3*V4 +age*age => V1 + V3 =4+1-3=2 */
1.187 brouard 11376: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 11377: * cst, age and age*age
11378: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
11379: /* including age products which are counted in cptcovage.
11380: * but the covariates which are products must be treated
11381: * separately: ncovn=4- 2=2 (V1+V3). */
1.349 brouard 11382: cptcovprod=0; /**< Number of products V1*V2 +v3*age = 2 */
11383: cptcovdageprod=0; /* Number of doouble products with age age*Vn*VM or Vn*age*Vm or Vn*Vm*age */
1.187 brouard 11384: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.349 brouard 11385: cptcovprodage=0;
11386: /* cptcovprodage=nboccstr(modelsav,"age");*/
1.225 brouard 11387:
1.187 brouard 11388: /* Design
11389: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
11390: * < ncovcol=8 >
11391: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
11392: * k= 1 2 3 4 5 6 7 8
11393: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
1.345 brouard 11394: * covar[k,i], are for fixed covariates, value of kth covariate if not including age for individual i:
1.224 brouard 11395: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
11396: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 11397: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
11398: * Tage[++cptcovage]=k
1.345 brouard 11399: * if products, new covar are created after ncovcol + nqv (quanti fixed) with k1
1.187 brouard 11400: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
11401: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
11402: * 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
11403: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
11404: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
11405: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
1.345 brouard 11406: * < ncovcol=8 8 fixed covariate. Additional starts at 9 (V5*V6) and 10(V7*V8) >
1.187 brouard 11407: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
11408: * k= 1 2 3 4 5 6 7 8 9 10 11 12
1.345 brouard 11409: * Tvard[k]= 2 1 3 3 10 11 8 8 5 6 7 8
11410: * p Tvar[1]@12={2, 1, 3, 3, 9, 10, 8, 8}
1.187 brouard 11411: * p Tprod[1]@2={ 6, 5}
11412: *p Tvard[1][1]@4= {7, 8, 5, 6}
11413: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
11414: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
1.319 brouard 11415: *How to reorganize? Tvars(orted)
1.187 brouard 11416: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
11417: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
11418: * {2, 1, 4, 8, 5, 6, 3, 7}
11419: * Struct []
11420: */
1.225 brouard 11421:
1.187 brouard 11422: /* This loop fills the array Tvar from the string 'model'.*/
11423: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
11424: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
11425: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
11426: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
11427: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
11428: /* k=1 Tvar[1]=2 (from V2) */
11429: /* k=5 Tvar[5] */
11430: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 11431: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 11432: /* } */
1.198 brouard 11433: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 11434: /*
11435: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 11436: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
11437: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
11438: }
1.187 brouard 11439: cptcovage=0;
1.319 brouard 11440: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model line */
11441: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+' cutl from left to right
11442: 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" */
11443: if (nbocc(modelsav,'+')==0)
11444: strcpy(strb,modelsav); /* and analyzes it */
1.234 brouard 11445: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
11446: /*scanf("%d",i);*/
1.349 brouard 11447: 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 */
11448: 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 */
11449: 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 */
11450: Typevar[k]=3; /* 3 for age and double product age*Vn*Vm varying of fixed */
11451: if(strstr(strc,"age")!=0) { /* It means that strc=V2*age or age*V2 and thus that strd=Vn */
11452: cutl(stre,strf,strc,'*') ; /* strf=age or Vm, stre=Vm or age. If strc=V6*V2 then strf=V6 and stre=V2 */
11453: strcpy(strc,strb); /* save strb(=age*Vn*Vm) into strc */
11454: /* We want strb=Vn*Vm */
11455: if(strcmp(strf,"age")==0){ /* strf is "age" so that stre=Vm =V2 . */
11456: strcpy(strb,strd);
11457: strcat(strb,"*");
11458: strcat(strb,stre);
11459: }else{ /* strf=Vm If strf=V6 then stre=V2 */
11460: strcpy(strb,strf);
11461: strcat(strb,"*");
11462: strcat(strb,stre);
11463: strcpy(strd,strb); /* in order for strd to not be "age" for next test (will be Vn*Vm */
11464: }
11465: 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]]]);
11466: FixedV[Tvar[Tage[k]]]=0; /* HERY not sure */
11467: }else{ /* strc=Vn*Vm (and strd=age) and should be strb=Vn*Vm but want to keep original strb double product */
11468: strcpy(stre,strb); /* save full b in stre */
11469: strcpy(strb,strc); /* save short c in new short b for next block strb=Vn*Vm*/
11470: strcpy(strf,strc); /* save short c in new short f */
11471: cutl(strc,strd,strf,'*'); /* We get strd=Vn and strc=Vm for next block (strb=Vn*Vm)*/
11472: /* strcpy(strc,stre);*/ /* save full e in c for future */
11473: }
11474: cptcovdageprod++; /* double product with age Which product is it? */
11475: /* 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 *\/ */
11476: /* cutl(strc,strd,strb,'*'); /\* strd= V6 or V2 or age and strc= V2 or age or V2 *\/ */
1.234 brouard 11477: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
1.349 brouard 11478: n=atoi(stre);
1.234 brouard 11479: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
1.349 brouard 11480: m=atoi(strc);
11481: cptcovage++; /* Counts the number of covariates which include age as a product */
11482: Tage[cptcovage]=k; /* For age*V3*V2 gives the position in model of covariates associated with age Tage[1]=6 HERY too*/
11483: if(existcomb[n][m] == 0){
11484: /* r /home/brouard/Documents/Recherches/REVES/Zachary/Zach-2022/Feinuo_Sun/Feinuo-threeway/femV12V15_3wayintNBe.imach */
11485: 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);
11486: 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);
11487: fflush(ficlog);
11488: k1++; /* The combination Vn*Vm will be in the model so we create it at k1 */
11489: k12++;
11490: existcomb[n][m]=k1;
11491: existcomb[m][n]=k1;
11492: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1;
11493: 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*/
11494: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 Gives the k1 double product Vn*Vm or age*Vn*Vm at the k position */
11495: Tvard[k1][1] =m; /* m 1 for V1*/
11496: Tvardk[k][1] =m; /* m 1 for V1*/
11497: Tvard[k1][2] =n; /* n 4 for V4*/
11498: Tvardk[k][2] =n; /* n 4 for V4*/
11499: /* Tvar[Tage[cptcovage]]=k1;*/ /* Tvar[6=age*V3*V2]=9 (new fixed covariate) */
11500: 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 */
11501: for (i=1; i<=lastobs;i++){/* For fixed product */
11502: /* Computes the new covariate which is a product of
11503: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
11504: covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
11505: }
11506: cptcovprodage++; /* Counting the number of fixed covariate with age */
11507: FixedV[ncovcolt+k12]=0; /* We expand Vn*Vm */
11508: k12++;
11509: FixedV[ncovcolt+k12]=0;
11510: }else{ /*End of FixedV */
11511: cptcovprodvage++; /* Counting the number of varying covariate with age */
11512: FixedV[ncovcolt+k12]=1; /* We expand Vn*Vm */
11513: k12++;
11514: FixedV[ncovcolt+k12]=1;
11515: }
11516: }else{ /* k1 Vn*Vm already exists */
11517: k11=existcomb[n][m];
11518: Tposprod[k]=k11; /* OK */
11519: Tvar[k]=Tvar[Tprod[k11]]; /* HERY */
11520: Tvardk[k][1]=m;
11521: Tvardk[k][2]=n;
11522: 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 */
11523: /*cptcovage++;*/ /* Counts the number of covariates which include age as a product */
11524: cptcovprodage++; /* Counting the number of fixed covariate with age */
11525: /*Tage[cptcovage]=k;*/ /* For age*V3*V2 Tage[1]=V3*V3=9 HERY too*/
11526: Tvar[Tage[cptcovage]]=k1;
11527: FixedV[ncovcolt+k12]=0; /* We expand Vn*Vm */
11528: k12++;
11529: FixedV[ncovcolt+k12]=0;
11530: }else{ /* Already exists but time varying (and age) */
11531: /*cptcovage++;*/ /* Counts the number of covariates which include age as a product */
11532: /*Tage[cptcovage]=k;*/ /* For age*V3*V2 Tage[1]=V3*V3=9 HERY too*/
11533: /* Tvar[Tage[cptcovage]]=k1; */
11534: cptcovprodvage++;
11535: FixedV[ncovcolt+k12]=1; /* We expand Vn*Vm */
11536: k12++;
11537: FixedV[ncovcolt+k12]=1;
11538: }
11539: }
11540: /* Tage[cptcovage]=k; /\* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
11541: /* Tvar[k]=k11; /\* HERY *\/ */
11542: } 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 */
11543: cptcovprod++;
11544: if (strcmp(strc,"age")==0) { /**< Model includes age: strb= Vn*age c=age d=Vn*/
11545: /* covar is not filled and then is empty */
11546: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
11547: 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 */
11548: Typevar[k]=1; /* 1 for age product */
11549: cptcovage++; /* Counts the number of covariates which include age as a product */
11550: Tage[cptcovage]=k; /* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
11551: if( FixedV[Tvar[k]] == 0){
11552: cptcovprodage++; /* Counting the number of fixed covariate with age */
11553: }else{
11554: cptcovprodvage++; /* Counting the number of fixedvarying covariate with age */
11555: }
11556: /*printf("stre=%s ", stre);*/
11557: } else if (strcmp(strd,"age")==0) { /* strb= age*Vn c=Vn */
11558: cutl(stre,strb,strc,'V');
11559: Tvar[k]=atoi(stre);
11560: Typevar[k]=1; /* 1 for age product */
11561: cptcovage++;
11562: Tage[cptcovage]=k;
11563: if( FixedV[Tvar[k]] == 0){
11564: cptcovprodage++; /* Counting the number of fixed covariate with age */
11565: }else{
11566: cptcovprodvage++; /* Counting the number of fixedvarying covariate with age */
1.339 brouard 11567: }
1.349 brouard 11568: }else{ /* for product Vn*Vm */
11569: Typevar[k]=2; /* 2 for product Vn*Vm */
11570: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
11571: n=atoi(stre);
11572: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
11573: m=atoi(strc);
11574: k1++;
11575: cptcovprodnoage++;
11576: if(existcomb[n][m] != 0 || existcomb[m][n] != 0){
11577: printf("Warning in model combination V%d*V%d already exists in the model in position k1=%d!\n",n,m,existcomb[n][m]);
11578: 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]);
11579: fflush(ficlog);
11580: k11=existcomb[n][m];
11581: Tvar[k]=ncovcol+nqv+ntv+nqtv+k11;
11582: Tposprod[k]=k11;
11583: Tprod[k11]=k;
11584: Tvardk[k][1] =m; /* m 1 for V1*/
11585: /* Tvard[k11][1] =m; /\* n 4 for V4*\/ */
11586: Tvardk[k][2] =n; /* n 4 for V4*/
11587: /* Tvard[k11][2] =n; /\* n 4 for V4*\/ */
11588: }else{ /* combination Vn*Vm doesn't exist we create it (no age)*/
11589: existcomb[n][m]=k1;
11590: existcomb[m][n]=k1;
11591: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* ncovcolt+k1; For model-covariate k tells which data-covariate to use but
11592: because this model-covariate is a construction we invent a new column
11593: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
11594: If already ncovcol=4 and model= V2 + V1 + V1*V4 + age*V3 + V3*V2
11595: thus after V4 we invent V5 and V6 because age*V3 will be computed in 4
11596: Tvar[3=V1*V4]=4+1=5 Tvar[5=V3*V2]=4 + 2= 6, Tvar[4=age*V3]=3 etc */
11597: /* Please remark that the new variables are model dependent */
11598: /* If we have 4 variable but the model uses only 3, like in
11599: * model= V1 + age*V1 + V2 + V3 + age*V2 + age*V3 + V1*V2 + V1*V3
11600: * k= 1 2 3 4 5 6 7 8
11601: * Tvar[k]=1 1 2 3 2 3 (5 6) (and not 4 5 because of V4 missing)
11602: * Tage[kk] [1]= 2 [2]=5 [3]=6 kk=1 to cptcovage=3
11603: * Tvar[Tage[kk]][1]=2 [2]=2 [3]=3
11604: */
11605: /* We need to feed some variables like TvarVV, but later on next loop because of ncovv (k2) is not correct */
11606: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 +V6*V2*age */
11607: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 */
11608: Tvard[k1][1] =m; /* m 1 for V1*/
11609: Tvardk[k][1] =m; /* m 1 for V1*/
11610: Tvard[k1][2] =n; /* n 4 for V4*/
11611: Tvardk[k][2] =n; /* n 4 for V4*/
11612: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
11613: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
11614: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
11615: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
11616: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
11617: 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 */
11618: for (i=1; i<=lastobs;i++){/* For fixed product */
11619: /* Computes the new covariate which is a product of
11620: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
11621: covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
11622: }
11623: /* TvarVV[k2]=n; */
11624: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11625: /* TvarVV[k2+1]=m; */
11626: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11627: }else{ /* not FixedV */
11628: /* TvarVV[k2]=n; */
11629: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11630: /* TvarVV[k2+1]=m; */
11631: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11632: }
11633: } /* End of creation of Vn*Vm if not created by age*Vn*Vm earlier */
11634: } /* End of product Vn*Vm */
11635: } /* End of age*double product or simple product */
11636: }else { /* not a product */
1.234 brouard 11637: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
11638: /* scanf("%d",i);*/
11639: cutl(strd,strc,strb,'V');
11640: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
11641: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
11642: Tvar[k]=atoi(strd);
11643: Typevar[k]=0; /* 0 for simple covariates */
11644: }
11645: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 11646: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 11647: scanf("%d",i);*/
1.187 brouard 11648: } /* end of loop + on total covariates */
11649: } /* end if strlen(modelsave == 0) age*age might exist */
11650: } /* end if strlen(model == 0) */
1.349 brouard 11651: 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 */
11652:
1.136 brouard 11653: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
11654: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 11655:
1.136 brouard 11656: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 11657: printf("cptcovprod=%d ", cptcovprod);
11658: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
11659: scanf("%d ",i);*/
11660:
11661:
1.230 brouard 11662: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
11663: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 11664: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
11665: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
11666: k = 1 2 3 4 5 6 7 8 9
11667: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
1.319 brouard 11668: Typevar[k]= 0 0 0 2 1 0 2 1 0
1.227 brouard 11669: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
11670: Dummy[k] 1 0 0 0 3 1 1 2 3
11671: Tmodelind[combination of covar]=k;
1.225 brouard 11672: */
11673: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 11674: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 11675: /* 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 11676: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.318 brouard 11677: printf("Model=1+age+%s\n\
1.349 brouard 11678: 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 11679: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
11680: 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 11681: fprintf(ficlog,"Model=1+age+%s\n\
1.349 brouard 11682: 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 11683: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
11684: 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 11685: for(k=-1;k<=NCOVMAX; k++){ Fixed[k]=0; Dummy[k]=0;}
11686: for(k=1;k<=NCOVMAX; k++){TvarFind[k]=0; TvarVind[k]=0;}
1.349 brouard 11687: 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 11688: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 11689: Fixed[k]= 0;
11690: Dummy[k]= 0;
1.225 brouard 11691: ncoveff++;
1.232 brouard 11692: ncovf++;
1.234 brouard 11693: nsd++;
11694: modell[k].maintype= FTYPE;
11695: TvarsD[nsd]=Tvar[k];
11696: TvarsDind[nsd]=k;
1.330 brouard 11697: TnsdVar[Tvar[k]]=nsd;
1.234 brouard 11698: TvarF[ncovf]=Tvar[k];
11699: TvarFind[ncovf]=k;
11700: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
11701: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.339 brouard 11702: /* }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 11703: }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 11704: Fixed[k]= 0;
11705: Dummy[k]= 1;
1.230 brouard 11706: nqfveff++;
1.234 brouard 11707: modell[k].maintype= FTYPE;
11708: modell[k].subtype= FQ;
11709: nsq++;
1.334 brouard 11710: TvarsQ[nsq]=Tvar[k]; /* Gives the variable name (extended to products) of first nsq simple quantitative covariates (fixed or time vary see below */
11711: TvarsQind[nsq]=k; /* Gives the position in the model equation of the first nsq simple quantitative covariates (fixed or time vary) */
1.232 brouard 11712: ncovf++;
1.234 brouard 11713: TvarF[ncovf]=Tvar[k];
11714: TvarFind[ncovf]=k;
1.231 brouard 11715: 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 11716: 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 11717: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.339 brouard 11718: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11719: /* model V1+V3+age*V1+age*V3+V1*V3 */
11720: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11721: ncovvt++;
11722: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
11723: TvarVVind[ncovvt]=k; /* TvarVVind[1]=2 (second position in the model equation */
11724:
1.227 brouard 11725: Fixed[k]= 1;
11726: Dummy[k]= 0;
1.225 brouard 11727: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 11728: modell[k].maintype= VTYPE;
11729: modell[k].subtype= VD;
11730: nsd++;
11731: TvarsD[nsd]=Tvar[k];
11732: TvarsDind[nsd]=k;
1.330 brouard 11733: TnsdVar[Tvar[k]]=nsd; /* To be verified */
1.234 brouard 11734: ncovv++; /* Only simple time varying variables */
11735: TvarV[ncovv]=Tvar[k];
1.242 brouard 11736: 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 11737: 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 */
11738: 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 11739: 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);
11740: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 11741: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.339 brouard 11742: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11743: /* model V1+V3+age*V1+age*V3+V1*V3 */
11744: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11745: ncovvt++;
11746: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
11747: TvarVVind[ncovvt]=k; /* TvarVV[1]=V3 (first time varying in the model equation */
11748:
1.234 brouard 11749: Fixed[k]= 1;
11750: Dummy[k]= 1;
11751: nqtveff++;
11752: modell[k].maintype= VTYPE;
11753: modell[k].subtype= VQ;
11754: ncovv++; /* Only simple time varying variables */
11755: nsq++;
1.334 brouard 11756: 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) */
11757: 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 11758: TvarV[ncovv]=Tvar[k];
1.242 brouard 11759: 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 11760: 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 */
11761: 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 11762: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
11763: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
1.349 brouard 11764: /* 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 11765: /* printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv); */
1.227 brouard 11766: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 11767: ncova++;
11768: TvarA[ncova]=Tvar[k];
11769: TvarAind[ncova]=k;
1.349 brouard 11770: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
11771: /** 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 11772: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 11773: Fixed[k]= 2;
11774: Dummy[k]= 2;
11775: modell[k].maintype= ATYPE;
11776: modell[k].subtype= APFD;
1.349 brouard 11777: ncovta++;
11778: TvarAVVA[ncovta]=Tvar[k]; /* (2)age*V3 */
11779: TvarAVVAind[ncovta]=k;
1.240 brouard 11780: /* ncoveff++; */
1.227 brouard 11781: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 11782: Fixed[k]= 2;
11783: Dummy[k]= 3;
11784: modell[k].maintype= ATYPE;
11785: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
1.349 brouard 11786: ncovta++;
11787: TvarAVVA[ncovta]=Tvar[k]; /* */
11788: TvarAVVAind[ncovta]=k;
1.240 brouard 11789: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 11790: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 11791: Fixed[k]= 3;
11792: Dummy[k]= 2;
11793: modell[k].maintype= ATYPE;
11794: modell[k].subtype= APVD; /* Product age * varying dummy */
1.349 brouard 11795: ncovva++;
11796: TvarVVA[ncovva]=Tvar[k]; /* (1)+age*V6 + (2)age*V7 */
11797: TvarVVAind[ncovva]=k;
11798: ncovta++;
11799: TvarAVVA[ncovta]=Tvar[k]; /* */
11800: TvarAVVAind[ncovta]=k;
1.240 brouard 11801: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 11802: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 11803: Fixed[k]= 3;
11804: Dummy[k]= 3;
11805: modell[k].maintype= ATYPE;
11806: modell[k].subtype= APVQ; /* Product age * varying quantitative */
1.349 brouard 11807: ncovva++;
11808: TvarVVA[ncovva]=Tvar[k]; /* */
11809: TvarVVAind[ncovva]=k;
11810: ncovta++;
11811: TvarAVVA[ncovta]=Tvar[k]; /* (1)+age*V6 + (2)age*V7 */
11812: TvarAVVAind[ncovta]=k;
1.240 brouard 11813: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 11814: }
1.349 brouard 11815: }else if( Tposprod[k]>0 && Typevar[k]==2){ /* Detects if fixed product no age Vm*Vn */
11816: printf("MEMORY ERRORR k=%d Tposprod[k]=%d, Typevar[k]=%d\n ",k, Tposprod[k], Typevar[k]);
11817: 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 */
11818: 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]]);
11819: Fixed[k]= 0;
11820: Dummy[k]= 0;
11821: ncoveff++;
11822: ncovf++;
11823: /* ncovv++; */
11824: /* TvarVV[ncovv]=Tvardk[k][1]; */
11825: /* FixedV[ncovcolt+ncovv]=0; /\* or FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11826: /* ncovv++; */
11827: /* TvarVV[ncovv]=Tvardk[k][2]; */
11828: /* FixedV[ncovcolt+ncovv]=0; /\* or FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11829: modell[k].maintype= FTYPE;
11830: TvarF[ncovf]=Tvar[k];
11831: /* TnsdVar[Tvar[k]]=nsd; */ /* To be done */
11832: TvarFind[ncovf]=k;
11833: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
11834: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
11835: }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 */
11836: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11837: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age*/
11838: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11839: 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 */
11840: ncovvt++;
11841: TvarVV[ncovvt]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */
11842: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
11843: ncovvt++;
11844: TvarVV[ncovvt]=Tvard[k1][2]; /* TvarVV[3]=V3 */
11845: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
11846:
11847: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
11848: /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
11849:
11850: if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */
11851: if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */
11852: Fixed[k]= 1;
11853: Dummy[k]= 0;
11854: modell[k].maintype= FTYPE;
11855: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
11856: ncovf++; /* Fixed variables without age */
11857: TvarF[ncovf]=Tvar[k];
11858: TvarFind[ncovf]=k;
11859: }else if(Tvard[k1][2] <=ncovcol+nqv){ /* Vm is quanti fixed */
11860: Fixed[k]= 0; /* Fixed product */
11861: Dummy[k]= 1;
11862: modell[k].maintype= FTYPE;
11863: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
11864: ncovf++; /* Varying variables without age */
11865: TvarF[ncovf]=Tvar[k];
11866: TvarFind[ncovf]=k;
11867: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is a time varying dummy covariate */
11868: Fixed[k]= 1;
11869: Dummy[k]= 0;
11870: modell[k].maintype= VTYPE;
11871: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
11872: ncovv++; /* Varying variables without age */
11873: TvarV[ncovv]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */
11874: TvarVind[ncovv]=k;/* TvarVind[1]=5 */
11875: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */
11876: Fixed[k]= 1;
11877: Dummy[k]= 1;
11878: modell[k].maintype= VTYPE;
11879: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
11880: ncovv++; /* Varying variables without age */
11881: TvarV[ncovv]=Tvar[k];
11882: TvarVind[ncovv]=k;
11883: }
11884: }else if(Tvard[k1][1] <=ncovcol+nqv){ /* Vn is fixed quanti */
11885: if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */
11886: Fixed[k]= 0; /* Fixed product */
11887: Dummy[k]= 1;
11888: modell[k].maintype= FTYPE;
11889: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
11890: ncovf++; /* Fixed variables without age */
11891: TvarF[ncovf]=Tvar[k];
11892: TvarFind[ncovf]=k;
11893: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is time varying */
11894: Fixed[k]= 1;
11895: Dummy[k]= 1;
11896: modell[k].maintype= VTYPE;
11897: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
11898: ncovv++; /* Varying variables without age */
11899: TvarV[ncovv]=Tvar[k];
11900: TvarVind[ncovv]=k;
11901: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is time varying quanti */
11902: Fixed[k]= 1;
11903: Dummy[k]= 1;
11904: modell[k].maintype= VTYPE;
11905: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
11906: ncovv++; /* Varying variables without age */
11907: TvarV[ncovv]=Tvar[k];
11908: TvarVind[ncovv]=k;
11909: ncovv++; /* Varying variables without age */
11910: TvarV[ncovv]=Tvar[k];
11911: TvarVind[ncovv]=k;
11912: }
11913: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ /* Vn is time varying dummy */
11914: if(Tvard[k1][2] <=ncovcol){
11915: Fixed[k]= 1;
11916: Dummy[k]= 1;
11917: modell[k].maintype= VTYPE;
11918: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
11919: ncovv++; /* Varying variables without age */
11920: TvarV[ncovv]=Tvar[k];
11921: TvarVind[ncovv]=k;
11922: }else if(Tvard[k1][2] <=ncovcol+nqv){
11923: Fixed[k]= 1;
11924: Dummy[k]= 1;
11925: modell[k].maintype= VTYPE;
11926: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
11927: ncovv++; /* Varying variables without age */
11928: TvarV[ncovv]=Tvar[k];
11929: TvarVind[ncovv]=k;
11930: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
11931: Fixed[k]= 1;
11932: Dummy[k]= 0;
11933: modell[k].maintype= VTYPE;
11934: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
11935: ncovv++; /* Varying variables without age */
11936: TvarV[ncovv]=Tvar[k];
11937: TvarVind[ncovv]=k;
11938: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
11939: Fixed[k]= 1;
11940: Dummy[k]= 1;
11941: modell[k].maintype= VTYPE;
11942: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
11943: ncovv++; /* Varying variables without age */
11944: TvarV[ncovv]=Tvar[k];
11945: TvarVind[ncovv]=k;
11946: }
11947: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ /* Vn is time varying quanti */
11948: if(Tvard[k1][2] <=ncovcol){
11949: Fixed[k]= 1;
11950: Dummy[k]= 1;
11951: modell[k].maintype= VTYPE;
11952: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
11953: ncovv++; /* Varying variables without age */
11954: TvarV[ncovv]=Tvar[k];
11955: TvarVind[ncovv]=k;
11956: }else if(Tvard[k1][2] <=ncovcol+nqv){
11957: Fixed[k]= 1;
11958: Dummy[k]= 1;
11959: modell[k].maintype= VTYPE;
11960: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
11961: ncovv++; /* Varying variables without age */
11962: TvarV[ncovv]=Tvar[k];
11963: TvarVind[ncovv]=k;
11964: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
11965: Fixed[k]= 1;
11966: Dummy[k]= 1;
11967: modell[k].maintype= VTYPE;
11968: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
11969: ncovv++; /* Varying variables without age */
11970: TvarV[ncovv]=Tvar[k];
11971: TvarVind[ncovv]=k;
11972: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
11973: Fixed[k]= 1;
11974: Dummy[k]= 1;
11975: modell[k].maintype= VTYPE;
11976: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
11977: ncovv++; /* Varying variables without age */
11978: TvarV[ncovv]=Tvar[k];
11979: TvarVind[ncovv]=k;
11980: }
11981: }else{
11982: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
11983: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
11984: } /*end k1*/
11985: }
11986: }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 11987: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
1.349 brouard 11988: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age*/
11989: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11990: 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 */
11991: ncova++;
11992: TvarA[ncova]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */
11993: TvarAind[ncova]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
11994: ncova++;
11995: TvarA[ncova]=Tvard[k1][2]; /* TvarVV[3]=V3 */
11996: TvarAind[ncova]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
1.339 brouard 11997:
1.349 brouard 11998: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
11999: /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
12000: if( FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){
12001: ncovta++;
12002: TvarAVVA[ncovta]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12003: TvarAVVAind[ncovta]=k;
12004: ncovta++;
12005: TvarAVVA[ncovta]=Tvard[k1][2]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12006: TvarAVVAind[ncovta]=k;
12007: }else{
12008: ncovva++; /* HERY reached */
12009: TvarVVA[ncovva]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12010: TvarVVAind[ncovva]=k;
12011: ncovva++;
12012: TvarVVA[ncovva]=Tvard[k1][2]; /* */
12013: TvarVVAind[ncovva]=k;
12014: ncovta++;
12015: TvarAVVA[ncovta]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12016: TvarAVVAind[ncovta]=k;
12017: ncovta++;
12018: TvarAVVA[ncovta]=Tvard[k1][2]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12019: TvarAVVAind[ncovta]=k;
12020: }
1.339 brouard 12021: if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */
12022: if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */
1.349 brouard 12023: Fixed[k]= 2;
12024: Dummy[k]= 2;
1.240 brouard 12025: modell[k].maintype= FTYPE;
12026: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
1.349 brouard 12027: /* TvarF[ncova]=Tvar[k]; /\* Problem to solve *\/ */
12028: /* TvarFind[ncova]=k; */
1.339 brouard 12029: }else if(Tvard[k1][2] <=ncovcol+nqv){ /* Vm is quanti fixed */
1.349 brouard 12030: Fixed[k]= 2; /* Fixed product */
12031: Dummy[k]= 3;
1.240 brouard 12032: modell[k].maintype= FTYPE;
12033: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
1.349 brouard 12034: /* TvarF[ncova]=Tvar[k]; */
12035: /* TvarFind[ncova]=k; */
1.339 brouard 12036: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is a time varying dummy covariate */
1.349 brouard 12037: Fixed[k]= 3;
12038: Dummy[k]= 2;
1.240 brouard 12039: modell[k].maintype= VTYPE;
12040: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
1.349 brouard 12041: TvarV[ncova]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */
12042: TvarVind[ncova]=k;/* TvarVind[1]=5 */
1.339 brouard 12043: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */
1.349 brouard 12044: Fixed[k]= 3;
12045: Dummy[k]= 3;
1.240 brouard 12046: modell[k].maintype= VTYPE;
12047: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
1.349 brouard 12048: /* ncovv++; /\* Varying variables without age *\/ */
12049: /* TvarV[ncovv]=Tvar[k]; */
12050: /* TvarVind[ncovv]=k; */
1.240 brouard 12051: }
1.339 brouard 12052: }else if(Tvard[k1][1] <=ncovcol+nqv){ /* Vn is fixed quanti */
12053: if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */
1.349 brouard 12054: Fixed[k]= 2; /* Fixed product */
12055: Dummy[k]= 2;
1.240 brouard 12056: modell[k].maintype= FTYPE;
12057: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
1.349 brouard 12058: /* ncova++; /\* Fixed variables with age *\/ */
12059: /* TvarF[ncovf]=Tvar[k]; */
12060: /* TvarFind[ncovf]=k; */
1.339 brouard 12061: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is time varying */
1.349 brouard 12062: Fixed[k]= 2;
12063: Dummy[k]= 3;
1.240 brouard 12064: modell[k].maintype= VTYPE;
12065: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
1.349 brouard 12066: /* ncova++; /\* Varying variables with age *\/ */
12067: /* TvarV[ncova]=Tvar[k]; */
12068: /* TvarVind[ncova]=k; */
1.339 brouard 12069: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is time varying quanti */
1.349 brouard 12070: Fixed[k]= 3;
12071: Dummy[k]= 2;
1.240 brouard 12072: modell[k].maintype= VTYPE;
12073: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
1.349 brouard 12074: ncova++; /* Varying variables without age */
12075: TvarV[ncova]=Tvar[k];
12076: TvarVind[ncova]=k;
12077: /* ncova++; /\* Varying variables without age *\/ */
12078: /* TvarV[ncova]=Tvar[k]; */
12079: /* TvarVind[ncova]=k; */
1.240 brouard 12080: }
1.339 brouard 12081: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ /* Vn is time varying dummy */
1.240 brouard 12082: if(Tvard[k1][2] <=ncovcol){
1.349 brouard 12083: Fixed[k]= 2;
12084: Dummy[k]= 2;
1.240 brouard 12085: modell[k].maintype= VTYPE;
12086: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
1.349 brouard 12087: /* ncova++; /\* Varying variables with age *\/ */
12088: /* TvarV[ncova]=Tvar[k]; */
12089: /* TvarVind[ncova]=k; */
1.240 brouard 12090: }else if(Tvard[k1][2] <=ncovcol+nqv){
1.349 brouard 12091: Fixed[k]= 2;
12092: Dummy[k]= 3;
1.240 brouard 12093: modell[k].maintype= VTYPE;
12094: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
1.349 brouard 12095: /* ncova++; /\* Varying variables with age *\/ */
12096: /* TvarV[ncova]=Tvar[k]; */
12097: /* TvarVind[ncova]=k; */
1.240 brouard 12098: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
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 time varying dummy * time varying dummy */
1.349 brouard 12103: /* ncova++; /\* Varying variables with age *\/ */
12104: /* TvarV[ncova]=Tvar[k]; */
12105: /* TvarVind[ncova]=k; */
1.240 brouard 12106: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
1.349 brouard 12107: Fixed[k]= 3;
12108: Dummy[k]= 3;
1.240 brouard 12109: modell[k].maintype= VTYPE;
12110: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
1.349 brouard 12111: /* ncova++; /\* Varying variables with age *\/ */
12112: /* TvarV[ncova]=Tvar[k]; */
12113: /* TvarVind[ncova]=k; */
1.240 brouard 12114: }
1.339 brouard 12115: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ /* Vn is time varying quanti */
1.240 brouard 12116: if(Tvard[k1][2] <=ncovcol){
1.349 brouard 12117: Fixed[k]= 2;
12118: Dummy[k]= 2;
1.240 brouard 12119: modell[k].maintype= VTYPE;
12120: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
1.349 brouard 12121: /* ncova++; /\* Varying variables with age *\/ */
12122: /* TvarV[ncova]=Tvar[k]; */
12123: /* TvarVind[ncova]=k; */
1.240 brouard 12124: }else if(Tvard[k1][2] <=ncovcol+nqv){
1.349 brouard 12125: Fixed[k]= 2;
12126: Dummy[k]= 3;
1.240 brouard 12127: modell[k].maintype= VTYPE;
12128: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
1.349 brouard 12129: /* ncova++; /\* Varying variables with age *\/ */
12130: /* TvarV[ncova]=Tvar[k]; */
12131: /* TvarVind[ncova]=k; */
1.240 brouard 12132: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
1.349 brouard 12133: Fixed[k]= 3;
12134: Dummy[k]= 2;
1.240 brouard 12135: modell[k].maintype= VTYPE;
12136: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
1.349 brouard 12137: /* ncova++; /\* Varying variables with age *\/ */
12138: /* TvarV[ncova]=Tvar[k]; */
12139: /* TvarVind[ncova]=k; */
1.240 brouard 12140: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
1.349 brouard 12141: Fixed[k]= 3;
12142: Dummy[k]= 3;
1.240 brouard 12143: modell[k].maintype= VTYPE;
12144: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
1.349 brouard 12145: /* ncova++; /\* Varying variables with age *\/ */
12146: /* TvarV[ncova]=Tvar[k]; */
12147: /* TvarVind[ncova]=k; */
1.240 brouard 12148: }
1.227 brouard 12149: }else{
1.240 brouard 12150: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12151: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12152: } /*end k1*/
1.349 brouard 12153: } else{
1.226 brouard 12154: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
12155: 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 12156: }
1.342 brouard 12157: /* 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]); */
12158: /* printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype); */
1.227 brouard 12159: 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]);
12160: }
1.349 brouard 12161: ncovvta=ncovva;
1.227 brouard 12162: /* Searching for doublons in the model */
12163: for(k1=1; k1<= cptcovt;k1++){
12164: for(k2=1; k2 <k1;k2++){
1.285 brouard 12165: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
12166: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 12167: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
12168: if(Tvar[k1]==Tvar[k2]){
1.338 brouard 12169: 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]);
12170: 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 12171: return(1);
12172: }
12173: }else if (Typevar[k1] ==2){
12174: k3=Tposprod[k1];
12175: k4=Tposprod[k2];
12176: 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 12177: 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]]);
12178: 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 12179: return(1);
12180: }
12181: }
1.227 brouard 12182: }
12183: }
1.225 brouard 12184: }
12185: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
12186: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 12187: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
12188: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.349 brouard 12189:
12190: free_imatrix(existcomb,1,NCOVMAX,1,NCOVMAX);
1.137 brouard 12191: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 12192: /*endread:*/
1.225 brouard 12193: printf("Exiting decodemodel: ");
12194: return (1);
1.136 brouard 12195: }
12196:
1.169 brouard 12197: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 12198: {/* Check ages at death */
1.136 brouard 12199: int i, m;
1.218 brouard 12200: int firstone=0;
12201:
1.136 brouard 12202: for (i=1; i<=imx; i++) {
12203: for(m=2; (m<= maxwav); m++) {
12204: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
12205: anint[m][i]=9999;
1.216 brouard 12206: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
12207: s[m][i]=-1;
1.136 brouard 12208: }
12209: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 12210: *nberr = *nberr + 1;
1.218 brouard 12211: if(firstone == 0){
12212: firstone=1;
1.260 brouard 12213: 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 12214: }
1.262 brouard 12215: 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 12216: s[m][i]=-1; /* Droping the death status */
1.136 brouard 12217: }
12218: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 12219: (*nberr)++;
1.259 brouard 12220: 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 12221: 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 12222: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 12223: }
12224: }
12225: }
12226:
12227: for (i=1; i<=imx; i++) {
12228: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
12229: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 12230: 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 12231: if (s[m][i] >= nlstate+1) {
1.169 brouard 12232: if(agedc[i]>0){
12233: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 12234: agev[m][i]=agedc[i];
1.214 brouard 12235: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 12236: }else {
1.136 brouard 12237: if ((int)andc[i]!=9999){
12238: nbwarn++;
12239: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
12240: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
12241: agev[m][i]=-1;
12242: }
12243: }
1.169 brouard 12244: } /* agedc > 0 */
1.214 brouard 12245: } /* end if */
1.136 brouard 12246: else if(s[m][i] !=9){ /* Standard case, age in fractional
12247: years but with the precision of a month */
12248: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
12249: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
12250: agev[m][i]=1;
12251: else if(agev[m][i] < *agemin){
12252: *agemin=agev[m][i];
12253: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
12254: }
12255: else if(agev[m][i] >*agemax){
12256: *agemax=agev[m][i];
1.156 brouard 12257: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 12258: }
12259: /*agev[m][i]=anint[m][i]-annais[i];*/
12260: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 12261: } /* en if 9*/
1.136 brouard 12262: else { /* =9 */
1.214 brouard 12263: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 12264: agev[m][i]=1;
12265: s[m][i]=-1;
12266: }
12267: }
1.214 brouard 12268: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 12269: agev[m][i]=1;
1.214 brouard 12270: else{
12271: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
12272: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
12273: agev[m][i]=0;
12274: }
12275: } /* End for lastpass */
12276: }
1.136 brouard 12277:
12278: for (i=1; i<=imx; i++) {
12279: for(m=firstpass; (m<=lastpass); m++){
12280: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 12281: (*nberr)++;
1.136 brouard 12282: 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);
12283: 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);
12284: return 1;
12285: }
12286: }
12287: }
12288:
12289: /*for (i=1; i<=imx; i++){
12290: for (m=firstpass; (m<lastpass); m++){
12291: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
12292: }
12293:
12294: }*/
12295:
12296:
1.139 brouard 12297: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
12298: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 12299:
12300: return (0);
1.164 brouard 12301: /* endread:*/
1.136 brouard 12302: printf("Exiting calandcheckages: ");
12303: return (1);
12304: }
12305:
1.172 brouard 12306: #if defined(_MSC_VER)
12307: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
12308: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
12309: //#include "stdafx.h"
12310: //#include <stdio.h>
12311: //#include <tchar.h>
12312: //#include <windows.h>
12313: //#include <iostream>
12314: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
12315:
12316: LPFN_ISWOW64PROCESS fnIsWow64Process;
12317:
12318: BOOL IsWow64()
12319: {
12320: BOOL bIsWow64 = FALSE;
12321:
12322: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
12323: // (HANDLE, PBOOL);
12324:
12325: //LPFN_ISWOW64PROCESS fnIsWow64Process;
12326:
12327: HMODULE module = GetModuleHandle(_T("kernel32"));
12328: const char funcName[] = "IsWow64Process";
12329: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
12330: GetProcAddress(module, funcName);
12331:
12332: if (NULL != fnIsWow64Process)
12333: {
12334: if (!fnIsWow64Process(GetCurrentProcess(),
12335: &bIsWow64))
12336: //throw std::exception("Unknown error");
12337: printf("Unknown error\n");
12338: }
12339: return bIsWow64 != FALSE;
12340: }
12341: #endif
1.177 brouard 12342:
1.191 brouard 12343: void syscompilerinfo(int logged)
1.292 brouard 12344: {
12345: #include <stdint.h>
12346:
12347: /* #include "syscompilerinfo.h"*/
1.185 brouard 12348: /* command line Intel compiler 32bit windows, XP compatible:*/
12349: /* /GS /W3 /Gy
12350: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
12351: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
12352: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 12353: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
12354: */
12355: /* 64 bits */
1.185 brouard 12356: /*
12357: /GS /W3 /Gy
12358: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
12359: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
12360: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
12361: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
12362: /* Optimization are useless and O3 is slower than O2 */
12363: /*
12364: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
12365: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
12366: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
12367: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
12368: */
1.186 brouard 12369: /* Link is */ /* /OUT:"visual studio
1.185 brouard 12370: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
12371: /PDB:"visual studio
12372: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
12373: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
12374: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
12375: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
12376: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
12377: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
12378: uiAccess='false'"
12379: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
12380: /NOLOGO /TLBID:1
12381: */
1.292 brouard 12382:
12383:
1.177 brouard 12384: #if defined __INTEL_COMPILER
1.178 brouard 12385: #if defined(__GNUC__)
12386: struct utsname sysInfo; /* For Intel on Linux and OS/X */
12387: #endif
1.177 brouard 12388: #elif defined(__GNUC__)
1.179 brouard 12389: #ifndef __APPLE__
1.174 brouard 12390: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 12391: #endif
1.177 brouard 12392: struct utsname sysInfo;
1.178 brouard 12393: int cross = CROSS;
12394: if (cross){
12395: printf("Cross-");
1.191 brouard 12396: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 12397: }
1.174 brouard 12398: #endif
12399:
1.191 brouard 12400: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 12401: #if defined(__clang__)
1.191 brouard 12402: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 12403: #endif
12404: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 12405: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 12406: #endif
12407: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 12408: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 12409: #endif
12410: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 12411: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 12412: #endif
12413: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 12414: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 12415: #endif
12416: #if defined(_MSC_VER)
1.191 brouard 12417: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 12418: #endif
12419: #if defined(__PGI)
1.191 brouard 12420: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 12421: #endif
12422: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 12423: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 12424: #endif
1.191 brouard 12425: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 12426:
1.167 brouard 12427: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
12428: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
12429: // Windows (x64 and x86)
1.191 brouard 12430: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 12431: #elif __unix__ // all unices, not all compilers
12432: // Unix
1.191 brouard 12433: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 12434: #elif __linux__
12435: // linux
1.191 brouard 12436: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 12437: #elif __APPLE__
1.174 brouard 12438: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 12439: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 12440: #endif
12441:
12442: /* __MINGW32__ */
12443: /* __CYGWIN__ */
12444: /* __MINGW64__ */
12445: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
12446: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
12447: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
12448: /* _WIN64 // Defined for applications for Win64. */
12449: /* _M_X64 // Defined for compilations that target x64 processors. */
12450: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 12451:
1.167 brouard 12452: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 12453: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 12454: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 12455: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 12456: #else
1.191 brouard 12457: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 12458: #endif
12459:
1.169 brouard 12460: #if defined(__GNUC__)
12461: # if defined(__GNUC_PATCHLEVEL__)
12462: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
12463: + __GNUC_MINOR__ * 100 \
12464: + __GNUC_PATCHLEVEL__)
12465: # else
12466: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
12467: + __GNUC_MINOR__ * 100)
12468: # endif
1.174 brouard 12469: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 12470: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 12471:
12472: if (uname(&sysInfo) != -1) {
12473: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 12474: 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 12475: }
12476: else
12477: perror("uname() error");
1.179 brouard 12478: //#ifndef __INTEL_COMPILER
12479: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 12480: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 12481: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 12482: #endif
1.169 brouard 12483: #endif
1.172 brouard 12484:
1.286 brouard 12485: // void main ()
1.172 brouard 12486: // {
1.169 brouard 12487: #if defined(_MSC_VER)
1.174 brouard 12488: if (IsWow64()){
1.191 brouard 12489: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
12490: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 12491: }
12492: else{
1.191 brouard 12493: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
12494: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 12495: }
1.172 brouard 12496: // printf("\nPress Enter to continue...");
12497: // getchar();
12498: // }
12499:
1.169 brouard 12500: #endif
12501:
1.167 brouard 12502:
1.219 brouard 12503: }
1.136 brouard 12504:
1.219 brouard 12505: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 12506: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.332 brouard 12507: /* Computes the prevalence limit for each combination of the dummy covariates */
1.235 brouard 12508: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 12509: /* double ftolpl = 1.e-10; */
1.180 brouard 12510: double age, agebase, agelim;
1.203 brouard 12511: double tot;
1.180 brouard 12512:
1.202 brouard 12513: strcpy(filerespl,"PL_");
12514: strcat(filerespl,fileresu);
12515: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 12516: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
12517: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 12518: }
1.288 brouard 12519: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
12520: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 12521: pstamp(ficrespl);
1.288 brouard 12522: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 12523: fprintf(ficrespl,"#Age ");
12524: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
12525: fprintf(ficrespl,"\n");
1.180 brouard 12526:
1.219 brouard 12527: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 12528:
1.219 brouard 12529: agebase=ageminpar;
12530: agelim=agemaxpar;
1.180 brouard 12531:
1.227 brouard 12532: /* i1=pow(2,ncoveff); */
1.234 brouard 12533: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 12534: if (cptcovn < 1){i1=1;}
1.180 brouard 12535:
1.337 brouard 12536: /* for(k=1; k<=i1;k++){ /\* For each combination k of dummy covariates in the model *\/ */
1.238 brouard 12537: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 12538: k=TKresult[nres];
1.338 brouard 12539: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12540: /* if(i1 != 1 && TKresult[nres]!= k) /\* We found the combination k corresponding to the resultline value of dummies *\/ */
12541: /* continue; */
1.235 brouard 12542:
1.238 brouard 12543: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12544: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
12545: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
12546: /* k=k+1; */
12547: /* to clean */
1.332 brouard 12548: /*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*/
1.238 brouard 12549: fprintf(ficrespl,"#******");
12550: printf("#******");
12551: fprintf(ficlog,"#******");
1.337 brouard 12552: 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 12553: /* fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Here problem for varying dummy*\/ */
1.337 brouard 12554: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12555: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12556: fprintf(ficrespl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12557: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12558: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12559: }
12560: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
12561: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12562: /* fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12563: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12564: /* } */
1.238 brouard 12565: fprintf(ficrespl,"******\n");
12566: printf("******\n");
12567: fprintf(ficlog,"******\n");
12568: if(invalidvarcomb[k]){
12569: printf("\nCombination (%d) ignored because no case \n",k);
12570: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
12571: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
12572: continue;
12573: }
1.219 brouard 12574:
1.238 brouard 12575: fprintf(ficrespl,"#Age ");
1.337 brouard 12576: /* for(j=1;j<=cptcoveff;j++) { */
12577: /* fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12578: /* } */
12579: for(j=1;j<=cptcovs;j++) { /* New the quanti variable is added */
12580: fprintf(ficrespl,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12581: }
12582: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
12583: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 12584:
1.238 brouard 12585: for (age=agebase; age<=agelim; age++){
12586: /* for (age=agebase; age<=agebase; age++){ */
1.337 brouard 12587: /**< Computes the prevalence limit in each live state at age x and for covariate combination (k and) nres */
12588: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres); /* Nicely done */
1.238 brouard 12589: fprintf(ficrespl,"%.0f ",age );
1.337 brouard 12590: /* for(j=1;j<=cptcoveff;j++) */
12591: /* fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12592: for(j=1;j<=cptcovs;j++)
12593: fprintf(ficrespl,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12594: tot=0.;
12595: for(i=1; i<=nlstate;i++){
12596: tot += prlim[i][i];
12597: fprintf(ficrespl," %.5f", prlim[i][i]);
12598: }
12599: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
12600: } /* Age */
12601: /* was end of cptcod */
1.337 brouard 12602: } /* nres */
12603: /* } /\* for each combination *\/ */
1.219 brouard 12604: return 0;
1.180 brouard 12605: }
12606:
1.218 brouard 12607: 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 12608: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 12609:
12610: /* Computes the back prevalence limit for any combination of covariate values
12611: * at any age between ageminpar and agemaxpar
12612: */
1.235 brouard 12613: int i, j, k, i1, nres=0 ;
1.217 brouard 12614: /* double ftolpl = 1.e-10; */
12615: double age, agebase, agelim;
12616: double tot;
1.218 brouard 12617: /* double ***mobaverage; */
12618: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 12619:
12620: strcpy(fileresplb,"PLB_");
12621: strcat(fileresplb,fileresu);
12622: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 12623: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
12624: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 12625: }
1.288 brouard 12626: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
12627: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 12628: pstamp(ficresplb);
1.288 brouard 12629: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 12630: fprintf(ficresplb,"#Age ");
12631: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
12632: fprintf(ficresplb,"\n");
12633:
1.218 brouard 12634:
12635: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
12636:
12637: agebase=ageminpar;
12638: agelim=agemaxpar;
12639:
12640:
1.227 brouard 12641: i1=pow(2,cptcoveff);
1.218 brouard 12642: if (cptcovn < 1){i1=1;}
1.227 brouard 12643:
1.238 brouard 12644: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.338 brouard 12645: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
12646: k=TKresult[nres];
12647: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
12648: /* if(i1 != 1 && TKresult[nres]!= k) */
12649: /* continue; */
12650: /* /\*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*\/ */
1.238 brouard 12651: fprintf(ficresplb,"#******");
12652: printf("#******");
12653: fprintf(ficlog,"#******");
1.338 brouard 12654: 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) */
12655: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12656: fprintf(ficresplb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12657: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12658: }
1.338 brouard 12659: /* for(j=1;j<=cptcoveff ;j++) {/\* all covariates *\/ */
12660: /* fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12661: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12662: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12663: /* } */
12664: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
12665: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12666: /* fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12667: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12668: /* } */
1.238 brouard 12669: fprintf(ficresplb,"******\n");
12670: printf("******\n");
12671: fprintf(ficlog,"******\n");
12672: if(invalidvarcomb[k]){
12673: printf("\nCombination (%d) ignored because no cases \n",k);
12674: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
12675: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
12676: continue;
12677: }
1.218 brouard 12678:
1.238 brouard 12679: fprintf(ficresplb,"#Age ");
1.338 brouard 12680: for(j=1;j<=cptcovs;j++) {
12681: fprintf(ficresplb,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12682: }
12683: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
12684: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 12685:
12686:
1.238 brouard 12687: for (age=agebase; age<=agelim; age++){
12688: /* for (age=agebase; age<=agebase; age++){ */
12689: if(mobilavproj > 0){
12690: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
12691: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 12692: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 12693: }else if (mobilavproj == 0){
12694: 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);
12695: 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);
12696: exit(1);
12697: }else{
12698: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 12699: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 12700: /* printf("TOTOT\n"); */
12701: /* exit(1); */
1.238 brouard 12702: }
12703: fprintf(ficresplb,"%.0f ",age );
1.338 brouard 12704: for(j=1;j<=cptcovs;j++)
12705: fprintf(ficresplb,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12706: tot=0.;
12707: for(i=1; i<=nlstate;i++){
12708: tot += bprlim[i][i];
12709: fprintf(ficresplb," %.5f", bprlim[i][i]);
12710: }
12711: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
12712: } /* Age */
12713: /* was end of cptcod */
1.255 brouard 12714: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.338 brouard 12715: /* } /\* end of any combination *\/ */
1.238 brouard 12716: } /* end of nres */
1.218 brouard 12717: /* hBijx(p, bage, fage); */
12718: /* fclose(ficrespijb); */
12719:
12720: return 0;
1.217 brouard 12721: }
1.218 brouard 12722:
1.180 brouard 12723: int hPijx(double *p, int bage, int fage){
12724: /*------------- h Pij x at various ages ------------*/
1.336 brouard 12725: /* to be optimized with precov */
1.180 brouard 12726: int stepsize;
12727: int agelim;
12728: int hstepm;
12729: int nhstepm;
1.235 brouard 12730: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 12731:
12732: double agedeb;
12733: double ***p3mat;
12734:
1.337 brouard 12735: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
12736: if((ficrespij=fopen(filerespij,"w"))==NULL) {
12737: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
12738: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
12739: }
12740: printf("Computing pij: result on file '%s' \n", filerespij);
12741: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
12742:
12743: stepsize=(int) (stepm+YEARM-1)/YEARM;
12744: /*if (stepm<=24) stepsize=2;*/
12745:
12746: agelim=AGESUP;
12747: hstepm=stepsize*YEARM; /* Every year of age */
12748: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
12749:
12750: /* hstepm=1; aff par mois*/
12751: pstamp(ficrespij);
12752: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
12753: i1= pow(2,cptcoveff);
12754: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12755: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
12756: /* k=k+1; */
12757: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
12758: k=TKresult[nres];
1.338 brouard 12759: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12760: /* for(k=1; k<=i1;k++){ */
12761: /* if(i1 != 1 && TKresult[nres]!= k) */
12762: /* continue; */
12763: fprintf(ficrespij,"\n#****** ");
12764: for(j=1;j<=cptcovs;j++){
12765: fprintf(ficrespij," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12766: /* fprintf(ficrespij,"@wV%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12767: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
12768: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12769: /* fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12770: }
12771: fprintf(ficrespij,"******\n");
12772:
12773: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
12774: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
12775: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
12776:
12777: /* nhstepm=nhstepm*YEARM; aff par mois*/
12778:
12779: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12780: oldm=oldms;savm=savms;
12781: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
12782: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
12783: for(i=1; i<=nlstate;i++)
12784: for(j=1; j<=nlstate+ndeath;j++)
12785: fprintf(ficrespij," %1d-%1d",i,j);
12786: fprintf(ficrespij,"\n");
12787: for (h=0; h<=nhstepm; h++){
12788: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
12789: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.183 brouard 12790: for(i=1; i<=nlstate;i++)
12791: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 12792: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.183 brouard 12793: fprintf(ficrespij,"\n");
12794: }
1.337 brouard 12795: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12796: fprintf(ficrespij,"\n");
1.180 brouard 12797: }
1.337 brouard 12798: }
12799: /*}*/
12800: return 0;
1.180 brouard 12801: }
1.218 brouard 12802:
12803: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 12804: /*------------- h Bij x at various ages ------------*/
1.336 brouard 12805: /* To be optimized with precov */
1.217 brouard 12806: int stepsize;
1.218 brouard 12807: /* int agelim; */
12808: int ageminl;
1.217 brouard 12809: int hstepm;
12810: int nhstepm;
1.238 brouard 12811: int h, i, i1, j, k, nres;
1.218 brouard 12812:
1.217 brouard 12813: double agedeb;
12814: double ***p3mat;
1.218 brouard 12815:
12816: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
12817: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
12818: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
12819: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
12820: }
12821: printf("Computing pij back: result on file '%s' \n", filerespijb);
12822: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
12823:
12824: stepsize=(int) (stepm+YEARM-1)/YEARM;
12825: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 12826:
1.218 brouard 12827: /* agelim=AGESUP; */
1.289 brouard 12828: ageminl=AGEINF; /* was 30 */
1.218 brouard 12829: hstepm=stepsize*YEARM; /* Every year of age */
12830: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
12831:
12832: /* hstepm=1; aff par mois*/
12833: pstamp(ficrespijb);
1.255 brouard 12834: 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 12835: i1= pow(2,cptcoveff);
1.218 brouard 12836: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12837: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
12838: /* k=k+1; */
1.238 brouard 12839: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 12840: k=TKresult[nres];
1.338 brouard 12841: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12842: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
12843: /* if(i1 != 1 && TKresult[nres]!= k) */
12844: /* continue; */
12845: fprintf(ficrespijb,"\n#****** ");
12846: for(j=1;j<=cptcovs;j++){
1.338 brouard 12847: fprintf(ficrespijb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.337 brouard 12848: /* for(j=1;j<=cptcoveff;j++) */
12849: /* fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12850: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
12851: /* fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12852: }
12853: fprintf(ficrespijb,"******\n");
12854: if(invalidvarcomb[k]){ /* Is it necessary here? */
12855: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
12856: continue;
12857: }
12858:
12859: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
12860: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
12861: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
12862: 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 */
12863: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 or 28*/
12864:
12865: /* nhstepm=nhstepm*YEARM; aff par mois*/
12866:
12867: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
12868: /* and memory limitations if stepm is small */
12869:
12870: /* oldm=oldms;savm=savms; */
12871: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
12872: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);/* Bug valgrind */
12873: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
12874: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
12875: for(i=1; i<=nlstate;i++)
12876: for(j=1; j<=nlstate+ndeath;j++)
12877: fprintf(ficrespijb," %1d-%1d",i,j);
12878: fprintf(ficrespijb,"\n");
12879: for (h=0; h<=nhstepm; h++){
12880: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
12881: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
12882: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
1.217 brouard 12883: for(i=1; i<=nlstate;i++)
12884: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 12885: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);/* Bug valgrind */
1.217 brouard 12886: fprintf(ficrespijb,"\n");
1.337 brouard 12887: }
12888: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12889: fprintf(ficrespijb,"\n");
12890: } /* end age deb */
12891: /* } /\* end combination *\/ */
1.238 brouard 12892: } /* end nres */
1.218 brouard 12893: return 0;
12894: } /* hBijx */
1.217 brouard 12895:
1.180 brouard 12896:
1.136 brouard 12897: /***********************************************/
12898: /**************** Main Program *****************/
12899: /***********************************************/
12900:
12901: int main(int argc, char *argv[])
12902: {
12903: #ifdef GSL
12904: const gsl_multimin_fminimizer_type *T;
12905: size_t iteri = 0, it;
12906: int rval = GSL_CONTINUE;
12907: int status = GSL_SUCCESS;
12908: double ssval;
12909: #endif
12910: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 12911: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
12912: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 12913: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 12914: int jj, ll, li, lj, lk;
1.136 brouard 12915: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 12916: int num_filled;
1.136 brouard 12917: int itimes;
12918: int NDIM=2;
12919: int vpopbased=0;
1.235 brouard 12920: int nres=0;
1.258 brouard 12921: int endishere=0;
1.277 brouard 12922: int noffset=0;
1.274 brouard 12923: int ncurrv=0; /* Temporary variable */
12924:
1.164 brouard 12925: char ca[32], cb[32];
1.136 brouard 12926: /* FILE *fichtm; *//* Html File */
12927: /* FILE *ficgp;*/ /*Gnuplot File */
12928: struct stat info;
1.191 brouard 12929: double agedeb=0.;
1.194 brouard 12930:
12931: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 12932: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 12933:
1.165 brouard 12934: double fret;
1.191 brouard 12935: double dum=0.; /* Dummy variable */
1.136 brouard 12936: double ***p3mat;
1.218 brouard 12937: /* double ***mobaverage; */
1.319 brouard 12938: double wald;
1.164 brouard 12939:
12940: char line[MAXLINE];
1.197 brouard 12941: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
12942:
1.234 brouard 12943: char modeltemp[MAXLINE];
1.332 brouard 12944: char resultline[MAXLINE], resultlineori[MAXLINE];
1.230 brouard 12945:
1.136 brouard 12946: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 12947: char *tok, *val; /* pathtot */
1.334 brouard 12948: /* int firstobs=1, lastobs=10; /\* nobs = lastobs-firstobs declared globally ;*\/ */
1.195 brouard 12949: int c, h , cpt, c2;
1.191 brouard 12950: int jl=0;
12951: int i1, j1, jk, stepsize=0;
1.194 brouard 12952: int count=0;
12953:
1.164 brouard 12954: int *tab;
1.136 brouard 12955: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.296 brouard 12956: /* double anprojd, mprojd, jprojd; /\* For eventual projections *\/ */
12957: /* double anprojf, mprojf, jprojf; */
12958: /* double jintmean,mintmean,aintmean; */
12959: int prvforecast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
12960: int prvbackcast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
12961: double yrfproj= 10.0; /* Number of years of forward projections */
12962: double yrbproj= 10.0; /* Number of years of backward projections */
12963: int prevbcast=0; /* defined as global for mlikeli and mle, replacing backcast */
1.136 brouard 12964: int mobilav=0,popforecast=0;
1.191 brouard 12965: int hstepm=0, nhstepm=0;
1.136 brouard 12966: int agemortsup;
12967: float sumlpop=0.;
12968: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
12969: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
12970:
1.191 brouard 12971: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 12972: double ftolpl=FTOL;
12973: double **prlim;
1.217 brouard 12974: double **bprlim;
1.317 brouard 12975: double ***param; /* Matrix of parameters, param[i][j][k] param=ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel)
12976: state of origin, state of destination including death, for each covariate: constante, age, and V1 V2 etc. */
1.251 brouard 12977: double ***paramstart; /* Matrix of starting parameter values */
12978: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 12979: double **matcov; /* Matrix of covariance */
1.203 brouard 12980: double **hess; /* Hessian matrix */
1.136 brouard 12981: double ***delti3; /* Scale */
12982: double *delti; /* Scale */
12983: double ***eij, ***vareij;
12984: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 12985:
1.136 brouard 12986: double *epj, vepp;
1.164 brouard 12987:
1.273 brouard 12988: double dateprev1, dateprev2;
1.296 brouard 12989: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0, dateprojd=0, dateprojf=0;
12990: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0, datebackd=0, datebackf=0;
12991:
1.217 brouard 12992:
1.136 brouard 12993: double **ximort;
1.145 brouard 12994: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 12995: int *dcwave;
12996:
1.164 brouard 12997: char z[1]="c";
1.136 brouard 12998:
12999: /*char *strt;*/
13000: char strtend[80];
1.126 brouard 13001:
1.164 brouard 13002:
1.126 brouard 13003: /* setlocale (LC_ALL, ""); */
13004: /* bindtextdomain (PACKAGE, LOCALEDIR); */
13005: /* textdomain (PACKAGE); */
13006: /* setlocale (LC_CTYPE, ""); */
13007: /* setlocale (LC_MESSAGES, ""); */
13008:
13009: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 13010: rstart_time = time(NULL);
13011: /* (void) gettimeofday(&start_time,&tzp);*/
13012: start_time = *localtime(&rstart_time);
1.126 brouard 13013: curr_time=start_time;
1.157 brouard 13014: /*tml = *localtime(&start_time.tm_sec);*/
13015: /* strcpy(strstart,asctime(&tml)); */
13016: strcpy(strstart,asctime(&start_time));
1.126 brouard 13017:
13018: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 13019: /* tp.tm_sec = tp.tm_sec +86400; */
13020: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 13021: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
13022: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
13023: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 13024: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 13025: /* strt=asctime(&tmg); */
13026: /* printf("Time(after) =%s",strstart); */
13027: /* (void) time (&time_value);
13028: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
13029: * tm = *localtime(&time_value);
13030: * strstart=asctime(&tm);
13031: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
13032: */
13033:
13034: nberr=0; /* Number of errors and warnings */
13035: nbwarn=0;
1.184 brouard 13036: #ifdef WIN32
13037: _getcwd(pathcd, size);
13038: #else
1.126 brouard 13039: getcwd(pathcd, size);
1.184 brouard 13040: #endif
1.191 brouard 13041: syscompilerinfo(0);
1.196 brouard 13042: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 13043: if(argc <=1){
13044: printf("\nEnter the parameter file name: ");
1.205 brouard 13045: if(!fgets(pathr,FILENAMELENGTH,stdin)){
13046: printf("ERROR Empty parameter file name\n");
13047: goto end;
13048: }
1.126 brouard 13049: i=strlen(pathr);
13050: if(pathr[i-1]=='\n')
13051: pathr[i-1]='\0';
1.156 brouard 13052: i=strlen(pathr);
1.205 brouard 13053: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 13054: pathr[i-1]='\0';
1.205 brouard 13055: }
13056: i=strlen(pathr);
13057: if( i==0 ){
13058: printf("ERROR Empty parameter file name\n");
13059: goto end;
13060: }
13061: for (tok = pathr; tok != NULL; ){
1.126 brouard 13062: printf("Pathr |%s|\n",pathr);
13063: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
13064: printf("val= |%s| pathr=%s\n",val,pathr);
13065: strcpy (pathtot, val);
13066: if(pathr[0] == '\0') break; /* Dirty */
13067: }
13068: }
1.281 brouard 13069: else if (argc<=2){
13070: strcpy(pathtot,argv[1]);
13071: }
1.126 brouard 13072: else{
13073: strcpy(pathtot,argv[1]);
1.281 brouard 13074: strcpy(z,argv[2]);
13075: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 13076: }
13077: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
13078: /*cygwin_split_path(pathtot,path,optionfile);
13079: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
13080: /* cutv(path,optionfile,pathtot,'\\');*/
13081:
13082: /* Split argv[0], imach program to get pathimach */
13083: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
13084: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
13085: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
13086: /* strcpy(pathimach,argv[0]); */
13087: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
13088: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
13089: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 13090: #ifdef WIN32
13091: _chdir(path); /* Can be a relative path */
13092: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
13093: #else
1.126 brouard 13094: chdir(path); /* Can be a relative path */
1.184 brouard 13095: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
13096: #endif
13097: printf("Current directory %s!\n",pathcd);
1.126 brouard 13098: strcpy(command,"mkdir ");
13099: strcat(command,optionfilefiname);
13100: if((outcmd=system(command)) != 0){
1.169 brouard 13101: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 13102: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
13103: /* fclose(ficlog); */
13104: /* exit(1); */
13105: }
13106: /* if((imk=mkdir(optionfilefiname))<0){ */
13107: /* perror("mkdir"); */
13108: /* } */
13109:
13110: /*-------- arguments in the command line --------*/
13111:
1.186 brouard 13112: /* Main Log file */
1.126 brouard 13113: strcat(filelog, optionfilefiname);
13114: strcat(filelog,".log"); /* */
13115: if((ficlog=fopen(filelog,"w"))==NULL) {
13116: printf("Problem with logfile %s\n",filelog);
13117: goto end;
13118: }
13119: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 13120: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 13121: fprintf(ficlog,"\nEnter the parameter file name: \n");
13122: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
13123: path=%s \n\
13124: optionfile=%s\n\
13125: optionfilext=%s\n\
1.156 brouard 13126: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 13127:
1.197 brouard 13128: syscompilerinfo(1);
1.167 brouard 13129:
1.126 brouard 13130: printf("Local time (at start):%s",strstart);
13131: fprintf(ficlog,"Local time (at start): %s",strstart);
13132: fflush(ficlog);
13133: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 13134: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 13135:
13136: /* */
13137: strcpy(fileres,"r");
13138: strcat(fileres, optionfilefiname);
1.201 brouard 13139: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 13140: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 13141: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 13142:
1.186 brouard 13143: /* Main ---------arguments file --------*/
1.126 brouard 13144:
13145: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 13146: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
13147: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 13148: fflush(ficlog);
1.149 brouard 13149: /* goto end; */
13150: exit(70);
1.126 brouard 13151: }
13152:
13153: strcpy(filereso,"o");
1.201 brouard 13154: strcat(filereso,fileresu);
1.126 brouard 13155: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
13156: printf("Problem with Output resultfile: %s\n", filereso);
13157: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
13158: fflush(ficlog);
13159: goto end;
13160: }
1.278 brouard 13161: /*-------- Rewriting parameter file ----------*/
13162: strcpy(rfileres,"r"); /* "Rparameterfile */
13163: strcat(rfileres,optionfilefiname); /* Parameter file first name */
13164: strcat(rfileres,"."); /* */
13165: strcat(rfileres,optionfilext); /* Other files have txt extension */
13166: if((ficres =fopen(rfileres,"w"))==NULL) {
13167: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
13168: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
13169: fflush(ficlog);
13170: goto end;
13171: }
13172: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 13173:
1.278 brouard 13174:
1.126 brouard 13175: /* Reads comments: lines beginning with '#' */
13176: numlinepar=0;
1.277 brouard 13177: /* Is it a BOM UTF-8 Windows file? */
13178: /* First parameter line */
1.197 brouard 13179: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 13180: noffset=0;
13181: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
13182: {
13183: noffset=noffset+3;
13184: printf("# File is an UTF8 Bom.\n"); // 0xBF
13185: }
1.302 brouard 13186: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
13187: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
1.277 brouard 13188: {
13189: noffset=noffset+2;
13190: printf("# File is an UTF16BE BOM file\n");
13191: }
13192: else if( line[0] == 0 && line[1] == 0)
13193: {
13194: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
13195: noffset=noffset+4;
13196: printf("# File is an UTF16BE BOM file\n");
13197: }
13198: } else{
13199: ;/*printf(" Not a BOM file\n");*/
13200: }
13201:
1.197 brouard 13202: /* If line starts with a # it is a comment */
1.277 brouard 13203: if (line[noffset] == '#') {
1.197 brouard 13204: numlinepar++;
13205: fputs(line,stdout);
13206: fputs(line,ficparo);
1.278 brouard 13207: fputs(line,ficres);
1.197 brouard 13208: fputs(line,ficlog);
13209: continue;
13210: }else
13211: break;
13212: }
13213: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
13214: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
13215: if (num_filled != 5) {
13216: printf("Should be 5 parameters\n");
1.283 brouard 13217: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 13218: }
1.126 brouard 13219: numlinepar++;
1.197 brouard 13220: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 13221: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
13222: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
13223: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 13224: }
13225: /* Second parameter line */
13226: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 13227: /* while(fscanf(ficpar,"%[^\n]", line)) { */
13228: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 13229: if (line[0] == '#') {
13230: numlinepar++;
1.283 brouard 13231: printf("%s",line);
13232: fprintf(ficres,"%s",line);
13233: fprintf(ficparo,"%s",line);
13234: fprintf(ficlog,"%s",line);
1.197 brouard 13235: continue;
13236: }else
13237: break;
13238: }
1.223 brouard 13239: 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", \
13240: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
13241: if (num_filled != 11) {
13242: 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 13243: printf("but line=%s\n",line);
1.283 brouard 13244: 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");
13245: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 13246: }
1.286 brouard 13247: if( lastpass > maxwav){
13248: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
13249: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
13250: fflush(ficlog);
13251: goto end;
13252: }
13253: 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 13254: 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 13255: 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 13256: 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 13257: }
1.203 brouard 13258: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 13259: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 13260: /* Third parameter line */
13261: while(fgets(line, MAXLINE, ficpar)) {
13262: /* If line starts with a # it is a comment */
13263: if (line[0] == '#') {
13264: numlinepar++;
1.283 brouard 13265: printf("%s",line);
13266: fprintf(ficres,"%s",line);
13267: fprintf(ficparo,"%s",line);
13268: fprintf(ficlog,"%s",line);
1.197 brouard 13269: continue;
13270: }else
13271: break;
13272: }
1.201 brouard 13273: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.279 brouard 13274: if (num_filled != 1){
1.302 brouard 13275: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
13276: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
1.197 brouard 13277: model[0]='\0';
13278: goto end;
13279: }
13280: else{
13281: if (model[0]=='+'){
13282: for(i=1; i<=strlen(model);i++)
13283: modeltemp[i-1]=model[i];
1.201 brouard 13284: strcpy(model,modeltemp);
1.197 brouard 13285: }
13286: }
1.338 brouard 13287: /* printf(" model=1+age%s modeltemp= %s, model=1+age+%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 13288: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 13289: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
13290: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
13291: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 13292: }
13293: /* 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); */
13294: /* numlinepar=numlinepar+3; /\* In general *\/ */
13295: /* 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 13296: /* 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); */
13297: /* 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 13298: fflush(ficlog);
1.190 brouard 13299: /* if(model[0]=='#'|| model[0]== '\0'){ */
13300: if(model[0]=='#'){
1.279 brouard 13301: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
13302: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
13303: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 13304: if(mle != -1){
1.279 brouard 13305: 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 13306: exit(1);
13307: }
13308: }
1.126 brouard 13309: while((c=getc(ficpar))=='#' && c!= EOF){
13310: ungetc(c,ficpar);
13311: fgets(line, MAXLINE, ficpar);
13312: numlinepar++;
1.195 brouard 13313: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
13314: z[0]=line[1];
1.342 brouard 13315: }else if(line[1]=='d'){ /* For debugging individual values of covariates in ficresilk */
1.343 brouard 13316: debugILK=1;printf("DebugILK\n");
1.195 brouard 13317: }
13318: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 13319: fputs(line, stdout);
13320: //puts(line);
1.126 brouard 13321: fputs(line,ficparo);
13322: fputs(line,ficlog);
13323: }
13324: ungetc(c,ficpar);
13325:
13326:
1.290 brouard 13327: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
13328: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
13329: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
1.341 brouard 13330: /* if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /\**< Time varying covariate (dummy and quantitative)*\/ */
13331: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs); /**< Might be better */
1.136 brouard 13332: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
13333: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
13334: v1+v2*age+v2*v3 makes cptcovn = 3
13335: */
13336: if (strlen(model)>1)
1.187 brouard 13337: 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 13338: else
1.187 brouard 13339: ncovmodel=2; /* Constant and age */
1.133 brouard 13340: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
13341: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 13342: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
13343: 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);
13344: 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);
13345: fflush(stdout);
13346: fclose (ficlog);
13347: goto end;
13348: }
1.126 brouard 13349: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
13350: delti=delti3[1][1];
13351: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
13352: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 13353: /* We could also provide initial parameters values giving by simple logistic regression
13354: * only one way, that is without matrix product. We will have nlstate maximizations */
13355: /* for(i=1;i<nlstate;i++){ */
13356: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
13357: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
13358: /* } */
1.126 brouard 13359: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 13360: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
13361: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 13362: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
13363: fclose (ficparo);
13364: fclose (ficlog);
13365: goto end;
13366: exit(0);
1.220 brouard 13367: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 13368: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 13369: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
13370: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 13371: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
13372: matcov=matrix(1,npar,1,npar);
1.203 brouard 13373: hess=matrix(1,npar,1,npar);
1.220 brouard 13374: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 13375: /* Read guessed parameters */
1.126 brouard 13376: /* Reads comments: lines beginning with '#' */
13377: while((c=getc(ficpar))=='#' && c!= EOF){
13378: ungetc(c,ficpar);
13379: fgets(line, MAXLINE, ficpar);
13380: numlinepar++;
1.141 brouard 13381: fputs(line,stdout);
1.126 brouard 13382: fputs(line,ficparo);
13383: fputs(line,ficlog);
13384: }
13385: ungetc(c,ficpar);
13386:
13387: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 13388: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 13389: for(i=1; i <=nlstate; i++){
1.234 brouard 13390: j=0;
1.126 brouard 13391: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 13392: if(jj==i) continue;
13393: j++;
1.292 brouard 13394: while((c=getc(ficpar))=='#' && c!= EOF){
13395: ungetc(c,ficpar);
13396: fgets(line, MAXLINE, ficpar);
13397: numlinepar++;
13398: fputs(line,stdout);
13399: fputs(line,ficparo);
13400: fputs(line,ficlog);
13401: }
13402: ungetc(c,ficpar);
1.234 brouard 13403: fscanf(ficpar,"%1d%1d",&i1,&j1);
13404: if ((i1 != i) || (j1 != jj)){
13405: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 13406: It might be a problem of design; if ncovcol and the model are correct\n \
13407: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 13408: exit(1);
13409: }
13410: fprintf(ficparo,"%1d%1d",i1,j1);
13411: if(mle==1)
13412: printf("%1d%1d",i,jj);
13413: fprintf(ficlog,"%1d%1d",i,jj);
13414: for(k=1; k<=ncovmodel;k++){
13415: fscanf(ficpar," %lf",¶m[i][j][k]);
13416: if(mle==1){
13417: printf(" %lf",param[i][j][k]);
13418: fprintf(ficlog," %lf",param[i][j][k]);
13419: }
13420: else
13421: fprintf(ficlog," %lf",param[i][j][k]);
13422: fprintf(ficparo," %lf",param[i][j][k]);
13423: }
13424: fscanf(ficpar,"\n");
13425: numlinepar++;
13426: if(mle==1)
13427: printf("\n");
13428: fprintf(ficlog,"\n");
13429: fprintf(ficparo,"\n");
1.126 brouard 13430: }
13431: }
13432: fflush(ficlog);
1.234 brouard 13433:
1.251 brouard 13434: /* Reads parameters values */
1.126 brouard 13435: p=param[1][1];
1.251 brouard 13436: pstart=paramstart[1][1];
1.126 brouard 13437:
13438: /* Reads comments: lines beginning with '#' */
13439: while((c=getc(ficpar))=='#' && c!= EOF){
13440: ungetc(c,ficpar);
13441: fgets(line, MAXLINE, ficpar);
13442: numlinepar++;
1.141 brouard 13443: fputs(line,stdout);
1.126 brouard 13444: fputs(line,ficparo);
13445: fputs(line,ficlog);
13446: }
13447: ungetc(c,ficpar);
13448:
13449: for(i=1; i <=nlstate; i++){
13450: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 13451: fscanf(ficpar,"%1d%1d",&i1,&j1);
13452: if ( (i1-i) * (j1-j) != 0){
13453: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
13454: exit(1);
13455: }
13456: printf("%1d%1d",i,j);
13457: fprintf(ficparo,"%1d%1d",i1,j1);
13458: fprintf(ficlog,"%1d%1d",i1,j1);
13459: for(k=1; k<=ncovmodel;k++){
13460: fscanf(ficpar,"%le",&delti3[i][j][k]);
13461: printf(" %le",delti3[i][j][k]);
13462: fprintf(ficparo," %le",delti3[i][j][k]);
13463: fprintf(ficlog," %le",delti3[i][j][k]);
13464: }
13465: fscanf(ficpar,"\n");
13466: numlinepar++;
13467: printf("\n");
13468: fprintf(ficparo,"\n");
13469: fprintf(ficlog,"\n");
1.126 brouard 13470: }
13471: }
13472: fflush(ficlog);
1.234 brouard 13473:
1.145 brouard 13474: /* Reads covariance matrix */
1.126 brouard 13475: delti=delti3[1][1];
1.220 brouard 13476:
13477:
1.126 brouard 13478: /* 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 13479:
1.126 brouard 13480: /* Reads comments: lines beginning with '#' */
13481: while((c=getc(ficpar))=='#' && c!= EOF){
13482: ungetc(c,ficpar);
13483: fgets(line, MAXLINE, ficpar);
13484: numlinepar++;
1.141 brouard 13485: fputs(line,stdout);
1.126 brouard 13486: fputs(line,ficparo);
13487: fputs(line,ficlog);
13488: }
13489: ungetc(c,ficpar);
1.220 brouard 13490:
1.126 brouard 13491: matcov=matrix(1,npar,1,npar);
1.203 brouard 13492: hess=matrix(1,npar,1,npar);
1.131 brouard 13493: for(i=1; i <=npar; i++)
13494: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 13495:
1.194 brouard 13496: /* Scans npar lines */
1.126 brouard 13497: for(i=1; i <=npar; i++){
1.226 brouard 13498: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 13499: if(count != 3){
1.226 brouard 13500: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 13501: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
13502: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 13503: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 13504: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
13505: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 13506: exit(1);
1.220 brouard 13507: }else{
1.226 brouard 13508: if(mle==1)
13509: printf("%1d%1d%d",i1,j1,jk);
13510: }
13511: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
13512: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 13513: for(j=1; j <=i; j++){
1.226 brouard 13514: fscanf(ficpar," %le",&matcov[i][j]);
13515: if(mle==1){
13516: printf(" %.5le",matcov[i][j]);
13517: }
13518: fprintf(ficlog," %.5le",matcov[i][j]);
13519: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 13520: }
13521: fscanf(ficpar,"\n");
13522: numlinepar++;
13523: if(mle==1)
1.220 brouard 13524: printf("\n");
1.126 brouard 13525: fprintf(ficlog,"\n");
13526: fprintf(ficparo,"\n");
13527: }
1.194 brouard 13528: /* End of read covariance matrix npar lines */
1.126 brouard 13529: for(i=1; i <=npar; i++)
13530: for(j=i+1;j<=npar;j++)
1.226 brouard 13531: matcov[i][j]=matcov[j][i];
1.126 brouard 13532:
13533: if(mle==1)
13534: printf("\n");
13535: fprintf(ficlog,"\n");
13536:
13537: fflush(ficlog);
13538:
13539: } /* End of mle != -3 */
1.218 brouard 13540:
1.186 brouard 13541: /* Main data
13542: */
1.290 brouard 13543: nobs=lastobs-firstobs+1; /* was = lastobs;*/
13544: /* num=lvector(1,n); */
13545: /* moisnais=vector(1,n); */
13546: /* annais=vector(1,n); */
13547: /* moisdc=vector(1,n); */
13548: /* andc=vector(1,n); */
13549: /* weight=vector(1,n); */
13550: /* agedc=vector(1,n); */
13551: /* cod=ivector(1,n); */
13552: /* for(i=1;i<=n;i++){ */
13553: num=lvector(firstobs,lastobs);
13554: moisnais=vector(firstobs,lastobs);
13555: annais=vector(firstobs,lastobs);
13556: moisdc=vector(firstobs,lastobs);
13557: andc=vector(firstobs,lastobs);
13558: weight=vector(firstobs,lastobs);
13559: agedc=vector(firstobs,lastobs);
13560: cod=ivector(firstobs,lastobs);
13561: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 13562: num[i]=0;
13563: moisnais[i]=0;
13564: annais[i]=0;
13565: moisdc[i]=0;
13566: andc[i]=0;
13567: agedc[i]=0;
13568: cod[i]=0;
13569: weight[i]=1.0; /* Equal weights, 1 by default */
13570: }
1.290 brouard 13571: mint=matrix(1,maxwav,firstobs,lastobs);
13572: anint=matrix(1,maxwav,firstobs,lastobs);
1.325 brouard 13573: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
1.336 brouard 13574: /* printf("BUG ncovmodel=%d NCOVMAX=%d 2**ncovmodel=%f BUG\n",ncovmodel,NCOVMAX,pow(2,ncovmodel)); */
1.126 brouard 13575: tab=ivector(1,NCOVMAX);
1.144 brouard 13576: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 13577: 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 13578:
1.136 brouard 13579: /* Reads data from file datafile */
13580: if (readdata(datafile, firstobs, lastobs, &imx)==1)
13581: goto end;
13582:
13583: /* Calculation of the number of parameters from char model */
1.234 brouard 13584: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 13585: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
13586: k=3 V4 Tvar[k=3]= 4 (from V4)
13587: k=2 V1 Tvar[k=2]= 1 (from V1)
13588: k=1 Tvar[1]=2 (from V2)
1.234 brouard 13589: */
13590:
13591: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
13592: TvarsDind=ivector(1,NCOVMAX); /* */
1.330 brouard 13593: TnsdVar=ivector(1,NCOVMAX); /* */
1.335 brouard 13594: /* for(i=1; i<=NCOVMAX;i++) TnsdVar[i]=3; */
1.234 brouard 13595: TvarsD=ivector(1,NCOVMAX); /* */
13596: TvarsQind=ivector(1,NCOVMAX); /* */
13597: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 13598: TvarF=ivector(1,NCOVMAX); /* */
13599: TvarFind=ivector(1,NCOVMAX); /* */
13600: TvarV=ivector(1,NCOVMAX); /* */
13601: TvarVind=ivector(1,NCOVMAX); /* */
13602: TvarA=ivector(1,NCOVMAX); /* */
13603: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 13604: TvarFD=ivector(1,NCOVMAX); /* */
13605: TvarFDind=ivector(1,NCOVMAX); /* */
13606: TvarFQ=ivector(1,NCOVMAX); /* */
13607: TvarFQind=ivector(1,NCOVMAX); /* */
13608: TvarVD=ivector(1,NCOVMAX); /* */
13609: TvarVDind=ivector(1,NCOVMAX); /* */
13610: TvarVQ=ivector(1,NCOVMAX); /* */
13611: TvarVQind=ivector(1,NCOVMAX); /* */
1.339 brouard 13612: TvarVV=ivector(1,NCOVMAX); /* */
13613: TvarVVind=ivector(1,NCOVMAX); /* */
1.349 brouard 13614: TvarVVA=ivector(1,NCOVMAX); /* */
13615: TvarVVAind=ivector(1,NCOVMAX); /* */
13616: TvarAVVA=ivector(1,NCOVMAX); /* */
13617: TvarAVVAind=ivector(1,NCOVMAX); /* */
1.231 brouard 13618:
1.230 brouard 13619: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 13620: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 13621: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
13622: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
13623: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.349 brouard 13624: DummyV=ivector(-1,NCOVMAX); /* 1 to 3 */
13625: FixedV=ivector(-1,NCOVMAX); /* 1 to 3 */
13626:
1.137 brouard 13627: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
13628: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
13629: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
13630: */
13631: /* For model-covariate k tells which data-covariate to use but
13632: because this model-covariate is a construction we invent a new column
13633: ncovcol + k1
13634: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
13635: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 13636: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
13637: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 13638: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
13639: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 13640: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 13641: */
1.145 brouard 13642: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
13643: 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 13644: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
13645: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.349 brouard 13646: Tvardk=imatrix(-1,NCOVMAX,1,2);
1.145 brouard 13647: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 13648: 4 covariates (3 plus signs)
13649: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
1.328 brouard 13650: */
13651: for(i=1;i<NCOVMAX;i++)
13652: Tage[i]=0;
1.230 brouard 13653: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 13654: * individual dummy, fixed or varying:
13655: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
13656: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 13657: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
13658: * V1 df, V2 qf, V3 & V4 dv, V5 qv
13659: * Tmodelind[1]@9={9,0,3,2,}*/
13660: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
13661: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 13662: * individual quantitative, fixed or varying:
13663: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
13664: * 3, 1, 0, 0, 0, 0, 0, 0},
13665: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.349 brouard 13666:
13667: /* Probably useless zeroes */
13668: for(i=1;i<NCOVMAX;i++){
13669: DummyV[i]=0;
13670: FixedV[i]=0;
13671: }
13672:
13673: for(i=1; i <=ncovcol;i++){
13674: DummyV[i]=0;
13675: FixedV[i]=0;
13676: }
13677: for(i=ncovcol+1; i <=ncovcol+nqv;i++){
13678: DummyV[i]=1;
13679: FixedV[i]=0;
13680: }
13681: for(i=ncovcol+nqv+1; i <=ncovcol+nqv+ntv;i++){
13682: DummyV[i]=0;
13683: FixedV[i]=1;
13684: }
13685: for(i=ncovcol+nqv+ntv+1; i <=ncovcol+nqv+ntv+nqtv;i++){
13686: DummyV[i]=1;
13687: FixedV[i]=1;
13688: }
13689: for(i=1; i <=ncovcol+nqv+ntv+nqtv;i++){
13690: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",i,i,DummyV[i],i,FixedV[i]);
13691: 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]);
13692: }
13693:
13694:
13695:
1.186 brouard 13696: /* Main decodemodel */
13697:
1.187 brouard 13698:
1.223 brouard 13699: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 13700: goto end;
13701:
1.137 brouard 13702: if((double)(lastobs-imx)/(double)imx > 1.10){
13703: nbwarn++;
13704: 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);
13705: 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);
13706: }
1.136 brouard 13707: /* if(mle==1){*/
1.137 brouard 13708: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
13709: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 13710: }
13711:
13712: /*-calculation of age at interview from date of interview and age at death -*/
13713: agev=matrix(1,maxwav,1,imx);
13714:
13715: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
13716: goto end;
13717:
1.126 brouard 13718:
1.136 brouard 13719: agegomp=(int)agemin;
1.290 brouard 13720: free_vector(moisnais,firstobs,lastobs);
13721: free_vector(annais,firstobs,lastobs);
1.126 brouard 13722: /* free_matrix(mint,1,maxwav,1,n);
13723: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 13724: /* free_vector(moisdc,1,n); */
13725: /* free_vector(andc,1,n); */
1.145 brouard 13726: /* */
13727:
1.126 brouard 13728: wav=ivector(1,imx);
1.214 brouard 13729: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
13730: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
13731: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
13732: 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.*/
13733: bh=imatrix(1,lastpass-firstpass+2,1,imx);
13734: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 13735:
13736: /* Concatenates waves */
1.214 brouard 13737: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
13738: Death is a valid wave (if date is known).
13739: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
13740: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
13741: and mw[mi+1][i]. dh depends on stepm.
13742: */
13743:
1.126 brouard 13744: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 13745: /* Concatenates waves */
1.145 brouard 13746:
1.290 brouard 13747: free_vector(moisdc,firstobs,lastobs);
13748: free_vector(andc,firstobs,lastobs);
1.215 brouard 13749:
1.126 brouard 13750: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
13751: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
13752: ncodemax[1]=1;
1.145 brouard 13753: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 13754: cptcoveff=0;
1.220 brouard 13755: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
1.335 brouard 13756: 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 13757: }
13758:
13759: ncovcombmax=pow(2,cptcoveff);
1.338 brouard 13760: invalidvarcomb=ivector(0, ncovcombmax);
13761: for(i=0;i<ncovcombmax;i++)
1.227 brouard 13762: invalidvarcomb[i]=0;
13763:
1.211 brouard 13764: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 13765: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 13766: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 13767:
1.200 brouard 13768: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 13769: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 13770: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 13771: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
13772: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
13773: * (currently 0 or 1) in the data.
13774: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
13775: * corresponding modality (h,j).
13776: */
13777:
1.145 brouard 13778: h=0;
13779: /*if (cptcovn > 0) */
1.126 brouard 13780: m=pow(2,cptcoveff);
13781:
1.144 brouard 13782: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 13783: * For k=4 covariates, h goes from 1 to m=2**k
13784: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
13785: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.329 brouard 13786: * h\k 1 2 3 4 * h-1\k-1 4 3 2 1
13787: *______________________________ *______________________
13788: * 1 i=1 1 i=1 1 i=1 1 i=1 1 * 0 0 0 0 0
13789: * 2 2 1 1 1 * 1 0 0 0 1
13790: * 3 i=2 1 2 1 1 * 2 0 0 1 0
13791: * 4 2 2 1 1 * 3 0 0 1 1
13792: * 5 i=3 1 i=2 1 2 1 * 4 0 1 0 0
13793: * 6 2 1 2 1 * 5 0 1 0 1
13794: * 7 i=4 1 2 2 1 * 6 0 1 1 0
13795: * 8 2 2 2 1 * 7 0 1 1 1
13796: * 9 i=5 1 i=3 1 i=2 1 2 * 8 1 0 0 0
13797: * 10 2 1 1 2 * 9 1 0 0 1
13798: * 11 i=6 1 2 1 2 * 10 1 0 1 0
13799: * 12 2 2 1 2 * 11 1 0 1 1
13800: * 13 i=7 1 i=4 1 2 2 * 12 1 1 0 0
13801: * 14 2 1 2 2 * 13 1 1 0 1
13802: * 15 i=8 1 2 2 2 * 14 1 1 1 0
13803: * 16 2 2 2 2 * 15 1 1 1 1
13804: */
1.212 brouard 13805: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 13806: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
13807: * and the value of each covariate?
13808: * V1=1, V2=1, V3=2, V4=1 ?
13809: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
13810: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
13811: * In order to get the real value in the data, we use nbcode
13812: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
13813: * We are keeping this crazy system in order to be able (in the future?)
13814: * to have more than 2 values (0 or 1) for a covariate.
13815: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
13816: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
13817: * bbbbbbbb
13818: * 76543210
13819: * h-1 00000101 (6-1=5)
1.219 brouard 13820: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 13821: * &
13822: * 1 00000001 (1)
1.219 brouard 13823: * 00000000 = 1 & ((h-1) >> (k-1))
13824: * +1= 00000001 =1
1.211 brouard 13825: *
13826: * h=14, k=3 => h'=h-1=13, k'=k-1=2
13827: * h' 1101 =2^3+2^2+0x2^1+2^0
13828: * >>k' 11
13829: * & 00000001
13830: * = 00000001
13831: * +1 = 00000010=2 = codtabm(14,3)
13832: * Reverse h=6 and m=16?
13833: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
13834: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
13835: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
13836: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
13837: * V3=decodtabm(14,3,2**4)=2
13838: * h'=13 1101 =2^3+2^2+0x2^1+2^0
13839: *(h-1) >> (j-1) 0011 =13 >> 2
13840: * &1 000000001
13841: * = 000000001
13842: * +1= 000000010 =2
13843: * 2211
13844: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
13845: * V3=2
1.220 brouard 13846: * codtabm and decodtabm are identical
1.211 brouard 13847: */
13848:
1.145 brouard 13849:
13850: free_ivector(Ndum,-1,NCOVMAX);
13851:
13852:
1.126 brouard 13853:
1.186 brouard 13854: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 13855: strcpy(optionfilegnuplot,optionfilefiname);
13856: if(mle==-3)
1.201 brouard 13857: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 13858: strcat(optionfilegnuplot,".gp");
13859:
13860: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
13861: printf("Problem with file %s",optionfilegnuplot);
13862: }
13863: else{
1.204 brouard 13864: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 13865: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 13866: //fprintf(ficgp,"set missing 'NaNq'\n");
13867: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 13868: }
13869: /* fclose(ficgp);*/
1.186 brouard 13870:
13871:
13872: /* Initialisation of --------- index.htm --------*/
1.126 brouard 13873:
13874: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
13875: if(mle==-3)
1.201 brouard 13876: strcat(optionfilehtm,"-MORT_");
1.126 brouard 13877: strcat(optionfilehtm,".htm");
13878: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 13879: printf("Problem with %s \n",optionfilehtm);
13880: exit(0);
1.126 brouard 13881: }
13882:
13883: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
13884: strcat(optionfilehtmcov,"-cov.htm");
13885: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
13886: printf("Problem with %s \n",optionfilehtmcov), exit(0);
13887: }
13888: else{
13889: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
13890: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 13891: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 13892: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
13893: }
13894:
1.335 brouard 13895: fprintf(fichtm,"<html><head>\n<meta charset=\"utf-8\"/><meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n\
13896: <title>IMaCh %s</title></head>\n\
13897: <body><font size=\"7\"><a href=http:/euroreves.ined.fr/imach>IMaCh for Interpolated Markov Chain</a> </font><br>\n\
13898: <font size=\"3\">Sponsored by Copyright (C) 2002-2015 <a href=http://www.ined.fr>INED</a>\
13899: -EUROREVES-Institut de longévité-2013-2022-Japan Society for the Promotion of Sciences 日本学術振興会 \
13900: (<a href=https://www.jsps.go.jp/english/e-grants/>Grant-in-Aid for Scientific Research 25293121</a>) - \
13901: <a href=https://software.intel.com/en-us>Intel Software 2015-2018</a></font><br> \n", optionfilehtm);
13902:
13903: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 13904: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 13905: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.337 brouard 13906: 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 13907: \n\
13908: <hr size=\"2\" color=\"#EC5E5E\">\
13909: <ul><li><h4>Parameter files</h4>\n\
13910: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
13911: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
13912: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
13913: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
13914: - Date and time at start: %s</ul>\n",\
1.335 brouard 13915: version,fullversion,optionfilehtm,optionfilehtm,title,datafile,datafile,firstpass,lastpass,stepm, weightopt, model, \
1.126 brouard 13916: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
13917: fileres,fileres,\
13918: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
13919: fflush(fichtm);
13920:
13921: strcpy(pathr,path);
13922: strcat(pathr,optionfilefiname);
1.184 brouard 13923: #ifdef WIN32
13924: _chdir(optionfilefiname); /* Move to directory named optionfile */
13925: #else
1.126 brouard 13926: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 13927: #endif
13928:
1.126 brouard 13929:
1.220 brouard 13930: /* Calculates basic frequencies. Computes observed prevalence at single age
13931: and for any valid combination of covariates
1.126 brouard 13932: and prints on file fileres'p'. */
1.251 brouard 13933: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 13934: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 13935:
13936: fprintf(fichtm,"\n");
1.286 brouard 13937: 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 13938: ftol, stepm);
13939: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
13940: ncurrv=1;
13941: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
13942: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
13943: ncurrv=i;
13944: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 13945: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 13946: ncurrv=i;
13947: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 13948: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 13949: ncurrv=i;
13950: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
13951: 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", \
13952: nlstate, ndeath, maxwav, mle, weightopt);
13953:
13954: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
13955: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
13956:
13957:
1.317 brouard 13958: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Number of (used) observations=%d <br>\n\
1.126 brouard 13959: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
13960: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 13961: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 13962: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 13963: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
13964: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
13965: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
13966: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 13967:
1.126 brouard 13968: /* For Powell, parameters are in a vector p[] starting at p[1]
13969: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
13970: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
13971:
13972: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 13973: /* For mortality only */
1.126 brouard 13974: if (mle==-3){
1.136 brouard 13975: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 13976: for(i=1;i<=NDIM;i++)
13977: for(j=1;j<=NDIM;j++)
13978: ximort[i][j]=0.;
1.186 brouard 13979: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 13980: cens=ivector(firstobs,lastobs);
13981: ageexmed=vector(firstobs,lastobs);
13982: agecens=vector(firstobs,lastobs);
13983: dcwave=ivector(firstobs,lastobs);
1.223 brouard 13984:
1.126 brouard 13985: for (i=1; i<=imx; i++){
13986: dcwave[i]=-1;
13987: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 13988: if (s[m][i]>nlstate) {
13989: dcwave[i]=m;
13990: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
13991: break;
13992: }
1.126 brouard 13993: }
1.226 brouard 13994:
1.126 brouard 13995: for (i=1; i<=imx; i++) {
13996: if (wav[i]>0){
1.226 brouard 13997: ageexmed[i]=agev[mw[1][i]][i];
13998: j=wav[i];
13999: agecens[i]=1.;
14000:
14001: if (ageexmed[i]> 1 && wav[i] > 0){
14002: agecens[i]=agev[mw[j][i]][i];
14003: cens[i]= 1;
14004: }else if (ageexmed[i]< 1)
14005: cens[i]= -1;
14006: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
14007: cens[i]=0 ;
1.126 brouard 14008: }
14009: else cens[i]=-1;
14010: }
14011:
14012: for (i=1;i<=NDIM;i++) {
14013: for (j=1;j<=NDIM;j++)
1.226 brouard 14014: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 14015: }
14016:
1.302 brouard 14017: p[1]=0.0268; p[NDIM]=0.083;
14018: /* printf("%lf %lf", p[1], p[2]); */
1.126 brouard 14019:
14020:
1.136 brouard 14021: #ifdef GSL
14022: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 14023: #else
1.126 brouard 14024: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 14025: #endif
1.201 brouard 14026: strcpy(filerespow,"POW-MORT_");
14027: strcat(filerespow,fileresu);
1.126 brouard 14028: if((ficrespow=fopen(filerespow,"w"))==NULL) {
14029: printf("Problem with resultfile: %s\n", filerespow);
14030: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
14031: }
1.136 brouard 14032: #ifdef GSL
14033: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 14034: #else
1.126 brouard 14035: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 14036: #endif
1.126 brouard 14037: /* for (i=1;i<=nlstate;i++)
14038: for(j=1;j<=nlstate+ndeath;j++)
14039: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
14040: */
14041: fprintf(ficrespow,"\n");
1.136 brouard 14042: #ifdef GSL
14043: /* gsl starts here */
14044: T = gsl_multimin_fminimizer_nmsimplex;
14045: gsl_multimin_fminimizer *sfm = NULL;
14046: gsl_vector *ss, *x;
14047: gsl_multimin_function minex_func;
14048:
14049: /* Initial vertex size vector */
14050: ss = gsl_vector_alloc (NDIM);
14051:
14052: if (ss == NULL){
14053: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
14054: }
14055: /* Set all step sizes to 1 */
14056: gsl_vector_set_all (ss, 0.001);
14057:
14058: /* Starting point */
1.126 brouard 14059:
1.136 brouard 14060: x = gsl_vector_alloc (NDIM);
14061:
14062: if (x == NULL){
14063: gsl_vector_free(ss);
14064: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
14065: }
14066:
14067: /* Initialize method and iterate */
14068: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 14069: /* gsl_vector_set(x, 0, 0.0268); */
14070: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 14071: gsl_vector_set(x, 0, p[1]);
14072: gsl_vector_set(x, 1, p[2]);
14073:
14074: minex_func.f = &gompertz_f;
14075: minex_func.n = NDIM;
14076: minex_func.params = (void *)&p; /* ??? */
14077:
14078: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
14079: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
14080:
14081: printf("Iterations beginning .....\n\n");
14082: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
14083:
14084: iteri=0;
14085: while (rval == GSL_CONTINUE){
14086: iteri++;
14087: status = gsl_multimin_fminimizer_iterate(sfm);
14088:
14089: if (status) printf("error: %s\n", gsl_strerror (status));
14090: fflush(0);
14091:
14092: if (status)
14093: break;
14094:
14095: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
14096: ssval = gsl_multimin_fminimizer_size (sfm);
14097:
14098: if (rval == GSL_SUCCESS)
14099: printf ("converged to a local maximum at\n");
14100:
14101: printf("%5d ", iteri);
14102: for (it = 0; it < NDIM; it++){
14103: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
14104: }
14105: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
14106: }
14107:
14108: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
14109:
14110: gsl_vector_free(x); /* initial values */
14111: gsl_vector_free(ss); /* inital step size */
14112: for (it=0; it<NDIM; it++){
14113: p[it+1]=gsl_vector_get(sfm->x,it);
14114: fprintf(ficrespow," %.12lf", p[it]);
14115: }
14116: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
14117: #endif
14118: #ifdef POWELL
14119: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
14120: #endif
1.126 brouard 14121: fclose(ficrespow);
14122:
1.203 brouard 14123: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 14124:
14125: for(i=1; i <=NDIM; i++)
14126: for(j=i+1;j<=NDIM;j++)
1.220 brouard 14127: matcov[i][j]=matcov[j][i];
1.126 brouard 14128:
14129: printf("\nCovariance matrix\n ");
1.203 brouard 14130: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 14131: for(i=1; i <=NDIM; i++) {
14132: for(j=1;j<=NDIM;j++){
1.220 brouard 14133: printf("%f ",matcov[i][j]);
14134: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 14135: }
1.203 brouard 14136: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 14137: }
14138:
14139: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 14140: for (i=1;i<=NDIM;i++) {
1.126 brouard 14141: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 14142: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
14143: }
1.302 brouard 14144: lsurv=vector(agegomp,AGESUP);
14145: lpop=vector(agegomp,AGESUP);
14146: tpop=vector(agegomp,AGESUP);
1.126 brouard 14147: lsurv[agegomp]=100000;
14148:
14149: for (k=agegomp;k<=AGESUP;k++) {
14150: agemortsup=k;
14151: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
14152: }
14153:
14154: for (k=agegomp;k<agemortsup;k++)
14155: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
14156:
14157: for (k=agegomp;k<agemortsup;k++){
14158: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
14159: sumlpop=sumlpop+lpop[k];
14160: }
14161:
14162: tpop[agegomp]=sumlpop;
14163: for (k=agegomp;k<(agemortsup-3);k++){
14164: /* tpop[k+1]=2;*/
14165: tpop[k+1]=tpop[k]-lpop[k];
14166: }
14167:
14168:
14169: printf("\nAge lx qx dx Lx Tx e(x)\n");
14170: for (k=agegomp;k<(agemortsup-2);k++)
14171: 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]);
14172:
14173:
14174: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 14175: ageminpar=50;
14176: agemaxpar=100;
1.194 brouard 14177: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
14178: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
14179: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14180: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
14181: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
14182: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14183: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 14184: }else{
14185: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
14186: 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 14187: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 14188: }
1.201 brouard 14189: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 14190: stepm, weightopt,\
14191: model,imx,p,matcov,agemortsup);
14192:
1.302 brouard 14193: free_vector(lsurv,agegomp,AGESUP);
14194: free_vector(lpop,agegomp,AGESUP);
14195: free_vector(tpop,agegomp,AGESUP);
1.220 brouard 14196: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 14197: free_ivector(dcwave,firstobs,lastobs);
14198: free_vector(agecens,firstobs,lastobs);
14199: free_vector(ageexmed,firstobs,lastobs);
14200: free_ivector(cens,firstobs,lastobs);
1.220 brouard 14201: #ifdef GSL
1.136 brouard 14202: #endif
1.186 brouard 14203: } /* Endof if mle==-3 mortality only */
1.205 brouard 14204: /* Standard */
14205: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
14206: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
14207: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 14208: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 14209: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
14210: for (k=1; k<=npar;k++)
14211: printf(" %d %8.5f",k,p[k]);
14212: printf("\n");
1.205 brouard 14213: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
14214: /* mlikeli uses func not funcone */
1.247 brouard 14215: /* for(i=1;i<nlstate;i++){ */
14216: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
14217: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
14218: /* } */
1.205 brouard 14219: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
14220: }
14221: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
14222: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
14223: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
14224: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
14225: }
14226: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 14227: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
14228: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
1.335 brouard 14229: /* exit(0); */
1.126 brouard 14230: for (k=1; k<=npar;k++)
14231: printf(" %d %8.5f",k,p[k]);
14232: printf("\n");
14233:
14234: /*--------- results files --------------*/
1.283 brouard 14235: /* 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 14236:
14237:
14238: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 14239: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); /* Printing model equation */
1.126 brouard 14240: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 14241:
14242: printf("#model= 1 + age ");
14243: fprintf(ficres,"#model= 1 + age ");
14244: fprintf(ficlog,"#model= 1 + age ");
14245: fprintf(fichtm,"\n<ul><li> model=1+age+%s\n \
14246: </ul>", model);
14247:
14248: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">\n");
14249: fprintf(fichtm, "<tr><th>Model=</th><th>1</th><th>+ age</th>");
14250: if(nagesqr==1){
14251: printf(" + age*age ");
14252: fprintf(ficres," + age*age ");
14253: fprintf(ficlog," + age*age ");
14254: fprintf(fichtm, "<th>+ age*age</th>");
14255: }
14256: for(j=1;j <=ncovmodel-2;j++){
14257: if(Typevar[j]==0) {
14258: printf(" + V%d ",Tvar[j]);
14259: fprintf(ficres," + V%d ",Tvar[j]);
14260: fprintf(ficlog," + V%d ",Tvar[j]);
14261: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
14262: }else if(Typevar[j]==1) {
14263: printf(" + V%d*age ",Tvar[j]);
14264: fprintf(ficres," + V%d*age ",Tvar[j]);
14265: fprintf(ficlog," + V%d*age ",Tvar[j]);
14266: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
14267: }else if(Typevar[j]==2) {
14268: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14269: fprintf(ficres," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14270: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14271: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 14272: }else if(Typevar[j]==3) { /* TO VERIFY */
14273: printf(" + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14274: fprintf(ficres," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14275: fprintf(ficlog," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14276: fprintf(fichtm, "<th>+ V%d*V%d*age</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.319 brouard 14277: }
14278: }
14279: printf("\n");
14280: fprintf(ficres,"\n");
14281: fprintf(ficlog,"\n");
14282: fprintf(fichtm, "</tr>");
14283: fprintf(fichtm, "\n");
14284:
14285:
1.126 brouard 14286: for(i=1,jk=1; i <=nlstate; i++){
14287: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 14288: if (k != i) {
1.319 brouard 14289: fprintf(fichtm, "<tr>");
1.225 brouard 14290: printf("%d%d ",i,k);
14291: fprintf(ficlog,"%d%d ",i,k);
14292: fprintf(ficres,"%1d%1d ",i,k);
1.319 brouard 14293: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 14294: for(j=1; j <=ncovmodel; j++){
14295: printf("%12.7f ",p[jk]);
14296: fprintf(ficlog,"%12.7f ",p[jk]);
14297: fprintf(ficres,"%12.7f ",p[jk]);
1.319 brouard 14298: fprintf(fichtm, "<td>%12.7f</td>",p[jk]);
1.225 brouard 14299: jk++;
14300: }
14301: printf("\n");
14302: fprintf(ficlog,"\n");
14303: fprintf(ficres,"\n");
1.319 brouard 14304: fprintf(fichtm, "</tr>\n");
1.225 brouard 14305: }
1.126 brouard 14306: }
14307: }
1.319 brouard 14308: /* fprintf(fichtm,"</tr>\n"); */
14309: fprintf(fichtm,"</table>\n");
14310: fprintf(fichtm, "\n");
14311:
1.203 brouard 14312: if(mle != 0){
14313: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 14314: ftolhess=ftol; /* Usually correct */
1.203 brouard 14315: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
14316: 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");
14317: 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 14318: 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 14319: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">");
14320: fprintf(fichtm, "\n<tr><th>Model=</th><th>1</th><th>+ age</th>");
14321: if(nagesqr==1){
14322: printf(" + age*age ");
14323: fprintf(ficres," + age*age ");
14324: fprintf(ficlog," + age*age ");
14325: fprintf(fichtm, "<th>+ age*age</th>");
14326: }
14327: for(j=1;j <=ncovmodel-2;j++){
14328: if(Typevar[j]==0) {
14329: printf(" + V%d ",Tvar[j]);
14330: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
14331: }else if(Typevar[j]==1) {
14332: printf(" + V%d*age ",Tvar[j]);
14333: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
14334: }else if(Typevar[j]==2) {
14335: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 14336: }else if(Typevar[j]==3) { /* TO VERIFY */
14337: fprintf(fichtm, "<th>+ V%d*V%d*age</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.319 brouard 14338: }
14339: }
14340: fprintf(fichtm, "</tr>\n");
14341:
1.203 brouard 14342: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 14343: for(k=1; k <=(nlstate+ndeath); k++){
14344: if (k != i) {
1.319 brouard 14345: fprintf(fichtm, "<tr valign=top>");
1.225 brouard 14346: printf("%d%d ",i,k);
14347: fprintf(ficlog,"%d%d ",i,k);
1.319 brouard 14348: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 14349: for(j=1; j <=ncovmodel; j++){
1.319 brouard 14350: wald=p[jk]/sqrt(matcov[jk][jk]);
1.324 brouard 14351: 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]));
14352: 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 14353: if(fabs(wald) > 1.96){
1.321 brouard 14354: fprintf(fichtm, "<td><b>%12.7f</b></br> (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
1.319 brouard 14355: }else{
14356: fprintf(fichtm, "<td>%12.7f (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
14357: }
1.324 brouard 14358: fprintf(fichtm,"W=%8.3f</br>",wald);
1.319 brouard 14359: 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 14360: jk++;
14361: }
14362: printf("\n");
14363: fprintf(ficlog,"\n");
1.319 brouard 14364: fprintf(fichtm, "</tr>\n");
1.225 brouard 14365: }
14366: }
1.193 brouard 14367: }
1.203 brouard 14368: } /* end of hesscov and Wald tests */
1.319 brouard 14369: fprintf(fichtm,"</table>\n");
1.225 brouard 14370:
1.203 brouard 14371: /* */
1.126 brouard 14372: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
14373: printf("# Scales (for hessian or gradient estimation)\n");
14374: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
14375: for(i=1,jk=1; i <=nlstate; i++){
14376: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 14377: if (j!=i) {
14378: fprintf(ficres,"%1d%1d",i,j);
14379: printf("%1d%1d",i,j);
14380: fprintf(ficlog,"%1d%1d",i,j);
14381: for(k=1; k<=ncovmodel;k++){
14382: printf(" %.5e",delti[jk]);
14383: fprintf(ficlog," %.5e",delti[jk]);
14384: fprintf(ficres," %.5e",delti[jk]);
14385: jk++;
14386: }
14387: printf("\n");
14388: fprintf(ficlog,"\n");
14389: fprintf(ficres,"\n");
14390: }
1.126 brouard 14391: }
14392: }
14393:
14394: 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 14395: if(mle >= 1) /* Too big for the screen */
1.126 brouard 14396: 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");
14397: 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");
14398: /* # 121 Var(a12)\n\ */
14399: /* # 122 Cov(b12,a12) Var(b12)\n\ */
14400: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
14401: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
14402: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
14403: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
14404: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
14405: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
14406:
14407:
14408: /* Just to have a covariance matrix which will be more understandable
14409: even is we still don't want to manage dictionary of variables
14410: */
14411: for(itimes=1;itimes<=2;itimes++){
14412: jj=0;
14413: for(i=1; i <=nlstate; i++){
1.225 brouard 14414: for(j=1; j <=nlstate+ndeath; j++){
14415: if(j==i) continue;
14416: for(k=1; k<=ncovmodel;k++){
14417: jj++;
14418: ca[0]= k+'a'-1;ca[1]='\0';
14419: if(itimes==1){
14420: if(mle>=1)
14421: printf("#%1d%1d%d",i,j,k);
14422: fprintf(ficlog,"#%1d%1d%d",i,j,k);
14423: fprintf(ficres,"#%1d%1d%d",i,j,k);
14424: }else{
14425: if(mle>=1)
14426: printf("%1d%1d%d",i,j,k);
14427: fprintf(ficlog,"%1d%1d%d",i,j,k);
14428: fprintf(ficres,"%1d%1d%d",i,j,k);
14429: }
14430: ll=0;
14431: for(li=1;li <=nlstate; li++){
14432: for(lj=1;lj <=nlstate+ndeath; lj++){
14433: if(lj==li) continue;
14434: for(lk=1;lk<=ncovmodel;lk++){
14435: ll++;
14436: if(ll<=jj){
14437: cb[0]= lk +'a'-1;cb[1]='\0';
14438: if(ll<jj){
14439: if(itimes==1){
14440: if(mle>=1)
14441: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
14442: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
14443: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
14444: }else{
14445: if(mle>=1)
14446: printf(" %.5e",matcov[jj][ll]);
14447: fprintf(ficlog," %.5e",matcov[jj][ll]);
14448: fprintf(ficres," %.5e",matcov[jj][ll]);
14449: }
14450: }else{
14451: if(itimes==1){
14452: if(mle>=1)
14453: printf(" Var(%s%1d%1d)",ca,i,j);
14454: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
14455: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
14456: }else{
14457: if(mle>=1)
14458: printf(" %.7e",matcov[jj][ll]);
14459: fprintf(ficlog," %.7e",matcov[jj][ll]);
14460: fprintf(ficres," %.7e",matcov[jj][ll]);
14461: }
14462: }
14463: }
14464: } /* end lk */
14465: } /* end lj */
14466: } /* end li */
14467: if(mle>=1)
14468: printf("\n");
14469: fprintf(ficlog,"\n");
14470: fprintf(ficres,"\n");
14471: numlinepar++;
14472: } /* end k*/
14473: } /*end j */
1.126 brouard 14474: } /* end i */
14475: } /* end itimes */
14476:
14477: fflush(ficlog);
14478: fflush(ficres);
1.225 brouard 14479: while(fgets(line, MAXLINE, ficpar)) {
14480: /* If line starts with a # it is a comment */
14481: if (line[0] == '#') {
14482: numlinepar++;
14483: fputs(line,stdout);
14484: fputs(line,ficparo);
14485: fputs(line,ficlog);
1.299 brouard 14486: fputs(line,ficres);
1.225 brouard 14487: continue;
14488: }else
14489: break;
14490: }
14491:
1.209 brouard 14492: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
14493: /* ungetc(c,ficpar); */
14494: /* fgets(line, MAXLINE, ficpar); */
14495: /* fputs(line,stdout); */
14496: /* fputs(line,ficparo); */
14497: /* } */
14498: /* ungetc(c,ficpar); */
1.126 brouard 14499:
14500: estepm=0;
1.209 brouard 14501: 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 14502:
14503: if (num_filled != 6) {
14504: 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);
14505: 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);
14506: goto end;
14507: }
14508: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
14509: }
14510: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
14511: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
14512:
1.209 brouard 14513: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 14514: if (estepm==0 || estepm < stepm) estepm=stepm;
14515: if (fage <= 2) {
14516: bage = ageminpar;
14517: fage = agemaxpar;
14518: }
14519:
14520: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 14521: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
14522: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 14523:
1.186 brouard 14524: /* Other stuffs, more or less useful */
1.254 brouard 14525: while(fgets(line, MAXLINE, ficpar)) {
14526: /* If line starts with a # it is a comment */
14527: if (line[0] == '#') {
14528: numlinepar++;
14529: fputs(line,stdout);
14530: fputs(line,ficparo);
14531: fputs(line,ficlog);
1.299 brouard 14532: fputs(line,ficres);
1.254 brouard 14533: continue;
14534: }else
14535: break;
14536: }
14537:
14538: 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){
14539:
14540: if (num_filled != 7) {
14541: 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);
14542: 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);
14543: goto end;
14544: }
14545: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
14546: 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);
14547: 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);
14548: 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 14549: }
1.254 brouard 14550:
14551: while(fgets(line, MAXLINE, ficpar)) {
14552: /* If line starts with a # it is a comment */
14553: if (line[0] == '#') {
14554: numlinepar++;
14555: fputs(line,stdout);
14556: fputs(line,ficparo);
14557: fputs(line,ficlog);
1.299 brouard 14558: fputs(line,ficres);
1.254 brouard 14559: continue;
14560: }else
14561: break;
1.126 brouard 14562: }
14563:
14564:
14565: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
14566: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
14567:
1.254 brouard 14568: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
14569: if (num_filled != 1) {
14570: 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);
14571: 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);
14572: goto end;
14573: }
14574: printf("pop_based=%d\n",popbased);
14575: fprintf(ficlog,"pop_based=%d\n",popbased);
14576: fprintf(ficparo,"pop_based=%d\n",popbased);
14577: fprintf(ficres,"pop_based=%d\n",popbased);
14578: }
14579:
1.258 brouard 14580: /* Results */
1.332 brouard 14581: /* Value of covariate in each resultine will be compututed (if product) and sorted according to model rank */
14582: /* It is precov[] because we need the varying age in order to compute the real cov[] of the model equation */
14583: precov=matrix(1,MAXRESULTLINESPONE,1,NCOVMAX+1);
1.307 brouard 14584: endishere=0;
1.258 brouard 14585: nresult=0;
1.308 brouard 14586: parameterline=0;
1.258 brouard 14587: do{
14588: if(!fgets(line, MAXLINE, ficpar)){
14589: endishere=1;
1.308 brouard 14590: parameterline=15;
1.258 brouard 14591: }else if (line[0] == '#') {
14592: /* If line starts with a # it is a comment */
1.254 brouard 14593: numlinepar++;
14594: fputs(line,stdout);
14595: fputs(line,ficparo);
14596: fputs(line,ficlog);
1.299 brouard 14597: fputs(line,ficres);
1.254 brouard 14598: continue;
1.258 brouard 14599: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
14600: parameterline=11;
1.296 brouard 14601: else if(sscanf(line,"prevbackcast=%[^\n]\n",modeltemp))
1.258 brouard 14602: parameterline=12;
1.307 brouard 14603: else if(sscanf(line,"result:%[^\n]\n",modeltemp)){
1.258 brouard 14604: parameterline=13;
1.307 brouard 14605: }
1.258 brouard 14606: else{
14607: parameterline=14;
1.254 brouard 14608: }
1.308 brouard 14609: switch (parameterline){ /* =0 only if only comments */
1.258 brouard 14610: case 11:
1.296 brouard 14611: 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)){
14612: 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 14613: 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);
14614: 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);
14615: 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);
14616: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 14617: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
14618: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
1.296 brouard 14619: prvforecast = 1;
14620: }
14621: else if((num_filled=sscanf(line,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",&prevfcast,&yrfproj,&mobilavproj)) !=EOF){/* && (num_filled == 3))*/
1.313 brouard 14622: printf("prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
14623: fprintf(ficlog,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
14624: fprintf(ficres,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
1.296 brouard 14625: prvforecast = 2;
14626: }
14627: else {
14628: 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);
14629: 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);
14630: goto end;
1.258 brouard 14631: }
1.254 brouard 14632: break;
1.258 brouard 14633: case 12:
1.296 brouard 14634: 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)){
14635: 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);
14636: 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);
14637: 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);
14638: 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);
14639: /* day and month of back2 are not used but only year anback2.*/
1.273 brouard 14640: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
14641: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.296 brouard 14642: prvbackcast = 1;
14643: }
14644: else if((num_filled=sscanf(line,"prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",&prevbcast,&yrbproj,&mobilavproj)) ==3){/* && (num_filled == 3))*/
1.313 brouard 14645: printf("prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
14646: fprintf(ficlog,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
14647: fprintf(ficres,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
1.296 brouard 14648: prvbackcast = 2;
14649: }
14650: else {
14651: 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);
14652: 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);
14653: goto end;
1.258 brouard 14654: }
1.230 brouard 14655: break;
1.258 brouard 14656: case 13:
1.332 brouard 14657: num_filled=sscanf(line,"result:%[^\n]\n",resultlineori);
1.307 brouard 14658: nresult++; /* Sum of resultlines */
1.342 brouard 14659: /* printf("Result %d: result:%s\n",nresult, resultlineori); */
1.332 brouard 14660: /* removefirstspace(&resultlineori); */
14661:
14662: if(strstr(resultlineori,"v") !=0){
14663: printf("Error. 'v' must be in upper case 'V' result: %s ",resultlineori);
14664: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultlineori);fflush(ficlog);
14665: return 1;
14666: }
14667: trimbb(resultline, resultlineori); /* Suppressing double blank in the resultline */
1.342 brouard 14668: /* printf("Decoderesult resultline=\"%s\" resultlineori=\"%s\"\n", resultline, resultlineori); */
1.318 brouard 14669: if(nresult > MAXRESULTLINESPONE-1){
14670: 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);
14671: 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 14672: goto end;
14673: }
1.332 brouard 14674:
1.310 brouard 14675: if(!decoderesult(resultline, nresult)){ /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
1.314 brouard 14676: fprintf(ficparo,"result: %s\n",resultline);
14677: fprintf(ficres,"result: %s\n",resultline);
14678: fprintf(ficlog,"result: %s\n",resultline);
1.310 brouard 14679: } else
14680: goto end;
1.307 brouard 14681: break;
14682: case 14:
14683: printf("Error: Unknown command '%s'\n",line);
14684: fprintf(ficlog,"Error: Unknown command '%s'\n",line);
1.314 brouard 14685: if(line[0] == ' ' || line[0] == '\n'){
14686: printf("It should not be an empty line '%s'\n",line);
14687: fprintf(ficlog,"It should not be an empty line '%s'\n",line);
14688: }
1.307 brouard 14689: if(ncovmodel >=2 && nresult==0 ){
14690: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
14691: fprintf(ficlog,"ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 14692: }
1.307 brouard 14693: /* goto end; */
14694: break;
1.308 brouard 14695: case 15:
14696: printf("End of resultlines.\n");
14697: fprintf(ficlog,"End of resultlines.\n");
14698: break;
14699: default: /* parameterline =0 */
1.307 brouard 14700: nresult=1;
14701: decoderesult(".",nresult ); /* No covariate */
1.258 brouard 14702: } /* End switch parameterline */
14703: }while(endishere==0); /* End do */
1.126 brouard 14704:
1.230 brouard 14705: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 14706: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 14707:
14708: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 14709: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 14710: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 14711: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14712: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 14713: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 14714: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14715: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 14716: }else{
1.270 brouard 14717: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
1.296 brouard 14718: /* It seems that anprojd which is computed from the mean year at interview which is known yet because of freqsummary */
14719: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */ /* Done in freqsummary */
14720: if(prvforecast==1){
14721: dateprojd=(jproj1+12*mproj1+365*anproj1)/365;
14722: jprojd=jproj1;
14723: mprojd=mproj1;
14724: anprojd=anproj1;
14725: dateprojf=(jproj2+12*mproj2+365*anproj2)/365;
14726: jprojf=jproj2;
14727: mprojf=mproj2;
14728: anprojf=anproj2;
14729: } else if(prvforecast == 2){
14730: dateprojd=dateintmean;
14731: date2dmy(dateprojd,&jprojd, &mprojd, &anprojd);
14732: dateprojf=dateintmean+yrfproj;
14733: date2dmy(dateprojf,&jprojf, &mprojf, &anprojf);
14734: }
14735: if(prvbackcast==1){
14736: datebackd=(jback1+12*mback1+365*anback1)/365;
14737: jbackd=jback1;
14738: mbackd=mback1;
14739: anbackd=anback1;
14740: datebackf=(jback2+12*mback2+365*anback2)/365;
14741: jbackf=jback2;
14742: mbackf=mback2;
14743: anbackf=anback2;
14744: } else if(prvbackcast == 2){
14745: datebackd=dateintmean;
14746: date2dmy(datebackd,&jbackd, &mbackd, &anbackd);
14747: datebackf=dateintmean-yrbproj;
14748: date2dmy(datebackf,&jbackf, &mbackf, &anbackf);
14749: }
14750:
1.350 ! brouard 14751: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage);/* HERE valgrind Tvard*/
1.220 brouard 14752: }
14753: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.296 brouard 14754: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,prevbcast, estepm, \
14755: jprev1,mprev1,anprev1,dateprev1, dateprojd, datebackd,jprev2,mprev2,anprev2,dateprev2,dateprojf, datebackf);
1.220 brouard 14756:
1.225 brouard 14757: /*------------ free_vector -------------*/
14758: /* chdir(path); */
1.220 brouard 14759:
1.215 brouard 14760: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
14761: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
14762: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
14763: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 14764: free_lvector(num,firstobs,lastobs);
14765: free_vector(agedc,firstobs,lastobs);
1.126 brouard 14766: /*free_matrix(covar,0,NCOVMAX,1,n);*/
14767: /*free_matrix(covar,1,NCOVMAX,1,n);*/
14768: fclose(ficparo);
14769: fclose(ficres);
1.220 brouard 14770:
14771:
1.186 brouard 14772: /* Other results (useful)*/
1.220 brouard 14773:
14774:
1.126 brouard 14775: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 14776: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
14777: prlim=matrix(1,nlstate,1,nlstate);
1.332 brouard 14778: /* Computes the prevalence limit for each combination k of the dummy covariates by calling prevalim(k) */
1.209 brouard 14779: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 14780: fclose(ficrespl);
14781:
14782: /*------------- h Pij x at various ages ------------*/
1.180 brouard 14783: /*#include "hpijx.h"*/
1.332 brouard 14784: /** 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?*/
14785: /* calls hpxij with combination k */
1.180 brouard 14786: hPijx(p, bage, fage);
1.145 brouard 14787: fclose(ficrespij);
1.227 brouard 14788:
1.220 brouard 14789: /* ncovcombmax= pow(2,cptcoveff); */
1.332 brouard 14790: /*-------------- Variance of one-step probabilities for a combination ij or for nres ?---*/
1.145 brouard 14791: k=1;
1.126 brouard 14792: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 14793:
1.269 brouard 14794: /* Prevalence for each covariate combination in probs[age][status][cov] */
14795: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
14796: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 14797: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 14798: for(k=1;k<=ncovcombmax;k++)
14799: probs[i][j][k]=0.;
1.269 brouard 14800: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
14801: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 14802: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 14803: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
14804: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 14805: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 14806: for(k=1;k<=ncovcombmax;k++)
14807: mobaverages[i][j][k]=0.;
1.219 brouard 14808: mobaverage=mobaverages;
14809: if (mobilav!=0) {
1.235 brouard 14810: printf("Movingaveraging observed prevalence\n");
1.258 brouard 14811: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 14812: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
14813: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
14814: printf(" Error in movingaverage mobilav=%d\n",mobilav);
14815: }
1.269 brouard 14816: } else if (mobilavproj !=0) {
1.235 brouard 14817: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 14818: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 14819: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
14820: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
14821: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
14822: }
1.269 brouard 14823: }else{
14824: printf("Internal error moving average\n");
14825: fflush(stdout);
14826: exit(1);
1.219 brouard 14827: }
14828: }/* end if moving average */
1.227 brouard 14829:
1.126 brouard 14830: /*---------- Forecasting ------------------*/
1.296 brouard 14831: if(prevfcast==1){
14832: /* /\* if(stepm ==1){*\/ */
14833: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
14834: /*This done previously after freqsummary.*/
14835: /* dateprojd=(jproj1+12*mproj1+365*anproj1)/365; */
14836: /* dateprojf=(jproj2+12*mproj2+365*anproj2)/365; */
14837:
14838: /* } else if (prvforecast==2){ */
14839: /* /\* if(stepm ==1){*\/ */
14840: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
14841: /* } */
14842: /*prevforecast(fileresu, dateintmean, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);*/
14843: prevforecast(fileresu,dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, p, cptcoveff);
1.126 brouard 14844: }
1.269 brouard 14845:
1.296 brouard 14846: /* Prevbcasting */
14847: if(prevbcast==1){
1.219 brouard 14848: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14849: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14850: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14851:
14852: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
14853:
14854: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 14855:
1.219 brouard 14856: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
14857: fclose(ficresplb);
14858:
1.222 brouard 14859: hBijx(p, bage, fage, mobaverage);
14860: fclose(ficrespijb);
1.219 brouard 14861:
1.296 brouard 14862: /* /\* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, *\/ */
14863: /* /\* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); *\/ */
14864: /* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, */
14865: /* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
14866: prevbackforecast(fileresu, mobaverage, dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2,
14867: mobilavproj, bage, fage, firstpass, lastpass, p, cptcoveff);
14868:
14869:
1.269 brouard 14870: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 14871:
14872:
1.269 brouard 14873: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 14874: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
14875: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
14876: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.296 brouard 14877: } /* end Prevbcasting */
1.268 brouard 14878:
1.186 brouard 14879:
14880: /* ------ Other prevalence ratios------------ */
1.126 brouard 14881:
1.215 brouard 14882: free_ivector(wav,1,imx);
14883: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
14884: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
14885: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 14886:
14887:
1.127 brouard 14888: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 14889:
1.201 brouard 14890: strcpy(filerese,"E_");
14891: strcat(filerese,fileresu);
1.126 brouard 14892: if((ficreseij=fopen(filerese,"w"))==NULL) {
14893: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
14894: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
14895: }
1.208 brouard 14896: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
14897: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 14898:
14899: pstamp(ficreseij);
1.219 brouard 14900:
1.235 brouard 14901: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
14902: if (cptcovn < 1){i1=1;}
14903:
14904: for(nres=1; nres <= nresult; nres++) /* For each resultline */
14905: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 14906: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 14907: continue;
1.219 brouard 14908: fprintf(ficreseij,"\n#****** ");
1.235 brouard 14909: printf("\n#****** ");
1.225 brouard 14910: for(j=1;j<=cptcoveff;j++) {
1.332 brouard 14911: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
14912: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.235 brouard 14913: }
14914: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.337 brouard 14915: printf(" V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]); /* TvarsQ[j] gives the name of the jth quantitative (fixed or time v) */
14916: fprintf(ficreseij,"V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]);
1.219 brouard 14917: }
14918: fprintf(ficreseij,"******\n");
1.235 brouard 14919: printf("******\n");
1.219 brouard 14920:
14921: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
14922: oldm=oldms;savm=savms;
1.330 brouard 14923: /* 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 14924: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 14925:
1.219 brouard 14926: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 14927: }
14928: fclose(ficreseij);
1.208 brouard 14929: printf("done evsij\n");fflush(stdout);
14930: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 14931:
1.218 brouard 14932:
1.227 brouard 14933: /*---------- State-specific expectancies and variances ------------*/
1.336 brouard 14934: /* Should be moved in a function */
1.201 brouard 14935: strcpy(filerest,"T_");
14936: strcat(filerest,fileresu);
1.127 brouard 14937: if((ficrest=fopen(filerest,"w"))==NULL) {
14938: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
14939: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
14940: }
1.208 brouard 14941: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
14942: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 14943: strcpy(fileresstde,"STDE_");
14944: strcat(fileresstde,fileresu);
1.126 brouard 14945: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 14946: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
14947: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 14948: }
1.227 brouard 14949: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
14950: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 14951:
1.201 brouard 14952: strcpy(filerescve,"CVE_");
14953: strcat(filerescve,fileresu);
1.126 brouard 14954: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 14955: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
14956: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 14957: }
1.227 brouard 14958: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
14959: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 14960:
1.201 brouard 14961: strcpy(fileresv,"V_");
14962: strcat(fileresv,fileresu);
1.126 brouard 14963: if((ficresvij=fopen(fileresv,"w"))==NULL) {
14964: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
14965: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
14966: }
1.227 brouard 14967: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
14968: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 14969:
1.235 brouard 14970: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
14971: if (cptcovn < 1){i1=1;}
14972:
1.334 brouard 14973: for(nres=1; nres <= nresult; nres++) /* For each resultline, find the combination and output results according to the values of dummies and then quanti. */
14974: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying. For each nres and each value at position k
14975: * we know Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline
14976: * Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline
14977: * and Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
14978: /* */
14979: 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 14980: continue;
1.350 ! brouard 14981: printf("\n# model %s \n#****** Result for:", model); /* HERE model is empty */
1.321 brouard 14982: fprintf(ficrest,"\n# model %s \n#****** Result for:", model);
14983: fprintf(ficlog,"\n# model %s \n#****** Result for:", model);
1.334 brouard 14984: /* It might not be a good idea to mix dummies and quantitative */
14985: /* 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 *\/ */
14986: 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 */
14987: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /\* Output by variables in the resultline *\/ */
14988: /* Tvaraff[j] is the name of the dummy variable in position j in the equation model:
14989: * Tvaraff[1]@9={4, 3, 0, 0, 0, 0, 0, 0, 0}, in model=V5+V4+V3+V4*V3+V5*age
14990: * (V5 is quanti) V4 and V3 are dummies
14991: * TnsdVar[4] is the position 1 and TnsdVar[3]=2 in codtabm(k,l)(V4 V3)=V4 V3
14992: * l=1 l=2
14993: * k=1 1 1 0 0
14994: * k=2 2 1 1 0
14995: * k=3 [1] [2] 0 1
14996: * k=4 2 2 1 1
14997: * If nres=1 result: V3=1 V4=0 then k=3 and outputs
14998: * If nres=2 result: V4=1 V3=0 then k=2 and outputs
14999: * nres=1 =>k=3 j=1 V4= nbcode[4][codtabm(3,1)=1)=0; j=2 V3= nbcode[3][codtabm(3,2)=2]=1
15000: * nres=2 =>k=2 j=1 V4= nbcode[4][codtabm(2,1)=2)=1; j=2 V3= nbcode[3][codtabm(2,2)=1]=0
15001: */
15002: /* Tvresult[nres][j] Name of the variable at position j in this resultline */
15003: /* Tresult[nres][j] Value of this variable at position j could be a float if quantitative */
15004: /* We give up with the combinations!! */
1.342 brouard 15005: /* if(debugILK) */
15006: /* 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 15007:
15008: 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 15009: /* 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] */
15010: 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 */
15011: 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 */
15012: 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 15013: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
15014: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
15015: }else{
15016: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
15017: }
15018: /* fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15019: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15020: }else if(Dummy[modelresult[nres][j]]==1){ /* Quanti variable */
15021: /* For each selected (single) quantitative value */
1.337 brouard 15022: printf(" V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
15023: fprintf(ficlog," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
15024: fprintf(ficrest," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
1.334 brouard 15025: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
15026: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
15027: }else{
15028: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
15029: }
15030: }else{
15031: 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 */
15032: 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 */
15033: exit(1);
15034: }
1.335 brouard 15035: } /* End loop for each variable in the resultline */
1.334 brouard 15036: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
15037: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /\* Wrong j is not in the equation model *\/ */
15038: /* fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
15039: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
15040: /* } */
1.208 brouard 15041: fprintf(ficrest,"******\n");
1.227 brouard 15042: fprintf(ficlog,"******\n");
15043: printf("******\n");
1.208 brouard 15044:
15045: fprintf(ficresstdeij,"\n#****** ");
15046: fprintf(ficrescveij,"\n#****** ");
1.337 brouard 15047: /* It could have been: for(j=1;j<=cptcoveff;j++) {printf("V=%d=%lg",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);} */
15048: /* But it won't be sorted and depends on how the resultline is ordered */
1.225 brouard 15049: for(j=1;j<=cptcoveff;j++) {
1.334 brouard 15050: fprintf(ficresstdeij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
15051: /* fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15052: /* fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15053: }
15054: 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 15055: fprintf(ficresstdeij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
15056: fprintf(ficrescveij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
1.235 brouard 15057: }
1.208 brouard 15058: fprintf(ficresstdeij,"******\n");
15059: fprintf(ficrescveij,"******\n");
15060:
15061: fprintf(ficresvij,"\n#****** ");
1.238 brouard 15062: /* pstamp(ficresvij); */
1.225 brouard 15063: for(j=1;j<=cptcoveff;j++)
1.335 brouard 15064: fprintf(ficresvij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
15065: /* fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[TnsdVar[Tvaraff[j]]])]); */
1.235 brouard 15066: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.332 brouard 15067: /* fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); /\* To solve *\/ */
1.337 brouard 15068: fprintf(ficresvij," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /* Solved */
1.235 brouard 15069: }
1.208 brouard 15070: fprintf(ficresvij,"******\n");
15071:
15072: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
15073: oldm=oldms;savm=savms;
1.235 brouard 15074: printf(" cvevsij ");
15075: fprintf(ficlog, " cvevsij ");
15076: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 15077: printf(" end cvevsij \n ");
15078: fprintf(ficlog, " end cvevsij \n ");
15079:
15080: /*
15081: */
15082: /* goto endfree; */
15083:
15084: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
15085: pstamp(ficrest);
15086:
1.269 brouard 15087: epj=vector(1,nlstate+1);
1.208 brouard 15088: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 15089: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
15090: cptcod= 0; /* To be deleted */
15091: printf("varevsij vpopbased=%d \n",vpopbased);
15092: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 15093: 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 15094: 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 ");
15095: if(vpopbased==1)
15096: 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);
15097: else
1.288 brouard 15098: fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n");
1.335 brouard 15099: fprintf(ficrest,"# Age popbased mobilav e.. (std) "); /* Adding covariate values? */
1.227 brouard 15100: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
15101: fprintf(ficrest,"\n");
15102: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 15103: printf("Computing age specific forward period (stable) prevalences in each health state \n");
15104: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 15105: for(age=bage; age <=fage ;age++){
1.235 brouard 15106: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 15107: if (vpopbased==1) {
15108: if(mobilav ==0){
15109: for(i=1; i<=nlstate;i++)
15110: prlim[i][i]=probs[(int)age][i][k];
15111: }else{ /* mobilav */
15112: for(i=1; i<=nlstate;i++)
15113: prlim[i][i]=mobaverage[(int)age][i][k];
15114: }
15115: }
1.219 brouard 15116:
1.227 brouard 15117: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
15118: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
15119: /* printf(" age %4.0f ",age); */
15120: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
15121: for(i=1, epj[j]=0.;i <=nlstate;i++) {
15122: epj[j] += prlim[i][i]*eij[i][j][(int)age];
15123: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
15124: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
15125: }
15126: epj[nlstate+1] +=epj[j];
15127: }
15128: /* printf(" age %4.0f \n",age); */
1.219 brouard 15129:
1.227 brouard 15130: for(i=1, vepp=0.;i <=nlstate;i++)
15131: for(j=1;j <=nlstate;j++)
15132: vepp += vareij[i][j][(int)age];
15133: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
15134: for(j=1;j <=nlstate;j++){
15135: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
15136: }
15137: fprintf(ficrest,"\n");
15138: }
1.208 brouard 15139: } /* End vpopbased */
1.269 brouard 15140: free_vector(epj,1,nlstate+1);
1.208 brouard 15141: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
15142: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 15143: printf("done selection\n");fflush(stdout);
15144: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 15145:
1.335 brouard 15146: } /* End k selection or end covariate selection for nres */
1.227 brouard 15147:
15148: printf("done State-specific expectancies\n");fflush(stdout);
15149: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
15150:
1.335 brouard 15151: /* variance-covariance of forward period prevalence */
1.269 brouard 15152: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 15153:
1.227 brouard 15154:
1.290 brouard 15155: free_vector(weight,firstobs,lastobs);
1.349 brouard 15156: free_imatrix(Tvardk,-1,NCOVMAX,1,2);
1.227 brouard 15157: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 15158: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
15159: free_matrix(anint,1,maxwav,firstobs,lastobs);
15160: free_matrix(mint,1,maxwav,firstobs,lastobs);
15161: free_ivector(cod,firstobs,lastobs);
1.227 brouard 15162: free_ivector(tab,1,NCOVMAX);
15163: fclose(ficresstdeij);
15164: fclose(ficrescveij);
15165: fclose(ficresvij);
15166: fclose(ficrest);
15167: fclose(ficpar);
15168:
15169:
1.126 brouard 15170: /*---------- End : free ----------------*/
1.219 brouard 15171: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 15172: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
15173: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 15174: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
15175: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 15176: } /* mle==-3 arrives here for freeing */
1.227 brouard 15177: /* endfree:*/
15178: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
15179: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
15180: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.341 brouard 15181: /* if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs); */
15182: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs);
1.290 brouard 15183: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
15184: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
15185: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 15186: free_matrix(matcov,1,npar,1,npar);
15187: free_matrix(hess,1,npar,1,npar);
15188: /*free_vector(delti,1,npar);*/
15189: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
15190: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 15191: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 15192: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
15193:
15194: free_ivector(ncodemax,1,NCOVMAX);
15195: free_ivector(ncodemaxwundef,1,NCOVMAX);
15196: free_ivector(Dummy,-1,NCOVMAX);
15197: free_ivector(Fixed,-1,NCOVMAX);
1.349 brouard 15198: free_ivector(DummyV,-1,NCOVMAX);
15199: free_ivector(FixedV,-1,NCOVMAX);
1.227 brouard 15200: free_ivector(Typevar,-1,NCOVMAX);
15201: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 15202: free_ivector(TvarsQ,1,NCOVMAX);
15203: free_ivector(TvarsQind,1,NCOVMAX);
15204: free_ivector(TvarsD,1,NCOVMAX);
1.330 brouard 15205: free_ivector(TnsdVar,1,NCOVMAX);
1.234 brouard 15206: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 15207: free_ivector(TvarFD,1,NCOVMAX);
15208: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 15209: free_ivector(TvarF,1,NCOVMAX);
15210: free_ivector(TvarFind,1,NCOVMAX);
15211: free_ivector(TvarV,1,NCOVMAX);
15212: free_ivector(TvarVind,1,NCOVMAX);
15213: free_ivector(TvarA,1,NCOVMAX);
15214: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 15215: free_ivector(TvarFQ,1,NCOVMAX);
15216: free_ivector(TvarFQind,1,NCOVMAX);
15217: free_ivector(TvarVD,1,NCOVMAX);
15218: free_ivector(TvarVDind,1,NCOVMAX);
15219: free_ivector(TvarVQ,1,NCOVMAX);
15220: free_ivector(TvarVQind,1,NCOVMAX);
1.349 brouard 15221: free_ivector(TvarAVVA,1,NCOVMAX);
15222: free_ivector(TvarAVVAind,1,NCOVMAX);
15223: free_ivector(TvarVVA,1,NCOVMAX);
15224: free_ivector(TvarVVAind,1,NCOVMAX);
1.339 brouard 15225: free_ivector(TvarVV,1,NCOVMAX);
15226: free_ivector(TvarVVind,1,NCOVMAX);
15227:
1.230 brouard 15228: free_ivector(Tvarsel,1,NCOVMAX);
15229: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 15230: free_ivector(Tposprod,1,NCOVMAX);
15231: free_ivector(Tprod,1,NCOVMAX);
15232: free_ivector(Tvaraff,1,NCOVMAX);
1.338 brouard 15233: free_ivector(invalidvarcomb,0,ncovcombmax);
1.227 brouard 15234: free_ivector(Tage,1,NCOVMAX);
15235: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 15236: free_ivector(TmodelInvind,1,NCOVMAX);
15237: free_ivector(TmodelInvQind,1,NCOVMAX);
1.332 brouard 15238:
15239: free_matrix(precov, 1,MAXRESULTLINESPONE,1,NCOVMAX+1); /* Could be elsewhere ?*/
15240:
1.227 brouard 15241: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
15242: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 15243: fflush(fichtm);
15244: fflush(ficgp);
15245:
1.227 brouard 15246:
1.126 brouard 15247: if((nberr >0) || (nbwarn>0)){
1.216 brouard 15248: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
15249: 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 15250: }else{
15251: printf("End of Imach\n");
15252: fprintf(ficlog,"End of Imach\n");
15253: }
15254: printf("See log file on %s\n",filelog);
15255: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 15256: /*(void) gettimeofday(&end_time,&tzp);*/
15257: rend_time = time(NULL);
15258: end_time = *localtime(&rend_time);
15259: /* tml = *localtime(&end_time.tm_sec); */
15260: strcpy(strtend,asctime(&end_time));
1.126 brouard 15261: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
15262: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 15263: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 15264:
1.157 brouard 15265: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
15266: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
15267: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 15268: /* printf("Total time was %d uSec.\n", total_usecs);*/
15269: /* if(fileappend(fichtm,optionfilehtm)){ */
15270: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
15271: fclose(fichtm);
15272: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
15273: fclose(fichtmcov);
15274: fclose(ficgp);
15275: fclose(ficlog);
15276: /*------ End -----------*/
1.227 brouard 15277:
1.281 brouard 15278:
15279: /* Executes gnuplot */
1.227 brouard 15280:
15281: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 15282: #ifdef WIN32
1.227 brouard 15283: if (_chdir(pathcd) != 0)
15284: printf("Can't move to directory %s!\n",path);
15285: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 15286: #else
1.227 brouard 15287: if(chdir(pathcd) != 0)
15288: printf("Can't move to directory %s!\n", path);
15289: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 15290: #endif
1.126 brouard 15291: printf("Current directory %s!\n",pathcd);
15292: /*strcat(plotcmd,CHARSEPARATOR);*/
15293: sprintf(plotcmd,"gnuplot");
1.157 brouard 15294: #ifdef _WIN32
1.126 brouard 15295: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
15296: #endif
15297: if(!stat(plotcmd,&info)){
1.158 brouard 15298: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 15299: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 15300: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 15301: }else
15302: strcpy(pplotcmd,plotcmd);
1.157 brouard 15303: #ifdef __unix
1.126 brouard 15304: strcpy(plotcmd,GNUPLOTPROGRAM);
15305: if(!stat(plotcmd,&info)){
1.158 brouard 15306: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 15307: }else
15308: strcpy(pplotcmd,plotcmd);
15309: #endif
15310: }else
15311: strcpy(pplotcmd,plotcmd);
15312:
15313: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 15314: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 brouard 15315: strcpy(pplotcmd,plotcmd);
1.227 brouard 15316:
1.126 brouard 15317: if((outcmd=system(plotcmd)) != 0){
1.292 brouard 15318: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 15319: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 15320: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 brouard 15321: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 15322: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 brouard 15323: strcpy(plotcmd,pplotcmd);
15324: }
1.126 brouard 15325: }
1.158 brouard 15326: printf(" Successful, please wait...");
1.126 brouard 15327: while (z[0] != 'q') {
15328: /* chdir(path); */
1.154 brouard 15329: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 15330: scanf("%s",z);
15331: /* if (z[0] == 'c') system("./imach"); */
15332: if (z[0] == 'e') {
1.158 brouard 15333: #ifdef __APPLE__
1.152 brouard 15334: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 15335: #elif __linux
15336: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 15337: #else
1.152 brouard 15338: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 15339: #endif
15340: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
15341: system(pplotcmd);
1.126 brouard 15342: }
15343: else if (z[0] == 'g') system(plotcmd);
15344: else if (z[0] == 'q') exit(0);
15345: }
1.227 brouard 15346: end:
1.126 brouard 15347: while (z[0] != 'q') {
1.195 brouard 15348: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 15349: scanf("%s",z);
15350: }
1.283 brouard 15351: printf("End\n");
1.282 brouard 15352: exit(0);
1.126 brouard 15353: }
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